Mapping the Daily Progression of Large Wildland Fires Using MODIS Active Fire Data

NASA Technical Reports Server (NTRS)

Veraverbeke, Sander; Sedano, Fernando; Hook, Simon J.; Randerson, James T.; Jin, Yufang; Rogers, Brendan

2013-01-01

High temporal resolution information on burned area is a prerequisite for incorporating bottom-up estimates of wildland fire emissions in regional air transport models and for improving models of fire behavior. We used the Moderate Resolution Imaging Spectroradiometer (MODIS) active fire product (MO(Y)D14) as input to a kriging interpolation to derive continuous maps of the evolution of nine large wildland fires. For each fire, local input parameters for the kriging model were defined using variogram analysis. The accuracy of the kriging model was assessed using high resolution daily fire perimeter data available from the U.S. Forest Service. We also assessed the temporal reporting accuracy of the MODIS burned area products (MCD45A1 and MCD64A1). Averaged over the nine fires, the kriging method correctly mapped 73% of the pixels within the accuracy of a single day, compared to 33% for MCD45A1 and 53% for MCD64A1.

Functional brain microstate predicts the outcome in a visuospatial working memory task.

PubMed

Muthukrishnan, Suriya-Prakash; Ahuja, Navdeep; Mehta, Nalin; Sharma, Ratna

2016-11-01

Humans have limited capacity of processing just up to 4 integrated items of information in the working memory. Thus, it is inevitable to commit more errors when challenged with high memory loads. However, the neural mechanisms that determine the accuracy of response at high memory loads still remain unclear. High temporal resolution of Electroencephalography (EEG) technique makes it the best tool to resolve the temporal dynamics of brain networks. EEG-defined microstate is the quasi-stable scalp electrical potential topography that represents the momentary functional state of brain. Thus, it has been possible to assess the information processing currently performed by the brain using EEG microstate analysis. We hypothesize that the EEG microstate preceding the trial could determine its outcome in a visuospatial working memory (VSWM) task. Twenty-four healthy participants performed a high memory load VSWM task, while their brain activity was recorded using EEG. Four microstate maps were found to represent the functional brain state prior to the trials in the VSWM task. One pre-trial microstate map was found to determine the accuracy of subsequent behavioural response. The intracranial generators of the pre-trial microstate map that determined the response accuracy were localized to the visuospatial processing areas at bilateral occipital, right temporal and limbic cortices. Our results imply that the behavioural outcome in a VSWM task could be determined by the intensity of activation of memory representations in the visuospatial processing brain regions prior to the trial. Copyright © 2016 Elsevier B.V. All rights reserved.

The Eyes Know Time: A Novel Paradigm to Reveal the Development of Temporal Memory

ERIC Educational Resources Information Center

Pathman, Thanujeni; Ghetti, Simona

2014-01-01

Temporal memory in 7-year-olds, 10-year-olds, and young adults (N = 78) was examined introducing a novel eye-movement paradigm. Participants learned object sequences and were tested under three conditions: temporal order, temporal context, and recognition. Age-related improvements in accuracy were found across conditions; accuracy in the temporal…

Mesial Temporal Sclerosis: Accuracy of NeuroQuant versus Neuroradiologist.

PubMed

Azab, M; Carone, M; Ying, S H; Yousem, D M

2015-08-01

We sought to compare the accuracy of a volumetric fully automated computer assessment of hippocampal volume asymmetry versus neuroradiologists' interpretations of the temporal lobes for mesial temporal sclerosis. Detecting mesial temporal sclerosis (MTS) is important for the evaluation of patients with temporal lobe epilepsy as it often guides surgical intervention. One feature of MTS is hippocampal volume loss. Electronic medical record and researcher reports of scans of patients with proved mesial temporal sclerosis were compared with volumetric assessment with an FDA-approved software package, NeuroQuant, for detection of mesial temporal sclerosis in 63 patients. The degree of volumetric asymmetry was analyzed to determine the neuroradiologists' threshold for detecting right-left asymmetry in temporal lobe volumes. Thirty-six patients had left-lateralized MTS, 25 had right-lateralized MTS, and 2 had bilateral MTS. The estimated accuracy of the neuroradiologist was 72.6% with a κ statistic of 0.512 (95% CI, 0.315-0.710) [moderate agreement, P < 3 × 10(-6)]), whereas the estimated accuracy of NeuroQuant was 79.4% with a κ statistic of 0.588 (95% CI, 0.388-0.787) [moderate agreement, P < 2 × 10(-6)]). This discrepancy in accuracy was not statistically significant. When at least a 5%-10% volume discrepancy between temporal lobes was present, the neuroradiologists detected it 75%-80% of the time. As a stand-alone fully automated software program that can process temporal lobe volume in 5-10 minutes, NeuroQuant compares favorably with trained neuroradiologists in predicting the side of mesial temporal sclerosis. Neuroradiologists can often detect even small temporal lobe volumetric changes visually. © 2015 by American Journal of Neuroradiology.

Time-Accurate Local Time Stepping and High-Order Time CESE Methods for Multi-Dimensional Flows Using Unstructured Meshes

NASA Technical Reports Server (NTRS)

Chang, Chau-Lyan; Venkatachari, Balaji Shankar; Cheng, Gary

2013-01-01

With the wide availability of affordable multiple-core parallel supercomputers, next generation numerical simulations of flow physics are being focused on unsteady computations for problems involving multiple time scales and multiple physics. These simulations require higher solution accuracy than most algorithms and computational fluid dynamics codes currently available. This paper focuses on the developmental effort for high-fidelity multi-dimensional, unstructured-mesh flow solvers using the space-time conservation element, solution element (CESE) framework. Two approaches have been investigated in this research in order to provide high-accuracy, cross-cutting numerical simulations for a variety of flow regimes: 1) time-accurate local time stepping and 2) highorder CESE method. The first approach utilizes consistent numerical formulations in the space-time flux integration to preserve temporal conservation across the cells with different marching time steps. Such approach relieves the stringent time step constraint associated with the smallest time step in the computational domain while preserving temporal accuracy for all the cells. For flows involving multiple scales, both numerical accuracy and efficiency can be significantly enhanced. The second approach extends the current CESE solver to higher-order accuracy. Unlike other existing explicit high-order methods for unstructured meshes, the CESE framework maintains a CFL condition of one for arbitrarily high-order formulations while retaining the same compact stencil as its second-order counterpart. For large-scale unsteady computations, this feature substantially enhances numerical efficiency. Numerical formulations and validations using benchmark problems are discussed in this paper along with realistic examples.

The effect of stimulus intensity on response time and accuracy in dynamic, temporally constrained environments.

PubMed

Causer, J; McRobert, A P; Williams, A M

2013-10-01

The ability to make accurate judgments and execute effective skilled movements under severe temporal constraints are fundamental to elite performance in a number of domains including sport, military combat, law enforcement, and medicine. In two experiments, we examine the effect of stimulus strength on response time and accuracy in a temporally constrained, real-world, decision-making task. Specifically, we examine the effect of low stimulus intensity (black) and high stimulus intensity (sequin) uniform designs, worn by teammates, to determine the effect of stimulus strength on the ability of soccer players to make rapid and accurate responses. In both field- and laboratory-based scenarios, professional soccer players viewed developing patterns of play and were required to make a penetrative pass to an attacking player. Significant differences in response accuracy between uniform designs were reported in laboratory- and field-based experiments. Response accuracy was significantly higher in the sequin compared with the black uniform condition. Response times only differed between uniform designs in the laboratory-based experiment. These findings extend the literature into a real-world environment and have significant implications for the design of clothing wear in a number of domains. © 2012 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Mapping of land cover in northern California with simulated hyperspectral satellite imagery

NASA Astrophysics Data System (ADS)

Clark, Matthew L.; Kilham, Nina E.

2016-09-01

Land-cover maps are important science products needed for natural resource and ecosystem service management, biodiversity conservation planning, and assessing human-induced and natural drivers of land change. Analysis of hyperspectral, or imaging spectrometer, imagery has shown an impressive capacity to map a wide range of natural and anthropogenic land cover. Applications have been mostly with single-date imagery from relatively small spatial extents. Future hyperspectral satellites will provide imagery at greater spatial and temporal scales, and there is a need to assess techniques for mapping land cover with these data. Here we used simulated multi-temporal HyspIRI satellite imagery over a 30,000 km2 area in the San Francisco Bay Area, California to assess its capabilities for mapping classes defined by the international Land Cover Classification System (LCCS). We employed a mapping methodology and analysis framework that is applicable to regional and global scales. We used the Random Forests classifier with three sets of predictor variables (reflectance, MNF, hyperspectral metrics), two temporal resolutions (summer, spring-summer-fall), two sample scales (pixel, polygon) and two levels of classification complexity (12, 20 classes). Hyperspectral metrics provided a 16.4-21.8% and 3.1-6.7% increase in overall accuracy relative to MNF and reflectance bands, respectively, depending on pixel or polygon scales of analysis. Multi-temporal metrics improved overall accuracy by 0.9-3.1% over summer metrics, yet increases were only significant at the pixel scale of analysis. Overall accuracy at pixel scales was 72.2% (Kappa 0.70) with three seasons of metrics. Anthropogenic and homogenous natural vegetation classes had relatively high confidence and producer and user accuracies were over 70%; in comparison, woodland and forest classes had considerable confusion. We next focused on plant functional types with relatively pure spectra by removing open-canopy shrublands, woodlands and mixed forests from the classification. This 12-class map had significantly improved accuracy of 85.1% (Kappa 0.83) and most classes had over 70% producer and user accuracies. Finally, we summarized important metrics from the multi-temporal Random Forests to infer the underlying chemical and structural properties that best discriminated our land-cover classes across seasons.

Achieving behavioral control with millisecond resolution in a high-level programming environment.

PubMed

Asaad, Wael F; Eskandar, Emad N

2008-08-30

The creation of psychophysical tasks for the behavioral neurosciences has generally relied upon low-level software running on a limited range of hardware. Despite the availability of software that allows the coding of behavioral tasks in high-level programming environments, many researchers are still reluctant to trust the temporal accuracy and resolution of programs running in such environments, especially when they run atop non-real-time operating systems. Thus, the creation of behavioral paradigms has been slowed by the intricacy of the coding required and their dissemination across labs has been hampered by the various types of hardware needed. However, we demonstrate here that, when proper measures are taken to handle the various sources of temporal error, accuracy can be achieved at the 1 ms time-scale that is relevant for the alignment of behavioral and neural events.

Fuzzy Temporal Logic Based Railway Passenger Flow Forecast Model

PubMed Central

Dou, Fei; Jia, Limin; Wang, Li; Xu, Jie; Huang, Yakun

2014-01-01

Passenger flow forecast is of essential importance to the organization of railway transportation and is one of the most important basics for the decision-making on transportation pattern and train operation planning. Passenger flow of high-speed railway features the quasi-periodic variations in a short time and complex nonlinear fluctuation because of existence of many influencing factors. In this study, a fuzzy temporal logic based passenger flow forecast model (FTLPFFM) is presented based on fuzzy logic relationship recognition techniques that predicts the short-term passenger flow for high-speed railway, and the forecast accuracy is also significantly improved. An applied case that uses the real-world data illustrates the precision and accuracy of FTLPFFM. For this applied case, the proposed model performs better than the k-nearest neighbor (KNN) and autoregressive integrated moving average (ARIMA) models. PMID:25431586

Movement amplitude and tempo change in piano performance

NASA Astrophysics Data System (ADS)

Palmer, Caroline

2004-05-01

Music performance places stringent temporal and cognitive demands on individuals that should yield large speed/accuracy tradeoffs. Skilled piano performance, however, shows consistently high accuracy across a wide variety of rates. Movement amplitude may affect the speed/accuracy tradeoff, so that high accuracy can be obtained even at very fast tempi. The contribution of movement amplitude changes in rate (tempo) is investigated with motion capture. Cameras recorded pianists with passive markers on hands and fingers, who performed on an electronic (MIDI) keyboard. Pianists performed short melodies at faster and faster tempi until they made errors (altering the speed/accuracy function). Variability of finger movements in the three motion planes indicated most change in the plane perpendicular to the keyboard across tempi. Surprisingly, peak amplitudes of motion before striking the keys increased as tempo increased. Increased movement amplitudes at faster rates may reduce or compensate for speed/accuracy tradeoffs. [Work supported by Canada Research Chairs program, HIMH R01 45764.

Accuracy assessment of NLCD 2006 land cover and impervious surface

USGS Publications Warehouse

Wickham, James D.; Stehman, Stephen V.; Gass, Leila; Dewitz, Jon; Fry, Joyce A.; Wade, Timothy G.

2013-01-01

Release of NLCD 2006 provides the first wall-to-wall land-cover change database for the conterminous United States from Landsat Thematic Mapper (TM) data. Accuracy assessment of NLCD 2006 focused on four primary products: 2001 land cover, 2006 land cover, land-cover change between 2001 and 2006, and impervious surface change between 2001 and 2006. The accuracy assessment was conducted by selecting a stratified random sample of pixels with the reference classification interpreted from multi-temporal high resolution digital imagery. The NLCD Level II (16 classes) overall accuracies for the 2001 and 2006 land cover were 79% and 78%, respectively, with Level II user's accuracies exceeding 80% for water, high density urban, all upland forest classes, shrubland, and cropland for both dates. Level I (8 classes) accuracies were 85% for NLCD 2001 and 84% for NLCD 2006. The high overall and user's accuracies for the individual dates translated into high user's accuracies for the 2001–2006 change reporting themes water gain and loss, forest loss, urban gain, and the no-change reporting themes for water, urban, forest, and agriculture. The main factor limiting higher accuracies for the change reporting themes appeared to be difficulty in distinguishing the context of grass. We discuss the need for more research on land-cover change accuracy assessment.

Enhanced Deforestation Mapping in North Korea using Spatial-temporal Image Fusion Method and Phenology-based Index

NASA Astrophysics Data System (ADS)

Jin, Y.; Lee, D.

2017-12-01

North Korea (the Democratic People's Republic of Korea, DPRK) is known to have some of the most degraded forest in the world. The characteristics of forest landscape in North Korea is complex and heterogeneous, the major vegetation cover types in the forest are hillside farm, unstocked forest, natural forest, and plateau vegetation. Better classification of types in high spatial resolution of deforested areas could provide essential information for decisions about forest management priorities and restoration of deforested areas. For mapping heterogeneous vegetation covers, the phenology-based indices are helpful to overcome the reflectance value confusion that occurs when using one season images. Coarse spatial resolution images may be acquired with a high repetition rate and it is useful for analyzing phenology characteristics, but may not capture the spatial detail of the land cover mosaic of the region of interest. Previous spatial-temporal fusion methods were only capture the temporal change, or focused on both temporal change and spatial change but with low accuracy in heterogeneous landscapes and small patches. In this study, a new concept for spatial-temporal image fusion method focus on heterogeneous landscape was proposed to produce fine resolution images at both fine spatial and temporal resolution. We classified the three types of pixels between the base image and target image, the first type is only reflectance changed caused by phenology, this type of pixels supply the reflectance, shape and texture information; the second type is both reflectance and spectrum changed in some bands caused by phenology like rice paddy or farmland, this type of pixels only supply shape and texture information; the third type is reflectance and spectrum changed caused by land cover type change, this type of pixels don't provide any information because we can't know how land cover changed in target image; and each type of pixels were applied different prediction methods. Results show that both STARFM and FSDAF predicted in low accuracy in second type pixels and small patches. Classification results used spatial-temporal image fusion method proposed in this study showed overall classification accuracy of 89.38%, with corresponding kappa coefficients of 0.87.

PubMed Central

LINKE, R.; LEICHTLE, A.; SHEIKH, F.; SCHMIDT, C.; FRENZEL, H.; GRAEFE, H.; WOLLENBERG, B.; MEYER, J.E.

2013-01-01

SUMMARY Surgery on the temporal bone is technically challenging due to its complex anatomy. Precise anatomical dissection of the human temporal bone is essential and is fundamental for middle ear surgery. We assessed the possible application of a virtual reality temporal bone surgery simulator to the education of ear surgeons. Seventeen ENT physicians with different levels of surgical training and 20 medical students performed an antrotomy with a computer-based virtual temporal bone surgery simulator. The ease, accuracy and timing of the simulated temporal bone surgery were assessed using the automatic assessment software provided by the simulator device and additionally with a modified Final Product Analysis Scale. Trained ENT surgeons, physicians without temporal bone surgical training and medical students were all able to perform the antrotomy. However, the highly trained ENT surgeons were able to complete the surgery in approximately half the time, with better handling and accuracy as assessed by the significant reduction in injury to important middle ear structures. Trained ENT surgeons achieved significantly higher scores using both dissection analysis methods. Surprisingly, there were no significant differences in the results between medical students and physicians without experience in ear surgery. The virtual temporal bone training system can stratify users of known levels of experience. This system can be used not only to improve the surgical skills of trained ENT surgeons for more successful and injury-free surgeries, but also to train inexperienced physicians/medical students in developing their surgical skills for the ear. PMID:24043916

A multi-temporal fusion-based approach for land cover mapping in support of nuclear incident response

NASA Astrophysics Data System (ADS)

Sah, Shagan

An increasingly important application of remote sensing is to provide decision support during emergency response and disaster management efforts. Land cover maps constitute one such useful application product during disaster events; if generated rapidly after any disaster, such map products can contribute to the efficacy of the response effort. In light of recent nuclear incidents, e.g., after the earthquake/tsunami in Japan (2011), our research focuses on constructing rapid and accurate land cover maps of the impacted area in case of an accidental nuclear release. The methodology involves integration of results from two different approaches, namely coarse spatial resolution multi-temporal and fine spatial resolution imagery, to increase classification accuracy. Although advanced methods have been developed for classification using high spatial or temporal resolution imagery, only a limited amount of work has been done on fusion of these two remote sensing approaches. The presented methodology thus involves integration of classification results from two different remote sensing modalities in order to improve classification accuracy. The data used included RapidEye and MODIS scenes over the Nine Mile Point Nuclear Power Station in Oswego (New York, USA). The first step in the process was the construction of land cover maps from freely available, high temporal resolution, low spatial resolution MODIS imagery using a time-series approach. We used the variability in the temporal signatures among different land cover classes for classification. The time series-specific features were defined by various physical properties of a pixel, such as variation in vegetation cover and water content over time. The pixels were classified into four land cover classes - forest, urban, water, and vegetation - using Euclidean and Mahalanobis distance metrics. On the other hand, a high spatial resolution commercial satellite, such as RapidEye, can be tasked to capture images over the affected area in the case of a nuclear event. This imagery served as a second source of data to augment results from the time series approach. The classifications from the two approaches were integrated using an a posteriori probability-based fusion approach. This was done by establishing a relationship between the classes, obtained after classification of the two data sources. Despite the coarse spatial resolution of MODIS pixels, acceptable accuracies were obtained using time series features. The overall accuracies using the fusion-based approach were in the neighborhood of 80%, when compared with GIS data sets from New York State. This fusion thus contributed to classification accuracy refinement, with a few additional advantages, such as correction for cloud cover and providing for an approach that is robust against point-in-time seasonal anomalies, due to the inclusion of multi-temporal data. We concluded that this approach is capable of generating land cover maps of acceptable accuracy and rapid turnaround, which in turn can yield reliable estimates of crop acreage of a region. The final algorithm is part of an automated software tool, which can be used by emergency response personnel to generate a nuclear ingestion pathway information product within a few hours of data collection.

Human motor cortical activity recorded with Micro-ECoG electrodes, during individual finger movements.

PubMed

Wang, W; Degenhart, A D; Collinger, J L; Vinjamuri, R; Sudre, G P; Adelson, P D; Holder, D L; Leuthardt, E C; Moran, D W; Boninger, M L; Schwartz, A B; Crammond, D J; Tyler-Kabara, E C; Weber, D J

2009-01-01

In this study human motor cortical activity was recorded with a customized micro-ECoG grid during individual finger movements. The quality of the recorded neural signals was characterized in the frequency domain from three different perspectives: (1) coherence between neural signals recorded from different electrodes, (2) modulation of neural signals by finger movement, and (3) accuracy of finger movement decoding. It was found that, for the high frequency band (60-120 Hz), coherence between neighboring micro-ECoG electrodes was 0.3. In addition, the high frequency band showed significant modulation by finger movement both temporally and spatially, and a classification accuracy of 73% (chance level: 20%) was achieved for individual finger movement using neural signals recorded from the micro-ECoG grid. These results suggest that the micro-ECoG grid presented here offers sufficient spatial and temporal resolution for the development of minimally-invasive brain-computer interface applications.

Achieving behavioral control with millisecond resolution in a high-level programming environment

PubMed Central

Asaad, Wael F.; Eskandar, Emad N.

2008-01-01

The creation of psychophysical tasks for the behavioral neurosciences has generally relied upon low-level software running on a limited range of hardware. Despite the availability of software that allows the coding of behavioral tasks in high-level programming environments, many researchers are still reluctant to trust the temporal accuracy and resolution of programs running in such environments, especially when they run atop non-real-time operating systems. Thus, the creation of behavioral paradigms has been slowed by the intricacy of the coding required and their dissemination across labs has been hampered by the various types of hardware needed. However, we demonstrate here that, when proper measures are taken to handle the various sources of temporal error, accuracy can be achieved at the one millisecond time-scale that is relevant for the alignment of behavioral and neural events. PMID:18606188

Comparison of Several Numerical Methods for Simulation of Compressible Shear Layers

NASA Technical Reports Server (NTRS)

Kennedy, Christopher A.; Carpenter, Mark H.

1997-01-01

An investigation is conducted on several numerical schemes for use in the computation of two-dimensional, spatially evolving, laminar variable-density compressible shear layers. Schemes with various temporal accuracies and arbitrary spatial accuracy for both inviscid and viscous terms are presented and analyzed. All integration schemes use explicit or compact finite-difference derivative operators. Three classes of schemes are considered: an extension of MacCormack's original second-order temporally accurate method, a new third-order variant of the schemes proposed by Rusanov and by Kutier, Lomax, and Warming (RKLW), and third- and fourth-order Runge-Kutta schemes. In each scheme, stability and formal accuracy are considered for the interior operators on the convection-diffusion equation U(sub t) + aU(sub x) = alpha U(sub xx). Accuracy is also verified on the nonlinear problem, U(sub t) + F(sub x) = 0. Numerical treatments of various orders of accuracy are chosen and evaluated for asymptotic stability. Formally accurate boundary conditions are derived for several sixth- and eighth-order central-difference schemes. Damping of high wave-number data is accomplished with explicit filters of arbitrary order. Several schemes are used to compute variable-density compressible shear layers, where regions of large gradients exist.

Assessment of skills using a virtual reality temporal bone surgery simulator.

PubMed

Linke, R; Leichtle, A; Sheikh, F; Schmidt, C; Frenzel, H; Graefe, H; Wollenberg, B; Meyer, J E

2013-08-01

Surgery on the temporal bone is technically challenging due to its complex anatomy. Precise anatomical dissection of the human temporal bone is essential and is fundamental for middle ear surgery. We assessed the possible application of a virtual reality temporal bone surgery simulator to the education of ear surgeons. Seventeen ENT physicians with different levels of surgical training and 20 medical students performed an antrotomy with a computer-based virtual temporal bone surgery simulator. The ease, accuracy and timing of the simulated temporal bone surgery were assessed using the automatic assessment software provided by the simulator device and additionally with a modified Final Product Analysis Scale. Trained ENT surgeons, physicians without temporal bone surgical training and medical students were all able to perform the antrotomy. However, the highly trained ENT surgeons were able to complete the surgery in approximately half the time, with better handling and accuracy as assessed by the significant reduction in injury to important middle ear structures. Trained ENT surgeons achieved significantly higher scores using both dissection analysis methods. Surprisingly, there were no significant differences in the results between medical students and physicians without experience in ear surgery. The virtual temporal bone training system can stratify users of known levels of experience. This system can be used not only to improve the surgical skills of trained ENT surgeons for more successful and injury-free surgeries, but also to train inexperienced physicians/medical students in developing their surgical skills for the ear.

A Predictive Risk Model for A(H7N9) Human Infections Based on Spatial-Temporal Autocorrelation and Risk Factors: China, 2013–2014

PubMed Central

Dong, Wen; Yang, Kun; Xu, Quan-Li; Yang, Yu-Lian

2015-01-01

This study investigated the spatial distribution, spatial autocorrelation, temporal cluster, spatial-temporal autocorrelation and probable risk factors of H7N9 outbreaks in humans from March 2013 to December 2014 in China. The results showed that the epidemic spread with significant spatial-temporal autocorrelation. In order to describe the spatial-temporal autocorrelation of H7N9, an improved model was developed by introducing a spatial-temporal factor in this paper. Logistic regression analyses were utilized to investigate the risk factors associated with their distribution, and nine risk factors were significantly associated with the occurrence of A(H7N9) human infections: the spatial-temporal factor φ (OR = 2546669.382, p < 0.001), migration route (OR = 0.993, p < 0.01), river (OR = 0.861, p < 0.001), lake(OR = 0.992, p < 0.001), road (OR = 0.906, p < 0.001), railway (OR = 0.980, p < 0.001), temperature (OR = 1.170, p < 0.01), precipitation (OR = 0.615, p < 0.001) and relative humidity (OR = 1.337, p < 0.001). The improved model obtained a better prediction performance and a higher fitting accuracy than the traditional model: in the improved model 90.1% (91/101) of the cases during February 2014 occurred in the high risk areas (the predictive risk > 0.70) of the predictive risk map, whereas 44.6% (45/101) of which overlaid on the high risk areas (the predictive risk > 0.70) for the traditional model, and the fitting accuracy of the improved model was 91.6% which was superior to the traditional model (86.1%). The predictive risk map generated based on the improved model revealed that the east and southeast of China were the high risk areas of A(H7N9) human infections in February 2014. These results provided baseline data for the control and prevention of future human infections. PMID:26633446

Open Source Tools for Temporally Controlled Rodent Behavior Suitable for Electrophysiology and Optogenetic Manipulations.

PubMed

Solari, Nicola; Sviatkó, Katalin; Laszlovszky, Tamás; Hegedüs, Panna; Hangya, Balázs

2018-01-01

Understanding how the brain controls behavior requires observing and manipulating neural activity in awake behaving animals. Neuronal firing is timed at millisecond precision. Therefore, to decipher temporal coding, it is necessary to monitor and control animal behavior at the same level of temporal accuracy. However, it is technically challenging to deliver sensory stimuli and reinforcers as well as to read the behavioral responses they elicit with millisecond precision. Presently available commercial systems often excel in specific aspects of behavior control, but they do not provide a customizable environment allowing flexible experimental design while maintaining high standards for temporal control necessary for interpreting neuronal activity. Moreover, delay measurements of stimulus and reinforcement delivery are largely unavailable. We combined microcontroller-based behavior control with a sound delivery system for playing complex acoustic stimuli, fast solenoid valves for precisely timed reinforcement delivery and a custom-built sound attenuated chamber using high-end industrial insulation materials. Together this setup provides a physical environment to train head-fixed animals, enables calibrated sound stimuli and precisely timed fluid and air puff presentation as reinforcers. We provide latency measurements for stimulus and reinforcement delivery and an algorithm to perform such measurements on other behavior control systems. Combined with electrophysiology and optogenetic manipulations, the millisecond timing accuracy will help interpret temporally precise neural signals and behavioral changes. Additionally, since software and hardware provided here can be readily customized to achieve a large variety of paradigms, these solutions enable an unusually flexible design of rodent behavioral experiments.

Time reproduction performance is associated with age and working memory in high-functioning youth with autism spectrum disorder.

PubMed

Brenner, Laurie A; Shih, Vivian H; Colich, Natalie L; Sugar, Catherine A; Bearden, Carrie E; Dapretto, Mirella

2015-02-01

Impaired temporal processing has historically been viewed as a hallmark feature of attention deficit hyperactivity disorder. Recent evidence suggests temporal processing deficits may also be characteristic of autism spectrum disorder (ASD). However, little is known about the factors that impact temporal processing in children with ASD. The purpose of this study was to assess the effects of co-morbid attention problems, working memory (WM), age, and their interactions, on time reproduction in youth with and without ASD. Twenty-seven high-functioning individuals with ASD and 25 demographically comparable typically developing individuals (ages 9-17; 85% male) were assessed on measures of time reproduction, auditory WM, and inattention/hyperactivity. The time reproduction task required depression of a computer key to mimic interval durations of 4, 8, 12, 16, or 20 sec. Mixed effects regression analyses were used to model accuracy and variability of time reproduction as functions of diagnostic group, interval duration, age, WM, and inattention/hyperactivity. A significant group by age interaction was detected for accuracy, with the deficit in the ASD group being greater in younger children. There was a significant group by WM interaction for consistency, with the effects of poor WM on performance consistency being more pronounced in youth with ASD. All participants tended to underestimate longer interval durations and to be less consistent for shorter interval durations; these effects appeared more pronounced in those who were younger or who had poorer WM performance. Inattention/hyperactivity symptoms in the ASD group were not related to either accuracy or consistency. This study highlights the potential value of temporal processing as an intermediate trait of relevance to multiple neurodevelopmental disorders. © 2014 International Society for Autism Research, Wiley Periodicals, Inc.

Evaluating the capacity of GF-4 satellite data for estimating fractional vegetation cover

NASA Astrophysics Data System (ADS)

Zhang, C.; Qin, Q.; Ren, H.; Zhang, T.; Sun, Y.

2016-12-01

Fractional vegetation cover (FVC) is a crucial parameter for many agricultural, environmental, meteorological and ecological applications, which is of great importance for studies on ecosystem structure and function. The Chinese GaoFen-4 (GF-4) geostationary satellite designed for the purpose of environmental and ecological observation was launched in December 29, 2015, and official use has been started by Chinese Government on June 13, 2016. Multi-spectral images with spatial resolution of 50 m and high temporal resolution, could be acquired by the sensor on GF-4 satellite on the 36000 km-altitude orbit. To take full advantage of the outstanding performance of GF-4 satellite, this study evaluated the capacity of GF-4 satellite data for monitoring FVC. To the best of our knowledge, this is the first research about estimating FVC from GF-4 satellite images. First, we developed a procedure for preprocessing GF-4 satellite data, including radiometric calibration and atmospheric correction, to acquire surface reflectance. Then single image and multi-temporal images were used for extracting the endmembers of vegetation and soil, respectively. After that, dimidiate pixel model and square model based on vegetation indices were used for estimating FVC. Finally, the estimation results were comparatively analyzed with FVC estimated by other existing sensors. The experimental results showed that satisfying accuracy of FVC estimation could be achieved from GF-4 satellite images using dimidiate pixel model and square model based on vegetation indices. What's more, the multi-temporal images increased the probability to find pure vegetation and soil endmembers, thus the characteristic of high temporal resolution of GF-4 satellite images improved the accuracy of FVC estimation. This study demonstrated the capacity of GF-4 satellite data for monitoring FVC. The conclusions reached by this study are significant for improving the accuracy and spatial-temporal resolution of existing FVC products, which provides a basis for the studies on ecosystem structure and function using remote sensing data acquired by GF-4 satellite.

Temporal Processing Instability with Millisecond Accuracy Is a Cardinal Feature of Sensorimotor Impairments in Autism Spectrum Disorder: Analysis Using the Synchronized Finger-Tapping Task

ERIC Educational Resources Information Center

Morimoto, Chie; Hida, Eisuke; Shima, Keisuke; Okamura, Hitoshi

2018-01-01

To identify a specific sensorimotor impairment feature of autism spectrum disorder (ASD), we focused on temporal processing with millisecond accuracy. A synchronized finger-tapping task was used to characterize temporal processing in individuals with ASD as compared to typically developing (TD) individuals. We found that individuals with ASD…

Bottom-Up Mechanisms Are Involved in the Relation between Accuracy in Timing Tasks and Intelligence--Further Evidence Using Manipulations of State Motivation

ERIC Educational Resources Information Center

Ullen, Fredrik; Soderlund, Therese; Kaaria, Lenita; Madison, Guy

2012-01-01

Intelligence correlates with accuracy in various timing tasks. Such correlations could be due to both bottom-up mechanisms, e.g. neural properties that influence both temporal accuracy and cognitive processing, and differences in top-down control. We have investigated the timing-intelligence relation using a simple temporal motor task, isochronous…

Influence of Gridded Standoff Measurement Resolution on Numerical Bathymetric Inversion

NASA Astrophysics Data System (ADS)

Hesser, T.; Farthing, M. W.; Brodie, K.

2016-02-01

The bathymetry from the surfzone to the shoreline incurs frequent, active movement due to wave energy interacting with the seafloor. Methodologies to measure bathymetry range from point-source in-situ instruments, vessel-mounted single-beam or multi-beam sonar surveys, airborne bathymetric lidar, as well as inversion techniques from standoff measurements of wave processes from video or radar imagery. Each type of measurement has unique sources of error and spatial and temporal resolution and availability. Numerical bathymetry estimation frameworks can use these disparate data types in combination with model-based inversion techniques to produce a "best-estimate of bathymetry" at a given time. Understanding how the sources of error and varying spatial or temporal resolution of each data type affect the end result is critical for determining best practices and in turn increase the accuracy of bathymetry estimation techniques. In this work, we consider an initial step in the development of a complete framework for estimating bathymetry in the nearshore by focusing on gridded standoff measurements and in-situ point observations in model-based inversion at the U.S. Army Corps of Engineers Field Research Facility in Duck, NC. The standoff measurement methods return wave parameters computed using linear wave theory from the direct measurements. These gridded datasets can range in temporal and spatial resolution that do not match the desired model parameters and therefore could lead to a reduction in the accuracy of these methods. Specifically, we investigate the affect of numerical resolution on the accuracy of an Ensemble Kalman Filter bathymetric inversion technique in relation to the spatial and temporal resolution of the gridded standoff measurements. The accuracies of the bathymetric estimates are compared with both high-resolution Real Time Kinematic (RTK) single-beam surveys as well as alternative direct in-situ measurements using sonic altimeters.

Functional response in ventral temporal cortex differentiates mild cognitive impairment from normal aging

PubMed Central

Gold, Brian T.; Jiang, Yang; Jicha, Greg A.; Smith, Charles D.

2010-01-01

The present study sought to identify altered brain activation patterns in amnestic mild cognitive impairment (MCI) that could precede frank task impairment and neocortical atrophy. A high accuracy lexical decision (LD) task was therefore employed. Both MCI and normal senior (NS) groups completed the LD task while functional magnetic resonance imaging (fMRI) was performed. Accuracy on the LD task was high (≥ 89% correct for both groups), and both groups activated a network of occipitotemporal regions and inferior frontal cortex. However, compared to the NS group, the MCI group showed reduced fMRI activation in these regions and increased activation in bilateral portions of anterior cingluate cortex. Results from a voxel-based morphometry analysis indicate that altered activations in the MCI group were not within regions of atrophy. Receiver operating characteristic curves demonstrate that reduced fMRI response in the left and right mid-fusiform gyri accurately discriminate MCI from NS. When activation magnitude in both fusiform gyri were included in a single logistic regression model, group classification accuracy was very high (area under the curve = 0.93). These results show that a disrupted functional response in the ventral temporal lobe accurately distinguishes individuals with MCI from normal seniors, a finding which may have implications for identifying seniors at risk for cognitive decline. PMID:20063353

Estimation of Temporal Gait Parameters Using a Human Body Electrostatic Sensing-Based Method.

PubMed

Li, Mengxuan; Li, Pengfei; Tian, Shanshan; Tang, Kai; Chen, Xi

2018-05-28

Accurate estimation of gait parameters is essential for obtaining quantitative information on motor deficits in Parkinson's disease and other neurodegenerative diseases, which helps determine disease progression and therapeutic interventions. Due to the demand for high accuracy, unobtrusive measurement methods such as optical motion capture systems, foot pressure plates, and other systems have been commonly used in clinical environments. However, the high cost of existing lab-based methods greatly hinders their wider usage, especially in developing countries. In this study, we present a low-cost, noncontact, and an accurate temporal gait parameters estimation method by sensing and analyzing the electrostatic field generated from human foot stepping. The proposed method achieved an average 97% accuracy on gait phase detection and was further validated by comparison to the foot pressure system in 10 healthy subjects. Two results were compared using the Pearson coefficient r and obtained an excellent consistency ( r = 0.99, p < 0.05). The repeatability of the purposed method was calculated between days by intraclass correlation coefficients (ICC), and showed good test-retest reliability (ICC = 0.87, p < 0.01). The proposed method could be an affordable and accurate tool to measure temporal gait parameters in hospital laboratories and in patients' home environments.

Technical note: Coupling infrared gas analysis and cavity ring down spectroscopy for autonomous, high-temporal-resolution measurements of DIC and δ13C-DIC

NASA Astrophysics Data System (ADS)

Call, Mitchell; Schulz, Kai G.; Carvalho, Matheus C.; Santos, Isaac R.; Maher, Damien T.

2017-03-01

A new approach to autonomously determine concentrations of dissolved inorganic carbon (DIC) and its carbon stable isotope ratio (δ13C-DIC) at high temporal resolution is presented. The simple method requires no customised design. Instead it uses two commercially available instruments currently used in aquatic carbon research. An inorganic carbon analyser utilising non-dispersive infrared detection (NDIR) is coupled to a Cavity Ring-down Spectrometer (CRDS) to determine DIC and δ13C-DIC based on the liberated CO2 from acidified aliquots of water. Using a small sample volume of 2 mL, the precision and accuracy of the new method was comparable to standard isotope ratio mass spectrometry (IRMS) methods. The system achieved a sampling resolution of 16 min, with a DIC precision of ±1.5 to 2 µmol kg-1 and δ13C-DIC precision of ±0.14 ‰ for concentrations spanning 1000 to 3600 µmol kg-1. Accuracy of 0.1 ± 0.06 ‰ for δ13C-DIC based on DIC concentrations ranging from 2000 to 2230 µmol kg-1 was achieved during a laboratory-based algal bloom experiment. The high precision data that can be autonomously obtained by the system should enable complex carbonate system questions to be explored in aquatic sciences using high-temporal-resolution observations.

Temporal regularization of ultrasound-based liver motion estimation for image-guided radiation therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

O’Shea, Tuathan P., E-mail: tuathan.oshea@icr.ac.uk; Bamber, Jeffrey C.; Harris, Emma J.

Purpose: Ultrasound-based motion estimation is an expanding subfield of image-guided radiation therapy. Although ultrasound can detect tissue motion that is a fraction of a millimeter, its accuracy is variable. For controlling linear accelerator tracking and gating, ultrasound motion estimates must remain highly accurate throughout the imaging sequence. This study presents a temporal regularization method for correlation-based template matching which aims to improve the accuracy of motion estimates. Methods: Liver ultrasound sequences (15–23 Hz imaging rate, 2.5–5.5 min length) from ten healthy volunteers under free breathing were used. Anatomical features (blood vessels) in each sequence were manually annotated for comparison withmore » normalized cross-correlation based template matching. Five sequences from a Siemens Acuson™ scanner were used for algorithm development (training set). Results from incremental tracking (IT) were compared with a temporal regularization method, which included a highly specific similarity metric and state observer, known as the α–β filter/similarity threshold (ABST). A further five sequences from an Elekta Clarity™ system were used for validation, without alteration of the tracking algorithm (validation set). Results: Overall, the ABST method produced marked improvements in vessel tracking accuracy. For the training set, the mean and 95th percentile (95%) errors (defined as the difference from manual annotations) were 1.6 and 1.4 mm, respectively (compared to 6.2 and 9.1 mm, respectively, for IT). For each sequence, the use of the state observer leads to improvement in the 95% error. For the validation set, the mean and 95% errors for the ABST method were 0.8 and 1.5 mm, respectively. Conclusions: Ultrasound-based motion estimation has potential to monitor liver translation over long time periods with high accuracy. Nonrigid motion (strain) and the quality of the ultrasound data are likely to have an impact on tracking performance. A future study will investigate spatial uniformity of motion and its effect on the motion estimation errors.« less

Object-Based Paddy Rice Mapping Using HJ-1A/B Data and Temporal Features Extracted from Time Series MODIS NDVI Data

PubMed Central

Singha, Mrinal; Wu, Bingfang; Zhang, Miao

2016-01-01

Accurate and timely mapping of paddy rice is vital for food security and environmental sustainability. This study evaluates the utility of temporal features extracted from coarse resolution data for object-based paddy rice classification of fine resolution data. The coarse resolution vegetation index data is first fused with the fine resolution data to generate the time series fine resolution data. Temporal features are extracted from the fused data and added with the multi-spectral data to improve the classification accuracy. Temporal features provided the crop growth information, while multi-spectral data provided the pattern variation of paddy rice. The achieved overall classification accuracy and kappa coefficient were 84.37% and 0.68, respectively. The results indicate that the use of temporal features improved the overall classification accuracy of a single-date multi-spectral image by 18.75% from 65.62% to 84.37%. The minimum sensitivity (MS) of the paddy rice classification has also been improved. The comparison showed that the mapped paddy area was analogous to the agricultural statistics at the district level. This work also highlighted the importance of feature selection to achieve higher classification accuracies. These results demonstrate the potential of the combined use of temporal and spectral features for accurate paddy rice classification. PMID:28025525

Object-Based Paddy Rice Mapping Using HJ-1A/B Data and Temporal Features Extracted from Time Series MODIS NDVI Data.

PubMed

Singha, Mrinal; Wu, Bingfang; Zhang, Miao

2016-12-22

Accurate and timely mapping of paddy rice is vital for food security and environmental sustainability. This study evaluates the utility of temporal features extracted from coarse resolution data for object-based paddy rice classification of fine resolution data. The coarse resolution vegetation index data is first fused with the fine resolution data to generate the time series fine resolution data. Temporal features are extracted from the fused data and added with the multi-spectral data to improve the classification accuracy. Temporal features provided the crop growth information, while multi-spectral data provided the pattern variation of paddy rice. The achieved overall classification accuracy and kappa coefficient were 84.37% and 0.68, respectively. The results indicate that the use of temporal features improved the overall classification accuracy of a single-date multi-spectral image by 18.75% from 65.62% to 84.37%. The minimum sensitivity (MS) of the paddy rice classification has also been improved. The comparison showed that the mapped paddy area was analogous to the agricultural statistics at the district level. This work also highlighted the importance of feature selection to achieve higher classification accuracies. These results demonstrate the potential of the combined use of temporal and spectral features for accurate paddy rice classification.

Projection-based motion estimation for cardiac functional analysis with high temporal resolution: a proof-of-concept study with digital phantom experiment

NASA Astrophysics Data System (ADS)

Suzuki, Yuki; Fung, George S. K.; Shen, Zeyang; Otake, Yoshito; Lee, Okkyun; Ciuffo, Luisa; Ashikaga, Hiroshi; Sato, Yoshinobu; Taguchi, Katsuyuki

2017-03-01

Cardiac motion (or functional) analysis has shown promise not only for non-invasive diagnosis of cardiovascular diseases but also for prediction of cardiac future events. Current imaging modalities has limitations that could degrade the accuracy of the analysis indices. In this paper, we present a projection-based motion estimation method for x-ray CT that estimates cardiac motion with high spatio-temporal resolution using projection data and a reference 3D volume image. The experiment using a synthesized digital phantom showed promising results for motion analysis.

Performance of the Multi-Radar Multi-Sensor System over the Lower Colorado River, Texas

NASA Astrophysics Data System (ADS)

Bayabil, H. K.; Sharif, H. O.; Fares, A.; Awal, R.; Risch, E.

2017-12-01

Recently observed increases in intensities and frequencies of climate extremes (e.g., floods, dam failure, and overtopping of river banks) necessitate the development of effective disaster prevention and mitigation strategies. Hydrologic models can be useful tools in predicting such events at different spatial and temporal scales. However, accuracy and prediction capability of such models are often constrained by the availability of high-quality representative hydro-meteorological data (e.g., precipitation) that are required to calibrate and validate such models. Improved technologies and products such as the Multi-Radar Multi-Sensor (MRMS) system that allows gathering and transmission of vast meteorological data have been developed to provide such data needs. While the MRMS data are available with high spatial and temporal resolutions (1 km and 15 min, respectively), its accuracy in estimating precipitation is yet to be fully investigated. Therefore, the main objective of this study is to evaluate the performance of the MRMS system in effectively capturing precipitation over the Lower Colorado River, Texas using observations from a dense rain gauge network. In addition, effects of spatial and temporal aggregation scales on the performance of the MRMS system were evaluated. Point scale comparisons were made at 215 gauging locations using rain gauges and MRMS data from May 2015. Moreover, the effects of temporal and spatial data aggregation scales (30, 45, 60, 75, 90, 105, and 120 min) and (4 to 50 km), respectively on the performance of the MRMS system were tested. Overall, the MRMS system (at 15 min temporal resolution) captured precipitation reasonably well, with an average R2 value of 0.65 and RMSE of 0.5 mm. In addition, spatial and temporal data aggregations resulted in increases in R2 values. However, reduction in RMSE was achieved only with an increase in spatial aggregations.

Temporal Data Set Reduction Based on D-Optimality for Quantitative FLIM-FRET Imaging.

PubMed

Omer, Travis; Intes, Xavier; Hahn, Juergen

2015-01-01

Fluorescence lifetime imaging (FLIM) when paired with Förster resonance energy transfer (FLIM-FRET) enables the monitoring of nanoscale interactions in living biological samples. FLIM-FRET model-based estimation methods allow the quantitative retrieval of parameters such as the quenched (interacting) and unquenched (non-interacting) fractional populations of the donor fluorophore and/or the distance of the interactions. The quantitative accuracy of such model-based approaches is dependent on multiple factors such as signal-to-noise ratio and number of temporal points acquired when sampling the fluorescence decays. For high-throughput or in vivo applications of FLIM-FRET, it is desirable to acquire a limited number of temporal points for fast acquisition times. Yet, it is critical to acquire temporal data sets with sufficient information content to allow for accurate FLIM-FRET parameter estimation. Herein, an optimal experimental design approach based upon sensitivity analysis is presented in order to identify the time points that provide the best quantitative estimates of the parameters for a determined number of temporal sampling points. More specifically, the D-optimality criterion is employed to identify, within a sparse temporal data set, the set of time points leading to optimal estimations of the quenched fractional population of the donor fluorophore. Overall, a reduced set of 10 time points (compared to a typical complete set of 90 time points) was identified to have minimal impact on parameter estimation accuracy (≈5%), with in silico and in vivo experiment validations. This reduction of the number of needed time points by almost an order of magnitude allows the use of FLIM-FRET for certain high-throughput applications which would be infeasible if the entire number of time sampling points were used.

Improved accuracy of quantitative parameter estimates in dynamic contrast-enhanced CT study with low temporal resolution

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kim, Sun Mo, E-mail: Sunmo.Kim@rmp.uhn.on.ca; Haider, Masoom A.; Jaffray, David A.

Purpose: A previously proposed method to reduce radiation dose to patient in dynamic contrast-enhanced (DCE) CT is enhanced by principal component analysis (PCA) filtering which improves the signal-to-noise ratio (SNR) of time-concentration curves in the DCE-CT study. The efficacy of the combined method to maintain the accuracy of kinetic parameter estimates at low temporal resolution is investigated with pixel-by-pixel kinetic analysis of DCE-CT data. Methods: The method is based on DCE-CT scanning performed with low temporal resolution to reduce the radiation dose to the patient. The arterial input function (AIF) with high temporal resolution can be generated with a coarselymore » sampled AIF through a previously published method of AIF estimation. To increase the SNR of time-concentration curves (tissue curves), first, a region-of-interest is segmented into squares composed of 3 × 3 pixels in size. Subsequently, the PCA filtering combined with a fraction of residual information criterion is applied to all the segmented squares for further improvement of their SNRs. The proposed method was applied to each DCE-CT data set of a cohort of 14 patients at varying levels of down-sampling. The kinetic analyses using the modified Tofts’ model and singular value decomposition method, then, were carried out for each of the down-sampling schemes between the intervals from 2 to 15 s. The results were compared with analyses done with the measured data in high temporal resolution (i.e., original scanning frequency) as the reference. Results: The patients’ AIFs were estimated to high accuracy based on the 11 orthonormal bases of arterial impulse responses established in the previous paper. In addition, noise in the images was effectively reduced by using five principal components of the tissue curves for filtering. Kinetic analyses using the proposed method showed superior results compared to those with down-sampling alone; they were able to maintain the accuracy in the quantitative histogram parameters of volume transfer constant [standard deviation (SD), 98th percentile, and range], rate constant (SD), blood volume fraction (mean, SD, 98th percentile, and range), and blood flow (mean, SD, median, 98th percentile, and range) for sampling intervals between 10 and 15 s. Conclusions: The proposed method of PCA filtering combined with the AIF estimation technique allows low frequency scanning for DCE-CT study to reduce patient radiation dose. The results indicate that the method is useful in pixel-by-pixel kinetic analysis of DCE-CT data for patients with cervical cancer.« less

FMRI Is a Valid Noninvasive Alternative to Wada Testing

PubMed Central

Binder, Jeffrey R.

2010-01-01

Partial removal of the anterior temporal lobe (ATL) is a highly effective surgical treatment for intractable temporal lobe epilepsy, yet roughly half of patients who undergo left ATL resection show decline in language or verbal memory function postoperatively. Two recent studies demonstrate that preoperative fMRI can predict postoperative naming and verbal memory changes in such patients. Most importantly, fMRI significantly improves the accuracy of prediction relative to other noninvasive measures used alone. Addition of language and memory lateralization data from the intracarotid amobarbital (Wada) test did not improve prediction accuracy in these studies. Thus, fMRI provides patients and practitioners with a safe, non-invasive, and well-validated tool for making better-informed decisions regarding elective surgery based on a quantitative assessment of cognitive risk. PMID:20850386

A Subspace Pursuit–based Iterative Greedy Hierarchical Solution to the Neuromagnetic Inverse Problem

PubMed Central

Babadi, Behtash; Obregon-Henao, Gabriel; Lamus, Camilo; Hämäläinen, Matti S.; Brown, Emery N.; Purdon, Patrick L.

2013-01-01

Magnetoencephalography (MEG) is an important non-invasive method for studying activity within the human brain. Source localization methods can be used to estimate spatiotemporal activity from MEG measurements with high temporal resolution, but the spatial resolution of these estimates is poor due to the ill-posed nature of the MEG inverse problem. Recent developments in source localization methodology have emphasized temporal as well as spatial constraints to improve source localization accuracy, but these methods can be computationally intense. Solutions emphasizing spatial sparsity hold tremendous promise, since the underlying neurophysiological processes generating MEG signals are often sparse in nature, whether in the form of focal sources, or distributed sources representing large-scale functional networks. Recent developments in the theory of compressed sensing (CS) provide a rigorous framework to estimate signals with sparse structure. In particular, a class of CS algorithms referred to as greedy pursuit algorithms can provide both high recovery accuracy and low computational complexity. Greedy pursuit algorithms are difficult to apply directly to the MEG inverse problem because of the high-dimensional structure of the MEG source space and the high spatial correlation in MEG measurements. In this paper, we develop a novel greedy pursuit algorithm for sparse MEG source localization that overcomes these fundamental problems. This algorithm, which we refer to as the Subspace Pursuit-based Iterative Greedy Hierarchical (SPIGH) inverse solution, exhibits very low computational complexity while achieving very high localization accuracy. We evaluate the performance of the proposed algorithm using comprehensive simulations, as well as the analysis of human MEG data during spontaneous brain activity and somatosensory stimuli. These studies reveal substantial performance gains provided by the SPIGH algorithm in terms of computational complexity, localization accuracy, and robustness. PMID:24055554

The Evaluation of a Temporal Reasoning System in Processing Clinical Discharge Summaries

PubMed Central

Zhou, Li; Parsons, Simon; Hripcsak, George

2008-01-01

Context TimeText is a temporal reasoning system designed to represent, extract, and reason about temporal information in clinical text. Objective To measure the accuracy of the TimeText for processing clinical discharge summaries. Design Six physicians with biomedical informatics training served as domain experts. Twenty discharge summaries were randomly selected for the evaluation. For each of the first 14 reports, 5 to 8 clinically important medical events were chosen. The temporal reasoning system generated temporal relations about the endpoints (start or finish) of pairs of medical events. Two experts (subjects) manually generated temporal relations for these medical events. The system and expert-generated results were assessed by four other experts (raters). All of the twenty discharge summaries were used to assess the system’s accuracy in answering time-oriented clinical questions. For each report, five to ten clinically plausible temporal questions about events were generated. Two experts generated answers to the questions to serve as the gold standard. We wrote queries to retrieve answers from system’s output. Measurements Correctness of generated temporal relations, recall of clinically important relations, and accuracy in answering temporal questions. Results The raters determined that 97% of subjects’ 295 generated temporal relations were correct and that 96.5% of the system’s 995 generated temporal relations were correct. The system captured 79% of 307 temporal relations determined to be clinically important by the subjects and raters. The system answered 84% of the temporal questions correctly. Conclusion The system encoded the majority of information identified by experts, and was able to answer simple temporal questions. PMID:17947618

MR-based source localization for MR-guided HDR brachytherapy

NASA Astrophysics Data System (ADS)

Beld, E.; Moerland, M. A.; Zijlstra, F.; Viergever, M. A.; Lagendijk, J. J. W.; Seevinck, P. R.

2018-04-01

For the purpose of MR-guided high-dose-rate (HDR) brachytherapy, a method for real-time localization of an HDR brachytherapy source was developed, which requires high spatial and temporal resolutions. MR-based localization of an HDR source serves two main aims. First, it enables real-time treatment verification by determination of the HDR source positions during treatment. Second, when using a dummy source, MR-based source localization provides an automatic detection of the source dwell positions after catheter insertion, allowing elimination of the catheter reconstruction procedure. Localization of the HDR source was conducted by simulation of the MR artifacts, followed by a phase correlation localization algorithm applied to the MR images and the simulated images, to determine the position of the HDR source in the MR images. To increase the temporal resolution of the MR acquisition, the spatial resolution was decreased, and a subpixel localization operation was introduced. Furthermore, parallel imaging (sensitivity encoding) was applied to further decrease the MR scan time. The localization method was validated by a comparison with CT, and the accuracy and precision were investigated. The results demonstrated that the described method could be used to determine the HDR source position with a high accuracy (0.4–0.6 mm) and a high precision (⩽0.1 mm), at high temporal resolutions (0.15–1.2 s per slice). This would enable real-time treatment verification as well as an automatic detection of the source dwell positions.

Temporal variability in estuarine fish otolith elemental fingerprints: Implications for connectivity assessments

NASA Astrophysics Data System (ADS)

Reis-Santos, Patrick; Gillanders, Bronwyn M.; Tanner, Susanne E.; Vasconcelos, Rita P.; Elsdon, Travis S.; Cabral, Henrique N.

2012-10-01

The chemical composition of fish otoliths can provide valuable information for determining the nursery value of estuaries to adult populations of coastal fishes. However, understanding temporal variation in elemental fingerprints at different scales is important as it can potentially confound spatial discrimination among estuaries. Otolith elemental ratios (Li:Ca, Mg:Ca, Mn:Ca, Cu:Ca, Sr:Ca, Ba:Ca and Pb:Ca) of Platichthys flesus and Dicentrarchus labrax, from several estuaries along the Portuguese coast in two years and three seasons (spring, summer and autumn) within a year, were determined via Laser Ablation Inductively Coupled Plasma Mass Spectrometry. Elemental fingerprints varied significantly among years and seasons within a year but we achieved accurate classifications of juvenile fish to estuarine nursery of origin (77-96% overall cross-validated accuracy). Although elemental fingerprints were year-specific, variation among seasons did not hinder spatial discrimination. Estuarine fingerprints of pooled seasonal data were representative of the entire juvenile year class and attained high discrimination (77% and 80% overall cross-validated accuracy for flounder and sea bass, respectively). Incorporating seasonal variation resulted in up to an 11% increase in correct classification of individual estuaries, in comparison to seasons where accuracies were lowest. Overall, understanding the implications of temporal variations in otolith chemistry for spatial discrimination is key to establish baseline data for connectivity studies.

Extended Kalman filtering for continuous volumetric MR-temperature imaging.

PubMed

Denis de Senneville, Baudouin; Roujol, Sébastien; Hey, Silke; Moonen, Chrit; Ries, Mario

2013-04-01

Real time magnetic resonance (MR) thermometry has evolved into the method of choice for the guidance of high-intensity focused ultrasound (HIFU) interventions. For this role, MR-thermometry should preferably have a high temporal and spatial resolution and allow observing the temperature over the entire targeted area and its vicinity with a high accuracy. In addition, the precision of real time MR-thermometry for therapy guidance is generally limited by the available signal-to-noise ratio (SNR) and the influence of physiological noise. MR-guided HIFU would benefit of the large coverage volumetric temperature maps, including characterization of volumetric heating trajectories as well as near- and far-field heating. In this paper, continuous volumetric MR-temperature monitoring was obtained as follows. The targeted area was continuously scanned during the heating process by a multi-slice sequence. Measured data and a priori knowledge of 3-D data derived from a forecast based on a physical model were combined using an extended Kalman filter (EKF). The proposed reconstruction improved the temperature measurement resolution and precision while maintaining guaranteed output accuracy. The method was evaluated experimentally ex vivo on a phantom, and in vivo on a porcine kidney, using HIFU heating. On the in vivo experiment, it allowed the reconstruction from a spatio-temporally under-sampled data set (with an update rate for each voxel of 1.143 s) to a 3-D dataset covering a field of view of 142.5×285×54 mm(3) with a voxel size of 3×3×6 mm(3) and a temporal resolution of 0.127 s. The method also provided noise reduction, while having a minimal impact on accuracy and latency.

Open Source Tools for Temporally Controlled Rodent Behavior Suitable for Electrophysiology and Optogenetic Manipulations

PubMed Central

Solari, Nicola; Sviatkó, Katalin; Laszlovszky, Tamás; Hegedüs, Panna; Hangya, Balázs

2018-01-01

Understanding how the brain controls behavior requires observing and manipulating neural activity in awake behaving animals. Neuronal firing is timed at millisecond precision. Therefore, to decipher temporal coding, it is necessary to monitor and control animal behavior at the same level of temporal accuracy. However, it is technically challenging to deliver sensory stimuli and reinforcers as well as to read the behavioral responses they elicit with millisecond precision. Presently available commercial systems often excel in specific aspects of behavior control, but they do not provide a customizable environment allowing flexible experimental design while maintaining high standards for temporal control necessary for interpreting neuronal activity. Moreover, delay measurements of stimulus and reinforcement delivery are largely unavailable. We combined microcontroller-based behavior control with a sound delivery system for playing complex acoustic stimuli, fast solenoid valves for precisely timed reinforcement delivery and a custom-built sound attenuated chamber using high-end industrial insulation materials. Together this setup provides a physical environment to train head-fixed animals, enables calibrated sound stimuli and precisely timed fluid and air puff presentation as reinforcers. We provide latency measurements for stimulus and reinforcement delivery and an algorithm to perform such measurements on other behavior control systems. Combined with electrophysiology and optogenetic manipulations, the millisecond timing accuracy will help interpret temporally precise neural signals and behavioral changes. Additionally, since software and hardware provided here can be readily customized to achieve a large variety of paradigms, these solutions enable an unusually flexible design of rodent behavioral experiments. PMID:29867383

Temporal binning of time-correlated single photon counting data improves exponential decay fits and imaging speed

PubMed Central

Walsh, Alex J.; Sharick, Joe T.; Skala, Melissa C.; Beier, Hope T.

2016-01-01

Time-correlated single photon counting (TCSPC) enables acquisition of fluorescence lifetime decays with high temporal resolution within the fluorescence decay. However, many thousands of photons per pixel are required for accurate lifetime decay curve representation, instrument response deconvolution, and lifetime estimation, particularly for two-component lifetimes. TCSPC imaging speed is inherently limited due to the single photon per laser pulse nature and low fluorescence event efficiencies (<10%) required to reduce bias towards short lifetimes. Here, simulated fluorescence lifetime decays are analyzed by SPCImage and SLIM Curve software to determine the limiting lifetime parameters and photon requirements of fluorescence lifetime decays that can be accurately fit. Data analysis techniques to improve fitting accuracy for low photon count data were evaluated. Temporal binning of the decays from 256 time bins to 42 time bins significantly (p<0.0001) improved fit accuracy in SPCImage and enabled accurate fits with low photon counts (as low as 700 photons/decay), a 6-fold reduction in required photons and therefore improvement in imaging speed. Additionally, reducing the number of free parameters in the fitting algorithm by fixing the lifetimes to known values significantly reduced the lifetime component error from 27.3% to 3.2% in SPCImage (p<0.0001) and from 50.6% to 4.2% in SLIM Curve (p<0.0001). Analysis of nicotinamide adenine dinucleotide–lactate dehydrogenase (NADH-LDH) solutions confirmed temporal binning of TCSPC data and a reduced number of free parameters improves exponential decay fit accuracy in SPCImage. Altogether, temporal binning (in SPCImage) and reduced free parameters are data analysis techniques that enable accurate lifetime estimation from low photon count data and enable TCSPC imaging speeds up to 6x and 300x faster, respectively, than traditional TCSPC analysis. PMID:27446663

A use case study on late stent thrombosis for ontology-based temporal reasoning and analysis.

PubMed

Clark, Kim; Sharma, Deepak; Qin, Rui; Chute, Christopher G; Tao, Cui

2014-01-01

In this paper, we show how we have applied the Clinical Narrative Temporal Relation Ontology (CNTRO) and its associated temporal reasoning system (the CNTRO Timeline Library) to trend temporal information within medical device adverse event report narratives. 238 narratives documenting occurrences of late stent thrombosis adverse events from the Food and Drug Administration's (FDA) Manufacturing and User Facility Device Experience (MAUDE) database were annotated and evaluated using the CNTRO Timeline Library to identify, order, and calculate the duration of temporal events. The CNTRO Timeline Library had a 95% accuracy in correctly ordering events within the 238 narratives. 41 narratives included an event in which the duration was documented, and the CNTRO Timeline Library had an 80% accuracy in correctly determining these durations. 77 narratives included documentation of a duration between events, and the CNTRO Timeline Library had a 76% accuracy in determining these durations. This paper also includes an example of how this temporal output from the CNTRO ontology can be used to verify recommendations for length of drug administration, and proposes that these same tools could be applied to other medical device adverse event narratives in order to identify currently unknown temporal trends.

Socio-neuro risk factors for suicidal behavior in criminal offenders with psychotic disorders.

PubMed

Harenski, Carla L; Brook, Michael; Kosson, David S; Bustillo, Juan R; Harenski, Keith A; Caldwell, Michael F; Van Rybroek, Gregory J; Koenigs, Michael; Decety, Jean; Thornton, David M; Calhoun, Vince D; Kiehl, Kent A

2017-01-01

Relative to the general population, individuals with psychotic disorders have a higher risk of suicide. Suicide risk is also elevated in criminal offenders. Thus, psychotic-disordered individuals with antisocial tendencies may form an especially high-risk group. We built upon prior risk analyses by examining whether neurobehavioral correlates of social cognition were associated with suicidal behavior in criminal offenders with psychotic disorders. We assessed empathic accuracy and brain structure in four groups: (i) incarcerated offenders with psychotic disorders and past suicide attempts, (ii) incarcerated offenders with psychotic disorders and no suicide attempts, (iii) incarcerated offenders without psychotic disorders and (iv) community non-offenders without psychotic disorders. Established suicide risk variables were examined along with empathic accuracy and gray matter in brain regions implicated in social cognition. Relative to the other groups, offenders with psychotic disorders and suicide attempts had lower empathic accuracy and smaller temporal pole volumes. Empathic accuracy and temporal pole volumes were significantly associated with suicide attempts independent of other risk variables. The results indicate that brain and behavioral correlates of social cognition may add incremental value to models of suicide risk. © The Author (2017). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Socio-neuro risk factors for suicidal behavior in criminal offenders with psychotic disorders

PubMed Central

Brook, Michael; Kosson, David S.; Bustillo, Juan R.; Harenski, Keith A.; Caldwell, Michael F.; Van Rybroek, Gregory J.; Koenigs, Michael; Decety, Jean; Thornton, David M.; Calhoun, Vince D.; Kiehl, Kent A.

2017-01-01

Abstract Relative to the general population, individuals with psychotic disorders have a higher risk of suicide. Suicide risk is also elevated in criminal offenders. Thus, psychotic-disordered individuals with antisocial tendencies may form an especially high-risk group. We built upon prior risk analyses by examining whether neurobehavioral correlates of social cognition were associated with suicidal behavior in criminal offenders with psychotic disorders. We assessed empathic accuracy and brain structure in four groups: (i) incarcerated offenders with psychotic disorders and past suicide attempts, (ii) incarcerated offenders with psychotic disorders and no suicide attempts, (iii) incarcerated offenders without psychotic disorders and (iv) community non-offenders without psychotic disorders. Established suicide risk variables were examined along with empathic accuracy and gray matter in brain regions implicated in social cognition. Relative to the other groups, offenders with psychotic disorders and suicide attempts had lower empathic accuracy and smaller temporal pole volumes. Empathic accuracy and temporal pole volumes were significantly associated with suicide attempts independent of other risk variables. The results indicate that brain and behavioral correlates of social cognition may add incremental value to models of suicide risk. PMID:28065894

Measuring water level in rivers and lakes from lightweight Unmanned Aerial Vehicles

NASA Astrophysics Data System (ADS)

Bandini, Filippo; Jakobsen, Jakob; Olesen, Daniel; Reyna-Gutierrez, Jose Antonio; Bauer-Gottwein, Peter

2017-05-01

The assessment of hydrologic dynamics in rivers, lakes, reservoirs and wetlands requires measurements of water level, its temporal and spatial derivatives, and the extent and dynamics of open water surfaces. Motivated by the declining number of ground-based measurement stations, research efforts have been devoted to the retrieval of these hydraulic properties from spaceborne platforms in the past few decades. However, due to coarse spatial and temporal resolutions, spaceborne missions have several limitations when assessing the water level of terrestrial surface water bodies and determining complex water dynamics. Unmanned Aerial Vehicles (UAVs) can fill the gap between spaceborne and ground-based observations, and provide high spatial resolution and dense temporal coverage data, in quick turn-around time, using flexible payload design. This study focused on categorizing and testing sensors, which comply with the weight constraint of small UAVs (around 1.5 kg), capable of measuring the range to water surface. Subtracting the measured range from the vertical position retrieved by the onboard Global Navigation Satellite System (GNSS) receiver, we can determine the water level (orthometric height). Three different ranging payloads, which consisted of a radar, a sonar and an in-house developed camera-based laser distance sensor (CLDS), have been evaluated in terms of accuracy, precision, maximum ranging distance and beam divergence. After numerous flights, the relative accuracy of the overall system was estimated. A ranging accuracy better than 0.5% of the range and a maximum ranging distance of 60 m were achieved with the radar. The CLDS showed the lowest beam divergence, which is required to avoid contamination of the signal from interfering surroundings for narrow fields of view. With the GNSS system delivering a relative vertical accuracy better than 3-5 cm, water level can be retrieved with an overall accuracy better than 5-7 cm.

Feasibility Analysis of DEM Differential Method on Tree Height Assessment wit Terra-SAR/TanDEM-X Data

NASA Astrophysics Data System (ADS)

Zhang, Wangfei; Chen, Erxue; Li, Zengyuan; Feng, Qi; Zhao, Lei

2016-08-01

DEM Differential Method is an effective and efficient way for forest tree height assessment with Polarimetric and interferometric technology, however, the assessment accuracy of it is based on the accuracy of interferometric results and DEM. Terra-SAR/TanDEM-X, which established the first spaceborne bistatic interferometer, can provide highly accurate cross-track interferometric images in the whole global without inherent accuracy limitations like temporal decorrelation and atmospheric disturbance. These characters of Terra-SAR/TandDEM-X give great potential for global or regional tree height assessment, which have been constraint by the temporal decorrelation in traditional repeat-pass interferometry. Currently, in China, it will be costly to collect high accurate DEM with Lidar. At the same time, it is also difficult to get truly representative ground survey samples to test and verify the assessment results. In this paper, we analyzed the feasibility of using TerraSAR/TanDEM-X data to assess forest tree height with current free DEM data like ASTER-GDEM and archived ground in-suit data like forest management inventory data (FMI). At first, the accuracy and of ASTER-GDEM and forest management inventory data had been assessment according to the DEM and canopy height model (CHM) extracted from Lidar data. The results show the average elevation RMSE between ASTER-GEDM and Lidar-DEM is about 13 meters, but they have high correlation with the correlation coefficient of 0.96. With a linear regression model, we can compensate ASTER-GDEM and improve its accuracy nearly to the Lidar-DEM with same scale. The correlation coefficient between FMI and CHM is 0.40. its accuracy is able to be improved by a linear regression model withinconfidence intervals of 95%. After compensation of ASTER-GDEM and FMI, we calculated the tree height in Mengla test site with DEM Differential Method. The results showed that the corrected ASTER-GDEM can effectively improve the assessment accuracy. The average assessment accuracy before and after corrected is 0.73 and 0.76, the RMSE is 5.5 and 4.4, respectively.

Calibrating a numerical model's morphology using high-resolution spatial and temporal datasets from multithread channel flume experiments.

NASA Astrophysics Data System (ADS)

Javernick, L.; Bertoldi, W.; Redolfi, M.

2017-12-01

Accessing or acquiring high quality, low-cost topographic data has never been easier due to recent developments of the photogrammetric techniques of Structure-from-Motion (SfM). Researchers can acquire the necessary SfM imagery with various platforms, with the ability to capture millimetre resolution and accuracy, or large-scale areas with the help of unmanned platforms. Such datasets in combination with numerical modelling have opened up new opportunities to study river environments physical and ecological relationships. While numerical models overall predictive accuracy is most influenced by topography, proper model calibration requires hydraulic data and morphological data; however, rich hydraulic and morphological datasets remain scarce. This lack in field and laboratory data has limited model advancement through the inability to properly calibrate, assess sensitivity, and validate the models performance. However, new time-lapse imagery techniques have shown success in identifying instantaneous sediment transport in flume experiments and their ability to improve hydraulic model calibration. With new capabilities to capture high resolution spatial and temporal datasets of flume experiments, there is a need to further assess model performance. To address this demand, this research used braided river flume experiments and captured time-lapse observed sediment transport and repeat SfM elevation surveys to provide unprecedented spatial and temporal datasets. Through newly created metrics that quantified observed and modeled activation, deactivation, and bank erosion rates, the numerical model Delft3d was calibrated. This increased temporal data of both high-resolution time series and long-term temporal coverage provided significantly improved calibration routines that refined calibration parameterization. Model results show that there is a trade-off between achieving quantitative statistical and qualitative morphological representations. Specifically, statistical agreement simulations suffered to represent braiding planforms (evolving toward meandering), and parameterization that ensured braided produced exaggerated activation and bank erosion rates. Marie Sklodowska-Curie Individual Fellowship: River-HMV, 656917

Exploring the time course of face matching: temporal constraints impair unfamiliar face identification under temporally unconstrained viewing.

PubMed

Ozbek, Müge; Bindemann, Markus

2011-10-01

The identification of unfamiliar faces has been studied extensively with matching tasks, in which observers decide if pairs of photographs depict the same person (identity matches) or different people (mismatches). In experimental studies in this field, performance is usually self-paced under the assumption that this will encourage best-possible accuracy. Here, we examined the temporal characteristics of this task by limiting display times and tracking observers' eye movements. Observers were required to make match/mismatch decisions to pairs of faces shown for 200, 500, 1000, or 2000ms, or for an unlimited duration. Peak accuracy was reached within 2000ms and two fixations to each face. However, intermixing exposure conditions produced a context effect that generally reduced accuracy on identity mismatch trials, even when unlimited viewing of faces was possible. These findings indicate that less than 2s are required for face matching when exposure times are variable, but temporal constraints should be avoided altogether if accuracy is truly paramount. The implications of these findings are discussed. Copyright © 2011 Elsevier Ltd. All rights reserved.

Agent-based Large-Scale Emergency Evacuation Using Real-Time Open Government Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lu, Wei; Liu, Cheng; Bhaduri, Budhendra L

The open government initiatives have provided tremendous data resources for the transportation system and emergency services in urban areas. This paper proposes a traffic simulation framework using high temporal resolution demographic data and real time open government data for evacuation planning and operation. A comparison study using real-world data in Seattle, Washington is conducted to evaluate the framework accuracy and evacuation efficiency. The successful simulations of selected area prove the concept to take advantage open government data, open source data, and high resolution demographic data in emergency management domain. There are two aspects of parameters considered in this study: usermore » equilibrium (UE) conditions of traffic assignment model (simple Non-UE vs. iterative UE) and data temporal resolution (Daytime vs. Nighttime). Evacuation arrival rate, average travel time, and computation time are adopted as Measure of Effectiveness (MOE) for evacuation performance analysis. The temporal resolution of demographic data has significant impacts on urban transportation dynamics during evacuation scenarios. Better evacuation performance estimation can be approached by integrating both Non-UE and UE scenarios. The new framework shows flexibility in implementing different evacuation strategies and accuracy in evacuation performance. The use of this framework can be explored to day-to-day traffic assignment to support daily traffic operations.« less

Video quality assessment using motion-compensated temporal filtering and manifold feature similarity

PubMed Central

Yu, Mei; Jiang, Gangyi; Shao, Feng; Peng, Zongju

2017-01-01

Well-performed Video quality assessment (VQA) method should be consistent with human visual systems for better prediction accuracy. In this paper, we propose a VQA method using motion-compensated temporal filtering (MCTF) and manifold feature similarity. To be more specific, a group of frames (GoF) is first decomposed into a temporal high-pass component (HPC) and a temporal low-pass component (LPC) by MCTF. Following this, manifold feature learning (MFL) and phase congruency (PC) are used to predict the quality of temporal LPC and temporal HPC respectively. The quality measures of the LPC and the HPC are then combined as GoF quality. A temporal pooling strategy is subsequently used to integrate GoF qualities into an overall video quality. The proposed VQA method appropriately processes temporal information in video by MCTF and temporal pooling strategy, and simulate human visual perception by MFL. Experiments on publicly available video quality database showed that in comparison with several state-of-the-art VQA methods, the proposed VQA method achieves better consistency with subjective video quality and can predict video quality more accurately. PMID:28445489

High precise measurements of cosmogenic radiocarbon abundance by complex of scintillation equipments

NASA Technical Reports Server (NTRS)

Kocharov, G. E.; Metskvarishvili, R. Y.; Tsereteli, S. L.

1985-01-01

The main characteristics of scintillation equipments which enable the measurements of radiocarbon content with high accuracy of 0.2 to 0.3% were considered. The complex of scintillation devices operated very well for the last 15 years and allowed the investigation of the temporal variation of solar activity and intensity of cosmic rays for the last 300 years.

The value of crossdating to retain high-frequency variability, climate signals, and extreme events in environmental proxies

Treesearch

Bryan A. Black; Daniel Griffin; Peter van der Sleen; Alan D. Wanamaker; James H. Speer; David C. Frank; David W. Stahle; Neil Pederson; Carolyn A. Copenheaver; Valerie Trouet; Shelly Griffin; Bronwyn M. Gillanders

2016-01-01

High-resolution biogenic and geologic proxies in which one increment or layer is formed per year are crucial to describing natural ranges of environmental variability in Earth's physical and biological systems. However, dating controls are necessary to ensure temporal precision and accuracy; simple counts cannot ensure that all layers are placed correctly in time...

Sensitivity of chemical transport model simulations to the duration of chemical and transport operators: a case study with GEOS-Chem v10-01

NASA Astrophysics Data System (ADS)

Philip, S.; Martin, R. V.; Keller, C. A.

2015-11-01

Chemical transport models involve considerable computational expense. Fine temporal resolution offers accuracy at the expense of computation time. Assessment is needed of the sensitivity of simulation accuracy to the duration of chemical and transport operators. We conduct a series of simulations with the GEOS-Chem chemical transport model at different temporal and spatial resolutions to examine the sensitivity of simulated atmospheric composition to temporal resolution. Subsequently, we compare the tracers simulated with operator durations from 10 to 60 min as typically used by global chemical transport models, and identify the timesteps that optimize both computational expense and simulation accuracy. We found that longer transport timesteps increase concentrations of emitted species such as nitrogen oxides and carbon monoxide since a more homogeneous distribution reduces loss through chemical reactions and dry deposition. The increased concentrations of ozone precursors increase ozone production at longer transport timesteps. Longer chemical timesteps decrease sulfate and ammonium but increase nitrate due to feedbacks with in-cloud sulfur dioxide oxidation and aerosol thermodynamics. The simulation duration decreases by an order of magnitude from fine (5 min) to coarse (60 min) temporal resolution. We assess the change in simulation accuracy with resolution by comparing the root mean square difference in ground-level concentrations of nitrogen oxides, ozone, carbon monoxide and secondary inorganic aerosols with a finer temporal or spatial resolution taken as truth. Simulation error for these species increases by more than a factor of 5 from the shortest (5 min) to longest (60 min) temporal resolution. Chemical timesteps twice that of the transport timestep offer more simulation accuracy per unit computation. However, simulation error from coarser spatial resolution generally exceeds that from longer timesteps; e.g. degrading from 2° × 2.5° to 4° × 5° increases error by an order of magnitude. We recommend prioritizing fine spatial resolution before considering different temporal resolutions in offline chemical transport models. We encourage the chemical transport model users to specify in publications the durations of operators due to their effects on simulation accuracy.

Object Manifold Alignment for Multi-Temporal High Resolution Remote Sensing Images Classification

NASA Astrophysics Data System (ADS)

Gao, G.; Zhang, M.; Gu, Y.

2017-05-01

Multi-temporal remote sensing images classification is very useful for monitoring the land cover changes. Traditional approaches in this field mainly face to limited labelled samples and spectral drift of image information. With spatial resolution improvement, "pepper and salt" appears and classification results will be effected when the pixelwise classification algorithms are applied to high-resolution satellite images, in which the spatial relationship among the pixels is ignored. For classifying the multi-temporal high resolution images with limited labelled samples, spectral drift and "pepper and salt" problem, an object-based manifold alignment method is proposed. Firstly, multi-temporal multispectral images are cut to superpixels by simple linear iterative clustering (SLIC) respectively. Secondly, some features obtained from superpixels are formed as vector. Thirdly, a majority voting manifold alignment method aiming at solving high resolution problem is proposed and mapping the vector data to alignment space. At last, all the data in the alignment space are classified by using KNN method. Multi-temporal images from different areas or the same area are both considered in this paper. In the experiments, 2 groups of multi-temporal HR images collected by China GF1 and GF2 satellites are used for performance evaluation. Experimental results indicate that the proposed method not only has significantly outperforms than traditional domain adaptation methods in classification accuracy, but also effectively overcome the problem of "pepper and salt".

Improving the spatial and temporal resolution with quantification of uncertainty and errors in earth observation data sets using Data Interpolating Empirical Orthogonal Functions methodology

NASA Astrophysics Data System (ADS)

El Serafy, Ghada; Gaytan Aguilar, Sandra; Ziemba, Alexander

2016-04-01

There is an increasing use of process-based models in the investigation of ecological systems and scenario predictions. The accuracy and quality of these models are improved when run with high spatial and temporal resolution data sets. However, ecological data can often be difficult to collect which manifests itself through irregularities in the spatial and temporal domain of these data sets. Through the use of Data INterpolating Empirical Orthogonal Functions(DINEOF) methodology, earth observation products can be improved to have full spatial coverage within the desired domain as well as increased temporal resolution to daily and weekly time step, those frequently required by process-based models[1]. The DINEOF methodology results in a degree of error being affixed to the refined data product. In order to determine the degree of error introduced through this process, the suspended particulate matter and chlorophyll-a data from MERIS is used with DINEOF to produce high resolution products for the Wadden Sea. These new data sets are then compared with in-situ and other data sources to determine the error. Also, artificial cloud cover scenarios are conducted in order to substantiate the findings from MERIS data experiments. Secondly, the accuracy of DINEOF is explored to evaluate the variance of the methodology. The degree of accuracy is combined with the overall error produced by the methodology and reported in an assessment of the quality of DINEOF when applied to resolution refinement of chlorophyll-a and suspended particulate matter in the Wadden Sea. References [1] Sirjacobs, D.; Alvera-Azcárate, A.; Barth, A.; Lacroix, G.; Park, Y.; Nechad, B.; Ruddick, K.G.; Beckers, J.-M. (2011). Cloud filling of ocean colour and sea surface temperature remote sensing products over the Southern North Sea by the Data Interpolating Empirical Orthogonal Functions methodology. J. Sea Res. 65(1): 114-130. Dx.doi.org/10.1016/j.seares.2010.08.002

Configuration optimization and experimental accuracy evaluation of a bone-attached, parallel robot for skull surgery.

PubMed

Kobler, Jan-Philipp; Nuelle, Kathrin; Lexow, G Jakob; Rau, Thomas S; Majdani, Omid; Kahrs, Lueder A; Kotlarski, Jens; Ortmaier, Tobias

2016-03-01

Minimally invasive cochlear implantation is a novel surgical technique which requires highly accurate guidance of a drilling tool along a trajectory from the mastoid surface toward the basal turn of the cochlea. The authors propose a passive, reconfigurable, parallel robot which can be directly attached to bone anchors implanted in a patient's skull, avoiding the need for surgical tracking systems. Prior to clinical trials, methods are necessary to patient specifically optimize the configuration of the mechanism with respect to accuracy and stability. Furthermore, the achievable accuracy has to be determined experimentally. A comprehensive error model of the proposed mechanism is established, taking into account all relevant error sources identified in previous studies. Two optimization criteria to exploit the given task redundancy and reconfigurability of the passive robot are derived from the model. The achievable accuracy of the optimized robot configurations is first estimated with the help of a Monte Carlo simulation approach and finally evaluated in drilling experiments using synthetic temporal bone specimen. Experimental results demonstrate that the bone-attached mechanism exhibits a mean targeting accuracy of [Formula: see text] mm under realistic conditions. A systematic targeting error is observed, which indicates that accurate identification of the passive robot's kinematic parameters could further reduce deviations from planned drill trajectories. The accuracy of the proposed mechanism demonstrates its suitability for minimally invasive cochlear implantation. Future work will focus on further evaluation experiments on temporal bone specimen.

Spatial and temporal accuracy of asynchrony-tolerant finite difference schemes for partial differential equations at extreme scales

NASA Astrophysics Data System (ADS)

Kumari, Komal; Donzis, Diego

2017-11-01

Highly resolved computational simulations on massively parallel machines are critical in understanding the physics of a vast number of complex phenomena in nature governed by partial differential equations. Simulations at extreme levels of parallelism present many challenges with communication between processing elements (PEs) being a major bottleneck. In order to fully exploit the computational power of exascale machines one needs to devise numerical schemes that relax global synchronizations across PEs. This asynchronous computations, however, have a degrading effect on the accuracy of standard numerical schemes.We have developed asynchrony-tolerant (AT) schemes that maintain order of accuracy despite relaxed communications. We show, analytically and numerically, that these schemes retain their numerical properties with multi-step higher order temporal Runge-Kutta schemes. We also show that for a range of optimized parameters,the computation time and error for AT schemes is less than their synchronous counterpart. Stability of the AT schemes which depends upon history and random nature of delays, are also discussed. Support from NSF is gratefully acknowledged.

Joint inversion for transponder localization and sound-speed profile temporal variation in high-precision acoustic surveys.

PubMed

Li, Zhao; Dosso, Stan E; Sun, Dajun

2016-07-01

This letter develops a Bayesian inversion for localizing underwater acoustic transponders using a surface ship which compensates for sound-speed profile (SSP) temporal variation during the survey. The method is based on dividing observed acoustic travel-time data into time segments and including depth-independent SSP variations for each segment as additional unknown parameters to approximate the SSP temporal variation. SSP variations are estimated jointly with transponder locations, rather than calculated separately as in existing two-step inversions. Simulation and sea-trial results show this localization/SSP joint inversion performs better than two-step inversion in terms of localization accuracy, agreement with measured SSP variations, and computational efficiency.

Entropy of space-time outcome in a movement speed-accuracy task.

PubMed

Hsieh, Tsung-Yu; Pacheco, Matheus Maia; Newell, Karl M

2015-12-01

The experiment reported was set-up to investigate the space-time entropy of movement outcome as a function of a range of spatial (10, 20 and 30 cm) and temporal (250-2500 ms) criteria in a discrete aiming task. The variability and information entropy of the movement spatial and temporal errors considered separately increased and decreased on the respective dimension as a function of an increment of movement velocity. However, the joint space-time entropy was lowest when the relative contribution of spatial and temporal task criteria was comparable (i.e., mid-range of space-time constraints), and it increased with a greater trade-off between spatial or temporal task demands, revealing a U-shaped function across space-time task criteria. The traditional speed-accuracy functions of spatial error and temporal error considered independently mapped to this joint space-time U-shaped entropy function. The trade-off in movement tasks with joint space-time criteria is between spatial error and timing error, rather than movement speed and accuracy. Copyright © 2015 Elsevier B.V. All rights reserved.

A fully-implicit high-order system thermal-hydraulics model for advanced non-LWR safety analyses

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hu, Rui

An advanced system analysis tool is being developed for advanced reactor safety analysis. This paper describes the underlying physics and numerical models used in the code, including the governing equations, the stabilization schemes, the high-order spatial and temporal discretization schemes, and the Jacobian Free Newton Krylov solution method. The effects of the spatial and temporal discretization schemes are investigated. Additionally, a series of verification test problems are presented to confirm the high-order schemes. Furthermore, it is demonstrated that the developed system thermal-hydraulics model can be strictly verified with the theoretical convergence rates, and that it performs very well for amore » wide range of flow problems with high accuracy, efficiency, and minimal numerical diffusions.« less

A fully-implicit high-order system thermal-hydraulics model for advanced non-LWR safety analyses

DOE PAGES

Hu, Rui

2016-11-19

An advanced system analysis tool is being developed for advanced reactor safety analysis. This paper describes the underlying physics and numerical models used in the code, including the governing equations, the stabilization schemes, the high-order spatial and temporal discretization schemes, and the Jacobian Free Newton Krylov solution method. The effects of the spatial and temporal discretization schemes are investigated. Additionally, a series of verification test problems are presented to confirm the high-order schemes. Furthermore, it is demonstrated that the developed system thermal-hydraulics model can be strictly verified with the theoretical convergence rates, and that it performs very well for amore » wide range of flow problems with high accuracy, efficiency, and minimal numerical diffusions.« less

Locating the source of spreading in temporal networks

NASA Astrophysics Data System (ADS)

Huang, Qiangjuan; Zhao, Chengli; Zhang, Xue; Yi, Dongyun

2017-02-01

The topological structure of many real networks changes with time. Thus, locating the sources of a temporal network is a creative and challenging problem, as the enormous size of many real networks makes it unfeasible to observe the state of all nodes. In this paper, we propose an algorithm to solve this problem, named the backward temporal diffusion process. The proposed algorithm calculates the shortest temporal distance to locate the transmission source. We assume that the spreading process can be modeled as a simple diffusion process and by consensus dynamics. To improve the location accuracy, we also adopt four strategies to select which nodes should be observed by ranking their importance in the temporal network. Our paper proposes a highly accurate method for locating the source in temporal networks and is, to the best of our knowledge, a frontier work in this field. Moreover, our framework has important significance for controlling the transmission of diseases or rumors and formulating immediate immunization strategies.

Establishing nursery estuary otolith geochemical tags for Sea Bass (Dicentrarchus labrax): Is temporal stability estuary dependent?

NASA Astrophysics Data System (ADS)

Ryan, Diarmuid; Wögerbauer, Ciara; Roche, William

2016-12-01

The ability to determine connectivity between juveniles in nursery estuaries and adult populations is an important tool for fisheries management. Otoliths of juvenile fish contain geochemical tags, which reflect the variation in estuarine elemental chemistry, and allow discrimination of their natal and/or nursery estuaries. These tags can be used to investigate connectivity patterns between juveniles and adults. However, inter-annual variability of geochemical tags may limit the accuracy of nursery origin determinations. Otolith elemental composition was used to assign a single cohort of 0-group sea bass Dicentrarchus labrax to their nursery estuary thus establishing an initial baseline for stocks in waters around Ireland. Using a standard LDFA model, high classification accuracies to nursery sites (80-88%) were obtained. Temporal stability of otolith geochemical tags was also investigated to assess if annual sampling is required for connectivity studies. Geochemical tag stability was found to be strongly estuary dependent.

Word pair classification during imagined speech using direct brain recordings

NASA Astrophysics Data System (ADS)

Martin, Stephanie; Brunner, Peter; Iturrate, Iñaki; Millán, José Del R.; Schalk, Gerwin; Knight, Robert T.; Pasley, Brian N.

2016-05-01

People that cannot communicate due to neurological disorders would benefit from an internal speech decoder. Here, we showed the ability to classify individual words during imagined speech from electrocorticographic signals. In a word imagery task, we used high gamma (70-150 Hz) time features with a support vector machine model to classify individual words from a pair of words. To account for temporal irregularities during speech production, we introduced a non-linear time alignment into the SVM kernel. Classification accuracy reached 88% in a two-class classification framework (50% chance level), and average classification accuracy across fifteen word-pairs was significant across five subjects (mean = 58% p < 0.05). We also compared classification accuracy between imagined speech, overt speech and listening. As predicted, higher classification accuracy was obtained in the listening and overt speech conditions (mean = 89% and 86%, respectively; p < 0.0001), where speech stimuli were directly presented. The results provide evidence for a neural representation for imagined words in the temporal lobe, frontal lobe and sensorimotor cortex, consistent with previous findings in speech perception and production. These data represent a proof of concept study for basic decoding of speech imagery, and delineate a number of key challenges to usage of speech imagery neural representations for clinical applications.

Word pair classification during imagined speech using direct brain recordings

PubMed Central

Martin, Stephanie; Brunner, Peter; Iturrate, Iñaki; Millán, José del R.; Schalk, Gerwin; Knight, Robert T.; Pasley, Brian N.

2016-01-01

People that cannot communicate due to neurological disorders would benefit from an internal speech decoder. Here, we showed the ability to classify individual words during imagined speech from electrocorticographic signals. In a word imagery task, we used high gamma (70–150 Hz) time features with a support vector machine model to classify individual words from a pair of words. To account for temporal irregularities during speech production, we introduced a non-linear time alignment into the SVM kernel. Classification accuracy reached 88% in a two-class classification framework (50% chance level), and average classification accuracy across fifteen word-pairs was significant across five subjects (mean = 58%; p < 0.05). We also compared classification accuracy between imagined speech, overt speech and listening. As predicted, higher classification accuracy was obtained in the listening and overt speech conditions (mean = 89% and 86%, respectively; p < 0.0001), where speech stimuli were directly presented. The results provide evidence for a neural representation for imagined words in the temporal lobe, frontal lobe and sensorimotor cortex, consistent with previous findings in speech perception and production. These data represent a proof of concept study for basic decoding of speech imagery, and delineate a number of key challenges to usage of speech imagery neural representations for clinical applications. PMID:27165452

Logistic regression accuracy across different spatial and temporal scales for a wide-ranging species, the marbled murrelet

Treesearch

Carolyn B. Meyer; Sherri L. Miller; C. John Ralph

2004-01-01

The scale at which habitat variables are measured affects the accuracy of resource selection functions in predicting animal use of sites. We used logistic regression models for a wide-ranging species, the marbled murrelet, (Brachyramphus marmoratus) in a large region in California to address how much changing the spatial or temporal scale of...

Temporal Response Properties of Accessory Olfactory Bulb Neurons: Limitations and Opportunities for Decoding.

PubMed

Yoles-Frenkel, Michal; Kahan, Anat; Ben-Shaul, Yoram

2018-05-23

The vomeronasal system (VNS) is a major vertebrate chemosensory system that functions in parallel to the main olfactory system (MOS). Despite many similarities, the two systems dramatically differ in the temporal domain. While MOS responses are governed by breathing and follow a subsecond temporal scale, VNS responses are uncoupled from breathing and evolve over seconds. This suggests that the contribution of response dynamics to stimulus information will differ between these systems. While temporal dynamics in the MOS are widely investigated, similar analyses in the accessory olfactory bulb (AOB) are lacking. Here, we have addressed this issue using controlled stimulus delivery to the vomeronasal organ of male and female mice. We first analyzed the temporal properties of AOB projection neurons and demonstrated that neurons display prolonged, variable, and neuron-specific characteristics. We then analyzed various decoding schemes using AOB population responses. We showed that compared with the simplest scheme (i.e., integration of spike counts over the entire response period), the division of this period into smaller temporal bins actually yields poorer decoding accuracy. However, optimal classification accuracy can be achieved well before the end of the response period by integrating spike counts within temporally defined windows. Since VNS stimulus uptake is variable, we analyzed decoding using limited information about stimulus uptake time, and showed that with enough neurons, such time-invariant decoding is feasible. Finally, we conducted simulations that demonstrated that, unlike the main olfactory bulb, the temporal features of AOB neurons disfavor decoding with high temporal accuracy, and, rather, support decoding without precise knowledge of stimulus uptake time. SIGNIFICANCE STATEMENT A key goal in sensory system research is to identify which metrics of neuronal activity are relevant for decoding stimulus features. Here, we describe the first systematic analysis of temporal coding in the vomeronasal system (VNS), a chemosensory system devoted to socially relevant cues. Compared with the main olfactory system, timescales of VNS function are inherently slower and variable. Using various analyses of real and simulated data, we show that the consideration of response times relative to stimulus uptake can aid the decoding of stimulus information from neuronal activity. However, response properties of accessory olfactory bulb neurons favor decoding schemes that do not rely on the precise timing of stimulus uptake. Such schemes are consistent with the variable nature of VNS stimulus uptake. Copyright © 2018 the authors 0270-6474/18/384957-20$15.00/0.

Mapping paddy rice planting areas through time series analysis of MODIS land surface temperature and vegetation index data

PubMed Central

Zhang, Geli; Xiao, Xiangming; Dong, Jinwei; Kou, Weili; Jin, Cui; Qin, Yuanwei; Zhou, Yuting; Wang, Jie; Menarguez, Michael Angelo; Biradar, Chandrashekhar

2016-01-01

Knowledge of the area and spatial distribution of paddy rice is important for assessment of food security, management of water resources, and estimation of greenhouse gas (methane) emissions. Paddy rice agriculture has expanded rapidly in northeastern China in the last decade, but there are no updated maps of paddy rice fields in the region. Existing algorithms for identifying paddy rice fields are based on the unique physical features of paddy rice during the flooding and transplanting phases and use vegetation indices that are sensitive to the dynamics of the canopy and surface water content. However, the flooding phenomena in high latitude area could also be from spring snowmelt flooding. We used land surface temperature (LST) data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor to determine the temporal window of flooding and rice transplantation over a year to improve the existing phenology-based approach. Other land cover types (e.g., evergreen vegetation, permanent water bodies, and sparse vegetation) with potential influences on paddy rice identification were removed (masked out) due to their different temporal profiles. The accuracy assessment using high-resolution images showed that the resultant MODIS-derived paddy rice map of northeastern China in 2010 had a high accuracy (producer and user accuracies of 92% and 96%, respectively). The MODIS-based map also had a comparable accuracy to the 2010 Landsat-based National Land Cover Dataset (NLCD) of China in terms of both area and spatial pattern. This study demonstrated that our improved algorithm by using both thermal and optical MODIS data, provides a robust, simple and automated approach to identify and map paddy rice fields in temperate and cold temperate zones, the northern frontier of rice planting. PMID:27667901

Mapping paddy rice planting areas through time series analysis of MODIS land surface temperature and vegetation index data.

PubMed

Zhang, Geli; Xiao, Xiangming; Dong, Jinwei; Kou, Weili; Jin, Cui; Qin, Yuanwei; Zhou, Yuting; Wang, Jie; Menarguez, Michael Angelo; Biradar, Chandrashekhar

2015-08-01

Knowledge of the area and spatial distribution of paddy rice is important for assessment of food security, management of water resources, and estimation of greenhouse gas (methane) emissions. Paddy rice agriculture has expanded rapidly in northeastern China in the last decade, but there are no updated maps of paddy rice fields in the region. Existing algorithms for identifying paddy rice fields are based on the unique physical features of paddy rice during the flooding and transplanting phases and use vegetation indices that are sensitive to the dynamics of the canopy and surface water content. However, the flooding phenomena in high latitude area could also be from spring snowmelt flooding. We used land surface temperature (LST) data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor to determine the temporal window of flooding and rice transplantation over a year to improve the existing phenology-based approach. Other land cover types (e.g., evergreen vegetation, permanent water bodies, and sparse vegetation) with potential influences on paddy rice identification were removed (masked out) due to their different temporal profiles. The accuracy assessment using high-resolution images showed that the resultant MODIS-derived paddy rice map of northeastern China in 2010 had a high accuracy (producer and user accuracies of 92% and 96%, respectively). The MODIS-based map also had a comparable accuracy to the 2010 Landsat-based National Land Cover Dataset (NLCD) of China in terms of both area and spatial pattern. This study demonstrated that our improved algorithm by using both thermal and optical MODIS data, provides a robust, simple and automated approach to identify and map paddy rice fields in temperate and cold temperate zones, the northern frontier of rice planting.

Radiocarbon content in the annual tree rings during last 150 years and time variation of cosmic rays

NASA Technical Reports Server (NTRS)

Kocharov, G. E.; Metskvarishvili, R. Y.; Tsereteli, S. L.

1985-01-01

The results of the high accuracy measurements of radiocarbon abundance in precisely dated tree rings in the interval 1800 to 1950 yrs are discussed. Radiocarbon content caused by solar activity is established. The temporal dependence of cosmic rays is constructed, by use of radio abundance data.

High Frequency rTMS over the Left Parietal Lobule Increases Non-Word Reading Accuracy

ERIC Educational Resources Information Center

Costanzo, Floriana; Menghini, Deny; Caltagirone, Carlo; Oliveri, Massimiliano; Vicari, Stefano

2012-01-01

Increasing evidence in the literature supports the usefulness of Transcranial Magnetic Stimulation (TMS) in studying reading processes. Two brain regions are primarily involved in phonological decoding: the left superior temporal gyrus (STG), which is associated with the auditory representation of spoken words, and the left inferior parietal lobe…

Investigation of Portevin-Le Chatelier effect in 5456 Al-based alloy using digital image correlation

NASA Astrophysics Data System (ADS)

Cheng, Teng; Xu, Xiaohai; Cai, Yulong; Fu, Shihua; Gao, Yue; Su, Yong; Zhang, Yong; Zhang, Qingchuan

2015-02-01

A variety of experimental methods have been proposed for Portevin-Le Chatelier (PLC) effect. They mainly focused on the in-plane deformation. In order to achieve the high-accuracy measurement, three-dimensional digital image correlation (3D-DIC) was employed in this work to investigate the PLC effect in 5456 Al-based alloy. The temporal and spatial evolutions of deformation in the full field of specimen surface were observed. The large deformation of localized necking was determined experimentally. The distributions of out-of-plane displacement over the loading procedure were also obtained. Furthermore, a comparison of measurement accuracy between two-dimensional digital image correlation (2D-DIC) and 3D-DIC was also performed. Due to the theoretical restriction, the measurement accuracy of 2D-DIC decreases with the increase of deformation. A maximum discrepancy of about 20% with 3D-DIC was observed in this work. Therefore, 3D-DIC is actually more essential for the high-accuracy investigation of PLC effect.

Measurement configuration optimization for dynamic metrology using Stokes polarimetry

NASA Astrophysics Data System (ADS)

Liu, Jiamin; Zhang, Chuanwei; Zhong, Zhicheng; Gu, Honggang; Chen, Xiuguo; Jiang, Hao; Liu, Shiyuan

2018-05-01

As dynamic loading experiments such as a shock compression test are usually characterized by short duration, unrepeatability and high costs, high temporal resolution and precise accuracy of the measurements is required. Due to high temporal resolution up to a ten-nanosecond-scale, a Stokes polarimeter with six parallel channels has been developed to capture such instantaneous changes in optical properties in this paper. Since the measurement accuracy heavily depends on the configuration of the probing beam incident angle and the polarizer azimuth angle, it is important to select an optimal combination from the numerous options. In this paper, a systematic error propagation-based measurement configuration optimization method corresponding to the Stokes polarimeter was proposed. The maximal Frobenius norm of the combinatorial matrix of the configuration error propagating matrix and the intrinsic error propagating matrix is introduced to assess the measurement accuracy. The optimal configuration for thickness measurement of a SiO2 thin film deposited on a Si substrate has been achieved by minimizing the merit function. Simulation and experimental results show a good agreement between the optimal measurement configuration achieved experimentally using the polarimeter and the theoretical prediction. In particular, the experimental result shows that the relative error in the thickness measurement can be reduced from 6% to 1% by using the optimal polarizer azimuth angle when the incident angle is 45°. Furthermore, the optimal configuration for the dynamic metrology of a nickel foil under quasi-dynamic loading is investigated using the proposed optimization method.

DOE Office of Scientific and Technical Information (OSTI.GOV)

You, D; Aryal, M; Samuels, S

Purpose: A previous study showed that large sub-volumes of tumor with low blood volume (BV) (poorly perfused) in head-and-neck (HN) cancers are significantly associated with local-regional failure (LRF) after chemoradiation therapy, and could be targeted with intensified radiation doses. This study aimed to develop an automated and scalable model to extract voxel-wise contrast-enhanced temporal features of dynamic contrastenhanced (DCE) MRI in HN cancers for predicting LRF. Methods: Our model development consists of training and testing stages. The training stage includes preprocessing of individual-voxel DCE curves from tumors for intensity normalization and temporal alignment, temporal feature extraction from the curves, featuremore » selection, and training classifiers. For feature extraction, multiresolution Haar discrete wavelet transformation is applied to each DCE curve to capture temporal contrast-enhanced features. The wavelet coefficients as feature vectors are selected. Support vector machine classifiers are trained to classify tumor voxels having either low or high BV, for which a BV threshold of 7.6% is previously established and used as ground truth. The model is tested by a new dataset. The voxel-wise DCE curves for training and testing were from 14 and 8 patients, respectively. A posterior probability map of the low BV class was created to examine the tumor sub-volume classification. Voxel-wise classification accuracy was computed to evaluate performance of the model. Results: Average classification accuracies were 87.2% for training (10-fold crossvalidation) and 82.5% for testing. The lowest and highest accuracies (patient-wise) were 68.7% and 96.4%, respectively. Posterior probability maps of the low BV class showed the sub-volumes extracted by our model similar to ones defined by the BV maps with most misclassifications occurred near the sub-volume boundaries. Conclusion: This model could be valuable to support adaptive clinical trials with further validation. The framework could be extendable and scalable to extract temporal contrastenhanced features of DCE-MRI in other tumors. We would like to acknowledge NIH for funding support: UO1 CA183848.« less

A multi-temporal analysis approach for land cover mapping in support of nuclear incident response

NASA Astrophysics Data System (ADS)

Sah, Shagan; van Aardt, Jan A. N.; McKeown, Donald M.; Messinger, David W.

2012-06-01

Remote sensing can be used to rapidly generate land use maps for assisting emergency response personnel with resource deployment decisions and impact assessments. In this study we focus on constructing accurate land cover maps to map the impacted area in the case of a nuclear material release. The proposed methodology involves integration of results from two different approaches to increase classification accuracy. The data used included RapidEye scenes over Nine Mile Point Nuclear Power Station (Oswego, NY). The first step was building a coarse-scale land cover map from freely available, high temporal resolution, MODIS data using a time-series approach. In the case of a nuclear accident, high spatial resolution commercial satellites such as RapidEye or IKONOS can acquire images of the affected area. Land use maps from the two image sources were integrated using a probability-based approach. Classification results were obtained for four land classes - forest, urban, water and vegetation - using Euclidean and Mahalanobis distances as metrics. Despite the coarse resolution of MODIS pixels, acceptable accuracies were obtained using time series features. The overall accuracies using the fusion based approach were in the neighborhood of 80%, when compared with GIS data sets from New York State. The classifications were augmented using this fused approach, with few supplementary advantages such as correction for cloud cover and independence from time of year. We concluded that this method would generate highly accurate land maps, using coarse spatial resolution time series satellite imagery and a single date, high spatial resolution, multi-spectral image.

Mapping Crop Patterns in Central US Agricultural Systems from 2000 to 2014 Based on Landsat Data: To What Degree Does Fusing MODIS Data Improve Classification Accuracies?

NASA Astrophysics Data System (ADS)

Zhu, L.; Radeloff, V.; Ives, A. R.; Barton, B.

2015-12-01

Deriving crop pattern with high accuracy is of great importance for characterizing landscape diversity, which affects the resilience of food webs in agricultural systems in the face of climatic and land cover changes. Landsat sensors were originally designed to monitor agricultural areas, and both radiometric and spatial resolution are optimized for monitoring large agricultural fields. Unfortunately, few clear Landsat images per year are available, which has limited the use of Landsat for making crop classification, and this situation is worse in cloudy areas of the Earth. Meanwhile, the MODerate Resolution Imaging Spectroradiometer (MODIS) data has better temporal resolution but cannot capture fine spatial heterogeneity of agricultural systems. Our question was to what extent fusing imagery from both sensors could improve crop classifications. We utilized the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) algorithm to simulate Landsat-like images at MODIS temporal resolution. Based on Random Forests (RF) classifier, we tested whether and by what degree crop maps from 2000 to 2014 of the Arlington Agricultural Research Station (Wisconsin, USA) were improved by integrating available clear Landsat images each year with synthetic images. We predicted that the degree to which classification accuracy can be improved by incorporating synthetic imagery depends on the number and acquisition time of clear Landsat images. Moreover, multi-season data are essential for mapping crop types by capturing their phenological dynamics, and STARFM-simulated images can be used to compensate for missing Landsat observations. Our study is helpful for eliminating the limits of the use of Landsat data in mapping crop patterns, and can provide a benchmark of accuracy when choosing STARFM-simulated images to make crop classification at broader scales.

Fast depth decision for HEVC inter prediction based on spatial and temporal correlation

NASA Astrophysics Data System (ADS)

Chen, Gaoxing; Liu, Zhenyu; Ikenaga, Takeshi

2016-07-01

High efficiency video coding (HEVC) is a video compression standard that outperforms the predecessor H.264/AVC by doubling the compression efficiency. To enhance the compression accuracy, the partition sizes ranging is from 4x4 to 64x64 in HEVC. However, the manifold partition sizes dramatically increase the encoding complexity. This paper proposes a fast depth decision based on spatial and temporal correlation. Spatial correlation utilize the code tree unit (CTU) Splitting information and temporal correlation utilize the motion vector predictor represented CTU in inter prediction to determine the maximum depth in each CTU. Experimental results show that the proposed method saves about 29.1% of the original processing time with 0.9% of BD-bitrate increase on average.

Frontotemporal oxyhemoglobin dynamics predict performance accuracy of dance simulation gameplay: temporal characteristics of top-down and bottom-up cortical activities.

PubMed

Ono, Yumie; Nomoto, Yasunori; Tanaka, Shohei; Sato, Keisuke; Shimada, Sotaro; Tachibana, Atsumichi; Bronner, Shaw; Noah, J Adam

2014-01-15

We utilized the high temporal resolution of functional near-infrared spectroscopy to explore how sensory input (visual and rhythmic auditory cues) are processed in the cortical areas of multimodal integration to achieve coordinated motor output during unrestricted dance simulation gameplay. Using an open source clone of the dance simulation video game, Dance Dance Revolution, two cortical regions of interest were selected for study, the middle temporal gyrus (MTG) and the frontopolar cortex (FPC). We hypothesized that activity in the FPC would indicate top-down regulatory mechanisms of motor behavior; while that in the MTG would be sustained due to bottom-up integration of visual and auditory cues throughout the task. We also hypothesized that a correlation would exist between behavioral performance and the temporal patterns of the hemodynamic responses in these regions of interest. Results indicated that greater temporal accuracy of dance steps positively correlated with persistent activation of the MTG and with cumulative suppression of the FPC. When auditory cues were eliminated from the simulation, modifications in cortical responses were found depending on the gameplay performance. In the MTG, high-performance players showed an increase but low-performance players displayed a decrease in cumulative amount of the oxygenated hemoglobin response in the no music condition compared to that in the music condition. In the FPC, high-performance players showed relatively small variance in the activity regardless of the presence of auditory cues, while low-performance players showed larger differences in the activity between the no music and music conditions. These results suggest that the MTG plays an important role in the successful integration of visual and rhythmic cues and the FPC may work as top-down control to compensate for insufficient integrative ability of visual and rhythmic cues in the MTG. The relative relationships between these cortical areas indicated high- to low-performance levels when performing cued motor tasks. We propose that changes in these relationships can be monitored to gauge performance increases in motor learning and rehabilitation programs. Copyright © 2013 Elsevier Inc. All rights reserved.

Isolating Flow-field Discontinuities while Preserving Monotonicity and High-order Accuracy on Cartesian Meshes

DTIC Science & Technology

2017-01-09

2017 Distribution A – Approved for public release; Distribution Unlimited. PA Clearance 17030 Introduction • Filtering schemes offer a less...dissipative alternative to the standard artificial dissipation operators when applied to high- order spatial/temporal schemes • Limiting Fact: Filters impart...systems require a preconditioned dual-time framework to be solved efficiently • Limiting Fact: Filtering cannot be applied only at the physical- time

Regional Scale High Resolution δ18O Prediction in Precipitation Using MODIS EVI

PubMed Central

Huang, Cho-Ying; Wang, Chung-Ho; Lin, Shou-De; Lo, Yi-Chen; Huang, Bo-Wen; Hatch, Kent A.; Shiu, Hau-Jie; You, Cheng-Feng; Chang, Yuan-Mou; Shen, Sheng-Feng

2012-01-01

The natural variation in stable water isotope ratio data, also known as water isoscape, is a spatiotemporal fingerprint and a powerful natural tracer that has been widely applied in disciplines as diverse as hydrology, paleoclimatology, ecology and forensic investigation. Although much effort has been devoted to developing a predictive water isoscape model, it remains a central challenge for scientists to generate high accuracy, fine scale spatiotemporal water isoscape prediction. Here we develop a novel approach of using the MODIS-EVI (the Moderate Resolution Imagining Spectroradiometer-Enhanced Vegetation Index), to predict δ18O in precipitation at the regional scale. Using a structural equation model, we show that the EVI and precipitated δ18O are highly correlated and thus the EVI is a good predictor of precipitated δ18O. We then test the predictability of our EVI-δ18O model and demonstrate that our approach can provide high accuracy with fine spatial (250×250 m) and temporal (16 days) scale δ18O predictions (annual and monthly predictabilities [r] are 0.96 and 0.80, respectively). We conclude the merging of the EVI and δ18O in precipitation can greatly extend the spatial and temporal data availability and thus enhance the applicability for both the EVI and water isoscape. PMID:23029053

Multi-source remotely sensed data fusion for improving land cover classification

NASA Astrophysics Data System (ADS)

Chen, Bin; Huang, Bo; Xu, Bing

2017-02-01

Although many advances have been made in past decades, land cover classification of fine-resolution remotely sensed (RS) data integrating multiple temporal, angular, and spectral features remains limited, and the contribution of different RS features to land cover classification accuracy remains uncertain. We proposed to improve land cover classification accuracy by integrating multi-source RS features through data fusion. We further investigated the effect of different RS features on classification performance. The results of fusing Landsat-8 Operational Land Imager (OLI) data with Moderate Resolution Imaging Spectroradiometer (MODIS), China Environment 1A series (HJ-1A), and Advanced Spaceborne Thermal Emission and Reflection (ASTER) digital elevation model (DEM) data, showed that the fused data integrating temporal, spectral, angular, and topographic features achieved better land cover classification accuracy than the original RS data. Compared with the topographic feature, the temporal and angular features extracted from the fused data played more important roles in classification performance, especially those temporal features containing abundant vegetation growth information, which markedly increased the overall classification accuracy. In addition, the multispectral and hyperspectral fusion successfully discriminated detailed forest types. Our study provides a straightforward strategy for hierarchical land cover classification by making full use of available RS data. All of these methods and findings could be useful for land cover classification at both regional and global scales.

The outlook for precipitation measurements from space

NASA Technical Reports Server (NTRS)

Atlas, D.; Eckerman, J.; Meneghini, R.; Moore, R. K.

1981-01-01

To provide useful precipitation measurements from space, two requirements must be met: adequate spatial and temporal sampling of the storm and sufficient accuracy in the estimate of precipitation intensity. Although presently no single instrument or method completely satisfies both requirements, the visible/IR, microwave radiometer and radar methods can be used in a complementary manner. Visible/IR instruments provide good temporal sampling and rain area depiction, but recourse must be made to microwave measurements for quantitative rainfall estimates. The inadequacy of microwave radiometer measurements over land suggests, in turn, the use of radar. Several recently developed attenuating-wavelength radar methods are discussed in terms of their accuracy, dynamic range and system implementation. Traditionally, the requirements of high resolution and adequate dynamic range led to fairly costly and complex radar systems. Some simplications and cost reduction can be made; however, by using K-band wavelengths which have the advantages of greater sensitivity at the low rain rates and higher resolution capabilities. Several recently proposed methods of this kind are reviewed in terms of accuracy and system implementation. Finally, an adaptive-pointing multi-sensor instrument is described that would exploit certain advantages of the IR, radiometric and radar methods.

Familiarity and Recollection Produce Distinct Eye Movement, Pupil and Medial Temporal Lobe Responses when Memory Strength Is Matched

ERIC Educational Resources Information Center

Kafkas, Alexandros; Montaldi, Daniela

2012-01-01

Two experiments explored eye measures (fixations and pupil response patterns) and brain responses (BOLD) accompanying the recognition of visual object stimuli based on familiarity and recollection. In both experiments, the use of a modified remember/know procedure led to high confidence and matched accuracy levels characterising strong familiarity…

Snow-covered Landsat time series stacks improve automated disturbance mapping accuracy in forested landscapes

Treesearch

Kirk M. Stueve; Ian W. Housman; Patrick L. Zimmerman; Mark D. Nelson; Jeremy B. Webb; Charles H. Perry; Robert A. Chastain; Dale D. Gormanson; Chengquan Huang; Sean P. Healey; Warren B. Cohen

2011-01-01

Accurate landscape-scale maps of forests and associated disturbances are critical to augment studies on biodiversity, ecosystem services, and the carbon cycle, especially in terms of understanding how the spatial and temporal complexities of damage sustained from disturbances influence forest structure and function. Vegetation change tracker (VCT) is a highly automated...

Tropical land use land cover mapping in Pará (Brazil) using discriminative Markov random fields and multi-temporal TerraSAR-X data

NASA Astrophysics Data System (ADS)

Hagensieker, Ron; Roscher, Ribana; Rosentreter, Johannes; Jakimow, Benjamin; Waske, Björn

2017-12-01

Remote sensing satellite data offer the unique possibility to map land use land cover transformations by providing spatially explicit information. However, detection of short-term processes and land use patterns of high spatial-temporal variability is a challenging task. We present a novel framework using multi-temporal TerraSAR-X data and machine learning techniques, namely discriminative Markov random fields with spatio-temporal priors, and import vector machines, in order to advance the mapping of land cover characterized by short-term changes. Our study region covers a current deforestation frontier in the Brazilian state Pará with land cover dominated by primary forests, different types of pasture land and secondary vegetation, and land use dominated by short-term processes such as slash-and-burn activities. The data set comprises multi-temporal TerraSAR-X imagery acquired over the course of the 2014 dry season, as well as optical data (RapidEye, Landsat) for reference. Results show that land use land cover is reliably mapped, resulting in spatially adjusted overall accuracies of up to 79% in a five class setting, yet limitations for the differentiation of different pasture types remain. The proposed method is applicable on multi-temporal data sets, and constitutes a feasible approach to map land use land cover in regions that are affected by high-frequent temporal changes.

Rod phototransduction determines the trade-off of temporal integration and speed of vision in dark-adapted toads.

PubMed

Haldin, Charlotte; Nymark, Soile; Aho, Ann-Christine; Koskelainen, Ari; Donner, Kristian

2009-05-06

Human vision is approximately 10 times less sensitive than toad vision on a cool night. Here, we investigate (1) how far differences in the capacity for temporal integration underlie such differences in sensitivity and (2) whether the response kinetics of the rod photoreceptors can explain temporal integration at the behavioral level. The toad was studied as a model that allows experimentation at different body temperatures. Sensitivity, integration time, and temporal accuracy of vision were measured psychophysically by recording snapping at worm dummies moving at different velocities. Rod photoresponses were studied by ERG recording across the isolated retina. In both types of experiments, the general timescale of vision was varied by using two temperatures, 15 and 25 degrees C. Behavioral integration times were 4.3 s at 15 degrees C and 0.9 s at 25 degrees C, and rod integration times were 4.2-4.3 s at 15 degrees C and 1.0-1.3 s at 25 degrees C. Maximal behavioral sensitivity was fivefold lower at 25 degrees C than at 15 degrees C, which can be accounted for by inability of the "warm" toads to integrate light over longer times than the rods. However, the long integration time at 15 degrees C, allowing high sensitivity, degraded the accuracy of snapping toward quickly moving worms. We conclude that temporal integration explains a considerable part of all variation in absolute visual sensitivity. The strong correlation between rods and behavior suggests that the integration time of dark-adapted vision is set by rod phototransduction at the input to the visual system. This implies that there is an inexorable trade-off between temporal integration and resolution.

Temporal optimisation of image acquisition for land cover classification with Random Forest and MODIS time-series

NASA Astrophysics Data System (ADS)

Nitze, Ingmar; Barrett, Brian; Cawkwell, Fiona

2015-02-01

The analysis and classification of land cover is one of the principal applications in terrestrial remote sensing. Due to the seasonal variability of different vegetation types and land surface characteristics, the ability to discriminate land cover types changes over time. Multi-temporal classification can help to improve the classification accuracies, but different constraints, such as financial restrictions or atmospheric conditions, may impede their application. The optimisation of image acquisition timing and frequencies can help to increase the effectiveness of the classification process. For this purpose, the Feature Importance (FI) measure of the state-of-the art machine learning method Random Forest was used to determine the optimal image acquisition periods for a general (Grassland, Forest, Water, Settlement, Peatland) and Grassland specific (Improved Grassland, Semi-Improved Grassland) land cover classification in central Ireland based on a 9-year time-series of MODIS Terra 16 day composite data (MOD13Q1). Feature Importances for each acquisition period of the Enhanced Vegetation Index (EVI) and Normalised Difference Vegetation Index (NDVI) were calculated for both classification scenarios. In the general land cover classification, the months December and January showed the highest, and July and August the lowest separability for both VIs over the entire nine-year period. This temporal separability was reflected in the classification accuracies, where the optimal choice of image dates outperformed the worst image date by 13% using NDVI and 5% using EVI on a mono-temporal analysis. With the addition of the next best image periods to the data input the classification accuracies converged quickly to their limit at around 8-10 images. The binary classification schemes, using two classes only, showed a stronger seasonal dependency with a higher intra-annual, but lower inter-annual variation. Nonetheless anomalous weather conditions, such as the cold winter of 2009/2010 can alter the temporal separability pattern significantly. Due to the extensive use of the NDVI for land cover discrimination, the findings of this study should be transferrable to data from other optical sensors with a higher spatial resolution. However, the high impact of outliers from the general climatic pattern highlights the limitation of spatial transferability to locations with different climatic and land cover conditions. The use of high-temporal, moderate resolution data such as MODIS in conjunction with machine-learning techniques proved to be a good base for the prediction of image acquisition timing for optimal land cover classification results.

A method for generating high resolution satellite image time series

NASA Astrophysics Data System (ADS)

Guo, Tao

2014-10-01

There is an increasing demand for satellite remote sensing data with both high spatial and temporal resolution in many applications. But it still is a challenge to simultaneously improve spatial resolution and temporal frequency due to the technical limits of current satellite observation systems. To this end, much R&D efforts have been ongoing for years and lead to some successes roughly in two aspects, one includes super resolution, pan-sharpen etc. methods which can effectively enhance the spatial resolution and generate good visual effects, but hardly preserve spectral signatures and result in inadequate analytical value, on the other hand, time interpolation is a straight forward method to increase temporal frequency, however it increase little informative contents in fact. In this paper we presented a novel method to simulate high resolution time series data by combing low resolution time series data and a very small number of high resolution data only. Our method starts with a pair of high and low resolution data set, and then a spatial registration is done by introducing LDA model to map high and low resolution pixels correspondingly. Afterwards, temporal change information is captured through a comparison of low resolution time series data, and then projected onto the high resolution data plane and assigned to each high resolution pixel according to the predefined temporal change patterns of each type of ground objects. Finally the simulated high resolution data is generated. A preliminary experiment shows that our method can simulate a high resolution data with a reasonable accuracy. The contribution of our method is to enable timely monitoring of temporal changes through analysis of time sequence of low resolution images only, and usage of costly high resolution data can be reduces as much as possible, and it presents a highly effective way to build up an economically operational monitoring solution for agriculture, forest, land use investigation, environment and etc. applications.

Dispersal and extrapolation on the accuracy of temporal predictions from distribution models for the Darwin's frog.

PubMed

Uribe-Rivera, David E; Soto-Azat, Claudio; Valenzuela-Sánchez, Andrés; Bizama, Gustavo; Simonetti, Javier A; Pliscoff, Patricio

2017-07-01

Climate change is a major threat to biodiversity; the development of models that reliably predict its effects on species distributions is a priority for conservation biogeography. Two of the main issues for accurate temporal predictions from Species Distribution Models (SDM) are model extrapolation and unrealistic dispersal scenarios. We assessed the consequences of these issues on the accuracy of climate-driven SDM predictions for the dispersal-limited Darwin's frog Rhinoderma darwinii in South America. We calibrated models using historical data (1950-1975) and projected them across 40 yr to predict distribution under current climatic conditions, assessing predictive accuracy through the area under the ROC curve (AUC) and True Skill Statistics (TSS), contrasting binary model predictions against temporal-independent validation data set (i.e., current presences/absences). To assess the effects of incorporating dispersal processes we compared the predictive accuracy of dispersal constrained models with no dispersal limited SDMs; and to assess the effects of model extrapolation on the predictive accuracy of SDMs, we compared this between extrapolated and no extrapolated areas. The incorporation of dispersal processes enhanced predictive accuracy, mainly due to a decrease in the false presence rate of model predictions, which is consistent with discrimination of suitable but inaccessible habitat. This also had consequences on range size changes over time, which is the most used proxy for extinction risk from climate change. The area of current climatic conditions that was absent in the baseline conditions (i.e., extrapolated areas) represents 39% of the study area, leading to a significant decrease in predictive accuracy of model predictions for those areas. Our results highlight (1) incorporating dispersal processes can improve predictive accuracy of temporal transference of SDMs and reduce uncertainties of extinction risk assessments from global change; (2) as geographical areas subjected to novel climates are expected to arise, they must be reported as they show less accurate predictions under future climate scenarios. Consequently, environmental extrapolation and dispersal processes should be explicitly incorporated to report and reduce uncertainties in temporal predictions of SDMs, respectively. Doing so, we expect to improve the reliability of the information we provide for conservation decision makers under future climate change scenarios. © 2017 by the Ecological Society of America.

Accuracy Assessment of Coastal Topography Derived from Uav Images

NASA Astrophysics Data System (ADS)

Long, N.; Millescamps, B.; Pouget, F.; Dumon, A.; Lachaussée, N.; Bertin, X.

2016-06-01

To monitor coastal environments, Unmanned Aerial Vehicle (UAV) is a low-cost and easy to use solution to enable data acquisition with high temporal frequency and spatial resolution. Compared to Light Detection And Ranging (LiDAR) or Terrestrial Laser Scanning (TLS), this solution produces Digital Surface Model (DSM) with a similar accuracy. To evaluate the DSM accuracy on a coastal environment, a campaign was carried out with a flying wing (eBee) combined with a digital camera. Using the Photoscan software and the photogrammetry process (Structure From Motion algorithm), a DSM and an orthomosaic were produced. Compared to GNSS surveys, the DSM accuracy is estimated. Two parameters are tested: the influence of the methodology (number and distribution of Ground Control Points, GCPs) and the influence of spatial image resolution (4.6 cm vs 2 cm). The results show that this solution is able to reproduce the topography of a coastal area with a high vertical accuracy (< 10 cm). The georeferencing of the DSM require a homogeneous distribution and a large number of GCPs. The accuracy is correlated with the number of GCPs (use 19 GCPs instead of 10 allows to reduce the difference of 4 cm); the required accuracy should be dependant of the research problematic. Last, in this particular environment, the presence of very small water surfaces on the sand bank does not allow to improve the accuracy when the spatial resolution of images is decreased.

Individual Patient Diagnosis of AD and FTD via High-Dimensional Pattern Classification of MRI

PubMed Central

Davatzikos, C.; Resnick, S. M.; Wu, X.; Parmpi, P.; Clark, C. M.

2008-01-01

The purpose of this study is to determine the diagnostic accuracy of MRI-based high-dimensional pattern classification in differentiating between patients with Alzheimer’s Disease (AD), Frontotemporal Dementia (FTD), and healthy controls, on an individual patient basis. MRI scans of 37 patients with AD and 37 age-matched cognitively normal elderly individuals, as well as 12 patients with FTD and 12 age-matched cognitively normal elderly individuals, were analyzed using voxel-based analysis and high-dimensional pattern classification. Diagnostic sensitivity and specificity of spatial patterns of regional brain atrophy found to be characteristic of AD and FTD were determined via cross-validation and via split-sample methods. Complex spatial patterns of relatively reduced brain volumes were identified, including temporal, orbitofrontal, parietal and cingulate regions, which were predominantly characteristic of either AD or FTD. These patterns provided 100% diagnostic accuracy, when used to separate AD or FTD from healthy controls. The ability to correctly distinguish AD from FTD averaged 84.3%. All estimates of diagnostic accuracy were determined via cross-validation. In conclusion, AD- and FTD-specific patterns of brain atrophy can be detected with high accuracy using high-dimensional pattern classification of MRI scans obtained in a typical clinical setting. PMID:18474436

Time perception of visual motion is tuned by the motor representation of human actions

PubMed Central

Gavazzi, Gioele; Bisio, Ambra; Pozzo, Thierry

2013-01-01

Several studies have shown that the observation of a rapidly moving stimulus dilates our perception of time. However, this effect appears to be at odds with the fact that our interactions both with environment and with each other are temporally accurate. This work exploits this paradox to investigate whether the temporal accuracy of visual motion uses motor representations of actions. To this aim, the stimuli were a dot moving with kinematics belonging or not to the human motor repertoire and displayed at different velocities. Participants had to replicate its duration with two tasks differing in the underlying motor plan. Results show that independently of the task's motor plan, the temporal accuracy and precision depend on the correspondence between the stimulus' kinematics and the observer's motor competencies. Our data suggest that the temporal mechanism of visual motion exploits a temporal visuomotor representation tuned by the motor knowledge of human actions. PMID:23378903

Intercepting moving targets: does memory from practice in a specific condition of target displacement affect movement timing?

PubMed

de Azevedo Neto, Raymundo Machado; Teixeira, Luis Augusto

2011-05-01

This investigation aimed at assessing the extent to which memory from practice in a specific condition of target displacement modulates temporal errors and movement timing of interceptive movements. We compared two groups practicing with certainty of future target velocity either in unchanged target velocity or in target velocity decrease. Following practice, both experimental groups were probed in the situations of unchanged target velocity and target velocity decrease either under the context of certainty or uncertainty about target velocity. Results from practice showed similar improvement of temporal accuracy between groups, revealing that target velocity decrease did not disturb temporal movement organization when fully predictable. Analysis of temporal errors in the probing trials indicated that both groups had higher timing accuracy in velocity decrease in comparison with unchanged velocity. Effect of practice was detected by increased temporal accuracy of the velocity decrease group in situations of decreased velocity; a trend consistent with the expected effect of practice was observed for temporal errors in the unchanged velocity group and in movement initiation at a descriptive level. An additional point of theoretical interest was the fast adaptation in both groups to a target velocity pattern different from that practiced. These points are discussed under the perspective of integration of vision and motor control by means of an internal forward model of external motion.

Forest fuel treatment detection using multi-temporal airborne Lidar data and high resolution aerial imagery ---- A case study at Sierra Nevada, California

NASA Astrophysics Data System (ADS)

Su, Y.; Guo, Q.; Collins, B.; Fry, D.; Kelly, M.

2014-12-01

Forest fuel treatments (FFT) are often employed in Sierra Nevada forest (located in California, US) to enhance forest health, regulate stand density, and reduce wildfire risk. However, there have been concerns that FFTs may have negative impacts on certain protected wildlife species. Due to the constraints and protection of resources (e.g., perennial streams, cultural resources, wildlife habitat, etc.), the actual FFT extents are usually different from planned extents. Identifying the actual extent of treated areas is of primary importance to understand the environmental influence of FFTs. Light detection and ranging (Lidar) is a powerful remote sensing technique that can provide accurate forest structure measurements, which provides great potential to monitor forest changes. This study used canopy height model (CHM) and canopy cover (CC) products derived from multi-temporal airborne Lidar data to detect FFTs by an approach combining a pixel-wise thresholding method and a object-of-interest segmentation method. We also investigated forest change following the implementation of landscape-scale FFT projects through the use of normalized difference vegetation index (NDVI) and standardized principle component analysis (PCA) from multi-temporal high resolution aerial imagery. The same FFT detection routine was applied on the Lidar data and aerial imagery for the purpose of comparing the capability of Lidar data and aerial imagery on FFT detection. Our results demonstrated that the FFT detection using Lidar derived CC products produced both the highest total accuracy and kappa coefficient, and was more robust at identifying areas with light FFTs. The accuracy using Lidar derived CHM products was significantly lower than that of the result using Lidar derived CC, but was still slightly higher than using aerial imagery. FFT detection results using NDVI and standardized PCA using multi-temporal aerial imagery produced almost identical total accuracy and kappa coefficient. Both methods showed relatively limited capacity to detect light FFT areas, and had higher false detection rate (recognized untreated areas as treated areas) compared to the methods using Lidar derived parameters.

Avulsion research using flume experiments and highly accurate and temporal-rich SfM datasets

NASA Astrophysics Data System (ADS)

Javernick, L.; Bertoldi, W.; Vitti, A.

2017-12-01

SfM's ability to produce high-quality, large-scale digital elevation models (DEMs) of complicated and rapidly evolving systems has made it a valuable technique for low-budget researchers and practitioners. While SfM has provided valuable datasets that capture single-flood event DEMs, there is an increasing scientific need to capture higher temporal resolution datasets that can quantify the evolutionary processes instead of pre- and post-flood snapshots. However, flood events' dangerous field conditions and image matching challenges (e.g. wind, rain) prevent quality SfM-image acquisition. Conversely, flume experiments offer opportunities to document flood events, but achieving consistent and accurate DEMs to detect subtle changes in dry and inundated areas remains a challenge for SfM (e.g. parabolic error signatures).This research aimed at investigating the impact of naturally occurring and manipulated avulsions on braided river morphology and on the encroachment of floodplain vegetation, using laboratory experiments. This required DEMs with millimeter accuracy and precision and at a temporal resolution to capture the processes. SfM was chosen as it offered the most practical method. Through redundant local network design and a meticulous ground control point (GCP) survey with a Leica Total Station in red laser configuration (reported 2 mm accuracy), the SfM residual errors compared to separate ground truthing data produced mean errors of 1.5 mm (accuracy) and standard deviations of 1.4 mm (precision) without parabolic error signatures. Lighting conditions in the flume were limited to uniform, oblique, and filtered LED strips, which removed glint and thus improved bed elevation mean errors to 4 mm, but errors were further reduced by means of an open source software for refraction correction. The obtained datasets have provided the ability to quantify how small flood events with avulsion can have similar morphologic and vegetation impacts as large flood events without avulsion. Further, this research highlights the potential application of SfM in the laboratory and ability to document physical and biological processes at greater spatial and temporal resolution. Marie Sklodowska-Curie Individual Fellowship: River-HMV, 656917

Retrieving high-resolution surface solar radiation with cloud parameters derived by combining MODIS and MTSAT data

NASA Astrophysics Data System (ADS)

Tang, W.; Qin, J.; Yang, K.; Liu, S.; Lu, N.; Niu, X.

2015-12-01

Cloud parameters (cloud mask, effective particle radius and liquid/ice water path) are the important inputs in determining surface solar radiation (SSR). These parameters can be derived from MODIS with high accuracy but their temporal resolution is too low to obtain high temporal resolution SSR retrievals. In order to obtain hourly cloud parameters, the Artificial Neural Network (ANN) is applied in this study to directly construct a functional relationship between MODIS cloud products and Multi-functional Transport Satellite (MTSAT) geostationary satellite signals. Meanwhile, an efficient parameterization model for SSR retrieval is introduced and, when driven with MODIS atmospheric and land products, its root mean square error (RMSE) is about 100 W m-2 for 44 Baseline Surface Radiation Network (BSRN) stations. Once the estimated cloud parameters and other information (such as aerosol, precipitable water, ozone and so on) are input to the model, we can derive SSR at high spatio-temporal resolution. The retrieved SSR is first evaluated against hourly radiation data at three experimental stations in the Haihe River Basin of China. The mean bias error (MBE) and RMSE in hourly SSR estimate are 12.0 W m-2 (or 3.5 %) and 98.5 W m-2 (or 28.9 %), respectively. The retrieved SSR is also evaluated against daily radiation data at 90 China Meteorological Administration (CMA) stations. The MBEs are 9.8 W m-2 (5.4 %); the RMSEs in daily and monthly-mean SSR estimates are 34.2 W m-2 (19.1 %) and 22.1 W m-2 (12.3 %), respectively. The accuracy is comparable or even higher than other two radiation products (GLASS and ISCCP-FD), and the present method is more computationally efficient and can produce hourly SSR data at a spatial resolution of 5 km.

Selective Attention in Pigeon Temporal Discrimination.

PubMed

Subramaniam, Shrinidhi; Kyonka, Elizabeth

2017-07-27

Cues can vary in how informative they are about when specific outcomes, such as food availability, will occur. This study was an experimental investigation of the functional relation between cue informativeness and temporal discrimination in a peak-interval (PI) procedure. Each session consisted of fixed-interval (FI) 2-s and 4-s schedules of food and occasional, 12-s PI trials during which pecks had no programmed consequences. Across conditions, the phi (ϕ) correlation between key light color and FI schedule value was manipulated. Red and green key lights signaled the onset of either or both FI schedules. Different colors were either predictive (ϕ = 1), moderately predictive (ϕ = 0.2-0.8), or not predictive (ϕ = 0) of a specific FI schedule. This study tested the hypothesis that temporal discrimination is a function of the momentary conditional probability of food; that is, pigeons peck the most at either 2 s or 4 s when ϕ = 1 and peck at both intervals when ϕ < 1. Response distributions were bimodal Gaussian curves; distributions from red- and green-key PI trials converged when ϕ ≤ 0.6. Peak times estimated by summed Gaussian functions, averaged across conditions and pigeons, were 1.85 s and 3.87 s, however, pigeons did not always maximize the momentary probability of food. When key light color was highly correlated with FI schedules (ϕ ≥ 0.6), estimates of peak times indicated that temporal discrimination accuracy was reduced at the unlikely interval, but not the likely interval. The mechanism of this reduced temporal discrimination accuracy could be interpreted as an attentional process.

Integration of smartphones and webcam for the measure of spatio-temporal gait parameters.

PubMed

Barone, V; Maranesi, E; Fioretti, S

2014-01-01

A very low cost prototype has been made for the spatial and temporal analysis of human movement using an integrated system of last generation smartphones and a highdefinition webcam, controlled by a laptop. The system can be used to analyze mainly planar motions in non-structured environments. In this paper, the accelerometer signal as captured by the 3D sensor embedded in one smartphone, and the position of colored markers derived by the webcam frames, are used for the computation of spatial-temporal parameters of gait. Accuracy of results is compared with that obtainable by a gold-standard instrumentation. The system is characterized by a very low cost and by a very high level of automation. It has been thought to be used by non-expert users in ambulatory settings.

Multi-scale approaches for high-speed imaging and analysis of large neural populations

PubMed Central

Ahrens, Misha B.; Yuste, Rafael; Peterka, Darcy S.; Paninski, Liam

2017-01-01

Progress in modern neuroscience critically depends on our ability to observe the activity of large neuronal populations with cellular spatial and high temporal resolution. However, two bottlenecks constrain efforts towards fast imaging of large populations. First, the resulting large video data is challenging to analyze. Second, there is an explicit tradeoff between imaging speed, signal-to-noise, and field of view: with current recording technology we cannot image very large neuronal populations with simultaneously high spatial and temporal resolution. Here we describe multi-scale approaches for alleviating both of these bottlenecks. First, we show that spatial and temporal decimation techniques based on simple local averaging provide order-of-magnitude speedups in spatiotemporally demixing calcium video data into estimates of single-cell neural activity. Second, once the shapes of individual neurons have been identified at fine scale (e.g., after an initial phase of conventional imaging with standard temporal and spatial resolution), we find that the spatial/temporal resolution tradeoff shifts dramatically: after demixing we can accurately recover denoised fluorescence traces and deconvolved neural activity of each individual neuron from coarse scale data that has been spatially decimated by an order of magnitude. This offers a cheap method for compressing this large video data, and also implies that it is possible to either speed up imaging significantly, or to “zoom out” by a corresponding factor to image order-of-magnitude larger neuronal populations with minimal loss in accuracy or temporal resolution. PMID:28771570

TH-CD-202-04: Evaluation of Virtual Non-Contrast Images From a Novel Split-Filter Dual-Energy CT Technique

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huang, J; Szczykutowicz, T; Bayouth, J

Purpose: To compare the ability of two dual-energy CT techniques, a novel split-filter single-source technique of superior temporal resolution against an established sequential-scan technique, to remove iodine contrast from images with minimal impact on CT number accuracy. Methods: A phantom containing 8 tissue substitute materials and vials of varying iodine concentrations (1.7–20.1 mg I /mL) was imaged using a Siemens Edge CT scanner. Dual-energy virtual non-contrast (VNC) images were generated using the novel split-filter technique, in which a 120kVp spectrum is filtered by tin and gold to create high- and low-energy spectra with < 1 second temporal separation between themore » acquisition of low- and high-energy data. Additionally, VNC images were generated with the sequential-scan technique (80 and 140kVp) for comparison. CT number accuracy was evaluated for all materials at 15, 25, and 35mGy CTDIvol. Results: The spectral separation was greater for the sequential-scan technique than the split-filter technique with dual-energy ratios of 2.18 and 1.26, respectively. Both techniques successfully removed iodine contrast, resulting in mean CT numbers within 60HU of 0HU (split-filter) and 40HU of 0HU (sequential-scan) for all iodine concentrations. Additionally, for iodine vials of varying diameter (2–20 mm) with the same concentration (9.9 mg I /mL), the system accurately detected iodine for all sizes investigated. Both dual-energy techniques resulted in reduced CT numbers for bone materials (by >400HU for the densest bone). Increasing the imaging dose did not improve the CT number accuracy for bone in VNC images. Conclusion: VNC images from the split-filter technique successfully removed iodine contrast. These results demonstrate a potential for improving dose calculation accuracy and reducing patient imaging dose, while achieving superior temporal resolution in comparison sequential scans. For both techniques, inaccuracies in CT numbers for bone materials necessitate consideration for radiation therapy treatment planning.« less

Wide Swath Stereo Mapping from Gaofen-1 Wide-Field-View (WFV) Images Using Calibration

PubMed Central

Chen, Shoubin; Liu, Jingbin; Huang, Wenchao

2018-01-01

The development of Earth observation systems has changed the nature of survey and mapping products, as well as the methods for updating maps. Among optical satellite mapping methods, the multiline array stereo and agile stereo modes are the most common methods for acquiring stereo images. However, differences in temporal resolution and spatial coverage limit their application. In terms of this issue, our study takes advantage of the wide spatial coverage and high revisit frequencies of wide swath images and aims at verifying the feasibility of stereo mapping with the wide swath stereo mode and reaching a reliable stereo accuracy level using calibration. In contrast with classic stereo modes, the wide swath stereo mode is characterized by both a wide spatial coverage and high-temporal resolution and is capable of obtaining a wide range of stereo images over a short period. In this study, Gaofen-1 (GF-1) wide-field-view (WFV) images, with total imaging widths of 800 km, multispectral resolutions of 16 m and revisit periods of four days, are used for wide swath stereo mapping. To acquire a high-accuracy digital surface model (DSM), the nonlinear system distortion in the GF-1 WFV images is detected and compensated for in advance. The elevation accuracy of the wide swath stereo mode of the GF-1 WFV images can be improved from 103 m to 30 m for a DSM with proper calibration, meeting the demands for 1:250,000 scale mapping and rapid topographic map updates and showing improved efficacy for satellite imaging. PMID:29494540

Freezing degrees of freedom under stress: kinematic evidence of constrained movement strategies.

PubMed

Higuchi, Takahiro; Imanaka, Kuniyasu; Hatayama, Toshiteru

2002-12-01

The present study investigated the effect of psychological stress imposed on movement kinematics in a computer-simulated batting task involving a backward and forward swing of the forearm. The psychological stress was imposed by a mild electric stimulus following poor performance. Fourteen participants hit a moving ball with a horizontal lever and aimed at a distant target with as much accuracy as possible. The kinematic characteristics appearing under stress were delay of movement initiation, small amplitude of movement and low variability of spatial kinematic events between trials. These features were also found in previous studies in which the experimental task required high accuracy. The characteristic kinematics evident in the present study suggested that the movement strategies adopted by the stressed participants were similar to those that appear under high accuracy demand. Moreover, a correlation analysis between the onset times of kinematic events revealed that temporally consistent movements were reproduced under stress. Taken together, the present findings demonstrated that, under psychological stress, movement strategies tend to shift toward the production of more constrained trajectories, as is seen under conditions of high accuracy demand, even though the difficulty of the task itself does not change. Copyright 2002 Elsevier Science B.V.

The lexical processing of abstract and concrete nouns.

PubMed

Papagno, Costanza; Fogliata, Arianna; Catricalà, Eleonora; Miniussi, Carlo

2009-03-31

Recent activation studies have suggested different neural correlates for processing concrete and abstract words. However, the precise localization is far from being defined. One reason for the heterogeneity of these results could lie in the extreme variability of experimental paradigms, ranging from explicit semantic judgments to lexical decision tasks (auditory and/or visual). The present study explored the processing of abstract/concrete nouns by using repetitive Transcranial Magnetic Stimulation (rTMS) and a lexical decision paradigm in neurologically-unimpaired subjects. Four sites were investigated: left inferior frontal, bilaterally posterior-superior temporal and left posterior-inferior parietal. An interference on accuracy was found for abstract words when rTMS was applied over the left temporal site, while for concrete words accuracy decreased when rTMS was applied over the right temporal site. Accuracy for abstract words, but not for concrete words, decreased after frontal stimulation as compared to the sham condition. These results suggest that abstract lexical entries are stored in the posterior part of the left temporal superior gyrus and possibly in the left frontal inferior gyrus, while the regions involved in storing concrete items include the right temporal cortex. It cannot be excluded, however, that additional areas, not tested in this experiment, are involved in processing both, concrete and abstract nouns.

High-accuracy reference standards for two-photon absorption in the 680–1050 nm wavelength range

PubMed Central

de Reguardati, Sophie; Pahapill, Juri; Mikhailov, Alexander; Stepanenko, Yuriy; Rebane, Aleksander

2016-01-01

Degenerate two-photon absorption (2PA) of a series of organic fluorophores is measured using femtosecond fluorescence excitation method in the wavelength range, λ2PA = 680–1050 nm, and ~100 MHz pulse repetition rate. The function of relative 2PA spectral shape is obtained with estimated accuracy 5%, and the absolute 2PA cross section is measured at selected wavelengths with the accuracy 8%. Significant improvement of the accuracy is achieved by means of rigorous evaluation of the quadratic dependence of the fluorescence signal on the incident photon flux in the whole wavelength range, by comparing results obtained from two independent experiments, as well as due to meticulous evaluation of critical experimental parameters, including the excitation spatial- and temporal pulse shape, laser power and sample geometry. Application of the reference standards in nonlinear transmittance measurements is discussed. PMID:27137334

Temporal trends in symptom experience predict the accuracy of recall PROs

PubMed Central

Schneider, Stefan; Broderick, Joan E.; Junghaenel, Doerte U.; Schwartz, Joseph E.; Stone, Arthur A.

2013-01-01

Objective Patient-reported outcome measures with reporting periods of a week or more are often used to evaluate the change of symptoms over time, but the accuracy of recall in the context of change is not well understood. This study examined whether temporal trends in symptoms that occur during the reporting period impact the accuracy of 7-day recall reports. Methods Women with premenstrual symptoms (n = 95) completed daily reports of anger, depression, fatigue, and pain intensity for 4 weeks, as well as 7-day recall reports at the end of each week. Latent class growth analysis was used to categorize recall periods based on the direction and rate of change in the daily reports. Agreement (level differences and correlations) between 7-day recall and aggregated daily scores was compared for recall periods with different temporal trends. Results Recall periods with positive, negative, and flat temporal trends were identified and they varied in accordance with weeks of the menstrual cycle. Replicating previous research, 7-day recall scores were consistently higher than aggregated daily scores, but this level difference was more pronounced for recall periods involving positive and negative trends compared with flat trends. Moreover, correlations between 7-day recall and aggregated daily scores were lower in the presence of positive and negative trends compared with flat trends. These findings were largely consistent for anger, depression, fatigue, and pain intensity. Conclusion Temporal trends in symptoms can influence the accuracy of recall reports and this should be considered in research designs involving change. PMID:23915773

Higher-Order Compact Schemes for Numerical Simulation of Incompressible Flows

NASA Technical Reports Server (NTRS)

Wilson, Robert V.; Demuren, Ayodeji O.; Carpenter, Mark

1998-01-01

A higher order accurate numerical procedure has been developed for solving incompressible Navier-Stokes equations for 2D or 3D fluid flow problems. It is based on low-storage Runge-Kutta schemes for temporal discretization and fourth and sixth order compact finite-difference schemes for spatial discretization. The particular difficulty of satisfying the divergence-free velocity field required in incompressible fluid flow is resolved by solving a Poisson equation for pressure. It is demonstrated that for consistent global accuracy, it is necessary to employ the same order of accuracy in the discretization of the Poisson equation. Special care is also required to achieve the formal temporal accuracy of the Runge-Kutta schemes. The accuracy of the present procedure is demonstrated by application to several pertinent benchmark problems.

Using Multi-Temporal Imaging Spectroscopy Data to Detect Drought and Bark Beetle Related Conifer Mortality across the Central Sierra Nevada, California, USA

NASA Astrophysics Data System (ADS)

Tane, Z.; Ramirez, C.; Roberts, D. A.; Koltunov, A.; Sweeney, S.

2016-12-01

There is considerable scientific and public interest in the ongoing drought and bark beetle driven conifer mortality in the Central and Southern Sierra Nevada, the scale of which has not been seen previously in California's recorded history. Just before and during this mortality event (2013-2016), Airborne Visible / Infrared Imaging Spectrometer (AVIRIS) data were acquired seasonally over part of the affected area as part of the HyspIRI Preparatory Mission. In this study, we used 11 AVIRIS flight lines from 8 seasonal flights (from spring 2013 to summer 2015) to detect conifer mortality. In addition to the standard pre-processing completed by NASA's Jet Propulsion Lab, AVIRIS images were co-registered and georeferenced between time steps and images were resampled to the spatial resolution and signal-to-noise ratio expected from the proposed HyspIRI satellite. We used summer 2015 high-spatial resolution WorldView-2 and WorldView-3 images from across the study area to collect training data from five scenes, and independent validation data from five additional scenes. A cover class map developed with a machine-learning algorithm, separated pixels into green conifer, red-attack conifer, and non-conifer dominant cover, yielding a high accuracy (above 85% accuracy on the independent validation data) in the tree mortality final map. Discussion will include the effects of temporal information and input dimensionality on classification accuracy, comparison with multi-spectral classification accuracy, the ecological and forest management implications of this work, incorporating 2016 AVIRS images to detect 2016 mortality, and future work in understanding the spatial patterns underlying the mortality.

Longer-Term Investigation of the Value of 18F-FDG-PET and Magnetic Resonance Imaging for Predicting the Conversion of Mild Cognitive Impairment to Alzheimer's Disease: A Multicenter Study.

PubMed

Inui, Yoshitaka; Ito, Kengo; Kato, Takashi

2017-01-01

The value of fluorine-18-fluorodeoxyglucose positron emission tomography (18F-FDG-PET) and magnetic resonance imaging (MRI) for predicting conversion of mild cognitive impairment (MCI) to Alzheimer's disease (AD) in longer-term is unclear. To evaluate longer-term prediction of MCI to AD conversion using 18F-FDG-PET and MRI in a multicenter study. One-hundred and fourteen patients with MCI were followed for 5 years. They underwent clinical and neuropsychological examinations, 18F-FDG-PET, and MRI at baseline. PET images were visually classified into predefined dementia patterns. PET scores were calculated as a semi quantitative index. For structural MRI, z-scores in medial temporal area were calculated by automated volume-based morphometry (VBM). Overall, 72% patients with amnestic MCI progressed to AD during the 5-year follow-up. The diagnostic accuracy of PET scores over 5 years was 60% with 53% sensitivity and 84% specificity. Visual interpretation of PET images predicted conversion to AD with an overall 82% diagnostic accuracy, 94% sensitivity, and 53% specificity. The accuracy of VBM analysis presented little fluctuation through 5 years and it was highest (73%) at the 5-year follow-up, with 79% sensitivity and 63% specificity. The best performance (87.9% diagnostic accuracy, 89.8% sensitivity, and 82.4% specificity) was with a combination identified using multivariate logistic regression analysis that included PET visual interpretation, educational level, and neuropsychological tests as predictors. 18F-FDG-PET visual assessment showed high performance for predicting conversion to AD from MCI, particularly in combination with neuropsychological tests. PET scores showed high diagnostic specificity. Structural MRI focused on the medial temporal area showed stable predictive value throughout the 5-year course.

Temporal Accuracy and Modern High Performance Processors: A Case Study Using Pentium Pro

DTIC Science & Technology

1998-10-15

conducted. We discuss the results of our experiments and how these results will be usedfor implementing the next release of Maruti hard real - time operating system in...Even though the resolution of the APIC timer is not as good as the TSCcounter, an interruptible timer may be used in several ways in a real - time operating system . Theobjective

High-order Spatio-temporal Schemes for Coupled, Multi-physics Reactor Simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mr. Vijay S. Mahadevan; Dr. Jean C. Ragusa

2008-09-01

This report summarizes the work done in the summer of 08 by the Ph.D. student Vijay Mahadevan. The main focus of the work was to coupled 3-D neutron difusion to 3-D heat conduction in parallel with accuracy greater than or equal to 2nd order in space and time. Results show that the goal was attained.

Impact of geophysical model error for recovering temporal gravity field model

NASA Astrophysics Data System (ADS)

Zhou, Hao; Luo, Zhicai; Wu, Yihao; Li, Qiong; Xu, Chuang

2016-07-01

The impact of geophysical model error on recovered temporal gravity field models with both real and simulated GRACE observations is assessed in this paper. With real GRACE observations, we build four temporal gravity field models, i.e., HUST08a, HUST11a, HUST04 and HUST05. HUST08a and HUST11a are derived from different ocean tide models (EOT08a and EOT11a), while HUST04 and HUST05 are derived from different non-tidal models (AOD RL04 and AOD RL05). The statistical result shows that the discrepancies of the annual mass variability amplitudes in six river basins between HUST08a and HUST11a models, HUST04 and HUST05 models are all smaller than 1 cm, which demonstrates that geophysical model error slightly affects the current GRACE solutions. The impact of geophysical model error for future missions with more accurate satellite ranging is also assessed by simulation. The simulation results indicate that for current mission with range rate accuracy of 2.5 × 10- 7 m/s, observation error is the main reason for stripe error. However, when the range rate accuracy improves to 5.0 × 10- 8 m/s in the future mission, geophysical model error will be the main source for stripe error, which will limit the accuracy and spatial resolution of temporal gravity model. Therefore, observation error should be the primary error source taken into account at current range rate accuracy level, while more attention should be paid to improving the accuracy of background geophysical models for the future mission.

Spatial and temporal laser pulse design for material processing on ultrafast scales

NASA Astrophysics Data System (ADS)

Stoian, R.; Colombier, J. P.; Mauclair, C.; Cheng, G.; Bhuyan, M. K.; Velpula, P. K.; Srisungsitthisunti, P.

2014-01-01

The spatio-temporal design of ultrafast laser excitation can have a determinant influence on the physical and engineering aspects of laser-matter interactions, with the potential of upgrading laser processing effects. Energy relaxation channels can be synergetically stimulated as the energy delivery rate is synchronized with the material response on ps timescales. Experimental and theoretical loops based on the temporal design of laser irradiation and rapid monitoring of irradiation effects are, therefore, able to predict and determine ideal optimal laser pulse forms for specific ablation objectives. We illustrate this with examples on manipulating the thermodynamic relaxation pathways impacting the ablation products and nanostructuring of bulk and surfaces using longer pulse envelopes. Some of the potential control factors will be pointed out. At the same time the spatial character can dramatically influence the development of laser interaction. We discuss spatial beam engineering examples such as parallel and non-diffractive approaches designed for high-throughput, high-accuracy processing events.

A Temporal Mining Framework for Classifying Un-Evenly Spaced Clinical Data: An Approach for Building Effective Clinical Decision-Making System.

PubMed

Jane, Nancy Yesudhas; Nehemiah, Khanna Harichandran; Arputharaj, Kannan

2016-01-01

Clinical time-series data acquired from electronic health records (EHR) are liable to temporal complexities such as irregular observations, missing values and time constrained attributes that make the knowledge discovery process challenging. This paper presents a temporal rough set induced neuro-fuzzy (TRiNF) mining framework that handles these complexities and builds an effective clinical decision-making system. TRiNF provides two functionalities namely temporal data acquisition (TDA) and temporal classification. In TDA, a time-series forecasting model is constructed by adopting an improved double exponential smoothing method. The forecasting model is used in missing value imputation and temporal pattern extraction. The relevant attributes are selected using a temporal pattern based rough set approach. In temporal classification, a classification model is built with the selected attributes using a temporal pattern induced neuro-fuzzy classifier. For experimentation, this work uses two clinical time series dataset of hepatitis and thrombosis patients. The experimental result shows that with the proposed TRiNF framework, there is a significant reduction in the error rate, thereby obtaining the classification accuracy on an average of 92.59% for hepatitis and 91.69% for thrombosis dataset. The obtained classification results prove the efficiency of the proposed framework in terms of its improved classification accuracy.

Evaluating RGB photogrammetry and multi-temporal digital surface models for detecting soil erosion

NASA Astrophysics Data System (ADS)

Anders, Niels; Keesstra, Saskia; Seeger, Manuel

2013-04-01

Photogrammetry is a widely used tool for generating high-resolution digital surface models. Unmanned Aerial Vehicles (UAVs), equipped with a Red Green Blue (RGB) camera, have great potential in quickly acquiring multi-temporal high-resolution orthophotos and surface models. Such datasets would ease the monitoring of geomorphological processes, such as local soil erosion and rill formation after heavy rainfall events. In this study we test a photogrammetric setup to determine data requirements for soil erosion studies with UAVs. We used a rainfall simulator (5 m2) and above a rig with attached a Panasonic GX1 16 megapixel digital camera and 20mm lens. The soil material in the simulator consisted of loamy sand at an angle of 5 degrees. Stereo pair images were taken before and after rainfall simulation with 75-85% overlap. Acquired images were automatically mosaicked to create high-resolution orthorectified images and digital surface models (DSM). We resampled the DSM to different spatial resolutions to analyze the effect of cell size to the accuracy of measured rill depth and soil loss estimations, and determined an optimal cell size (thus flight altitude). Furthermore, the high spatial accuracy of the acquired surface models allows further analysis of rill formation and channel initiation related to e.g. surface roughness. We suggest implementing near-infrared and temperature sensors to combine soil moisture and soil physical properties with surface morphology for future investigations.

Satellite image time series simulation for environmental monitoring

NASA Astrophysics Data System (ADS)

Guo, Tao

2014-11-01

The performance of environmental monitoring heavily depends on the availability of consecutive observation data and it turns out an increasing demand in remote sensing community for satellite image data in the sufficient resolution with respect to both spatial and temporal requirements, which appear to be conflictive and hard to tune tradeoffs. Multiple constellations could be a solution if without concerning cost, and thus it is so far interesting but very challenging to develop a method which can simultaneously improve both spatial and temporal details. There are some research efforts to deal with the problem from various aspects, a type of approaches is to enhance the spatial resolution using techniques of super resolution, pan-sharpen etc. which can produce good visual effects, but mostly cannot preserve spectral signatures and result in losing analytical value. Another type is to fill temporal frequency gaps by adopting time interpolation, which actually doesn't increase informative context at all. In this paper we presented a novel method to generate satellite images in higher spatial and temporal details, which further enables satellite image time series simulation. Our method starts with a pair of high-low resolution data set, and then a spatial registration is done by introducing LDA model to map high and low resolution pixels correspondingly. Afterwards, temporal change information is captured through a comparison of low resolution time series data, and the temporal change is then projected onto high resolution data plane and assigned to each high resolution pixel referring the predefined temporal change patterns of each type of ground objects to generate a simulated high resolution data. A preliminary experiment shows that our method can simulate a high resolution data with a good accuracy. We consider the contribution of our method is to enable timely monitoring of temporal changes through analysis of low resolution images time series only, and usage of costly high resolution data can be reduced as much as possible, and it presents an efficient solution with great cost performance to build up an economically operational monitoring service for environment, agriculture, forest, land use investigation, and other applications.

RSS Fingerprint Based Indoor Localization Using Sparse Representation with Spatio-Temporal Constraint

PubMed Central

Piao, Xinglin; Zhang, Yong; Li, Tingshu; Hu, Yongli; Liu, Hao; Zhang, Ke; Ge, Yun

2016-01-01

The Received Signal Strength (RSS) fingerprint-based indoor localization is an important research topic in wireless network communications. Most current RSS fingerprint-based indoor localization methods do not explore and utilize the spatial or temporal correlation existing in fingerprint data and measurement data, which is helpful for improving localization accuracy. In this paper, we propose an RSS fingerprint-based indoor localization method by integrating the spatio-temporal constraints into the sparse representation model. The proposed model utilizes the inherent spatial correlation of fingerprint data in the fingerprint matching and uses the temporal continuity of the RSS measurement data in the localization phase. Experiments on the simulated data and the localization tests in the real scenes show that the proposed method improves the localization accuracy and stability effectively compared with state-of-the-art indoor localization methods. PMID:27827882

High-Resolution Strain Analysis of the Human Heart with Fast-DENSE

NASA Astrophysics Data System (ADS)

Aletras, Anthony H.; Balaban, Robert S.; Wen, Han

1999-09-01

Single breath-hold displacement data from the human heart were acquired with fast-DENSE (fast displacement encoding with stimulated echoes) during systolic contraction at 2.5 × 2.5 mm in-plane resolution. Encoding strengths of 0.86-1.60 mm/π were utilized in order to extend the dynamic range of the phase measurements and minimize effects of physiologic and instrument noise. The noise level in strain measurements for both contraction and dilation corresponded to a strain value of 2.8%. In the human heart, strain analysis has sufficient resolution to reveal transmural variation across the left ventricular wall. Data processing required minimal user intervention and provided a rapid quantitative feedback. The intrinsic temporal integration of fast-DENSE achieves high accuracy at the expense of temporal resolution.

The role of blood vessels in high-resolution volume conductor head modeling of EEG.

PubMed

Fiederer, L D J; Vorwerk, J; Lucka, F; Dannhauer, M; Yang, S; Dümpelmann, M; Schulze-Bonhage, A; Aertsen, A; Speck, O; Wolters, C H; Ball, T

2016-03-01

Reconstruction of the electrical sources of human EEG activity at high spatio-temporal accuracy is an important aim in neuroscience and neurological diagnostics. Over the last decades, numerous studies have demonstrated that realistic modeling of head anatomy improves the accuracy of source reconstruction of EEG signals. For example, including a cerebro-spinal fluid compartment and the anisotropy of white matter electrical conductivity were both shown to significantly reduce modeling errors. Here, we for the first time quantify the role of detailed reconstructions of the cerebral blood vessels in volume conductor head modeling for EEG. To study the role of the highly arborized cerebral blood vessels, we created a submillimeter head model based on ultra-high-field-strength (7T) structural MRI datasets. Blood vessels (arteries and emissary/intraosseous veins) were segmented using Frangi multi-scale vesselness filtering. The final head model consisted of a geometry-adapted cubic mesh with over 17×10(6) nodes. We solved the forward model using a finite-element-method (FEM) transfer matrix approach, which allowed reducing computation times substantially and quantified the importance of the blood vessel compartment by computing forward and inverse errors resulting from ignoring the blood vessels. Our results show that ignoring emissary veins piercing the skull leads to focal localization errors of approx. 5 to 15mm. Large errors (>2cm) were observed due to the carotid arteries and the dense arterial vasculature in areas such as in the insula or in the medial temporal lobe. Thus, in such predisposed areas, errors caused by neglecting blood vessels can reach similar magnitudes as those previously reported for neglecting white matter anisotropy, the CSF or the dura - structures which are generally considered important components of realistic EEG head models. Our findings thus imply that including a realistic blood vessel compartment in EEG head models will be helpful to improve the accuracy of EEG source analyses particularly when high accuracies in brain areas with dense vasculature are required. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Correlation methods in optical metrology with state-of-the-art x-ray mirrors

NASA Astrophysics Data System (ADS)

Yashchuk, Valeriy V.; Centers, Gary; Gevorkyan, Gevork S.; Lacey, Ian; Smith, Brian V.

2018-01-01

The development of fully coherent free electron lasers and diffraction limited storage ring x-ray sources has brought to focus the need for higher performing x-ray optics with unprecedented tolerances for surface slope and height errors and roughness. For example, the proposed beamlines for the future upgraded Advance Light Source, ALS-U, require optical elements characterized by a residual slope error of <100 nrad (root-mean-square) and height error of <1-2 nm (peak-tovalley). These are for optics with a length of up to one meter. However, the current performance of x-ray optical fabrication and metrology generally falls short of these requirements. The major limitation comes from the lack of reliable and efficient surface metrology with required accuracy and with reasonably high measurement rate, suitable for integration into the modern deterministic surface figuring processes. The major problems of current surface metrology relate to the inherent instrumental temporal drifts, systematic errors, and/or an unacceptably high cost, as in the case of interferometry with computer-generated holograms as a reference. In this paper, we discuss the experimental methods and approaches based on correlation analysis to the acquisition and processing of metrology data developed at the ALS X-Ray Optical Laboratory (XROL). Using an example of surface topography measurements of a state-of-the-art x-ray mirror performed at the XROL, we demonstrate the efficiency of combining the developed experimental correlation methods to the advanced optimal scanning strategy (AOSS) technique. This allows a significant improvement in the accuracy and capacity of the measurements via suppression of the instrumental low frequency noise, temporal drift, and systematic error in a single measurement run. Practically speaking, implementation of the AOSS technique leads to an increase of the measurement accuracy, as well as the capacity of ex situ metrology by a factor of about four. The developed method is general and applicable to a broad spectrum of high accuracy measurements.

Classification with spatio-temporal interpixel class dependency contexts

NASA Technical Reports Server (NTRS)

Jeon, Byeungwoo; Landgrebe, David A.

1992-01-01

A contextual classifier which can utilize both spatial and temporal interpixel dependency contexts is investigated. After spatial and temporal neighbors are defined, a general form of maximum a posterior spatiotemporal contextual classifier is derived. This contextual classifier is simplified under several assumptions. Joint prior probabilities of the classes of each pixel and its spatial neighbors are modeled by the Gibbs random field. The classification is performed in a recursive manner to allow a computationally efficient contextual classification. Experimental results with bitemporal TM data show significant improvement of classification accuracy over noncontextual pixelwise classifiers. This spatiotemporal contextual classifier should find use in many applications of remote sensing, especially when the classification accuracy is important.

Monitoring height and greenness of non-woody floodplain vegetation with UAV time series

NASA Astrophysics Data System (ADS)

van Iersel, Wimala; Straatsma, Menno; Addink, Elisabeth; Middelkoop, Hans

2018-07-01

Vegetation in river floodplains has important functions for biodiversity, but can also have a negative influence on flood safety. Floodplain vegetation is becoming increasingly heterogeneous in space and time as a result of river restoration projects. To document the spatio-temporal patterns of the floodplain vegetation, the need arises for efficient monitoring techniques. Monitoring is commonly performed by mapping floodplains based on single-epoch remote sensing data, thereby not considering seasonal dynamics of vegetation. The rising availability of unmanned airborne vehicles (UAV) increases monitoring frequency potential. Therefore, we aimed to evaluate the performance of multi-temporal high-spatial-resolution imagery, collected with a UAV, to record the dynamics in floodplain vegetation height and greenness over a growing season. Since the classification accuracy of current airborne surveys remains insufficient for low vegetation types, we focussed on seasonal variation of herbaceous and grassy vegetation with a height up to 3 m. Field reference data on vegetation height were collected six times during one year in 28 field plots within a single floodplain along the Waal River, the main distributary of the Rhine River in the Netherlands. Simultaneously with each field survey, we recorded UAV true-colour and false-colour imagery from which normalized digital surface models (nDSMs) and a consumer-grade camera vegetation index (CGCVI) were calculated. We observed that: (1) the accuracy of a UAV-derived digital terrain model (DTM) varies over the growing season and is most accurate during winter when the vegetation is dormant, (2) vegetation height can be determined from the nDSMs in leaf-on conditions via linear regression (RSME = 0.17-0.33 m), (3) the multitemporal nDSMs yielded meaningful temporal profiles of greenness and vegetation height and (4) herbaceous vegetation shows hysteresis for greenness and vegetation height, but no clear hysteresis was observed for grassland vegetation. These results show the high potential of using UAV-borne sensors for increasing the classification accuracy of low floodplain vegetation within the framework of floodplain monitoring.

Cloudy-sky Longwave Downward Radiation Estimation by Combining MODIS and AIRS/AMSU Measurements

NASA Astrophysics Data System (ADS)

Wang, T.; Shi, J.

2017-12-01

Longwave downward radiation (LWDR) is another main energy source received by the earth's surface except solar radiation. Its importance in regulating air temperature and balancing surface energy is enlarged especially under cloudy-sky. Unfortunately, to date, a large number of efforts have been made to derive LWDR from space under only clear-sky conditions leading to difficulty in utilizing space-based LWDR in most models due to its spatio-temporal discontinuity. Currently, only few studies focused on LWDR estimation under cloudy-sky conditions, while their global application is still questionable. In this paper, an alternative strategy is proposed aiming to derive high resolution(1km) cloudy-sky LWDR by fusing collocated satellite multi-sensor measurements. The results show that the newly developed method can work well and can derive LWDR at better accuracy with RMSE<27 W/m2 and bias < 10 W/m2 even under cloudy skies and at 1km scales. By comparing to CALIPSO-CloudSat-CERES-MODIS (CCCM) and SSF products of CERES, MERRA, ERA-interim and NCEP-CSFR products, the new approach demonstrates its superiority in terms of accuracy, temporal variation and spatial distribution pattern of LWDR. The comprehensive comparison analyses also reveal that, except for the proposed product, other four products (CERES, MERRA, ERA-interim and NCEP-CSFR) also show a big difference from each other in the LWDR spatio-temporal distribution pattern and magnitude. The difference between these products can still up to 60W/m2 even at the monthly scale, implying large uncertainties in current LWDR estimations. Besides the higher accuracy of the proposed method, more importantly, it provides unprecedented possibilities for jointly generating high resolution global LWDR datasets by connecting the NASA's Earth Observing System-(EOS) mission (MODIS-AIRS/AMSU) and the Suomi National Polar-orbiting Partnership-(NPP) mission (VIIRS-CrIS/ATMS). Meanwhile, the scheme proposed in this study also gives some clues for multiple data fusing in the remote sensing community.

Daily Estimation of High Resolution PM2.5 Concentrations over BTH area by Fusing MODIS AOD and Ground Observations

NASA Astrophysics Data System (ADS)

Lyu, Baolei; Hu, Yongtao; Chang, Howard; Russell, Armistead; Bai, Yuqi

2017-04-01

The satellite-borne Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth (AOD) is often used to predict ground-level fine particulate matter (PM2.5) concentrations. The associated estimation accuracy is always reduced by AOD missing values and by insufficiently accounting for the spatio-temporal PM2.5 variations. This study aims to estimate PM2.5 concentrations at a high resolution with enhanced accuracy by fusing MODIS AOD and ground observations in the polluted and populated Beijing-Tianjin-Hebei (BTH) area of China in 2014 and 2015. A Bayesian-based statistical downscaler was employed to model the spatio-temporally varied AOD-PM2.5 relationships. We resampled a 3 km MODIS AOD product to a 4 km resolution in a Lambert conic conformal projection, to assist comparison and fusion with CMAQ predictions. A two-step method was used to fill the missing AOD values to obtain a full AOD dataset with complete spatial coverage. The downscaler has a relatively good performance in the fitting procedure (R2 = 0.75) and in the cross validation procedure (with two evaluation methods, R2 = 0.58 by random method and R2 = 0.47 by city-specific method). The number of missing AOD values was serious and related to elevated PM2.5 concentrations. The gap-filled AOD values corresponded well with our understanding of PM2.5 pollution conditions in BTH. The prediction accuracy of PM2.5 concentrations were improved in terms of their annual and seasonal mean. As a result of its fine spatio-temporal resolution and complete spatial coverage, the daily PM2.5 estimation dataset could provide extensive and insightful benefits to related studies in the BTH area. This may include understanding the formation processes of regional PM2.5 pollution episodes, evaluating daily human exposure, and establishing pollution controlling measures.

A time series modeling approach in risk appraisal of violent and sexual recidivism.

PubMed

Bani-Yaghoub, Majid; Fedoroff, J Paul; Curry, Susan; Amundsen, David E

2010-10-01

For over half a century, various clinical and actuarial methods have been employed to assess the likelihood of violent recidivism. Yet there is a need for new methods that can improve the accuracy of recidivism predictions. This study proposes a new time series modeling approach that generates high levels of predictive accuracy over short and long periods of time. The proposed approach outperformed two widely used actuarial instruments (i.e., the Violence Risk Appraisal Guide and the Sex Offender Risk Appraisal Guide). Furthermore, analysis of temporal risk variations based on specific time series models can add valuable information into risk assessment and management of violent offenders.

Context Memory Decline in Middle Aged Adults is Related to Changes in Prefrontal Cortex Function

PubMed Central

Kwon, Diana; Maillet, David; Pasvanis, Stamatoula; Ankudowich, Elizabeth; Grady, Cheryl L.; Rajah, M. Natasha

2016-01-01

The ability to encode and retrieve spatial and temporal contextual details of episodic memories (context memory) begins to decline at midlife. In the current study, event-related fMRI was used to investigate the neural correlates of context memory decline in healthy middle aged adults (MA) compared with young adults (YA). Participants were scanned while performing easy and hard versions of spatial and temporal context memory tasks. Scans were obtained at encoding and retrieval. Significant reductions in context memory retrieval accuracy were observed in MA, compared with YA. The fMRI results revealed that overall, both groups exhibited similar patterns of brain activity in parahippocampal cortex, ventral occipito-temporal regions and prefrontal cortex (PFC) during encoding. In contrast, at retrieval, there were group differences in ventral occipito-temporal and PFC activity, due to these regions being more activated in MA, compared with YA. Furthermore, only in YA, increased encoding activity in ventrolateral PFC, and increased retrieval activity in occipital cortex, predicted increased retrieval accuracy. In MA, increased retrieval activity in anterior PFC predicted increased retrieval accuracy. These results suggest that there are changes in PFC contributions to context memory at midlife. PMID:25882039

Water quality modeling in the dead end sections of drinking water distribution networks.

PubMed

Abokifa, Ahmed A; Yang, Y Jeffrey; Lo, Cynthia S; Biswas, Pratim

2016-02-01

Dead-end sections of drinking water distribution networks are known to be problematic zones in terms of water quality degradation. Extended residence time due to water stagnation leads to rapid reduction of disinfectant residuals allowing the regrowth of microbial pathogens. Water quality models developed so far apply spatial aggregation and temporal averaging techniques for hydraulic parameters by assigning hourly averaged water demands to the main nodes of the network. Although this practice has generally resulted in minimal loss of accuracy for the predicted disinfectant concentrations in main water transmission lines, this is not the case for the peripheries of the distribution network. This study proposes a new approach for simulating disinfectant residuals in dead end pipes while accounting for both spatial and temporal variability in hydraulic and transport parameters. A stochastic demand generator was developed to represent residential water pulses based on a non-homogenous Poisson process. Dispersive solute transport was considered using highly dynamic dispersion rates. A genetic algorithm was used to calibrate the axial hydraulic profile of the dead-end pipe based on the different demand shares of the withdrawal nodes. A parametric sensitivity analysis was done to assess the model performance under variation of different simulation parameters. A group of Monte-Carlo ensembles was carried out to investigate the influence of spatial and temporal variations in flow demands on the simulation accuracy. A set of three correction factors were analytically derived to adjust residence time, dispersion rate and wall demand to overcome simulation error caused by spatial aggregation approximation. The current model results show better agreement with field-measured concentrations of conservative fluoride tracer and free chlorine disinfectant than the simulations of recent advection dispersion reaction models published in the literature. Accuracy of the simulated concentration profiles showed significant dependence on the spatial distribution of the flow demands compared to temporal variation. Copyright © 2015 Elsevier Ltd. All rights reserved.

Temporal bone borehole accuracy for cochlear implantation influenced by drilling strategy: an in vitro study.

PubMed

Kobler, Jan-Philipp; Schoppe, Michael; Lexow, G Jakob; Rau, Thomas S; Majdani, Omid; Kahrs, Lüder A; Ortmaier, Tobias

2014-11-01

Minimally invasive cochlear implantation is a surgical technique which requires drilling a canal from the mastoid surface toward the basal turn of the cochlea. The choice of an appropriate drilling strategy is hypothesized to have significant influence on the achievable targeting accuracy. Therefore, a method is presented to analyze the contribution of the drilling process and drilling tool to the targeting error isolated from other error sources. The experimental setup to evaluate the borehole accuracy comprises a drill handpiece attached to a linear slide as well as a highly accurate coordinate measuring machine (CMM). Based on the specific requirements of the minimally invasive cochlear access, three drilling strategies, mainly characterized by different drill tools, are derived. The strategies are evaluated by drilling into synthetic temporal bone substitutes containing air-filled cavities to simulate mastoid cells. Deviations from the desired drill trajectories are determined based on measurements using the CMM. Using the experimental setup, a total of 144 holes were drilled for accuracy evaluation. Errors resulting from the drilling process depend on the specific geometry of the tool as well as the angle at which the drill contacts the bone surface. Furthermore, there is a risk of the drill bit deflecting due to synthetic mastoid cells. A single-flute gun drill combined with a pilot drill of the same diameter provided the best results for simulated minimally invasive cochlear implantation, based on an experimental method that may be used for testing further drilling process improvements.

Classification of prostate cancer grade using temporal ultrasound: in vivo feasibility study

NASA Astrophysics Data System (ADS)

Ghavidel, Sahar; Imani, Farhad; Khallaghi, Siavash; Gibson, Eli; Khojaste, Amir; Gaed, Mena; Moussa, Madeleine; Gomez, Jose A.; Siemens, D. Robert; Leveridge, Michael; Chang, Silvia; Fenster, Aaron; Ward, Aaron D.; Abolmaesumi, Purang; Mousavi, Parvin

2016-03-01

Temporal ultrasound has been shown to have high classification accuracy in differentiating cancer from benign tissue. In this paper, we extend the temporal ultrasound method to classify lower grade Prostate Cancer (PCa) from all other grades. We use a group of nine patients with mostly lower grade PCa, where cancerous regions are also limited. A critical challenge is to train a classifier with limited aggressive cancerous tissue compared to low grade cancerous tissue. To resolve the problem of imbalanced data, we use Synthetic Minority Oversampling Technique (SMOTE) to generate synthetic samples for the minority class. We calculate spectral features of temporal ultrasound data and perform feature selection using Random Forests. In leave-one-patient-out cross-validation strategy, an area under receiver operating characteristic curve (AUC) of 0.74 is achieved with overall sensitivity and specificity of 70%. Using an unsupervised learning approach prior to proposed method improves sensitivity and AUC to 80% and 0.79. This work represents promising results to classify lower and higher grade PCa with limited cancerous training samples, using temporal ultrasound.

Automated extraction and validation of children's gait parameters with the Kinect.

PubMed

Motiian, Saeid; Pergami, Paola; Guffey, Keegan; Mancinelli, Corrie A; Doretto, Gianfranco

2015-12-02

Gait analysis for therapy regimen prescription and monitoring requires patients to physically access clinics with specialized equipment. The timely availability of such infrastructure at the right frequency is especially important for small children. Besides being very costly, this is a challenge for many children living in rural areas. This is why this work develops a low-cost, portable, and automated approach for in-home gait analysis, based on the Microsoft Kinect. A robust and efficient method for extracting gait parameters is introduced, which copes with the high variability of noisy Kinect skeleton tracking data experienced across the population of young children. This is achieved by temporally segmenting the data with an approach based on coupling a probabilistic matching of stride template models, learned offline, with the estimation of their global and local temporal scaling. A preliminary study conducted on healthy children between 2 and 4 years of age is performed to analyze the accuracy, precision, repeatability, and concurrent validity of the proposed method against the GAITRite when measuring several spatial and temporal children's gait parameters. The method has excellent accuracy and good precision, with segmenting temporal sequences of body joint locations into stride and step cycles. Also, the spatial and temporal gait parameters, estimated automatically, exhibit good concurrent validity with those provided by the GAITRite, as well as very good repeatability. In particular, on a range of nine gait parameters, the relative and absolute agreements were found to be good and excellent, and the overall agreements were found to be good and moderate. This work enables and validates the automated use of the Kinect for children's gait analysis in healthy subjects. In particular, the approach makes a step forward towards developing a low-cost, portable, parent-operated in-home tool for clinicians assisting young children.

A third-order gas-kinetic CPR method for the Euler and Navier-Stokes equations on triangular meshes

NASA Astrophysics Data System (ADS)

Zhang, Chao; Li, Qibing; Fu, Song; Wang, Z. J.

2018-06-01

A third-order accurate gas-kinetic scheme based on the correction procedure via reconstruction (CPR) framework is developed for the Euler and Navier-Stokes equations on triangular meshes. The scheme combines the accuracy and efficiency of the CPR formulation with the multidimensional characteristics and robustness of the gas-kinetic flux solver. Comparing with high-order finite volume gas-kinetic methods, the current scheme is more compact and efficient by avoiding wide stencils on unstructured meshes. Unlike the traditional CPR method where the inviscid and viscous terms are treated differently, the inviscid and viscous fluxes in the current scheme are coupled and computed uniformly through the kinetic evolution model. In addition, the present scheme adopts a fully coupled spatial and temporal gas distribution function for the flux evaluation, achieving high-order accuracy in both space and time within a single step. Numerical tests with a wide range of flow problems, from nearly incompressible to supersonic flows with strong shocks, for both inviscid and viscous problems, demonstrate the high accuracy and efficiency of the present scheme.

Integrated change detection and temporal trajectory analysis of coastal wetlands using high spatial resolution Korean Multi-Purpose Satellite series imagery

NASA Astrophysics Data System (ADS)

Nguyen, Hoang Hai; Tran, Hien; Sunwoo, Wooyeon; Yi, Jong-hyuk; Kim, Dongkyun; Choi, Minha

2017-04-01

A series of multispectral high-resolution Korean Multi-Purpose Satellite (KOMPSAT) images was used to detect the geographical changes in four different tidal flats between the Yellow Sea and the west coast of South Korea. The method of unsupervised classification was used to generate a series of land use/land cover (LULC) maps from satellite images, which were then used as input for temporal trajectory analysis to detect the temporal change of coastal wetlands and its association with natural and anthropogenic activities. The accurately classified LULC maps of KOMPSAT images, with overall accuracy ranging from 83.34% to 95.43%, indicate that these multispectral high-resolution satellite data are highly applicable to the generation of high-quality thematic maps for extracting wetlands. The result of the trajectory analysis showed that, while the variation of the tidal flats in the Gyeonggi and Jeollabuk provinces was well correlated with the regular tidal regimes, the reductive trajectory of the wetland areas belonging to the Saemangeum province was caused by a high degree of human-induced activities including large reclamation and urbanization. The conservation of the Jeungdo Wetland Protected Area in the Jeollanam province revealed that effective social and environmental policies could help in protecting coastal wetlands from degradation.

A Flexible Spatio-Temporal Model for Air Pollution with Spatial and Spatio-Temporal Covariates.

PubMed

Lindström, Johan; Szpiro, Adam A; Sampson, Paul D; Oron, Assaf P; Richards, Mark; Larson, Tim V; Sheppard, Lianne

2014-09-01

The development of models that provide accurate spatio-temporal predictions of ambient air pollution at small spatial scales is of great importance for the assessment of potential health effects of air pollution. Here we present a spatio-temporal framework that predicts ambient air pollution by combining data from several different monitoring networks and deterministic air pollution model(s) with geographic information system (GIS) covariates. The model presented in this paper has been implemented in an R package, SpatioTemporal, available on CRAN. The model is used by the EPA funded Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air) to produce estimates of ambient air pollution; MESA Air uses the estimates to investigate the relationship between chronic exposure to air pollution and cardiovascular disease. In this paper we use the model to predict long-term average concentrations of NO x in the Los Angeles area during a ten year period. Predictions are based on measurements from the EPA Air Quality System, MESA Air specific monitoring, and output from a source dispersion model for traffic related air pollution (Caline3QHCR). Accuracy in predicting long-term average concentrations is evaluated using an elaborate cross-validation setup that accounts for a sparse spatio-temporal sampling pattern in the data, and adjusts for temporal effects. The predictive ability of the model is good with cross-validated R 2 of approximately 0.7 at subject sites. Replacing four geographic covariate indicators of traffic density with the Caline3QHCR dispersion model output resulted in very similar prediction accuracy from a more parsimonious and more interpretable model. Adding traffic-related geographic covariates to the model that included Caline3QHCR did not further improve the prediction accuracy.

HOTS: A Hierarchy of Event-Based Time-Surfaces for Pattern Recognition.

PubMed

Lagorce, Xavier; Orchard, Garrick; Galluppi, Francesco; Shi, Bertram E; Benosman, Ryad B

2017-07-01

This paper describes novel event-based spatio-temporal features called time-surfaces and how they can be used to create a hierarchical event-based pattern recognition architecture. Unlike existing hierarchical architectures for pattern recognition, the presented model relies on a time oriented approach to extract spatio-temporal features from the asynchronously acquired dynamics of a visual scene. These dynamics are acquired using biologically inspired frameless asynchronous event-driven vision sensors. Similarly to cortical structures, subsequent layers in our hierarchy extract increasingly abstract features using increasingly large spatio-temporal windows. The central concept is to use the rich temporal information provided by events to create contexts in the form of time-surfaces which represent the recent temporal activity within a local spatial neighborhood. We demonstrate that this concept can robustly be used at all stages of an event-based hierarchical model. First layer feature units operate on groups of pixels, while subsequent layer feature units operate on the output of lower level feature units. We report results on a previously published 36 class character recognition task and a four class canonical dynamic card pip task, achieving near 100 percent accuracy on each. We introduce a new seven class moving face recognition task, achieving 79 percent accuracy.This paper describes novel event-based spatio-temporal features called time-surfaces and how they can be used to create a hierarchical event-based pattern recognition architecture. Unlike existing hierarchical architectures for pattern recognition, the presented model relies on a time oriented approach to extract spatio-temporal features from the asynchronously acquired dynamics of a visual scene. These dynamics are acquired using biologically inspired frameless asynchronous event-driven vision sensors. Similarly to cortical structures, subsequent layers in our hierarchy extract increasingly abstract features using increasingly large spatio-temporal windows. The central concept is to use the rich temporal information provided by events to create contexts in the form of time-surfaces which represent the recent temporal activity within a local spatial neighborhood. We demonstrate that this concept can robustly be used at all stages of an event-based hierarchical model. First layer feature units operate on groups of pixels, while subsequent layer feature units operate on the output of lower level feature units. We report results on a previously published 36 class character recognition task and a four class canonical dynamic card pip task, achieving near 100 percent accuracy on each. We introduce a new seven class moving face recognition task, achieving 79 percent accuracy.

Entropy of Movement Outcome in Space-Time.

PubMed

Lai, Shih-Chiung; Hsieh, Tsung-Yu; Newell, Karl M

2015-07-01

Information entropy of the joint spatial and temporal (space-time) probability of discrete movement outcome was investigated in two experiments as a function of different movement strategies (space-time, space, and time instructional emphases), task goals (point-aiming and target-aiming) and movement speed-accuracy constraints. The variance of the movement spatial and temporal errors was reduced by instructional emphasis on the respective spatial or temporal dimension, but increased on the other dimension. The space-time entropy was lower in targetaiming task than the point aiming task but did not differ between instructional emphases. However, the joint probabilistic measure of spatial and temporal entropy showed that spatial error is traded for timing error in tasks with space-time criteria and that the pattern of movement error depends on the dimension of the measurement process. The unified entropy measure of movement outcome in space-time reveals a new relation for the speed-accuracy.

Improved Diagnostic Accuracy of Alzheimer's Disease by Combining Regional Cortical Thickness and Default Mode Network Functional Connectivity: Validated in the Alzheimer's Disease Neuroimaging Initiative Set.

PubMed

Park, Ji Eun; Park, Bumwoo; Kim, Sang Joon; Kim, Ho Sung; Choi, Choong Gon; Jung, Seung Chai; Oh, Joo Young; Lee, Jae-Hong; Roh, Jee Hoon; Shim, Woo Hyun

2017-01-01

To identify potential imaging biomarkers of Alzheimer's disease by combining brain cortical thickness (CThk) and functional connectivity and to validate this model's diagnostic accuracy in a validation set. Data from 98 subjects was retrospectively reviewed, including a study set (n = 63) and a validation set from the Alzheimer's Disease Neuroimaging Initiative (n = 35). From each subject, data for CThk and functional connectivity of the default mode network was extracted from structural T1-weighted and resting-state functional magnetic resonance imaging. Cortical regions with significant differences between patients and healthy controls in the correlation of CThk and functional connectivity were identified in the study set. The diagnostic accuracy of functional connectivity measures combined with CThk in the identified regions was evaluated against that in the medial temporal lobes using the validation set and application of a support vector machine. Group-wise differences in the correlation of CThk and default mode network functional connectivity were identified in the superior temporal ( p < 0.001) and supramarginal gyrus ( p = 0.007) of the left cerebral hemisphere. Default mode network functional connectivity combined with the CThk of those two regions were more accurate than that combined with the CThk of both medial temporal lobes (91.7% vs. 75%). Combining functional information with CThk of the superior temporal and supramarginal gyri in the left cerebral hemisphere improves diagnostic accuracy, making it a potential imaging biomarker for Alzheimer's disease.

Temporal reliability of ultra-high field resting-state MRI for single-subject sensorimotor and language mapping.

PubMed

Branco, Paulo; Seixas, Daniela; Castro, São Luís

2018-03-01

Resting-state fMRI is a well-suited technique to map functional networks in the brain because unlike task-based approaches it requires little collaboration from subjects. This is especially relevant in clinical settings where a number of subjects cannot comply with task demands. Previous studies using conventional scanner fields have shown that resting-state fMRI is able to map functional networks in single subjects, albeit with moderate temporal reliability. Ultra-high resolution (7T) imaging provides higher signal-to-noise ratio and better spatial resolution and is thus well suited to assess the temporal reliability of mapping results, and to determine if resting-state fMRI can be applied in clinical decision making including preoperative planning. We used resting-state fMRI at ultra-high resolution to examine whether the sensorimotor and language networks are reliable over time - same session and one week after. Resting-state networks were identified for all subjects and sessions with good accuracy. Both networks were well delimited within classical regions of interest. Mapping was temporally reliable at short and medium time-scales as demonstrated by high values of overlap in the same session and one week after for both networks. Results were stable independently of data quality metrics and physiological variables. Taken together, these findings provide strong support for the suitability of ultra-high field resting-state fMRI mapping at the single-subject level. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Autobiographical memory of the recent past following frontal cortex or temporal lobe excisions.

PubMed

Thaiss, Laila; Petrides, Michael

2008-08-01

Previous research has raised questions regarding the necessity of the frontal cortex in autobiographical memory and the role that it plays in actively retrieving contextual information associated with personally relevant events. Autobiographical memory was studied in patients with unilateral excisions restricted to the frontal cortex or temporal lobe involving the amygdalo-hippocampal region and in normal controls using an event-sampling method. We examined accuracy of free recall, use of strategies during retrieval and memory for specific aspects of the autobiographical events, including temporal order. Patients with temporal lobe excisions were impaired in autobiographical recall. By contrast, patients with frontal cortical excisions exhibited normal autobiographical recall but were less likely to use temporal order spontaneously to organize event retrieval. Instruction to organize retrieval by temporal order failed to improve recall in temporal lobe patients and increased the incidence of plausible intrusion errors in left temporal patients. In contrast, patients with frontal cortical excisions now surpassed control subjects in recall of autobiographical events. Furthermore, the retrieval accuracy for the temporal order of diary events was not impaired in these patients. In a subsequent cued recall test, temporal lobe patients were impaired in their memory for the details of the diary events and their context. In conclusion, a basic impairment in autobiographical memory (including memory for temporal context) results from damage to the temporal lobe and not the frontal cortex. Patients with frontal excisions fail to use organizational strategies spontaneously to aid retrieval but can use these effectively if instructed to do so.

Spatio-temporal image-based parametric water surface reconstruction: a novel methodology based on refraction

NASA Astrophysics Data System (ADS)

Engelen, L.; Creëlle, S.; Schindfessel, L.; De Mulder, T.

2018-03-01

This paper presents a low-cost and easy-to-implement image-based reconstruction technique for laboratory experiments, which results in a temporal description of the water surface topography. The distortion due to refraction of a known pattern, located below the water surface, is used to fit a low parameter surface model that describes the time-dependent and three-dimensional surface variation. Instead of finding the optimal water depth for characteristic points on the surface, the deformation of the entire pattern is compared to its original shape. This avoids the need for feature tracking adopted in similar techniques, which improves the robustness to suboptimal optical conditions and small-scale, high-frequency surface perturbations. Experimental validation, by comparison with water depth measurements using a level gauge and pressure sensor, proves sub-millimetre accuracy for smooth and steady surface shapes. Although such accuracy cannot be achieved in case of highly dynamic surface phenomena, the low-frequency and large-scale free surface oscillations can still be measured with a temporal and spatial resolution mostly limited by the available optical set-up. The technique is initially intended for periodic surface phenomena, but the results presented in this paper indicate that also irregular surface shapes can robustly be reconstructed. Therefore, the presented technique is a promising tool for other research applications that require non-intrusive, low-cost surface measurements while maintaining visual access to the water below the surface. The latter ensures that the suggested surface reconstruction is compatible with simultaneous image-based velocity measurements, enabling a detailed study of the flow.

Effect of terminal accuracy requirements on temporal gaze-hand coordination during fast discrete and reciprocal pointings

PubMed Central

2011-01-01

Background Rapid discrete goal-directed movements are characterized by a well known coordination pattern between the gaze and the hand displacements. The gaze always starts prior to the hand movement and reaches the target before hand velocity peak. Surprisingly, the effect of the target size on the temporal gaze-hand coordination has not been directly investigated. Moreover, goal-directed movements are often produced in a reciprocal rather than in a discrete manner. The objectives of this work were to assess the effect of the target size on temporal gaze-hand coordination during fast 1) discrete and 2) reciprocal pointings. Methods Subjects performed fast discrete (experiment 1) and reciprocal (experiment 2) pointings with an amplitude of 50 cm and four target diameters (7.6, 3.8, 1.9 and 0.95 cm) leading to indexes of difficulty (ID = log2[2A/D]) of 3.7, 4.7, 5.7 and 6.7 bits. Gaze and hand displacements were synchronously recorded. Temporal gaze-hand coordination parameters were compared between experiments (discrete and reciprocal pointings) and IDs using analyses of variance (ANOVAs). Results Data showed that the magnitude of the gaze-hand lead pattern was much higher for discrete than for reciprocal pointings. Moreover, while it was constant for discrete pointings, it decreased systematically with an increasing ID for reciprocal pointings because of the longer duration of gaze anchoring on target. Conclusion Overall, the temporal gaze-hand coordination analysis revealed that even for high IDs, fast reciprocal pointings could not be considered as a concatenation of discrete units. Moreover, our data clearly illustrate the smooth adaptation of temporal gaze-hand coordination to terminal accuracy requirements during fast reciprocal pointings. It will be interesting for further researches to investigate if the methodology used in the experiment 2 allows assessing the effect of sensori-motor deficits on gaze-hand coordination. PMID:21320315

Event-Based Tone Mapping for Asynchronous Time-Based Image Sensor

PubMed Central

Simon Chane, Camille; Ieng, Sio-Hoi; Posch, Christoph; Benosman, Ryad B.

2016-01-01

The asynchronous time-based neuromorphic image sensor ATIS is an array of autonomously operating pixels able to encode luminance information with an exceptionally high dynamic range (>143 dB). This paper introduces an event-based methodology to display data from this type of event-based imagers, taking into account the large dynamic range and high temporal accuracy that go beyond available mainstream display technologies. We introduce an event-based tone mapping methodology for asynchronously acquired time encoded gray-level data. A global and a local tone mapping operator are proposed. Both are designed to operate on a stream of incoming events rather than on time frame windows. Experimental results on real outdoor scenes are presented to evaluate the performance of the tone mapping operators in terms of quality, temporal stability, adaptation capability, and computational time. PMID:27642275

Mapping invasive Fallopia japonica by combined spectral, spatial, and temporal analysis of digital orthophotos

NASA Astrophysics Data System (ADS)

Dorigo, Wouter; Lucieer, Arko; Podobnikar, Tomaž; Čarni, Andraž

2012-10-01

Japanese knotweed (Fallopia japonica) is listed among 100 of the World's worst invasive alien species and poses an increasing threat to ecosystems and agriculture in Northern America, Europe, and Oceania. This study proposes a remote sensing method to detect local occurrences of F. japonica from low-cost digital orthophotos taken in early spring and summer by concurrently exploring its temporal, spectral, and spatial characteristics. Temporal characteristics of the species are quantified by a band ratio calculated from the green and red spectral channels of both images. The normalized difference vegetation index was used to capture the high near-infrared (NIR) reflectance of F. japonica in summer while the characteristic texture of F. japonica is quantified by calculating gray level co-occurrence matrix (GLCM) measures. After establishing the optimum kernel size to quantify texture, the different input features (spectral, spatial, and texture) were stacked and used as input to the random forest (RF) classifier. The proposed method was tested for a built-up and semi-natural area in Slovenia. The spectral, spatial, and temporal provided an equally important contribution for differentiating F. japonica from other land cover types. The combination of all signatures resulted in a producer accuracy of 90.3% and a user accuracy of 98.1% for F. japonica when validation was based on independent regions of interest. A producer accuracy of 61.4% was obtained for F. japonica when comparing the classification result with all occurrences of F. japonica identified during a field validation campaign. This is an encouraging result given the very small patches in which the species usually occur and the high degree of intermingling with other plants. All hot spots were identified and even likely infestations of F. japonica that had remained undiscovered during the field campaign were detected. The probability images resulting from the RF classifier can be used to reduce the relatively large number of false alarms and may assist in targeted eradication measures. Classification skill only slightly reduced when NIR information was not considered, which is an important recognition with regard to transferability of the method to the most basic type of digital color orthophotos. The possibility to use orthophotos, which at most municipalities are commonly available and easily accessible, facilitates an immediate implementation of the approach in situations where intervention is urgent.

A comparison of technologies used for estimation of body temperature.

PubMed

Mangat, Jasdip; Standley, Thomas; Prevost, Andrew; Vasconcelos, Joana; White, Paul

2010-09-01

Body temperature measurement is an important clinical parameter. The performance of a number of non-invasive thermometers was measured by comparing intra- and inter-operator variability (n = 100) and clinical accuracy (n = 61). Variability was elevated in febrile compared to normothermic subjects for axillary and oral electronic contact thermometer measures and a temporal artery thermometer (p < 0.001 for both). Temporal artery thermometry and one mode of an infrared tympanic thermometer demonstrated significant clinical inaccuracy (p < 0.001 for both). Electronic contact thermometer repeatability and reproducibility are highly variable in febrile adults both in the axilla and oral cavity. Infrared thermometry of the skin over the superficial temporal artery is unreliable for measuring core body temperature, particularly in febrile subjects and patients in theatre. The infrared tympanic thermometers tested are acceptable for clinical practice; however, care should be exercised with the different modes of operation offered.

Impact of different training strategies on the accuracy of a Bayesian network for predicting hospital admission.

PubMed

Leegon, Jeffrey; Aronsky, Dominik

2006-01-01

The healthcare environment is constantly changing. Probabilistic clinical decision support systems need to recognize and incorporate the changing patterns and adjust the decision model to maintain high levels of accuracy. Using data from >75,000 ED patients during a 19-month study period we examined the impact of various static and dynamic training strategies on a decision support system designed to predict hospital admission status for ED patients. Training durations ranged from 1 to 12 weeks. During the study period major institutional changes occurred that affected the system's performance level. The average area under the receiver operating characteristic curve was higher and more stable when longer training periods were used. The system showed higher accuracy when retrained an updated with more recent data as compared to static training period. To adjust for temporal trends the accuracy of decision support systems can benefit from longer training periods and retraining with more recent data.

The loss of short-term visual representations over time: decay or temporal distinctiveness?

PubMed

Mercer, Tom

2014-12-01

There has been much recent interest in the loss of visual short-term memories over the passage of time. According to decay theory, visual representations are gradually forgotten as time passes, reflecting a slow and steady distortion of the memory trace. However, this is controversial and decay effects can be explained in other ways. The present experiment aimed to reexamine the maintenance and loss of visual information over the short term. Decay and temporal distinctiveness models were tested using a delayed discrimination task, in which participants compared complex and novel objects over unfilled retention intervals of variable length. Experiment 1 found no significant change in the accuracy of visual memory from 2 to 6 s, but the gap separating trials reliably influenced task performance. Experiment 2 found evidence for information loss at a 10-s retention interval, but temporally separating trials restored the fidelity of visual memory, possibly because temporally isolated representations are distinct from older memory traces. In conclusion, visual representations lose accuracy at some point after 6 s, but only within temporally crowded contexts. These findings highlight the importance of temporal distinctiveness within visual short-term memory. PsycINFO Database Record (c) 2014 APA, all rights reserved.

LaSVM-based big data learning system for dynamic prediction of air pollution in Tehran.

PubMed

Ghaemi, Z; Alimohammadi, A; Farnaghi, M

2018-04-20

Due to critical impacts of air pollution, prediction and monitoring of air quality in urban areas are important tasks. However, because of the dynamic nature and high spatio-temporal variability, prediction of the air pollutant concentrations is a complex spatio-temporal problem. Distribution of pollutant concentration is influenced by various factors such as the historical pollution data and weather conditions. Conventional methods such as the support vector machine (SVM) or artificial neural networks (ANN) show some deficiencies when huge amount of streaming data have to be analyzed for urban air pollution prediction. In order to overcome the limitations of the conventional methods and improve the performance of urban air pollution prediction in Tehran, a spatio-temporal system is designed using a LaSVM-based online algorithm. Pollutant concentration and meteorological data along with geographical parameters are continually fed to the developed online forecasting system. Performance of the system is evaluated by comparing the prediction results of the Air Quality Index (AQI) with those of a traditional SVM algorithm. Results show an outstanding increase of speed by the online algorithm while preserving the accuracy of the SVM classifier. Comparison of the hourly predictions for next coming 24 h, with those of the measured pollution data in Tehran pollution monitoring stations shows an overall accuracy of 0.71, root mean square error of 0.54 and coefficient of determination of 0.81. These results are indicators of the practical usefulness of the online algorithm for real-time spatial and temporal prediction of the urban air quality.

Temporal Delineation and Quantification of Short Term Clustered Mining Seismicity

NASA Astrophysics Data System (ADS)

Woodward, Kyle; Wesseloo, Johan; Potvin, Yves

2017-07-01

The assessment of the temporal characteristics of seismicity is fundamental to understanding and quantifying the seismic hazard associated with mining, the effectiveness of strategies and tactics used to manage seismic hazard, and the relationship between seismicity and changes to the mining environment. This article aims to improve the accuracy and precision in which the temporal dimension of seismic responses can be quantified and delineated. We present a review and discussion on the occurrence of time-dependent mining seismicity with a specific focus on temporal modelling and the modified Omori law (MOL). This forms the basis for the development of a simple weighted metric that allows for the consistent temporal delineation and quantification of a seismic response. The optimisation of this metric allows for the selection of the most appropriate modelling interval given the temporal attributes of time-dependent mining seismicity. We evaluate the performance weighted metric for the modelling of a synthetic seismic dataset. This assessment shows that seismic responses can be quantified and delineated by the MOL, with reasonable accuracy and precision, when the modelling is optimised by evaluating the weighted MLE metric. Furthermore, this assessment highlights that decreased weighted MLE metric performance can be expected if there is a lack of contrast between the temporal characteristics of events associated with different processes.

Modeling Geometric-Temporal Context With Directional Pyramid Co-Occurrence for Action Recognition.

PubMed

Yuan, Chunfeng; Li, Xi; Hu, Weiming; Ling, Haibin; Maybank, Stephen J

2014-02-01

In this paper, we present a new geometric-temporal representation for visual action recognition based on local spatio-temporal features. First, we propose a modified covariance descriptor under the log-Euclidean Riemannian metric to represent the spatio-temporal cuboids detected in the video sequences. Compared with previously proposed covariance descriptors, our descriptor can be measured and clustered in Euclidian space. Second, to capture the geometric-temporal contextual information, we construct a directional pyramid co-occurrence matrix (DPCM) to describe the spatio-temporal distribution of the vector-quantized local feature descriptors extracted from a video. DPCM characterizes the co-occurrence statistics of local features as well as the spatio-temporal positional relationships among the concurrent features. These statistics provide strong descriptive power for action recognition. To use DPCM for action recognition, we propose a directional pyramid co-occurrence matching kernel to measure the similarity of videos. The proposed method achieves the state-of-the-art performance and improves on the recognition performance of the bag-of-visual-words (BOVWs) models by a large margin on six public data sets. For example, on the KTH data set, it achieves 98.78% accuracy while the BOVW approach only achieves 88.06%. On both Weizmann and UCF CIL data sets, the highest possible accuracy of 100% is achieved.

Context Memory Decline in Middle Aged Adults is Related to Changes in Prefrontal Cortex Function.

PubMed

Kwon, Diana; Maillet, David; Pasvanis, Stamatoula; Ankudowich, Elizabeth; Grady, Cheryl L; Rajah, M Natasha

2016-06-01

The ability to encode and retrieve spatial and temporal contextual details of episodic memories (context memory) begins to decline at midlife. In the current study, event-related fMRI was used to investigate the neural correlates of context memory decline in healthy middle aged adults (MA) compared with young adults (YA). Participants were scanned while performing easy and hard versions of spatial and temporal context memory tasks. Scans were obtained at encoding and retrieval. Significant reductions in context memory retrieval accuracy were observed in MA, compared with YA. The fMRI results revealed that overall, both groups exhibited similar patterns of brain activity in parahippocampal cortex, ventral occipito-temporal regions and prefrontal cortex (PFC) during encoding. In contrast, at retrieval, there were group differences in ventral occipito-temporal and PFC activity, due to these regions being more activated in MA, compared with YA. Furthermore, only in YA, increased encoding activity in ventrolateral PFC, and increased retrieval activity in occipital cortex, predicted increased retrieval accuracy. In MA, increased retrieval activity in anterior PFC predicted increased retrieval accuracy. These results suggest that there are changes in PFC contributions to context memory at midlife. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Rigorous accuracy assessment for 3D reconstruction using time-series Dual Fluoroscopy (DF) image pairs

NASA Astrophysics Data System (ADS)

Al-Durgham, Kaleel; Lichti, Derek D.; Kuntze, Gregor; Ronsky, Janet

2017-06-01

High-speed biplanar videoradiography, or clinically referred to as dual fluoroscopy (DF), imaging systems are being used increasingly for skeletal kinematics analysis. Typically, a DF system comprises two X-ray sources, two image intensifiers and two high-speed video cameras. The combination of these elements provides time-series image pairs of articulating bones of a joint, which permits the measurement of bony rotation and translation in 3D at high temporal resolution (e.g., 120-250 Hz). Assessment of the accuracy of 3D measurements derived from DF imaging has been the subject of recent research efforts by several groups, however with methodological limitations. This paper presents a novel and simple accuracy assessment procedure based on using precise photogrammetric tools. We address the fundamental photogrammetry principles for the accuracy evaluation of an imaging system. Bundle adjustment with selfcalibration is used for the estimation of the system parameters. The bundle adjustment calibration uses an appropriate sensor model and applies free-network constraints and relative orientation stability constraints for a precise estimation of the system parameters. A photogrammetric intersection of time-series image pairs is used for the 3D reconstruction of a rotating planar object. A point-based registration method is used to combine the 3D coordinates from the intersection and independently surveyed coordinates. The final DF accuracy measure is reported as the distance between 3D coordinates from image intersection and the independently surveyed coordinates. The accuracy assessment procedure is designed to evaluate the accuracy over the full DF image format and a wide range of object rotation. Experiment of reconstruction of a rotating planar object reported an average positional error of 0.44 +/- 0.2 mm in the derived 3D coordinates (minimum 0.05 and maximum 1.2 mm).

Estimating Traveler Populations at Airport and Cruise Terminals for Population Distribution and Dynamics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jochem, Warren C; Sims, Kelly M; Bright, Eddie A

In recent years, uses of high-resolution population distribution databases are increasing steadily for environmental, socioeconomic, public health, and disaster-related research and operations. With the development of daytime population distribution, temporal resolution of such databases has been improved. However, the lack of incorporation of transitional population, namely business and leisure travelers, leaves a significant population unaccounted for within the critical infrastructure networks, such as at transportation hubs. This paper presents two general methodologies for estimating passenger populations in airport and cruise port terminals at a high temporal resolution which can be incorporated into existing population distribution models. The methodologies are geographicallymore » scalable and are based on, and demonstrate how, two different transportation hubs with disparate temporal population dynamics can be modeled utilizing publicly available databases including novel data sources of flight activity from the Internet which are updated in near-real time. The airport population estimation model shows great potential for rapid implementation for a large collection of airports on a national scale, and the results suggest reasonable accuracy in the estimated passenger traffic. By incorporating population dynamics at high temporal resolutions into population distribution models, we hope to improve the estimates of populations exposed to or at risk to disasters, thereby improving emergency planning and response, and leading to more informed policy decisions.« less

An Improved STARFM with Help of an Unmixing-Based Method to Generate High Spatial and Temporal Resolution Remote Sensing Data in Complex Heterogeneous Regions.

PubMed

Xie, Dengfeng; Zhang, Jinshui; Zhu, Xiufang; Pan, Yaozhong; Liu, Hongli; Yuan, Zhoumiqi; Yun, Ya

2016-02-05

Remote sensing technology plays an important role in monitoring rapid changes of the Earth's surface. However, sensors that can simultaneously provide satellite images with both high temporal and spatial resolution haven't been designed yet. This paper proposes an improved spatial and temporal adaptive reflectance fusion model (STARFM) with the help of an Unmixing-based method (USTARFM) to generate the high spatial and temporal data needed for the study of heterogeneous areas. The results showed that the USTARFM had higher accuracy than STARFM methods in two aspects of analysis: individual bands and of heterogeneity analysis. Taking the predicted NIR band as an example, the correlation coefficients (r) for the USTARFM, STARFM and unmixing methods were 0.96, 0.95, 0.90, respectively (p-value < 0.001); Root Mean Square Error (RMSE) values were 0.0245, 0.0300, 0.0401, respectively; and ERGAS values were 0.5416, 0.6507, 0.8737, respectively. The USTARM showed consistently higher performance than STARM when the degree of heterogeneity ranged from 2 to 10, highlighting that the use of this method provides the capacity to solve the data fusion problems faced when using STARFM. Additionally, the USTARFM method could help researchers achieve better performance than STARFM at a smaller window size from its heterogeneous land surface quantitative representation.

Investigation of breadboard temperature profiling system for SSME fuel preburner diagnostics

NASA Technical Reports Server (NTRS)

Shirley, J. A.

1986-01-01

The feasibility of measuring temperatures in the space shuttle main engine (SSME) fuel preburner using spontaneous Raman scattering from molecular hydrogen was studied. Laser radiation is transmitted to the preburner through a multimode optical fiber. Backscattered Raman-shifted light is collected and focused into a second fiber which connects to a remote-located spectrograph and a mutlichannel optical detector. Optics collimate and focus laser light from the transmitter fiber defining the probe volume. The high pressure, high temperature preburner environment was simulated by a heated pressure cell. Temperatures determined by the distribution of Q-branch co-vibrational transitions demonstrate precision and accuracy of 3%. It is indicated heat preburner temperatures can be determined with 5% accuracy with spatial resolution less than 1 cm and temporal resolution of 10 millisec at the nominal preburner operation conditions.

Implicit time accurate simulation of unsteady flow

NASA Astrophysics Data System (ADS)

van Buuren, René; Kuerten, Hans; Geurts, Bernard J.

2001-03-01

Implicit time integration was studied in the context of unsteady shock-boundary layer interaction flow. With an explicit second-order Runge-Kutta scheme, a reference solution to compare with the implicit second-order Crank-Nicolson scheme was determined. The time step in the explicit scheme is restricted by both temporal accuracy as well as stability requirements, whereas in the A-stable implicit scheme, the time step has to obey temporal resolution requirements and numerical convergence conditions. The non-linear discrete equations for each time step are solved iteratively by adding a pseudo-time derivative. The quasi-Newton approach is adopted and the linear systems that arise are approximately solved with a symmetric block Gauss-Seidel solver. As a guiding principle for properly setting numerical time integration parameters that yield an efficient time accurate capturing of the solution, the global error caused by the temporal integration is compared with the error resulting from the spatial discretization. Focus is on the sensitivity of properties of the solution in relation to the time step. Numerical simulations show that the time step needed for acceptable accuracy can be considerably larger than the explicit stability time step; typical ratios range from 20 to 80. At large time steps, convergence problems that are closely related to a highly complex structure of the basins of attraction of the iterative method may occur. Copyright

Consistency of Aquarius version-4 sea surface salinity with Argo products on various spatial and temporal scales

NASA Astrophysics Data System (ADS)

Lee, T.

2016-12-01

Understanding the accuracies of satellite-derived sea surface salinity (SSS) measurements in depicting temporal changes and the dependence of the accuracies on spatio-temporal scales are important to applications, capability assessment, and future mission design. This study quantifies the consistency between Aquarius Version-4 monthly gridded SSS (released in October 2015) with two widely used Argo monthly gridded near-surface salinity products. The analysis focused on their consistency in depicting temporal changes (including seasonal and non-seasonal) on various spatial scales: 1°x1°, 3°x3°, and 10°x10°. Globally averaged standard deviation (STD) values for Aquarius-Argo salinity differences on these three spatial scales are 0.16, 0.14, 0.09 psu, compared to those between the two Argo products of 0.10, 0.09, and 0.04 psu. Aquarius SSS compare better with Argo data on non-seasonal (e.g., interannual and intraseasonal) than for seasonal time scales. The seasonal Aquarius-Argo SSS differences are mostly concentrated at high latitudes. The Aquarius team is making active efforts to further reduce these high-latitude seasonal biases. The consistency between Aquarius and Argo salinity is similar to that between the two Argo products in the tropics and subtropics for non-seasonal signals, and in the tropics for seasonal signals. Therefore, the representativeness errors of the Argo products for various spatial scales (related to sampling and gridding) need to be taken into account when estimating the uncertainty of Aquarius SSS. The globally averaged uncertainty of large-scale (10°x10°) non-seasonal Aquarius SSS is approximately 0.04 psu. These estimates reflect the significant improvements of Aquarius Version-4 SSS over the previous versions. The estimates can be used as baseline requirements for future ocean salinity missions from space.

Optimizing a Sensor Network with Data from Hazard Mapping Demonstrated in a Heavy-Vehicle Manufacturing Facility.

PubMed

Berman, Jesse D; Peters, Thomas M; Koehler, Kirsten A

2018-05-28

To design a method that uses preliminary hazard mapping data to optimize the number and location of sensors within a network for a long-term assessment of occupational concentrations, while preserving temporal variability, accuracy, and precision of predicted hazards. Particle number concentrations (PNCs) and respirable mass concentrations (RMCs) were measured with direct-reading instruments in a large heavy-vehicle manufacturing facility at 80-82 locations during 7 mapping events, stratified by day and season. Using kriged hazard mapping, a statistical approach identified optimal orders for removing locations to capture temporal variability and high prediction precision of PNC and RMC concentrations. We compared optimal-removal, random-removal, and least-optimal-removal orders to bound prediction performance. The temporal variability of PNC was found to be higher than RMC with low correlation between the two particulate metrics (ρ = 0.30). Optimal-removal orders resulted in more accurate PNC kriged estimates (root mean square error [RMSE] = 49.2) at sample locations compared with random-removal order (RMSE = 55.7). For estimates at locations having concentrations in the upper 10th percentile, the optimal-removal order preserved average estimated concentrations better than random- or least-optimal-removal orders (P < 0.01). However, estimated average concentrations using an optimal-removal were not statistically different than random-removal when averaged over the entire facility. No statistical difference was observed for optimal- and random-removal methods for RMCs that were less variable in time and space than PNCs. Optimized removal performed better than random-removal in preserving high temporal variability and accuracy of hazard map for PNC, but not for the more spatially homogeneous RMC. These results can be used to reduce the number of locations used in a network of static sensors for long-term monitoring of hazards in the workplace, without sacrificing prediction performance.

Improved Diagnostic Accuracy of Alzheimer's Disease by Combining Regional Cortical Thickness and Default Mode Network Functional Connectivity: Validated in the Alzheimer's Disease Neuroimaging Initiative Set

PubMed Central

Park, Ji Eun; Park, Bumwoo; Kim, Ho Sung; Choi, Choong Gon; Jung, Seung Chai; Oh, Joo Young; Lee, Jae-Hong; Roh, Jee Hoon; Shim, Woo Hyun

2017-01-01

Objective To identify potential imaging biomarkers of Alzheimer's disease by combining brain cortical thickness (CThk) and functional connectivity and to validate this model's diagnostic accuracy in a validation set. Materials and Methods Data from 98 subjects was retrospectively reviewed, including a study set (n = 63) and a validation set from the Alzheimer's Disease Neuroimaging Initiative (n = 35). From each subject, data for CThk and functional connectivity of the default mode network was extracted from structural T1-weighted and resting-state functional magnetic resonance imaging. Cortical regions with significant differences between patients and healthy controls in the correlation of CThk and functional connectivity were identified in the study set. The diagnostic accuracy of functional connectivity measures combined with CThk in the identified regions was evaluated against that in the medial temporal lobes using the validation set and application of a support vector machine. Results Group-wise differences in the correlation of CThk and default mode network functional connectivity were identified in the superior temporal (p < 0.001) and supramarginal gyrus (p = 0.007) of the left cerebral hemisphere. Default mode network functional connectivity combined with the CThk of those two regions were more accurate than that combined with the CThk of both medial temporal lobes (91.7% vs. 75%). Conclusion Combining functional information with CThk of the superior temporal and supramarginal gyri in the left cerebral hemisphere improves diagnostic accuracy, making it a potential imaging biomarker for Alzheimer's disease. PMID:29089831

Spatial-temporal variability of soil moisture and its estimation across scales

NASA Astrophysics Data System (ADS)

Brocca, L.; Melone, F.; Moramarco, T.; Morbidelli, R.

2010-02-01

The soil moisture is a quantity of paramount importance in the study of hydrologic phenomena and soil-atmosphere interaction. Because of its high spatial and temporal variability, the soil moisture monitoring scheme was investigated here both for soil moisture retrieval by remote sensing and in view of the use of soil moisture data in rainfall-runoff modeling. To this end, by using a portable Time Domain Reflectometer, a sequence of 35 measurement days were carried out within a single year in seven fields located inside the Vallaccia catchment, central Italy, with area of 60 km2. Every sampling day, soil moisture measurements were collected at each field over a regular grid with an extension of 2000 m2. The optimization of the monitoring scheme, with the aim of an accurate mean soil moisture estimation at the field and catchment scale, was addressed by the statistical and the temporal stability. At the field scale, the number of required samples (NRS) to estimate the field-mean soil moisture within an accuracy of 2%, necessary for the validation of remotely sensed soil moisture, ranged between 4 and 15 for almost dry conditions (the worst case); at the catchment scale, this number increased to nearly 40 and it refers to almost wet conditions. On the other hand, to estimate the mean soil moisture temporal pattern, useful for rainfall-runoff modeling, the NRS was found to be lower. In fact, at the catchment scale only 10 measurements collected in the most "representative" field, previously determined through the temporal stability analysis, can reproduce the catchment-mean soil moisture with a determination coefficient, R2, higher than 0.96 and a root-mean-square error, RMSE, equal to 2.38%. For the "nonrepresentative" fields the accuracy in terms of RMSE decreased, but similar R2 coefficients were found. This insight can be exploited for the sampling in a generic field when it is sufficient to know an index of soil moisture temporal pattern to be incorporated in conceptual rainfall-runoff models. The obtained results can address the soil moisture monitoring network design from which a reliable soil moisture temporal pattern at the catchment scale can be derived.

Time series analysis of temporal networks

NASA Astrophysics Data System (ADS)

Sikdar, Sandipan; Ganguly, Niloy; Mukherjee, Animesh

2016-01-01

A common but an important feature of all real-world networks is that they are temporal in nature, i.e., the network structure changes over time. Due to this dynamic nature, it becomes difficult to propose suitable growth models that can explain the various important characteristic properties of these networks. In fact, in many application oriented studies only knowing these properties is sufficient. For instance, if one wishes to launch a targeted attack on a network, this can be done even without the knowledge of the full network structure; rather an estimate of some of the properties is sufficient enough to launch the attack. We, in this paper show that even if the network structure at a future time point is not available one can still manage to estimate its properties. We propose a novel method to map a temporal network to a set of time series instances, analyze them and using a standard forecast model of time series, try to predict the properties of a temporal network at a later time instance. To our aim, we consider eight properties such as number of active nodes, average degree, clustering coefficient etc. and apply our prediction framework on them. We mainly focus on the temporal network of human face-to-face contacts and observe that it represents a stochastic process with memory that can be modeled as Auto-Regressive-Integrated-Moving-Average (ARIMA). We use cross validation techniques to find the percentage accuracy of our predictions. An important observation is that the frequency domain properties of the time series obtained from spectrogram analysis could be used to refine the prediction framework by identifying beforehand the cases where the error in prediction is likely to be high. This leads to an improvement of 7.96% (for error level ≤20%) in prediction accuracy on an average across all datasets. As an application we show how such prediction scheme can be used to launch targeted attacks on temporal networks. Contribution to the Topical Issue "Temporal Network Theory and Applications", edited by Petter Holme.

Trend analysis of the aerosol optical depth from fusion of MISR and MODIS retrievals over China

NASA Astrophysics Data System (ADS)

Guo, Jing; Gu, Xingfa; Yu, Tao; Cheng, Tianhai; Chen, Hao

2014-03-01

Atmospheric aerosol plays an important role in the climate change though direct and indirect processes. In order to evaluate the effects of aerosols on climate, it is necessary to have a research on their spatial and temporal distributions. Satellite aerosol remote sensing is a developing technology that may provide good temporal sampling and superior spatial coverage to study aerosols. The Moderate Resolution Imaging Spectroradiometer (MODIS) and Multi-angle Imaging Spectroradiometer (MISR) have provided aerosol observations since 2000, with large coverage and high accuracy. However, due to the complex surface, cloud contamination, and aerosol models used in the retrieving process, the uncertainties still exist in current satellite aerosol products. There are several observed differences in comparing the MISR and MODIS AOD data with the AERONET AOD. Combing multiple sensors could reduce uncertainties and improve observational accuracy. The validation results reveal that a better agreement between fusion AOD and AERONET AOD. The results confirm that the fusion AOD values are more accurate than single sensor. We have researched the trend analysis of the aerosol properties over China based on nine-year (2002-2010) fusion data. Compared with trend analysis in Jingjintang and Yangtze River Delta, the accuracy has increased by 5% and 3%, respectively. It is obvious that the increasing trend of the AOD occurred in Yangtze River Delta, where human activities may be the main source of the increasing AOD.

Multi-temporal Land Use Mapping of Coastal Wetlands Area using Machine Learning in Google Earth Engine

NASA Astrophysics Data System (ADS)

Farda, N. M.

2017-12-01

Coastal wetlands provide ecosystem services essential to people and the environment. Changes in coastal wetlands, especially on land use, are important to monitor by utilizing multi-temporal imagery. The Google Earth Engine (GEE) provides many machine learning algorithms (10 algorithms) that are very useful for extracting land use from imagery. The research objective is to explore machine learning in Google Earth Engine and its accuracy for multi-temporal land use mapping of coastal wetland area. Landsat 3 MSS (1978), Landsat 5 TM (1991), Landsat 7 ETM+ (2001), and Landsat 8 OLI (2014) images located in Segara Anakan lagoon are selected to represent multi temporal images. The input for machine learning are visible and near infrared bands, PCA band, invers PCA bands, bare soil index, vegetation index, wetness index, elevation from ASTER GDEM, and GLCM (Harralick) texture, and also polygon samples in 140 locations. There are 10 machine learning algorithms applied to extract coastal wetlands land use from Landsat imagery. The algorithms are Fast Naive Bayes, CART (Classification and Regression Tree), Random Forests, GMO Max Entropy, Perceptron (Multi Class Perceptron), Winnow, Voting SVM, Margin SVM, Pegasos (Primal Estimated sub-GrAdient SOlver for Svm), IKPamir (Intersection Kernel Passive Aggressive Method for Information Retrieval, SVM). Machine learning in Google Earth Engine are very helpful in multi-temporal land use mapping, the highest accuracy for land use mapping of coastal wetland is CART with 96.98 % Overall Accuracy using K-Fold Cross Validation (K = 10). GEE is particularly useful for multi-temporal land use mapping with ready used image and classification algorithms, and also very challenging for other applications.

Ultra-high resolution coded wavefront sensor.

PubMed

Wang, Congli; Dun, Xiong; Fu, Qiang; Heidrich, Wolfgang

2017-06-12

Wavefront sensors and more general phase retrieval methods have recently attracted a lot of attention in a host of application domains, ranging from astronomy to scientific imaging and microscopy. In this paper, we introduce a new class of sensor, the Coded Wavefront Sensor, which provides high spatio-temporal resolution using a simple masked sensor under white light illumination. Specifically, we demonstrate megapixel spatial resolution and phase accuracy better than 0.1 wavelengths at reconstruction rates of 50 Hz or more, thus opening up many new applications from high-resolution adaptive optics to real-time phase retrieval in microscopy.

Temporal Analysis and Automatic Calibration of the Velodyne HDL-32E LiDAR System

NASA Astrophysics Data System (ADS)

Chan, T. O.; Lichti, D. D.; Belton, D.

2013-10-01

At the end of the first quarter of 2012, more than 600 Velodyne LiDAR systems had been sold worldwide for various robotic and high-accuracy survey applications. The ultra-compact Velodyne HDL-32E LiDAR has become a predominant sensor for many applications that require lower sensor size/weight and cost. For high accuracy applications, cost-effective calibration methods with minimal manual intervention are always desired by users. However, the calibrations are complicated by the Velodyne LiDAR's narrow vertical field of view and the very highly time-variant nature of its measurements. In the paper, the temporal stability of the HDL-32E is first analysed as the motivation for developing a new, automated calibration method. This is followed by a detailed description of the calibration method that is driven by a novel segmentation method for extracting vertical cylindrical features from the Velodyne point clouds. The proposed segmentation method utilizes the Velodyne point cloud's slice-like nature and first decomposes the point clouds into 2D layers. Then the layers are treated as 2D images and are processed with the Generalized Hough Transform which extracts the points distributed in circular patterns from the point cloud layers. Subsequently, the vertical cylindrical features can be readily extracted from the whole point clouds based on the previously extracted points. The points are passed to the calibration that estimates the cylinder parameters and the LiDAR's additional parameters simultaneously by constraining the segmented points to fit to the cylindrical geometric model in such a way the weighted sum of the adjustment residuals are minimized. The proposed calibration is highly automatic and this allows end users to obtain the time-variant additional parameters instantly and frequently whenever there are vertical cylindrical features presenting in scenes. The methods were verified with two different real datasets, and the results suggest that up to 78.43% accuracy improvement for the HDL-32E can be achieved using the proposed calibration method.

Assessing the quality of bottom water temperatures from the Finite-Volume Community Ocean Model (FVCOM) in the Northwest Atlantic Shelf region

NASA Astrophysics Data System (ADS)

Li, Bai; Tanaka, Kisei R.; Chen, Yong; Brady, Damian C.; Thomas, Andrew C.

2017-09-01

The Finite-Volume Community Ocean Model (FVCOM) is an advanced coastal circulation model widely utilized for its ability to simulate spatially and temporally evolving three-dimensional geophysical conditions of complex and dynamic coastal regions. While a body of literature evaluates model skill in surface fields, independent studies validating model skill in bottom fields over large spatial and temporal scales are scarce because these fields cannot be remotely sensed. In this study, an evaluation of FVCOM skill in modeling bottom water temperature was conducted by comparison to hourly in situ observed bottom temperatures recorded by the Environmental Monitors on Lobster Traps (eMOLT), a program that attached thermistors to commercial lobster traps from 2001 to 2013. Over 2 × 106 pairs of FVCOM-eMOLT records were evaluated by a series of statistical measures to quantify accuracy and precision of the modeled data across the Northwest Atlantic Shelf region. The overall comparison between modeled and observed data indicates reliable skill of FVCOM (r2 = 0.72; root mean squared error = 2.28 °C). Seasonally, the average absolute errors show higher model skill in spring, fall and winter than summer. We speculate that this is due to the increased difficulty of modeling high frequency variability in the exact position of the thermocline and frontal zones. The spatial patterns of the residuals suggest that there is improved similarity between modeled and observed data at higher latitudes. We speculate that this is due to increased tidal mixing at higher latitudes in our study area that reduces stratification in winter, allowing improved model accuracy. Modeled bottom water temperatures around Cape Cod, the continental shelf edges, and at one location at the entrance to Penobscot Bay were characterized by relatively high errors. Constraints for future uses of FVCOM bottom water temperature are provided based on the uncertainties in temporal-spatial patterns. This study is novel as it is the first skill assessment of a regional ocean circulation model in bottom fields at high spatial and temporal scales in the Northwest Atlantic Shelf region.

Microbarograph - ESRL Hi-Res Microbarograph, Goldendale - Raw Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

McCaffrey, Katherine

High-precision barometers (Paroscientific 6000-16B-IS) are combined with Nishiyama-Bedard Quad Disk pressure probes, measuring pressure (mb) at the surface, nominally 2 m above ground level. Data are sampled at 20 Hz for potential studies of turbulence. The sensors' high accuracy makes them useful for determining horizontal pressure gradients and their relation to wind ramp events, as well as the temporal variability of pressure associated with mountain wakes and waves. **Note different ASCII file formats for Goldendale (z04) and Walla Walla (z09) sites.**

Microbarograph - ESRL Hi-Res Microbarograph, Condon - Reviewed Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

McCaffrey, Katherine

High-precision barometers (Paroscientific 6000-16B-IS) are combined with Nishiyama-Bedard Quad Disk pressure probes, measuring pressure (mb) at the surface, nominally 2 m above ground level. Data are sampled at 20 Hz for potential studies of turbulence. The sensors' high accuracy makes them useful for determining horizontal pressure gradients and their relation to wind ramp events, as well as the temporal variability of pressure associated with mountain wakes and waves. **Note different ASCII file formats for Goldendale (z04) and Walla Walla (z09) sites.**

Microbarograph - ESRL Hi-Res Microbarograph, Troutdale - Raw Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

McCaffrey, Katherine

High-precision barometers (Paroscientific 6000-16B-IS) are combined with Nishiyama-Bedard Quad Disk pressure probes, measuring pressure (mb) at the surface, nominally 2 m above ground level. Data are sampled at 20 Hz for potential studies of turbulence. The sensors' high accuracy makes them useful for determining horizontal pressure gradients and their relation to wind ramp events, as well as the temporal variability of pressure associated with mountain wakes and waves. **Note different ASCII file formats for Goldendale (z04) and Walla Walla (z09) sites.**

Microbarograph - ESRL Hi-Res Microbarograph, Troutdale - Reviewed Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

McCaffrey, Katherine

High-precision barometers (Paroscientific 6000-16B-IS) are combined with Nishiyama-Bedard Quad Disk pressure probes, measuring pressure (mb) at the surface, nominally 2 m above ground level. Data are sampled at 20 Hz for potential studies of turbulence. The sensors' high accuracy makes them useful for determining horizontal pressure gradients and their relation to wind ramp events, as well as the temporal variability of pressure associated with mountain wakes and waves. **Note different ASCII file formats for Goldendale (z04) and Walla Walla (z09) sites.**

Microbarograph - ESRL Hi-Res Microbarograph, Condon - Raw Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

McCaffrey, Katherine

High-precision barometers (Paroscientific 6000-16B-IS) are combined with Nishiyama-Bedard Quad Disk pressure probes, measuring pressure (mb) at the surface, nominally 2 m above ground level. Data are sampled at 20 Hz for potential studies of turbulence. The sensors' high accuracy makes them useful for determining horizontal pressure gradients and their relation to wind ramp events, as well as the temporal variability of pressure associated with mountain wakes and waves. **Note different ASCII file formats for Goldendale (z04) and Walla Walla (z09) sites.**

Microbarograph - ESRL Hi-Res Microbarograph, Wasco Airport - Reviewed Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

McCaffrey, Katherine

High-precision barometers (Paroscientific 6000-16B-IS) are combined with Nishiyama-Bedard Quad Disk pressure probes, measuring pressure (mb) at the surface, nominally 2 m above ground level. Data are sampled at 20 Hz for potential studies of turbulence. The sensors' high accuracy makes them useful for determining horizontal pressure gradients and their relation to wind ramp events, as well as the temporal variability of pressure associated with mountain wakes and waves. **Note different ASCII file formats for Goldendale (z04) and Walla Walla (z09) sites.**

Microbarograph - ESRL Hi-Res Microbarograph, Walla Walla - Raw Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

McCaffrey, Katherine

High-precision barometers (Paroscientific 6000-16B-IS) are combined with Nishiyama-Bedard Quad Disk pressure probes, measuring pressure (mb) at the surface, nominally 2 m above ground level. Data are sampled at 20 Hz for potential studies of turbulence. The sensors' high accuracy makes them useful for determining horizontal pressure gradients and their relation to wind ramp events, as well as the temporal variability of pressure associated with mountain wakes and waves. **Note different ASCII file formats for Goldendale (z04) and Walla Walla (z09) sites.**

Microbarograph - ESRL Hi-Res Microbarograph, Goldendale - Reviewed Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

McCaffrey, Katherine

High-precision barometers (Paroscientific 6000-16B-IS) are combined with Nishiyama-Bedard Quad Disk pressure probes, measuring pressure (mb) at the surface, nominally 2 m above ground level. Data are sampled at 20 Hz for potential studies of turbulence. The sensors' high accuracy makes them useful for determining horizontal pressure gradients and their relation to wind ramp events, as well as the temporal variability of pressure associated with mountain wakes and waves. **Note different ASCII file formats for Goldendale (z04) and Walla Walla (z09) sites.**

Microbarograph - ESRL Hi-Res Microbarograph, Walla Walla - Reviewed Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

McCaffrey, Katherine

High-precision barometers (Paroscientific 6000-16B-IS) are combined with Nishiyama-Bedard Quad Disk pressure probes, measuring pressure (mb) at the surface, nominally 2 m above ground level. Data are sampled at 20 Hz for potential studies of turbulence. The sensors' high accuracy makes them useful for determining horizontal pressure gradients and their relation to wind ramp events, as well as the temporal variability of pressure associated with mountain wakes and waves. **Note different ASCII file formats for Goldendale (z04) and Walla Walla (z09) sites.**

Microbarograph - ESRL Hi-Res Microbarograph, Wasco Airport - Raw Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

McCaffrey, Katherine

High-precision barometers (Paroscientific 6000-16B-IS) are combined with Nishiyama-Bedard Quad Disk pressure probes, measuring pressure (mb) at the surface, nominally 2 m above ground level. Data are sampled at 20 Hz for potential studies of turbulence. The sensors' high accuracy makes them useful for determining horizontal pressure gradients and their relation to wind ramp events, as well as the temporal variability of pressure associated with mountain wakes and waves. **Note different ASCII file formats for Goldendale (z04) and Walla Walla (z09) sites.**

Microbarograph - ESRL Hi-Res Microbarograph, Boardman - Raw Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

McCaffrey, Katherine

High-precision barometers (Paroscientific 6000-16B-IS) are combined with Nishiyama-Bedard Quad Disk pressure probes, measuring pressure (mb) at the surface, nominally 2 m above ground level. Data are sampled at 20 Hz for potential studies of turbulence. The sensors' high accuracy makes them useful for determining horizontal pressure gradients and their relation to wind ramp events, as well as the temporal variability of pressure associated with mountain wakes and waves. **Note different ASCII file formats for Goldendale (z04) and Walla Walla (z09) sites.**

Microbarograph - ESRL Hi-Res Microbarograph, John Day - Raw Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

McCaffrey, Katherine

High-precision barometers (Paroscientific 6000-16B-IS) are combined with Nishiyama-Bedard Quad Disk pressure probes, measuring pressure (mb) at the surface, nominally 2 m above ground level. Data are sampled at 20 Hz for potential studies of turbulence. The sensors' high accuracy makes them useful for determining horizontal pressure gradients and their relation to wind ramp events, as well as the temporal variability of pressure associated with mountain wakes and waves. **Note different ASCII file formats for Goldendale (z04) and Walla Walla (z09) sites.**

Microbarograph - ESRL Hi-Res Microbarograph, Hood River - Raw Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

McCaffrey, Katherine

High-precision barometers (Paroscientific 6000-16B-IS) are combined with Nishiyama-Bedard Quad Disk pressure probes, measuring pressure (mb) at the surface, nominally 2 m above ground level. Data are sampled at 20 Hz for potential studies of turbulence. The sensors' high accuracy makes them useful for determining horizontal pressure gradients and their relation to wind ramp events, as well as the temporal variability of pressure associated with mountain wakes and waves. **Note different ASCII file formats for Goldendale (z04) and Walla Walla (z09) sites.**

Microbarograph - ESRL Hi-Res Microbarograph, Umatilla - Reviewed Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

McCaffrey, Katherine

High-precision barometers (Paroscientific 6000-16B-IS) are combined with Nishiyama-Bedard Quad Disk pressure probes, measuring pressure (mb) at the surface, nominally 2 m above ground level. Data are sampled at 20 Hz for potential studies of turbulence. The sensors' high accuracy makes them useful for determining horizontal pressure gradients and their relation to wind ramp events, as well as the temporal variability of pressure associated with mountain wakes and waves. **Note different ASCII file formats for Goldendale (z04) and Walla Walla (z09) sites.**

Microbarograph - ESRL Hi-Res Microbarograph, Boardman - Reviewed Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

McCaffrey, Katherine

High-precision barometers (Paroscientific 6000-16B-IS) are combined with Nishiyama-Bedard Quad Disk pressure probes, measuring pressure (mb) at the surface, nominally 2 m above ground level. Data are sampled at 20 Hz for potential studies of turbulence. The sensors' high accuracy makes them useful for determining horizontal pressure gradients and their relation to wind ramp events, as well as the temporal variability of pressure associated with mountain wakes and waves. **Note different ASCII file formats for Goldendale (z04) and Walla Walla (z09) sites.**

Microbarograph - ESRL Hi-Res Microbarograph, Bonneville - Reviewed Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

McCaffrey, Katherine

High-precision barometers (Paroscientific 6000-16B-IS) are combined with Nishiyama-Bedard Quad Disk pressure probes, measuring pressure (mb) at the surface, nominally 2 m above ground level. Data are sampled at 20 Hz for potential studies of turbulence. The sensors' high accuracy makes them useful for determining horizontal pressure gradients and their relation to wind ramp events, as well as the temporal variability of pressure associated with mountain wakes and waves. **Note different ASCII file formats for Goldendale (z04) and Walla Walla (z09) sites.**

Microbarograph - ESRL Hi-Res Microbarograph, Bonneville - Raw Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

McCaffrey, Katherine

High-precision barometers (Paroscientific 6000-16B-IS) are combined with Nishiyama-Bedard Quad Disk pressure probes, measuring pressure (mb) at the surface, nominally 2 m above ground level. Data are sampled at 20 Hz for potential studies of turbulence. The sensors' high accuracy makes them useful for determining horizontal pressure gradients and their relation to wind ramp events, as well as the temporal variability of pressure associated with mountain wakes and waves. **Note different ASCII file formats for Goldendale (z04) and Walla Walla (z09) sites.**

Microbarograph - ESRL Hi-Res Microbarograph, Umatilla - Raw Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

McCaffrey, Katherine

High-precision barometers (Paroscientific 6000-16B-IS) are combined with Nishiyama-Bedard Quad Disk pressure probes, measuring pressure (mb) at the surface, nominally 2 m above ground level. Data are sampled at 20 Hz for potential studies of turbulence. The sensors' high accuracy makes them useful for determining horizontal pressure gradients and their relation to wind ramp events, as well as the temporal variability of pressure associated with mountain wakes and waves. **Note different ASCII file formats for Goldendale (z04) and Walla Walla (z09) sites.**

Microbarograph - ESRL Hi-Res Microbarograph, John Day - Reviewed Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

McCaffrey, Katherine

High-precision barometers (Paroscientific 6000-16B-IS) are combined with Nishiyama-Bedard Quad Disk pressure probes, measuring pressure (mb) at the surface, nominally 2 m above ground level. Data are sampled at 20 Hz for potential studies of turbulence. The sensors' high accuracy makes them useful for determining horizontal pressure gradients and their relation to wind ramp events, as well as the temporal variability of pressure associated with mountain wakes and waves. **Note different ASCII file formats for Goldendale (z04) and Walla Walla (z09) sites.**

Microbarograph - ESRL Hi-Res Microbarograph, Hood River - Reviewed Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

McCaffrey, Katherine

High-precision barometers (Paroscientific 6000-16B-IS) are combined with Nishiyama-Bedard Quad Disk pressure probes, measuring pressure (mb) at the surface, nominally 2 m above ground level. Data are sampled at 20 Hz for potential studies of turbulence. The sensors' high accuracy makes them useful for determining horizontal pressure gradients and their relation to wind ramp events, as well as the temporal variability of pressure associated with mountain wakes and waves. **Note different ASCII file formats for Goldendale (z04) and Walla Walla (z09) sites.**

Prose memory deficits associated with schizophrenia.

PubMed

Lee, Tatia M C; Chan, Michelle W C; Chan, Chetwyn C H; Gao, Junling; Wang, Kai; Chen, Eric Y H

2006-01-31

Memory of contextual information is essential to one's quality of living. This study investigated if the different components of prose memory, across three recall conditions: first learning trial immediate recall, fifth learning trial immediate recall, and 30-min delayed recall, are differentially impaired in people with schizophrenia, relative to healthy controls. A total of 39 patients with schizophrenia and 39 matched healthy controls were recruited. Their prose memory, in terms of recall accuracy, temporal sequence, recognition accuracy and false positives, commission of distortions, and rates of learning, forgetting, and retention were tested and compared. After controlling for the level of intelligence and depression, the patients with schizophrenia were found to commit more distortions. Furthermore, they performed poorer on recall accuracy and temporal sequence accuracy only during the first initial immediate recall. On the other hand, the rates of forgetting/retention and recognition accuracy were comparable between the two groups. These findings suggest that people with schizophrenia could be benefited by repeated exposure to the materials to be remembered. These results may have important implications for rehabilitation of verbal declarative memory deficits in schizophrenia.

a Comparison Study of Different Kernel Functions for Svm-Based Classification of Multi-Temporal Polarimetry SAR Data

NASA Astrophysics Data System (ADS)

Yekkehkhany, B.; Safari, A.; Homayouni, S.; Hasanlou, M.

2014-10-01

In this paper, a framework is developed based on Support Vector Machines (SVM) for crop classification using polarimetric features extracted from multi-temporal Synthetic Aperture Radar (SAR) imageries. The multi-temporal integration of data not only improves the overall retrieval accuracy but also provides more reliable estimates with respect to single-date data. Several kernel functions are employed and compared in this study for mapping the input space to higher Hilbert dimension space. These kernel functions include linear, polynomials and Radial Based Function (RBF). The method is applied to several UAVSAR L-band SAR images acquired over an agricultural area near Winnipeg, Manitoba, Canada. In this research, the temporal alpha features of H/A/α decomposition method are used in classification. The experimental tests show an SVM classifier with RBF kernel for three dates of data increases the Overall Accuracy (OA) to up to 3% in comparison to using linear kernel function, and up to 1% in comparison to a 3rd degree polynomial kernel function.

Everyday conversation requires cognitive inference: neural bases of comprehending implicated meanings in conversations.

PubMed

Jang, Gijeong; Yoon, Shin-ae; Lee, Sung-Eun; Park, Haeil; Kim, Joohan; Ko, Jeong Hoon; Park, Hae-Jeong

2013-11-01

In ordinary conversations, literal meanings of an utterance are often quite different from implicated meanings and the inference about implicated meanings is essentially required for successful comprehension of the speaker's utterances. Inference of finding implicated meanings is based on the listener's assumption that the conversational partner says only relevant matters according to the maxim of relevance in Grice's theory of conversational implicature. To investigate the neural correlates of comprehending implicated meanings under the maxim of relevance, a total of 23 participants underwent an fMRI task with a series of conversational pairs, each consisting of a question and an answer. The experimental paradigm was composed of three conditions: explicit answers, moderately implicit answers, and highly implicit answers. Participants were asked to decide whether the answer to the Yes/No question meant 'Yes' or 'No'. Longer reaction time was required for the highly implicit answers than for the moderately implicit answers without affecting the accuracy. The fMRI results show that the left anterior temporal lobe, left angular gyrus, and left posterior middle temporal gyrus had stronger activation in both moderately and highly implicit conditions than in the explicit condition. Comprehension of highly implicit answers had increased activations in additional regions including the left inferior frontal gyrus, left medial prefrontal cortex, left posterior cingulate cortex and right anterior temporal lobe. The activation results indicate involvement of these regions in the inference process to build coherence between literally irrelevant but pragmatically associated utterances under the maxim of relevance. Especially, the left anterior temporal lobe showed high sensitivity to the level of implicitness and showed increased activation for highly versus moderately implicit conditions, which imply its central role in inference such as semantic integration. The right hemisphere activation, uniquely found in the anterior temporal lobe for highly implicit utterances, suggests its competence for integrating distant concepts in implied utterances under the relevance principle. Copyright © 2013 Elsevier Inc. All rights reserved.

In Situ Methods, Infrastructures, and Applications on High Performance Computing Platforms, a State-of-the-art (STAR) Report

DOE PAGES

Bethel, EW; Bauer, A; Abbasi, H; ...

2016-06-10

The considerable interest in the high performance computing (HPC) community regarding analyzing and visualization data without first writing to disk, i.e., in situ processing, is due to several factors. First is an I/O cost savings, where data is analyzed /visualized while being generated, without first storing to a filesystem. Second is the potential for increased accuracy, where fine temporal sampling of transient analysis might expose some complex behavior missed in coarse temporal sampling. Third is the ability to use all available resources, CPU’s and accelerators, in the computation of analysis products. This STAR paper brings together researchers, developers and practitionersmore » using in situ methods in extreme-scale HPC with the goal to present existing methods, infrastructures, and a range of computational science and engineering applications using in situ analysis and visualization.« less

Spatiotemporal attention operator using isotropic contrast and regional homogeneity

NASA Astrophysics Data System (ADS)

Palenichka, Roman; Lakhssassi, Ahmed; Zaremba, Marek

2011-04-01

A multiscale operator for spatiotemporal isotropic attention is proposed to reliably extract attention points during image sequence analysis. Its consecutive local maxima indicate attention points as the centers of image fragments of variable size with high intensity contrast, region homogeneity, regional shape saliency, and temporal change presence. The scale-adaptive estimation of temporal change (motion) and its aggregation with the regional shape saliency contribute to the accurate determination of attention points in image sequences. Multilocation descriptors of an image sequence are extracted at the attention points in the form of a set of multidimensional descriptor vectors. A fast recursive implementation is also proposed to make the operator's computational complexity independent from the spatial scale size, which is the window size in the spatial averaging filter. Experiments on the accuracy of attention-point detection have proved the operator consistency and its high potential for multiscale feature extraction from image sequences.

IMPROVING THE ACCURACY OF HISTORIC SATELLITE IMAGE CLASSIFICATION BY COMBINING LOW-RESOLUTION MULTISPECTRAL DATA WITH HIGH-RESOLUTION PANCHROMATIC DATA

DOE Office of Scientific and Technical Information (OSTI.GOV)

Getman, Daniel J

2008-01-01

Many attempts to observe changes in terrestrial systems over time would be significantly enhanced if it were possible to improve the accuracy of classifications of low-resolution historic satellite data. In an effort to examine improving the accuracy of historic satellite image classification by combining satellite and air photo data, two experiments were undertaken in which low-resolution multispectral data and high-resolution panchromatic data were combined and then classified using the ECHO spectral-spatial image classification algorithm and the Maximum Likelihood technique. The multispectral data consisted of 6 multispectral channels (30-meter pixel resolution) from Landsat 7. These data were augmented with panchromatic datamore » (15m pixel resolution) from Landsat 7 in the first experiment, and with a mosaic of digital aerial photography (1m pixel resolution) in the second. The addition of the Landsat 7 panchromatic data provided a significant improvement in the accuracy of classifications made using the ECHO algorithm. Although the inclusion of aerial photography provided an improvement in accuracy, this improvement was only statistically significant at a 40-60% level. These results suggest that once error levels associated with combining aerial photography and multispectral satellite data are reduced, this approach has the potential to significantly enhance the precision and accuracy of classifications made using historic remotely sensed data, as a way to extend the time range of efforts to track temporal changes in terrestrial systems.« less

Auditory and motor imagery modulate learning in music performance

PubMed Central

Brown, Rachel M.; Palmer, Caroline

2013-01-01

Skilled performers such as athletes or musicians can improve their performance by imagining the actions or sensory outcomes associated with their skill. Performers vary widely in their auditory and motor imagery abilities, and these individual differences influence sensorimotor learning. It is unknown whether imagery abilities influence both memory encoding and retrieval. We examined how auditory and motor imagery abilities influence musicians' encoding (during Learning, as they practiced novel melodies), and retrieval (during Recall of those melodies). Pianists learned melodies by listening without performing (auditory learning) or performing without sound (motor learning); following Learning, pianists performed the melodies from memory with auditory feedback (Recall). During either Learning (Experiment 1) or Recall (Experiment 2), pianists experienced either auditory interference, motor interference, or no interference. Pitch accuracy (percentage of correct pitches produced) and temporal regularity (variability of quarter-note interonset intervals) were measured at Recall. Independent tests measured auditory and motor imagery skills. Pianists' pitch accuracy was higher following auditory learning than following motor learning and lower in motor interference conditions (Experiments 1 and 2). Both auditory and motor imagery skills improved pitch accuracy overall. Auditory imagery skills modulated pitch accuracy encoding (Experiment 1): Higher auditory imagery skill corresponded to higher pitch accuracy following auditory learning with auditory or motor interference, and following motor learning with motor or no interference. These findings suggest that auditory imagery abilities decrease vulnerability to interference and compensate for missing auditory feedback at encoding. Auditory imagery skills also influenced temporal regularity at retrieval (Experiment 2): Higher auditory imagery skill predicted greater temporal regularity during Recall in the presence of auditory interference. Motor imagery aided pitch accuracy overall when interference conditions were manipulated at encoding (Experiment 1) but not at retrieval (Experiment 2). Thus, skilled performers' imagery abilities had distinct influences on encoding and retrieval of musical sequences. PMID:23847495

Comparison of Object-Based Image Analysis Approaches to Mapping New Buildings in Accra, Ghana Using Multi-Temporal QuickBird Satellite Imagery

PubMed Central

Tsai, Yu Hsin; Stow, Douglas; Weeks, John

2013-01-01

The goal of this study was to map and quantify the number of newly constructed buildings in Accra, Ghana between 2002 and 2010 based on high spatial resolution satellite image data. Two semi-automated feature detection approaches for detecting and mapping newly constructed buildings based on QuickBird very high spatial resolution satellite imagery were analyzed: (1) post-classification comparison; and (2) bi-temporal layerstack classification. Feature Analyst software based on a spatial contextual classifier and ENVI Feature Extraction that uses a true object-based image analysis approach of image segmentation and segment classification were evaluated. Final map products representing new building objects were compared and assessed for accuracy using two object-based accuracy measures, completeness and correctness. The bi-temporal layerstack method generated more accurate results compared to the post-classification comparison method due to less confusion with background objects. The spectral/spatial contextual approach (Feature Analyst) outperformed the true object-based feature delineation approach (ENVI Feature Extraction) due to its ability to more reliably delineate individual buildings of various sizes. Semi-automated, object-based detection followed by manual editing appears to be a reliable and efficient approach for detecting and enumerating new building objects. A bivariate regression analysis was performed using neighborhood-level estimates of new building density regressed on a census-derived measure of socio-economic status, yielding an inverse relationship with R2 = 0.31 (n = 27; p = 0.00). The primary utility of the new building delineation results is to support spatial analyses of land cover and land use and demographic change. PMID:24415810

COMPARISON OF DIRECT AND INDIRECT IMPACTS OF FECAL CONTAMINATION IN TWO DIFFERENT WATERSHEDS

EPA Science Inventory

There are many environmental parameters that could affect the accuracy of microbial source tracking (MST) methods. Spatial and temporal determinants are among the most common factors missing in MST studies. To understand how spatial and temporal variability affect the level of fe...

Evaluating an Automated Approach for Monitoring Forest Disturbances in the Pacific Northwest from Logging, Fire and Insect Outbreaks with Landsat Time Series Data

NASA Technical Reports Server (NTRS)

R.Neigh, Christopher S.; Bolton, Douglas K.; Williams, Jennifer J.; Diabate, Mouhamad

2014-01-01

Forests are the largest aboveground sink for atmospheric carbon (C), and understanding how they change through time is critical to reduce our C-cycle uncertainties. We investigated a strong decline in Normalized Difference Vegetation Index (NDVI) from 1982 to 1991 in Pacific Northwest forests, observed with the National Ocean and Atmospheric Administration's (NOAA) series of Advanced Very High Resolution Radiometers (AVHRRs). To understand the causal factors of this decline, we evaluated an automated classification method developed for Landsat time series stacks (LTSS) to map forest change. This method included: (1) multiple disturbance index thresholds; and (2) a spectral trajectory-based image analysis with multiple confidence thresholds. We produced 48 maps and verified their accuracy with air photos, monitoring trends in burn severity data and insect aerial detection survey data. Area-based accuracy estimates for change in forest cover resulted in producer's and user's accuracies of 0.21 +/- 0.06 to 0.38 +/- 0.05 for insect disturbance, 0.23 +/- 0.07 to 1 +/- 0 for burned area and 0.74 +/- 0.03 to 0.76 +/- 0.03 for logging. We believe that accuracy was low for insect disturbance because air photo reference data were temporally sparse, hence missing some outbreaks, and the annual anniversary time step is not dense enough to track defoliation and progressive stand mortality. Producer's and user's accuracy for burned area was low due to the temporally abrupt nature of fire and harvest with a similar response of spectral indices between the disturbance index and normalized burn ratio. We conclude that the spectral trajectory approach also captures multi-year stress that could be caused by climate, acid deposition, pathogens, partial harvest, thinning, etc. Our study focused on understanding the transferability of previously successful methods to new ecosystems and found that this automated method does not perform with the same accuracy in Pacific Northwest forests. Using a robust accuracy assessment, we demonstrate the difficulty of transferring change attribution methods to other ecosystems, which has implications for the development of automated detection/attribution approaches. Widespread disturbance was found within AVHRR-negative anomalies, but identifying causal factors in LTSS with adequate mapping accuracy for fire and insects proved to be elusive. Our results provide a background framework for future studies to improve methods for the accuracy assessment of automated LTSS classifications.

Four Decades of Microwave Satellite Soil Moisture Observations: Product validation and inter-satellite comparisons

NASA Astrophysics Data System (ADS)

Lanka, K.; Pan, M.; Wanders, N.; Kumar, D. N.; Wood, E. F.

2017-12-01

The satellite based passive and active microwave sensors enhanced our ability to retrieve soil moisture at global scales. It has been almost four decades since the first passive microwave satellite sensor was launched in 1978. Since then soil moisture has gained considerable attention in hydro-meteorological, climate, and agricultural research resulting in the deployment of two dedicated missions in the last decade, SMOS and SMAP. Signifying the four decades of microwave remote sensing of soil moisture, this work aims to present an overview of how our knowledge in this field has improved in terms of the design of sensors and their accuracy of retrieving soil moisture. We considered daily coverage, temporal performance, and spatial performance to assess the accuracy of products corresponding to eight passive sensors (SMMR, SSM/I, TMI, AMSR-E, WindSAT, AMSR2, SMOS and SMAP), two active sensors (ERS-Scatterometer, MetOp-ASCAT), and one active/passive merged soil moisture product (ESA-CCI combined product), using 1058 ISMN in-situ stations and the VIC LSM soil moisture simulations (VICSM) over the CONUS. Our analysis indicated that the daily coverage has increased from 30 % during 1980s to 85 % (during non-winter months) with the launch of dedicated soil moisture missions SMOS and SMAP. The temporal validation of passive and active soil moisture products with the ISMN data place the range of median RMSE as 0.06-0.10 m3/m3 and median correlation as 0.20-0.68. When TMI, AMSR-E and WindSAT are evaluated, the AMSR-E sensor is found to have produced the brightness temperatures with better quality, given that these sensors are paired with same retrieval algorithm (LPRM). The ASCAT product shows a significant improvement during the temporal validation of retrievals compared to its predecessor ERS, thanks to enhanced sensor configuration. The SMAP mission, through its improved sensor design and RFI handling, shows a high retrieval accuracy under all-topography conditions. Although the retrievals from the SMOS mission are affected by issues such as RFI, the accuracy is still comparable to or better than that of AMSR-E and ASCAT sensors. All soil moisture products have indicated better agreement with the ISMN data than the VICSM, which indicate that they produce soil moisture with better accuracy than the VICSM over the CONUS.

Estimation of sub-pixel water area on Tibet plateau using multiple endmembers spectral mixture spectral analysis from MODIS data

NASA Astrophysics Data System (ADS)

Cui, Qian; Shi, Jiancheng; Xu, Yuanliu

2011-12-01

Water is the basic needs for human society, and the determining factor of stability of ecosystem as well. There are lots of lakes on Tibet Plateau, which will lead to flood and mudslide when the water expands sharply. At present, water area is extracted from TM or SPOT data for their high spatial resolution; however, their temporal resolution is insufficient. MODIS data have high temporal resolution and broad coverage. So it is valuable resource for detecting the change of water area. Because of its low spatial resolution, mixed-pixels are common. In this paper, four spectral libraries are built using MOD09A1 product, based on that, water body is extracted in sub-pixels utilizing Multiple Endmembers Spectral Mixture Analysis (MESMA) using MODIS daily reflectance data MOD09GA. The unmixed result is comparing with contemporaneous TM data and it is proved that this method has high accuracy.

Spatial and temporal microbial pollution patterns in a tropical estuary during high and low river flow conditions.

PubMed

Wiegner, T N; Edens, C J; Abaya, L M; Carlson, K M; Lyon-Colbert, A; Molloy, S L

2017-01-30

Spatial and temporal patterns of coastal microbial pollution are not well documented. Our study examined these patterns through measurements of fecal indicator bacteria (FIB), nutrients, and physiochemical parameters in Hilo Bay, Hawai'i, during high and low river flow. >40% of samples tested positive for the human-associated Bacteroides marker, with highest percentages near rivers. Other FIB were also higher near rivers, but only Clostridium perfringens concentrations were related to discharge. During storms, FIB concentrations were three times to an order of magnitude higher, and increased with decreasing salinity and water temperature, and increasing turbidity. These relationships and high spatial resolution data for these parameters were used to create Enterococcus spp. and C. perfringens maps that predicted exceedances with 64% and 95% accuracy, respectively. Mapping microbial pollution patterns and predicting exceedances is a valuable tool that can improve water quality monitoring and aid in visualizing FIB hotspots for management actions. Copyright © 2016 Elsevier Ltd. All rights reserved.

Estimation of Temporal Gait Parameters Using a Wearable Microphone-Sensor-Based System

PubMed Central

Wang, Cheng; Wang, Xiangdong; Long, Zhou; Yuan, Jing; Qian, Yueliang; Li, Jintao

2016-01-01

Most existing wearable gait analysis methods focus on the analysis of data obtained from inertial sensors. This paper proposes a novel, low-cost, wireless and wearable gait analysis system which uses microphone sensors to collect footstep sound signals during walking. This is the first time a microphone sensor is used as a wearable gait analysis device as far as we know. Based on this system, a gait analysis algorithm for estimating the temporal parameters of gait is presented. The algorithm fully uses the fusion of two feet footstep sound signals and includes three stages: footstep detection, heel-strike event and toe-on event detection, and calculation of gait temporal parameters. Experimental results show that with a total of 240 data sequences and 1732 steps collected using three different gait data collection strategies from 15 healthy subjects, the proposed system achieves an average 0.955 F1-measure for footstep detection, an average 94.52% accuracy rate for heel-strike detection and 94.25% accuracy rate for toe-on detection. Using these detection results, nine temporal related gait parameters are calculated and these parameters are consistent with their corresponding normal gait temporal parameters and labeled data calculation results. The results verify the effectiveness of our proposed system and algorithm for temporal gait parameter estimation. PMID:27999321

High Resolution Insights into Snow Distribution Provided by Drone Photogrammetry

NASA Astrophysics Data System (ADS)

Redpath, T.; Sirguey, P. J.; Cullen, N. J.; Fitzsimons, S.

2017-12-01

Dynamic in time and space, New Zealand's seasonal snow is largely confined to remote alpine areas, complicating ongoing in situ measurement and characterisation. Improved understanding and modeling of the seasonal snowpack requires fine scale resolution of snow distribution and spatial variability. The potential of remotely piloted aircraft system (RPAS) photogrammetry to resolve spatial and temporal variability of snow depth and water equivalent in a New Zealand alpine catchment is assessed in the Pisa Range, Central Otago. This approach yielded orthophotomosaics and digital surface models (DSM) at 0.05 and 0.15 m spatial resolution, respectively. An autumn reference DSM allowed mapping of winter (02/08/2016) and spring (10/09/2016) snow depth at 0.15 m spatial resolution, via DSM differencing. The consistency and accuracy of the RPAS-derived surface was assessed by comparison of snow-free regions of the spring and autumn DSMs, while accuracy of RPAS retrieved snow depth was assessed with 86 in situ snow probe measurements. Results show a mean vertical residual of 0.024 m between DSMs acquired in autumn and spring. This residual approximated a Laplace distribution, reflecting the influence of large outliers on the small overall bias. Propagation of errors associated with successive DSMs saw snow depth mapped with an accuracy of ± 0.09 m (95% c.l.). Comparing RPAS and in situ snow depth measurements revealed the influence of geo-location uncertainty and interactions between vegetation and the snowpack on snow depth uncertainty and bias. Semi-variogram analysis revealed that the RPAS outperformed systematic in situ measurements in resolving fine scale spatial variability. Despite limitations accompanying RPAS photogrammetry, this study demonstrates a repeatable means of accurately mapping snow depth for an entire, yet relatively small, hydrological basin ( 0.5 km2), at high resolution. Resolving snowpack features associated with re-distribution and preferential accumulation and ablation, snow depth maps provide geostatistically robust insights into seasonal snow processes, with unprecedented detail. Such data may enhance understanding of physical processes controlling spatial and temporal distribution of seasonal snow, and their relative importance at varying spatial and temporal scales.

Single particle tracking through highly scattering media with multiplexed two-photon excitation

NASA Astrophysics Data System (ADS)

Perillo, Evan; Liu, Yen-Liang; Liu, Cong; Yeh, Hsin-Chih; Dunn, Andrew K.

2015-03-01

3D single-particle tracking (SPT) has been a pivotal tool to furthering our understanding of dynamic cellular processes in complex biological systems, with a molecular localization accuracy (10-100 nm) often better than the diffraction limit of light. However, current SPT techniques utilize either CCDs or a confocal detection scheme which not only suffer from poor temporal resolution but also limit tracking to a depth less than one scattering mean free path in the sample (typically <15μm). In this report we highlight our novel design for a spatiotemporally multiplexed two-photon microscope which is able to reach sub-diffraction-limit tracking accuracy and sub-millisecond temporal resolution, but with a dramatically extended SPT range of up to 200 μm through dense cell samples. We have validated our microscope by tracking (1) fluorescent nanoparticles in a prescribed motion inside gelatin gel (with 1% intralipid) and (2) labeled single EGFR complexes inside skin cancer spheroids (at least 8 layers of cells thick) for ~10 minutes. Furthermore we discuss future capabilities of our multiplexed two-photon microscope design, specifically to the extension of (1) simultaneous multicolor tracking (i.e. spatiotemporal co-localization analysis) and (2) FRET studies (i.e. lifetime analysis). The high resolution, high depth penetration, and multicolor features of this microscope make it well poised to study a variety of molecular scale dynamics in the cell, especially related to cellular trafficking studies with in vitro tumor models and in vivo.

Modeling Pathologic Response of Esophageal Cancer to Chemoradiation Therapy Using Spatial-Temporal {sup 18}F-FDG PET Features, Clinical Parameters, and Demographics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Hao; Tan, Shan; Department of Control Science and Engineering, Huazhong University of Science and Technology, Wuhan

2014-01-01

Purpose: To construct predictive models using comprehensive tumor features for the evaluation of tumor response to neoadjuvant chemoradiation therapy (CRT) in patients with esophageal cancer. Methods and Materials: This study included 20 patients who underwent trimodality therapy (CRT + surgery) and underwent {sup 18}F-fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) both before and after CRT. Four groups of tumor features were examined: (1) conventional PET/CT response measures (eg, standardized uptake value [SUV]{sub max}, tumor diameter); (2) clinical parameters (eg, TNM stage, histology) and demographics; (3) spatial-temporal PET features, which characterize tumor SUV intensity distribution, spatial patterns, geometry, and associated changesmore » resulting from CRT; and (4) all features combined. An optimal feature set was identified with recursive feature selection and cross-validations. Support vector machine (SVM) and logistic regression (LR) models were constructed for prediction of pathologic tumor response to CRT, cross-validations being used to avoid model overfitting. Prediction accuracy was assessed by area under the receiver operating characteristic curve (AUC), and precision was evaluated by confidence intervals (CIs) of AUC. Results: When applied to the 4 groups of tumor features, the LR model achieved AUCs (95% CI) of 0.57 (0.10), 0.73 (0.07), 0.90 (0.06), and 0.90 (0.06). The SVM model achieved AUCs (95% CI) of 0.56 (0.07), 0.60 (0.06), 0.94 (0.02), and 1.00 (no misclassifications). With the use of spatial-temporal PET features combined with conventional PET/CT measures and clinical parameters, the SVM model achieved very high accuracy (AUC 1.00) and precision (no misclassifications)—results that were significantly better than when conventional PET/CT measures or clinical parameters and demographics alone were used. For groups with many tumor features (groups 3 and 4), the SVM model achieved significantly higher accuracy than did the LR model. Conclusions: The SVM model that used all features including spatial-temporal PET features accurately and precisely predicted pathologic tumor response to CRT in esophageal cancer.« less

Spatio-temporal alignment of pedobarographic image sequences.

PubMed

Oliveira, Francisco P M; Sousa, Andreia; Santos, Rubim; Tavares, João Manuel R S

2011-07-01

This article presents a methodology to align plantar pressure image sequences simultaneously in time and space. The spatial position and orientation of a foot in a sequence are changed to match the foot represented in a second sequence. Simultaneously with the spatial alignment, the temporal scale of the first sequence is transformed with the aim of synchronizing the two input footsteps. Consequently, the spatial correspondence of the foot regions along the sequences as well as the temporal synchronizing is automatically attained, making the study easier and more straightforward. In terms of spatial alignment, the methodology can use one of four possible geometric transformation models: rigid, similarity, affine, or projective. In the temporal alignment, a polynomial transformation up to the 4th degree can be adopted in order to model linear and curved time behaviors. Suitable geometric and temporal transformations are found by minimizing the mean squared error (MSE) between the input sequences. The methodology was tested on a set of real image sequences acquired from a common pedobarographic device. When used in experimental cases generated by applying geometric and temporal control transformations, the methodology revealed high accuracy. In addition, the intra-subject alignment tests from real plantar pressure image sequences showed that the curved temporal models produced better MSE results (P < 0.001) than the linear temporal model. This article represents an important step forward in the alignment of pedobarographic image data, since previous methods can only be applied on static images.

Quantification of errors induced by temporal resolution on Lagrangian particles in an eddy-resolving model

NASA Astrophysics Data System (ADS)

Qin, Xuerong; van Sebille, Erik; Sen Gupta, Alexander

2014-04-01

Lagrangian particle tracking within ocean models is an important tool for the examination of ocean circulation, ventilation timescales and connectivity and is increasingly being used to understand ocean biogeochemistry. Lagrangian trajectories are obtained by advecting particles within velocity fields derived from hydrodynamic ocean models. For studies of ocean flows on scales ranging from mesoscale up to basin scales, the temporal resolution of the velocity fields should ideally not be more than a few days to capture the high frequency variability that is inherent in mesoscale features. However, in reality, the model output is often archived at much lower temporal resolutions. Here, we quantify the differences in the Lagrangian particle trajectories embedded in velocity fields of varying temporal resolution. Particles are advected from 3-day to 30-day averaged fields in a high-resolution global ocean circulation model. We also investigate whether adding lateral diffusion to the particle movement can compensate for the reduced temporal resolution. Trajectory errors reveal the expected degradation of accuracy in the trajectory positions when decreasing the temporal resolution of the velocity field. Divergence timescales associated with averaging velocity fields up to 30 days are faster than the intrinsic dispersion of the velocity fields but slower than the dispersion caused by the interannual variability of the velocity fields. In experiments focusing on the connectivity along major currents, including western boundary currents, the volume transport carried between two strategically placed sections tends to increase with increased temporal averaging. Simultaneously, the average travel times tend to decrease. Based on these two bulk measured diagnostics, Lagrangian experiments that use temporal averaging of up to nine days show no significant degradation in the flow characteristics for a set of six currents investigated in more detail. The addition of random-walk-style diffusion does not mitigate the errors introduced by temporal averaging for large-scale open ocean Lagrangian simulations.

Machine learning approaches to diagnosis and laterality effects in semantic dementia discourse.

PubMed

Garrard, Peter; Rentoumi, Vassiliki; Gesierich, Benno; Miller, Bruce; Gorno-Tempini, Maria Luisa

2014-06-01

Advances in automatic text classification have been necessitated by the rapid increase in the availability of digital documents. Machine learning (ML) algorithms can 'learn' from data: for instance a ML system can be trained on a set of features derived from written texts belonging to known categories, and learn to distinguish between them. Such a trained system can then be used to classify unseen texts. In this paper, we explore the potential of the technique to classify transcribed speech samples along clinical dimensions, using vocabulary data alone. We report the accuracy with which two related ML algorithms [naive Bayes Gaussian (NBG) and naive Bayes multinomial (NBM)] categorized picture descriptions produced by: 32 semantic dementia (SD) patients versus 10 healthy, age-matched controls; and SD patients with left- (n = 21) versus right-predominant (n = 11) patterns of temporal lobe atrophy. We used information gain (IG) to identify the vocabulary features that were most informative to each of these two distinctions. In the SD versus control classification task, both algorithms achieved accuracies of greater than 90%. In the right- versus left-temporal lobe predominant classification, NBM achieved a high level of accuracy (88%), but this was achieved by both NBM and NBG when the features used in the training set were restricted to those with high values of IG. The most informative features for the patient versus control task were low frequency content words, generic terms and components of metanarrative statements. For the right versus left task the number of informative lexical features was too small to support any specific inferences. An enriched feature set, including values derived from Quantitative Production Analysis (QPA) may shed further light on this little understood distinction. Copyright © 2013 Elsevier Ltd. All rights reserved.

Interhemispheric coupling between the posterior sylvian regions impacts successful auditory temporal order judgment.

PubMed

Bernasconi, Fosco; Grivel, Jeremy; Murray, Micah M; Spierer, Lucas

2010-07-01

Accurate perception of the temporal order of sensory events is a prerequisite in numerous functions ranging from language comprehension to motor coordination. We investigated the spatio-temporal brain dynamics of auditory temporal order judgment (aTOJ) using electrical neuroimaging analyses of auditory evoked potentials (AEPs) recorded while participants completed a near-threshold task requiring spatial discrimination of left-right and right-left sound sequences. AEPs to sound pairs modulated topographically as a function of aTOJ accuracy over the 39-77ms post-stimulus period, indicating the engagement of distinct configurations of brain networks during early auditory processing stages. Source estimations revealed that accurate and inaccurate performance were linked to bilateral posterior sylvian regions activity (PSR). However, activity within left, but not right, PSR predicted behavioral performance suggesting that left PSR activity during early encoding phases of pairs of auditory spatial stimuli appears critical for the perception of their order of occurrence. Correlation analyses of source estimations further revealed that activity between left and right PSR was significantly correlated in the inaccurate but not accurate condition, indicating that aTOJ accuracy depends on the functional decoupling between homotopic PSR areas. These results support a model of temporal order processing wherein behaviorally relevant temporal information--i.e. a temporal 'stamp'--is extracted within the early stages of cortical processes within left PSR but critically modulated by inputs from right PSR. We discuss our results with regard to current models of temporal of temporal order processing, namely gating and latency mechanisms. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

MRI-assisted PET motion correction for neurologic studies in an integrated MR-PET scanner.

PubMed

Catana, Ciprian; Benner, Thomas; van der Kouwe, Andre; Byars, Larry; Hamm, Michael; Chonde, Daniel B; Michel, Christian J; El Fakhri, Georges; Schmand, Matthias; Sorensen, A Gregory

2011-01-01

Head motion is difficult to avoid in long PET studies, degrading the image quality and offsetting the benefit of using a high-resolution scanner. As a potential solution in an integrated MR-PET scanner, the simultaneously acquired MRI data can be used for motion tracking. In this work, a novel algorithm for data processing and rigid-body motion correction (MC) for the MRI-compatible BrainPET prototype scanner is described, and proof-of-principle phantom and human studies are presented. To account for motion, the PET prompt and random coincidences and sensitivity data for postnormalization were processed in the line-of-response (LOR) space according to the MRI-derived motion estimates. The processing time on the standard BrainPET workstation is approximately 16 s for each motion estimate. After rebinning in the sinogram space, the motion corrected data were summed, and the PET volume was reconstructed using the attenuation and scatter sinograms in the reference position. The accuracy of the MC algorithm was first tested using a Hoffman phantom. Next, human volunteer studies were performed, and motion estimates were obtained using 2 high-temporal-resolution MRI-based motion-tracking techniques. After accounting for the misalignment between the 2 scanners, perfectly coregistered MRI and PET volumes were reproducibly obtained. The MRI output gates inserted into the PET list-mode allow the temporal correlation of the 2 datasets within 0.2 ms. The Hoffman phantom volume reconstructed by processing the PET data in the LOR space was similar to the one obtained by processing the data using the standard methods and applying the MC in the image space, demonstrating the quantitative accuracy of the procedure. In human volunteer studies, motion estimates were obtained from echo planar imaging and cloverleaf navigator sequences every 3 s and 20 ms, respectively. Motion-deblurred PET images, with excellent delineation of specific brain structures, were obtained using these 2 MRI-based estimates. An MRI-based MC algorithm was implemented for an integrated MR-PET scanner. High-temporal-resolution MRI-derived motion estimates (obtained while simultaneously acquiring anatomic or functional MRI data) can be used for PET MC. An MRI-based MC method has the potential to improve PET image quality, increasing its reliability, reproducibility, and quantitative accuracy, and to benefit many neurologic applications.

Adaptive multiresolution modeling of groundwater flow in heterogeneous porous media

NASA Astrophysics Data System (ADS)

Malenica, Luka; Gotovac, Hrvoje; Srzic, Veljko; Andric, Ivo

2016-04-01

Proposed methodology was originally developed by our scientific team in Split who designed multiresolution approach for analyzing flow and transport processes in highly heterogeneous porous media. The main properties of the adaptive Fup multi-resolution approach are: 1) computational capabilities of Fup basis functions with compact support capable to resolve all spatial and temporal scales, 2) multi-resolution presentation of heterogeneity as well as all other input and output variables, 3) accurate, adaptive and efficient strategy and 4) semi-analytical properties which increase our understanding of usually complex flow and transport processes in porous media. The main computational idea behind this approach is to separately find the minimum number of basis functions and resolution levels necessary to describe each flow and transport variable with the desired accuracy on a particular adaptive grid. Therefore, each variable is separately analyzed, and the adaptive and multi-scale nature of the methodology enables not only computational efficiency and accuracy, but it also describes subsurface processes closely related to their understood physical interpretation. The methodology inherently supports a mesh-free procedure, avoiding the classical numerical integration, and yields continuous velocity and flux fields, which is vitally important for flow and transport simulations. In this paper, we will show recent improvements within the proposed methodology. Since "state of the art" multiresolution approach usually uses method of lines and only spatial adaptive procedure, temporal approximation was rarely considered as a multiscale. Therefore, novel adaptive implicit Fup integration scheme is developed, resolving all time scales within each global time step. It means that algorithm uses smaller time steps only in lines where solution changes are intensive. Application of Fup basis functions enables continuous time approximation, simple interpolation calculations across different temporal lines and local time stepping control. Critical aspect of time integration accuracy is construction of spatial stencil due to accurate calculation of spatial derivatives. Since common approach applied for wavelets and splines uses a finite difference operator, we developed here collocation one including solution values and differential operator. In this way, new improved algorithm is adaptive in space and time enabling accurate solution for groundwater flow problems, especially in highly heterogeneous porous media with large lnK variances and different correlation length scales. In addition, differences between collocation and finite volume approaches are discussed. Finally, results show application of methodology to the groundwater flow problems in highly heterogeneous confined and unconfined aquifers.

Efficiency and Accuracy in Thermal Simulation of Powder Bed Fusion of Bulk Metallic Glass

NASA Astrophysics Data System (ADS)

Lindwall, J.; Malmelöv, A.; Lundbäck, A.; Lindgren, L.-E.

2018-05-01

Additive manufacturing by powder bed fusion processes can be utilized to create bulk metallic glass as the process yields considerably high cooling rates. However, there is a risk that reheated material set in layers may become devitrified, i.e., crystallize. Therefore, it is advantageous to simulate the process to fully comprehend it and design it to avoid the aforementioned risk. However, a detailed simulation is computationally demanding. It is necessary to increase the computational speed while maintaining accuracy of the computed temperature field in critical regions. The current study evaluates a few approaches based on temporal reduction to achieve this. It is found that the evaluated approaches save a lot of time and accurately predict the temperature history.

Evidence for Deficits in the Temporal Attention Span of Poor Readers

PubMed Central

Visser, Troy A. W.

2014-01-01

Background While poor reading is often associated with phonological deficits, many studies suggest that visual processing might also be impaired. In particular, recent research has indicated that poor readers show impaired spatial visual attention spans in partial and whole report tasks. Given the similarities between competition-based accounts for reduced visual attention span and similar explanations for impairments in sequential object processing, the present work examined whether poor readers show deficits in their “temporal attention span” – that is, their ability to rapidly and accurately process sequences of consecutive target items. Methodology/Principal Findings Poor and normal readers monitored a sequential stream of visual items for two (TT condition) or three (TTT condition) consecutive target digits. Target identification was examined using both unconditional and conditional measures of accuracy in order to gauge the overall likelihood of identifying a target and the likelihood of identifying a target given successful identification of previous items. Compared to normal readers, poor readers showed small but consistent deficits in identification across targets whether unconditional or conditional accuracy was used. Additionally, in the TTT condition, final-target conditional accuracy was poorer than unconditional accuracy, particularly for poor readers, suggesting a substantial cost arising from processing the previous two targets that was not present in normal readers. Conclusions/Significance Mirroring the differences found between poor and normal readers in spatial visual attention span, the present findings suggest two principal differences between the temporal attention spans of poor and normal readers. First, the consistent pattern of reduced performance across targets suggests increased competition amongst items within the same span for poor readers. Second, the steeper decline in final target performance amongst poor readers in the TTT condition suggests a reduction in the extent of their temporal attention span. PMID:24651313

Evidence for deficits in the temporal attention span of poor readers.

PubMed

Visser, Troy A W

2014-01-01

While poor reading is often associated with phonological deficits, many studies suggest that visual processing might also be impaired. In particular, recent research has indicated that poor readers show impaired spatial visual attention spans in partial and whole report tasks. Given the similarities between competition-based accounts for reduced visual attention span and similar explanations for impairments in sequential object processing, the present work examined whether poor readers show deficits in their "temporal attention span"--that is, their ability to rapidly and accurately process sequences of consecutive target items. Poor and normal readers monitored a sequential stream of visual items for two (TT condition) or three (TTT condition) consecutive target digits. Target identification was examined using both unconditional and conditional measures of accuracy in order to gauge the overall likelihood of identifying a target and the likelihood of identifying a target given successful identification of previous items. Compared to normal readers, poor readers showed small but consistent deficits in identification across targets whether unconditional or conditional accuracy was used. Additionally, in the TTT condition, final-target conditional accuracy was poorer than unconditional accuracy, particularly for poor readers, suggesting a substantial cost arising from processing the previous two targets that was not present in normal readers. Mirroring the differences found between poor and normal readers in spatial visual attention span, the present findings suggest two principal differences between the temporal attention spans of poor and normal readers. First, the consistent pattern of reduced performance across targets suggests increased competition amongst items within the same span for poor readers. Second, the steeper decline in final target performance amongst poor readers in the TTT condition suggests a reduction in the extent of their temporal attention span.

Technical Report: TG-142 compliant and comprehensive quality assurance tests for respiratory gating

DOE Office of Scientific and Technical Information (OSTI.GOV)

Woods, Kyle; Rong, Yi, E-mail: yrong@ucdavis.edu

2015-11-15

Purpose: To develop and establish a comprehensive gating commissioning and quality assurance procedure in compliance with TG-142. Methods: Eight Varian TrueBeam Linacs were used for this study. Gating commissioning included an end-to-end test and baseline establishment. The end-to-end test was performed using a CIRS dynamic thoracic phantom with a moving cylinder inside the lung, which was used for carrying both optically simulated luminescence detectors (OSLDs) and Gafchromic EBT2 films while the target is moving, for a point dose check and 2D profile check. In addition, baselines were established for beam-on temporal delay and calibration of the surrogate, for both megavoltagemore » (MV) and kilovoltage (kV) beams. A motion simulation device (MotionSim) was used to provide periodic motion on a platform, in synchronizing with a surrogate motion. The overall accuracy and uncertainties were analyzed and compared. Results: The OSLD readings were within 5% compared to the planned dose (within measurement uncertainty) for both phase and amplitude gated deliveries. Film results showed less than 3% agreement to the predicted dose with a standard sinusoid motion. The gate-on temporal accuracy was averaged at 139 ± 10 ms for MV beams and 92 ± 11 ms for kV beams. The temporal delay of the surrogate motion depends on the motion speed and was averaged at 54.6 ± 3.1 ms for slow, 24.9 ± 2.9 ms for intermediate, and 23.0 ± 20.1 ms for fast speed. Conclusions: A comprehensive gating commissioning procedure was introduced for verifying the output accuracy and establishing the temporal accuracy baselines with respiratory gating. The baselines are needed for routine quality assurance tests, as suggested by TG-142.« less

Technical Report: TG-142 compliant and comprehensive quality assurance tests for respiratory gating.

PubMed

Woods, Kyle; Rong, Yi

2015-11-01

To develop and establish a comprehensive gating commissioning and quality assurance procedure in compliance with TG-142. Eight Varian TrueBeam Linacs were used for this study. Gating commissioning included an end-to-end test and baseline establishment. The end-to-end test was performed using a CIRS dynamic thoracic phantom with a moving cylinder inside the lung, which was used for carrying both optically simulated luminescence detectors (OSLDs) and Gafchromic EBT2 films while the target is moving, for a point dose check and 2D profile check. In addition, baselines were established for beam-on temporal delay and calibration of the surrogate, for both megavoltage (MV) and kilovoltage (kV) beams. A motion simulation device (MotionSim) was used to provide periodic motion on a platform, in synchronizing with a surrogate motion. The overall accuracy and uncertainties were analyzed and compared. The OSLD readings were within 5% compared to the planned dose (within measurement uncertainty) for both phase and amplitude gated deliveries. Film results showed less than 3% agreement to the predicted dose with a standard sinusoid motion. The gate-on temporal accuracy was averaged at 139±10 ms for MV beams and 92±11 ms for kV beams. The temporal delay of the surrogate motion depends on the motion speed and was averaged at 54.6±3.1 ms for slow, 24.9±2.9 ms for intermediate, and 23.0±20.1 ms for fast speed. A comprehensive gating commissioning procedure was introduced for verifying the output accuracy and establishing the temporal accuracy baselines with respiratory gating. The baselines are needed for routine quality assurance tests, as suggested by TG-142.

Backscatter Analysis Using Multi-Temporal SENTINEL-1 SAR Data for Crop Growth of Maize in Konya Basin, Turkey

NASA Astrophysics Data System (ADS)

Abdikan, S.; Sekertekin, A.; Ustunern, M.; Balik Sanli, F.; Nasirzadehdizaji, R.

2018-04-01

Temporal monitoring of crop types is essential for the sustainable management of agricultural activities on both national and global levels. As a practical and efficient tool, remote sensing is widely used in such applications. In this study, Sentinel-1 Synthetic Aperture Radar (SAR) imagery was utilized to investigate the performance of the sensor backscatter image on crop monitoring. Multi-temporal C-band VV and VH polarized SAR images were acquired simultaneously by in-situ measurements which was conducted at Konya basin, central Anatolia Turkey. During the measurements, plant height of maize plant was collected and relationship between backscatter values and plant height was analysed. The maize growth development was described under Biologische Bundesanstalt, bundessortenamt und CHemische industrie (BBCH). Under BBCH stages, the test site was classified as leaf development, stem elongation, heading and flowering in general. The correlation coefficient values indicated high correlation for both polarimetry during the early stages of the plant, while late stages indicated lower values in both polarimetry. As a last step, multi-temporal coverage of crop fields was analysed to map seasonal land use. To this aim, object based image classification was applied following image segmentation. About 80 % accuracies of land use maps were created in this experiment. As preliminary results, it is concluded that Sentinel-1 data provides beneficial information about plant growth. Dual-polarized Sentinel-1 data has high potential for multi-temporal analyses for agriculture monitoring and reliable mapping.

Unified treatment and measurement of the spectral resolution and temporal effects in frequency-resolved sum-frequency generation vibrational spectroscopy (SFG-VS).

PubMed

Velarde, Luis; Wang, Hong-Fei

2013-12-14

The lack of understanding of the temporal effects and the restricted ability to control experimental conditions in order to obtain intrinsic spectral lineshapes in surface sum-frequency generation vibrational spectroscopy (SFG-VS) have limited its applications in surface and interfacial studies. The emergence of high-resolution broadband sum-frequency generation vibrational spectroscopy (HR-BB-SFG-VS) with sub-wavenumber resolution [Velarde et al., J. Chem. Phys., 2011, 135, 241102] offers new opportunities for obtaining and understanding the spectral lineshapes and temporal effects in SFG-VS. Particularly, the high accuracy of the HR-BB-SFG-VS experimental lineshape provides detailed information on the complex coherent vibrational dynamics through direct spectral measurements. Here we present a unified formalism for the theoretical and experimental routes for obtaining an accurate lineshape of the SFG response. Then, we present a detailed analysis of a cholesterol monolayer at the air/water interface with higher and lower resolution SFG spectra along with their temporal response. With higher spectral resolution and accurate vibrational spectral lineshapes, it is shown that the parameters of the experimental SFG spectra can be used both to understand and to quantitatively reproduce the temporal effects in lower resolution SFG measurements. This perspective provides not only a unified picture but also a novel experimental approach to measuring and understanding the frequency-domain and time-domain SFG response of a complex molecular interface.

Predicting Epidemic Risk from Past Temporal Contact Data

PubMed Central

Valdano, Eugenio; Poletto, Chiara; Giovannini, Armando; Palma, Diana; Savini, Lara; Colizza, Vittoria

2015-01-01

Understanding how epidemics spread in a system is a crucial step to prevent and control outbreaks, with broad implications on the system’s functioning, health, and associated costs. This can be achieved by identifying the elements at higher risk of infection and implementing targeted surveillance and control measures. One important ingredient to consider is the pattern of disease-transmission contacts among the elements, however lack of data or delays in providing updated records may hinder its use, especially for time-varying patterns. Here we explore to what extent it is possible to use past temporal data of a system’s pattern of contacts to predict the risk of infection of its elements during an emerging outbreak, in absence of updated data. We focus on two real-world temporal systems; a livestock displacements trade network among animal holdings, and a network of sexual encounters in high-end prostitution. We define the node’s loyalty as a local measure of its tendency to maintain contacts with the same elements over time, and uncover important non-trivial correlations with the node’s epidemic risk. We show that a risk assessment analysis incorporating this knowledge and based on past structural and temporal pattern properties provides accurate predictions for both systems. Its generalizability is tested by introducing a theoretical model for generating synthetic temporal networks. High accuracy of our predictions is recovered across different settings, while the amount of possible predictions is system-specific. The proposed method can provide crucial information for the setup of targeted intervention strategies. PMID:25763816

Temporal Stability and Convergent Validity of the Behavior Assessment System for Children.

ERIC Educational Resources Information Center

Merydith, Scott P.

2001-01-01

Assesses the temporal stability and convergent validity of the Behavioral Assessment System for Children (BASC). Teachers and parents rated kindergarten and first-grade students using BASC. Teachers were more stable in rating children's externalizing behaviors and attention problems. Discusses results in terms of the accuracy of information…

The effects of morphine on fixed-interval patterning and temporal discrimination.

PubMed Central

Odum, A L; Schaal, D W

2000-01-01

Changes produced by drugs in response patterns under fixed-interval schedules of reinforcement have been interpreted to result from changes in temporal discrimination. To examine this possibility, this experiment determined the effects of morphine on the response patterning of 4 pigeons during a fixed-interval 1-min schedule of food delivery with interpolated temporal discrimination trials. Twenty of the 50 total intervals were interrupted by choice trials. Pecks to one key color produced food if the interval was interrupted after a short time (after 2 or 4.64 s). Pecks to another key color produced food if the interval was interrupted after a long time (after 24.99 or 58 s). Morphine (1.0 to 10.0 mg/kg) decreased the index of curvature (a measure of response patterning) during fixed intervals and accuracy during temporal discrimination trials. Accuracy was equally disrupted following short and long sample durations. Although morphine disrupted temporal discrimination in the context of a fixed-interval schedule, these effects are inconsistent with interpretations of the disruption of response patterning as a selective overestimation of elapsed time. The effects of morphine may be related to the effects of more conventional external stimuli on response patterning. PMID:11029024

Research on Geometric Calibration of Spaceborne Linear Array Whiskbroom Camera

PubMed Central

Sheng, Qinghong; Wang, Qi; Xiao, Hui; Wang, Qing

2018-01-01

The geometric calibration of a spaceborne thermal-infrared camera with a high spatial resolution and wide coverage can set benchmarks for providing an accurate geographical coordinate for the retrieval of land surface temperature. The practice of using linear array whiskbroom Charge-Coupled Device (CCD) arrays to image the Earth can help get thermal-infrared images of a large breadth with high spatial resolutions. Focusing on the whiskbroom characteristics of equal time intervals and unequal angles, the present study proposes a spaceborne linear-array-scanning imaging geometric model, whilst calibrating temporal system parameters and whiskbroom angle parameters. With the help of the YG-14—China’s first satellite equipped with thermal-infrared cameras of high spatial resolution—China’s Anyang Imaging and Taiyuan Imaging are used to conduct an experiment of geometric calibration and a verification test, respectively. Results have shown that the plane positioning accuracy without ground control points (GCPs) is better than 30 pixels and the plane positioning accuracy with GCPs is better than 1 pixel. PMID:29337885

A deep convolutional neural network with new training methods for bearing fault diagnosis under noisy environment and different working load

NASA Astrophysics Data System (ADS)

Zhang, Wei; Li, Chuanhao; Peng, Gaoliang; Chen, Yuanhang; Zhang, Zhujun

2018-02-01

In recent years, intelligent fault diagnosis algorithms using machine learning technique have achieved much success. However, due to the fact that in real world industrial applications, the working load is changing all the time and noise from the working environment is inevitable, degradation of the performance of intelligent fault diagnosis methods is very serious. In this paper, a new model based on deep learning is proposed to address the problem. Our contributions of include: First, we proposed an end-to-end method that takes raw temporal signals as inputs and thus doesn't need any time consuming denoising preprocessing. The model can achieve pretty high accuracy under noisy environment. Second, the model does not rely on any domain adaptation algorithm or require information of the target domain. It can achieve high accuracy when working load is changed. To understand the proposed model, we will visualize the learned features, and try to analyze the reasons behind the high performance of the model.

Higher-order hybrid implicit/explicit FDTD time-stepping

NASA Astrophysics Data System (ADS)

Tierens, W.

2016-12-01

Both partially implicit FDTD methods, and symplectic FDTD methods of high temporal accuracy (3rd or 4th order), are well documented in the literature. In this paper we combine them: we construct a conservative FDTD method which is fourth order accurate in time and is partially implicit. We show that the stability condition for this method depends exclusively on the explicit part, which makes it suitable for use in e.g. modelling wave propagation in plasmas.

Photogrammetric determination of spatio-temporal velocity fields at Glaciar San Rafael in the Northern Patagonian Icefield

NASA Astrophysics Data System (ADS)

Maas, H.-G.; Casassa, G.; Schneider, D.; Schwalbe, E.; Wendt, A.

2010-11-01

Glaciar San Rafael in the Northern Patagonian Icefield, with a length of 46 km and an ice area of 722 km2, is the lowest latitude tidewater outlet glacier in the world and one of the fastest and most productive glaciers in southern South America in terms of iceberg flux. In a joint project of the TU Dresden and CECS, spatio-temporal velocity fields in the region of the glacier front were determined in a campaign in austral spring of 2009. Monoscopic terrestrial image sequences were recorded with an intervallometer mode high resolution digital camera over several days. In these image sequences, a large number of glacier surface points were tracked by subpixel accuracy feature tracking techniques. Scaling and georeferencing of the trajectories obtained from image space tracking was performed via a multi-station GPS-supported photogrammetric network. The technique allows for tracking hundreds of glacier surface points at a measurement accuracy in the order of one decimeter and an almost arbitrarily high temporary resolution. The results show velocities of up to 16 m per day. No significant tidal signals could be observed. Our velocities are in agreement with earlier measurements from theodolite and satellite interferometry performed in 1986-1994, suggesting that the current thinning of 3.5 m/y at the front is not due to dynamic thinning but rather by enhanced melting.

Radial k-t SPIRiT: autocalibrated parallel imaging for generalized phase-contrast MRI.

PubMed

Santelli, Claudio; Schaeffter, Tobias; Kozerke, Sebastian

2014-11-01

To extend SPIRiT to additionally exploit temporal correlations for highly accelerated generalized phase-contrast MRI and to compare the performance of the proposed radial k-t SPIRiT method relative to frame-by-frame SPIRiT and radial k-t GRAPPA reconstruction for velocity and turbulence mapping in the aortic arch. Free-breathing navigator-gated two-dimensional radial cine imaging with three-directional multi-point velocity encoding was implemented and fully sampled data were obtained in the aortic arch of healthy volunteers. Velocities were encoded with three different first gradient moments per axis to permit quantification of mean velocity and turbulent kinetic energy. Velocity and turbulent kinetic energy maps from up to 14-fold undersampled data were compared for k-t SPIRiT, frame-by-frame SPIRiT, and k-t GRAPPA relative to the fully sampled reference. Using k-t SPIRiT, improvements in magnitude and velocity reconstruction accuracy were found. Temporally resolved magnitude profiles revealed a reduction in spatial blurring with k-t SPIRiT compared with frame-by-frame SPIRiT and k-t GRAPPA for all velocity encodings, leading to improved estimates of turbulent kinetic energy. k-t SPIRiT offers improved reconstruction accuracy at high radial undersampling factors and hence facilitates the use of generalized phase-contrast MRI for routine use. Copyright © 2013 Wiley Periodicals, Inc.

MatTAP: A MATLAB toolbox for the control and analysis of movement synchronisation experiments.

PubMed

Elliott, Mark T; Welchman, Andrew E; Wing, Alan M

2009-02-15

Investigating movement timing and synchronisation at the sub-second range relies on an experimental setup that has high temporal fidelity, is able to deliver output cues and can capture corresponding responses. Modern, multi-tasking operating systems make this increasingly challenging when using standard PC hardware and programming languages. This paper describes a new free suite of tools (available from http://www.snipurl.com/mattap) for use within the MATLAB programming environment, compatible with Microsoft Windows and a range of data acquisition hardware. The toolbox allows flexible generation of timing cues with high temporal accuracy, the capture and automatic storage of corresponding participant responses and an integrated analysis module for the rapid processing of results. A simple graphical user interface is used to navigate the toolbox and so can be operated easily by users not familiar with programming languages. However, it is also fully extensible and customisable, allowing adaptation for individual experiments and facilitating the addition of new modules in future releases. Here we discuss the relevance of the MatTAP (MATLAB Timing Analysis Package) toolbox to current timing experiments and compare its use to alternative methods. We validate the accuracy of the analysis module through comparison to manual observation methods and replicate a previous sensorimotor synchronisation experiment to demonstrate the versatility of the toolbox features demanded by such movement synchronisation paradigms.

High-spatial-resolution mapping of precipitable water vapour using SAR interferograms, GPS observations and ERA-Interim reanalysis

NASA Astrophysics Data System (ADS)

Tang, Wei; Liao, Mingsheng; Zhang, Lu; Li, Wei; Yu, Weimin

2016-09-01

A high spatial and temporal resolution of the precipitable water vapour (PWV) in the atmosphere is a key requirement for the short-scale weather forecasting and climate research. The aim of this work is to derive temporally differenced maps of the spatial distribution of PWV by analysing the tropospheric delay "noise" in interferometric synthetic aperture radar (InSAR). Time series maps of differential PWV were obtained by processing a set of ENVISAT ASAR (Advanced Synthetic Aperture Radar) images covering the area of southern California, USA from 6 October 2007 to 29 November 2008. To get a more accurate PWV, the component of hydrostatic delay was calculated and subtracted by using ERA-Interim reanalysis products. In addition, the ERA-Interim was used to compute the conversion factors required to convert the zenith wet delay to water vapour. The InSAR-derived differential PWV maps were calibrated by means of the GPS PWV measurements over the study area. We validated our results against the measurements of PWV derived from the Medium Resolution Imaging Spectrometer (MERIS) which was located together with the ASAR sensor on board the ENVISAT satellite. Our comparative results show strong spatial correlations between the two data sets. The difference maps have Gaussian distributions with mean values close to zero and standard deviations below 2 mm. The advantage of the InSAR technique is that it provides water vapour distribution with a spatial resolution as fine as 20 m and an accuracy of ˜ 2 mm. Such high-spatial-resolution maps of PWV could lead to much greater accuracy in meteorological understanding and quantitative precipitation forecasts. With the launch of Sentinel-1A and Sentinel-1B satellites, every few days (6 days) new SAR images can be acquired with a wide swath up to 250 km, enabling a unique operational service for InSAR-based water vapour maps with unprecedented spatial and temporal resolution.

A new metric to assess temporal coherence for video retargeting

NASA Astrophysics Data System (ADS)

Li, Ke; Yan, Bo; Yuan, Binhang

2014-10-01

In video retargeting, how to assess the performance in maintaining temporal coherence has become the prominent challenge. In this paper, we will present a new objective measurement to assess temporal coherence after video retargeting. It's a general metric to assess jittery artifact for both discrete and continuous video retargeting methods, the accuracy of which is verified by psycho-visual tests. As a result, our proposed assessment method possesses huge practical significance.

An advanced stochastic weather generator for simulating 2-D high-resolution climate variables

NASA Astrophysics Data System (ADS)

Peleg, Nadav; Fatichi, Simone; Paschalis, Athanasios; Molnar, Peter; Burlando, Paolo

2017-07-01

A new stochastic weather generator, Advanced WEather GENerator for a two-dimensional grid (AWE-GEN-2d) is presented. The model combines physical and stochastic approaches to simulate key meteorological variables at high spatial and temporal resolution: 2 km × 2 km and 5 min for precipitation and cloud cover and 100 m × 100 m and 1 h for near-surface air temperature, solar radiation, vapor pressure, atmospheric pressure, and near-surface wind. The model requires spatially distributed data for the calibration process, which can nowadays be obtained by remote sensing devices (weather radar and satellites), reanalysis data sets and ground stations. AWE-GEN-2d is parsimonious in terms of computational demand and therefore is particularly suitable for studies where exploring internal climatic variability at multiple spatial and temporal scales is fundamental. Applications of the model include models of environmental systems, such as hydrological and geomorphological models, where high-resolution spatial and temporal meteorological forcing is crucial. The weather generator was calibrated and validated for the Engelberg region, an area with complex topography in the Swiss Alps. Model test shows that the climate variables are generated by AWE-GEN-2d with a level of accuracy that is sufficient for many practical applications.

Temporal epilepsy seizures monitoring and prediction using cross-correlation and chaos theory.

PubMed

Haddad, Tahar; Ben-Hamida, Naim; Talbi, Larbi; Lakhssassi, Ahmed; Aouini, Sadok

2014-01-01

Temporal seizures due to hippocampal origins are very common among epileptic patients. Presented is a novel seizure prediction approach employing correlation and chaos theories. The early identification of seizure signature allows for various preventive measures to be undertaken. Electro-encephalography signals are spectrally broken down into the following sub-bands: delta; theta; alpha; beta; and gamma. The proposed approach consists of observing a high correlation level between any pair of electrodes for the lower frequencies and a decrease in the Lyapunov index (chaos or entropy) for the higher frequencies. Power spectral density and statistical analysis tools were used to determine threshold levels for the lower frequencies. After studying all five sub-bands, the analysis has revealed that the seizure signature can be extracted from the delta band and the high frequencies. High frequencies are defined as both the gamma band and the ripples occurring within the 60-120 Hz sub-band. To validate the proposed approach, six patients from both sexes and various age groups with temporal epilepsies originating from the hippocampal area were studied using the Freiburg database. An average seizure prediction of 30 min, an anticipation accuracy of 72%, and a false-positive rate of 0% were accomplished throughout 200 h of recording time.

Effect of Spatio-Temporal Variability of Rainfall on Stream flow Prediction of Birr Watershed

NASA Astrophysics Data System (ADS)

Demisse, N. S.; Bitew, M. M.; Gebremichael, M.

2012-12-01

The effect of rainfall variability on our ability to forecast flooding events was poorly studied in complex terrain region of Ethiopia. In order to establish relation between rainfall variability and stream flow, we deployed 24 rain gauges across Birr watershed. Birr watershed is a medium size mountainous watershed with an area of 3000 km2 and elevation ranging between 1435 m.a.s.l and 3400 m.a.s.l in the central Ethiopia highlands. One summer monsoon rainfall of 2012 recorded at high temporal scale of 15 minutes interval and stream flow recorded at an hourly interval in three sub-watershed locations representing different scales were used in this study. Based on the data obtained from the rain gauges and stream flow observations, we quantify extent of temporal and spatial variability of rainfall across the watershed using standard statistical measures including mean, standard deviation and coefficient of variation. We also establish rainfall-runoff modeling system using a physically distributed hydrological model: the Soil and Water Assessment Tool (SWAT) and examine the effect of rainfall variability on stream flow prediction. The accuracy of predicted stream flow is measured through direct comparison with observed flooding events. The results demonstrate the significance of relation between stream flow prediction and rainfall variability in the understanding of runoff generation mechanisms at watershed scale, determination of dominant water balance components, and effect of variability on accuracy of flood forecasting activities.

Modelling spatio-temporal heterogeneities in groundwater quality in Ghana: a multivariate chemometric approach.

PubMed

Armah, Frederick Ato; Paintsil, Arnold; Yawson, David Oscar; Adu, Michael Osei; Odoi, Justice O

2017-08-01

Chemometric techniques were applied to evaluate the spatial and temporal heterogeneities in groundwater quality data for approximately 740 goldmining and agriculture-intensive locations in Ghana. The strongest linear and monotonic relationships occurred between Mn and Fe. Sixty-nine per cent of total variance in the dataset was explained by four variance factors: physicochemical properties, bacteriological quality, natural geologic attributes and anthropogenic factors (artisanal goldmining). There was evidence of significant differences in means of all trace metals and physicochemical parameters (p < 0.001) between goldmining and non-goldmining locations. Arsenic and turbidity produced very high value F's demonstrating that 'physical properties and chalcophilic elements' was the function that most discriminated between non-goldmining and goldmining locations. Variations in Escherichia coli and total coliforms were observed between the dry and wet seasons. The overall predictive accuracy of the discriminant function showed that non-goldmining locations were classified with slightly better accuracy (89%) than goldmining areas (69.6%). There were significant differences between the underlying distributions of Cd, Mn and Pb in the wet and dry seasons. This study emphasizes the practicality of chemometrics in the assessment and elucidation of complex water quality datasets to promote effective management of groundwater resources for sustaining human health.

Enhanced monitoring of the temporal and spatial relationships between water demand and water availability

NASA Astrophysics Data System (ADS)

Schneider, C. A.; Aggett, G. R.; Hattendorf, M. J.

2007-12-01

Better information on evapotranspiration (ET) is essential to better understanding of consumptive use of water by crops. RTi is using NASA Earth-sun System research results and METRIC (Mapping ET at high Resolution with Internalized Calibration) to increase the repeatability and accuracy of consumptive use estimates. METRIC, an image-processing model for calculating ET as a residual of the surface energy balance, utilizes the thermal band on various satellite remote sensors. Calculating actual ET from satellites can avoid many of the assumptions driving other methods of calculating ET over a large area. Because it is physically based and does not rely on explicit knowledge of crop type in the field, a large potential source of error should be eliminated. This paper assesses sources of error in current operational estimates of ET for an area of the South Platte irrigated lands of Colorado, and benchmarks potential improvements in the accuracy of ET estimates gained using METRIC, as well as the processing efficiency of consumptive use demand for large irrigated lands. Examples highlighting how better water planning decisions and water management can be achieved via enhanced monitoring of the temporal and spatial relationships between water demand and water availability are provided.

High-accuracy drilling with an image guided light weight robot: autonomous versus intuitive feed control.

PubMed

Tauscher, Sebastian; Fuchs, Alexander; Baier, Fabian; Kahrs, Lüder A; Ortmaier, Tobias

2017-10-01

Assistance of robotic systems in the operating room promises higher accuracy and, hence, demanding surgical interventions become realisable (e.g. the direct cochlear access). Additionally, an intuitive user interface is crucial for the use of robots in surgery. Torque sensors in the joints can be employed for intuitive interaction concepts. Regarding the accuracy, they lead to a lower structural stiffness and, thus, to an additional error source. The aim of this contribution is to examine, if an accuracy needed for demanding interventions can be achieved by such a system or not. Feasible accuracy results of the robot-assisted process depend on each work-flow step. This work focuses on the determination of the tool coordinate frame. A method for drill axis definition is implemented and analysed. Furthermore, a concept of admittance feed control is developed. This allows the user to control feeding along the planned path by applying a force to the robots structure. The accuracy is researched by drilling experiments with a PMMA phantom and artificial bone blocks. The described drill axis estimation process results in a high angular repeatability ([Formula: see text]). In the first set of drilling results, an accuracy of [Formula: see text] at entrance and [Formula: see text] at target point excluding imaging was achieved. With admittance feed control an accuracy of [Formula: see text] at target point was realised. In a third set twelve holes were drilled in artificial temporal bone phantoms including imaging. In this set-up an error of [Formula: see text] and [Formula: see text] was achieved. The results of conducted experiments show that accuracy requirements for demanding procedures such as the direct cochlear access can be fulfilled with compliant systems. Furthermore, it was shown that with the presented admittance feed control an accuracy of less then [Formula: see text] is achievable.

Structure-from-motion for MAV image sequence analysis with photogrammetric applications

NASA Astrophysics Data System (ADS)

Schönberger, J. L.; Fraundorfer, F.; Frahm, J.-M.

2014-08-01

MAV systems have found increased attention in the photogrammetric community as an (autonomous) image acquisition platform for accurate 3D reconstruction. For an accurate reconstruction in feasible time, the acquired imagery requires specialized SfM software. Current systems typically use high-resolution sensors in pre-planned flight missions from far distance. We describe and evaluate a new SfM pipeline specifically designed for sequential, close-distance, and low-resolution imagery from mobile cameras with relatively high frame-rate and high overlap. Experiments demonstrate reduced computational complexity by leveraging the temporal consistency, comparable accuracy and point density with respect to state-of-the-art systems.

The determination of high-resolution spatio-temporal glacier motion fields from time-lapse sequences

NASA Astrophysics Data System (ADS)

Schwalbe, Ellen; Maas, Hans-Gerd

2017-12-01

This paper presents a comprehensive method for the determination of glacier surface motion vector fields at high spatial and temporal resolution. These vector fields can be derived from monocular terrestrial camera image sequences and are a valuable data source for glaciological analysis of the motion behaviour of glaciers. The measurement concepts for the acquisition of image sequences are presented, and an automated monoscopic image sequence processing chain is developed. Motion vector fields can be derived with high precision by applying automatic subpixel-accuracy image matching techniques on grey value patterns in the image sequences. Well-established matching techniques have been adapted to the special characteristics of the glacier data in order to achieve high reliability in automatic image sequence processing, including the handling of moving shadows as well as motion effects induced by small instabilities in the camera set-up. Suitable geo-referencing techniques were developed to transform image measurements into a reference coordinate system.The result of monoscopic image sequence analysis is a dense raster of glacier surface point trajectories for each image sequence. Each translation vector component in these trajectories can be determined with an accuracy of a few centimetres for points at a distance of several kilometres from the camera. Extensive practical validation experiments have shown that motion vector and trajectory fields derived from monocular image sequences can be used for the determination of high-resolution velocity fields of glaciers, including the analysis of tidal effects on glacier movement, the investigation of a glacier's motion behaviour during calving events, the determination of the position and migration of the grounding line and the detection of subglacial channels during glacier lake outburst floods.

Building Change Detection in Very High Resolution Satellite Stereo Image Time Series

NASA Astrophysics Data System (ADS)

Tian, J.; Qin, R.; Cerra, D.; Reinartz, P.

2016-06-01

There is an increasing demand for robust methods on urban sprawl monitoring. The steadily increasing number of high resolution and multi-view sensors allows producing datasets with high temporal and spatial resolution; however, less effort has been dedicated to employ very high resolution (VHR) satellite image time series (SITS) to monitor the changes in buildings with higher accuracy. In addition, these VHR data are often acquired from different sensors. The objective of this research is to propose a robust time-series data analysis method for VHR stereo imagery. Firstly, the spatial-temporal information of the stereo imagery and the Digital Surface Models (DSMs) generated from them are combined, and building probability maps (BPM) are calculated for all acquisition dates. In the second step, an object-based change analysis is performed based on the derivative features of the BPM sets. The change consistence between object-level and pixel-level are checked to remove any outlier pixels. Results are assessed on six pairs of VHR satellite images acquired within a time span of 7 years. The evaluation results have proved the efficiency of the proposed method.

Applicability Assessment of Uavsar Data in Wetland Monitoring: a Case Study of Louisiana Wetland

NASA Astrophysics Data System (ADS)

Zhao, J.; Niu, Y.; Lu, Z.; Yang, J.; Li, P.; Liu, W.

2018-04-01

Wetlands are highly productive and support a wide variety of ecosystem goods and services. Monitoring wetland is essential and potential. Because of the repeat-pass nature of satellite orbit and airborne, time-series of remote sensing data can be obtained to monitor wetland. UAVSAR is a NASA L-band synthetic aperture radar (SAR) sensor compact pod-mounted polarimetric instrument for interferometric repeat-track observations. Moreover, UAVSAR images can accurately map crustal deformations associated with natural hazards, such as volcanoes and earthquakes. And its polarization agility facilitates terrain and land-use classification and change detection. In this paper, the multi-temporal UAVSAR data are applied for monitoring the wetland change. Using the multi-temporal polarimetric SAR (PolSAR) data, the change detection maps are obtained by unsupervised and supervised method. And the coherence is extracted from the interfometric SAR (InSAR) data to verify the accuracy of change detection map. The experimental results show that the multi-temporal UAVSAR data is fit for wetland monitor.

Spatiotemporal dynamics in understanding hand—object interactions

PubMed Central

Avanzini, Pietro; Fabbri-Destro, Maddalena; Campi, Cristina; Pascarella, Annalisa; Barchiesi, Guido; Cattaneo, Luigi; Rizzolatti, Giacomo

2013-01-01

It is generally accepted that visual perception results from the activation of a feed-forward hierarchy of areas, leading to increasingly complex representations. Here we present evidence for a fundamental role of backward projections to the occipito-temporal region for understanding conceptual object properties. The evidence is based on two studies. In the first study, using high-density EEG, we showed that during the observation of how objects are used there is an early activation of occipital and temporal areas, subsequently reaching the pole of the temporal lobe, and a late reactivation of the visual areas. In the second study, using transcranial magnetic stimulation over the occipital lobe, we showed a clear impairment in the accuracy of recognition of how objects are used during both early activation and, most importantly, late occipital reactivation. These findings represent strong neurophysiological evidence that a top-down mechanism is fundamental for understanding conceptual object properties, and suggest that a similar mechanism might be also present for other higher-order cognitive functions. PMID:24043805

Development and Performance of an Atomic Interferometer Gravity Gradiometer for Earth Science

NASA Astrophysics Data System (ADS)

Luthcke, S. B.; Saif, B.; Sugarbaker, A.; Rowlands, D. D.; Loomis, B.

2016-12-01

The wealth of multi-disciplinary science achieved from the GRACE mission, the commitment to GRACE Follow On (GRACE-FO), and Resolution 2 from the International Union of Geodesy and Geophysics (IUGG, 2015), highlight the importance to implement a long-term satellite gravity observational constellation. Such a constellation would measure time variable gravity (TVG) with accuracies 50 times better than the first generation missions, at spatial and temporal resolutions to support regional and sub-basin scale multi-disciplinary science. Improved TVG measurements would achieve significant societal benefits including: forecasting of floods and droughts, improved estimates of climate impacts on water cycle and ice sheets, coastal vulnerability, land management, risk assessment of natural hazards, and water management. To meet the accuracy and resolution challenge of the next generation gravity observational system, NASA GSFC and AOSense are currently developing an Atomic Interferometer Gravity Gradiometer (AIGG). This technology is capable of achieving the desired accuracy and resolution with a single instrument, exploiting the advantages of the microgravity environment. The AIGG development is funded under NASA's Earth Science Technology Office (ESTO) Instrument Incubator Program (IIP), and includes the design, build, and testing of a high-performance, single-tensor-component gravity gradiometer for TVG recovery from a satellite in low Earth orbit. The sensitivity per shot is 10-5 Eötvös (E) with a flat spectral bandwidth from 0.3 mHz - 0.03 Hz. Numerical simulations show that a single space-based AIGG in a 326 km altitude polar orbit is capable of exceeding the IUGG target requirement for monthly TVG accuracy of 1 cm equivalent water height at 200 km resolution. We discuss the current status of the AIGG IIP development and estimated instrument performance, and we present results of simulated Earth TVG recovery of the space-based AIGG. We explore the accuracy, and spatial and temporal resolution of surface mass change observations from several space-based implementations of the AIGG instrument, including various orbit configurations and multi-satellite/multi-orbit configurations.

Pressure-Sensitive Paint Measurements on Surfaces with Non-Uniform Temperature

NASA Technical Reports Server (NTRS)

Bencic, Timothy J.

1999-01-01

Pressure-sensitive paint (PSP) has become a useful tool to augment conventional pressure taps in measuring the surface pressure distribution of aerodynamic components in wind tunnel testing. While the PSP offers the advantage of a non-intrusive global mapping of the surface pressure, one prominent drawback to the accuracy of this technique is the inherent temperature sensitivity of the coating's luminescent intensity. A typical aerodynamic surface PSP test has relied on the coated surface to be both spatially and temporally isothermal, along with conventional instrumentation for an in situ calibration to generate the highest accuracy pressure mappings. In some tests however, spatial and temporal thermal gradients are generated by the nature of the test as in a blowing jet impinging on a surface. In these cases, the temperature variations on the painted surface must be accounted for in order to yield high accuracy and reliable data. A new temperature correction technique was developed at NASA Lewis to collapse a "family" of PSP calibration curves to a single intensity ratio versus pressure curve. This correction allows a streamlined procedure to be followed whether or not temperature information is used in the data reduction of the PSP. This paper explores the use of conventional instrumentation such as thermocouples and pressure taps along with temperature-sensitive paint (TSP) to correct for the thermal gradients that exist in aeropropulsion PSP tests. Temperature corrected PSP measurements for both a supersonic mixer ejector and jet cavity interaction tests are presented.

A geostatistical state-space model of animal densities for stream networks.

PubMed

Hocking, Daniel J; Thorson, James T; O'Neil, Kyle; Letcher, Benjamin H

2018-06-21

Population dynamics are often correlated in space and time due to correlations in environmental drivers as well as synchrony induced by individual dispersal. Many statistical analyses of populations ignore potential autocorrelations and assume that survey methods (distance and time between samples) eliminate these correlations, allowing samples to be treated independently. If these assumptions are incorrect, results and therefore inference may be biased and uncertainty under-estimated. We developed a novel statistical method to account for spatio-temporal correlations within dendritic stream networks, while accounting for imperfect detection in the surveys. Through simulations, we found this model decreased predictive error relative to standard statistical methods when data were spatially correlated based on stream distance and performed similarly when data were not correlated. We found that increasing the number of years surveyed substantially improved the model accuracy when estimating spatial and temporal correlation coefficients, especially from 10 to 15 years. Increasing the number of survey sites within the network improved the performance of the non-spatial model but only marginally improved the density estimates in the spatio-temporal model. We applied this model to Brook Trout data from the West Susquehanna Watershed in Pennsylvania collected over 34 years from 1981 - 2014. We found the model including temporal and spatio-temporal autocorrelation best described young-of-the-year (YOY) and adult density patterns. YOY densities were positively related to forest cover and negatively related to spring temperatures with low temporal autocorrelation and moderately-high spatio-temporal correlation. Adult densities were less strongly affected by climatic conditions and less temporally variable than YOY but with similar spatio-temporal correlation and higher temporal autocorrelation. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Improving the phase response of an atom interferometer by means of temporal pulse shaping

NASA Astrophysics Data System (ADS)

Fang, Bess; Mielec, Nicolas; Savoie, Denis; Altorio, Matteo; Landragin, Arnaud; Geiger, Remi

2018-02-01

We study theoretically and experimentally the influence of temporally shaping the light pulses in an atom interferometer, with a focus on the phase response of the interferometer. We show that smooth light pulse shapes allow rejecting high frequency phase fluctuations (above the Rabi frequency) and thus relax the requirements on the phase noise or frequency noise of the interrogation lasers driving the interferometer. The light pulse shape is also shown to modify the scale factor of the interferometer, which has to be taken into account in the evaluation of its accuracy budget. We discuss the trade-offs to operate when choosing a particular pulse shape, by taking into account phase noise rejection, velocity selectivity, and applicability to large momentum transfer atom interferometry.

Opportunities to improve monitoring of temporal trends with FIA panel data

Treesearch

Raymond Czaplewski; Michael Thompson

2009-01-01

The Forest Inventory and Analysis (FIA) Program of the Forest Service, Department of Agriculture, is an annual monitoring system for the entire United States. Each year, an independent "panel" of FIA field plots is measured. To improve accuracy, FIA uses the "Moving Average" or "Temporally Indifferent" method to combine estimates from...

Computationally efficient approach for solving time dependent diffusion equation with discrete temporal convolution applied to granular particles of battery electrodes

NASA Astrophysics Data System (ADS)

Senegačnik, Jure; Tavčar, Gregor; Katrašnik, Tomaž

2015-03-01

The paper presents a computationally efficient method for solving the time dependent diffusion equation in a granule of the Li-ion battery's granular solid electrode. The method, called Discrete Temporal Convolution method (DTC), is based on a discrete temporal convolution of the analytical solution of the step function boundary value problem. This approach enables modelling concentration distribution in the granular particles for arbitrary time dependent exchange fluxes that do not need to be known a priori. It is demonstrated in the paper that the proposed method features faster computational times than finite volume/difference methods and Padé approximation at the same accuracy of the results. It is also demonstrated that all three addressed methods feature higher accuracy compared to the quasi-steady polynomial approaches when applied to simulate the current densities variations typical for mobile/automotive applications. The proposed approach can thus be considered as one of the key innovative methods enabling real-time capability of the multi particle electrochemical battery models featuring spatial and temporal resolved particle concentration profiles.

Individual Differences in Memory Search and Their Relation to Intelligence

PubMed Central

Healey, M. Karl; Crutchley, Patrick; Kahana, Michael J.

2014-01-01

Attempts to understand why memory predicts intelligence have not fully leveraged state-of-the-art measures of recall dynamics. Using data from a multi–session free recall study we examine individual differences in measures of recall initiation and post–initiation transitions. We identify four sources of variation: a recency factor reflecting variation in the tendency to initiate recall from an item near the end of the list, a primacy factor reflecting a tendency to initiate from the beginning of the list, a temporal factor corresponding to transitions mediated by temporal associations, and a semantic factor corresponding to semantically–mediated transitions. Together these four factors account for 83% of the variability in overall recall accuracy, suggesting they provide a nearly complete picture of recall dynamics. We also show that these sources of variability account for over 80% of the variance shared between memory and intelligence. The temporal association factor was the most influential in predicting both recall accuracy and intelligence. We outline a theory of how controlled drift of temporal context may be critical across a range of cognitive activities. PMID:24730719

Hydrologic Evaluation of TRMM Multisatellite Precipitation Analysis for Nanliu River Basin in Humid Southwestern China.

PubMed

Zhao, Yinjun; Xie, Qiongying; Lu, Yuan; Hu, Baoqing

2017-06-01

The accuracy of Tropical Rainfall Measuring Mission (TRMM) multi-satellite precipitation analysis (TMPA) daily accumulated precipitation products (3B42RTV7 and 3B42V7) was evaluated for a small basin (the Nanliu river basin). A direct comparison was performed against gauge observations from a period of 9 years (2000-2009) at temporal and spatial scales. The results show that the temporal-spatial precipitation characteristics of the Nanliu river basin are highly consistent with 3B42V7 relative to 3B42RTV7, with higher correlation coefficient (CC) approximately 0.9 at all temporal scales except for the daily scale and a lower relative bias percentage. 3B42V7 slightly overestimates precipitation at all temporal scales except the yearly scale; it slightly underestimates the precipitation at the daily spatial scale. The results also reveal that the precision of TMPA products increases with longer time-aggregated data, and the detection capability of daily TMPA precipitation products are enhanced by augmentation with daily precipitation rates. In addition, daily TMPA products were input into the Xin'anjiang hydrologic model; the results show that 3B42V7-based simulated outputs were well in line with actual stream flow observations, with a high CC (0.90) and Nash-Sutcliffe efficiency coefficient (NSE, 0.79), and the results adequately captured the pattern of the observed flow curve.

Spatial-temporal consistency between gross primary productivity and solar-induced chlorophyll fluorescence of vegetation in China during 2007-2014

NASA Astrophysics Data System (ADS)

Ma, J.; Xiao, X.; Zhang, Y.; Chen, B.; Zhao, B.

2017-12-01

Great significance exists in accurately estimating spatial-temporal patterns of gross primary production (GPP) because of its important role in global carbon cycle. Satellite-based light use efficiency (LUE) models are regarded as an efficient tool in simulating spatially time-sires GPP. However, the estimation of the accuracy of GPP simulations from LUE at both spatial and temporal scales is still a challenging work. In this study, we simulated GPP of vegetation in China during 2007-2014 using a LUE model (Vegetation Photosynthesis Model, VPM) based on MODIS (moderate-resolution imaging spectroradiometer) images of 8-day temporal and 500-m spatial resolutions and NCEP (National Center for Environmental Prediction) climate data. Global Ozone Monitoring Instrument 2 (GOME-2) solar-induced chlorophyll fluorescence (SIF) data were used to compare with VPM simulated GPP (GPPVPM) temporally and spatially using linear correlation analysis. Significant positive linear correlations exist between monthly GPPVPM and SIF data over both single year (2010) and multiple years (2007-2014) in China. Annual GPPVPM is significantly positive correlated with SIF (R2>0.43) spatially for all years during 2007-2014 and all seasons in 2010 (R2>0.37). GPP dynamic trends is high spatial-temporal heterogeneous in China during 2007-2014. The results of this study indicate that GPPVPM is temporally and spatially in line with SIF data, and space-borne SIF data have great potential in validating and parameterizing GPP estimation of LUE-based models.

Improving z-tracking accuracy in the two-photon single-particle tracking microscope.

PubMed

Liu, C; Liu, Y-L; Perillo, E P; Jiang, N; Dunn, A K; Yeh, H-C

2015-10-12

Here, we present a method that can improve the z-tracking accuracy of the recently invented TSUNAMI (Tracking of Single particles Using Nonlinear And Multiplexed Illumination) microscope. This method utilizes a maximum likelihood estimator (MLE) to determine the particle's 3D position that maximizes the likelihood of the observed time-correlated photon count distribution. Our Monte Carlo simulations show that the MLE-based tracking scheme can improve the z-tracking accuracy of TSUNAMI microscope by 1.7 fold. In addition, MLE is also found to reduce the temporal correlation of the z-tracking error. Taking advantage of the smaller and less temporally correlated z-tracking error, we have precisely recovered the hybridization-melting kinetics of a DNA model system from thousands of short single-particle trajectories in silico . Our method can be generally applied to other 3D single-particle tracking techniques.

Improving z-tracking accuracy in the two-photon single-particle tracking microscope

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, C.; Liu, Y.-L.; Perillo, E. P.

Here, we present a method that can improve the z-tracking accuracy of the recently invented TSUNAMI (Tracking of Single particles Using Nonlinear And Multiplexed Illumination) microscope. This method utilizes a maximum likelihood estimator (MLE) to determine the particle's 3D position that maximizes the likelihood of the observed time-correlated photon count distribution. Our Monte Carlo simulations show that the MLE-based tracking scheme can improve the z-tracking accuracy of TSUNAMI microscope by 1.7 fold. In addition, MLE is also found to reduce the temporal correlation of the z-tracking error. Taking advantage of the smaller and less temporally correlated z-tracking error, we havemore » precisely recovered the hybridization-melting kinetics of a DNA model system from thousands of short single-particle trajectories in silico. Our method can be generally applied to other 3D single-particle tracking techniques.« less

Investigation on changes in complex vegetation coverage using multi-temporal landsat data of Western Black Sea region--a case study.

PubMed

Coban, Huseyin Oguz; Koc, Ayhan; Eker, Mehmet

2010-01-01

Previous studies have been able to successfully detect changes in gently-sloping forested areas with low-diversity and homogeneous vegetation cover using medium-resolution satellite data such as landsat. The aim of the present study is to examine the capacity of multi-temporal landsat data to identify changes in forested areas with mixed vegetation and generally located on steep slopes or non-uniform topography landsat thematic mapper (TM) and landsat enhanced thematic mapperplus (ETM+) data for the years 1987-2000 was used to detect changes within a 19,500 ha forested area in the Western Black sea region of Turkey. The data comply with the forest cover type maps previously created for forest management plans of the research area. The methods used to detect changes were: post-classification comparison, image differencing, image rationing and NDVI (Normalized Difference Vegetation Index) differencing methods. Following the supervised classification process, error matrices were used to evaluate the accuracy of classified images obtained. The overall accuracy has been calculated as 87.59% for 1987 image and as 91.81% for 2000 image. General kappa statistics have been calculated as 0.8543 and 0.9038 for 1987 and 2000, respectively. The changes identified via the post-classification comparison method were compared with other change detetion methods. Maximum coherence was found to be 74.95% at 4/3 band rate. The NDVI difference and 3rd band difference methods achieved the same coherence with slight variations. The results suggest that landsat satellite data accurately conveys the temporal changes which occur on steeply-sloping forested areas with a mixed structure, providing a limited amount of detail but with a high level of accuracy. Moreover it has been decided that the post-classification comparison method can meet the needs of forestry activities better than other methods as it provides information about the direction of these changes.

Automated Geo/Co-Registration of Multi-Temporal Very-High-Resolution Imagery.

PubMed

Han, Youkyung; Oh, Jaehong

2018-05-17

For time-series analysis using very-high-resolution (VHR) multi-temporal satellite images, both accurate georegistration to the map coordinates and subpixel-level co-registration among the images should be conducted. However, applying well-known matching methods, such as scale-invariant feature transform and speeded up robust features for VHR multi-temporal images, has limitations. First, they cannot be used for matching an optical image to heterogeneous non-optical data for georegistration. Second, they produce a local misalignment induced by differences in acquisition conditions, such as acquisition platform stability, the sensor's off-nadir angle, and relief displacement of the considered scene. Therefore, this study addresses the problem by proposing an automated geo/co-registration framework for full-scene multi-temporal images acquired from a VHR optical satellite sensor. The proposed method comprises two primary steps: (1) a global georegistration process, followed by (2) a fine co-registration process. During the first step, two-dimensional multi-temporal satellite images are matched to three-dimensional topographic maps to assign the map coordinates. During the second step, a local analysis of registration noise pixels extracted between the multi-temporal images that have been mapped to the map coordinates is conducted to extract a large number of well-distributed corresponding points (CPs). The CPs are finally used to construct a non-rigid transformation function that enables minimization of the local misalignment existing among the images. Experiments conducted on five Kompsat-3 full scenes confirmed the effectiveness of the proposed framework, showing that the georegistration performance resulted in an approximately pixel-level accuracy for most of the scenes, and the co-registration performance further improved the results among all combinations of the georegistered Kompsat-3 image pairs by increasing the calculated cross-correlation values.

Submillisecond Optogenetic Control of Neuronal Firing with Two-Photon Holographic Photoactivation of Chronos

PubMed Central

Ronzitti, Emiliano; Conti, Rossella; Zampini, Valeria; Tanese, Dimitrii; Klapoetke, Nathan; Boyden, Edward S.; Papagiakoumou, Eirini

2017-01-01

Optogenetic neuronal network manipulation promises to unravel a long-standing mystery in neuroscience: how does microcircuit activity relate causally to behavioral and pathological states? The challenge to evoke spikes with high spatial and temporal complexity necessitates further joint development of light-delivery approaches and custom opsins. Two-photon (2P) light-targeting strategies demonstrated in-depth generation of action potentials in photosensitive neurons both in vitro and in vivo, but thus far lack the temporal precision necessary to induce precisely timed spiking events. Here, we show that efficient current integration enabled by 2P holographic amplified laser illumination of Chronos, a highly light-sensitive and fast opsin, can evoke spikes with submillisecond precision and repeated firing up to 100 Hz in brain slices from Swiss male mice. These results pave the way for optogenetic manipulation with the spatial and temporal sophistication necessary to mimic natural microcircuit activity. SIGNIFICANCE STATEMENT To reveal causal links between neuronal activity and behavior, it is necessary to develop experimental strategies to induce spatially and temporally sophisticated perturbation of network microcircuits. Two-photon computer generated holography (2P-CGH) recently demonstrated 3D optogenetic control of selected pools of neurons with single-cell accuracy in depth in the brain. Here, we show that exciting the fast opsin Chronos with amplified laser 2P-CGH enables cellular-resolution targeting with unprecedented temporal control, driving spiking up to 100 Hz with submillisecond onset precision using low laser power densities. This system achieves a unique combination of spatial flexibility and temporal precision needed to pattern optogenetically inputs that mimic natural neuronal network activity patterns. PMID:28972125

A highly accurate symmetric optical flow based high-dimensional nonlinear spatial normalization of brain images.

PubMed

Wen, Ying; Hou, Lili; He, Lianghua; Peterson, Bradley S; Xu, Dongrong

2015-05-01

Spatial normalization plays a key role in voxel-based analyses of brain images. We propose a highly accurate algorithm for high-dimensional spatial normalization of brain images based on the technique of symmetric optical flow. We first construct a three dimension optical model with the consistency assumption of intensity and consistency of the gradient of intensity under a constraint of discontinuity-preserving spatio-temporal smoothness. Then, an efficient inverse consistency optical flow is proposed with aims of higher registration accuracy, where the flow is naturally symmetric. By employing a hierarchical strategy ranging from coarse to fine scales of resolution and a method of Euler-Lagrange numerical analysis, our algorithm is capable of registering brain images data. Experiments using both simulated and real datasets demonstrated that the accuracy of our algorithm is not only better than that of those traditional optical flow algorithms, but also comparable to other registration methods used extensively in the medical imaging community. Moreover, our registration algorithm is fully automated, requiring a very limited number of parameters and no manual intervention. Copyright © 2015 Elsevier Inc. All rights reserved.

Dopamine reward prediction-error signalling: a two-component response

PubMed Central

Schultz, Wolfram

2017-01-01

Environmental stimuli and objects, including rewards, are often processed sequentially in the brain. Recent work suggests that the phasic dopamine reward prediction-error response follows a similar sequential pattern. An initial brief, unselective and highly sensitive increase in activity unspecifically detects a wide range of environmental stimuli, then quickly evolves into the main response component, which reflects subjective reward value and utility. This temporal evolution allows the dopamine reward prediction-error signal to optimally combine speed and accuracy. PMID:26865020

An information-theoretic approach to designing the plane spacing for multifocal plane microscopy

PubMed Central

Tahmasbi, Amir; Ram, Sripad; Chao, Jerry; Abraham, Anish V.; Ward, E. Sally; Ober, Raimund J.

2015-01-01

Multifocal plane microscopy (MUM) is a 3D imaging modality which enables the localization and tracking of single molecules at high spatial and temporal resolution by simultaneously imaging distinct focal planes within the sample. MUM overcomes the depth discrimination problem of conventional microscopy and allows high accuracy localization of a single molecule in 3D along the z-axis. An important question in the design of MUM experiments concerns the appropriate number of focal planes and their spacings to achieve the best possible 3D localization accuracy along the z-axis. Ideally, it is desired to obtain a 3D localization accuracy that is uniform over a large depth and has small numerical values, which guarantee that the single molecule is continuously detectable. Here, we address this concern by developing a plane spacing design strategy based on the Fisher information. In particular, we analyze the Fisher information matrix for the 3D localization problem along the z-axis and propose spacing scenarios termed the strong coupling and the weak coupling spacings, which provide appropriate 3D localization accuracies. Using these spacing scenarios, we investigate the detectability of the single molecule along the z-axis and study the effect of changing the number of focal planes on the 3D localization accuracy. We further review a software module we recently introduced, the MUMDesignTool, that helps to design the plane spacings for a MUM setup. PMID:26113764

Hybrid method for building extraction in vegetation-rich urban areas from very high-resolution satellite imagery

NASA Astrophysics Data System (ADS)

Jayasekare, Ajith S.; Wickramasuriya, Rohan; Namazi-Rad, Mohammad-Reza; Perez, Pascal; Singh, Gaurav

2017-07-01

A continuous update of building information is necessary in today's urban planning. Digital images acquired by remote sensing platforms at appropriate spatial and temporal resolutions provide an excellent data source to achieve this. In particular, high-resolution satellite images are often used to retrieve objects such as rooftops using feature extraction. However, high-resolution images acquired over built-up areas are associated with noises such as shadows that reduce the accuracy of feature extraction. Feature extraction heavily relies on the reflectance purity of objects, which is difficult to perfect in complex urban landscapes. An attempt was made to increase the reflectance purity of building rooftops affected by shadows. In addition to the multispectral (MS) image, derivatives thereof namely, normalized difference vegetation index and principle component (PC) images were incorporated in generating the probability image. This hybrid probability image generation ensured that the effect of shadows on rooftop extraction, particularly on light-colored roofs, is largely eliminated. The PC image was also used for image segmentation, which further increased the accuracy compared to segmentation performed on an MS image. Results show that the presented method can achieve higher rooftop extraction accuracy (70.4%) in vegetation-rich urban areas compared to traditional methods.

The space station: Human factors and productivity

NASA Technical Reports Server (NTRS)

Gillan, D. J.; Burns, M. J.; Nicodemus, C. L.; Smith, R. L.

1986-01-01

Human factor researchers and engineers are making inputs into the early stages of the design of the Space Station to improve both the quality of life and work on-orbit. Effective integration of the human factors information related to various Intravehicular Activity (IVA), Extravehicular Activity (EVA), and teletobotics systems during the Space Station design will result in increased productivity, increased flexibility of the Space Stations systems, lower cost of operations, improved reliability, and increased safety for the crew onboard the Space Station. The major features of productivity examined include the cognitive and physical effort involved in work, the accuracy of worker output and ability to maintain performance at a high level of accuracy, the speed and temporal efficiency with which a worker performs, crewmember satisfaction with their work environment, and the relation between performance and cost.

Moving Beyond Streamflow Observations: Lessons From A Multi-Objective Calibration Experiment in the Mississippi Basin

NASA Astrophysics Data System (ADS)

Koppa, A.; Gebremichael, M.; Yeh, W. W. G.

2017-12-01

Calibrating hydrologic models in large catchments using a sparse network of streamflow gauges adversely affects the spatial and temporal accuracy of other water balance components which are important for climate-change, land-use and drought studies. This study combines remote sensing data and the concept of Pareto-Optimality to address the following questions: 1) What is the impact of streamflow (SF) calibration on the spatio-temporal accuracy of Evapotranspiration (ET), near-surface Soil Moisture (SM) and Total Water Storage (TWS)? 2) What is the best combination of fluxes that can be used to calibrate complex hydrological models such that both the accuracy of streamflow and the spatio-temporal accuracy of ET, SM and TWS is preserved? The study area is the Mississippi Basin in the United States (encompassing HUC-2 regions 5,6,7,9,10 and 11). 2003 and 2004, two climatologically average years are chosen for calibration and validation of the Noah-MP hydrologic model. Remotely sensed ET data is sourced from GLEAM, SM from ESA-CCI and TWS from GRACE. Single objective calibration is carried out using DDS Algorithm. For Multi objective calibration PA-DDS is used. First, the Noah-MP model is calibrated using a single objective function (Minimize Mean Square Error) for the outflow from the 6 HUC-2 sub-basins for 2003. Spatial correlograms are used to compare the spatial structure of ET, SM and TWS between the model and the remote sensing data. Spatial maps of RMSE and Mean Error are used to quantify the impact of calibrating streamflow on the accuracy of ET, SM and TWS estimates. Next, a multi-objective calibration experiment is setup to determine the pareto optimal parameter sets (pareto front) for the following cases - 1) SF and ET, 2) SF and SM, 3) SF and TWS, 4) SF, ET and SM, 5) SF, ET and TWS, 6) SF, SM and TWS, 7) SF, ET, SM and TWS. The best combination of fluxes that provides the optimal trade-off between accurate streamflow and preserving the spatio-temporal structure of ET, SM and TWS is then determined by validating the model outputs for the pareto-optimal parameter sets. Results from single-objective calibration experiment with streamflow shows that it does indeed negatively impact the accuracy of ET, SM and TWS estimates.

Accurate, reliable prototype earth horizon sensor head

NASA Technical Reports Server (NTRS)

Schwarz, F.; Cohen, H.

1973-01-01

The design and performance is described of an accurate and reliable prototype earth sensor head (ARPESH). The ARPESH employs a detection logic 'locator' concept and horizon sensor mechanization which should lead to high accuracy horizon sensing that is minimally degraded by spatial or temporal variations in sensing attitude from a satellite in orbit around the earth at altitudes in the 500 km environ 1,2. An accuracy of horizon location to within 0.7 km has been predicted, independent of meteorological conditions. This corresponds to an error of 0.015 deg-at 500 km altitude. Laboratory evaluation of the sensor indicates that this accuracy is achieved. First, the basic operating principles of ARPESH are described; next, detailed design and construction data is presented and then performance of the sensor under laboratory conditions in which the sensor is installed in a simulator that permits it to scan over a blackbody source against background representing the earth space interface for various equivalent plant temperatures.

Spatio-temporal Change Patterns of Tropical Forests from 2000 to 2014 Using MOD09A1 Dataset

NASA Astrophysics Data System (ADS)

Qin, Y.; Xiao, X.; Dong, J.

2016-12-01

Large-scale deforestation and forest degradation in the tropical region have resulted in extensive carbon emissions and biodiversity loss. However, restricted by the availability of good-quality observations, large uncertainty exists in mapping the spatial distribution of forests and their spatio-temporal changes. In this study, we proposed a pixel- and phenology-based algorithm to identify and map annual tropical forests from 2000 to 2014, using the 8-day, 500-m MOD09A1 (v005) product, under the support of Google cloud computing (Google Earth Engine). A temporal filter was applied to reduce the random noises and to identify the spatio-temporal changes of forests. We then built up a confusion matrix and assessed the accuracy of the annual forest maps based on the ground reference interpreted from high spatial resolution images in Google Earth. The resultant forest maps showed the consistent forest/non-forest, forest loss, and forest gain in the pan-tropical zone during 2000 - 2014. The proposed algorithm showed the potential for tropical forest mapping and the resultant forest maps are important for the estimation of carbon emission and biodiversity loss.

Spatio-temporal Event Classification using Time-series Kernel based Structured Sparsity

PubMed Central

Jeni, László A.; Lőrincz, András; Szabó, Zoltán; Cohn, Jeffrey F.; Kanade, Takeo

2016-01-01

In many behavioral domains, such as facial expression and gesture, sparse structure is prevalent. This sparsity would be well suited for event detection but for one problem. Features typically are confounded by alignment error in space and time. As a consequence, high-dimensional representations such as SIFT and Gabor features have been favored despite their much greater computational cost and potential loss of information. We propose a Kernel Structured Sparsity (KSS) method that can handle both the temporal alignment problem and the structured sparse reconstruction within a common framework, and it can rely on simple features. We characterize spatio-temporal events as time-series of motion patterns and by utilizing time-series kernels we apply standard structured-sparse coding techniques to tackle this important problem. We evaluated the KSS method using both gesture and facial expression datasets that include spontaneous behavior and differ in degree of difficulty and type of ground truth coding. KSS outperformed both sparse and non-sparse methods that utilize complex image features and their temporal extensions. In the case of early facial event classification KSS had 10% higher accuracy as measured by F1 score over kernel SVM methods1. PMID:27830214

The brain connectome as a personalized biomarker of seizure outcomes after temporal lobectomy.

PubMed

Bonilha, Leonardo; Jensen, Jens H; Baker, Nathaniel; Breedlove, Jesse; Nesland, Travis; Lin, Jack J; Drane, Daniel L; Saindane, Amit M; Binder, Jeffrey R; Kuzniecky, Ruben I

2015-05-05

We examined whether individual neuronal architecture obtained from the brain connectome can be used to estimate the surgical success of anterior temporal lobectomy (ATL) in patients with temporal lobe epilepsy (TLE). We retrospectively studied 35 consecutive patients with TLE who underwent ATL. The structural brain connectome was reconstructed from all patients using presurgical diffusion MRI. Network links in patients were standardized as Z scores based on connectomes reconstructed from healthy controls. The topography of abnormalities in linkwise elements of the connectome was assessed on subnetworks linking ipsilateral temporal with extratemporal regions. Predictive models were constructed based on the individual prevalence of linkwise Z scores >2 and based on presurgical clinical data. Patients were more likely to achieve postsurgical seizure freedom if they exhibited fewer abnormalities within a subnetwork composed of the ipsilateral hippocampus, amygdala, thalamus, superior frontal region, lateral temporal gyri, insula, orbitofrontal cortex, cingulate, and lateral occipital gyrus. Seizure-free surgical outcome was predicted by neural architecture alone with 90% specificity (83% accuracy), and by neural architecture combined with clinical data with 94% specificity (88% accuracy). Individual variations in connectome topography, combined with presurgical clinical data, may be used as biomarkers to better estimate surgical outcomes in patients with TLE. © 2015 American Academy of Neurology.

A new vehicle emission inventory for China with high spatial and temporal resolution

NASA Astrophysics Data System (ADS)

Zheng, B.; Huo, H.; Zhang, Q.; Yao, Z. L.; Wang, X. T.; Yang, X. F.; Liu, H.; He, K. B.

2013-12-01

This study is the first in a series of papers that aim to develop high-resolution emission databases for different anthropogenic sources in China. Here we focus on on-road transportation. Because of the increasing impact of on-road transportation on regional air quality, developing an accurate and high-resolution vehicle emission inventory is important for both the research community and air quality management. This work proposes a new inventory methodology to improve the spatial and temporal accuracy and resolution of vehicle emissions in China. We calculate, for the first time, the monthly vehicle emissions (CO, NMHC, NOx, and PM2.5) for 2008 in 2364 counties (an administrative unit one level lower than city) by developing a set of approaches to estimate vehicle stock and monthly emission factors at county-level, and technology distribution at provincial level. We then introduce allocation weights for the vehicle kilometers traveled to assign the county-level emissions onto 0.05° × 0.05° grids based on the China Digital Road-network Map (CDRM). The new methodology overcomes the common shortcomings of previous inventory methods, including neglecting the geographical differences between key parameters and using surrogates that are weakly related to vehicle activities to allocate vehicle emissions. The new method has great advantages over previous methods in depicting the spatial distribution characteristics of vehicle activities and emissions. This work provides a better understanding of the spatial representation of vehicle emissions in China and can benefit both air quality modeling and management with improved spatial accuracy.

Radiometric and geometric assessment of data from the RapidEye constellation of satellites

USGS Publications Warehouse

Chander, Gyanesh; Haque, Md. Obaidul; Sampath, Aparajithan; Brunn, A.; Trosset, G.; Hoffmann, D.; Roloff, S.; Thiele, M.; Anderson, C.

2013-01-01

To monitor land surface processes over a wide range of temporal and spatial scales, it is critical to have coordinated observations of the Earth's surface using imagery acquired from multiple spaceborne imaging sensors. The RapidEye (RE) satellite constellation acquires high-resolution satellite images covering the entire globe within a very short period of time by sensors identical in construction and cross-calibrated to each other. To evaluate the RE high-resolution Multi-spectral Imager (MSI) sensor capabilities, a cross-comparison between the RE constellation of sensors was performed first using image statistics based on large common areas observed over pseudo-invariant calibration sites (PICS) by the sensors and, second, by comparing the on-orbit radiometric calibration temporal trending over a large number of calibration sites. For any spectral band, the individual responses measured by the five satellites of the RE constellation were found to differ <2–3% from the average constellation response depending on the method used for evaluation. Geometric assessment was also performed to study the positional accuracy and relative band-to-band (B2B) alignment of the image data sets. The position accuracy was assessed by comparing the RE imagery against high-resolution aerial imagery, while the B2B characterization was performed by registering each band against every other band to ensure that the proper band alignment is provided for an image product. The B2B results indicate that the internal alignments of these five RE bands are in agreement, with bands typically registered to within 0.25 pixels of each other or better.

Targeting an efficient target-to-target interval for P300 speller brain–computer interfaces

PubMed Central

Sellers, Eric W.; Wang, Xingyu

2013-01-01

Longer target-to-target intervals (TTI) produce greater P300 event-related potential amplitude, which can increase brain–computer interface (BCI) classification accuracy and decrease the number of flashes needed for accurate character classification. However, longer TTIs requires more time for each trial, which will decrease the information transfer rate of BCI. In this paper, a P300 BCI using a 7 × 12 matrix explored new flash patterns (16-, 18- and 21-flash pattern) with different TTIs to assess the effects of TTI on P300 BCI performance. The new flash patterns were designed to minimize TTI, decrease repetition blindness, and examine the temporal relationship between each flash of a given stimulus by placing a minimum of one (16-flash pattern), two (18-flash pattern), or three (21-flash pattern) non-target flashes between each target flashes. Online results showed that the 16-flash pattern yielded the lowest classification accuracy among the three patterns. The results also showed that the 18-flash pattern provides a significantly higher information transfer rate (ITR) than the 21-flash pattern; both patterns provide high ITR and high accuracy for all subjects. PMID:22350331

Comparison of Hyperspectral and Multispectral Satellites for Discriminating Land Cover in Northern California

NASA Astrophysics Data System (ADS)

Clark, M. L.; Kilham, N. E.

2015-12-01

Land-cover maps are important science products needed for natural resource and ecosystem service management, biodiversity conservation planning, and assessing human-induced and natural drivers of land change. Most land-cover maps at regional to global scales are produced with remote sensing techniques applied to multispectral satellite imagery with 30-500 m pixel sizes (e.g., Landsat, MODIS). Hyperspectral, or imaging spectrometer, imagery measuring the visible to shortwave infrared regions (VSWIR) of the spectrum have shown impressive capacity to map plant species and coarser land-cover associations, yet techniques have not been widely tested at regional and greater spatial scales. The Hyperspectral Infrared Imager (HyspIRI) mission is a VSWIR hyperspectral and thermal satellite being considered for development by NASA. The goal of this study was to assess multi-temporal, HyspIRI-like satellite imagery for improved land cover mapping relative to multispectral satellites. We mapped FAO Land Cover Classification System (LCCS) classes over 22,500 km2 in the San Francisco Bay Area, California using 30-m HyspIRI, Landsat 8 and Sentinel-2 imagery simulated from data acquired by NASA's AVIRIS airborne sensor. Random Forests (RF) and Multiple-Endmember Spectral Mixture Analysis (MESMA) classifiers were applied to the simulated images and accuracies were compared to those from real Landsat 8 images. The RF classifier was superior to MESMA, and multi-temporal data yielded higher accuracy than summer-only data. With RF, hyperspectral data had overall accuracy of 72.2% and 85.1% with full 20-class and reduced 12-class schemes, respectively. Multispectral imagery had lower accuracy. For example, simulated and real Landsat data had 7.5% and 4.6% lower accuracy than HyspIRI data with 12 classes, respectively. In summary, our results indicate increased mapping accuracy using HyspIRI multi-temporal imagery, particularly in discriminating different natural vegetation types, such as spectrally-mixed woodlands and forests.

Influence of P300 latency jitter on event related potential-based brain-computer interface performance

NASA Astrophysics Data System (ADS)

Aricò, P.; Aloise, F.; Schettini, F.; Salinari, S.; Mattia, D.; Cincotti, F.

2014-06-01

Objective. Several ERP-based brain-computer interfaces (BCIs) that can be controlled even without eye movements (covert attention) have been recently proposed. However, when compared to similar systems based on overt attention, they displayed significantly lower accuracy. In the current interpretation, this is ascribed to the absence of the contribution of short-latency visual evoked potentials (VEPs) in the tasks performed in the covert attention modality. This study aims to investigate if this decrement (i) is fully explained by the lack of VEP contribution to the classification accuracy; (ii) correlates with lower temporal stability of the single-trial P300 potentials elicited in the covert attention modality. Approach. We evaluated the latency jitter of P300 evoked potentials in three BCI interfaces exploiting either overt or covert attention modalities in 20 healthy subjects. The effect of attention modality on the P300 jitter, and the relative contribution of VEPs and P300 jitter to the classification accuracy have been analyzed. Main results. The P300 jitter is higher when the BCI is controlled in covert attention. Classification accuracy negatively correlates with jitter. Even disregarding short-latency VEPs, overt-attention BCI yields better accuracy than covert. When the latency jitter is compensated offline, the difference between accuracies is not significant. Significance. The lower temporal stability of the P300 evoked potential generated during the tasks performed in covert attention modality should be regarded as the main contributing explanation of lower accuracy of covert-attention ERP-based BCIs.

A Critical Test of Temporal and Spatial Accuracy of the Tobii T60XL Eye Tracker

ERIC Educational Resources Information Center

Morgante, James D.; Zolfaghari, Rahman; Johnson, Scott P.

2012-01-01

Infant eye tracking is becoming increasingly popular for its presumed precision relative to traditional looking time paradigms and potential to yield new insights into developmental processes. However, there is strong reason to suspect that the temporal and spatial resolution of popular eye tracking systems is not entirely accurate, potentially…

Integration of TerraSAR-X, RapidEye and airborne lidar for remote sensing of intertidal bedforms on the upper flats of Norderney (German Wadden Sea)

NASA Astrophysics Data System (ADS)

Adolph, Winny; Jung, Richard; Schmidt, Alena; Ehlers, Manfred; Heipke, Christian; Bartholomä, Alexander; Farke, Hubert

2017-04-01

The Wadden Sea is a large coastal transition area adjoining the southern North Sea uniting ecological key functions with an important role in coastal protection. The region is strictly protected by EU directives and national law and is a UNESCO World Heritage Site, requiring frequent quality assessments and regular monitoring. In 2014 an intertidal bedform area characterised by alternating crests and water-covered troughs on the tidal flats of the island of Norderney (German Wadden Sea sector) was chosen to test different remote sensing methods for habitat mapping: airborne lidar, satellite-based radar (TerraSAR-X) and electro-optical sensors (RapidEye). The results revealed that, although sensitive to different surface qualities, all sensors were able to image the bedforms. A digital terrain model generated from the lidar data shows crests and slopes of the bedforms with high geometric accuracy in the centimetre range, but high costs limit the operation area. TerraSAR-X data enabled identifying the positions of the bedforms reflecting the residual water in the troughs also with a high resolution of up to 1.1 m, but with larger footprints and much higher temporal availability. RapidEye data are sensitive to differences in sediment moisture employed to identify crest areas, slopes and troughs, with high spatial coverage but the lowest resolution (6.5 m). Monitoring concepts may differ in their remote sensing requirements regarding areal coverage, spatial and temporal resolution, sensitivity and geometric accuracy. Also financial budgets limit the selection of sensors. Thus, combining differing assets into an integrated concept of remote sensing contributes to solving these issues.

Retrieving high-resolution surface solar radiation with cloud parameters derived by combining MODIS and MTSAT data

NASA Astrophysics Data System (ADS)

Tang, Wenjun; Qin, Jun; Yang, Kun; Liu, Shaomin; Lu, Ning; Niu, Xiaolei

2016-03-01

Cloud parameters (cloud mask, effective particle radius, and liquid/ice water path) are the important inputs in estimating surface solar radiation (SSR). These parameters can be derived from MODIS with high accuracy, but their temporal resolution is too low to obtain high-temporal-resolution SSR retrievals. In order to obtain hourly cloud parameters, an artificial neural network (ANN) is applied in this study to directly construct a functional relationship between MODIS cloud products and Multifunctional Transport Satellite (MTSAT) geostationary satellite signals. In addition, an efficient parameterization model for SSR retrieval is introduced and, when driven with MODIS atmospheric and land products, its root mean square error (RMSE) is about 100 W m-2 for 44 Baseline Surface Radiation Network (BSRN) stations. Once the estimated cloud parameters and other information (such as aerosol, precipitable water, ozone) are input to the model, we can derive SSR at high spatiotemporal resolution. The retrieved SSR is first evaluated against hourly radiation data at three experimental stations in the Haihe River basin of China. The mean bias error (MBE) and RMSE in hourly SSR estimate are 12.0 W m-2 (or 3.5 %) and 98.5 W m-2 (or 28.9 %), respectively. The retrieved SSR is also evaluated against daily radiation data at 90 China Meteorological Administration (CMA) stations. The MBEs are 9.8 W m-2 (or 5.4 %); the RMSEs in daily and monthly mean SSR estimates are 34.2 W m-2 (or 19.1 %) and 22.1 W m-2 (or 12.3 %), respectively. The accuracy is comparable to or even higher than two other radiation products (GLASS and ISCCP-FD), and the present method is more computationally efficient and can produce hourly SSR data at a spatial resolution of 5 km.

Methodology for in situ gas sampling, transport and laboratory analysis of gases from stranded cetaceans

NASA Astrophysics Data System (ADS)

de Quirós, Yara Bernaldo; González-Díaz, Óscar; Saavedra, Pedro; Arbelo, Manuel; Sierra, Eva; Sacchini, Simona; Jepson, Paul D.; Mazzariol, Sandro; di Guardo, Giovanni; Fernández, Antonio

2011-12-01

Gas-bubble lesions were described in cetaceans stranded in spatio-temporal concordance with naval exercises using high-powered sonars. A behaviourally induced decompression sickness-like disease was proposed as a plausible causal mechanism, although these findings remain scientifically controversial. Investigations into the constituents of the gas bubbles in suspected gas embolism cases are highly desirable. We have found that vacuum tubes, insulin syringes and an aspirometer are reliable tools for in situ gas sampling, storage and transportation without appreciable loss of gas and without compromising the accuracy of the analysis. Gas analysis is conducted by gas chromatography in the laboratory. This methodology was successfully applied to a mass stranding of sperm whales, to a beaked whale stranded in spatial and temporal association with military exercises and to a cetacean chronic gas embolism case. Results from the freshest animals confirmed that bubbles were relatively free of gases associated with putrefaction and consisted predominantly of nitrogen.

Temporal effects in trend prediction: identifying the most popular nodes in the future.

PubMed

Zhou, Yanbo; Zeng, An; Wang, Wei-Hong

2015-01-01

Prediction is an important problem in different science domains. In this paper, we focus on trend prediction in complex networks, i.e. to identify the most popular nodes in the future. Due to the preferential attachment mechanism in real systems, nodes' recent degree and cumulative degree have been successfully applied to design trend prediction methods. Here we took into account more detailed information about the network evolution and proposed a temporal-based predictor (TBP). The TBP predicts the future trend by the node strength in the weighted network with the link weight equal to its exponential aging. Three data sets with time information are used to test the performance of the new method. We find that TBP have high general accuracy in predicting the future most popular nodes. More importantly, it can identify many potential objects with low popularity in the past but high popularity in the future. The effect of the decay speed in the exponential aging on the results is discussed in detail.

Temporal Effects in Trend Prediction: Identifying the Most Popular Nodes in the Future

PubMed Central

Zhou, Yanbo; Zeng, An; Wang, Wei-Hong

2015-01-01

Prediction is an important problem in different science domains. In this paper, we focus on trend prediction in complex networks, i.e. to identify the most popular nodes in the future. Due to the preferential attachment mechanism in real systems, nodes’ recent degree and cumulative degree have been successfully applied to design trend prediction methods. Here we took into account more detailed information about the network evolution and proposed a temporal-based predictor (TBP). The TBP predicts the future trend by the node strength in the weighted network with the link weight equal to its exponential aging. Three data sets with time information are used to test the performance of the new method. We find that TBP have high general accuracy in predicting the future most popular nodes. More importantly, it can identify many potential objects with low popularity in the past but high popularity in the future. The effect of the decay speed in the exponential aging on the results is discussed in detail. PMID:25806810

3D-resolved fluorescence and phosphorescence lifetime imaging using temporal focusing wide-field two-photon excitation

PubMed Central

Choi, Heejin; Tzeranis, Dimitrios S.; Cha, Jae Won; Clémenceau, Philippe; de Jong, Sander J. G.; van Geest, Lambertus K.; Moon, Joong Ho; Yannas, Ioannis V.; So, Peter T. C.

2012-01-01

Fluorescence and phosphorescence lifetime imaging are powerful techniques for studying intracellular protein interactions and for diagnosing tissue pathophysiology. While lifetime-resolved microscopy has long been in the repertoire of the biophotonics community, current implementations fall short in terms of simultaneously providing 3D resolution, high throughput, and good tissue penetration. This report describes a new highly efficient lifetime-resolved imaging method that combines temporal focusing wide-field multiphoton excitation and simultaneous acquisition of lifetime information in frequency domain using a nanosecond gated imager from a 3D-resolved plane. This approach is scalable allowing fast volumetric imaging limited only by the available laser peak power. The accuracy and performance of the proposed method is demonstrated in several imaging studies important for understanding peripheral nerve regeneration processes. Most importantly, the parallelism of this approach may enhance the imaging speed of long lifetime processes such as phosphorescence by several orders of magnitude. PMID:23187477

Methodology for in situ gas sampling, transport and laboratory analysis of gases from stranded cetaceans

PubMed Central

de Quirós, Yara Bernaldo; González-Díaz, Óscar; Saavedra, Pedro; Arbelo, Manuel; Sierra, Eva; Sacchini, Simona; Jepson, Paul D.; Mazzariol, Sandro; Di Guardo, Giovanni; Fernández, Antonio

2011-01-01

Gas-bubble lesions were described in cetaceans stranded in spatio-temporal concordance with naval exercises using high-powered sonars. A behaviourally induced decompression sickness-like disease was proposed as a plausible causal mechanism, although these findings remain scientifically controversial. Investigations into the constituents of the gas bubbles in suspected gas embolism cases are highly desirable. We have found that vacuum tubes, insulin syringes and an aspirometer are reliable tools for in situ gas sampling, storage and transportation without appreciable loss of gas and without compromising the accuracy of the analysis. Gas analysis is conducted by gas chromatography in the laboratory. This methodology was successfully applied to a mass stranding of sperm whales, to a beaked whale stranded in spatial and temporal association with military exercises and to a cetacean chronic gas embolism case. Results from the freshest animals confirmed that bubbles were relatively free of gases associated with putrefaction and consisted predominantly of nitrogen. PMID:22355708

L-Band Transmit/Receive Module for Phase-Stable Array Antennas

NASA Technical Reports Server (NTRS)

Andricos, Constantine; Edelstein, Wendy; Krimskiy, Vladimir

2008-01-01

Interferometric synthetic aperture radar (InSAR) has been shown to provide very sensitive measurements of surface deformation and displacement on the order of 1 cm. Future systematic measurements of surface deformation will require this capability over very large areas (300 km) from space. To achieve these required accuracies, these spaceborne sensors must exhibit low temporal decorrelation and be temporally stable systems. An L-band (24-cmwavelength) InSAR instrument using an electronically steerable radar antenna is suited to meet these needs. In order to achieve the 1-cm displacement accuracy, the phased array antenna requires phase-stable transmit/receive (T/R) modules. The T/R module operates at L-band (1.24 GHz) and has less than 1- deg absolute phase stability and less than 0.1-dB absolute amplitude stability over temperature. The T/R module is also high power (30 W) and power efficient (60-percent overall efficiency). The design is currently implemented using discrete components and surface mount technology. The basic T/R module architecture is augmented with a calibration loop to compensate for temperature variations, component variations, and path loss variations as a function of beam settings. The calibration circuit consists of an amplitude and phase detector, and other control circuitry, to compare the measured gain and phase to a reference signal and uses this signal to control a precision analog phase shifter and analog attenuator. An architecture was developed to allow for the module to be bidirectional, to operate in both transmit and receive mode. The architecture also includes a power detector used to maintain a transmitter power output constant within 0.1 dB. The use of a simple, stable, low-cost, and high-accuracy gain and phase detector made by Analog Devices (AD8302), combined with a very-high efficiency T/R module, is novel. While a self-calibrating T/R module capability has been sought for years, a practical and cost-effective solution has never been demonstrated. By adding the calibration loop to an existing high-efficiency T/R module, there is a demonstrated order-of-magnitude improvement in the amplitude and phase stability.

High sensitive and high temporal and spatial resolved image of reactive species in atmospheric pressure surface discharge reactor by laser induced fluorescence

NASA Astrophysics Data System (ADS)

Gao, Liang; Feng, Chun-Lei; Wang, Zhi-Wei; Ding, Hongbin

2017-05-01

The current paucity of spatial and temporal characterization of reactive oxygen and nitrogen species (RONS) concentration has been a major hurdle to the advancement and clinical translation of low temperature atmospheric plasmas. In this study, an advanced laser induced fluorescence (LIF) system has been developed to be an effective antibacterial surface discharge reactor for the diagnosis of RONS, where the highest spatial and temporal resolution of the LIF system has been achieved to ˜100 μm scale and ˜20 ns scale, respectively. Measurements on an oxidative OH radical have been carried out as typical RONS for the benchmark of the whole LIF system, where absolute number density calibration has been performed on the basis of the laser Rayleigh scattering method. Requirements for pixel resolved spatial distribution and outer plasma region detection become challenging tasks due to the low RONS concentration (˜ppb level) and strong interference, especially the discharge induced emission and pulsed laser induced stray light. In order to design the highly sensitive LIF system, a self-developed fluorescence telescope, the optimization of high precision synchronization among a tunable pulsed laser, a surface discharge generator, intensified Charge Coupled Device (iCCD) camera, and an oscilloscope have been performed. Moreover, an image BOXCAR approach has been developed to remarkably improve the sensitivity of the whole LIF system by optimizing spatial and temporal gating functions via both hardware and software, which has been integrated into our automatic control and data acquisition system on the LabVIEW platform. In addition, a reciprocation averaging measurement has been applied to verify the accuracy of the whole LIF detecting system, indicating the relative standard deviation of ˜3%.

Respiratory-gated segment reconstruction for radiation treatment planning using 256-slice CT-scanner during free breathing

NASA Astrophysics Data System (ADS)

Mori, Shinichiro; Endo, Masahiro; Kohno, Ryosuke; Minohara, Shinichi; Kohno, Kazutoshi; Asakura, Hiroshi; Fujiwara, Hideaki; Murase, Kenya

2005-04-01

The conventional respiratory-gated CT scan technique includes anatomic motion induced artifacts due to the low temporal resolution. They are a significant source of error in radiotherapy treatment planning for the thorax and upper abdomen. Temporal resolution and image quality are important factors to minimize planning target volume margin due to the respiratory motion. To achieve high temporal resolution and high signal-to-noise ratio, we developed a respiratory gated segment reconstruction algorithm and adapted it to Feldkamp-Davis-Kress algorithm (FDK) with a 256-detector row CT. The 256-detector row CT could scan approximately 100 mm in the cranio-caudal direction with 0.5 mm slice thickness in one rotation. Data acquisition for the RS-FDK relies on the assistance of the respiratory sensing system by a cine scan mode (table remains stationary). We evaluated RS-FDK in phantom study with the 256-detector row CT and compared it with full scan (FS-FDK) and HS-FDK results with regard to volume accuracy and image noise, and finally adapted the RS-FDK to an animal study. The RS-FDK gave a more accurate volume than the others and it had the same signal-to-noise ratio as the FS-FDK. In the animal study, the RS-FDK visualized the clearest edges of the liver and pulmonary vessels of all the algorithms. In conclusion, the RS-FDK algorithm has a capability of high temporal resolution and high signal-to-noise ratio. Therefore it will be useful when combined with new radiotherapy techniques including image guided radiation therapy (IGRT) and 4D radiation therapy.

Responses of Tree Growths to Tree Size, Competition, and Topographic Conditions in Sierra Nevada Forests Using Bi-temporal Airborne LiDAR Data

NASA Astrophysics Data System (ADS)

Ma, Q.; Su, Y.; Tao, S.; Guo, Q.

2016-12-01

Trees in the Sierra Nevada (SN) forests are experiencing rapid changes due to human disturbances and climatic changes. An improved monitoring of tree growth and understanding of how tree growth responses to different impact factors, such as tree competition, forest density, topographic and hydrologic conditions, are urgently needed in tree growth modeling. Traditional tree growth modeling mainly relied on field survey, which was highly time-consuming and labor-intensive. Airborne Light detection and ranging System (ALS) is increasingly used in forest survey, due to its high efficiency and accuracy in three-dimensional tree structure delineation and terrain characterization. This study successfully detected individual tree growth in height (ΔH), crown area (ΔA), and crown volume (ΔV) over a five-year period (2007-2012) using bi-temporal ALS data in two conifer forest areas in SN. We further analyzed their responses to original tree size, competition indices, forest structure indices, and topographic environmental parameters at individual tree and forest stand scales. Our results indicated ΔH was strongly sensitive to topographic wetness index; whereas ΔA and ΔV were highly responsive to forest density and original tree sizes. These ALS based findings in ΔH were consistent with field measurements. Our study demonstrated the promising potential of using bi-temporal ALS data in forest growth measurements and analysis. A more comprehensive study over a longer temporal period and a wider range of forest stands would give better insights into tree growth in the SN, and provide useful guides for forest growth monitoring, modeling, and management.

Relationship between slow visual processing and reading speed in people with macular degeneration

PubMed Central

Cheong, Allen MY; Legge, Gordon E; Lawrence, Mary G; Cheung, Sing-Hang; Ruff, Mary A

2007-01-01

Purpose People with macular degeneration (MD) often read slowly even with adequate magnification to compensate for acuity loss. Oculomotor deficits may affect reading in MD, but cannot fully explain the substantial reduction in reading speed. Central-field loss (CFL) is often a consequence of macular degeneration, necessitating the use of peripheral vision for reading. We hypothesized that slower temporal processing of visual patterns in peripheral vision is a factor contributing to slow reading performance in MD patients. Methods Fifteen subjects with MD, including 12 with CFL, and five age-matched control subjects were recruited. Maximum reading speed and critical print size were measured with RSVP (Rapid Serial Visual Presentation). Temporal processing speed was studied by measuring letter-recognition accuracy for strings of three randomly selected letters centered at fixation for a range of exposure times. Temporal threshold was defined as the exposure time yielding 80% recognition accuracy for the central letter. Results Temporal thresholds for the MD subjects ranged from 159 to 5881 ms, much longer than values for age-matched controls in central vision (13 ms, p<0.01). The mean temporal threshold for the 11 MD subjects who used eccentric fixation (1555.8 ± 1708.4 ms) was much longer than the mean temporal threshold (97.0 ms ± 34.2 ms, p<0.01) for the age-matched controls at 10° in the lower visual field. Individual temporal thresholds accounted for 30% of the variance in reading speed (p<0.05). Conclusion The significant association between increased temporal threshold for letter recognition and reduced reading speed is consistent with the hypothesis that slower visual processing of letter recognition is one of the factors limiting reading speed in MD subjects. PMID:17881032

Oculomatic: High speed, reliable, and accurate open-source eye tracking for humans and non-human primates.

PubMed

Zimmermann, Jan; Vazquez, Yuriria; Glimcher, Paul W; Pesaran, Bijan; Louie, Kenway

2016-09-01

Video-based noninvasive eye trackers are an extremely useful tool for many areas of research. Many open-source eye trackers are available but current open-source systems are not designed to track eye movements with the temporal resolution required to investigate the mechanisms of oculomotor behavior. Commercial systems are available but employ closed source hardware and software and are relatively expensive, limiting wide-spread use. Here we present Oculomatic, an open-source software and modular hardware solution to eye tracking for use in humans and non-human primates. Oculomatic features high temporal resolution (up to 600Hz), real-time eye tracking with high spatial accuracy (<0.5°), and low system latency (∼1.8ms, 0.32ms STD) at a relatively low-cost. Oculomatic compares favorably to our existing scleral search-coil system while being fully non invasive. We propose that Oculomatic can support a wide range of research into the properties and neural mechanisms of oculomotor behavior. Copyright © 2016 Elsevier B.V. All rights reserved.

An event-version-based spatio-temporal modeling approach and its application in the cadastral management

NASA Astrophysics Data System (ADS)

Li, Yangdong; Han, Zhen; Liao, Zhongping

2009-10-01

Spatiality, temporality, legality, accuracy and continuality are characteristic of cadastral information, and the cadastral management demands that the cadastral data should be accurate, integrated and updated timely. It's a good idea to build an effective GIS management system to manage the cadastral data which are characterized by spatiality and temporality. Because no sound spatio-temporal data models have been adopted, however, the spatio-temporal characteristics of cadastral data are not well expressed in the existing cadastral management systems. An event-version-based spatio-temporal modeling approach is first proposed from the angle of event and version. Then with the help of it, an event-version-based spatio-temporal cadastral data model is built to represent spatio-temporal cadastral data. At last, the previous model is used in the design and implementation of a spatio-temporal cadastral management system. The result of the application of the system shows that the event-version-based spatio-temporal data model is very suitable for the representation and organization of cadastral data.

Measurement of slow-moving along-track displacement from an efficient multiple-aperture SAR interferometry (MAI) stacking

USGS Publications Warehouse

Jo, Min-Jeong; Jung, Hyung-Sup; Won, Joong-Sun; Poland, Michael; Miklius, Asta; Lu, Zhong

2015-01-01

Multiple-aperture SAR interferometry (MAI) has demonstrated outstanding measurement accuracy of along-track displacement when compared to pixel-offset-tracking methods; however, measuring slow-moving (cm/year) surface displacement remains a challenge. Stacking of multi-temporal observations is a potential approach to reducing noise and increasing measurement accuracy, but it is difficult to achieve a significant improvement by applying traditional stacking methods to multi-temporal MAI interferograms. This paper proposes an efficient MAI stacking method, where multi-temporal forward- and backward-looking residual interferograms are individually stacked before the MAI interferogram is generated. We tested the performance of this method using ENVISAT data from Kīlauea Volcano, Hawai‘i, where displacement on the order of several centimeters per year is common. By comparing results from the proposed stacking methods with displacements from GPS data, we documented measurement accuracies of about 1.03 and 1.07 cm/year for the descending and ascending tracks, respectively—an improvement of about a factor of two when compared with that from the conventional stacking approach. Three-dimensional surface-displacement maps can be constructed by combining stacked InSAR and MAI observations, which will contribute to a better understanding of a variety of geological phenomena.

Reconstructing the spectrotemporal modulations of real-life sounds from fMRI response patterns

PubMed Central

Santoro, Roberta; Moerel, Michelle; De Martino, Federico; Valente, Giancarlo; Ugurbil, Kamil; Yacoub, Essa; Formisano, Elia

2017-01-01

Ethological views of brain functioning suggest that sound representations and computations in the auditory neural system are optimized finely to process and discriminate behaviorally relevant acoustic features and sounds (e.g., spectrotemporal modulations in the songs of zebra finches). Here, we show that modeling of neural sound representations in terms of frequency-specific spectrotemporal modulations enables accurate and specific reconstruction of real-life sounds from high-resolution functional magnetic resonance imaging (fMRI) response patterns in the human auditory cortex. Region-based analyses indicated that response patterns in separate portions of the auditory cortex are informative of distinctive sets of spectrotemporal modulations. Most relevantly, results revealed that in early auditory regions, and progressively more in surrounding regions, temporal modulations in a range relevant for speech analysis (∼2–4 Hz) were reconstructed more faithfully than other temporal modulations. In early auditory regions, this effect was frequency-dependent and only present for lower frequencies (<∼2 kHz), whereas for higher frequencies, reconstruction accuracy was higher for faster temporal modulations. Further analyses suggested that auditory cortical processing optimized for the fine-grained discrimination of speech and vocal sounds underlies this enhanced reconstruction accuracy. In sum, the present study introduces an approach to embed models of neural sound representations in the analysis of fMRI response patterns. Furthermore, it reveals that, in the human brain, even general purpose and fundamental neural processing mechanisms are shaped by the physical features of real-world stimuli that are most relevant for behavior (i.e., speech, voice). PMID:28420788

French Meteor Network for High Precision Orbits of Meteoroids

NASA Technical Reports Server (NTRS)

Atreya, P.; Vaubaillon, J.; Colas, F.; Bouley, S.; Gaillard, B.; Sauli, I.; Kwon, M. K.

2011-01-01

There is a lack of precise meteoroids orbit from video observations as most of the meteor stations use off-the-shelf CCD cameras. Few meteoroids orbit with precise semi-major axis are available using film photographic method. Precise orbits are necessary to compute the dust flux in the Earth s vicinity, and to estimate the ejection time of the meteoroids accurately by comparing them with the theoretical evolution model. We investigate the use of large CCD sensors to observe multi-station meteors and to compute precise orbit of these meteoroids. An ideal spatial and temporal resolution to get an accuracy to those similar of photographic plates are discussed. Various problems faced due to the use of large CCD, such as increasing the spatial and the temporal resolution at the same time and computational problems in finding the meteor position are illustrated.

Single-Shot Measurement of Temporally-Dependent Polarization State of Femtosecond Pulses by Angle-Multiplexed Spectral-Spatial Interferometry

NASA Astrophysics Data System (ADS)

Lin, Ming-Wei; Jovanovic, Igor

2016-09-01

We demonstrate that temporally-dependent polarization states of ultrashort laser pulses can be reconstructed in a single shot by use of an angle-multiplexed spatial-spectral interferometry. This is achieved by introducing two orthogonally polarized reference pulses and interfering them with an arbitrarily polarized ultrafast pulse under measurement. A unique calibration procedure is developed for this technique which facilitates the subsequent polarization state measurements. The accuracy of several reconstructed polarization states is verified by comparison with that obtained from an analytic model that predicts the polarization state on the basis of its method of production. Laser pulses with mJ-level energies were characterized via this technique, including a time-dependent polarization state that can be used for polarization-gating of high-harmonic generation for production of attosecond pulses.

A Prediction Algorithm for Drug Response in Patients with Mesial Temporal Lobe Epilepsy Based on Clinical and Genetic Information

PubMed Central

Carvalho, Benilton S.; Bilevicius, Elizabeth; Alvim, Marina K. M.; Lopes-Cendes, Iscia

2017-01-01

Mesial temporal lobe epilepsy is the most common form of adult epilepsy in surgical series. Currently, the only characteristic used to predict poor response to clinical treatment in this syndrome is the presence of hippocampal sclerosis. Single nucleotide polymorphisms (SNPs) located in genes encoding drug transporter and metabolism proteins could influence response to therapy. Therefore, we aimed to evaluate whether combining information from clinical variables as well as SNPs in candidate genes could improve the accuracy of predicting response to drug therapy in patients with mesial temporal lobe epilepsy. For this, we divided 237 patients into two groups: 75 responsive and 162 refractory to antiepileptic drug therapy. We genotyped 119 SNPs in ABCB1, ABCC2, CYP1A1, CYP1A2, CYP1B1, CYP2C9, CYP2C19, CYP2D6, CYP2E1, CYP3A4, and CYP3A5 genes. We used 98 additional SNPs to evaluate population stratification. We assessed a first scenario using only clinical variables and a second one including SNP information. The random forests algorithm combined with leave-one-out cross-validation was used to identify the best predictive model in each scenario and compared their accuracies using the area under the curve statistic. Additionally, we built a variable importance plot to present the set of most relevant predictors on the best model. The selected best model included the presence of hippocampal sclerosis and 56 SNPs. Furthermore, including SNPs in the model improved accuracy from 0.4568 to 0.8177. Our findings suggest that adding genetic information provided by SNPs, located on drug transport and metabolism genes, can improve the accuracy for predicting which patients with mesial temporal lobe epilepsy are likely to be refractory to drug treatment, making it possible to identify patients who may benefit from epilepsy surgery sooner. PMID:28052106

Object and proper name retrieval in temporal lobe epilepsy: a study of difficulties and latencies.

PubMed

Condret-Santi, Valérie; Barragan-Jason, Gladys; Valton, Luc; Denuelle, Marie; Curot, Jonathan; Nespoulous, Jean-Luc; Barbeau, Emmanuel J

2014-12-01

Retrieving a specific name is sometimes difficult and can be even harder when pathology affects the temporal lobes. Word finding difficulties have been well documented in temporal lobe epilepsy (TLE) but analyses have mostly concentrated on the study of accuracy. Our aim here was to go beyond simple accuracy and to provide both a quantitative and a qualitative assessment of naming difficulties and latencies in patients with TLE. Thirty-two patients with temporal lobe epilepsy (16 with epilepsy affecting the cerebral hemisphere dominant for language (D-TLE) and 16 with epilepsy affecting the cerebral hemisphere non-dominant for language (ND-TLE)) and 34 healthy matched control subjects were included in the study. The experiment involved naming 70 photographs of objects and 70 photographs of celebrities as fast as possible. Accuracy and naming reaction times were recorded. Following each trial, a questionnaire was used to determine the specific nature of each subject's difficulty in retrieving the name (e.g., no difficulty, paraphasia, tip of the tongue, feeling of knowing the name, etc). Reaction times were analysed both across subjects and across trials. D-TLE patients showed consistent and quasi-systematic impairment compared to matched control subjects on both object and famous people naming. This impairment was characterized not only by lower accuracy but also by more qualitative errors and tip of the tongue phenomena. Furthermore, minimum reaction times were slowed down by about 70 ms for objects and 150 ms for famous people naming. In contrast, patients with ND-TLE were less impaired, and their impairment was limited to object naming. These results suggest that patients with TLE, in particular D-TLE, show a general impairment of lexical access. Furthermore, there was evidence of subtle difficulties (increased reaction times) in patients with TLE. Copyright © 2014 Elsevier B.V. All rights reserved.

Semantic and episodic memory in children with temporal lobe epilepsy: do they relate to literacy skills?

PubMed

Lah, Suncica; Smith, Mary Lou

2014-01-01

Children with temporal lobe epilepsy are at risk for deficits in new learning (episodic memory) and literacy skills. Semantic memory deficits and double dissociations between episodic and semantic memory have recently been found in this patient population. In the current study we investigate whether impairments of these 2 distinct memory systems relate to literacy skills. 57 children with unilateral temporal lobe epilepsy completed tests of verbal memory (episodic and semantic) and literacy skills (reading and spelling accuracy, and reading comprehension). For the entire group, semantic memory explained over 30% of variance in each of the literacy domains. Episodic memory explained a significant, but rather small proportion (< 10%) of variance in reading and spelling accuracy, but not in reading comprehension. Moreover, when children with opposite patterns of specific memory impairments (intact semantic/impaired episodic, intact episodic/impaired semantic) were compared, significant reductions in literacy skills were evident only in children with semantic memory impairments, but not in children with episodic memory impairments relative to the norms and to children with temporal lobe epilepsy who had intact memory. Our study provides the first evidence for differential relations between episodic and semantic memory impairments and literacy skills in children with temporal lobe epilepsy. As such, it highlights the urgent need to consider semantic memory deficits in management of children with temporal lobe epilepsy and undertake further research into the nature of reading difficulties of children with semantic memory impairments.

Multiscale high-order/low-order (HOLO) algorithms and applications

NASA Astrophysics Data System (ADS)

Chacón, L.; Chen, G.; Knoll, D. A.; Newman, C.; Park, H.; Taitano, W.; Willert, J. A.; Womeldorff, G.

2017-02-01

We review the state of the art in the formulation, implementation, and performance of so-called high-order/low-order (HOLO) algorithms for challenging multiscale problems. HOLO algorithms attempt to couple one or several high-complexity physical models (the high-order model, HO) with low-complexity ones (the low-order model, LO). The primary goal of HOLO algorithms is to achieve nonlinear convergence between HO and LO components while minimizing memory footprint and managing the computational complexity in a practical manner. Key to the HOLO approach is the use of the LO representations to address temporal stiffness, effectively accelerating the convergence of the HO/LO coupled system. The HOLO approach is broadly underpinned by the concept of nonlinear elimination, which enables segregation of the HO and LO components in ways that can effectively use heterogeneous architectures. The accuracy and efficiency benefits of HOLO algorithms are demonstrated with specific applications to radiation transport, gas dynamics, plasmas (both Eulerian and Lagrangian formulations), and ocean modeling. Across this broad application spectrum, HOLO algorithms achieve significant accuracy improvements at a fraction of the cost compared to conventional approaches. It follows that HOLO algorithms hold significant potential for high-fidelity system scale multiscale simulations leveraging exascale computing.

Improvement of Quantitative Measurements in Multiplex Proteomics Using High-Field Asymmetric Waveform Spectrometry.

PubMed

Pfammatter, Sibylle; Bonneil, Eric; Thibault, Pierre

2016-12-02

Quantitative proteomics using isobaric reagent tandem mass tags (TMT) or isobaric tags for relative and absolute quantitation (iTRAQ) provides a convenient approach to compare changes in protein abundance across multiple samples. However, the analysis of complex protein digests by isobaric labeling can be undermined by the relative large proportion of co-selected peptide ions that lead to distorted reporter ion ratios and affect the accuracy and precision of quantitative measurements. Here, we investigated the use of high-field asymmetric waveform ion mobility spectrometry (FAIMS) in proteomic experiments to reduce sample complexity and improve protein quantification using TMT isobaric labeling. LC-FAIMS-MS/MS analyses of human and yeast protein digests led to significant reductions in interfering ions, which increased the number of quantifiable peptides by up to 68% while significantly improving the accuracy of abundance measurements compared to that with conventional LC-MS/MS. The improvement in quantitative measurements using FAIMS is further demonstrated for the temporal profiling of protein abundance of HEK293 cells following heat shock treatment.

Forest Cover Estimation in Ireland Using Radar Remote Sensing: A Comparative Analysis of Forest Cover Assessment Methodologies.

PubMed

Devaney, John; Barrett, Brian; Barrett, Frank; Redmond, John; O Halloran, John

2015-01-01

Quantification of spatial and temporal changes in forest cover is an essential component of forest monitoring programs. Due to its cloud free capability, Synthetic Aperture Radar (SAR) is an ideal source of information on forest dynamics in countries with near-constant cloud-cover. However, few studies have investigated the use of SAR for forest cover estimation in landscapes with highly sparse and fragmented forest cover. In this study, the potential use of L-band SAR for forest cover estimation in two regions (Longford and Sligo) in Ireland is investigated and compared to forest cover estimates derived from three national (Forestry2010, Prime2, National Forest Inventory), one pan-European (Forest Map 2006) and one global forest cover (Global Forest Change) product. Two machine-learning approaches (Random Forests and Extremely Randomised Trees) are evaluated. Both Random Forests and Extremely Randomised Trees classification accuracies were high (98.1-98.5%), with differences between the two classifiers being minimal (<0.5%). Increasing levels of post classification filtering led to a decrease in estimated forest area and an increase in overall accuracy of SAR-derived forest cover maps. All forest cover products were evaluated using an independent validation dataset. For the Longford region, the highest overall accuracy was recorded with the Forestry2010 dataset (97.42%) whereas in Sligo, highest overall accuracy was obtained for the Prime2 dataset (97.43%), although accuracies of SAR-derived forest maps were comparable. Our findings indicate that spaceborne radar could aid inventories in regions with low levels of forest cover in fragmented landscapes. The reduced accuracies observed for the global and pan-continental forest cover maps in comparison to national and SAR-derived forest maps indicate that caution should be exercised when applying these datasets for national reporting.

Forest Cover Estimation in Ireland Using Radar Remote Sensing: A Comparative Analysis of Forest Cover Assessment Methodologies

PubMed Central

Devaney, John; Barrett, Brian; Barrett, Frank; Redmond, John; O`Halloran, John

2015-01-01

Quantification of spatial and temporal changes in forest cover is an essential component of forest monitoring programs. Due to its cloud free capability, Synthetic Aperture Radar (SAR) is an ideal source of information on forest dynamics in countries with near-constant cloud-cover. However, few studies have investigated the use of SAR for forest cover estimation in landscapes with highly sparse and fragmented forest cover. In this study, the potential use of L-band SAR for forest cover estimation in two regions (Longford and Sligo) in Ireland is investigated and compared to forest cover estimates derived from three national (Forestry2010, Prime2, National Forest Inventory), one pan-European (Forest Map 2006) and one global forest cover (Global Forest Change) product. Two machine-learning approaches (Random Forests and Extremely Randomised Trees) are evaluated. Both Random Forests and Extremely Randomised Trees classification accuracies were high (98.1–98.5%), with differences between the two classifiers being minimal (<0.5%). Increasing levels of post classification filtering led to a decrease in estimated forest area and an increase in overall accuracy of SAR-derived forest cover maps. All forest cover products were evaluated using an independent validation dataset. For the Longford region, the highest overall accuracy was recorded with the Forestry2010 dataset (97.42%) whereas in Sligo, highest overall accuracy was obtained for the Prime2 dataset (97.43%), although accuracies of SAR-derived forest maps were comparable. Our findings indicate that spaceborne radar could aid inventories in regions with low levels of forest cover in fragmented landscapes. The reduced accuracies observed for the global and pan-continental forest cover maps in comparison to national and SAR-derived forest maps indicate that caution should be exercised when applying these datasets for national reporting. PMID:26262681

Life History Traits and Niche Instability Impact Accuracy and Temporal Transferability for Historically Calibrated Distribution Models of North American Birds

PubMed Central

Wogan, Guinevere O. U.

2016-01-01

A primary assumption of environmental niche models (ENMs) is that models are both accurate and transferable across geography or time; however, recent work has shown that models may be accurate but not highly transferable. While some of this is due to modeling technique, individual species ecologies may also underlie this phenomenon. Life history traits certainly influence the accuracy of predictive ENMs, but their impact on model transferability is less understood. This study investigated how life history traits influence the predictive accuracy and transferability of ENMs using historically calibrated models for birds. In this study I used historical occurrence and climate data (1950-1990s) to build models for a sample of birds, and then projected them forward to the ‘future’ (1960-1990s). The models were then validated against models generated from occurrence data at that ‘future’ time. Internal and external validation metrics, as well as metrics assessing transferability, and Generalized Linear Models were used to identify life history traits that were significant predictors of accuracy and transferability. This study found that the predictive ability of ENMs differs with regard to life history characteristics such as range, migration, and habitat, and that the rarity versus commonness of a species affects the predicted stability and overlap and hence the transferability of projected models. Projected ENMs with both high accuracy and transferability scores, still sometimes suffered from over- or under- predicted species ranges. Life history traits certainly influenced the accuracy of predictive ENMs for birds, but while aspects of geographic range impact model transferability, the mechanisms underlying this are less understood. PMID:26959979

Integration of multi-temporal airborne and terrestrial laser scanning data for the analysis and modelling of proglacial geomorphodynamic processes

NASA Astrophysics Data System (ADS)

Briese, Christian; Glira, Philipp; Pfeifer, Norbert

2013-04-01

The actual on-going and predicted climate change leads in sensitive areas like in high-mountain proglacial regions to significant geomorphodynamic processes (e.g. landslides). Within a short time period (even less than a year) these processes lead to a substantial change of the landscape. In order to study and analyse the recent changes in a proglacial environment the multi-disciplinary research project PROSA (high-resolution measurements of morphodynamics in rapidly changing PROglacial Systems of the Alps) selected the study area of the Gepatschferner (Tyrol), the second largest glacier in Austria. One of the challenges within the project is the geometric integration (i.e. georeferencing) of multi-temporal topographic data sets in a continuously changing environment. Furthermore, one has to deal with data sets of multiple scales (large area data sets vs. highly detailed local area observations) that are on one hand necessary to cover the complete proglacial area with the whole catchment and on the other hand guaranty a highly dense and accurate sampling of individual areas of interest (e.g. a certain highly affected slope). This contribution suggests a comprehensive method for the georeferencing of multi-temporal airborne and terrestrial laser scanning (ALS resp. TLS). It is studied by application to the data that was acquired within the project PROSA. In a first step a stable coordinate frame that allows the analysis of the changing environment has to be defined. Subsequently procedures for the transformation of the individual ALS and TLS data sets into this coordinate frame were developed. This includes the selection of appropriate reference areas as well as the development of special targets for the local TLS acquisition that can be used for the absolute georeferencing in the common coordinate frame. Due to the fact that different TLS instruments can be used (some larger distance sensors that allow covering larger areas vs. closer operating sensors that allow a denser surface sampling) the different sensor properties (wavelength, resolution, etc., and therefore suitability of targets) have to be considered. Subsequently the multi-temporal analysis of the data sets can be performed. Within this analysis it is important to consider the different instrument properties as well as the different data acquisition geometry (observation direction). The aim is to reach an accuracy of a few centimetre in georeferencing for a single measurement epoch. Furthermore, next to an understanding of the individual measurement process the integration of geomorphological knowledge is essential in order to separate errors of the measurement process from actual dynamic environmental changes. This leads to a multi-disciplinary analysis of the measurement data. In addition to a geometric analysis the radiometric changes of the ALS data will be studied. The presentation illustrates next to the method and data itself the analysis of multi-temporal proglacial data sets and the obtained accuracy.

High-speed multi-exposure laser speckle contrast imaging with a single-photon counting camera

PubMed Central

Dragojević, Tanja; Bronzi, Danilo; Varma, Hari M.; Valdes, Claudia P.; Castellvi, Clara; Villa, Federica; Tosi, Alberto; Justicia, Carles; Zappa, Franco; Durduran, Turgut

2015-01-01

Laser speckle contrast imaging (LSCI) has emerged as a valuable tool for cerebral blood flow (CBF) imaging. We present a multi-exposure laser speckle imaging (MESI) method which uses a high-frame rate acquisition with a negligible inter-frame dead time to mimic multiple exposures in a single-shot acquisition series. Our approach takes advantage of the noise-free readout and high-sensitivity of a complementary metal-oxide-semiconductor (CMOS) single-photon avalanche diode (SPAD) array to provide real-time speckle contrast measurement with high temporal resolution and accuracy. To demonstrate its feasibility, we provide comparisons between in vivo measurements with both the standard and the new approach performed on a mouse brain, in identical conditions. PMID:26309751

Fully coupled approach to modeling shallow water flow, sediment transport, and bed evolution in rivers

NASA Astrophysics Data System (ADS)

Li, Shuangcai; Duffy, Christopher J.

2011-03-01

Our ability to predict complex environmental fluid flow and transport hinges on accurate and efficient simulations of multiple physical phenomenon operating simultaneously over a wide range of spatial and temporal scales, including overbank floods, coastal storm surge events, drying and wetting bed conditions, and simultaneous bed form evolution. This research implements a fully coupled strategy for solving shallow water hydrodynamics, sediment transport, and morphological bed evolution in rivers and floodplains (PIHM_Hydro) and applies the model to field and laboratory experiments that cover a wide range of spatial and temporal scales. The model uses a standard upwind finite volume method and Roe's approximate Riemann solver for unstructured grids. A multidimensional linear reconstruction and slope limiter are implemented, achieving second-order spatial accuracy. Model efficiency and stability are treated using an explicit-implicit method for temporal discretization with operator splitting. Laboratory-and field-scale experiments were compiled where coupled processes across a range of scales were observed and where higher-order spatial and temporal accuracy might be needed for accurate and efficient solutions. These experiments demonstrate the ability of the fully coupled strategy in capturing dynamics of field-scale flood waves and small-scale drying-wetting processes.

A spatio-temporal landslide inventory for the NW of Spain: BAPA database

NASA Astrophysics Data System (ADS)

Valenzuela, Pablo; Domínguez-Cuesta, María José; Mora García, Manuel Antonio; Jiménez-Sánchez, Montserrat

2017-09-01

A landslide database has been created for the Principality of Asturias, NW Spain: the BAPA (Base de datos de Argayos del Principado de Asturias - Principality of Asturias Landslide Database). Data collection is mainly performed through searching local newspaper archives. Moreover, a BAPA App and a BAPA website (http://geol.uniovi.es/BAPA) have been developed to obtain additional information from citizens and institutions. Presently, the dataset covers the period 1980-2015, recording 2063 individual landslides. The use of free cartographic servers, such as Google Maps, Google Street View and Iberpix (Government of Spain), combined with the spatial descriptions and pictures contained in the press news, makes it possible to assess different levels of spatial accuracy. In the database, 59% of the records show an exact spatial location, and 51% of the records provided accurate dates, showing the usefulness of press archives as temporal records. Thus, 32% of the landslides show the highest spatial and temporal accuracy levels. The database also gathers information about the type and characteristics of the landslides, the triggering factors and the damage and costs caused. Field work was conducted to validate the methodology used in assessing the spatial location, temporal occurrence and characteristics of the landslides.

Fault Diagnosis from Raw Sensor Data Using Deep Neural Networks Considering Temporal Coherence.

PubMed

Zhang, Ran; Peng, Zhen; Wu, Lifeng; Yao, Beibei; Guan, Yong

2017-03-09

Intelligent condition monitoring and fault diagnosis by analyzing the sensor data can assure the safety of machinery. Conventional fault diagnosis and classification methods usually implement pretreatments to decrease noise and extract some time domain or frequency domain features from raw time series sensor data. Then, some classifiers are utilized to make diagnosis. However, these conventional fault diagnosis approaches suffer from the expertise of feature selection and they do not consider the temporal coherence of time series data. This paper proposes a fault diagnosis model based on Deep Neural Networks (DNN). The model can directly recognize raw time series sensor data without feature selection and signal processing. It also takes advantage of the temporal coherence of the data. Firstly, raw time series training data collected by sensors are used to train the DNN until the cost function of DNN gets the minimal value; Secondly, test data are used to test the classification accuracy of the DNN on local time series data. Finally, fault diagnosis considering temporal coherence with former time series data is implemented. Experimental results show that the classification accuracy of bearing faults can get 100%. The proposed fault diagnosis approach is effective in recognizing the type of bearing faults.

Fault Diagnosis from Raw Sensor Data Using Deep Neural Networks Considering Temporal Coherence

PubMed Central

Zhang, Ran; Peng, Zhen; Wu, Lifeng; Yao, Beibei; Guan, Yong

2017-01-01

Intelligent condition monitoring and fault diagnosis by analyzing the sensor data can assure the safety of machinery. Conventional fault diagnosis and classification methods usually implement pretreatments to decrease noise and extract some time domain or frequency domain features from raw time series sensor data. Then, some classifiers are utilized to make diagnosis. However, these conventional fault diagnosis approaches suffer from the expertise of feature selection and they do not consider the temporal coherence of time series data. This paper proposes a fault diagnosis model based on Deep Neural Networks (DNN). The model can directly recognize raw time series sensor data without feature selection and signal processing. It also takes advantage of the temporal coherence of the data. Firstly, raw time series training data collected by sensors are used to train the DNN until the cost function of DNN gets the minimal value; Secondly, test data are used to test the classification accuracy of the DNN on local time series data. Finally, fault diagnosis considering temporal coherence with former time series data is implemented. Experimental results show that the classification accuracy of bearing faults can get 100%. The proposed fault diagnosis approach is effective in recognizing the type of bearing faults. PMID:28282936

High Accuracy Human Activity Recognition Based on Sparse Locality Preserving Projections.

PubMed

Zhu, Xiangbin; Qiu, Huiling

2016-01-01

Human activity recognition(HAR) from the temporal streams of sensory data has been applied to many fields, such as healthcare services, intelligent environments and cyber security. However, the classification accuracy of most existed methods is not enough in some applications, especially for healthcare services. In order to improving accuracy, it is necessary to develop a novel method which will take full account of the intrinsic sequential characteristics for time-series sensory data. Moreover, each human activity may has correlated feature relationship at different levels. Therefore, in this paper, we propose a three-stage continuous hidden Markov model (TSCHMM) approach to recognize human activities. The proposed method contains coarse, fine and accurate classification. The feature reduction is an important step in classification processing. In this paper, sparse locality preserving projections (SpLPP) is exploited to determine the optimal feature subsets for accurate classification of the stationary-activity data. It can extract more discriminative activities features from the sensor data compared with locality preserving projections. Furthermore, all of the gyro-based features are used for accurate classification of the moving data. Compared with other methods, our method uses significantly less number of features, and the over-all accuracy has been obviously improved.

High Accuracy Human Activity Recognition Based on Sparse Locality Preserving Projections

PubMed Central

2016-01-01

Human activity recognition(HAR) from the temporal streams of sensory data has been applied to many fields, such as healthcare services, intelligent environments and cyber security. However, the classification accuracy of most existed methods is not enough in some applications, especially for healthcare services. In order to improving accuracy, it is necessary to develop a novel method which will take full account of the intrinsic sequential characteristics for time-series sensory data. Moreover, each human activity may has correlated feature relationship at different levels. Therefore, in this paper, we propose a three-stage continuous hidden Markov model (TSCHMM) approach to recognize human activities. The proposed method contains coarse, fine and accurate classification. The feature reduction is an important step in classification processing. In this paper, sparse locality preserving projections (SpLPP) is exploited to determine the optimal feature subsets for accurate classification of the stationary-activity data. It can extract more discriminative activities features from the sensor data compared with locality preserving projections. Furthermore, all of the gyro-based features are used for accurate classification of the moving data. Compared with other methods, our method uses significantly less number of features, and the over-all accuracy has been obviously improved. PMID:27893761

Representations of Invariant Musical Categories Are Decodable by Pattern Analysis of Locally Distributed BOLD Responses in Superior Temporal and Intraparietal Sulci

PubMed Central

Klein, Mike E.; Zatorre, Robert J.

2015-01-01

In categorical perception (CP), continuous physical signals are mapped to discrete perceptual bins: mental categories not found in the physical world. CP has been demonstrated across multiple sensory modalities and, in audition, for certain over-learned speech and musical sounds. The neural basis of auditory CP, however, remains ambiguous, including its robustness in nonspeech processes and the relative roles of left/right hemispheres; primary/nonprimary cortices; and ventral/dorsal perceptual processing streams. Here, highly trained musicians listened to 2-tone musical intervals, which they perceive categorically while undergoing functional magnetic resonance imaging. Multivariate pattern analyses were performed after grouping sounds by interval quality (determined by frequency ratio between tones) or pitch height (perceived noncategorically, frequency ratios remain constant). Distributed activity patterns in spheres of voxels were used to determine sound sample identities. For intervals, significant decoding accuracy was observed in the right superior temporal and left intraparietal sulci, with smaller peaks observed homologously in contralateral hemispheres. For pitch height, no significant decoding accuracy was observed, consistent with the non-CP of this dimension. These results suggest that similar mechanisms are operative for nonspeech categories as for speech; espouse roles for 2 segregated processing streams; and support hierarchical processing models for CP. PMID:24488957

Robust estimation of cerebral hemodynamics in neonates using multilayered diffusion model for normal and oblique incidences

NASA Astrophysics Data System (ADS)

Steinberg, Idan; Harbater, Osnat; Gannot, Israel

2014-07-01

The diffusion approximation is useful for many optical diagnostics modalities, such as near-infrared spectroscopy. However, the simple normal incidence, semi-infinite layer model may prove lacking in estimation of deep-tissue optical properties such as required for monitoring cerebral hemodynamics, especially in neonates. To answer this need, we present an analytical multilayered, oblique incidence diffusion model. Initially, the model equations are derived in vector-matrix form to facilitate fast and simple computation. Then, the spatiotemporal reflectance predicted by the model for a complex neonate head is compared with time-resolved Monte Carlo (TRMC) simulations under a wide range of physiologically feasible parameters. The high accuracy of the multilayer model is demonstrated in that the deviation from TRMC simulations is only a few percent even under the toughest conditions. We then turn to solve the inverse problem and estimate the oxygen saturation of deep brain tissues based on the temporal and spatial behaviors of the reflectance. Results indicate that temporal features of the reflectance are more sensitive to deep-layer optical parameters. The accuracy of estimation is shown to be more accurate and robust than the commonly used single-layer diffusion model. Finally, the limitations of such approaches are discussed thoroughly.

Spatial-temporal consistency between gross primary productivity and solar-induced chlorophyll fluorescence of vegetation in China during 2007-2014.

PubMed

Ma, Jun; Xiao, Xiangming; Zhang, Yao; Doughty, Russell; Chen, Bangqian; Zhao, Bin

2018-10-15

Accurately estimating spatial-temporal patterns of gross primary production (GPP) is important for the global carbon cycle. Satellite-based light use efficiency (LUE) models are regarded as an efficient tool in simulating spatial-temporal dynamics of GPP. However, the accuracy assessment of GPP simulations from LUE models at both spatial and temporal scales remains a challenge. In this study, we simulated GPP of vegetation in China during 2007-2014 using a LUE model (Vegetation Photosynthesis Model, VPM) based on MODIS (moderate-resolution imaging spectroradiometer) images with 8-day temporal and 500-m spatial resolutions and NCEP (National Center for Environmental Prediction) climate data. Global Ozone Monitoring Instrument 2 (GOME-2) solar-induced chlorophyll fluorescence (SIF) data were used to compare with VPM simulated GPP (GPP VPM ) temporally and spatially using linear correlation analysis. Significant positive linear correlations exist between monthly GPP VPM and SIF data over a single year (2010) and multiple years (2007-2014) in most areas of China. GPP VPM is also significantly positive correlated with GOME-2 SIF (R 2  > 0.43) spatially for seasonal scales. However, poor consistency was detected between GPP VPM and SIF data at yearly scale. GPP dynamic trends have high spatial-temporal variation in China during 2007-2014. Temperature, leaf area index (LAI), and precipitation are the most important factors influence GPP VPM in the regions of East Qinghai-Tibet Plateau, Loss Plateau, and Southwestern China, respectively. The results of this study indicate that GPP VPM is temporally and spatially in line with GOME-2 SIF data, and space-borne SIF data have great potential for evaluating LUE-based GPP models. Copyright © 2018 Elsevier B.V. All rights reserved.

a New Approach for Subway Tunnel Deformation Monitoring: High-Resolution Terrestrial Laser Scanning

NASA Astrophysics Data System (ADS)

Li, J.; Wan, Y.; Gao, X.

2012-07-01

With the improvement of the accuracy and efficiency of laser scanning technology, high-resolution terrestrial laser scanning (TLS) technology can obtain high precise points-cloud and density distribution and can be applied to high-precision deformation monitoring of subway tunnels and high-speed railway bridges and other fields. In this paper, a new approach using a points-cloud segmentation method based on vectors of neighbor points and surface fitting method based on moving least squares was proposed and applied to subway tunnel deformation monitoring in Tianjin combined with a new high-resolution terrestrial laser scanner (Riegl VZ-400). There were three main procedures. Firstly, a points-cloud consisted of several scanning was registered by linearized iterative least squares approach to improve the accuracy of registration, and several control points were acquired by total stations (TS) and then adjusted. Secondly, the registered points-cloud was resampled and segmented based on vectors of neighbor points to select suitable points. Thirdly, the selected points were used to fit the subway tunnel surface with moving least squares algorithm. Then a series of parallel sections obtained from temporal series of fitting tunnel surfaces were compared to analysis the deformation. Finally, the results of the approach in z direction were compared with the fiber optical displacement sensor approach and the results in x, y directions were compared with TS respectively, and comparison results showed the accuracy errors of x, y, z directions were respectively about 1.5 mm, 2 mm, 1 mm. Therefore the new approach using high-resolution TLS can meet the demand of subway tunnel deformation monitoring.

Assessment of cardiac time intervals using high temporal resolution real-time spiral phase contrast with UNFOLDed-SENSE.

PubMed

Kowalik, Grzegorz T; Knight, Daniel S; Steeden, Jennifer A; Tann, Oliver; Odille, Freddy; Atkinson, David; Taylor, Andrew; Muthurangu, Vivek

2015-02-01

To develop a real-time phase contrast MR sequence with high enough temporal resolution to assess cardiac time intervals. The sequence utilized spiral trajectories with an acquisition strategy that allowed a combination of temporal encoding (Unaliasing by fourier-encoding the overlaps using the temporal dimension; UNFOLD) and parallel imaging (Sensitivity encoding; SENSE) to be used (UNFOLDed-SENSE). An in silico experiment was performed to determine the optimum UNFOLD filter. In vitro experiments were carried out to validate the accuracy of time intervals calculation and peak mean velocity quantification. In addition, 15 healthy volunteers were imaged with the new sequence, and cardiac time intervals were compared to reference standard Doppler echocardiography measures. For comparison, in silico, in vitro, and in vivo experiments were also carried out using sliding window reconstructions. The in vitro experiments demonstrated good agreement between real-time spiral UNFOLDed-SENSE phase contrast MR and the reference standard measurements of velocity and time intervals. The protocol was successfully performed in all volunteers. Subsequent measurement of time intervals produced values in keeping with literature values and good agreement with the gold standard echocardiography. Importantly, the proposed UNFOLDed-SENSE sequence outperformed the sliding window reconstructions. Cardiac time intervals can be successfully assessed with UNFOLDed-SENSE real-time spiral phase contrast. Real-time MR assessment of cardiac time intervals may be beneficial in assessment of patients with cardiac conditions such as diastolic dysfunction. © 2014 Wiley Periodicals, Inc.

Treatment of temporal aliasing effects in the context of next generation satellite gravimetry missions

NASA Astrophysics Data System (ADS)

Daras, Ilias; Pail, Roland

2017-09-01

Temporal aliasing effects have a large impact on the gravity field accuracy of current gravimetry missions and are also expected to dominate the error budget of Next Generation Gravimetry Missions (NGGMs). This paper focuses on aspects concerning their treatment in the context of Low-Low Satellite-to-Satellite Tracking NGGMs. Closed-loop full-scale simulations are performed for a two-pair Bender-type Satellite Formation Flight (SFF), by taking into account error models of new generation instrument technology. The enhanced spatial sampling and error isotropy enable a further reduction of temporal aliasing errors from the processing perspective. A parameterization technique is adopted where the functional model is augmented by low-resolution gravity field solutions coestimated at short time intervals, while the remaining higher-resolution gravity field solution is estimated at a longer time interval. Fine-tuning the parameterization choices leads to significant reduction of the temporal aliasing effects. The investigations reveal that the parameterization technique in case of a Bender-type SFF can successfully mitigate aliasing effects caused by undersampling of high-frequency atmospheric and oceanic signals, since their most significant variations can be captured by daily coestimated solutions. This amounts to a "self-dealiasing" method that differs significantly from the classical dealiasing approach used nowadays for Gravity Recovery and Climate Experiment processing, enabling NGGMs to retrieve the complete spectrum of Earth's nontidal geophysical processes, including, for the first time, high-frequency atmospheric and oceanic variations.

Vegetation Coverage and Impervious Surface Area Estimated Based on the Estarfm Model and Remote Sensing Monitoring

NASA Astrophysics Data System (ADS)

Hu, Rongming; Wang, Shu; Guo, Jiao; Guo, Liankun

2018-04-01

Impervious surface area and vegetation coverage are important biophysical indicators of urban surface features which can be derived from medium-resolution images. However, remote sensing data obtained by a single sensor are easily affected by many factors such as weather conditions, and the spatial and temporal resolution can not meet the needs for soil erosion estimation. Therefore, the integrated multi-source remote sensing data are needed to carry out high spatio-temporal resolution vegetation coverage estimation. Two spatial and temporal vegetation coverage data and impervious data were obtained from MODIS and Landsat 8 remote sensing images. Based on the Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM), the vegetation coverage data of two scales were fused and the data of vegetation coverage fusion (ESTARFM FVC) and impervious layer with high spatiotemporal resolution (30 m, 8 day) were obtained. On this basis, the spatial variability of the seepage-free surface and the vegetation cover landscape in the study area was measured by means of statistics and spatial autocorrelation analysis. The results showed that: 1) ESTARFM FVC and impermeable surface have higher accuracy and can characterize the characteristics of the biophysical components covered by the earth's surface; 2) The average impervious surface proportion and the spatial configuration of each area are different, which are affected by natural conditions and urbanization. In the urban area of Xi'an, which has typical characteristics of spontaneous urbanization, landscapes are fragmented and have less spatial dependence.

Object-Based Land Use Classification of Agricultural Land by Coupling Multi-Temporal Spectral Characteristics and Phenological Events in Germany

NASA Astrophysics Data System (ADS)

Knoefel, Patrick; Loew, Fabian; Conrad, Christopher

2015-04-01

Crop maps based on classification of remotely sensed data are of increased attendance in agricultural management. This induces a more detailed knowledge about the reliability of such spatial information. However, classification of agricultural land use is often limited by high spectral similarities of the studied crop types. More, spatially and temporally varying agro-ecological conditions can introduce confusion in crop mapping. Classification errors in crop maps in turn may have influence on model outputs, like agricultural production monitoring. One major goal of the PhenoS project ("Phenological structuring to determine optimal acquisition dates for Sentinel-2 data for field crop classification"), is the detection of optimal phenological time windows for land cover classification purposes. Since many crop species are spectrally highly similar, accurate classification requires the right selection of satellite images for a certain classification task. In the course of one growing season, phenological phases exist where crops are separable with higher accuracies. For this purpose, coupling of multi-temporal spectral characteristics and phenological events is promising. The focus of this study is set on the separation of spectrally similar cereal crops like winter wheat, barley, and rye of two test sites in Germany called "Harz/Central German Lowland" and "Demmin". However, this study uses object based random forest (RF) classification to investigate the impact of image acquisition frequency and timing on crop classification uncertainty by permuting all possible combinations of available RapidEye time series recorded on the test sites between 2010 and 2014. The permutations were applied to different segmentation parameters. Then, classification uncertainty was assessed and analysed, based on the probabilistic soft-output from the RF algorithm at the per-field basis. From this soft output, entropy was calculated as a spatial measure of classification uncertainty. The results indicate that uncertainty estimates provide a valuable addition to traditional accuracy assessments and helps the user to allocate error in crop maps.

Consistency of Aquarius version-4 sea surface salinity with Argo products on various spatial and temporal scales

NASA Astrophysics Data System (ADS)

Lee, Tong

2017-04-01

Understanding the accuracies of satellite-derived sea surface salinity (SSS) measurements in depicting temporal changes and the dependence of the accuracies on spatiotemporal scales are important to capability assessment, future mission design, and applications to study oceanic phenomena of different spatiotemporal scales. This study quantifies the consistency between Aquarius Version-4 monthly gridded SSS (released in late 2015) with two widely used Argo monthly gridded near-surface salinity products. The analysis focused on their consistency in depicting temporal changes (including seasonal and non-seasonal) on various spatial scales: 1˚ x1˚ , 3˚ x3˚ , and 10˚ x10˚ . Globally averaged standard deviation (STD) values for Aquarius-Argo salinity differences on these three spatial scales are 0.16, 0.14, 0.09 psu, compared to those between the two Argo products of 0.10, 0.09, and 0.04 psu. Aquarius SSS compare better with Argo data on non-seasonal (e.g., interannual and intraseasonal) than for seasonal time scales. The seasonal Aquarius-Argo SSS differences are mostly concentrated at high latitudes. The Aquarius team is making active efforts to further reduce these high-latitude seasonal biases. The consistency between Aquarius and Argo salinity is similar to that between the two Argo products in the tropics and subtropics for non-seasonal signals, and in the tropics for seasonal signals. Therefore, the representativeness errors of the Argo products for various spatial scales (related to sampling and gridding) need to be taken into account when estimating the uncertainty of Aquarius SSS. The globally averaged uncertainty of large-scale (10˚ x10˚ ) non-seasonal Aquarius SSS is approximately 0.04 psu. These estimates reflect the significant improvements of Aquarius Version-4 SSS over the previous versions. The estimates can be used as baseline requirements for future ocean salinity missions from space. The spatial distribution of the uncertainty estimates is also useful for assimilation of Aquarius SSS.

Assessment of a vertical high-resolution distributed-temperature-sensing system in a shallow thermohaline environment

NASA Astrophysics Data System (ADS)

Suárez, F.; Aravena, J. E.; Hausner, M. B.; Childress, A. E.; Tyler, S. W.

2011-01-01

In shallow thermohaline-driven lakes it is important to measure temperature on fine spatial and temporal scales to detect stratification or different hydrodynamic regimes. Raman spectra distributed temperature sensing (DTS) is an approach available to provide high spatial and temporal temperature resolution. A vertical high-resolution DTS system was constructed to overcome the problems of typical methods used in the past, i.e., without disturbing the water column, and with resistance to corrosive environments. This system monitors the temperature profile each 1.1 cm vertically and in time averages as small as 10 s. Temperature resolution as low as 0.035 °C is obtained when the data are collected at 5-min intervals. The vertical high-resolution DTS system is used to monitor the thermal behavior of a salt-gradient solar pond, which is an engineered shallow thermohaline system that allows collection and storage of solar energy for a long period of time. This paper describes a method to quantitatively assess accuracy, precision and other limitations of DTS systems to fully utilize the capacity of this technology. It also presents, for the first time, a method to manually calibrate temperatures along the optical fiber.

Role of perceptual and organizational factors in amnesics' recall of the Rey-Osterrieth complex figure: a comparison of three amnesic groups.

PubMed

Kixmiller, J S; Verfaellie, M M; Mather, M M; Cermak, L S

2000-04-01

To examine the contribution of visual-perceptual and visual-organizational factors to visual memory in amnesia, Korsakoff, medial temporal, and anterior communicating artery (ACoA) aneurysm amnesics' copy, organization, and recall performance on the Rey-Osterrieth Complex Figure was assessed. Korsakoff patients were matched to medial temporal patients in terms of severity of amnesia, while the ACoA group, which was less severely amnesic, was matched to the Korsakoff patients on performance on executive tasks. Results indicated that while both the ACoA and Korsakoff groups had poorer copy accuracy and organization than controls, only the Korsakoff patients' copy accuracy was worse than the other two amnesic groups. While the Korsakoff patient's visuoperceptual deficits could partially explain this group's poor performance at immediate recall, the Korsakoff group's comparatively worse performance at delayed recall could not be accounted for by poor copy accuracy, reduced visual organization, or even the combined influence of these two factors.

Improving Prediction Accuracy for WSN Data Reduction by Applying Multivariate Spatio-Temporal Correlation

PubMed Central

Carvalho, Carlos; Gomes, Danielo G.; Agoulmine, Nazim; de Souza, José Neuman

2011-01-01

This paper proposes a method based on multivariate spatial and temporal correlation to improve prediction accuracy in data reduction for Wireless Sensor Networks (WSN). Prediction of data not sent to the sink node is a technique used to save energy in WSNs by reducing the amount of data traffic. However, it may not be very accurate. Simulations were made involving simple linear regression and multiple linear regression functions to assess the performance of the proposed method. The results show a higher correlation between gathered inputs when compared to time, which is an independent variable widely used for prediction and forecasting. Prediction accuracy is lower when simple linear regression is used, whereas multiple linear regression is the most accurate one. In addition to that, our proposal outperforms some current solutions by about 50% in humidity prediction and 21% in light prediction. To the best of our knowledge, we believe that we are probably the first to address prediction based on multivariate correlation for WSN data reduction. PMID:22346626

Crop classification using multidate/multifrequency radar data. [Colby, Kansas

NASA Technical Reports Server (NTRS)

Ulaby, F. T. (Principal Investigator); Shanmugam, K. S.; Narayanan, V.; Dobson, C.

1981-01-01

Both C- and L-band radar data acquired over a test site near Colby, Kansas during the summer of 1978 were used to identify three types of vegetation cover and bare soil. The effects of frequency, polarization, and the look angle on the overall accuracy of recognizing the four types of ground cover were analyzed. In addition, multidate data were used to study the improvement in recognition accuracy possible with the addition of temporal information. The soil moisture conditions had changed considerably during the temporal sequence of the data; hence, the effects of soil moisture on the ability to discriminate between cover types were also analyzed. The results provide useful information needed for selecting the parameters of a radar system for monitoring crops.

Robust phase-shifting interferometry resistant to multiple disturbances

NASA Astrophysics Data System (ADS)

Liu, Qian; Yue, Xiaobin; Li, Lulu; Zhang, Hui; He, Jianguo

2018-04-01

Phase-shifting interferometry (PSI) is sensitive to many disturbances, including the environmental vibration, laser instability, phase-shifting error and camera nonlinearity. A robust PSI (RPSI) based on the temporal spectrum analysis is proposed to suppress the effects of these common disturbances. RPSI retrieves wavefront phase from the temporal Fourier spectrum peak, which is identified by detecting the modulus of spectrum, and a referencing method is presented to improve the phase extracting accuracy. Simulations demonstrate the feasibility and effectiveness of RPSI. Experimental results indicate that RPSI is resistant to common disturbances in implementing PSI and achieves accuracy better than 0.03 rad in the disturbed environment. RPSI relaxes requirements on the hardware, environment and operator, and provides an easy-to-use design of an interferometer.

Estimating top-of-atmosphere thermal infrared radiance using MERRA-2 atmospheric data

NASA Astrophysics Data System (ADS)

Kleynhans, Tania; Montanaro, Matthew; Gerace, Aaron; Kanan, Christopher

2017-05-01

Thermal infrared satellite images have been widely used in environmental studies. However, satellites have limited temporal resolution, e.g., 16 day Landsat or 1 to 2 day Terra MODIS. This paper investigates the use of the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) reanalysis data product, produced by NASA's Global Modeling and Assimilation Office (GMAO) to predict global topof-atmosphere (TOA) thermal infrared radiance. The high temporal resolution of the MERRA-2 data product presents opportunities for novel research and applications. Various methods were applied to estimate TOA radiance from MERRA-2 variables namely (1) a parameterized physics based method, (2) Linear regression models and (3) non-linear Support Vector Regression. Model prediction accuracy was evaluated using temporally and spatially coincident Moderate Resolution Imaging Spectroradiometer (MODIS) thermal infrared data as reference data. This research found that Support Vector Regression with a radial basis function kernel produced the lowest error rates. Sources of errors are discussed and defined. Further research is currently being conducted to train deep learning models to predict TOA thermal radiance

Preserved ability to recognize keywords related to remote events in the absence of retrieval of relevant knowledge: a case of postencephalitic amnesia.

PubMed

Tsukiura, Takashi; Ohtake, Hiroya; Fujii, Toshikatsu; Miura, Rina; Ogawa, Tatsuji; Yamadori, Atsushi

2003-02-01

We describe a case of severe anterograde and retrograde amnesia resulting from herpes simplex encephalitis. Magnetic resonance imaging revealed pathological changes in the bilateral hippocampi, parahippocampal gyri, fusiform gyri, medial temporal poles, posterior part of the cingulate gyri, and insula. The patient showed severe amnesia for autobiographical episodic memory in relation to events that had occurred throughout her life, but temporally graded amnesia for autobiographical semantic memory, and severe amnesia without a temporal gradient for public events and famous people. However, using a multiple-choice method, she showed a high level of accuracy when choosing keywords related to public or personal events, although this did not prompt her recollection of the events. An important indication of these results is that, even with severe retrograde amnesia, memories of past events are not completely lost. We propose that an event may be stored in a fragmented form, consisting of many components, and that normal recall of an event may require recombination or reconstruction of these components. Copyright 2003 Elsevier Science (USA)

Spatiotemporal topology and temporal sequence identification with an adaptive time-delay neural network

NASA Astrophysics Data System (ADS)

Lin, Daw-Tung; Ligomenides, Panos A.; Dayhoff, Judith E.

1993-08-01

Inspired from the time delays that occur in neurobiological signal transmission, we describe an adaptive time delay neural network (ATNN) which is a powerful dynamic learning technique for spatiotemporal pattern transformation and temporal sequence identification. The dynamic properties of this network are formulated through the adaptation of time-delays and synapse weights, which are adjusted on-line based on gradient descent rules according to the evolution of observed inputs and outputs. We have applied the ATNN to examples that possess spatiotemporal complexity, with temporal sequences that are completed by the network. The ATNN is able to be applied to pattern completion. Simulation results show that the ATNN learns the topology of a circular and figure eight trajectories within 500 on-line training iterations, and reproduces the trajectory dynamically with very high accuracy. The ATNN was also trained to model the Fourier series expansion of the sum of different odd harmonics. The resulting network provides more flexibility and efficiency than the TDNN and allows the network to seek optimal values for time-delays as well as optimal synapse weights.

Neural correlates of cognitive dysfunction in Lewy body diseases and tauopathies: combined assessment with FDG-PET and the CERAD test battery.

PubMed

Hellwig, Sabine; Frings, Lars; Bormann, Tobias; Kreft, Annabelle; Amtage, Florian; Spehl, Timo S; Weiller, Cornelius; Tüscher, Oliver; Meyer, Philipp T

2013-11-01

We investigated disease-specific cognitive profiles and their neural correlates in Lewy-body diseases (LBD) and tauopathies by CERAD assessment and FDG-PET. Analyses revealed a significant interaction between reduced semantic fluency in tauopathies and impaired verbal learning in LBD. Semantic fluency discriminated between groups with high accuracy (83%). Compared to LBD, tauopathy patients showed bilateral hypometabolism of midbrain, thalamus, middle cingulate gyrus and supplementary motor/premotor cortex. In the reverse contrast, LBD patients exhibited bilateral hypometabolism in posterior parietal cortex, precuneus and inferior temporal gyrus extending into occipital and frontal cortices. In diagnosis-independent voxel-based analyses, verbal learning/memory correlated with left temporal and right parietal metabolism, while fluency was coupled to bilateral striatal and frontal metabolism. Naming correlated with left frontal metabolism and drawing with metabolism in bilateral temporal and left frontal regions. In line with disease-specific patterns of regional glucose metabolism, tauopathies and LBD show distinct cognitive profiles, which may assist clinical differentiation. Copyright © 2013 Elsevier Inc. All rights reserved.

High-Accuracy Ultrasound Contrast Agent Detection Method for Diagnostic Ultrasound Imaging Systems.

PubMed

Ito, Koichi; Noro, Kazumasa; Yanagisawa, Yukari; Sakamoto, Maya; Mori, Shiro; Shiga, Kiyoto; Kodama, Tetsuya; Aoki, Takafumi

2015-12-01

An accurate method for detecting contrast agents using diagnostic ultrasound imaging systems is proposed. Contrast agents, such as microbubbles, passing through a blood vessel during ultrasound imaging are detected as blinking signals in the temporal axis, because their intensity value is constantly in motion. Ultrasound contrast agents are detected by evaluating the intensity variation of a pixel in the temporal axis. Conventional methods are based on simple subtraction of ultrasound images to detect ultrasound contrast agents. Even if the subject moves only slightly, a conventional detection method will introduce significant error. In contrast, the proposed technique employs spatiotemporal analysis of the pixel intensity variation over several frames. Experiments visualizing blood vessels in the mouse tail illustrated that the proposed method performs efficiently compared with conventional approaches. We also report that the new technique is useful for observing temporal changes in microvessel density in subiliac lymph nodes containing tumors. The results are compared with those of contrast-enhanced computed tomography. Copyright © 2015 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

Movement Control in Older Adults: Does Old Age Mean Middle of the Road?

ERIC Educational Resources Information Center

Raw, Rachael K.; Kountouriotis, Georgios K.; Mon-Williams, Mark; Wilkie, Richard M.

2012-01-01

Old age is associated with poorer movement skill, as indexed by reduced speed and accuracy. Nevertheless, reductions in speed and accuracy can also reflect compensation as well as deficit. We used a manual tracing and a driving task to identify generalized spatial and temporal compensations and deficits associated with old age. In Experiment 1,…

Does a Sensory Processing Deficit Explain Counting Accuracy on Rapid Visual Sequencing Tasks in Adults with and without Dyslexia?

ERIC Educational Resources Information Center

Conlon, Elizabeth G.; Wright, Craig M.; Norris, Karla; Chekaluk, Eugene

2011-01-01

The experiments conducted aimed to investigate whether reduced accuracy when counting stimuli presented in rapid temporal sequence in adults with dyslexia could be explained by a sensory processing deficit, a general slowing in processing speed or difficulties shifting attention between stimuli. To achieve these aims, the influence of the…

Assessment of a vertical high-resolution distributed-temperature-sensing system in a shallow thermohaline environment

NASA Astrophysics Data System (ADS)

Suárez, F.; Aravena, J. E.; Hausner, M. B.; Childress, A. E.; Tyler, S. W.

2011-03-01

In shallow thermohaline-driven lakes it is important to measure temperature on fine spatial and temporal scales to detect stratification or different hydrodynamic regimes. Raman spectra distributed temperature sensing (DTS) is an approach available to provide high spatial and temporal temperature resolution. A vertical high-resolution DTS system was constructed to overcome the problems of typical methods used in the past, i.e., without disturbing the water column, and with resistance to corrosive environments. This paper describes a method to quantitatively assess accuracy, precision and other limitations of DTS systems to fully utilize the capacity of this technology, with a focus on vertical high-resolution to measure temperatures in shallow thermohaline environments. It also presents a new method to manually calibrate temperatures along the optical fiber achieving significant improved resolution. The vertical high-resolution DTS system is used to monitor the thermal behavior of a salt-gradient solar pond, which is an engineered shallow thermohaline system that allows collection and storage of solar energy for a long period of time. The vertical high-resolution DTS system monitors the temperature profile each 1.1 cm vertically and in time averages as small as 10 s. Temperature resolution as low as 0.035 °C is obtained when the data are collected at 5-min intervals.

How spatial and temporal rainfall variability affect runoff across basin scales: insights from field observations in the (semi-)urbanised Charlotte watershed

NASA Astrophysics Data System (ADS)

Ten Veldhuis, M. C.; Smith, J. A.; Zhou, Z.

2017-12-01

Impacts of rainfall variability on runoff response are highly scale-dependent. Sensitivity analyses based on hydrological model simulations have shown that impacts are likely to depend on combinations of storm type, basin versus storm scale, temporal versus spatial rainfall variability. So far, few of these conclusions have been confirmed on observational grounds, since high quality datasets of spatially variable rainfall and runoff over prolonged periods are rare. Here we investigate relationships between rainfall variability and runoff response based on 30 years of radar-rainfall datasets and flow measurements for 16 hydrological basins ranging from 7 to 111 km2. Basins vary not only in scale, but also in their degree of urbanisation. We investigated temporal and spatial variability characteristics of rainfall fields across a range of spatial and temporal scales to identify main drivers for variability in runoff response. We identified 3 ranges of basin size with different temporal versus spatial rainfall variability characteristics. Total rainfall volume proved to be the dominant agent determining runoff response at all basin scales, independent of their degree of urbanisation. Peak rainfall intensity and storm core volume are of secondary importance. This applies to all runoff parameters, including runoff volume, runoff peak, volume-to-peak and lag time. Position and movement of the storm with respect to the basin have a negligible influence on runoff response, with the exception of lag times in some of the larger basins. This highlights the importance of accuracy in rainfall estimation: getting the position right but the volume wrong will inevitably lead to large errors in runoff prediction. Our study helps to identify conditions where rainfall variability matters for correct estimation of the rainfall volume as well as the associated runoff response.

Enhanced spatio-temporal alignment of plantar pressure image sequences using B-splines.

PubMed

Oliveira, Francisco P M; Tavares, João Manuel R S

2013-03-01

This article presents an enhanced methodology to align plantar pressure image sequences simultaneously in time and space. The temporal alignment of the sequences is accomplished using B-splines in the time modeling, and the spatial alignment can be attained using several geometric transformation models. The methodology was tested on a dataset of 156 real plantar pressure image sequences (3 sequences for each foot of the 26 subjects) that was acquired using a common commercial plate during barefoot walking. In the alignment of image sequences that were synthetically deformed both in time and space, an outstanding accuracy was achieved with the cubic B-splines. This accuracy was significantly better (p < 0.001) than the one obtained using the best solution proposed in our previous work. When applied to align real image sequences with unknown transformation involved, the alignment based on cubic B-splines also achieved superior results than our previous methodology (p < 0.001). The consequences of the temporal alignment on the dynamic center of pressure (COP) displacement was also assessed by computing the intraclass correlation coefficients (ICC) before and after the temporal alignment of the three image sequence trials of each foot of the associated subject at six time instants. The results showed that, generally, the ICCs related to the medio-lateral COP displacement were greater when the sequences were temporally aligned than the ICCs of the original sequences. Based on the experimental findings, one can conclude that the cubic B-splines are a remarkable solution for the temporal alignment of plantar pressure image sequences. These findings also show that the temporal alignment can increase the consistency of the COP displacement on related acquired plantar pressure image sequences.

Short-term Temperature Prediction Using Adaptive Computing on Dynamic Scales

NASA Astrophysics Data System (ADS)

Hu, W.; Cervone, G.; Jha, S.; Balasubramanian, V.; Turilli, M.

2017-12-01

When predicting temperature, there are specific places and times when high accuracy predictions are harder. For example, not all the sub-regions in the domain require the same amount of computing resources to generate an accurate prediction. Plateau areas might require less computing resources than mountainous areas because of the steeper gradient of temperature change in the latter. However, it is difficult to estimate beforehand the optimal allocation of computational resources because several parameters play a role in determining the accuracy of the forecasts, in addition to orography. The allocation of resources to perform simulations can become a bottleneck because it requires human intervention to stop jobs or start new ones. The goal of this project is to design and develop a dynamic approach to generate short-term temperature predictions that can automatically determines the required computing resources and the geographic scales of the predictions based on the spatial and temporal uncertainties. The predictions and the prediction quality metrics are computed using a numeric weather prediction model, Analog Ensemble (AnEn), and the parallelization on high performance computing systems is accomplished using Ensemble Toolkit, one component of the RADICAL-Cybertools family of tools. RADICAL-Cybertools decouple the science needs from the computational capabilities by building an intermediate layer to run general ensemble patterns, regardless of the science. In this research, we show how the ensemble toolkit allows generating high resolution temperature forecasts at different spatial and temporal resolution. The AnEn algorithm is run using NAM analysis and forecasts data for the continental United States for a period of 2 years. AnEn results show that temperature forecasts perform well according to different probabilistic and deterministic statistical tests.

Estimating daily minimum, maximum, and mean near surface air temperature using hybrid satellite models across Israel.

PubMed

Rosenfeld, Adar; Dorman, Michael; Schwartz, Joel; Novack, Victor; Just, Allan C; Kloog, Itai

2017-11-01

Meteorological stations measure air temperature (Ta) accurately with high temporal resolution, but usually suffer from limited spatial resolution due to their sparse distribution across rural, undeveloped or less populated areas. Remote sensing satellite-based measurements provide daily surface temperature (Ts) data in high spatial and temporal resolution and can improve the estimation of daily Ta. In this study we developed spatiotemporally resolved models which allow us to predict three daily parameters: Ta Max (day time), 24h mean, and Ta Min (night time) on a fine 1km grid across the state of Israel. We used and compared both the Aqua and Terra MODIS satellites. We used linear mixed effect models, IDW (inverse distance weighted) interpolations and thin plate splines (using a smooth nonparametric function of longitude and latitude) to first calibrate between Ts and Ta in those locations where we have available data for both and used that calibration to fill in neighboring cells without surface monitors or missing Ts. Out-of-sample ten-fold cross validation (CV) was used to quantify the accuracy of our predictions. Our model performance was excellent for both days with and without available Ts observations for both Aqua and Terra (CV Aqua R 2 results for min 0.966, mean 0.986, and max 0.967; CV Terra R 2 results for min 0.965, mean 0.987, and max 0.968). Our research shows that daily min, mean and max Ta can be reliably predicted using daily MODIS Ts data even across Israel, with high accuracy even for days without Ta or Ts data. These predictions can be used as three separate Ta exposures in epidemiology studies for better diurnal exposure assessment. Copyright © 2017 Elsevier Inc. All rights reserved.

Evaluation of the influence of acquisition and reconstruction parameters for 16-row multidetector CT on coronary calcium scoring using a stationary and dynamic cardiac phantom.

PubMed

Begemann, Philipp G C; van Stevendaal, Udo; Koester, Ralph; Mahnken, Andreas H; Koops, Andreas; Adam, Gerhard; Grass, Michael; Nolte-Ernsting, Claus

2007-08-01

A calcium-scoring phantom with hydroxyapatite-filled cylindrical holes (0.5 to 4 mm) was used. High-resolution scans were performed for an accuracy baseline. The phantom was mounted to a moving heart phantom. Non-moving data with the implementation of an ECG-signal were acquired for different pitches (0.2/0.3), heart rates (60/80/95 bpm) and collimations (16 x 0.75/16 x 1.5 mm). Images were reconstructed with a cone-beam multi-cycle algorithm at a standard thickness/increment of 3 mm/1.5 mm and the thinnest possible thickness (0.8/0.4 and 2/1). Subsequently, ECG-gated moving calcium-scoring phantom data were acquired. The calcium volume and Agatston score were measured. The temporal resolution and reconstruction cycles were calculated. High-resolution scans determine the calcium volume with a high accuracy (mean overestimation, 0.8%). In the non-moving measurements, the volume underestimation ranged from about 6% (16 x 0.75 mm; 0.8/0.4 mm) to nearly 25% (16 x 1.5 mm; 3/1.5 mm). Moving scans showed increased measurement errors depending on the reconstructed RR interval, collimation, pitch, heart rate and gantry rotation time. Also, a correlation with the temporal resolution could be found. The reliability of calcium-scoring results can be improved with the use of a narrower collimation, a lower pitch and the reconstruction of thinner images, resulting in higher patient doses. The choice of the correct cardiac phase within the RR interval is essential to minimize measurement errors.

Applications of high resolution rainfall radar data to quantify water temperature dynamics in urban catchments

NASA Astrophysics Data System (ADS)

Croghan, Danny; Van Loon, Anne; Bradley, Chris; Sadler, Jon; Hannnah, David

2017-04-01

Studies relating rainfall events to river water quality are frequently hindered by the lack of high resolution rainfall data. Local studies are particularly vulnerable due to the spatial variability of precipitation, whilst studies in urban environments require precipitation data at high spatial and temporal resolutions. The use of point-source data makes identifying causal effects of storms on water quality problematic and can lead to erroneous interpretations. High spatial and temporal resolution rainfall radar data offers great potential to address these issues. Here we use rainfall radar data with a 1km spatial resolution and 5 minute temporal resolution sourced from the UK Met Office Nimrod system to study the effects of storm events on water temperature (WTemp) in Birmingham, UK. 28 WTemp loggers were placed over 3 catchments on a rural-urban land use gradient to identify trends in WTemp during extreme events within urban environments. Using GIS, the catchment associated with each logger was estimated, and 5 min. rainfall totals and intensities were produced for each sub-catchment. Comparisons of rainfall radar data to meteorological stations in the same grid cell revealed the high accuracy of rainfall radar data in our catchments (<5% difference for studied months). The rainfall radar data revealed substantial differences in rainfall quantity between the three adjacent catchments. The most urban catchment generally received more rainfall, with this effect greatest in the highest intensity storms, suggesting the possibility of urban heat island effects on precipitation dynamics within the catchment. Rainfall radar data provided more accurate sub-catchment rainfall totals allowing better modelled estimates of storm flow, whilst spatial fluctuations in both discharge and WTemp can be simply related to precipitation intensity. Storm flow inputs for each sub-catchment were estimated and linked to changes in WTemp. WTemp showed substantial fluctuations (>1 °C) over short durations (<30 minutes) during storm events in urbanised sub-catchments, however WTemp recovery times were more prolonged. Use of the rainfall radar data allowed increased accuracy in estimates of storm flow timings and rainfall quantities at each sub-catchment, from which the impact of storm flow on WTemp could be quantified. We are currently using the radar data to derive thresholds for rainfall amount and intensity at which these storm deviations occur for each logger, from which the relative effects of land use and other catchment characteristics in each sub-catchment can be assessed. Our use of the rainfall radar data calls into question the validity of using station based data for small scale studies, particularly in urban areas, with high variation apparent in rainfall intensity both spatially and temporally. Variation was particularly high within the heavily urbanised catchment. For water quality studies, high resolution rainfall radar can be implemented to increase the reliability of interpretations of the response of water quality variables to storm water inputs in urban catchments.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chacón, L., E-mail: chacon@lanl.gov; Chen, G.; Knoll, D.A.

We review the state of the art in the formulation, implementation, and performance of so-called high-order/low-order (HOLO) algorithms for challenging multiscale problems. HOLO algorithms attempt to couple one or several high-complexity physical models (the high-order model, HO) with low-complexity ones (the low-order model, LO). The primary goal of HOLO algorithms is to achieve nonlinear convergence between HO and LO components while minimizing memory footprint and managing the computational complexity in a practical manner. Key to the HOLO approach is the use of the LO representations to address temporal stiffness, effectively accelerating the convergence of the HO/LO coupled system. The HOLOmore » approach is broadly underpinned by the concept of nonlinear elimination, which enables segregation of the HO and LO components in ways that can effectively use heterogeneous architectures. The accuracy and efficiency benefits of HOLO algorithms are demonstrated with specific applications to radiation transport, gas dynamics, plasmas (both Eulerian and Lagrangian formulations), and ocean modeling. Across this broad application spectrum, HOLO algorithms achieve significant accuracy improvements at a fraction of the cost compared to conventional approaches. It follows that HOLO algorithms hold significant potential for high-fidelity system scale multiscale simulations leveraging exascale computing.« less

Evaluation of the Global Land Data Assimilation System (GLDAS) air temperature data products

USGS Publications Warehouse

Ji, Lei; Senay, Gabriel B.; Verdin, James P.

2015-01-01

There is a high demand for agrohydrologic models to use gridded near-surface air temperature data as the model input for estimating regional and global water budgets and cycles. The Global Land Data Assimilation System (GLDAS) developed by combining simulation models with observations provides a long-term gridded meteorological dataset at the global scale. However, the GLDAS air temperature products have not been comprehensively evaluated, although the accuracy of the products was assessed in limited areas. In this study, the daily 0.25° resolution GLDAS air temperature data are compared with two reference datasets: 1) 1-km-resolution gridded Daymet data (2002 and 2010) for the conterminous United States and 2) global meteorological observations (2000–11) archived from the Global Historical Climatology Network (GHCN). The comparison of the GLDAS datasets with the GHCN datasets, including 13 511 weather stations, indicates a fairly high accuracy of the GLDAS data for daily temperature. The quality of the GLDAS air temperature data, however, is not always consistent in different regions of the world; for example, some areas in Africa and South America show relatively low accuracy. Spatial and temporal analyses reveal a high agreement between GLDAS and Daymet daily air temperature datasets, although spatial details in high mountainous areas are not sufficiently estimated by the GLDAS data. The evaluation of the GLDAS data demonstrates that the air temperature estimates are generally accurate, but caution should be taken when the data are used in mountainous areas or places with sparse weather stations.

Individual differences in working memory capacity and search efficiency.

PubMed

Miller, Ashley L; Unsworth, Nash

2018-05-29

In two experiments, we examined how various learning conditions impact the relation between working memory capacity (WMC) and memory search abilities. Experiment 1 employed a delayed free recall task with semantically related words to induce the buildup of proactive interference (PI) and revealed that the buildup of PI differentially impacted recall accuracy and recall latency for low-WMC and high-WMC individuals. Namely, the buildup of PI impaired recall accuracy and slowed recall latency for low-WMC individuals to a greater extent than what was observed for high-WMC individuals. To provide a circumstance in which previously learned information remains relevant over the course of learning, Experiment 2 required participants to complete a multitrial delayed free recall task with unrelated words. Results revealed that with increased practice with the same word list, WMC-related differences were eventually eliminated in interresponse times (IRTs) and recall accuracy, but not recall latency. Thus, despite still accumulating larger search sets, low-WMC individuals searched LTM as efficiently as high-WMC individuals. Collectively, these results are consistent with the notion that under normal free recall conditions, low-WMC individuals search LTM less efficiently than do high-WMC individuals because of their reliance on noisy temporal-contextual cues at retrieval. However, it appears that under conditions in which previously learned items remain relevant at recall, this tendency to rely on vague self-generated retrieval cues can actually facilitate the ability to accurately and quickly recall information.

Post-traumatic stress disorder: a right temporal lobe syndrome?

NASA Astrophysics Data System (ADS)

Engdahl, B.; Leuthold, A. C.; Tan, H.-R. M.; Lewis, S. M.; Winskowski, A. M.; Dikel, T. N.; Georgopoulos, A. P.

2010-12-01

In a recent paper (Georgopoulos et al 2010 J. Neural Eng. 7 016011) we reported on the power of the magnetoencephalography (MEG)-based synchronous neural interactions (SNI) test to differentiate post-traumatic stress disorder (PTSD) subjects from healthy control subjects and to classify them with a high degree of accuracy. Here we show that the main differences in cortical communication circuitry between these two groups lie in the miscommunication of temporal and parietal and/or parieto-occipital right hemispheric areas with other brain areas. This lateralized temporal-posterior pattern of miscommunication was very similar but was attenuated in patients with PTSD in remission. These findings are consistent with observations (Penfield 1958 Proc. Natl Acad. Sci. USA 44 51-66, Penfield and Perot 1963 Brain 86 595-696, Gloor 1990 Brain 113 1673-94, Banceaud et al 1994 Brain 117 71-90, Fried 1997 J. Neuropsychiatry Clin. Neurosci. 9 420-8) that electrical stimulation of the temporal cortex in awake human subjects, mostly in the right hemisphere, can elicit the re-enactment and re-living of past experiences. Based on these facts, we attribute our findings to the re-experiencing component of PTSD and hypothesize that it reflects an involuntarily persistent activation of interacting neural networks involved in experiential consolidation.

A simulation to study the feasibility of improving the temporal resolution of LAGEOS geodynamic solutions by using a sequential process noise filter

NASA Technical Reports Server (NTRS)

Hartman, Brian Davis

1995-01-01

A key drawback to estimating geodetic and geodynamic parameters over time based on satellite laser ranging (SLR) observations is the inability to accurately model all the forces acting on the satellite. Errors associated with the observations and the measurement model can detract from the estimates as well. These 'model errors' corrupt the solutions obtained from the satellite orbit determination process. Dynamical models for satellite motion utilize known geophysical parameters to mathematically detail the forces acting on the satellite. However, these parameters, while estimated as constants, vary over time. These temporal variations must be accounted for in some fashion to maintain meaningful solutions. The primary goal of this study is to analyze the feasibility of using a sequential process noise filter for estimating geodynamic parameters over time from the Laser Geodynamics Satellite (LAGEOS) SLR data. This evaluation is achieved by first simulating a sequence of realistic LAGEOS laser ranging observations. These observations are generated using models with known temporal variations in several geodynamic parameters (along track drag and the J(sub 2), J(sub 3), J(sub 4), and J(sub 5) geopotential coefficients). A standard (non-stochastic) filter and a stochastic process noise filter are then utilized to estimate the model parameters from the simulated observations. The standard non-stochastic filter estimates these parameters as constants over consecutive fixed time intervals. Thus, the resulting solutions contain constant estimates of parameters that vary in time which limits the temporal resolution and accuracy of the solution. The stochastic process noise filter estimates these parameters as correlated process noise variables. As a result, the stochastic process noise filter has the potential to estimate the temporal variations more accurately since the constraint of estimating the parameters as constants is eliminated. A comparison of the temporal resolution of solutions obtained from standard sequential filtering methods and process noise sequential filtering methods shows that the accuracy is significantly improved using process noise. The results show that the positional accuracy of the orbit is improved as well. The temporal resolution of the resulting solutions are detailed, and conclusions drawn about the results. Benefits and drawbacks of using process noise filtering in this type of scenario are also identified.

An Evaluation of Data Fusion Products for the Analysis of Dryland Forest Phenology

NASA Astrophysics Data System (ADS)

Walker, J. J.; de Beurs, K.; Wynne, R. H.; Gao, F.

2010-12-01

Semi-arid forest areas cover a significant proportion of the world’s land surface; in the interior western U.S. alone, dryland forests extend across more than 56 million hectares. The scarcity of water in these systems makes them acutely sensitive to sustained weather fluctuations, such as the higher temperatures and altered water regimes predicted under most climate change scenarios. To understand, monitor, and predict the anticipated spatial and temporal changes in these areas, it is vital to characterize current phenological patterns. Phenological analysis of western U.S. drylands is complicated by patchy land cover and mosaics of plant phenology states at a variety of spatial scales. Our aim is to use complementary satellite sensors to mitigate these difficulties and gain greater insight into phenological patterns in dryland forests. In this study we applied the spatial and temporal adaptive reflectance model (STARFM; Gao et al. 2006) to fuse Landsat and MODIS imagery to create synthetic images at Landsat spatial resolution and MODIS temporal resolution. To determine which MODIS dataset is most appropriate for the creation of synthetic images intended for the analysis of dryland forest phenology, we examined the effect of temporal compositing and BRDF function adjustment on the accuracy of STARFM imagery. We assembled seven Landsat 5 scenes (path/row 37/36) and temporally-coincident 500m MODIS datasets (seven daily (MOD09GA), seven 8-day composite (MOD09A1), and fourteen 16-day nadir BRDF-adjusted composite (MCD43A4) images) spanning the 2006 April - October growing season in northern Arizona, which is characterized by large tracts of dryland forest. The STARFM algorithm was applied to each MODIS data series to produce four synthetic images (one daily; one 8-day composite; and two 16-day composites) corresponding to each Landsat image. Validation of the accuracy of the synthetic images was achieved by comparing the reflectance values of a random sample of the identified dryland forest pixels in both images. Preliminary data analysis of the effect of the temporal resolution and dataset parameters indicates that the MODIS 8-day composite image may be a suitable and sufficient dataset for phenological analysis in this dryland forest ecosystem. Overall, this work demonstrates the feasibility of using data fusion products to assemble an imagery dataset at sufficiently high temporal and spatial scales to permit a more detailed examination of the underlying phenological processes and trends in dryland forest areas.

In pursuit of an accurate spatial and temporal model of biomolecules at the atomistic level: a perspective on computer simulation.

PubMed

Gray, Alan; Harlen, Oliver G; Harris, Sarah A; Khalid, Syma; Leung, Yuk Ming; Lonsdale, Richard; Mulholland, Adrian J; Pearson, Arwen R; Read, Daniel J; Richardson, Robin A

2015-01-01

Despite huge advances in the computational techniques available for simulating biomolecules at the quantum-mechanical, atomistic and coarse-grained levels, there is still a widespread perception amongst the experimental community that these calculations are highly specialist and are not generally applicable by researchers outside the theoretical community. In this article, the successes and limitations of biomolecular simulation and the further developments that are likely in the near future are discussed. A brief overview is also provided of the experimental biophysical methods that are commonly used to probe biomolecular structure and dynamics, and the accuracy of the information that can be obtained from each is compared with that from modelling. It is concluded that progress towards an accurate spatial and temporal model of biomacromolecules requires a combination of all of these biophysical techniques, both experimental and computational.

Early, but not late visual distractors affect movement synchronization to a temporal-spatial visual cue.

PubMed

Booth, Ashley J; Elliott, Mark T

2015-01-01

The ease of synchronizing movements to a rhythmic cue is dependent on the modality of the cue presentation: timing accuracy is much higher when synchronizing with discrete auditory rhythms than an equivalent visual stimulus presented through flashes. However, timing accuracy is improved if the visual cue presents spatial as well as temporal information (e.g., a dot following an oscillatory trajectory). Similarly, when synchronizing with an auditory target metronome in the presence of a second visual distracting metronome, the distraction is stronger when the visual cue contains spatial-temporal information rather than temporal only. The present study investigates individuals' ability to synchronize movements to a temporal-spatial visual cue in the presence of same-modality temporal-spatial distractors. Moreover, we investigated how increasing the number of distractor stimuli impacted on maintaining synchrony with the target cue. Participants made oscillatory vertical arm movements in time with a vertically oscillating white target dot centered on a large projection screen. The target dot was surrounded by 2, 8, or 14 distractor dots, which had an identical trajectory to the target but at a phase lead or lag of 0, 100, or 200 ms. We found participants' timing performance was only affected in the phase-lead conditions and when there were large numbers of distractors present (8 and 14). This asymmetry suggests participants still rely on salient events in the stimulus trajectory to synchronize movements. Subsequently, distractions occurring in the window of attention surrounding those events have the maximum impact on timing performance.

Determination of Flaw Size and Depth From Temporal Evolution of Thermal Response

NASA Technical Reports Server (NTRS)

Winfree, William P.; Zalameda, Joseph N.; Cramer, Elliott; Howell, Patricia A.

2015-01-01

Simple methods for reducing the pulsed thermographic responses of flaws have tended to be based on either the spatial or temporal response. This independent assessment limits the accuracy of characterization. A variational approach is presented for reducing the thermographic data to produce an estimated size for a flaw that incorporates both the temporal and spatial response to improve the characterization. The size and depth are determined from both the temporal and spatial thermal response of the exterior surface above a flaw and constraints on the length of the contour surrounding the delamination. Examples of the application of the technique to simulation and experimental data acquired are presented to investigate the limitations of the technique.

Temporal correlation between two channels EEG of bipolar lead in the head midline is associated with sleep-wake stages.

PubMed

Li, Yanjun; Tang, Xiaoying; Xu, Zhi; Liu, Weifeng; Li, Jing

2016-03-01

Whether the temporal correlation between inter-leads Electroencephalogram (EEG) that located on the boundary between left and right brain hemispheres is associated with sleep stages or not is still unknown. The purpose of this paper is to evaluate the role of correlation coefficients between EEG leads Fpz-Cz and Pz-Oz for automatic classification of sleep stages. A total number of 39 EEG recordings (about 20 h each) were selected from the expanded sleep database in European data format for temporal correlation analysis. Original waveform of EEG was decomposed into sub-bands δ (1-4 Hz), θ (4-8 Hz), α (8-13 Hz) and β (13-30 Hz). The correlation coefficient between original EEG leads Fpz-Cz and Pz-Oz within frequency band 0.5-30 Hz was defined as r(EEG) and was calculated every 30 s, while that between the two leads EEG in sub-bands δ, θ, α and β were defined as r(δ), r(θ), r(α) and r(β), respectively. Classification of wakefulness and sleep was processed by fixed threshold that derived from the probability density function of correlation coefficients. There was no correlation between EEG leads Fpz-Cz and Pz-Oz during wakefulness (|r| < 0.1 for r(θ), r(α) and r(β), while 0.3 > r > 0.1 for r(EEG) and r(δ)), while low correlation existed during sleep (r ≈ -0.4 for r(EEG), r(δ), r(θ), r(α) and r(β)). There were significant differences (analysis of variance, P < 0.001) for r(EEG), r(δ), r(θ), r(α) and r(β) during sleep when in comparison with that during wakefulness, respectively. The accuracy for distinguishing states between wakefulness and sleep was 94.2, 93.4, 89.4, 85.2 and 91.4% in terms of r(EEG), r(δ), r(θ), r(α) and r(β), respectively. However, no correlation index between EEG leads Fpz-Cz and Pz-Oz could distinguish all five types of wakefulness, rapid eye movement (REM) sleep, N1 sleep, N2 sleep and N3 sleep. In conclusion, the temporal correlation between EEG bipolar leads Fpz-Cz and Pz-Oz are highly associated with sleep-wake stages. Moreover, high accuracy of sleep-wake classification could be achieved by the temporal correlation within frequency band 0.5-30 Hz between EEG leads Fpz-Cz and Pz-Oz.

Fusion of Computed Tomography and PROPELLER Diffusion-Weighted Magnetic Resonance Imaging for the Detection and Localization of Middle Ear Cholesteatoma.

PubMed

Locketz, Garrett D; Li, Peter M M C; Fischbein, Nancy J; Holdsworth, Samantha J; Blevins, Nikolas H

2016-10-01

A method to optimize imaging of cholesteatoma by combining the strengths of available modalities will improve diagnostic accuracy and help to target treatment. To assess whether fusing Periodically Rotated Overlapping Parallel Lines With Enhanced Reconstruction (PROPELLER) diffusion-weighted magnetic resonance imaging (DW-MRI) with corresponding temporal bone computed tomography (CT) images could increase cholesteatoma diagnostic and localization accuracy across 6 distinct anatomical regions of the temporal bone. Case series and preliminary technology evaluation of adults with preoperative temporal bone CT and PROPELLER DW-MRI scans who underwent surgery for clinically suggested cholesteatoma at a tertiary academic hospital. When cholesteatoma was encountered surgically, the precise location was recorded in a diagram of the middle ear and mastoid. For each patient, the 3 image data sets (CT, PROPELLER DW-MRI, and CT-MRI fusion) were reviewed in random order for the presence or absence of cholesteatoma by an investigator blinded to operative findings. If cholesteatoma was deemed present on review of each imaging modality, the location of the lesion was mapped presumptively. Image analysis was then compared with surgical findings. Twelve adults (5 women and 7 men; median [range] age, 45.5 [19-77] years) were included. The use of CT-MRI fusion had greater diagnostic sensitivity (0.88 vs 0.75), positive predictive value (0.88 vs 0.86), and negative predictive value (0.75 vs 0.60) than PROPELLER DW-MRI alone. Image fusion also showed increased overall localization accuracy when stratified across 6 distinct anatomical regions of the temporal bone (localization sensitivity and specificity, 0.76 and 0.98 for CT-MRI fusion vs 0.58 and 0.98 for PROPELLER DW-MRI). For PROPELLER DW-MRI, there were 15 true-positive, 45 true-negative, 1 false-positive, and 11 false-negative results; overall accuracy was 0.83. For CT-MRI fusion, there were 20 true-positive, 45 true-negative, 1 false-positive, and 6 false-negative results; overall accuracy was 0.90. The poor anatomical spatial resolution of DW-MRI makes precise localization of cholesteatoma within the middle ear and mastoid a diagnostic challenge. This study suggests that the bony anatomic detail obtained via CT coupled with the excellent sensitivity and specificity of PROPELLER DW-MRI for cholesteatoma can improve both preoperative identification and localization of disease over DW-MRI alone.

EEG Beta Oscillations in the Temporoparietal Area Related to the Accuracy in Estimating Others' Preference

PubMed Central

Park, Jonghyeok; Kim, Hackjin; Sohn, Jeong-Woo; Choi, Jong-ryul; Kim, Sung-Phil

2018-01-01

Humans often attempt to predict what others prefer based on a narrow slice of experience, called thin-slicing. According to the theoretical bases for how humans can predict the preference of others, one tends to estimate the other's preference using a perceived difference between the other and self. Previous neuroimaging studies have revealed that the network of dorsal medial prefrontal cortex (dmPFC) and right temporoparietal junction (rTPJ) is related to the ability of predicting others' preference. However, it still remains unknown about the temporal patterns of neural activities for others' preference prediction through thin-slicing. To investigate such temporal aspects of neural activities, we investigated human electroencephalography (EEG) recorded during the task of predicting the preference of others while only a facial picture of others was provided. Twenty participants (all female, average age: 21.86) participated in the study. In each trial of the task, participants were shown a picture of either a target person or self for 3 s, followed by the presentation of a movie poster over which participants predicted the target person's preference as liking or disliking. The time-frequency EEG analysis was employed to analyze temporal changes in the amplitudes of brain oscillations. Participants could predict others' preference for movies with accuracy of 56.89 ± 3.16% and 10 out of 20 participants exhibited prediction accuracy higher than a chance level (95% interval). There was a significant difference in the power of the parietal alpha (10~13 Hz) oscillation 0.6~0.8 s after the onset of poster presentation between the cases when participants predicted others' preference and when they reported self-preference (p < 0.05). The power of brain oscillations at any frequency band and time period during the trial did not show a significant correlation with individual prediction accuracy. However, when we measured differences of the power between the trials of predicting other's preference and reporting self-preference, the right temporal beta oscillations 1.6~1.8 s after the onset of facial picture presentation exhibited a significant correlation with individual accuracy. Our results suggest that right temporoparietal beta oscillations may be correlated with one's ability to predict what others prefer with minimal information. PMID:29479312

EEG Beta Oscillations in the Temporoparietal Area Related to the Accuracy in Estimating Others' Preference.

PubMed

Park, Jonghyeok; Kim, Hackjin; Sohn, Jeong-Woo; Choi, Jong-Ryul; Kim, Sung-Phil

2018-01-01

Humans often attempt to predict what others prefer based on a narrow slice of experience, called thin-slicing. According to the theoretical bases for how humans can predict the preference of others, one tends to estimate the other's preference using a perceived difference between the other and self. Previous neuroimaging studies have revealed that the network of dorsal medial prefrontal cortex (dmPFC) and right temporoparietal junction (rTPJ) is related to the ability of predicting others' preference. However, it still remains unknown about the temporal patterns of neural activities for others' preference prediction through thin-slicing. To investigate such temporal aspects of neural activities, we investigated human electroencephalography (EEG) recorded during the task of predicting the preference of others while only a facial picture of others was provided. Twenty participants (all female, average age: 21.86) participated in the study. In each trial of the task, participants were shown a picture of either a target person or self for 3 s, followed by the presentation of a movie poster over which participants predicted the target person's preference as liking or disliking. The time-frequency EEG analysis was employed to analyze temporal changes in the amplitudes of brain oscillations. Participants could predict others' preference for movies with accuracy of 56.89 ± 3.16% and 10 out of 20 participants exhibited prediction accuracy higher than a chance level (95% interval). There was a significant difference in the power of the parietal alpha (10~13 Hz) oscillation 0.6~0.8 s after the onset of poster presentation between the cases when participants predicted others' preference and when they reported self-preference ( p < 0.05). The power of brain oscillations at any frequency band and time period during the trial did not show a significant correlation with individual prediction accuracy. However, when we measured differences of the power between the trials of predicting other's preference and reporting self-preference, the right temporal beta oscillations 1.6~1.8 s after the onset of facial picture presentation exhibited a significant correlation with individual accuracy. Our results suggest that right temporoparietal beta oscillations may be correlated with one's ability to predict what others prefer with minimal information.

Accuracy Assessment of Underwater Photogrammetric Three Dimensional Modelling for Coral Reefs

NASA Astrophysics Data System (ADS)

Guo, T.; Capra, A.; Troyer, M.; Gruen, A.; Brooks, A. J.; Hench, J. L.; Schmitt, R. J.; Holbrook, S. J.; Dubbini, M.

2016-06-01

Recent advances in automation of photogrammetric 3D modelling software packages have stimulated interest in reconstructing highly accurate 3D object geometry in unconventional environments such as underwater utilizing simple and low-cost camera systems. The accuracy of underwater 3D modelling is affected by more parameters than in single media cases. This study is part of a larger project on 3D measurements of temporal change of coral cover in tropical waters. It compares the accuracies of 3D point clouds generated by using images acquired from a system camera mounted in an underwater housing and the popular GoPro cameras respectively. A precisely measured calibration frame was placed in the target scene in order to provide accurate control information and also quantify the errors of the modelling procedure. In addition, several objects (cinder blocks) with various shapes were arranged in the air and underwater and 3D point clouds were generated by automated image matching. These were further used to examine the relative accuracy of the point cloud generation by comparing the point clouds of the individual objects with the objects measured by the system camera in air (the best possible values). Given a working distance of about 1.5 m, the GoPro camera can achieve a relative accuracy of 1.3 mm in air and 2.0 mm in water. The system camera achieved an accuracy of 1.8 mm in water, which meets our requirements for coral measurement in this system.

Simultaneous acquisition sequence for improved hepatic pharmacokinetics quantification accuracy (SAHA) for dynamic contrast-enhanced MRI of liver.

PubMed

Ning, Jia; Sun, Yongliang; Xie, Sheng; Zhang, Bida; Huang, Feng; Koken, Peter; Smink, Jouke; Yuan, Chun; Chen, Huijun

2018-05-01

To propose a simultaneous acquisition sequence for improved hepatic pharmacokinetics quantification accuracy (SAHA) method for liver dynamic contrast-enhanced MRI. The proposed SAHA simultaneously acquired high temporal-resolution 2D images for vascular input function extraction using Cartesian sampling and 3D large-coverage high spatial-resolution liver dynamic contrast-enhanced images using golden angle stack-of-stars acquisition in an interleaved way. Simulations were conducted to investigate the accuracy of SAHA in pharmacokinetic analysis. A healthy volunteer and three patients with cirrhosis or hepatocellular carcinoma were included in the study to investigate the feasibility of SAHA in vivo. Simulation studies showed that SAHA can provide closer results to the true values and lower root mean square error of estimated pharmacokinetic parameters in all of the tested scenarios. The in vivo scans of subjects provided fair image quality of both 2D images for arterial input function and portal venous input function and 3D whole liver images. The in vivo fitting results showed that the perfusion parameters of healthy liver were significantly different from those of cirrhotic liver and HCC. The proposed SAHA can provide improved accuracy in pharmacokinetic modeling and is feasible in human liver dynamic contrast-enhanced MRI, suggesting that SAHA is a potential tool for liver dynamic contrast-enhanced MRI. Magn Reson Med 79:2629-2641, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

Evaluation of NLDAS 12-km and downscaled 1-km temperature products in New York State for potential use in health exposure response studies

NASA Astrophysics Data System (ADS)

Estes, M. G., Jr.; Insaf, T.; Crosson, W. L.; Al-Hamdan, M. Z.

2017-12-01

Heat exposure metrics (maximum and minimum daily temperatures,) have a close relationship with human health. While meteorological station data provide a good source of point measurements, temporal and spatially consistent temperature data are needed for health studies. Reanalysis data such as the North American Land Data Assimilation System's (NLDAS) 12-km gridded product are an effort to resolve spatio-temporal environmental data issues; the resolution may be too coarse to accurately capture the effects of elevation, mixed land/water areas, and urbanization. As part of this NASA Applied Sciences Program funded project, the NLDAS 12-km air temperature product has been downscaled to 1-km using MODIS Land Surface Temperature patterns. Limited validation of the native 12-km NLDAS reanalysis data has been undertaken. Our objective is to evaluate the accuracy of both the 12-km and 1-km downscaled products using the US Historical Climatology Network station data geographically dispersed across New York State. Statistical methods including correlation, scatterplots, time series and summary statistics were used to determine the accuracy of the remotely-sensed maximum and minimum temperature products. The specific effects of elevation and slope on remotely-sensed temperature product accuracy were determined with 10-m digital elevation data that were used to calculate percent slope and link with the temperature products at multiple scales. Preliminary results indicate the downscaled temperature product improves accuracy over the native 12-km temperature product with average correlation improvements from 0.81 to 0.85 for minimum and 0.71 to 0.79 for maximum temperatures in 2009. However, the benefits vary temporally and geographically. Our results will inform health studies using remotely-sensed temperature products to determine health risk from excessive heat by providing a more robust assessment of the accuracy of the 12-km NLDAS product and additional accuracy gained from the 1-km downscaled product. Also, the results will be shared with the National Weather Service to determine potential benefits to heat warning systems and evaluated for inclusion in the Centers of Disease Control and Prevention (CDC) Environmental Public Health Tracking Network as a resource for the health community.

Sensitivity of chemistry-transport model simulations to the duration of chemical and transport operators: a case study with GEOS-Chem v10-01

NASA Astrophysics Data System (ADS)

Philip, Sajeev; Martin, Randall V.; Keller, Christoph A.

2016-05-01

Chemistry-transport models involve considerable computational expense. Fine temporal resolution offers accuracy at the expense of computation time. Assessment is needed of the sensitivity of simulation accuracy to the duration of chemical and transport operators. We conduct a series of simulations with the GEOS-Chem chemistry-transport model at different temporal and spatial resolutions to examine the sensitivity of simulated atmospheric composition to operator duration. Subsequently, we compare the species simulated with operator durations from 10 to 60 min as typically used by global chemistry-transport models, and identify the operator durations that optimize both computational expense and simulation accuracy. We find that longer continuous transport operator duration increases concentrations of emitted species such as nitrogen oxides and carbon monoxide since a more homogeneous distribution reduces loss through chemical reactions and dry deposition. The increased concentrations of ozone precursors increase ozone production with longer transport operator duration. Longer chemical operator duration decreases sulfate and ammonium but increases nitrate due to feedbacks with in-cloud sulfur dioxide oxidation and aerosol thermodynamics. The simulation duration decreases by up to a factor of 5 from fine (5 min) to coarse (60 min) operator duration. We assess the change in simulation accuracy with resolution by comparing the root mean square difference in ground-level concentrations of nitrogen oxides, secondary inorganic aerosols, ozone and carbon monoxide with a finer temporal or spatial resolution taken as "truth". Relative simulation error for these species increases by more than a factor of 5 from the shortest (5 min) to longest (60 min) operator duration. Chemical operator duration twice that of the transport operator duration offers more simulation accuracy per unit computation. However, the relative simulation error from coarser spatial resolution generally exceeds that from longer operator duration; e.g., degrading from 2° × 2.5° to 4° × 5° increases error by an order of magnitude. We recommend prioritizing fine spatial resolution before considering different operator durations in offline chemistry-transport models. We encourage chemistry-transport model users to specify in publications the durations of operators due to their effects on simulation accuracy.

Accuracy and precision of a custom camera-based system for 2D and 3D motion tracking during speech and nonspeech motor tasks

PubMed Central

Feng, Yongqiang; Max, Ludo

2014-01-01

Purpose Studying normal or disordered motor control requires accurate motion tracking of the effectors (e.g., orofacial structures). The cost of electromagnetic, optoelectronic, and ultrasound systems is prohibitive for many laboratories, and limits clinical applications. For external movements (lips, jaw), video-based systems may be a viable alternative, provided that they offer high temporal resolution and sub-millimeter accuracy. Method We examined the accuracy and precision of 2D and 3D data recorded with a system that combines consumer-grade digital cameras capturing 60, 120, or 240 frames per second (fps), retro-reflective markers, commercially-available computer software (APAS, Ariel Dynamics), and a custom calibration device. Results Overall mean error (RMSE) across tests was 0.15 mm for static tracking and 0.26 mm for dynamic tracking, with corresponding precision (SD) values of 0.11 and 0.19 mm, respectively. The effect of frame rate varied across conditions, but, generally, accuracy was reduced at 240 fps. The effect of marker size (3 vs. 6 mm diameter) was negligible at all frame rates for both 2D and 3D data. Conclusion Motion tracking with consumer-grade digital cameras and the APAS software can achieve sub-millimeter accuracy at frame rates that are appropriate for kinematic analyses of lip/jaw movements for both research and clinical purposes. PMID:24686484

Dual-source spiral CT with pitch up to 3.2 and 75 ms temporal resolution: image reconstruction and assessment of image quality.

PubMed

Flohr, Thomas G; Leng, Shuai; Yu, Lifeng; Aiimendinger, Thomas; Bruder, Herbert; Petersilka, Martin; Eusemann, Christian D; Stierstorfer, Karl; Schmidt, Bernhard; McCollough, Cynthia H

2009-12-01

To present the theory for image reconstruction of a high-pitch, high-temporal-resolution spiral scan mode for dual-source CT (DSCT) and evaluate its image quality and dose. With the use of two x-ray sources and two data acquisition systems, spiral CT exams having a nominal temporal resolution per image of up to one-quarter of the gantry rotation time can be acquired using pitch values up to 3.2. The scan field of view (SFOV) for this mode, however, is limited to the SFOV of the second detector as a maximum, depending on the pitch. Spatial and low contrast resolution, image uniformity and noise, CT number accuracy and linearity, and radiation dose were assessed using the ACR CT accreditation phantom, a 30 cm diameter cylindrical water phantom or a 32 cm diameter cylindrical PMMA CTDI phantom. Slice sensitivity profiles (SSPs) were measured for different nominal slice thicknesses, and an anthropomorphic phantom was used to assess image artifacts. Results were compared between single-source scans at pitch = 1.0 and dual-source scans at pitch = 3.2. In addition, image quality and temporal resolution of an ECG-triggered version of the DSCT high-pitch spiral scan mode were evaluated with a moving coronary artery phantom, and radiation dose was assessed in comparison with other existing cardiac scan techniques. No significant differences in quantitative measures of image quality were found between single-source scans at pitch = 1.0 and dual-source scans at pitch = 3.2 for spatial and low contrast resolution, CT number accuracy and linearity, SSPs, image uniformity, and noise. The pitch value (1.6 pitch 3.2) had only a minor impact on radiation dose and image noise when the effective tube current time product (mA s/pitch) was kept constant. However, while not severe, artifacts were found to be more prevalent for the dual-source pitch = 3.2 scan mode when structures varied markedly along the z axis, particularly for head scans. Images of the moving coronary artery phantom acquired with the ECG-triggered high-pitch scan mode were visually free from motion artifacts at heart rates of 60 and 70 bpm. However, image quality started to deteriorate for higher heart rates. At equivalent image quality, the ECG-triggered high-pitch scan mode demonstrated lower radiation dose than other cardiac scan techniques on the same DSCT equipment (25% and 60% dose reduction compared to ECG-triggered sequential step-and-shoot and ECG-gated spiral with x-ray pulsing). A high-pitch (up to pitch = 3.2), high-temporal-resolution (up to 75 ms) dual-source CT scan mode produced equivalent image quality relative to single-source scans using a more typical pitch value (pitch = 1.0). The resultant reduction in the overall acquisition time may offer clinical advantage for cardiovascular, trauma, and pediatric CT applications. In addition, ECG-triggered high-pitch scanning may be useful as an alternative to ECG-triggered sequential scanning for patients with low to moderate heart rates up to 70 bpm, with the potential to scan the heart within one heart beat at reduced radiation dose.

Abnormal early dynamic individual patterns of functional networks in low gamma band for depression recognition.

PubMed

Bi, Kun; Chattun, Mahammad Ridwan; Liu, Xiaoxue; Wang, Qiang; Tian, Shui; Zhang, Siqi; Lu, Qing; Yao, Zhijian

2018-06-13

The functional networks are associated with emotional processing in depression. The mapping of dynamic spatio-temporal brain networks is used to explore individual performance during early negative emotional processing. However, the dysfunctions of functional networks in low gamma band and their discriminative potentialities during early period of emotional face processing remain to be explored. Functional brain networks were constructed from the MEG recordings of 54 depressed patients and 54 controls in low gamma band (30-48 Hz). Dynamic connectivity regression (DCR) algorithm analyzed the individual change points of time series in response to emotional stimuli and constructed individualized spatio-temporal patterns. The nodal characteristics of patterns were calculated and fed into support vector machine (SVM). Performance of the classification algorithm in low gamma band was validated by dynamic topological characteristics of individual patterns in comparison to alpha and beta band. The best discrimination accuracy of individual spatio-temporal patterns was 91.01% in low gamma band. Individual temporal patterns had better results compared to group-averaged temporal patterns in all bands. The most important discriminative networks included affective network (AN) and fronto-parietal network (FPN) in low gamma band. The sample size is relatively small. High gamma band was not considered. The abnormal dynamic functional networks in low gamma band during early emotion processing enabled depression recognition. The individual information processing is crucial in the discovery of abnormal spatio-temporal patterns in depression during early negative emotional processing. Individual spatio-temporal patterns may reflect the real dynamic function of subjects while group-averaged data may neglect some individual information. Copyright © 2018. Published by Elsevier B.V.

Direct current stimulation over the anterior temporal areas boosts semantic processing in primary progressive aphasia.

PubMed

Teichmann, Marc; Lesoil, Constance; Godard, Juliette; Vernet, Marine; Bertrand, Anne; Levy, Richard; Dubois, Bruno; Lemoine, Laurie; Truong, Dennis Q; Bikson, Marom; Kas, Aurélie; Valero-Cabré, Antoni

2016-11-01

Noninvasive brain stimulation in primary progressive aphasia (PPA) is a promising approach. Yet, applied to single cases or insufficiently controlled small-cohort studies, it has not clarified its therapeutic value. We here address the effectiveness of transcranial direct current stimulation (tDCS) on the semantic PPA variant (sv-PPA), applying a rigorous study design to a large, homogeneous sv-PPA cohort. Using a double-blind, sham-controlled counterbalanced cross-over design, we applied three tDCS conditions targeting the temporal poles of 12 sv-PPA patients. Efficiency was assessed by a semantic matching task orthogonally manipulating "living"/"nonliving" categories and verbal/visual modalities. Conforming to predominantly left-lateralized damage in sv-PPA and accounts of interhemispheric inhibition, we applied left hemisphere anodal-excitatory and right hemisphere cathodal-inhibitory tDCS, compared to sham stimulation. Prestimulation data, compared to 15 healthy controls, showed that patients had semantic disorders predominating with living categories in the verbal modality. Stimulation selectively impacted these most impaired domains: Left-excitatory and right-inhibitory tDCS improved semantic accuracy in verbal modality, and right-inhibitory tDCS improved processing speed with living categories and accuracy and processing speed in the combined verbal × living condition. Our findings demonstrate the efficiency of tDCS in sv-PPA by generating highly specific intrasemantic effects. They provide "proof of concept" for future applications of tDCS in therapeutic multiday regimes, potentially driving sustained improvement of semantic processing. Our data also support the hotly debated existence of a left temporal-pole network for verbal semantics selectively modulated through both left-excitatory and right-inhibitory brain stimulation. Ann Neurol 2016;80:693-707. © 2016 American Neurological Association.

Temporal Integration of Auditory Information Is Invariant to Temporal Grouping Cues

PubMed

Liu, Andrew S K; Tsunada, Joji; Gold, Joshua I; Cohen, Yale E

2015-01-01

Auditory perception depends on the temporal structure of incoming acoustic stimuli. Here, we examined whether a temporal manipulation that affects the perceptual grouping also affects the time dependence of decisions regarding those stimuli. We designed a novel discrimination task that required human listeners to decide whether a sequence of tone bursts was increasing or decreasing in frequency. We manipulated temporal perceptual-grouping cues by changing the time interval between the tone bursts, which led to listeners hearing the sequences as a single sound for short intervals or discrete sounds for longer intervals. Despite these strong perceptual differences, this manipulation did not affect the efficiency of how auditory information was integrated over time to form a decision. Instead, the grouping manipulation affected subjects' speed-accuracy trade-offs. These results indicate that the temporal dynamics of evidence accumulation for auditory perceptual decisions can be invariant to manipulations that affect the perceptual grouping of the evidence.

Spatio-temporal alignment of multiple sensors

NASA Astrophysics Data System (ADS)

Zhang, Tinghua; Ni, Guoqiang; Fan, Guihua; Sun, Huayan; Yang, Biao

2018-01-01

Aiming to achieve the spatio-temporal alignment of multi sensor on the same platform for space target observation, a joint spatio-temporal alignment method is proposed. To calibrate the parameters and measure the attitude of cameras, an astronomical calibration method is proposed based on star chart simulation and collinear invariant features of quadrilateral diagonal between the observed star chart. In order to satisfy a temporal correspondence and spatial alignment similarity simultaneously, the method based on the astronomical calibration and attitude measurement in this paper formulates the video alignment to fold the spatial and temporal alignment into a joint alignment framework. The advantage of this method is reinforced by exploiting the similarities and prior knowledge of velocity vector field between adjacent frames, which is calculated by the SIFT Flow algorithm. The proposed method provides the highest spatio-temporal alignment accuracy compared to the state-of-the-art methods on sequences recorded from multi sensor at different times.

Alterations in Cortical Thickness and White Matter Integrity in Mild Cognitive Impairment Measured by Whole Brain Cortical Thickness Mapping and Diffusion Tensor Imaging

PubMed Central

Wang, Liya; Goldstein, Felicia C.; Veledar, Emir; Levey, Allan I.; Lah, James J.; Meltzer, Carolyn C.; Holder, Chad A.; Mao, Hui

2010-01-01

Background and Purpose Mild cognitive impairment (MCI) is a risk factor for Alzheimer's disease (AD) and can be difficult to diagnose due to the subtlety of symptoms. This work attempted to examine gray and white matter changes with cortical thickness analysis and diffusion tensor imaging (DTI) in MCI patients and demographically-matched comparison subjects in order to test these measurements as possible imaging markers for diagnosis. Materials and Methods Subjects with amnestic MCI (n=10; age 72.2±7.1) and normal cognition (n=10; age 70.1±7.7) underwent DTI and T1 weighted MRI at 3T. Fractional anisotropy, apparent diffusion coefficient and cortical thickness were measured and compared between MCI and control groups. The diagnostic accuracy of two methods, either in combination or separately, was evaluated using binary logistic regression and nonparametric statistical analyses for sensitivity, specificity and accuracy. Results Decreased FA and increased ADC in white matter regions of frontal and temporal lobes and corpus callosum were observed in MCI patients. Cortical thickness was decreased in gray matter regions of the frontal, temporal, parietal lobes in MCI patients. Changes in white matter and cortical thickness appeared to be more pronounced in the left hemisphere than in the right hemisphere. Furthermore the combination of cortical thickness and DTI measurements in left temporal areas improved the accuracy of differentiating MCI patients from controls compared to either measure alone. Conclusion DTI and cortical thickness analyses may both serve imaging markers for differentiating MCI from normal aging. Combined use of two methods may improve the accuracy of MCI diagnosis. PMID:19279272

Surface Subsidence Analysis by Multi-Temporal InSAR and GRACE: A Case Study in Beijing.

PubMed

Guo, Jiming; Zhou, Lv; Yao, Chaolong; Hu, Jiyuan

2016-09-14

The aim of this study was to investigate the relationship between surface subsidence and groundwater changes. To investigate this relationship, we first analyzed surface subsidence. This paper presents the results of a case study of surface subsidence in Beijing from 1 August 2007 to 29 September 2010. The Multi-temporal Interferometric Synthetic Aperture Radar (multi-temporal InSAR) technique, which can simultaneously detect point-like stable reflectors (PSs) and distributed scatterers (DSs), was used to retrieve the subsidence magnitude and distribution in Beijing using 18 ENVISAT ASAR images. The multi-temporal InSAR-derived subsidence was verified by leveling at an accuracy better than 5 mm/year. Based on the verified multi-temporal InSAR results, a prominent uneven subsidence was identified in Beijing. Specifically, most of the subsidence velocities in the downtown area were within 10 mm/year, and the largest subsidence was detected in Tongzhou, with velocities exceeding 140 mm/year. Furthermore, Gravity Recovery and Climate Experiment (GRACE) data were used to derive the groundwater change series and trend. By comparison with the multi-temporal InSAR-derived subsidence results, the long-term decreasing trend between groundwater changes and surface subsidence showed a relatively high consistency, and a significant impact of groundwater changes on the surface subsidence was identified. Additionally, the spatial distribution of the subsidence funnel was partially consistent with that of groundwater depression, i.e., the former possessed a wider range than the latter. Finally, the relationship between surface subsidence and groundwater changes was determined.

Surface Subsidence Analysis by Multi-Temporal InSAR and GRACE: A Case Study in Beijing

PubMed Central

Guo, Jiming; Zhou, Lv; Yao, Chaolong; Hu, Jiyuan

2016-01-01

The aim of this study was to investigate the relationship between surface subsidence and groundwater changes. To investigate this relationship, we first analyzed surface subsidence. This paper presents the results of a case study of surface subsidence in Beijing from 1 August 2007 to 29 September 2010. The Multi-temporal Interferometric Synthetic Aperture Radar (multi-temporal InSAR) technique, which can simultaneously detect point-like stable reflectors (PSs) and distributed scatterers (DSs), was used to retrieve the subsidence magnitude and distribution in Beijing using 18 ENVISAT ASAR images. The multi-temporal InSAR-derived subsidence was verified by leveling at an accuracy better than 5 mm/year. Based on the verified multi-temporal InSAR results, a prominent uneven subsidence was identified in Beijing. Specifically, most of the subsidence velocities in the downtown area were within 10 mm/year, and the largest subsidence was detected in Tongzhou, with velocities exceeding 140 mm/year. Furthermore, Gravity Recovery and Climate Experiment (GRACE) data were used to derive the groundwater change series and trend. By comparison with the multi-temporal InSAR-derived subsidence results, the long-term decreasing trend between groundwater changes and surface subsidence showed a relatively high consistency, and a significant impact of groundwater changes on the surface subsidence was identified. Additionally, the spatial distribution of the subsidence funnel was partially consistent with that of groundwater depression, i.e., the former possessed a wider range than the latter. Finally, the relationship between surface subsidence and groundwater changes was determined. PMID:27649183

Collaborative Beamfocusing Radio (COBRA)

NASA Astrophysics Data System (ADS)

Rode, Jeremy P.; Hsu, Mark J.; Smith, David; Husain, Anis

2013-05-01

A Ziva team has recently demonstrated a novel technique called Collaborative Beamfocusing Radios (COBRA) which enables an ad-hoc collection of distributed commercial off-the-shelf software defined radios to coherently align and beamform to a remote radio. COBRA promises to operate even in high multipath and non-line-of-sight environments as well as mobile applications without resorting to computationally expensive closed loop techniques that are currently unable to operate with significant movement. COBRA exploits two key technologies to achieve coherent beamforming. The first is Time Reversal (TR) which compensates for multipath and automatically discovers the optimal spatio-temporal matched filter to enable peak signal gains (up to 20 dB) and diffraction-limited focusing at the intended receiver in NLOS and severe multipath environments. The second is time-aligned buffering which enables TR to synchronize distributed transmitters into a collaborative array. This time alignment algorithm avoids causality violations through the use of reciprocal buffering. Preserving spatio-temporal reciprocity through the TR capture and retransmission process achieves coherent alignment across multiple radios at ~GHz carriers using only standard quartz-oscillators. COBRA has been demonstrated in the lab, aligning two off-the-shelf software defined radios over-the-air to an accuracy of better than 2 degrees of carrier alignment at 450 MHz. The COBRA algorithms are lightweight, with computation in 5 ms on a smartphone class microprocessor. COBRA also has low start-up latency, achieving high accuracy from a cold-start in 30 ms. The COBRA technique opens up a large number of new capabilities in communications, and electronic warfare including selective spatial jamming, geolocation and anti-geolocation.

Assessing artificial neural networks and statistical methods for infilling missing soil moisture records

NASA Astrophysics Data System (ADS)

Dumedah, Gift; Walker, Jeffrey P.; Chik, Li

2014-07-01

Soil moisture information is critically important for water management operations including flood forecasting, drought monitoring, and groundwater recharge estimation. While an accurate and continuous record of soil moisture is required for these applications, the available soil moisture data, in practice, is typically fraught with missing values. There are a wide range of methods available to infilling hydrologic variables, but a thorough inter-comparison between statistical methods and artificial neural networks has not been made. This study examines 5 statistical methods including monthly averages, weighted Pearson correlation coefficient, a method based on temporal stability of soil moisture, and a weighted merging of the three methods, together with a method based on the concept of rough sets. Additionally, 9 artificial neural networks are examined, broadly categorized into feedforward, dynamic, and radial basis networks. These 14 infilling methods were used to estimate missing soil moisture records and subsequently validated against known values for 13 soil moisture monitoring stations for three different soil layer depths in the Yanco region in southeast Australia. The evaluation results show that the top three highest performing methods are the nonlinear autoregressive neural network, rough sets method, and monthly replacement. A high estimation accuracy (root mean square error (RMSE) of about 0.03 m/m) was found in the nonlinear autoregressive network, due to its regression based dynamic network which allows feedback connections through discrete-time estimation. An equally high accuracy (0.05 m/m RMSE) in the rough sets procedure illustrates the important role of temporal persistence of soil moisture, with the capability to account for different soil moisture conditions.

Meta-analysis of stratus OCT glaucoma diagnostic accuracy.

PubMed

Chen, Hsin-Yi; Chang, Yue-Cune

2014-09-01

To evaluate the diagnostic accuracy of glaucoma in different stages, different types of glaucoma, and different ethnic groups using Stratus optical coherence tomography (OCT). We searched MEDLINE to identify available articles on diagnostic accuracy of glaucoma published between January 2004 and December 2011. A PubMed (National Center for Biotechnology Information) search using medical subject headings and keywords was executed using the following terms: "diagnostic accuracy" or "receiver operator characteristic" or "area under curve" or "AUC" and "Stratus OCT" and "glaucoma." The search was subsequently limited to publications in English. The area under a receiver operator characteristic (AUC) curve was used to measure the diagnostic performance. A random-effects model was used to estimate the pooled AUC value of the 17 parameters (average retinal nerve fiber layer thickness, temporal quadrant, superior quadrant, nasal quadrant, inferior quadrant, and 1 to 12 o'clock). Meta-regression analysis was used to check the significance of some important factors: (1) glaucoma severity (five stages), (2) glaucoma types (four types), and (3) ethnicity (four categories). The orders of accuracy among those parameters were as follows: average > inferior > superior > 7 o'clock > 6 o'clock > 11 o'clock > 12 o'clock > 1 o'clock > 5 o'clock > nasal > temporal > 2 o'clock > 10 o'clock > 8 o'clock > 9 o'clock > 4 o'clock > 3 o'clock. After adjusting for the effects of age, glaucoma severity, glaucoma types, and ethnicity, the average retinal nerve fiber layer thickness provided highest accuracy compared with the other parameters of OCT. The diagnostic accuracy in Asian populations was significantly lower than that in whites and the other two ethnic types. Stratus OCT demonstrated good diagnostic capability in differentiating glaucomatous from normal eyes. However, we should be more cautious in applying this instrument in Asian groups in glaucoma management.

Monitoring Coral Growth - the Dichotomy Between Underwater Photogrammetry and Geodetic Control Network

NASA Astrophysics Data System (ADS)

Neyer, F.; Nocerino, E.; Gruen, A.

2018-05-01

Creating 3-dimensional (3D) models of underwater scenes has become a common approach for monitoring coral reef changes and its structural complexity. Also in underwater archeology, 3D models are often created using underwater optical imagery. In this paper, we focus on the aspect of detecting small changes in the coral reef using a multi-temporal photogrammetric modelling approach, which requires a high quality control network. We show that the quality of a good geodetic network limits the direct change detection, i.e., without any further registration process. As the photogrammetric accuracy is expected to exceed the geodetic network accuracy by at least one order of magnitude, we suggest to do a fine registration based on a number of signalized points. This work is part of the Moorea Island Digital Ecosystem Avatar (IDEA) project that has been initiated in 2013 by a group of international researchers (https://mooreaidea.ethz.ch/).

Polychromatic wave-optics models for image-plane speckle. 2. Unresolved objects.

PubMed

Van Zandt, Noah R; Spencer, Mark F; Steinbock, Michael J; Anderson, Brian M; Hyde, Milo W; Fiorino, Steven T

2018-05-20

Polychromatic laser light can reduce speckle noise in many wavefront-sensing and imaging applications. To help quantify the achievable reduction in speckle noise, this study investigates the accuracy of three polychromatic wave-optics models under the specific conditions of an unresolved object. Because existing theory assumes a well-resolved object, laboratory experiments are used to evaluate model accuracy. The three models use Monte-Carlo averaging, depth slicing, and spectral slicing, respectively, to simulate the laser-object interaction. The experiments involve spoiling the temporal coherence of laser light via a fiber-based, electro-optic modulator. After the light scatters off of the rough object, speckle statistics are measured. The Monte-Carlo method is found to be highly inaccurate, while depth-slicing error peaks at 7.8% but is generally much lower in comparison. The spectral-slicing method is the most accurate, always producing results within the error bounds of the experiment.

Uav-Based Crops Classification with Joint Features from Orthoimage and Dsm Data

NASA Astrophysics Data System (ADS)

Liu, B.; Shi, Y.; Duan, Y.; Wu, W.

2018-04-01

Accurate crops classification remains a challenging task due to the same crop with different spectra and different crops with same spectrum phenomenon. Recently, UAV-based remote sensing approach gains popularity not only for its high spatial and temporal resolution, but also for its ability to obtain spectraand spatial data at the same time. This paper focus on how to take full advantages of spatial and spectrum features to improve crops classification accuracy, based on an UAV platform equipped with a general digital camera. Texture and spatial features extracted from the RGB orthoimage and the digital surface model of the monitoring area are analysed and integrated within a SVM classification framework. Extensive experiences results indicate that the overall classification accuracy is drastically improved from 72.9 % to 94.5 % when the spatial features are combined together, which verified the feasibility and effectiveness of the proposed method.

Telephone-quality pathological speech classification using empirical mode decomposition.

PubMed

Kaleem, M F; Ghoraani, B; Guergachi, A; Krishnan, S

2011-01-01

This paper presents a computationally simple and effective methodology based on empirical mode decomposition (EMD) for classification of telephone quality normal and pathological speech signals. EMD is used to decompose continuous normal and pathological speech signals into intrinsic mode functions, which are analyzed to extract physically meaningful and unique temporal and spectral features. Using continuous speech samples from a database of 51 normal and 161 pathological speakers, which has been modified to simulate telephone quality speech under different levels of noise, a linear classifier is used with the feature vector thus obtained to obtain a high classification accuracy, thereby demonstrating the effectiveness of the methodology. The classification accuracy reported in this paper (89.7% for signal-to-noise ratio 30 dB) is a significant improvement over previously reported results for the same task, and demonstrates the utility of our methodology for cost-effective remote voice pathology assessment over telephone channels.

The impact of conventional surface data upon VAS regression retrievals in the lower troposphere

NASA Technical Reports Server (NTRS)

Lee, T. H.; Chesters, D.; Mostek, A.

1983-01-01

Surface temperature and dewpoint reports are added to the infrared radiances from the VISSR Atmospheric Sounder (VAS) in order to improve the retrieval of temperature and moisture profiles in the lower troposphere. The conventional (airways) surface data are combined with the twelve VAS channels as additional predictors in a ridge regression retrieval scheme, with the aim of using all available data to make high resolution space-time interpolations of the radiosonde network. For one day of VAS observations, retrievals using only VAS radiances are compared with retrievals using VAS radiances plus surface data. Temperature retrieval accuracy evaluated at coincident radiosonde sites shows a significant impact within the boundary layer. Dewpoint retrieval accuracy shows a broader improvement within the lowest tropospheric layers. The most dramatic impact of surface data is observed in the improved relative spatial and temporal continuity of low-level fields retrieved over the Midwestern United States.

The Pierre Auger Observatory scaler mode for the study of solar activity modulation of galactic cosmic rays

NASA Astrophysics Data System (ADS)

Pierre Auger Collaboration; Abreu, P.; Aglietta, M.; Ahn, E. J.; Allard, D.; Allekotte, I.; Allen, J.; Alvarez Castillo, J.; Alvarez-Muñiz, J.; Ambrosio, M.; Aminaei, A.; Anchordoqui, L.; Andringa, S.; Antičić, T.; Anzalone, A.; Aramo, C.; Arganda, E.; Arisaka, K.; Arqueros, F.; Asorey, H.; Assis, P.; Aublin, J.; Ave, M.; Avenier, M.; Avila, G.; Bäcker, T.; Badagnani, D.; Balzer, M.; Barber, K. B.; Barbosa, A. F.; Bardenet, R.; Barroso, S. L. C.; Baughman, B.; Beatty, J. J.; Becker, B. R.; Becker, K. H.; Bellétoile, A.; Bellido, J. A.; BenZvi, S.; Berat, C.; Bergmann, T.; Bertou, X.; Biermann, P. L.; Billoir, P.; Blanco, F.; Blanco, M.; Bleve, C.; Blümer, H.; Boháčová, M.; Boncioli, D.; Bonifazi, C.; Bonino, R.; Borodai, N.; Brack, J.; Brogueira, P.; Brown, W. C.; Bruijn, R.; Buchholz, P.; Bueno, A.; Burton, R. E.; Busca, N. G.; Caballero-Mora, K. S.; Caramete, L.; Caruso, R.; Castellina, A.; Catalano, O.; Cataldi, G.; Cazon, L.; Cester, R.; Chauvin, J.; Chiavassa, A.; Chinellato, J. A.; Chou, A.; Chudoba, J.; Clay, R. W.; Colombo, E.; Coluccia, M. R.; Conceição, R.; Contreras, F.; Cook, H.; Cooper, M. J.; Coppens, J.; Cordier, A.; Cotti, U.; Coutu, S.; Covault, C. E.; Creusot, A.; Criss, A.; Cronin, J.; Curutiu, A.; Dagoret-Campagne, S.; Dallier, R.; Dasso, S.; Daumiller, K.; Dawson, B. R.; de Almeida, R. M.; De Domenico, M.; De Donato, C.; de Jong, S. J.; De La Vega, G.; de Mello Junior, W. J. M.; de Mello Neto, J. R. T.; De Mitri, I.; de Souza, V.; de Vries, K. D.; Decerprit, G.; del Peral, L.; Deligny, O.; Della Selva, A.; Dembinski, H.; Denkiewicz, A.; Di Giulio, C.; Diaz, J. C.; Díaz Castro, M. L.; Diep, P. N.; Dobrigkeit, C.; D'Olivo, J. C.; Dong, P. N.; Dorofeev, A.; dos Anjos, J. C.; Dova, M. T.; D'Urso, D.; Dutan, I.; Ebr, J.; Engel, R.; Erdmann, M.; Escobar, C. O.; Etchegoyen, A.; Facal San Luis, P.; Falcke, H.; Farrar, G.; Fauth, A. C.; Fazzini, N.; Ferguson, A. P.; Ferrero, A.; Fick, B.; Filevich, A.; Filipčič, A.; Fleck, I.; Fliescher, S.; Fracchiolla, C. E.; Fraenkel, E. D.; Fröhlich, U.; Fuchs, B.; Fulgione, W.; Gamarra, R. F.; Gambetta, S.; García, B.; García Gámez, D.; Garcia-Pinto, D.; Garrido, X.; Gascon, A.; Gelmini, G.; Gemmeke, H.; Gesterling, K.; Ghia, P. L.; Giaccari, U.; Giller, M.; Glass, H.; Gold, M. S.; Golup, G.; Gomez Albarracin, F.; Gómez Berisso, M.; Gonçalves, P.; Gonzalez, D.; Gonzalez, J. G.; Gookin, B.; Góra, D.; Gorgi, A.; Gouffon, P.; Gozzini, S. R.; Grashorn, E.; Grebe, S.; Grigat, M.; Grillo, A. F.; Guardincerri, Y.; Guarino, F.; Guedes, G. P.; Hague, J. D.; Hansen, P.; Harari, D.; Harmsma, S.; Harton, J. L.; Haungs, A.; Hebbeker, T.; Heck, D.; Herve, A. E.; Hojvat, C.; Holmes, V. C.; Homola, P.; Hórandel, J. R.; Horneffer, A.; Hrabovský, M.; Huege, T.; Insolia, A.; Ionita, F.; Italiano, A.; Jiraskova, S.; Kadija, K.; Kaducak, M.; Kampert, K. H.; Karhan, P.; Karova, T.; Kasper, P.; Kégl, B.; Keilhauer, B.; Keivani, A.; Kelley, J. L.; Kemp, E.; Kieckhafer, R. M.; Klages, H. O.; Kleifges, M.; Kleinfeller, J.; Knapp, J.; Koang, D.-H.; Kotera, K.; Krohm, N.; Krömer, O.; Kruppke-Hansen, D.; Kuehn, F.; Kuempel, D.; Kulbartz, J. K.; Kunka, N.; La Rosa, G.; Lachaud, C.; Lautridou, P.; Leão, M. S. A. B.; Lebrun, D.; Lebrun, P.; Leigui de Oliveira, M. A.; Lemiere, A.; Letessier-Selvon, A.; Lhenry-Yvon, I.; Link, K.; López, R.; Lopez Agüera, A.; Louedec, K.; Lozano Bahilo, J.; Lucero, A.; Ludwig, M.; Lyberis, H.; Maccarone, M. C.; Macolino, C.; Maldera, S.; Mandat, D.; Mantsch, P.; Mariazzi, A. G.; Marin, V.; Maris, I. C.; Marquez Falcon, H. R.; Marsella, G.; Martello, D.; Martin, L.; Martínez Bravo, O.; Mathes, H. J.; Matthews, J.; Matthews, J. A. J.; Matthiae, G.; Maurizio, D.; Mazur, P. O.; Medina-Tanco, G.; Melissas, M.; Melo, D.; Menichetti, E.; Menshikov, A.; Meurer, C.; Mičanović, S.; Micheletti, M. I.; Miller, W.; Miramonti, L.; Mollerach, S.; Monasor, M.; Monnier Ragaigne, D.; Montanet, F.; Morales, B.; Morello, C.; Moreno, E.; Moreno, J. C.; Morris, C.; Mostafá, M.; Mueller, S.; Muller, M. A.; Müller, G.; Münchmeyer, M.; Mussa, R.; Navarra, G.; Navarro, J. L.; Navas, S.; Necesal, P.; Nellen, L.; Nhung, P. T.; Nierstenhoefer, N.; Nitz, D.; Nosek, D.; Nožka, L.; Nyklicek, M.; Oehlschläger, J.; Olinto, A.; Oliva, P.; Olmos-Gilbaja, V. M.; Ortiz, M.; Pacheco, N.; Pakk Selmi-Dei, D.; Palatka, M.; Pallotta, J.; Palmieri, N.; Parente, G.; Parizot, E.; Parra, A.; Parrisius, J.; Parsons, R. D.; Pastor, S.; Paul, T.; Pavlidou c, V.; Payet, K.; Pech, M.; Pękala, J.; Pelayo, R.; Pepe, I. M.; Perrone, L.; Pesce, R.; Petermann, E.; Petrera, S.; Petrinca, P.; Petrolini, A.; Petrov, Y.; Petrovic, J.; Pfendner, C.; Phan, N.; Piegaia, R.; Pierog, T.; Pieroni, P.; Pimenta, M.; Pirronello, V.; Platino, M.; Ponce, V. H.; Pontz, M.; Privitera, P.; Prouza, M.; Quel, E. J.; Rautenberg, J.; Ravel, O.; Ravignani, D.; Revenu, B.; Ridky, J.; Riggi, S.; Risse, M.; Ristori, P.; Rivera, H.; Rivière, C.; Rizi, V.; Robledo, C.; Rodriguez, G.; Rodriguez Martino, J.; Rodriguez Rojo, J.; Rodriguez-Cabo, I.; Rodríguez-Frías, M. D.; Ros, G.; Rosado, J.; Rossler, T.; Roth, M.; Rouillé-d'Orfeuil, B.; Roulet, E.; Rovero, A. C.; Salamida, F.; Salazar, H.; Salina, G.; Sánchez, F.; Santander, M.; Santo, C. E.; Santos, E.; Santos, E. M.; Sarazin, F.; Sarkar, S.; Sato, R.; Scharf, N.; Scherini, V.; Schieler, H.; Schiffer, P.; Schmidt, A.; Schmidt, F.; Schmidt, T.; Scholten, O.; Schoorlemmer, H.; Schovancova, J.; Schovánek, P.; Schroeder, F.; Schulte, S.; Schüssler, F.; Schuster, D.; Sciutto, S. J.; Scuderi, M.; Segreto, A.; Semikoz, D.; Settimo, M.; Shadkam, A.; Shellard, R. C.; Sidelnik, I.; Sigl, G.; Śmiałkowski, A.; Šmída, R.; Snow, G. R.; Sommers, P.; Sorokin, J.; Spinka, H.; Squartini, R.; Stapleton, J.; Stasielak, J.; Stephan, M.; Strazzeri, E.; Stutz, A.; Suarez, F.; Suomijärvi, T.; Supanitsky, A. D.; Šuša, T.; Sutherland, M. S.; Swain, J.; Szadkowski, Z.; Tamashiro, A.; Tapia, A.; Tarutina, T.; Taşcǎu, O.; Tcaciuc, R.; Tcherniakhovski, D.; Tegolo, D.; Thao, N. T.; Thomas, D.; Tiffenberg, J.; Timmermans, C.; Tiwari, D. K.; Tkaczyk, W.; Todero Peixoto, C. J.; Tomé, B.; Tonachini, A.; Travnicek, P.; Tridapalli, D. B.; Tristram, G.; Trovato, E.; Tueros, M.; Ulrich, R.; Unger, M.; Urban, M.; Valdés Galicia, J. F.; Valiño, I.; Valore, L.; van den Berg, A. M.; Vargas Cárdenas, B.; Vázquez, J. R.; Vázquez, R. A.; Veberič, D.; Venters, T.; Verzi, V.; Videla, M.; Villaseñor, L.; Wahlberg, H.; Wahrlich, P.; Wainberg, O.; Warner, D.; Watson, A. A.; Weber, M.; Weidenhaupt, K.; Weindl, A.; Westerhoff, S.; Whelan, B. J.; Wieczorek, G.; Wiencke, L.; Wilczyńska, B.; Wilczyński, H.; Will, M.; Williams, C.; Winchen, T.; Winders, L.; Winnick, M. G.; Wommer, M.; Wundheiler, B.; Yamamoto a, T.; Younk, P.; Yuan, G.; Yushkov, A.; Zamorano, B.; Zas, E.; Zavrtanik, D.; Zavrtanik, M.; Zaw, I.; Zepeda, A.; Ziolkowski, M.

2011-01-01

Since data-taking began in January 2004, the Pierre Auger Observatory has been recording the count rates of low energy secondary cosmic ray particles for the self-calibration of the ground detectors of its surface detector array. After correcting for atmospheric effects, modulations of galactic cosmic rays due to solar activity and transient events are observed. Temporal variations related with the activity of the heliosphere can be determined with high accuracy due to the high total count rates. In this study, the available data are presented together with an analysis focused on the observation of Forbush decreases, where a strong correlation with neutron monitor data is found.

Wavelets and Elman Neural Networks for monitoring environmental variables

NASA Astrophysics Data System (ADS)

Ciarlini, Patrizia; Maniscalco, Umberto

2008-11-01

An application in cultural heritage is introduced. Wavelet decomposition and Neural Networks like virtual sensors are jointly used to simulate physical and chemical measurements in specific locations of a monument. Virtual sensors, suitably trained and tested, can substitute real sensors in monitoring the monument surface quality, while the real ones should be installed for a long time and at high costs. The application of the wavelet decomposition to the environmental data series allows getting the treatment of underlying temporal structure at low frequencies. Consequently a separate training of suitable Elman Neural Networks for high/low components can be performed, thus improving the networks convergence in learning time and measurement accuracy in working time.

Attentional awakening: gradual modulation of temporal attention in rapid serial visual presentation.

PubMed

Ariga, Atsunori; Yokosawa, Kazuhiko

2008-03-01

Orienting attention to a point in time facilitates processing of an item within rapidly changing surroundings. We used a one-target RSVP task to look for differences in accuracy in reporting a target related to when the target temporally appeared in the sequence. The results show that observers correctly report a target early in the sequence less frequently than later in the sequence. Previous RSVP studies predicted equivalently accurate performances for one target wherever it appeared in the sequence. We named this new phenomenon attentional awakening, which reflects a gradual modulation of temporal attention in a rapid sequence.

Spatial patterns of brain atrophy in MCI patients, identified via high-dimensional pattern classification, predict subsequent cognitive decline

PubMed Central

Fan, Yong; Batmanghelich, Nematollah; Clark, Chris M.; Davatzikos, Christos

2010-01-01

Spatial patterns of brain atrophy in mild cognitive impairment (MCI) and Alzheimer’s disease (AD) were measured via methods of computational neuroanatomy. These patterns were spatially complex and involved many brain regions. In addition to the hippocampus and the medial temporal lobe gray matter, a number of other regions displayed significant atrophy, including orbitofrontal and medial-prefrontal grey matter, cingulate (mainly posterior), insula, uncus, and temporal lobe white matter. Approximately 2/3 of the MCI group presented patterns of atrophy that overlapped with AD, whereas the remaining 1/3 overlapped with cognitively normal individuals, thereby indicating that some, but not all, MCI patients have significant and extensive brain atrophy in this cohort of MCI patients. Importantly, the group with AD-like patterns presented much higher rate of MMSE decline in follow-up visits; conversely, pattern classification provided relatively high classification accuracy (87%) of the individuals that presented relatively higher MMSE decline within a year from baseline. High-dimensional pattern classification, a nonlinear multivariate analysis, provided measures of structural abnormality that can potentially be useful for individual patient classification, as well as for predicting progression and examining multivariate relationships in group analyses. PMID:18053747

Combining accuracy assessment of land-cover maps with environmental monitoring programs

USGS Publications Warehouse

Stehman, S.V.; Czaplewski, R.L.; Nusser, S.M.; Yang, L.; Zhu, Z.

2000-01-01

A scientifically valid accuracy assessment of a large-area, land-cover map is expensive. Environmental monitoring programs offer a potential source of data to partially defray the cost of accuracy assessment while still maintaining the statistical validity. In this article, three general strategies for combining accuracy assessment and environmental monitoring protocols are described. These strategies range from a fully integrated accuracy assessment and environmental monitoring protocol, to one in which the protocols operate nearly independently. For all three strategies, features critical to using monitoring data for accuracy assessment include compatibility of the land-cover classification schemes, precisely co-registered sample data, and spatial and temporal compatibility of the map and reference data. Two monitoring programs, the National Resources Inventory (NRI) and the Forest Inventory and Monitoring (FIM), are used to illustrate important features for implementing a combined protocol.

A high-order gas-kinetic Navier-Stokes flow solver

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li Qibing, E-mail: lqb@tsinghua.edu.c; Xu Kun, E-mail: makxu@ust.h; Fu Song, E-mail: fs-dem@tsinghua.edu.c

2010-09-20

The foundation for the development of modern compressible flow solver is based on the Riemann solution of the inviscid Euler equations. The high-order schemes are basically related to high-order spatial interpolation or reconstruction. In order to overcome the low-order wave interaction mechanism due to the Riemann solution, the temporal accuracy of the scheme can be improved through the Runge-Kutta method, where the dynamic deficiencies in the first-order Riemann solution is alleviated through the sub-step spatial reconstruction in the Runge-Kutta process. The close coupling between the spatial and temporal evolution in the original nonlinear governing equations seems weakened due to itsmore » spatial and temporal decoupling. Many recently developed high-order methods require a Navier-Stokes flux function under piece-wise discontinuous high-order initial reconstruction. However, the piece-wise discontinuous initial data and the hyperbolic-parabolic nature of the Navier-Stokes equations seem inconsistent mathematically, such as the divergence of the viscous and heat conducting terms due to initial discontinuity. In this paper, based on the Boltzmann equation, we are going to present a time-dependent flux function from a high-order discontinuous reconstruction. The theoretical basis for such an approach is due to the fact that the Boltzmann equation has no specific requirement on the smoothness of the initial data and the kinetic equation has the mechanism to construct a dissipative wave structure starting from an initially discontinuous flow condition on a time scale being larger than the particle collision time. The current high-order flux evaluation method is an extension of the second-order gas-kinetic BGK scheme for the Navier-Stokes equations (BGK-NS). The novelty for the easy extension from a second-order to a higher order is due to the simple particle transport and collision mechanism on the microscopic level. This paper will present a hierarchy to construct such a high-order method. The necessity to couple spatial and temporal evolution nonlinearly in the flux evaluation can be clearly observed through the numerical performance of the scheme for the viscous flow computations.« less

Multivariate pattern analysis reveals anatomical connectivity differences between the left and right mesial temporal lobe epilepsy.

PubMed

Fang, Peng; An, Jie; Zeng, Ling-Li; Shen, Hui; Chen, Fanglin; Wang, Wensheng; Qiu, Shijun; Hu, Dewen

2015-01-01

Previous studies have demonstrated differences of clinical signs and functional brain network organizations between the left and right mesial temporal lobe epilepsy (mTLE), but the anatomical connectivity differences underlying functional variance between the left and right mTLE remain uncharacterized. We examined 43 (22 left, 21 right) mTLE patients with hippocampal sclerosis and 39 healthy controls using diffusion tensor imaging. After the whole-brain anatomical networks were constructed for each subject, multivariate pattern analysis was applied to classify the left mTLE from the right mTLE and extract the anatomical connectivity differences between the left and right mTLE patients. The classification results reveal 93.0% accuracy for the left mTLE versus the right mTLE, 93.4% accuracy for the left mTLE versus controls and 90.0% accuracy for the right mTLE versus controls. Compared with the right mTLE, the left mTLE exhibited a different connectivity pattern in the cortical-limbic network and cerebellum. The majority of the most discriminating anatomical connections were located within or across the cortical-limbic network and cerebellum, thereby indicating that these disease-related anatomical network alterations may give rise to a portion of the complex of emotional and memory deficit between the left and right mTLE. Moreover, the orbitofrontal gyrus, cingulate cortex, hippocampus and parahippocampal gyrus, which exhibit high discriminative power in classification, may play critical roles in the pathophysiology of mTLE. The current study demonstrated that anatomical connectivity differences between the left mTLE and the right mTLE may have the potential to serve as a neuroimaging biomarker to guide personalized diagnosis of the left and right mTLE.

Temporal lobe epilepsy: quantitative MR volumetry in detection of hippocampal atrophy.

PubMed

Farid, Nikdokht; Girard, Holly M; Kemmotsu, Nobuko; Smith, Michael E; Magda, Sebastian W; Lim, Wei Y; Lee, Roland R; McDonald, Carrie R

2012-08-01

To determine the ability of fully automated volumetric magnetic resonance (MR) imaging to depict hippocampal atrophy (HA) and to help correctly lateralize the seizure focus in patients with temporal lobe epilepsy (TLE). This study was conducted with institutional review board approval and in compliance with HIPAA regulations. Volumetric MR imaging data were analyzed for 34 patients with TLE and 116 control subjects. Structural volumes were calculated by using U.S. Food and Drug Administration-cleared software for automated quantitative MR imaging analysis (NeuroQuant). Results of quantitative MR imaging were compared with visual detection of atrophy, and, when available, with histologic specimens. Receiver operating characteristic analyses were performed to determine the optimal sensitivity and specificity of quantitative MR imaging for detecting HA and asymmetry. A linear classifier with cross validation was used to estimate the ability of quantitative MR imaging to help lateralize the seizure focus. Quantitative MR imaging-derived hippocampal asymmetries discriminated patients with TLE from control subjects with high sensitivity (86.7%-89.5%) and specificity (92.2%-94.1%). When a linear classifier was used to discriminate left versus right TLE, hippocampal asymmetry achieved 94% classification accuracy. Volumetric asymmetries of other subcortical structures did not improve classification. Compared with invasive video electroencephalographic recordings, lateralization accuracy was 88% with quantitative MR imaging and 85% with visual inspection of volumetric MR imaging studies but only 76% with visual inspection of clinical MR imaging studies. Quantitative MR imaging can depict the presence and laterality of HA in TLE with accuracy rates that may exceed those achieved with visual inspection of clinical MR imaging studies. Thus, quantitative MR imaging may enhance standard visual analysis, providing a useful and viable means for translating volumetric analysis into clinical practice.

Forest Area Derivation from SENTINEL-1 Data

NASA Astrophysics Data System (ADS)

Dostálová, Alena; Hollaus, Markus; Milenković, Milutin; Wagner, Wolfgang

2016-06-01

The recently launched Sentinel-1A provides the high resolution Synthetic Aperture Radar (SAR) data with very high temporal coverage over large parts of European continent. Short revisit time and dual polarization availability supports its usability for forestry applications. The following study presents an analysis of the potential of the multi-temporal dual-polarization Sentinel-1A data for the forest area derivation using the standard methods based on Otsu thresholding and K-means clustering. Sentinel-1 data collected in winter season 2014-2015 over a test area in eastern Austria were used to derive forest area mask with spatial resolution of 10m and minimum mapping unit of 500 m2. The validation with reference forest mask derived from airborne full-waveform laser scanning data revealed overall accuracy of 92 % and kappa statistics of 0.81. Even better results can be achieved when using external mask for urban areas, which might be misclassified as forests when using the introduced approach based on SAR data only. The Sentinel-1 data and the described methods are well suited for forest change detection between consecutive years.

Prolongation of SMAP to Spatio-temporally Seamless Coverage of Continental US Using a Deep Learning Neural Network

NASA Astrophysics Data System (ADS)

Fang, K.; Shen, C.; Kifer, D.; Yang, X.

2017-12-01

The Soil Moisture Active Passive (SMAP) mission has delivered high-quality and valuable sensing of surface soil moisture since 2015. However, its short time span, coarse resolution, and irregular revisit schedule have limited its use. Utilizing a state-of-the-art deep-in-time neural network, Long Short-Term Memory (LSTM), we created a system that predicts SMAP level-3 soil moisture data using climate forcing, model-simulated moisture, and static physical attributes as inputs. The system removes most of the bias with model simulations and also improves predicted moisture climatology, achieving a testing accuracy of 0.025 to 0.03 in most parts of Continental United States (CONUS). As the first application of LSTM in hydrology, we show that it is more robust than simpler methods in either temporal or spatial extrapolation tests. We also discuss roles of different predictors, the effectiveness of regularization algorithms and impacts of training strategies. With high fidelity to SMAP products, our data can aid various applications including data assimilation, weather forecasting, and soil moisture hindcasting.

Quantifying multi-temporal urban development characteristics in Las Vegas from Landsat and ASTER data

USGS Publications Warehouse

Xian, G.; Crane, M.; McMahon, C.

2008-01-01

Urban development has expanded rapidly in Las Vegas, Nevada of the United States, over the last fifty years. A major environmental change associated with this urbanization trend is the transformation of the landscape from natural cover types to increasingly anthropogenic impervious surface. This research utilizes remote sensing data from both the Landsat and Terra-Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) instruments in conjunction with digital orthophotography to estimate urban extent and its temporal changes by determining sub-pixel impervious surfaces. Percent impervious surface area has shown encouraging agreement with urban land extent and development density. Results indicate that total urban land-use increases approximately 110 percent from 1984 to 2002. Most of the increases are associated with medium-to high-density urban development. Places having significant increases in impervious surfaces are in the northwestern and southeastern parts of Las Vegas. Most high-density urban development, however, appears in central Las Vegas. Impervious surface conditions for 2002 measured from Landsat and ASTER satellite data are compared in terms of their accuracy.

Quantitative imaging of single-shot liquid distributions in sprays using broadband flash x-ray radiography

DOE Office of Scientific and Technical Information (OSTI.GOV)

Halls, B. R.; Roy, S.; Gord, J. R.

Flash x-ray radiography is used to capture quantitative, two-dimensional line-of-sight averaged, single-shot liquid distribution measurements in impinging jet sprays. The accuracy of utilizing broadband x-ray radiation from compact flash tube sources is investigated for a range of conditions by comparing the data with radiographic high-speed measurements from a narrowband, high-intensity synchrotron x-ray facility at the Advanced Photon Source (APS) of Argonne National Laboratory. The path length of the liquid jets is varied to evaluate the effects of energy dependent x-ray attenuation, also known as spectral beam hardening. The spatial liquid distributions from flash x-ray and synchrotron-based radiography are compared, alongmore » with spectral characteristics using Taylor’s hypothesis. The results indicate that quantitative, single-shot imaging of liquid distributions can be achieved using broadband x-ray sources with nanosecond temporal resolution. Practical considerations for optimizing the imaging system performance are discussed, including the coupled effects of x-ray bandwidth, contrast, sensitivity, spatial resolution, temporal resolution, and spectral beam hardening.« less

Validating MODIS and Sentinel-2 NDVI Products at a Temperate Deciduous Forest Site Using Two Independent Ground-Based Sensors.

PubMed

Lange, Maximilian; Dechant, Benjamin; Rebmann, Corinna; Vohland, Michael; Cuntz, Matthias; Doktor, Daniel

2017-08-11

Quantifying the accuracy of remote sensing products is a timely endeavor given the rapid increase in Earth observation missions. A validation site for Sentinel-2 products was hence established in central Germany. Automatic multispectral and hyperspectral sensor systems were installed in parallel with an existing eddy covariance flux tower, providing spectral information of the vegetation present at high temporal resolution. Normalized Difference Vegetation Index (NDVI) values from ground-based hyperspectral and multispectral sensors were compared with NDVI products derived from Sentinel-2A and Moderate-resolution Imaging Spectroradiometer (MODIS). The influence of different spatial and temporal resolutions was assessed. High correlations and similar phenological patterns between in situ and satellite-based NDVI time series demonstrated the reliability of satellite-based phenological metrics. Sentinel-2-derived metrics showed better agreement with in situ measurements than MODIS-derived metrics. Dynamic filtering with the best index slope extraction algorithm was nevertheless beneficial for Sentinel-2 NDVI time series despite the availability of quality information from the atmospheric correction procedure.

Validating MODIS and Sentinel-2 NDVI Products at a Temperate Deciduous Forest Site Using Two Independent Ground-Based Sensors

PubMed Central

Lange, Maximilian; Rebmann, Corinna; Cuntz, Matthias; Doktor, Daniel

2017-01-01

Quantifying the accuracy of remote sensing products is a timely endeavor given the rapid increase in Earth observation missions. A validation site for Sentinel-2 products was hence established in central Germany. Automatic multispectral and hyperspectral sensor systems were installed in parallel with an existing eddy covariance flux tower, providing spectral information of the vegetation present at high temporal resolution. Normalized Difference Vegetation Index (NDVI) values from ground-based hyperspectral and multispectral sensors were compared with NDVI products derived from Sentinel-2A and Moderate-resolution Imaging Spectroradiometer (MODIS). The influence of different spatial and temporal resolutions was assessed. High correlations and similar phenological patterns between in situ and satellite-based NDVI time series demonstrated the reliability of satellite-based phenological metrics. Sentinel-2-derived metrics showed better agreement with in situ measurements than MODIS-derived metrics. Dynamic filtering with the best index slope extraction algorithm was nevertheless beneficial for Sentinel-2 NDVI time series despite the availability of quality information from the atmospheric correction procedure. PMID:28800065

Treatment for Alexia With Agraphia Following Left Ventral Occipito-Temporal Damage: Strengthening Orthographic Representations Common to Reading and Spelling

PubMed Central

Rising, Kindle; Rapcsak, Steven Z.; Beeson, Pélagie M.

2015-01-01

Purpose Damage to left ventral occipito-temporal cortex can give rise to written language impairment characterized by pure alexia/letter-by-letter (LBL) reading, as well as surface alexia and agraphia. The purpose of this study was to examine the therapeutic effects of a combined treatment approach to address concurrent LBL reading with surface alexia/agraphia. Method Simultaneous treatment to address slow reading and errorful spelling was administered to 3 individuals with reading and spelling impairments after left ventral occipito-temporal damage due to posterior cerebral artery stroke. Single-word reading/spelling accuracy, reading latencies, and text reading were monitored as outcome measures for the combined effects of multiple oral re-reading treatment and interactive spelling treatment. Results After treatment, participants demonstrated faster and more accurate single-word reading and improved text-reading rates. Spelling accuracy also improved, particularly for untrained irregular words, demonstrating generalization of the trained interactive spelling strategy. Conclusion This case series characterizes concomitant LBL with surface alexia/agraphia and demonstrates a successful treatment approach to address both the reading and spelling impairment. PMID:26110814

Treatment for Alexia With Agraphia Following Left Ventral Occipito-Temporal Damage: Strengthening Orthographic Representations Common to Reading and Spelling.

PubMed

Kim, Esther S; Rising, Kindle; Rapcsak, Steven Z; Beeson, Pélagie M

2015-10-01

Damage to left ventral occipito-temporal cortex can give rise to written language impairment characterized by pure alexia/letter-by-letter (LBL) reading, as well as surface alexia and agraphia. The purpose of this study was to examine the therapeutic effects of a combined treatment approach to address concurrent LBL reading with surface alexia/agraphia. Simultaneous treatment to address slow reading and errorful spelling was administered to 3 individuals with reading and spelling impairments after left ventral occipito-temporal damage due to posterior cerebral artery stroke. Single-word reading/spelling accuracy, reading latencies, and text reading were monitored as outcome measures for the combined effects of multiple oral re-reading treatment and interactive spelling treatment. After treatment, participants demonstrated faster and more accurate single-word reading and improved text-reading rates. Spelling accuracy also improved, particularly for untrained irregular words, demonstrating generalization of the trained interactive spelling strategy. This case series characterizes concomitant LBL with surface alexia/agraphia and demonstrates a successful treatment approach to address both the reading and spelling impairment.

Extracting the Textual and Temporal Structure of Supercomputing Logs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jain, S; Singh, I; Chandra, A

2009-05-26

Supercomputers are prone to frequent faults that adversely affect their performance, reliability and functionality. System logs collected on these systems are a valuable resource of information about their operational status and health. However, their massive size, complexity, and lack of standard format makes it difficult to automatically extract information that can be used to improve system management. In this work we propose a novel method to succinctly represent the contents of supercomputing logs, by using textual clustering to automatically find the syntactic structures of log messages. This information is used to automatically classify messages into semantic groups via an onlinemore » clustering algorithm. Further, we describe a methodology for using the temporal proximity between groups of log messages to identify correlated events in the system. We apply our proposed methods to two large, publicly available supercomputing logs and show that our technique features nearly perfect accuracy for online log-classification and extracts meaningful structural and temporal message patterns that can be used to improve the accuracy of other log analysis techniques.« less

Multitemporal Accuracy and Precision Assessment of Unmanned Aerial System Photogrammetry for Slope-Scale Snow Depth Maps in Alpine Terrain

NASA Astrophysics Data System (ADS)

Adams, Marc S.; Bühler, Yves; Fromm, Reinhard

2017-12-01

Reliable and timely information on the spatio-temporal distribution of snow in alpine terrain plays an important role for a wide range of applications. Unmanned aerial system (UAS) photogrammetry is increasingly applied to cost-efficiently map the snow depth at very high resolution with flexible applicability. However, crucial questions regarding quality and repeatability of this technique are still under discussion. Here we present a multitemporal accuracy and precision assessment of UAS photogrammetry for snow depth mapping on the slope-scale. We mapped a 0.12 km2 large snow-covered study site, located in a high-alpine valley in Western Austria. 12 UAS flights were performed to acquire imagery at 0.05 m ground sampling distance in visible (VIS) and near-infrared (NIR) wavelengths with a modified commercial, off-the-shelf sensor mounted on a custom-built fixed-wing UAS. The imagery was processed with structure-from-motion photogrammetry software to generate orthophotos, digital surface models (DSMs) and snow depth maps (SDMs). Accuracy of DSMs and SDMs were assessed with terrestrial laser scanning and manual snow depth probing, respectively. The results show that under good illumination conditions (study site in full sunlight), the DSMs and SDMs were acquired with an accuracy of ≤ 0.25 and ≤ 0.29 m (both at 1σ), respectively. In case of poorly illuminated snow surfaces (study site shadowed), the NIR imagery provided higher accuracy (0.19 m; 0.23 m) than VIS imagery (0.49 m; 0.37 m). The precision of the UASSDMs was 0.04 m for a small, stable area and below 0.33 m for the whole study site (both at 1σ).

Application of a temporal reasoning framework tool in analysis of medical device adverse events.

PubMed

Clark, Kimberly K; Sharma, Deepak K; Chute, Christopher G; Tao, Cui

2011-01-01

The Clinical Narrative Temporal Relation Ontology (CNTRO)1 project offers a semantic-web based reasoning framework, which represents temporal events and relationships within clinical narrative texts, and infer new knowledge over them. In this paper, the CNTRO reasoning framework is applied to temporal analysis of medical device adverse event files. One specific adverse event was used as a test case: late stent thrombosis. Adverse event narratives were obtained from the Food and Drug Administration's (FDA) Manufacturing and User Facility Device Experience (MAUDE) database2. 15 adverse event files in which late stent thrombosis was confirmed were randomly selected across multiple drug eluting stent devices. From these files, 81 events and 72 temporal relations were annotated. 73 temporal questions were generated, of which 65 were correctly answered by the CNTRO system. This results in an overall accuracy of 89%. This system should be pursued further to continue assessing its potential benefits in temporal analysis of medical device adverse events.

Multiscale high-order/low-order (HOLO) algorithms and applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chacon, Luis; Chen, Guangye; Knoll, Dana Alan

Here, we review the state of the art in the formulation, implementation, and performance of so-called high-order/low-order (HOLO) algorithms for challenging multiscale problems. HOLO algorithms attempt to couple one or several high-complexity physical models (the high-order model, HO) with low-complexity ones (the low-order model, LO). The primary goal of HOLO algorithms is to achieve nonlinear convergence between HO and LO components while minimizing memory footprint and managing the computational complexity in a practical manner. Key to the HOLO approach is the use of the LO representations to address temporal stiffness, effectively accelerating the convergence of the HO/LO coupled system. Themore » HOLO approach is broadly underpinned by the concept of nonlinear elimination, which enables segregation of the HO and LO components in ways that can effectively use heterogeneous architectures. The accuracy and efficiency benefits of HOLO algorithms are demonstrated with specific applications to radiation transport, gas dynamics, plasmas (both Eulerian and Lagrangian formulations), and ocean modeling. Across this broad application spectrum, HOLO algorithms achieve significant accuracy improvements at a fraction of the cost compared to conventional approaches. It follows that HOLO algorithms hold significant potential for high-fidelity system scale multiscale simulations leveraging exascale computing.« less

Multiscale high-order/low-order (HOLO) algorithms and applications

DOE PAGES

Chacon, Luis; Chen, Guangye; Knoll, Dana Alan; ...

2016-11-11

Here, we review the state of the art in the formulation, implementation, and performance of so-called high-order/low-order (HOLO) algorithms for challenging multiscale problems. HOLO algorithms attempt to couple one or several high-complexity physical models (the high-order model, HO) with low-complexity ones (the low-order model, LO). The primary goal of HOLO algorithms is to achieve nonlinear convergence between HO and LO components while minimizing memory footprint and managing the computational complexity in a practical manner. Key to the HOLO approach is the use of the LO representations to address temporal stiffness, effectively accelerating the convergence of the HO/LO coupled system. Themore » HOLO approach is broadly underpinned by the concept of nonlinear elimination, which enables segregation of the HO and LO components in ways that can effectively use heterogeneous architectures. The accuracy and efficiency benefits of HOLO algorithms are demonstrated with specific applications to radiation transport, gas dynamics, plasmas (both Eulerian and Lagrangian formulations), and ocean modeling. Across this broad application spectrum, HOLO algorithms achieve significant accuracy improvements at a fraction of the cost compared to conventional approaches. It follows that HOLO algorithms hold significant potential for high-fidelity system scale multiscale simulations leveraging exascale computing.« less

Feature Selection Methods for Zero-Shot Learning of Neural Activity.

PubMed

Caceres, Carlos A; Roos, Matthew J; Rupp, Kyle M; Milsap, Griffin; Crone, Nathan E; Wolmetz, Michael E; Ratto, Christopher R

2017-01-01

Dimensionality poses a serious challenge when making predictions from human neuroimaging data. Across imaging modalities, large pools of potential neural features (e.g., responses from particular voxels, electrodes, and temporal windows) have to be related to typically limited sets of stimuli and samples. In recent years, zero-shot prediction models have been introduced for mapping between neural signals and semantic attributes, which allows for classification of stimulus classes not explicitly included in the training set. While choices about feature selection can have a substantial impact when closed-set accuracy, open-set robustness, and runtime are competing design objectives, no systematic study of feature selection for these models has been reported. Instead, a relatively straightforward feature stability approach has been adopted and successfully applied across models and imaging modalities. To characterize the tradeoffs in feature selection for zero-shot learning, we compared correlation-based stability to several other feature selection techniques on comparable data sets from two distinct imaging modalities: functional Magnetic Resonance Imaging and Electrocorticography. While most of the feature selection methods resulted in similar zero-shot prediction accuracies and spatial/spectral patterns of selected features, there was one exception; A novel feature/attribute correlation approach was able to achieve those accuracies with far fewer features, suggesting the potential for simpler prediction models that yield high zero-shot classification accuracy.

Measuring Blood Glucose Concentrations in Photometric Glucometers Requiring Very Small Sample Volumes.

PubMed

Demitri, Nevine; Zoubir, Abdelhak M

2017-01-01

Glucometers present an important self-monitoring tool for diabetes patients and, therefore, must exhibit high accuracy as well as good usability features. Based on an invasive photometric measurement principle that drastically reduces the volume of the blood sample needed from the patient, we present a framework that is capable of dealing with small blood samples, while maintaining the required accuracy. The framework consists of two major parts: 1) image segmentation; and 2) convergence detection. Step 1 is based on iterative mode-seeking methods to estimate the intensity value of the region of interest. We present several variations of these methods and give theoretical proofs of their convergence. Our approach is able to deal with changes in the number and position of clusters without any prior knowledge. Furthermore, we propose a method based on sparse approximation to decrease the computational load, while maintaining accuracy. Step 2 is achieved by employing temporal tracking and prediction, herewith decreasing the measurement time, and, thus, improving usability. Our framework is tested on several real datasets with different characteristics. We show that we are able to estimate the underlying glucose concentration from much smaller blood samples than is currently state of the art with sufficient accuracy according to the most recent ISO standards and reduce measurement time significantly compared to state-of-the-art methods.

Species classification using Unmanned Aerial Vehicle (UAV)-acquired high spatial resolution imagery in a heterogeneous grassland

NASA Astrophysics Data System (ADS)

Lu, Bing; He, Yuhong

2017-06-01

Investigating spatio-temporal variations of species composition in grassland is an essential step in evaluating grassland health conditions, understanding the evolutionary processes of the local ecosystem, and developing grassland management strategies. Space-borne remote sensing images (e.g., MODIS, Landsat, and Quickbird) with spatial resolutions varying from less than 1 m to 500 m have been widely applied for vegetation species classification at spatial scales from community to regional levels. However, the spatial resolutions of these images are not fine enough to investigate grassland species composition, since grass species are generally small in size and highly mixed, and vegetation cover is greatly heterogeneous. Unmanned Aerial Vehicle (UAV) as an emerging remote sensing platform offers a unique ability to acquire imagery at very high spatial resolution (centimetres). Compared to satellites or airplanes, UAVs can be deployed quickly and repeatedly, and are less limited by weather conditions, facilitating advantageous temporal studies. In this study, we utilize an octocopter, on which we mounted a modified digital camera (with near-infrared (NIR), green, and blue bands), to investigate species composition in a tall grassland in Ontario, Canada. Seven flight missions were conducted during the growing season (April to December) in 2015 to detect seasonal variations, and four of them were selected in this study to investigate the spatio-temporal variations of species composition. To quantitatively compare images acquired at different times, we establish a processing flow of UAV-acquired imagery, focusing on imagery quality evaluation and radiometric correction. The corrected imagery is then applied to an object-based species classification. Maps of species distribution are subsequently used for a spatio-temporal change analysis. Results indicate that UAV-acquired imagery is an incomparable data source for studying fine-scale grassland species composition, owing to its high spatial resolution. The overall accuracy is around 85% for images acquired at different times. Species composition is spatially attributed by topographical features and soil moisture conditions. Spatio-temporal variation of species composition implies the growing process and succession of different species, which is critical for understanding the evolutionary features of grassland ecosystems. Strengths and challenges of applying UAV-acquired imagery for vegetation studies are summarized at the end.

Mapping grass communities based on multi-temporal Landsat TM imagery and environmental variables

NASA Astrophysics Data System (ADS)

Zeng, Yuandi; Liu, Yanfang; Liu, Yaolin; de Leeuw, Jan

2007-06-01

Information on the spatial distribution of grass communities in wetland is increasingly recognized as important for effective wetland management and biological conservation. Remote sensing techniques has been proved to be an effective alternative to intensive and costly ground surveys for mapping grass community. However, the mapping accuracy of grass communities in wetland is still not preferable. The aim of this paper is to develop an effective method to map grass communities in Poyang Lake Natural Reserve. Through statistic analysis, elevation is selected as an environmental variable for its high relationship with the distribution of grass communities; NDVI stacked from images of different months was used to generate Carex community map; the image in October was used to discriminate Miscanthus and Cynodon communities. Classifications were firstly performed with maximum likelihood classifier using single date satellite image with and without elevation; then layered classifications were performed using multi-temporal satellite imagery and elevation with maximum likelihood classifier, decision tree and artificial neural network separately. The results show that environmental variables can improve the mapping accuracy; and the classification with multitemporal imagery and elevation is significantly better than that with single date image and elevation (p=0.001). Besides, maximum likelihood (a=92.71%, k=0.90) and artificial neural network (a=94.79%, k=0.93) perform significantly better than decision tree (a=86.46%, k=0.83).

Cropland Area Extraction in China with Multi-Temporal MODIS Data

NASA Astrophysics Data System (ADS)

Bagan, H.; Baruah, P. J.; Wang, Q.; Yasuoka, Y.

2007-12-01

: extracting the area of cropland in China is very important for agricultural management, land degradation and ecosystem assessment. In this study we investigate the potential and the methodology for the cropland area extraction using multi-temporal MODIS EVI data and some ancillary data. A 16-day composite EVI time-series data for 2003 (6 March 2003 - 2 December 2003) with a spatial resolution of 500 m, and the ancillary data included Land-use GIS data, Landsat TM/ETM, ASTER data, and county-level cultivated land statistical data of year 2000. The Self-Organizing Map (SOM) neural network classification algorithm was applied to the EVI data set. To focus on agricultural and desertification, we designed 9 land-cover types: 1) water, 2) woodland, 3) grassland, 4) dry cropland, 5) sandy, 6) paddy, 7) wetland, 8) urban/bare, and 9) snow/ice. The overall classification accuracy was 85% with a kappa coefficient of 0.84. The EVI data sets were sensitive and performed well in distinguishing the majority of land cover types. We also used county-level cultivated land statistical data from the year 2000 to evaluate the accuracy of the agricultural area from classification results, and found that the correlation coefficient was high in most counties. The result of this study shows that the methodology used in this study is, in general, feasible for cropland extraction in China. Keywords: MODIS, EVI, SOM, Cropland, land cover.

Sub-pixel flood inundation mapping from multispectral remotely sensed images based on discrete particle swarm optimization

NASA Astrophysics Data System (ADS)

Li, Linyi; Chen, Yun; Yu, Xin; Liu, Rui; Huang, Chang

2015-03-01

The study of flood inundation is significant to human life and social economy. Remote sensing technology has provided an effective way to study the spatial and temporal characteristics of inundation. Remotely sensed images with high temporal resolutions are widely used in mapping inundation. However, mixed pixels do exist due to their relatively low spatial resolutions. One of the most popular approaches to resolve this issue is sub-pixel mapping. In this paper, a novel discrete particle swarm optimization (DPSO) based sub-pixel flood inundation mapping (DPSO-SFIM) method is proposed to achieve an improved accuracy in mapping inundation at a sub-pixel scale. The evaluation criterion for sub-pixel inundation mapping is formulated. The DPSO-SFIM algorithm is developed, including particle discrete encoding, fitness function designing and swarm search strategy. The accuracy of DPSO-SFIM in mapping inundation at a sub-pixel scale was evaluated using Landsat ETM + images from study areas in Australia and China. The results show that DPSO-SFIM consistently outperformed the four traditional SFIM methods in these study areas. A sensitivity analysis of DPSO-SFIM was also carried out to evaluate its performances. It is hoped that the results of this study will enhance the application of medium-low spatial resolution images in inundation detection and mapping, and thereby support the ecological and environmental studies of river basins.

Optimal acquisition and modeling parameters for accurate assessment of low Ktrans blood-brain barrier permeability using dynamic contrast-enhanced MRI.

PubMed

Barnes, Samuel R; Ng, Thomas S C; Montagne, Axel; Law, Meng; Zlokovic, Berislav V; Jacobs, Russell E

2016-05-01

To determine optimal parameters for acquisition and processing of dynamic contrast-enhanced MRI (DCE-MRI) to detect small changes in near normal low blood-brain barrier (BBB) permeability. Using a contrast-to-noise ratio metric (K-CNR) for Ktrans precision and accuracy, the effects of kinetic model selection, scan duration, temporal resolution, signal drift, and length of baseline on the estimation of low permeability values was evaluated with simulations. The Patlak model was shown to give the highest K-CNR at low Ktrans . The Ktrans transition point, above which other models yielded superior results, was highly dependent on scan duration and tissue extravascular extracellular volume fraction (ve ). The highest K-CNR for low Ktrans was obtained when Patlak model analysis was combined with long scan times (10-30 min), modest temporal resolution (<60 s/image), and long baseline scans (1-4 min). Signal drift as low as 3% was shown to affect the accuracy of Ktrans estimation with Patlak analysis. DCE acquisition and modeling parameters are interdependent and should be optimized together for the tissue being imaged. Appropriately optimized protocols can detect even the subtlest changes in BBB integrity and may be used to probe the earliest changes in neurodegenerative diseases such as Alzheimer's disease and multiple sclerosis. © 2015 Wiley Periodicals, Inc.

Implementation of a global-scale operational data assimilation system for satellite-based soil moisture retrievals

NASA Astrophysics Data System (ADS)

Bolten, J.; Crow, W.; Zhan, X.; Reynolds, C.

2008-08-01

Timely and accurate monitoring of global weather anomalies and drought conditions is essential for assessing global crop conditions. Soil moisture observations are particularly important for crop yield fluctuations provided by the US Department of Agriculture (USDA) Production Estimation and Crop Assessment Division (PECAD). The current system utilized by PECAD estimates soil moisture from a 2-layer water balance model based on precipitation and temperature data from World Meteorological Organization (WMO) and US Air Force Weather Agency (AFWA). The accuracy of this system is highly dependent on the data sources used; particularly the accuracy, consistency, and spatial and temporal coverage of the land and climatic data input into the models. However, many regions of the globe lack observations at the temporal and spatial resolutions required by PECAD. This study incorporates NASA's soil moisture remote sensing product provided by the EOS Advanced Microwave Scanning Radiometer (AMSR-E) into the U.S. Department of Agriculture Crop Assessment and Data Retrieval (CADRE) decision support system. A quasi-global-scale operational data assimilation system has been designed and implemented to provide CADRE a daily product of integrated AMSR-E soil moisture observations with the PECAD two-layer soil moisture model forecasts. A methodology of the system design and a brief evaluation of the system performance over the Conterminous United States (CONUS) is presented.

A comparison of radiometric correction techniques in the evaluation of the relationship between LST and NDVI in Landsat imagery.

PubMed

Tan, Kok Chooi; Lim, Hwee San; Matjafri, Mohd Zubir; Abdullah, Khiruddin

2012-06-01

Atmospheric corrections for multi-temporal optical satellite images are necessary, especially in change detection analyses, such as normalized difference vegetation index (NDVI) rationing. Abrupt change detection analysis using remote-sensing techniques requires radiometric congruity and atmospheric correction to monitor terrestrial surfaces over time. Two atmospheric correction methods were used for this study: relative radiometric normalization and the simplified method for atmospheric correction (SMAC) in the solar spectrum. A multi-temporal data set consisting of two sets of Landsat images from the period between 1991 and 2002 of Penang Island, Malaysia, was used to compare NDVI maps, which were generated using the proposed atmospheric correction methods. Land surface temperature (LST) was retrieved using ATCOR3_T in PCI Geomatica 10.1 image processing software. Linear regression analysis was utilized to analyze the relationship between NDVI and LST. This study reveals that both of the proposed atmospheric correction methods yielded high accuracy through examination of the linear correlation coefficients. To check for the accuracy of the equation obtained through linear regression analysis for every single satellite image, 20 points were randomly chosen. The results showed that the SMAC method yielded a constant value (in terms of error) to predict the NDVI value from linear regression analysis-derived equation. The errors (average) from both proposed atmospheric correction methods were less than 10%.

Label Identification from Statistical Tabulation (LIST) temporal extendability study. [North Dakota, South Dakota, and Minnesota

NASA Technical Reports Server (NTRS)

Dennis, T. B. (Principal Investigator)

1980-01-01

The author has identified the following significant results. The most apparent contributors to the problem of poor temporal extension of LIST are the drastic changes in the brightness keys and an inadequate set of AI responses in Phase 3. The brightness trajectories change drastically from Phase 3 to the transition year (TY). Removing brightness channels from the discriminant does not completely correct the lack of extendability. Removing brightness increases the accuracy of the extension from Phase 3 to TY from 57.7 percent to 64.18 percent. The removal of the Al keys increases accuracy to 65.76 percent. Although the latter increase appears insignificant when compared to the first, the removal of only the Al keys increased accuracy to 63.58 percent. Proper weighting of the responses explains 73.8 percent of the ground truth labels but only 56.7 percent of the Al labels. By contrast, the TY responses which were weighted to explain the TY ground truth labels fared equally well, explaining 73.6 percent of those labels and 87.1 percent of the Al labels.

Improving image-quality of interference fringes of out-of-plane vibration using temporal speckle pattern interferometry and standard deviation for piezoelectric plates.

PubMed

Chien-Ching Ma; Ching-Yuan Chang

2013-07-01

Interferometry provides a high degree of accuracy in the measurement of sub-micrometer deformations; however, the noise associated with experimental measurement undermines the integrity of interference fringes. This study proposes the use of standard deviation in the temporal domain to improve the image quality of patterns obtained from temporal speckle pattern interferometry. The proposed method combines the advantages of both mean and subtractive methods to remove background noise and ambient disturbance simultaneously, resulting in high-resolution images of excellent quality. The out-of-plane vibration of a thin piezoelectric plate is the main focus of this study, providing information useful to the development of energy harvesters. First, ten resonant states were measured using the proposed method, and both mode shape and resonant frequency were investigated. We then rebuilt the phase distribution of the first resonant mode based on the clear interference patterns obtained using the proposed method. This revealed instantaneous deformations in the dynamic characteristics of the resonant state. The proposed method also provides a frequency-sweeping function, facilitating its practical application in the precise measurement of resonant frequency. In addition, the mode shapes and resonant frequencies obtained using the proposed method were recorded and compared with results obtained using finite element method and laser Doppler vibrometery, which demonstrated close agreement.

Compositing multitemporal remote sensing data sets

USGS Publications Warehouse

Qi, J.; Huete, A.R.; Hood, J.; Kerr, Y.

1993-01-01

To eliminate cloud and atmosphere-affected pixels, the compositing of multi temporal remote sensing data sets is done by selecting the maximum vale of the normalized different vegetation index (NDVI) within a compositing period. The NDVI classifier, however, is strongly affected by surface type and anisotropic properties, sensor viewing geometries, and atmospheric conditions. Consequently, the composited, multi temporal, remote sensing data contain substantial noise from these external conditions. Consequently, the composited, multi temporal, remote sensing data contain substantial noise from these external effects. To improve the accuracy of compositing products, two key approaches can be taken: one is to refine the compositing classifier (NDVI) and the other is to improve existing compositing algorithms. In this project, an alternative classifier was developed and an alternative pixel selection criterion was proposed for compositing. The new classifier and the alternative compositing algorithm were applied to an advanced very high resolution radiometer data set of different biome types in the United States. The results were compared with the maximum value compositing and the best index slope extraction algorithms. The new approaches greatly reduced the high frequency noises related to the external factors and repainted more reliable data. The results suggest that the geometric-optical canopy properties of specific biomes may be needed in compositing. Limitations of the new approaches include the dependency of pixel selection on the length of the composite period and data discontinuity.

Comparison of automated volumetry of the hippocampus using NeuroQuant® and visual assessment of the medial temporal lobe in Alzheimer's disease.

PubMed

Persson, Karin; Barca, Maria Lage; Cavallin, Lena; Brækhus, Anne; Knapskog, Anne-Brita; Selbæk, Geir; Engedal, Knut

2017-01-01

Background Different clinically feasible methods for evaluation of medial temporal lobe atrophy exists and are useful in diagnostic work-up of Alzheimer's disease (AD). Purpose To compare the diagnostic properties of two clinically available magnetic resonance imaging (MRI)-based methods-an automated volumetric software, NeuroQuant® (NQ) (evaluation of hippocampus volume) and the Scheltens scale (visual evaluation of medial temporal lobe atrophy [MTA])-in patients with AD dementia, and subjective and mild cognitive impairment (non-dementia). Material and Methods MRIs from 56 patients (31 AD, 25 non-dementia) were assessed with both methods. Correlations between the methods were calculated and receiver operating curve (ROC) analyses that yield area under the curve (AUC) statistics were conducted. Results High correlations were found between the two MRI assessments for the total hippocampal volume measured with NQ and mean MTA score (-0.753, P < 0.001), for the right (-0.767, P < 0.001), and for the left (-0.675, P < 0.001) sides. The NQ total measure yielded somewhat higher AUC (0.88, "good") compared to the MTA mean measure (0.80, "good") in the comparison of patients with AD and non-dementia, but the accuracy was in favor of the MTA scale. Conclusion The two methods correlated highly and both methods reached equally "good" power.

Effect of education on listening comprehension of sentences on healthy elderly: analysis of number of correct responses and task execution time.

PubMed

Silagi, Marcela Lima; Rabelo, Camila Maia; Schochat, Eliane; Mansur, Letícia Lessa

2017-11-13

To analyze the effect of education on sentence listening comprehension on cognitively healthy elderly. A total of 111 healthy elderly, aged 60-80 years of both genders were divided into two groups according to educational level: low education (0-8 years of formal education) and high education (≥9 years of formal education). The participants were assessed using the Revised Token Test, an instrument that supports the evaluation of auditory comprehension of orders with different working memory and syntactic complexity demands. The indicators used for performance analysis were the number of correct responses (accuracy analysis) and task execution time (temporal analysis) in the different blocks. The low educated group had a lower number of correct responses than the high educated group on all blocks of the test. In the temporal analysis, participants with low education had longer execution time for commands on the first four blocks related to working memory. However, the two groups had similar execution time for blocks more related to syntactic comprehension. Education influenced sentence listening comprehension on elderly. Temporal analysis allowed to infer over the relationship between comprehension and other cognitive abilities, and to observe that the low educated elderly did not use effective compensation strategies to improve their performances on the task. Therefore, low educational level, associated with aging, may potentialize the risks for language decline.

Quantifying the role of motor imagery in brain-machine interfaces

NASA Astrophysics Data System (ADS)

Marchesotti, Silvia; Bassolino, Michela; Serino, Andrea; Bleuler, Hannes; Blanke, Olaf

2016-04-01

Despite technical advances in brain machine interfaces (BMI), for as-yet unknown reasons the ability to control a BMI remains limited to a subset of users. We investigate whether individual differences in BMI control based on motor imagery (MI) are related to differences in MI ability. We assessed whether differences in kinesthetic and visual MI, in the behavioral accuracy of MI, and in electroencephalographic variables, were able to differentiate between high- versus low-aptitude BMI users. High-aptitude BMI users showed higher MI accuracy as captured by subjective and behavioral measurements, pointing to a prominent role of kinesthetic rather than visual imagery. Additionally, for the first time, we applied mental chronometry, a measure quantifying the degree to which imagined and executed movements share a similar temporal profile. We also identified enhanced lateralized μ-band oscillations over sensorimotor cortices during MI in high- versus low-aptitude BMI users. These findings reveal that subjective, behavioral, and EEG measurements of MI are intimately linked to BMI control. We propose that poor BMI control cannot be ascribed only to intrinsic limitations of EEG recordings and that specific questionnaires and mental chronometry can be used as predictors of BMI performance (without the need to record EEG activity).

Quantifying the role of motor imagery in brain-machine interfaces

PubMed Central

Marchesotti, Silvia; Bassolino, Michela; Serino, Andrea; Bleuler, Hannes; Blanke, Olaf

2016-01-01

Despite technical advances in brain machine interfaces (BMI), for as-yet unknown reasons the ability to control a BMI remains limited to a subset of users. We investigate whether individual differences in BMI control based on motor imagery (MI) are related to differences in MI ability. We assessed whether differences in kinesthetic and visual MI, in the behavioral accuracy of MI, and in electroencephalographic variables, were able to differentiate between high- versus low-aptitude BMI users. High-aptitude BMI users showed higher MI accuracy as captured by subjective and behavioral measurements, pointing to a prominent role of kinesthetic rather than visual imagery. Additionally, for the first time, we applied mental chronometry, a measure quantifying the degree to which imagined and executed movements share a similar temporal profile. We also identified enhanced lateralized μ-band oscillations over sensorimotor cortices during MI in high- versus low-aptitude BMI users. These findings reveal that subjective, behavioral, and EEG measurements of MI are intimately linked to BMI control. We propose that poor BMI control cannot be ascribed only to intrinsic limitations of EEG recordings and that specific questionnaires and mental chronometry can be used as predictors of BMI performance (without the need to record EEG activity). PMID:27052520

Graph regularized nonnegative matrix factorization for temporal link prediction in dynamic networks

NASA Astrophysics Data System (ADS)

Ma, Xiaoke; Sun, Penggang; Wang, Yu

2018-04-01

Many networks derived from society and nature are temporal and incomplete. The temporal link prediction problem in networks is to predict links at time T + 1 based on a given temporal network from time 1 to T, which is essential to important applications. The current algorithms either predict the temporal links by collapsing the dynamic networks or collapsing features derived from each network, which are criticized for ignoring the connection among slices. to overcome the issue, we propose a novel graph regularized nonnegative matrix factorization algorithm (GrNMF) for the temporal link prediction problem without collapsing the dynamic networks. To obtain the feature for each network from 1 to t, GrNMF factorizes the matrix associated with networks by setting the rest networks as regularization, which provides a better way to characterize the topological information of temporal links. Then, the GrNMF algorithm collapses the feature matrices to predict temporal links. Compared with state-of-the-art methods, the proposed algorithm exhibits significantly improved accuracy by avoiding the collapse of temporal networks. Experimental results of a number of artificial and real temporal networks illustrate that the proposed method is not only more accurate but also more robust than state-of-the-art approaches.

Multi-material 3D Models for Temporal Bone Surgical Simulation.

PubMed

Rose, Austin S; Kimbell, Julia S; Webster, Caroline E; Harrysson, Ola L A; Formeister, Eric J; Buchman, Craig A

2015-07-01

A simulated, multicolor, multi-material temporal bone model can be created using 3-dimensional (3D) printing that will prove both safe and beneficial in training for actual temporal bone surgical cases. As the process of additive manufacturing, or 3D printing, has become more practical and affordable, a number of applications for the technology in the field of Otolaryngology-Head and Neck Surgery have been considered. One area of promise is temporal bone surgical simulation. Three-dimensional representations of human temporal bones were created from temporal bone computed tomography (CT) scans using biomedical image processing software. Multi-material models were then printed and dissected in a temporal bone laboratory by attending and resident otolaryngologists. A 5-point Likert scale was used to grade the models for their anatomical accuracy and suitability as a simulation of cadaveric and operative temporal bone drilling. The models produced for this study demonstrate significant anatomic detail and a likeness to human cadaver specimens for drilling and dissection. Simulated temporal bones created by this process have potential benefit in surgical training, preoperative simulation for challenging otologic cases, and the standardized testing of temporal bone surgical skills. © The Author(s) 2015.

An evaluation of a UAV guidance system with consumer grade GPS receivers

NASA Astrophysics Data System (ADS)

Rosenberg, Abigail Stella

Remote sensing has been demonstrated an important tool in agricultural and natural resource management and research applications, however there are limitations that exist with traditional platforms (i.e., hand held sensors, linear moves, vehicle mounted, airplanes, remotely piloted vehicles (RPVs), unmanned aerial vehicles (UAVs) and satellites). Rapid technological advances in electronics, computers, software applications, and the aerospace industry have dramatically reduced the cost and increased the availability of remote sensing technologies. Remote sensing imagery vary in spectral, spatial, and temporal resolutions and are available from numerous providers. Appendix A presented results of a test project that acquired high-resolution aerial photography with a RPV to map the boundary of a 0.42 km2 fire area. The project mapped the boundaries of the fire area from a mosaic of the aerial images collected and compared this with ground-based measurements. The project achieved a 92.4% correlation between the aerial assessment and the ground truth data. Appendix B used multi-objective analysis to quantitatively assess the tradeoffs between different sensor platform attributes to identify the best overall technology. Experts were surveyed to identify the best overall technology at three different pixel sizes. Appendix C evaluated the positional accuracy of a relatively low cost UAV designed for high resolution remote sensing of small areas in order to determine the positional accuracy of sensor readings. The study evaluated the accuracy and uncertainty of a UAV flight route with respect to the programmed waypoints and of the UAV's GPS position, respectively. In addition, the potential displacement of sensor data was evaluated based on (1) GPS measurements on board the aircraft and (2) the autopilot's circuit board with 3-axis gyros and accelerometers (i.e., roll, pitch, and yaw). The accuracies were estimated based on a 95% confidence interval or similar methods. The accuracy achieved in the second and third manuscripts demonstrates that reasonably priced, high resolution remote sensing via RPVs and UAVs is practical for agriculture and natural resource professionals.

Correlations of External Landmarks With Internal Structures of the Temporal Bone.

PubMed

Piromchai, Patorn; Wijewickrema, Sudanthi; Smeds, Henrik; Kennedy, Gregor; O'Leary, Stephen

2015-09-01

The internal anatomy of a temporal bone could be inferred from external landmarks. Mastoid surgery is an important skill that ENT surgeons need to acquire. Surgeons commonly use CT scans as a guide to understanding anatomical variations before surgery. Conversely, in cases where CT scans are not available, or in the temporal bone laboratory where residents are usually not provided with CT scans, it would be beneficial if the internal anatomy of a temporal bone could be inferred from external landmarks. We explored correlations between internal anatomical variations and metrics established to quantify the position of external landmarks that are commonly exposed in the operating room, or the temporal bone laboratory, before commencement of drilling. Mathematical models were developed to predict internal anatomy based on external structures. From an operating room view, the distances between the following external landmarks were observed to have statistically significant correlations with the internal anatomy of a temporal bone: temporal line, external auditory canal, mastoid tip, occipitomastoid suture, and Henle's spine. These structures can be used to infer a low lying dura mater (p = 0.002), an anteriorly located sigmoid sinus (p = 0.006), and a more lateral course of the facial nerve (p < 0.001). In the temporal bone laboratory view, the mastoid tegmen and sigmoid sinus were also regarded as external landmarks. The distances between these two landmarks and the operating view external structures were able to further infer the laterality of the facial nerve (p < 0.001) and a sclerotic mastoid (p < 0.001). Two nonlinear models were developed that predicted the distances between the following internal structures with a high level of accuracy: the distance from the sigmoid sinus to the posterior external auditory canal (p < 0.001) and the diameter of the round window niche (p < 0.001). The prospect of encountering some of the more technically challenging anatomical variants encountered in temporal bone dissection can be inferred from the distance between external landmarks found on the temporal bone. These relationships could be used as a guideline to predict challenges during drilling and choosing appropriate temporal bones for dissection.

Downscaling Solar Power Output to 4-Seconds for Use in Integration Studies (Presentation)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hummon, M.; Weekley, A.; Searight, K.

2013-10-01

High penetration renewable integration studies require solar power data with high spatial and temporal accuracy to quantify the impact of high frequency solar power ramps on the operation of the system. Our previous work concentrated on downscaling solar power from one hour to one minute by simulation. This method used clearness classifications to categorize temporal and spatial variability, and iterative methods to simulate intra-hour clearness variability. We determined that solar power ramp correlations between sites decrease with distance and the duration of the ramp, starting at around 0.6 for 30-minute ramps between sites that are less than 20 km apart.more » The sub-hour irradiance algorithm we developed has a noise floor that causes the correlations to approach ~0.005. Below one minute, the majority of the correlations of solar power ramps between sites less than 20 km apart are zero, and thus a new method to simulate intra-minute variability is needed. These intra-minute solar power ramps can be simulated using several methods, three of which we evaluate: a cubic spline fit to the one-minute solar power data; projection of the power spectral density toward the higher frequency domain; and average high frequency power spectral density from measured data. Each of these methods either under- or over-estimates the variability of intra-minute solar power ramps. We show that an optimized weighted linear sum of methods, dependent on the classification of temporal variability of the segment of one-minute solar power data, yields time series and ramp distributions similar to measured high-resolution solar irradiance data.« less

Downscaling Solar Power Output to 4-Seconds for Use in Integration Studies: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hummon, M.; Weekley, A.; Searight, K.

2013-10-01

High penetration renewable integration studies require solar power data with high spatial and temporal accuracy to quantify the impact of high frequency solar power ramps on the operation of the system. Our previous work concentrated on downscaling solar power from one hour to one minute by simulation. This method used clearness classifications to categorize temporal and spatial variability, and iterative methods to simulate intra-hour clearness variability. We determined that solar power ramp correlations between sites decrease with distance and the duration of the ramp, starting at around 0.6 for 30-minute ramps between sites that are less than 20 km apart.more » The sub-hour irradiance algorithm we developed has a noise floor that causes the correlations to approach ~0.005. Below one minute, the majority of the correlations of solar power ramps between sites less than 20 km apart are zero, and thus a new method to simulate intra-minute variability is needed. These intra-minute solar power ramps can be simulated using several methods, three of which we evaluate: a cubic spline fit to the one-minute solar power data; projection of the power spectral density toward the higher frequency domain; and average high frequency power spectral density from measured data. Each of these methods either under- or over-estimates the variability of intra-minute solar power ramps. We show that an optimized weighted linear sum of methods, dependent on the classification of temporal variability of the segment of one-minute solar power data, yields time series and ramp distributions similar to measured high-resolution solar irradiance data.« less

High-Order Moving Overlapping Grid Methodology in a Spectral Element Method

NASA Astrophysics Data System (ADS)

Merrill, Brandon E.

A moving overlapping mesh methodology that achieves spectral accuracy in space and up to second-order accuracy in time is developed for solution of unsteady incompressible flow equations in three-dimensional domains. The targeted applications are in aerospace and mechanical engineering domains and involve problems in turbomachinery, rotary aircrafts, wind turbines and others. The methodology is built within the dual-session communication framework initially developed for stationary overlapping meshes. The methodology employs semi-implicit spectral element discretization of equations in each subdomain and explicit treatment of subdomain interfaces with spectrally-accurate spatial interpolation and high-order accurate temporal extrapolation, and requires few, if any, iterations, yet maintains the global accuracy and stability of the underlying flow solver. Mesh movement is enabled through the Arbitrary Lagrangian-Eulerian formulation of the governing equations, which allows for prescription of arbitrary velocity values at discrete mesh points. The stationary and moving overlapping mesh methodologies are thoroughly validated using two- and three-dimensional benchmark problems in laminar and turbulent flows. The spatial and temporal global convergence, for both methods, is documented and is in agreement with the nominal order of accuracy of the underlying solver. Stationary overlapping mesh methodology was validated to assess the influence of long integration times and inflow-outflow global boundary conditions on the performance. In a turbulent benchmark of fully-developed turbulent pipe flow, the turbulent statistics are validated against the available data. Moving overlapping mesh simulations are validated on the problems of two-dimensional oscillating cylinder and a three-dimensional rotating sphere. The aerodynamic forces acting on these moving rigid bodies are determined, and all results are compared with published data. Scaling tests, with both methodologies, show near linear strong scaling, even for moderately large processor counts. The moving overlapping mesh methodology is utilized to investigate the effect of an upstream turbulent wake on a three-dimensional oscillating NACA0012 extruded airfoil. A direct numerical simulation (DNS) at Reynolds Number 44,000 is performed for steady inflow incident upon the airfoil oscillating between angle of attack 5.6° and 25° with reduced frequency k=0.16. Results are contrasted with subsequent DNS of the same oscillating airfoil in a turbulent wake generated by a stationary upstream cylinder.

Phase noise in pulsed Doppler lidar and limitations on achievable single-shot velocity accuracy

NASA Technical Reports Server (NTRS)

Mcnicholl, P.; Alejandro, S.

1992-01-01

The smaller sampling volumes afforded by Doppler lidars compared to radars allows for spatial resolutions at and below some sheer and turbulence wind structure scale sizes. This has brought new emphasis on achieving the optimum product of wind velocity and range resolutions. Several recent studies have considered the effects of amplitude noise, reduction algorithms, and possible hardware related signal artifacts on obtainable velocity accuracy. We discuss here the limitation on this accuracy resulting from the incoherent nature and finite temporal extent of backscatter from aerosols. For a lidar return from a hard (or slab) target, the phase of the intermediate frequency (IF) signal is random and the total return energy fluctuates from shot to shot due to speckle; however, the offset from the transmitted frequency is determinable with an accuracy subject only to instrumental effects and the signal to noise ratio (SNR), the noise being determined by the LO power in the shot noise limited regime. This is not the case for a return from a media extending over a range on the order of or greater than the spatial extent of the transmitted pulse, such as from atmospheric aerosols. In this case, the phase of the IF signal will exhibit a temporal random walk like behavior. It will be uncorrelated over times greater than the pulse duration as the transmitted pulse samples non-overlapping volumes of scattering centers. Frequency analysis of the IF signal in a window similar to the transmitted pulse envelope will therefore show shot-to-shot frequency deviations on the order of the inverse pulse duration reflecting the random phase rate variations. Like speckle, these deviations arise from the incoherent nature of the scattering process and diminish if the IF signal is averaged over times greater than a single range resolution cell (here the pulse duration). Apart from limiting the high SNR performance of a Doppler lidar, this shot-to-shot variance in velocity estimates has a practical impact on lidar design parameters. In high SNR operation, for example, a lidar's efficiency in obtaining mean wind measurements is determined by its repetition rate and not pulse energy or average power. In addition, this variance puts a practical limit on the shot-to-shot hard target performance required of a lidar.

A generalized procedure for analyzing sustained and dynamic vocal fold vibrations from laryngeal high-speed videos using phonovibrograms.

PubMed

Unger, Jakob; Schuster, Maria; Hecker, Dietmar J; Schick, Bernhard; Lohscheller, Jörg

2016-01-01

This work presents a computer-based approach to analyze the two-dimensional vocal fold dynamics of endoscopic high-speed videos, and constitutes an extension and generalization of a previously proposed wavelet-based procedure. While most approaches aim for analyzing sustained phonation conditions, the proposed method allows for a clinically adequate analysis of both dynamic as well as sustained phonation paradigms. The analysis procedure is based on a spatio-temporal visualization technique, the phonovibrogram, that facilitates the documentation of the visible laryngeal dynamics. From the phonovibrogram, a low-dimensional set of features is computed using a principle component analysis strategy that quantifies the type of vibration patterns, irregularity, lateral symmetry and synchronicity, as a function of time. Two different test bench data sets are used to validate the approach: (I) 150 healthy and pathologic subjects examined during sustained phonation. (II) 20 healthy and pathologic subjects that were examined twice: during sustained phonation and a glissando from a low to a higher fundamental frequency. In order to assess the discriminative power of the extracted features, a Support Vector Machine is trained to distinguish between physiologic and pathologic vibrations. The results for sustained phonation sequences are compared to the previous approach. Finally, the classification performance of the stationary analyzing procedure is compared to the transient analysis of the glissando maneuver. For the first test bench the proposed procedure outperformed the previous approach (proposed feature set: accuracy: 91.3%, sensitivity: 80%, specificity: 97%, previous approach: accuracy: 89.3%, sensitivity: 76%, specificity: 96%). Comparing the classification performance of the second test bench further corroborates that analyzing transient paradigms provides clear additional diagnostic value (glissando maneuver: accuracy: 90%, sensitivity: 100%, specificity: 80%, sustained phonation: accuracy: 75%, sensitivity: 80%, specificity: 70%). The incorporation of parameters describing the temporal evolvement of vocal fold vibration clearly improves the automatic identification of pathologic vibration patterns. Furthermore, incorporating a dynamic phonation paradigm provides additional valuable information about the underlying laryngeal dynamics that cannot be derived from sustained conditions. The proposed generalized approach provides a better overall classification performance than the previous approach, and hence constitutes a new advantageous tool for an improved clinical diagnosis of voice disorders. Copyright © 2015 Elsevier B.V. All rights reserved.

Camera calibration for multidirectional flame chemiluminescence tomography

NASA Astrophysics Data System (ADS)

Wang, Jia; Zhang, Weiguang; Zhang, Yuhong; Yu, Xun

2017-04-01

Flame chemiluminescence tomography (FCT), which combines computerized tomography theory and multidirectional chemiluminescence emission measurements, can realize instantaneous three-dimensional (3-D) diagnostics for flames with high spatial and temporal resolutions. One critical step of FCT is to record the projections by multiple cameras from different view angles. For high accuracy reconstructions, it requires that extrinsic parameters (the positions and orientations) and intrinsic parameters (especially the image distances) of cameras be accurately calibrated first. Taking the focus effect of the camera into account, a modified camera calibration method was presented for FCT, and a 3-D calibration pattern was designed to solve the parameters. The precision of the method was evaluated by reprojections of feature points to cameras with the calibration results. The maximum root mean square error of the feature points' position is 1.42 pixels and 0.0064 mm for the image distance. An FCT system with 12 cameras was calibrated by the proposed method and the 3-D CH* intensity of a propane flame was measured. The results showed that the FCT system provides reasonable reconstruction accuracy using the camera's calibration results.

Spatial distribution of arable and abandoned land across former Soviet Union countries

NASA Astrophysics Data System (ADS)

Lesiv, Myroslava; Schepaschenko, Dmitry; Moltchanova, Elena; Bun, Rostyslav; Dürauer, Martina; Prishchepov, Alexander V.; Schierhorn, Florian; Estel, Stephan; Kuemmerle, Tobias; Alcántara, Camilo; Kussul, Natalia; Shchepashchenko, Maria; Kutovaya, Olga; Martynenko, Olga; Karminov, Viktor; Shvidenko, Anatoly; Havlik, Petr; Kraxner, Florian; See, Linda; Fritz, Steffen

2018-04-01

Knowledge of the spatial distribution of agricultural abandonment following the collapse of the Soviet Union is highly uncertain. To help improve this situation, we have developed a new map of arable and abandoned land for 2010 at a 10 arc-second resolution. We have fused together existing land cover and land use maps at different temporal and spatial scales for the former Soviet Union (fSU) using a training data set collected from visual interpretation of very high resolution (VHR) imagery. We have also collected an independent validation data set to assess the map accuracy. The overall accuracies of the map by region and country, i.e. Caucasus, Belarus, Kazakhstan, Republic of Moldova, Russian Federation and Ukraine, are 90±2%, 84±2%, 92±1%, 78±3%, 95±1%, 83±2%, respectively. This new product can be used for numerous applications including the modelling of biogeochemical cycles, land-use modelling, the assessment of trade-offs between ecosystem services and land-use potentials (e.g., agricultural production), among others.

Spatial distribution of arable and abandoned land across former Soviet Union countries.

PubMed

Lesiv, Myroslava; Schepaschenko, Dmitry; Moltchanova, Elena; Bun, Rostyslav; Dürauer, Martina; Prishchepov, Alexander V; Schierhorn, Florian; Estel, Stephan; Kuemmerle, Tobias; Alcántara, Camilo; Kussul, Natalia; Shchepashchenko, Maria; Kutovaya, Olga; Martynenko, Olga; Karminov, Viktor; Shvidenko, Anatoly; Havlik, Petr; Kraxner, Florian; See, Linda; Fritz, Steffen

2018-04-03

Knowledge of the spatial distribution of agricultural abandonment following the collapse of the Soviet Union is highly uncertain. To help improve this situation, we have developed a new map of arable and abandoned land for 2010 at a 10 arc-second resolution. We have fused together existing land cover and land use maps at different temporal and spatial scales for the former Soviet Union (fSU) using a training data set collected from visual interpretation of very high resolution (VHR) imagery. We have also collected an independent validation data set to assess the map accuracy. The overall accuracies of the map by region and country, i.e. Caucasus, Belarus, Kazakhstan, Republic of Moldova, Russian Federation and Ukraine, are 90±2%, 84±2%, 92±1%, 78±3%, 95±1%, 83±2%, respectively. This new product can be used for numerous applications including the modelling of biogeochemical cycles, land-use modelling, the assessment of trade-offs between ecosystem services and land-use potentials (e.g., agricultural production), among others.

Spatial distribution of arable and abandoned land across former Soviet Union countries

PubMed Central

Lesiv, Myroslava; Schepaschenko, Dmitry; Moltchanova, Elena; Bun, Rostyslav; Dürauer, Martina; Prishchepov, Alexander V.; Schierhorn, Florian; Estel, Stephan; Kuemmerle, Tobias; Alcántara, Camilo; Kussul, Natalia; Shchepashchenko, Maria; Kutovaya, Olga; Martynenko, Olga; Karminov, Viktor; Shvidenko, Anatoly; Havlik, Petr; Kraxner, Florian; See, Linda; Fritz, Steffen

2018-01-01

Knowledge of the spatial distribution of agricultural abandonment following the collapse of the Soviet Union is highly uncertain. To help improve this situation, we have developed a new map of arable and abandoned land for 2010 at a 10 arc-second resolution. We have fused together existing land cover and land use maps at different temporal and spatial scales for the former Soviet Union (fSU) using a training data set collected from visual interpretation of very high resolution (VHR) imagery. We have also collected an independent validation data set to assess the map accuracy. The overall accuracies of the map by region and country, i.e. Caucasus, Belarus, Kazakhstan, Republic of Moldova, Russian Federation and Ukraine, are 90±2%, 84±2%, 92±1%, 78±3%, 95±1%, 83±2%, respectively. This new product can be used for numerous applications including the modelling of biogeochemical cycles, land-use modelling, the assessment of trade-offs between ecosystem services and land-use potentials (e.g., agricultural production), among others. PMID:29611843

Application of remotely sensed land-use information to improve estimates of streamflow characteristics, volume 8. [Maryland, Virginia, and Delaware

NASA Technical Reports Server (NTRS)

Pluhowski, E. J. (Principal Investigator)

1977-01-01

The author has identified the following significant results. Land use data derived from high altitude photography and satellite imagery were studied for 49 basins in Delaware, and eastern Maryland and Virginia. Applying multiple regression techniques to a network of gaging stations monitoring runoff from 39 of the basins, demonstrated that land use data from high altitude photography provided an effective means of significantly improving estimates of stream flow. Forty stream flow characteristic equations for incorporating remotely sensed land use information, were compared with a control set of equations using map derived land cover. Significant improvement was detected in six equations where level 1 data was added and in five equations where level 2 information was utilized. Only four equations were improved significantly using land use data derived from LANDSAT imagery. Significant losses in accuracy due to the use of remotely sensed land use information were detected only in estimates of flood peaks. Losses in accuracy for flood peaks were probably due to land cover changes associated with temporal differences among the primary land use data sources.

Automated Plantation Mapping in Indonesia Using Remote Sensing Data

NASA Astrophysics Data System (ADS)

Karpatne, A.; Jia, X.; Khandelwal, A.; Kumar, V.

2017-12-01

Plantation mapping is critical for understanding and addressing deforestation, a key driver of climate change and ecosystem degradation. Unfortunately, most plantation maps are limited to small areas for specific years because they rely on visual inspection of imagery. In this work, we propose a data-driven approach which automatically generates yearly plantation maps for large regions using MODIS multi-spectral data. While traditional machine learning algorithms face manifold challenges in this task, e.g. imperfect training labels, spatio-temporal data heterogeneity, noisy and high-dimensional data, lack of evaluation data, etc., we introduce a novel deep learning-based framework that combines existing imperfect plantation products as training labels and models the spatio-temporal relationships of land covers. We also explores the post-processing steps based on Hidden Markov Model that further improve the detection accuracy. Then we conduct extensive evaluation of the generated plantation maps. Specifically, by randomly sampling and comparing with high-resolution Digital Globe imagery, we demonstrate that the generated plantation maps achieve both high precision and high recall. When compared with existing plantation mapping products, our detection can avoid both false positives and false negatives. Finally, we utilize the generated plantation maps in analyzing the relationship between forest fires and growth of plantations, which assists in better understanding the cause of deforestation in Indonesia.

DNS of Low-Pressure Turbine Cascade Flows with Elevated Inflow Turbulence Using a Discontinuous-Galerkin Spectral-Element Method

NASA Technical Reports Server (NTRS)

Garai, Anirban; Diosady, Laslo T.; Murman, Scott M.; Madavan, Nateri K.

2016-01-01

Recent progress towards developing a new computational capability for accurate and efficient high-fidelity direct numerical simulation (DNS) and large-eddy simulation (LES) of turbomachinery is described. This capability is based on an entropy- stable Discontinuous-Galerkin spectral-element approach that extends to arbitrarily high orders of spatial and temporal accuracy, and is implemented in a computationally efficient manner on a modern high performance computer architecture. An inflow turbulence generation procedure based on a linear forcing approach has been incorporated in this framework and DNS conducted to study the effect of inflow turbulence on the suction- side separation bubble in low-pressure turbine (LPT) cascades. The T106 series of airfoil cascades in both lightly (T106A) and highly loaded (T106C) configurations at exit isentropic Reynolds numbers of 60,000 and 80,000, respectively, are considered. The numerical simulations are performed using 8th-order accurate spatial and 4th-order accurate temporal discretization. The changes in separation bubble topology due to elevated inflow turbulence is captured by the present method and the physical mechanisms leading to the changes are explained. The present results are in good agreement with prior numerical simulations but some expected discrepancies with the experimental data for the T106C case are noted and discussed.

[The Application of Magnetic Resonance Imaging in Alzheimer's Disease].

PubMed

Matsuda, Hiroshi

2017-07-01

In Alzheimer's disease (AD), magnetic resonance imaging (MRI) is essential for early diagnosis, differential diagnosis, and evaluation of disease progression. In structural MRI, the automatic diagnosis of atrophy by computers, even when it is not visually noticeable, is possible in daily clinical practice. Furthermore, subfield volumetric measurements of the medial temporal structures, as well as longitudinal volume measurements with high accuracy, have been developed and are useful for calculating the needed sample size in clinical trials. In addition to detecting local atrophy, graph theory has been applied to structural MRI for evaluation of alterations of the brain networks potentially affected in AD.

High-throughput and automated diagnosis of antimicrobial resistance using a cost-effective cellphone-based micro-plate reader

NASA Astrophysics Data System (ADS)

Feng, Steve; Tseng, Derek; di Carlo, Dino; Garner, Omai B.; Ozcan, Aydogan

2016-12-01

Routine antimicrobial susceptibility testing (AST) can prevent deaths due to bacteria and reduce the spread of multi-drug-resistance, but cannot be regularly performed in resource-limited-settings due to technological challenges, high-costs, and lack of trained professionals. We demonstrate an automated and cost-effective cellphone-based 96-well microtiter-plate (MTP) reader, capable of performing AST without the need for trained diagnosticians. Our system includes a 3D-printed smartphone attachment that holds and illuminates the MTP using a light-emitting-diode array. An inexpensive optical fiber-array enables the capture of the transmitted light of each well through the smartphone camera. A custom-designed application sends the captured image to a server to automatically determine well-turbidity, with results returned to the smartphone in ~1 minute. We tested this mobile-reader using MTPs prepared with 17 antibiotics targeting Gram-negative bacteria on clinical isolates of Klebsiella pneumoniae, containing highly-resistant antimicrobial profiles. Using 78 patient isolate test-plates, we demonstrated that our mobile-reader meets the FDA-defined AST criteria, with a well-turbidity detection accuracy of 98.21%, minimum-inhibitory-concentration accuracy of 95.12%, and a drug-susceptibility interpretation accuracy of 99.23%, with no very major errors. This mobile-reader could eliminate the need for trained diagnosticians to perform AST, reduce the cost-barrier for routine testing, and assist in spatio-temporal tracking of bacterial resistance.

Feature Selection for Motor Imagery EEG Classification Based on Firefly Algorithm and Learning Automata

PubMed Central

Liu, Aiming; Liu, Quan; Ai, Qingsong; Xie, Yi; Chen, Anqi

2017-01-01

Motor Imagery (MI) electroencephalography (EEG) is widely studied for its non-invasiveness, easy availability, portability, and high temporal resolution. As for MI EEG signal processing, the high dimensions of features represent a research challenge. It is necessary to eliminate redundant features, which not only create an additional overhead of managing the space complexity, but also might include outliers, thereby reducing classification accuracy. The firefly algorithm (FA) can adaptively select the best subset of features, and improve classification accuracy. However, the FA is easily entrapped in a local optimum. To solve this problem, this paper proposes a method of combining the firefly algorithm and learning automata (LA) to optimize feature selection for motor imagery EEG. We employed a method of combining common spatial pattern (CSP) and local characteristic-scale decomposition (LCD) algorithms to obtain a high dimensional feature set, and classified it by using the spectral regression discriminant analysis (SRDA) classifier. Both the fourth brain–computer interface competition data and real-time data acquired in our designed experiments were used to verify the validation of the proposed method. Compared with genetic and adaptive weight particle swarm optimization algorithms, the experimental results show that our proposed method effectively eliminates redundant features, and improves the classification accuracy of MI EEG signals. In addition, a real-time brain–computer interface system was implemented to verify the feasibility of our proposed methods being applied in practical brain–computer interface systems. PMID:29117100

Feature Selection for Motor Imagery EEG Classification Based on Firefly Algorithm and Learning Automata.

PubMed

Liu, Aiming; Chen, Kun; Liu, Quan; Ai, Qingsong; Xie, Yi; Chen, Anqi

2017-11-08

Motor Imagery (MI) electroencephalography (EEG) is widely studied for its non-invasiveness, easy availability, portability, and high temporal resolution. As for MI EEG signal processing, the high dimensions of features represent a research challenge. It is necessary to eliminate redundant features, which not only create an additional overhead of managing the space complexity, but also might include outliers, thereby reducing classification accuracy. The firefly algorithm (FA) can adaptively select the best subset of features, and improve classification accuracy. However, the FA is easily entrapped in a local optimum. To solve this problem, this paper proposes a method of combining the firefly algorithm and learning automata (LA) to optimize feature selection for motor imagery EEG. We employed a method of combining common spatial pattern (CSP) and local characteristic-scale decomposition (LCD) algorithms to obtain a high dimensional feature set, and classified it by using the spectral regression discriminant analysis (SRDA) classifier. Both the fourth brain-computer interface competition data and real-time data acquired in our designed experiments were used to verify the validation of the proposed method. Compared with genetic and adaptive weight particle swarm optimization algorithms, the experimental results show that our proposed method effectively eliminates redundant features, and improves the classification accuracy of MI EEG signals. In addition, a real-time brain-computer interface system was implemented to verify the feasibility of our proposed methods being applied in practical brain-computer interface systems.

A face in a (temporal) crowd.

PubMed

Hacker, Catrina M; Meschke, Emily X; Biederman, Irving

2018-03-20

Familiar objects, specified by name, can be identified with high accuracy when embedded in a rapidly presented sequence of images at rates exceeding 10 images/s. Not only can target objects be detected at such brief presentation rates, they can also be detected under high uncertainty, where their classification is defined negatively, e.g., "Not a Tool." The identification of a familiar speaker's voice declines precipitously when uncertainty is increased from one to a mere handful of possible speakers. Is the limitation imposed by uncertainty, i.e., the number of possible individuals, a general characteristic of processes for person individuation such that the identifiability of a familiar face would undergo a similar decline with uncertainty? Specifically, could the presence of an unnamed celebrity, thus any celebrity, be detected when presented in a rapid sequence of unfamiliar faces? If so, could the celebrity be identified? Despite the markedly greater physical similarity of faces compared to objects that are, say, not tools, the presence of a celebrity could be detected with moderately high accuracy (∼75%) at rates exceeding 7 faces/s. False alarms were exceedingly rare as almost all the errors were misses. Detection accuracy by moderate congenital prosopagnosics was lower than controls, but still well above chance. Given the detection of the presence of a celebrity, all subjects were almost always able to identify that celebrity, providing no role for a covert familiarity signal outside of awareness. Copyright © 2018 Elsevier Ltd. All rights reserved.

Stabilized linear semi-implicit schemes for the nonlocal Cahn-Hilliard equation

NASA Astrophysics Data System (ADS)

Du, Qiang; Ju, Lili; Li, Xiao; Qiao, Zhonghua

2018-06-01

Comparing with the well-known classic Cahn-Hilliard equation, the nonlocal Cahn-Hilliard equation is equipped with a nonlocal diffusion operator and can describe more practical phenomena for modeling phase transitions of microstructures in materials. On the other hand, it evidently brings more computational costs in numerical simulations, thus efficient and accurate time integration schemes are highly desired. In this paper, we propose two energy-stable linear semi-implicit methods with first and second order temporal accuracies respectively for solving the nonlocal Cahn-Hilliard equation. The temporal discretization is done by using the stabilization technique with the nonlocal diffusion term treated implicitly, while the spatial discretization is carried out by the Fourier collocation method with FFT-based fast implementations. The energy stabilities are rigorously established for both methods in the fully discrete sense. Numerical experiments are conducted for a typical case involving Gaussian kernels. We test the temporal convergence rates of the proposed schemes and make a comparison of the nonlocal phase transition process with the corresponding local one. In addition, long-time simulations of the coarsening dynamics are also performed to predict the power law of the energy decay.

Efficacy of High Frequency Ultrasound in Localization and Characterization of Orbital Lesions

PubMed Central

Gurushankar, G; Bhimarao; Kadakola, Bindushree

2015-01-01

Background The complicated anatomy of orbit and the wide spectrum of pathological conditions present a formidable challenge for early diagnosis, which is critical for management. Ultrasonography provides a detailed cross sectional anatomy of the entire globe with excellent topographic visualization and real time display of the moving organ. Objectives of the study To evaluate the efficacy of high frequency Ultrasound in localization of orbital diseases and to characterize various orbital pathologies sonologically. Materials and Methods Hundred eyes of 85 patients were examined with ultrasound using linear high frequency probe (5 to 17 MHz) of PHILPS IU22 ultrasound system. Sonological diagnosis was made based on location, acoustic characteristics, kinetic properties and Doppler flow dynamics. Final diagnosis was made based on clinical & laboratory findings/higher cross-sectional imaging/surgery & histopathology (as applicable). Diagnostic accuracy of ultrasonography was evaluated and compared with final diagnosis. Results The distinction between ocular and extraocular pathologies was made in 100% of cases. The overall sensitivity, specificity, NPV and accuracy of ultrasonography were 94.2%, 98.8%, 92.2% & 94.9% respectively for diagnosis of ocular pathologies and 94.2%, 99.2%, 95.9% & 95.2% respectively for extra ocular pathologies. Conclusion Ultrasonography is a readily available, simple, cost effective, non ionizing and non invasive modality with overall high diagnostic accuracy in localising and characterising orbital pathologies. It has higher spatial and temporal resolution compared to CT/MRI. However, CT/MRI may be indicated in certain cases for the evaluation of calcifications, bony involvement, extension to adjacent structures and intracranial extension. PMID:26500977

Near-Continuous Profiling of Temperature, Moisture, and Atmospheric Stability Using the Atmospheric Emitted Radiance Interferometer (AERI).

NASA Astrophysics Data System (ADS)

Feltz, W. F.; Smith, W. L.; Howell, H. B.; Knuteson, R. O.; Woolf, H.; Revercomb, H. E.

2003-05-01

The Department of Energy Atmospheric Radiation Measurement Program (ARM) has funded the development and installation of five ground-based atmospheric emitted radiance interferometer (AERI) systems at the Southern Great Plains (SGP) site. The purpose of this paper is to provide an overview of the AERI instrument, improvement of the AERI temperature and moisture retrieval technique, new profiling utility, and validation of high-temporal-resolution AERI-derived stability indices important for convective nowcasting. AERI systems have been built at the University of Wisconsin-Madison, Madison, Wisconsin, and deployed in the Oklahoma-Kansas area collocated with National Oceanic and Atmospheric Administration 404-MHz wind profilers at Lamont, Vici, Purcell, and Morris, Oklahoma, and Hillsboro, Kansas. The AERI systems produce absolutely calibrated atmospheric infrared emitted radiances at one-wavenumber resolution from 3 to 20 m at less than 10-min temporal resolution. The instruments are robust, are automated in the field, and are monitored via the Internet in near-real time. The infrared radiances measured by the AERI systems contain meteorological information about the vertical structure of temperature and water vapor in the planetary boundary layer (PBL; 0-3 km). A mature temperature and water vapor retrieval algorithm has been developed over a 10-yr period that provides vertical profiles at less than 10-min temporal resolution to 3 km in the PBL. A statistical retrieval is combined with the hourly Geostationary Operational Environmental Satellite (GOES) sounder water vapor or Rapid Update Cycle, version 2, numerical weather prediction (NWP) model profiles to provide a nominal hybrid first guess of temperature and moisture to the AERI physical retrieval algorithm. The hourly satellite or NWP data provide a best estimate of the atmospheric state in the upper PBL; the AERI radiances provide the mesoscale temperature and moisture profile correction in the PBL to the large-scale GOES and NWP model profiles at high temporal resolution. The retrieval product has been named AERIplus because the first guess used for the mathematical physical inversion uses an optimal combination of statistical climatological, satellite, and numerical model data to provide a best estimate of the atmospheric state. The AERI physical retrieval algorithm adjusts the boundary layer temperature and moisture structure provided by the hybrid first guess to fit the observed AERI downwelling radiance measurement. This provides a calculated AERI temperature and moisture profile using AERI-observed radiances `plus' the best-known atmospheric state above the boundary layer using NWP or satellite data. AERIplus retrieval accuracy for temperature has been determined to be better than 1 K, and water vapor retrieval accuracy is approximately 5% in absolute water vapor when compared with well-calibrated radiosondes from the surface to an altitude of 3 km. Because AERI can monitor the thermodynamics where the atmosphere usually changes most rapidly, atmospheric stability tendency information is readily available from the system. High-temporal-resolution retrieval of convective available potential energy, convective inhibition, and PBL equivalent potential temperature e are provided in near-real time from all five AERI systems at the ARM SGP site, offering a unique look at the atmospheric state. This new source of meteorological data has shown excellent skill in detecting rapid synoptic and mesoscale meteorological changes within clear atmospheric conditions. This method has utility in nowcasting temperature inversion strength and destabilization caused by e advection. This high-temporal-resolution monitoring of rapid atmospheric destabilization is especially important for nowcasting severe convection.

Mapping urban forest tree species using IKONOS imagery: preliminary results.

PubMed

Pu, Ruiliang

2011-01-01

A stepwise masking system with high-resolution IKONOS imagery was developed to identify and map urban forest tree species/groups in the City of Tampa, Florida, USA. The eight species/groups consist of sand live oak (Quercus geminata), laurel oak (Quercus laurifolia), live oak (Quercus virginiana), magnolia (Magnolia grandiflora), pine (species group), palm (species group), camphor (Cinnamomum camphora), and red maple (Acer rubrum). The system was implemented with soil-adjusted vegetation index (SAVI) threshold, textural information after running a low-pass filter, and brightness threshold of NIR band to separate tree canopies from non-vegetated areas from other vegetation types (e.g., grass/lawn) and to separate the tree canopies into sunlit and shadow areas. A maximum likelihood classifier was used to identify and map forest type and species. After IKONOS imagery was preprocessed, a total of nine spectral features were generated, including four spectral bands, three hue-intensity-saturation indices, one SAVI, and one texture image. The identified and mapped results were examined with independent ground survey data. The experimental results indicate that when classifying all the eight tree species/ groups with the high-resolution IKONOS image data, the identifying accuracy was very low and could not satisfy a practical application level, and when merging the eight species/groups into four major species/groups, the average accuracy is still low (average accuracy = 73%, overall accuracy = 86%, and κ = 0.76 with sunlit test samples). Such a low accuracy of identifying and mapping the urban tree species/groups is attributable to low spatial resolution IKONOS image data relative to tree crown size, to complex and variable background spectrum impact on crown spectra, and to shadow/shaded impact. The preliminary results imply that to improve the tree species identification accuracy and achieve a practical application level in urban area, multi-temporal (multi-seasonal) or hyperspectral data image data should be considered for use in the future.

Influence of Spatial Resolution in Three-dimensional Cine Phase Contrast Magnetic Resonance Imaging on the Accuracy of Hemodynamic Analysis

PubMed Central

Fukuyama, Atsushi; Isoda, Haruo; Morita, Kento; Mori, Marika; Watanabe, Tomoya; Ishiguro, Kenta; Komori, Yoshiaki; Kosugi, Takafumi

2017-01-01

Introduction: We aim to elucidate the effect of spatial resolution of three-dimensional cine phase contrast magnetic resonance (3D cine PC MR) imaging on the accuracy of the blood flow analysis, and examine the optimal setting for spatial resolution using flow phantoms. Materials and Methods: The flow phantom has five types of acrylic pipes that represent human blood vessels (inner diameters: 15, 12, 9, 6, and 3 mm). The pipes were fixed with 1% agarose containing 0.025 mol/L gadolinium contrast agent. A blood-mimicking fluid with human blood property values was circulated through the pipes at a steady flow. Magnetic resonance (MR) images (three-directional phase images with speed information and magnitude images for information of shape) were acquired using the 3-Tesla MR system and receiving coil. Temporal changes in spatially-averaged velocity and maximum velocity were calculated using hemodynamic analysis software. We calculated the error rates of the flow velocities based on the volume flow rates measured with a flowmeter and examined measurement accuracy. Results: When the acrylic pipe was the size of the thoracicoabdominal or cervical artery and the ratio of pixel size for the pipe was set at 30% or lower, spatially-averaged velocity measurements were highly accurate. When the pixel size ratio was set at 10% or lower, maximum velocity could be measured with high accuracy. It was difficult to accurately measure maximum velocity of the 3-mm pipe, which was the size of an intracranial major artery, but the error for spatially-averaged velocity was 20% or less. Conclusions: Flow velocity measurement accuracy of 3D cine PC MR imaging for pipes with inner sizes equivalent to vessels in the cervical and thoracicoabdominal arteries is good. The flow velocity accuracy for the pipe with a 3-mm-diameter that is equivalent to major intracranial arteries is poor for maximum velocity, but it is relatively good for spatially-averaged velocity. PMID:28132996

Decoding word and category-specific spatiotemporal representations from MEG and EEG

PubMed Central

Chan, Alexander M.; Halgren, Eric; Marinkovic, Ksenija; Cash, Sydney S.

2010-01-01

The organization and localization of lexico-semantic information in the brain has been debated for many years. Specifically, lesion and imaging studies have attempted to map the brain areas representing living versus non-living objects, however, results remain variable. This may be due, in part, to the fact that the univariate statistical mapping analyses used to detect these brain areas are typically insensitive to subtle, but widespread, effects. Decoding techniques, on the other hand, allow for a powerful multivariate analysis of multichannel neural data. In this study, we utilize machine-learning algorithms to first demonstrate that semantic category, as well as individual words, can be decoded from EEG and MEG recordings of subjects performing a language task. Mean accuracies of 76% (chance = 50%) and 83% (chance = 20%) were obtained for the decoding of living vs. non-living category or individual words respectively. Furthermore, we utilize this decoding analysis to demonstrate that the representations of words and semantic category are highly distributed both spatially and temporally. In particular, bilateral anterior temporal, bilateral inferior frontal, and left inferior temporal-occipital sensors are most important for discrimination. Successful intersubject and intermodality decoding shows that semantic representations between stimulus modalities and individuals are reasonably consistent. These results suggest that both word and category-specific information are present in extracranially recorded neural activity and that these representations may be more distributed, both spatially and temporally, than previous studies suggest. PMID:21040796

Spatial and Temporal Monitoring of Aerosol over Selected Urban Areas in Egypt

NASA Astrophysics Data System (ADS)

Shokr, Mohammed; El-Tahan, Mohammed; Ibrahim, Alaa

2015-04-01

We utilize remote sensing data of atmospheric aerosols from the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the Terra and Aqua satellites to explore spatio-temporal patterns over selected urban sites in Egypt during 2000-2015. High resolution (10 x 10 km^2) Level 2, collection 5, quality-controlled product was used. The selected sites are characterized by different human and industrial activities as well as landscape and meteorological attributes. These have impacts on the dominant types and intensity of aerosols. Aerosol robotic network (AERONET) data were used to validate the calculations from MODIS. The suitability of the MODIS product in terms of spatial and temporal coverage as well as accuracy and robustness has been established. Seasonal patterns of aerosol concentration are identified and compared between the sites. Spatial gradient of aerosol is assessed in the vicinity of major aerosol-emission sites (e.g. Cairo) to determine the range of influence of the generated pollution. Peak aerosol concentrations are explained in terms of meteorological events and land cover. The limited trends found in the temporal records of the aerosol measurements will be confirmed using calibrated long-term ground observations. The study has been conducted under the PEER 2-239 research project titled "The Impact of Biogenic and Anthropogenic Atmospheric Aerosols to Climate in Egypt". Project website is CleanAirEgypt.org

The accuracy of an electromagnetic navigation system in lateral skull base approaches.

PubMed

Komune, Noritaka; Matsushima, Ken; Matsuo, Satoshi; Safavi-Abbasi, Sam; Matsumoto, Nozomu; Rhoton, Albert L

2017-02-01

Image-guided optical tracking systems are being used with increased frequency in lateral skull base surgery. Recently, electromagnetic tracking systems have become available for use in this region. However, the clinical accuracy of the electromagnetic tracking system has not been examined in lateral skull base surgery. This study evaluates the accuracy of electromagnetic navigation in lateral skull base surgery. Cadaveric and radiographic study. Twenty cadaveric temporal bones were dissected in a surgical setting under a commercially available, electromagnetic surgical navigation system. The target registration error (TRE) was measured at 28 surgical landmarks during and after performing the standard translabyrinthine and middle cranial fossa surgical approaches to the internal acoustic canal. In addition, three demonstrative procedures that necessitate navigation with high accuracy were performed; that is, canalostomy of the superior semicircular canal from the middle cranial fossa, 1 cochleostomy from the middle cranial fossa, 2 and infralabyrinthine approach to the petrous apex. 3 RESULTS: Eleven of 17 (65%) of the targets in the translabyrinthine approach and five of 11 (45%) of the targets in the middle fossa approach could be identified in the navigation system with TRE of less than 0.5 mm. Three accuracy-dependent procedures were completed without anatomical injury of important anatomical structures. The electromagnetic navigation system had sufficient accuracy to be used in the surgical setting. It was possible to perform complex procedures in the lateral skull base under the guidance of the electromagnetically tracked navigation system. N/A. Laryngoscope, 2016 127:450-459, 2017. © 2016 The American Laryngological, Rhinological and Otological Society, Inc.

High-Accuracy Tidal Flat Digital Elevation Model Construction Using TanDEM-X Science Phase Data

NASA Technical Reports Server (NTRS)

Lee, Seung-Kuk; Ryu, Joo-Hyung

2017-01-01

This study explored the feasibility of using TanDEM-X (TDX) interferometric observations of tidal flats for digital elevation model (DEM) construction. Our goal was to generate high-precision DEMs in tidal flat areas, because accurate intertidal zone data are essential for monitoring coastal environment sand erosion processes. To monitor dynamic coastal changes caused by waves, currents, and tides, very accurate DEMs with high spatial resolution are required. The bi- and monostatic modes of the TDX interferometer employed during the TDX science phase provided a great opportunity for highly accurate intertidal DEM construction using radar interferometry with no time lag (bistatic mode) or an approximately 10-s temporal baseline (monostatic mode) between the master and slave synthetic aperture radar image acquisitions. In this study, DEM construction in tidal flat areas was first optimized based on the TDX system parameters used in various TDX modes. We successfully generated intertidal zone DEMs with 57-m spatial resolutions and interferometric height accuracies better than 0.15 m for three representative tidal flats on the west coast of the Korean Peninsula. Finally, we validated these TDX DEMs against real-time kinematic-GPS measurements acquired in two tidal flat areas; the correlation coefficient was 0.97 with a root mean square error of 0.20 m.

A comparison of the accuracy of the smart sock system to force platform and optical system for measurement of temporal parameters of locomotion

NASA Astrophysics Data System (ADS)

Oks, A.; Katashev, A.; Bernans, E.; Abolins, V.

2017-10-01

The aim of the study was to present a new DAid®Pressure Sock System for feet locomotion monitoring and to verify it’s temporal characteristics by data comparison with the same obtained by two other widely used methods as reference. Designed system is based on sensors which can be knitted directly in the garment or hosiery items. DAid®Pressure Sock System was created for sport and medical applications. Comparison of temporal characteristics of different types of locomotion, obtained using designed system and reference devises, showed good agreement between data.

Global Data for Ecology and Epidemiology: A Novel Algorithm for Temporal Fourier Processing MODIS Data

PubMed Central

Scharlemann, Jörn P. W.; Benz, David; Hay, Simon I.; Purse, Bethan V.; Tatem, Andrew J.; Wint, G. R. William; Rogers, David J.

2008-01-01

Background Remotely-sensed environmental data from earth-orbiting satellites are increasingly used to model the distribution and abundance of both plant and animal species, especially those of economic or conservation importance. Time series of data from the MODerate-resolution Imaging Spectroradiometer (MODIS) sensors on-board NASA's Terra and Aqua satellites offer the potential to capture environmental thermal and vegetation seasonality, through temporal Fourier analysis, more accurately than was previously possible using the NOAA Advanced Very High Resolution Radiometer (AVHRR) sensor data. MODIS data are composited over 8- or 16-day time intervals that pose unique problems for temporal Fourier analysis. Applying standard techniques to MODIS data can introduce errors of up to 30% in the estimation of the amplitudes and phases of the Fourier harmonics. Methodology/Principal Findings We present a novel spline-based algorithm that overcomes the processing problems of composited MODIS data. The algorithm is tested on artificial data generated using randomly selected values of both amplitudes and phases, and provides an accurate estimate of the input variables under all conditions. The algorithm was then applied to produce layers that capture the seasonality in MODIS data for the period from 2001 to 2005. Conclusions/Significance Global temporal Fourier processed images of 1 km MODIS data for Middle Infrared Reflectance, day- and night-time Land Surface Temperature (LST), Normalised Difference Vegetation Index (NDVI), and Enhanced Vegetation Index (EVI) are presented for ecological and epidemiological applications. The finer spatial and temporal resolution, combined with the greater geolocational and spectral accuracy of the MODIS instruments, compared with previous multi-temporal data sets, mean that these data may be used with greater confidence in species' distribution modelling. PMID:18183289

Global data for ecology and epidemiology: a novel algorithm for temporal Fourier processing MODIS data.

PubMed

Scharlemann, Jörn P W; Benz, David; Hay, Simon I; Purse, Bethan V; Tatem, Andrew J; Wint, G R William; Rogers, David J

2008-01-09

Remotely-sensed environmental data from earth-orbiting satellites are increasingly used to model the distribution and abundance of both plant and animal species, especially those of economic or conservation importance. Time series of data from the MODerate-resolution Imaging Spectroradiometer (MODIS) sensors on-board NASA's Terra and Aqua satellites offer the potential to capture environmental thermal and vegetation seasonality, through temporal Fourier analysis, more accurately than was previously possible using the NOAA Advanced Very High Resolution Radiometer (AVHRR) sensor data. MODIS data are composited over 8- or 16-day time intervals that pose unique problems for temporal Fourier analysis. Applying standard techniques to MODIS data can introduce errors of up to 30% in the estimation of the amplitudes and phases of the Fourier harmonics. We present a novel spline-based algorithm that overcomes the processing problems of composited MODIS data. The algorithm is tested on artificial data generated using randomly selected values of both amplitudes and phases, and provides an accurate estimate of the input variables under all conditions. The algorithm was then applied to produce layers that capture the seasonality in MODIS data for the period from 2001 to 2005. Global temporal Fourier processed images of 1 km MODIS data for Middle Infrared Reflectance, day- and night-time Land Surface Temperature (LST), Normalised Difference Vegetation Index (NDVI), and Enhanced Vegetation Index (EVI) are presented for ecological and epidemiological applications. The finer spatial and temporal resolution, combined with the greater geolocational and spectral accuracy of the MODIS instruments, compared with previous multi-temporal data sets, mean that these data may be used with greater confidence in species' distribution modelling.

Machine learning methods reveal the temporal pattern of dengue incidence using meteorological factors in metropolitan Manila, Philippines.

PubMed

Carvajal, Thaddeus M; Viacrusis, Katherine M; Hernandez, Lara Fides T; Ho, Howell T; Amalin, Divina M; Watanabe, Kozo

2018-04-17

Several studies have applied ecological factors such as meteorological variables to develop models and accurately predict the temporal pattern of dengue incidence or occurrence. With the vast amount of studies that investigated this premise, the modeling approaches differ from each study and only use a single statistical technique. It raises the question of whether which technique would be robust and reliable. Hence, our study aims to compare the predictive accuracy of the temporal pattern of Dengue incidence in Metropolitan Manila as influenced by meteorological factors from four modeling techniques, (a) General Additive Modeling, (b) Seasonal Autoregressive Integrated Moving Average with exogenous variables (c) Random Forest and (d) Gradient Boosting. Dengue incidence and meteorological data (flood, precipitation, temperature, southern oscillation index, relative humidity, wind speed and direction) of Metropolitan Manila from January 1, 2009 - December 31, 2013 were obtained from respective government agencies. Two types of datasets were used in the analysis; observed meteorological factors (MF) and its corresponding delayed or lagged effect (LG). After which, these datasets were subjected to the four modeling techniques. The predictive accuracy and variable importance of each modeling technique were calculated and evaluated. Among the statistical modeling techniques, Random Forest showed the best predictive accuracy. Moreover, the delayed or lag effects of the meteorological variables was shown to be the best dataset to use for such purpose. Thus, the model of Random Forest with delayed meteorological effects (RF-LG) was deemed the best among all assessed models. Relative humidity was shown to be the top-most important meteorological factor in the best model. The study exhibited that there are indeed different predictive outcomes generated from each statistical modeling technique and it further revealed that the Random forest model with delayed meteorological effects to be the best in predicting the temporal pattern of Dengue incidence in Metropolitan Manila. It is also noteworthy that the study also identified relative humidity as an important meteorological factor along with rainfall and temperature that can influence this temporal pattern.

Prediction of seizure-onset laterality by using Wada memory asymmetries in pediatric epilepsy surgery candidates.

PubMed

Lee, Gregory P; Park, Yong D; Hempel, Ann; Westerveld, Michael; Loring, David W

2002-09-01

Because the capacity of intracarotid amobarbital (Wada) memory assessment to predict seizure-onset laterality in children has not been thoroughly investigated, three comprehensive epilepsy surgery centers pooled their data and examined Wada memory asymmetries to predict side of seizure onset in children being considered for epilepsy surgery. One hundred fifty-two children with intractable epilepsy underwent Wada testing. Although the type and number of memory stimuli and methods varied at each institution, all children were presented with six to 10 items soon after amobarbital injection. After return to neurologic baseline, recognition memory for the stimuli was assessed. Seizure onset was determined by simultaneous video-EEG recordings of multiple seizures. In children with unilateral temporal lobe seizures (n = 87), Wada memory asymmetries accurately predicted seizure laterality to a statistically significant degree. Wada memory asymmetries also correctly predicted side of seizure onset in children with extra-temporal lobe seizures (n = 65). Although individual patient prediction accuracy was statistically significant in temporal lobe cases, onset laterality was incorrectly predicted in < or =52% of children with left temporal lobe seizure onset, depending on the methods and asymmetry criterion used. There also were significant differences between Wada prediction accuracy across the three epilepsy centers. Results suggest that Wada memory assessment is useful in predicting side of seizure onset in many children. However, Wada memory asymmetries should be interpreted more cautiously in children than in adults.

On reinitializing level set functions

NASA Astrophysics Data System (ADS)

Min, Chohong

2010-04-01

In this paper, we consider reinitializing level functions through equation ϕt+sgn(ϕ0)(‖∇ϕ‖-1)=0[16]. The method of Russo and Smereka [11] is taken in the spatial discretization of the equation. The spatial discretization is, simply speaking, the second order ENO finite difference with subcell resolution near the interface. Our main interest is on the temporal discretization of the equation. We compare the three temporal discretizations: the second order Runge-Kutta method, the forward Euler method, and a Gauss-Seidel iteration of the forward Euler method. The fact that the time in the equation is fictitious makes a hypothesis that all the temporal discretizations result in the same result in their stationary states. The fact that the absolute stability region of the forward Euler method is not wide enough to include all the eigenvalues of the linearized semi-discrete system of the second order ENO spatial discretization makes another hypothesis that the forward Euler temporal discretization should invoke numerical instability. Our results in this paper contradict both the hypotheses. The Runge-Kutta and Gauss-Seidel methods obtain the second order accuracy, and the forward Euler method converges with order between one and two. Examining all their properties, we conclude that the Gauss-Seidel method is the best among the three. Compared to the Runge-Kutta, it is twice faster and requires memory two times less with the same accuracy.

Improving reading skills in students with dyslexia: the efficacy of a sublexical training with rhythmic background

PubMed Central

Bonacina, Silvia; Cancer, Alice; Lanzi, Pier Luca; Lorusso, Maria Luisa; Antonietti, Alessandro

2015-01-01

The core deficit underlying developmental dyslexia (DD) has been identified in difficulties in dynamic and rapidly changing auditory information processing, which contribute to the development of impaired phonological representations for words. It has been argued that enhancing basic musical rhythm perception skills in children with DD may have a positive effect on reading abilities because music and language share common mechanisms and thus transfer effects from the former to the latter are expected to occur. A computer-assisted training, called Rhythmic Reading Training (RRT), was designed in which reading exercises are combined with rhythm background. Fourteen junior high school students with DD took part to 9 biweekly individual sessions of 30 min in which RRT was implemented. Reading improvements after the intervention period were compared with ones of a matched control group of 14 students with DD who received no intervention. Results indicated that RRT had a positive effect on both reading speed and accuracy and significant effects were found on short pseudo-words reading speed, long pseudo-words reading speed, high frequency long words reading accuracy, and text reading accuracy. No difference in rhythm perception between the intervention and control group were found. Findings suggest that rhythm facilitates the development of reading skill because of the temporal structure it imposes to word decoding. PMID:26500581

Identifying Optimal Temporal Scale for the Correlation of AOD and Ground Measurements of PM2.5 to Improve the Model Performance in a Real-time Air Quality Estimation System

NASA Technical Reports Server (NTRS)

Li, Hui; Faruque, Fazlay; Williams, Worth; Al-Hamdan, Mohammad; Luvall, Jeffrey C.; Crosson, William; Rickman, Douglas; Limaye, Ashutosh

2009-01-01

Aerosol optical depth (AOD), an indirect estimate of particle matter using satellite observations, has shown great promise in improving estimates of PM 2.5 air quality surface. Currently, few studies have been conducted to explore the optimal way to apply AOD data to improve the model accuracy of PM 2.5 surface estimation in a real-time air quality system. We believe that two major aspects may be worthy of consideration in that area: 1) the approach to integrate satellite measurements with ground measurements in the pollution estimation, and 2) identification of an optimal temporal scale to calculate the correlation of AOD and ground measurements. This paper is focused on the second aspect on the identifying the optimal temporal scale to correlate AOD with PM2.5. Five following different temporal scales were chosen to evaluate their impact on the model performance: 1) within the last 3 days, 2) within the last 10 days, 3) within the last 30 days, 4) within the last 90 days, and 5) the time period with the highest correlation in a year. The model performance is evaluated for its accuracy, bias, and errors based on the following selected statistics: the Mean Bias, the Normalized Mean Bias, the Root Mean Square Error, Normalized Mean Error, and the Index of Agreement. This research shows that the model with the temporal scale of within the last 30 days displays the best model performance in this study area using 2004 and 2005 data sets.

Temporal Integration of Auditory Information Is Invariant to Temporal Grouping Cues1,2,3

PubMed Central

Tsunada, Joji

2015-01-01

Abstract Auditory perception depends on the temporal structure of incoming acoustic stimuli. Here, we examined whether a temporal manipulation that affects the perceptual grouping also affects the time dependence of decisions regarding those stimuli. We designed a novel discrimination task that required human listeners to decide whether a sequence of tone bursts was increasing or decreasing in frequency. We manipulated temporal perceptual-grouping cues by changing the time interval between the tone bursts, which led to listeners hearing the sequences as a single sound for short intervals or discrete sounds for longer intervals. Despite these strong perceptual differences, this manipulation did not affect the efficiency of how auditory information was integrated over time to form a decision. Instead, the grouping manipulation affected subjects’ speed−accuracy trade-offs. These results indicate that the temporal dynamics of evidence accumulation for auditory perceptual decisions can be invariant to manipulations that affect the perceptual grouping of the evidence. PMID:26464975

Fine Particulate Matter Predictions Using High Resolution Aerosol Optical Depth (AOD) Retrievals

NASA Technical Reports Server (NTRS)

Chudnovsky, Alexandra A.; Koutrakis, Petros; Kloog, Itai; Melly, Steven; Nordio, Francesco; Lyapustin, Alexei; Wang, Jujie; Schwartz, Joel

2014-01-01

To date, spatial-temporal patterns of particulate matter (PM) within urban areas have primarily been examined using models. On the other hand, satellites extend spatial coverage but their spatial resolution is too coarse. In order to address this issue, here we report on spatial variability in PM levels derived from high 1 km resolution AOD product of Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm developed for MODIS satellite. We apply day-specific calibrations of AOD data to predict PM(sub 2.5) concentrations within the New England area of the United States. To improve the accuracy of our model, land use and meteorological variables were incorporated. We used inverse probability weighting (IPW) to account for nonrandom missingness of AOD and nested regions within days to capture spatial variation. With this approach we can control for the inherent day-to-day variability in the AOD-PM(sub 2.5) relationship, which depends on time-varying parameters such as particle optical properties, vertical and diurnal concentration profiles and ground surface reflectance among others. Out-of-sample "ten-fold" cross-validation was used to quantify the accuracy of model predictions. Our results show that the model-predicted PM(sub 2.5) mass concentrations are highly correlated with the actual observations, with out-of- sample R(sub 2) of 0.89. Furthermore, our study shows that the model captures the pollution levels along highways and many urban locations thereby extending our ability to investigate the spatial patterns of urban air quality, such as examining exposures in areas with high traffic. Our results also show high accuracy within the cities of Boston and New Haven thereby indicating that MAIAC data can be used to examine intra-urban exposure contrasts in PM(sub 2.5) levels.

SUMER: Solar Ultraviolet Measurements of Emitted Radiation

NASA Technical Reports Server (NTRS)

Wilhelm, K.; Axford, W. I.; Curdt, W.; Gabriel, A. H.; Grewing, M.; Huber, M. C. E.; Jordan, S. D.; Kuehne, M.; Lemaire, P.; Marsch, E.

1992-01-01

The experiment Solar Ultraviolet Measurements of Emitted Radiation (SUMER) is designed for the investigations of plasma flow characteristics, turbulence and wave motions, plasma densities and temperatures, structures and events associated with solar magnetic activity in the chromosphere, the transition zone and the corona. Specifically, SUMER will measure profiles and intensities of Extreme Ultraviolet (EUV) lines emitted in the solar atmosphere ranging from the upper chromosphere to the lower corona; determine line broadenings, spectral positions and Doppler shifts with high accuracy, provide stigmatic images of selected areas of the Sun in the EUV with high spatial, temporal and spectral resolution and obtain full images of the Sun and the inner corona in selectable EUV lines, corresponding to a temperature from 10,000 to more than 1,800,000 K.

Improved Estimation of Electron Temperature from Rocket-borne Impedance Probes

NASA Astrophysics Data System (ADS)

Rowland, D. E.; Wolfinger, K.; Stamm, J. D.

2017-12-01

The impedance probe technique is a well known method for determining high accuracy measurements of electron number density in the Earth's ionosphere. We present analysis of impedance probe data from several sounding rockets at low, mid-, and auroral latitudes, including high cadence estimates of the electron temperature, derived from analytical fits to the antenna impedance curves. These estimates compare favorably with independent estimates from Langmuir Probes, but at much higher temporal and spatial resolution, providing a capability to resolve small-scale temperature fluctuations. We also present some considerations for the design of impedance probes, including assessment of the effects of resonance damping due to rocket motion, effects of wake and spin modulation, and aspect angle to the magnetic field.

The Pierre Auger Observatory scaler mode for the study of solar activity modulation of galactic cosmic rays

DOE Office of Scientific and Technical Information (OSTI.GOV)

Abreu, P.; /Lisbon, LIFEP /Lisbon, IST; Aglietta, M.

2011-01-01

Since data-taking began in January 2004, the Pierre Auger Observatory has been recording the count rates of low energy secondary cosmic ray particles for the self-calibration of the ground detectors of its surface detector array. After correcting for atmospheric effects, modulations of galactic cosmic rays due to solar activity and transient events are observed. Temporal variations related with the activity of the heliosphere can be determined with high accuracy due to the high total count rates. In this study, the available data are presented together with an analysis focused on the observation of Forbush decreases, where a strong correlation withmore » neutron monitor data is found.« less

Under-sampling trajectory design for compressed sensing based DCE-MRI.

PubMed

Liu, Duan-duan; Liang, Dong; Zhang, Na; Liu, Xin; Zhang, Yuan-ting

2013-01-01

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) needs high temporal and spatial resolution to accurately estimate quantitative parameters and characterize tumor vasculature. Compressed Sensing (CS) has the potential to accomplish this mutual importance. However, the randomness in CS under-sampling trajectory designed using the traditional variable density (VD) scheme may translate to uncertainty in kinetic parameter estimation when high reduction factors are used. Therefore, accurate parameter estimation using VD scheme usually needs multiple adjustments on parameters of Probability Density Function (PDF), and multiple reconstructions even with fixed PDF, which is inapplicable for DCE-MRI. In this paper, an under-sampling trajectory design which is robust to the change on PDF parameters and randomness with fixed PDF is studied. The strategy is to adaptively segment k-space into low-and high frequency domain, and only apply VD scheme in high-frequency domain. Simulation results demonstrate high accuracy and robustness comparing to VD design.

Modeling diurnal land temperature cycles over Los Angeles using downscaled GOES imagery

NASA Astrophysics Data System (ADS)

Weng, Qihao; Fu, Peng

2014-11-01

Land surface temperature is a key parameter for monitoring urban heat islands, assessing heat related risks, and estimating building energy consumption. These environmental issues are characterized by high temporal variability. A possible solution from the remote sensing perspective is to utilize geostationary satellites images, for instance, images from Geostationary Operational Environmental System (GOES) and Meteosat Second Generation (MSG). These satellite systems, however, with coarse spatial but high temporal resolution (sub-hourly imagery at 3-10 km resolution), often limit their usage to meteorological forecasting and global climate modeling. Therefore, how to develop efficient and effective methods to disaggregate these coarse resolution images to a proper scale suitable for regional and local studies need be explored. In this study, we propose a least square support vector machine (LSSVM) method to achieve the goal of downscaling of GOES image data to half-hourly 1-km LSTs by fusing it with MODIS data products and Shuttle Radar Topography Mission (SRTM) digital elevation data. The result of downscaling suggests that the proposed method successfully disaggregated GOES images to half-hourly 1-km LSTs with accuracy of approximately 2.5 K when validated against with MODIS LSTs at the same over-passing time. The synthetic LST datasets were further explored for monitoring of surface urban heat island (UHI) in the Los Angeles region by extracting key diurnal temperature cycle (DTC) parameters. It is found that the datasets and DTC derived parameters were more suitable for monitoring of daytime- other than nighttime-UHI. With the downscaled GOES 1-km LSTs, the diurnal temperature variations can well be characterized. An accuracy of about 2.5 K was achieved in terms of the fitted results at both 1 km and 5 km resolutions.

Mapping paddy rice planting area in cold temperate climate region through analysis of time series Landsat 8 (OLI), Landsat 7 (ETM+) and MODIS imagery

NASA Astrophysics Data System (ADS)

Qin, Yuanwei; Xiao, Xiangming; Dong, Jinwei; Zhou, Yuting; Zhu, Zhe; Zhang, Geli; Du, Guoming; Jin, Cui; Kou, Weili; Wang, Jie; Li, Xiangping

2015-07-01

Accurate and timely rice paddy field maps with a fine spatial resolution would greatly improve our understanding of the effects of paddy rice agriculture on greenhouse gases emissions, food and water security, and human health. Rice paddy field maps were developed using optical images with high temporal resolution and coarse spatial resolution (e.g., Moderate Resolution Imaging Spectroradiometer (MODIS)) or low temporal resolution and high spatial resolution (e.g., Landsat TM/ETM+). In the past, the accuracy and efficiency for rice paddy field mapping at fine spatial resolutions were limited by the poor data availability and image-based algorithms. In this paper, time series MODIS and Landsat ETM+/OLI images, and the pixel- and phenology-based algorithm are used to map paddy rice planting area. The unique physical features of rice paddy fields during the flooding/open-canopy period are captured with the dynamics of vegetation indices, which are then used to identify rice paddy fields. The algorithm is tested in the Sanjiang Plain (path/row 114/27) in China in 2013. The overall accuracy of the resulted map of paddy rice planting area generated by both Landsat ETM+ and OLI is 97.3%, when evaluated with areas of interest (AOIs) derived from geo-referenced field photos. The paddy rice planting area map also agrees reasonably well with the official statistics at the level of state farms (R2 = 0.94). These results demonstrate that the combination of fine spatial resolution images and the phenology-based algorithm can provide a simple, robust, and automated approach to map the distribution of paddy rice agriculture in a year.

Mapping paddy rice planting area in cold temperate climate region through analysis of time series Landsat 8 (OLI), Landsat 7 (ETM+) and MODIS imagery.

PubMed

Qin, Yuanwei; Xiao, Xiangming; Dong, Jinwei; Zhou, Yuting; Zhu, Zhe; Zhang, Geli; Du, Guoming; Jin, Cui; Kou, Weili; Wang, Jie; Li, Xiangping

2015-07-01

Accurate and timely rice paddy field maps with a fine spatial resolution would greatly improve our understanding of the effects of paddy rice agriculture on greenhouse gases emissions, food and water security, and human health. Rice paddy field maps were developed using optical images with high temporal resolution and coarse spatial resolution (e.g., Moderate Resolution Imaging Spectroradiometer (MODIS)) or low temporal resolution and high spatial resolution (e.g., Landsat TM/ETM+). In the past, the accuracy and efficiency for rice paddy field mapping at fine spatial resolutions were limited by the poor data availability and image-based algorithms. In this paper, time series MODIS and Landsat ETM+/OLI images, and the pixel- and phenology-based algorithm are used to map paddy rice planting area. The unique physical features of rice paddy fields during the flooding/open-canopy period are captured with the dynamics of vegetation indices, which are then used to identify rice paddy fields. The algorithm is tested in the Sanjiang Plain (path/row 114/27) in China in 2013. The overall accuracy of the resulted map of paddy rice planting area generated by both Landsat ETM+ and OLI is 97.3%, when evaluated with areas of interest (AOIs) derived from geo-referenced field photos. The paddy rice planting area map also agrees reasonably well with the official statistics at the level of state farms ( R 2 = 0.94). These results demonstrate that the combination of fine spatial resolution images and the phenology-based algorithm can provide a simple, robust, and automated approach to map the distribution of paddy rice agriculture in a year.

Temporal variations in soil moisture content and its influence on biomass estimates, observed by UAVSAR, ALOS PALSAR, and in-situ field data

NASA Astrophysics Data System (ADS)

Calderhead, A. I.; Simard, M.; Lavalle, M.

2010-12-01

Temporal changes of repeat-pass SAR backscatter over bare ground or forests results mostly from changes in the target's dielectric properties or moisture content; especially when the timescale is on the order of a few days or weeks. It is important to properly correct for moisture content when using SAR based estimates of tree height or biomass. The objective of this work is to quantify the error in biomass estimates associated with variations in moisture content in temperate and boreal forested areas. In addition, the accuracy of three polarimetric soil moisture surface inversion models (Dubois et al., 1995, Oh et al., 1992; Oh, 2004) are tested on UAVSAR and PALSAR data of bare soils in temperate and boreal forested areas. In addition to PALSAR data from 2007 to 2009, a JPL/UAVSAR campaign over parts of New England and Quebec was completed in August, 2009; L-band SAR images were acquired on August 5th, August 7th, and August 14th. In-situ soil moisture probes at three locations gathered hourly soil moisture content data. LVIS LIDAR is used for quantifying and classifying biomass ranges. Slope corrected backscatter values resampled to 1 hectare at HH, HV, and VV polarizations, and ratios thereof, are compared with soil moisture, precipitation, biomass, and incidence angle. It is seen that the backscatter for high biomass areas varies significantly due to moisture variations. An increase in 1% soil moisture content at the Laurentides field site leads to a change in HV backscatter of 1dB. Regions with high biomass do not vary uniformly with varying moisture content: this can be explained by saturation of the L-band at higher biomass levels. The three inversion algorithms produce varying results with the ‘Dubois et al’ inversion producing the best correlation at the Bartlett Forest site while the ‘Oh 2004’ inversion produces better results at the Laurentides site. Although the accuracy is often poor, the temporal variation of the moisture content for all three inversion algorithms is generally captured.

Underlying Skills of Oral and Silent Reading Fluency in Chinese: Perspective of Visual Rapid Processing

PubMed Central

Zhao, Jing; Kwok, Rosa K. W.; Liu, Menglian; Liu, Hanlong; Huang, Chen

2017-01-01

Reading fluency is a critical skill to improve the quality of our daily life and working efficiency. The majority of previous studies focused on oral reading fluency rather than silent reading fluency, which is a much more dominant reading mode that is used in middle and high school and for leisure reading. It is still unclear whether the oral and silent reading fluency involved the same underlying skills. To address this issue, the present study examined the relationship between the visual rapid processing and Chinese reading fluency in different modes. Fifty-eight undergraduate students took part in the experiment. The phantom contour paradigm and the visual 1-back task were adopted to measure the visual rapid temporal and simultaneous processing respectively. These two tasks reflected the temporal and spatial dimensions of visual rapid processing separately. We recorded the temporal threshold in the phantom contour task, as well as reaction time and accuracy in the visual 1-back task. Reading fluency was measured in both single-character and sentence levels. Fluent reading of single characters was assessed with a paper-and-pencil lexical decision task, and a sentence verification task was developed to examine reading fluency on a sentence level. The reading fluency test in each level was conducted twice (i.e., oral reading and silent reading). Reading speed and accuracy were recorded. The correlation analysis showed that the temporal threshold in the phantom contour task did not correlate with the scores of the reading fluency tests. Although, the reaction time in visual 1-back task correlated with the reading speed of both oral and silent reading fluency, the comparison of the correlation coefficients revealed a closer relationship between the visual rapid simultaneous processing and silent reading. Furthermore, the visual rapid simultaneous processing exhibited a significant contribution to reading fluency in silent mode but not in oral reading mode. These findings suggest that the underlying mechanism between oral and silent reading fluency is different at the beginning of the basic visual coding. The current results also might reveal a potential modulation of the language characteristics of Chinese on the relationship between visual rapid processing and reading fluency. PMID:28119663

Underlying Skills of Oral and Silent Reading Fluency in Chinese: Perspective of Visual Rapid Processing.

PubMed

Zhao, Jing; Kwok, Rosa K W; Liu, Menglian; Liu, Hanlong; Huang, Chen

2016-01-01

Reading fluency is a critical skill to improve the quality of our daily life and working efficiency. The majority of previous studies focused on oral reading fluency rather than silent reading fluency, which is a much more dominant reading mode that is used in middle and high school and for leisure reading. It is still unclear whether the oral and silent reading fluency involved the same underlying skills. To address this issue, the present study examined the relationship between the visual rapid processing and Chinese reading fluency in different modes. Fifty-eight undergraduate students took part in the experiment. The phantom contour paradigm and the visual 1-back task were adopted to measure the visual rapid temporal and simultaneous processing respectively. These two tasks reflected the temporal and spatial dimensions of visual rapid processing separately. We recorded the temporal threshold in the phantom contour task, as well as reaction time and accuracy in the visual 1-back task. Reading fluency was measured in both single-character and sentence levels. Fluent reading of single characters was assessed with a paper-and-pencil lexical decision task, and a sentence verification task was developed to examine reading fluency on a sentence level. The reading fluency test in each level was conducted twice (i.e., oral reading and silent reading). Reading speed and accuracy were recorded. The correlation analysis showed that the temporal threshold in the phantom contour task did not correlate with the scores of the reading fluency tests. Although, the reaction time in visual 1-back task correlated with the reading speed of both oral and silent reading fluency, the comparison of the correlation coefficients revealed a closer relationship between the visual rapid simultaneous processing and silent reading. Furthermore, the visual rapid simultaneous processing exhibited a significant contribution to reading fluency in silent mode but not in oral reading mode. These findings suggest that the underlying mechanism between oral and silent reading fluency is different at the beginning of the basic visual coding. The current results also might reveal a potential modulation of the language characteristics of Chinese on the relationship between visual rapid processing and reading fluency.

Streak camera based SLR receiver for two color atmospheric measurements

NASA Technical Reports Server (NTRS)

Varghese, Thomas K.; Clarke, Christopher; Oldham, Thomas; Selden, Michael

1993-01-01

To realize accurate two-color differential measurements, an image digitizing system with variable spatial resolution was designed, built, and integrated to a photon-counting picosecond streak camera, yielding a temporal scan resolution better than 300 femtosecond/pixel. The streak camera is configured to operate with 3 spatial channels; two of these support green (532 nm) and uv (355 nm) while the third accommodates reference pulses (764 nm) for real-time calibration. Critical parameters affecting differential timing accuracy such as pulse width and shape, number of received photons, streak camera/imaging system nonlinearities, dynamic range, and noise characteristics were investigated to optimize the system for accurate differential delay measurements. The streak camera output image consists of three image fields, each field is 1024 pixels along the time axis and 16 pixels across the spatial axis. Each of the image fields may be independently positioned across the spatial axis. Two of the image fields are used for the two wavelengths used in the experiment; the third window measures the temporal separation of a pair of diode laser pulses which verify the streak camera sweep speed for each data frame. The sum of the 16 pixel intensities across each of the 1024 temporal positions for the three data windows is used to extract the three waveforms. The waveform data is processed using an iterative three-point running average filter (10 to 30 iterations are used) to remove high-frequency structure. The pulse pair separations are determined using the half-max and centroid type analysis. Rigorous experimental verification has demonstrated that this simplified process provides the best measurement accuracy. To calibrate the receiver system sweep, two laser pulses with precisely known temporal separation are scanned along the full length of the sweep axis. The experimental measurements are then modeled using polynomial regression to obtain a best fit to the data. Data aggregation using normal point approach has provided accurate data fitting techniques and is found to be much more convenient than using the full rate single shot data. The systematic errors from this model have been found to be less than 3 ps for normal points.

High Spatio-Temporal Resolution Bathymetry Estimation and Morphology

NASA Astrophysics Data System (ADS)

Bergsma, E. W. J.; Conley, D. C.; Davidson, M. A.; O'Hare, T. J.

2015-12-01

In recent years, bathymetry estimates using video images have become increasingly accurate. With the cBathy code (Holman et al., 2013) fully operational, bathymetry results with 0.5 metres accuracy have been regularly obtained at Duck, USA. cBathy is based on observations of the dominant frequencies and wavelengths of surface wave motions and estimates the depth (and hence allows inference of bathymetry profiles) based on linear wave theory. Despite the good performance at Duck, large discrepancies were found related to tidal elevation and camera height (Bergsma et al., 2014) and on the camera boundaries. A tide dependent floating pixel and camera boundary solution have been proposed to overcome these issues (Bergsma et al., under review). The video-data collection is set estimate depths hourly on a grid with resolution in the order of 10x25 meters. Here, the application of the cBathy at Porthtowan in the South-West of England is presented. Hourly depth estimates are combined and analysed over a period of 1.5 years (2013-2014). In this work the focus is on the sub-tidal region, where the best cBathy results are achieved. The morphology of the sub-tidal bar is tracked with high spatio-temporal resolution on short and longer time scales. Furthermore, the impact of the storm and reset (sudden and large changes in bathymetry) of the sub-tidal area is clearly captured with the depth estimations. This application shows that the high spatio-temporal resolution of cBathy makes it a powerful tool for coastal research and coastal zone management.

High-speed holographic system for full-field transient vibrometry of the human tympanic membrane

NASA Astrophysics Data System (ADS)

Dobrev, I.; Harrington, E. J.; Cheng, T.; Furlong, C.; Rosowski, J. J.

2014-07-01

Understanding of the human hearing process requires the quantification of the transient response of the human ear and the human tympanic membrane (TM or eardrum) in particular. Current state-of-the-art medical methods to quantify the transient acousto-mechanical response of the TM provide only averaged acoustic or local information at a few points. This may be insufficient to fully describe the complex patterns unfolding across the full surface of the TM. Existing engineering systems for full-field nanometer measurements of transient events, typically based on holographic methods, constrain the maximum sampling speed and/or require complex experimental setups. We have developed and implemented of a new high-speed (i.e., > 40 Kfps) holographic system (HHS) with a hybrid spatio-temporal local correlation phase sampling method that allows quantification of the full-field nanometer transient (i.e., > 10 kHz) displacement of the human TM. The HHS temporal accuracy and resolution is validated versus a LDV on both artificial membranes and human TMs. The high temporal (i.e., < 24 μs) and spatial (i.e., >100k data points) resolution of our HHS enables simultaneous measurement of the time waveform of the full surface of the TM. These capabilities allow for quantification of spatially-dependent motion parameters such as energy propagation delays surface wave speeds, which can be used to infer local material properties across the surface of the TM. The HHS could provide a new tool for the investigation of the auditory system with applications in medical research, in-vivo clinical diagnosis as well as hearing aids design.

Monitoring gait in multiple sclerosis with novel wearable motion sensors.

PubMed

Moon, Yaejin; McGinnis, Ryan S; Seagers, Kirsten; Motl, Robert W; Sheth, Nirav; Wright, John A; Ghaffari, Roozbeh; Sosnoff, Jacob J

2017-01-01

Mobility impairment is common in people with multiple sclerosis (PwMS) and there is a need to assess mobility in remote settings. Here, we apply a novel wireless, skin-mounted, and conformal inertial sensor (BioStampRC, MC10 Inc.) to examine gait characteristics of PwMS under controlled conditions. We determine the accuracy and precision of BioStampRC in measuring gait kinematics by comparing to contemporary research-grade measurement devices. A total of 45 PwMS, who presented with diverse walking impairment (Mild MS = 15, Moderate MS = 15, Severe MS = 15), and 15 healthy control subjects participated in the study. Participants completed a series of clinical walking tests. During the tests participants were instrumented with BioStampRC and MTx (Xsens, Inc.) sensors on their shanks, as well as an activity monitor GT3X (Actigraph, Inc.) on their non-dominant hip. Shank angular velocity was simultaneously measured with the inertial sensors. Step number and temporal gait parameters were calculated from the data recorded by each sensor. Visual inspection and the MTx served as the reference standards for computing the step number and temporal parameters, respectively. Accuracy (error) and precision (variance of error) was assessed based on absolute and relative metrics. Temporal parameters were compared across groups using ANOVA. Mean accuracy±precision for the BioStampRC was 2±2 steps error for step number, 6±9ms error for stride time and 6±7ms error for step time (0.6-2.6% relative error). Swing time had the least accuracy±precision (25±19ms error, 5±4% relative error) among the parameters. GT3X had the least accuracy±precision (8±14% relative error) in step number estimate among the devices. Both MTx and BioStampRC detected significantly distinct gait characteristics between PwMS with different disability levels (p<0.01). BioStampRC sensors accurately and precisely measure gait parameters in PwMS across diverse walking impairment levels and detected differences in gait characteristics by disability level in PwMS. This technology has the potential to provide granular monitoring of gait both inside and outside the clinic.

Classification of motor intent in transradial amputees using sonomyography and spatio-temporal image analysis

NASA Astrophysics Data System (ADS)

Hariharan, Harishwaran; Aklaghi, Nima; Baker, Clayton A.; Rangwala, Huzefa; Kosecka, Jana; Sikdar, Siddhartha

2016-04-01

In spite of major advances in biomechanical design of upper extremity prosthetics, these devices continue to lack intuitive control. Conventional myoelectric control strategies typically utilize electromyography (EMG) signal amplitude sensed from forearm muscles. EMG has limited specificity in resolving deep muscle activity and poor signal-to-noise ratio. We have been investigating alternative control strategies that rely on real-time ultrasound imaging that can overcome many of the limitations of EMG. In this work, we present an ultrasound image sequence classification method that utilizes spatiotemporal features to describe muscle activity and classify motor intent. Ultrasound images of the forearm muscles were obtained from able-bodied subjects and a trans-radial amputee while they attempted different hand movements. A grid-based approach is used to test the feasibility of using spatio-temporal features by classifying hand motions performed by the subjects. Using the leave-one-out cross validation on image sequences acquired from able-bodied subjects, we observe that the grid-based approach is able to discern four hand motions with 95.31% accuracy. In case of the trans-radial amputee, we are able to discern three hand motions with 80% accuracy. In a second set of experiments, we study classification accuracy by extracting spatio-temporal sub-sequences the depict activity due to the motion of local anatomical interfaces. Short time and space limited cuboidal sequences are initially extracted and assigned an optical flow behavior label, based on a response function. The image space is clustered based on the location of cuboids and features calculated from the cuboids in each cluster. Using sequences of known motions, we extract feature vectors that describe said motion. A K-nearest neighbor classifier is designed for classification experiments. Using the leave-one-out cross validation on image sequences for an amputee subject, we demonstrate that the classifier is able to discern three important hand motions with an accuracy of 93.33% accuracy, 91-100% precision and 80-100% recall rate. We anticipate that ultrasound imaging based methods will address some limitations of conventional myoelectric sensing, while adding advantages inherent to ultrasound imaging.

Continuous monitoring bed-level dynamics on an intertidal flat: introducing novel stand-alone high-resolution SED-sensors

NASA Astrophysics Data System (ADS)

Hu, Zhan; Lenting, Walther; van der Wal, Daphne; Bouma, Tjeerd

2015-04-01

Tidal flat morphology is continuously shaped by hydrodynamic force, resulting in highly dynamic bed elevations. The knowledge of short-term bed-level changes is important both for understanding sediment transport processes as well as for assessing critical ecological processes such as e.g. vegetation recruitment chances on tidal flats. Due to the labour involved, manual discontinuous measurements lack the ability to continuously monitor bed-elevation changes. Existing methods for automated continuous monitoring of bed-level changes lack vertical accuracy (e.g., Photo-Electronic Erosion Pin sensor and resistive rod) or limited in spatial application by using expensive technology (e.g., acoustic bed level sensors). A method provides sufficient accuracy with a reasonable cost is needed. In light of this, a high-accuracy sensor (2 mm) for continuously measuring short-term Surface-Elevation Dynamics (SED-sensor) was developed. This SED-sensor makes use of photovoltaic cells and operates stand-alone using internal power supply and data logging system. The unit cost and the labour in deployments is therefore reduced, which facilitates monitoring with a number of units. In this study, the performance of a group of SED-sensors is tested against data obtained with precise manual measurements using traditional Sediment Erosion Bars (SEB). An excellent agreement between the two methods was obtained, indicating the accuracy and precision of the SED-sensors. Furthermore, to demonstrate how the SED-sensors can be used for measuring short-term bed-level dynamics, two SED-sensors were deployed for 1 month at two sites with contrasting wave exposure conditions. Daily bed-level changes were obtained including a severe storm erosion event. The difference in observed bed-level dynamics at both sites was statistically explained by their different hydrodynamic conditions. Thus, the stand-alone SED-sensor can be applied to monitor sediment surface dynamics with high vertical and temporal resolutions, which provides opportunities to pinpoint morphological responses to various forces in a number of environments (e.g. tidal flats, beaches, rivers and dunes).

CLAAS: the CM SAF cloud property dataset using SEVIRI

NASA Astrophysics Data System (ADS)

Stengel, M.; Kniffka, A.; Meirink, J. F.; Lockhoff, M.; Tan, J.; Hollmann, R.

2013-10-01

An 8 yr record of satellite based cloud properties named CLAAS (CLoud property dAtAset using SEVIRI) is presented, which was derived within the EUMETSAT Satellite Application Facility on Climate Monitoring. The dataset is based on SEVIRI measurements of the Meteosat Second Generation satellites, of which the visible and near-infrared channels were intercalibrated with MODIS. Including latest development components of the two applied state-of-the-art retrieval schemes ensure high accuracy in cloud detection, cloud vertical placement and microphysical cloud properties. These properties were further processed to provide daily to monthly averaged quantities, mean diurnal cycles and monthly histograms. In particular the collected histogram information enhance the insight in spatio-temporal variability of clouds and their properties. Due to the underlying intercalibrated measurement record, the stability of the derived cloud properties is ensured, which is exemplarily demonstrated for three selected cloud variables for the entire SEVIRI disk and a European subregion. All data products and processing levels are introduced and validation results indicated. The sampling uncertainty of the averaged products in CLAAS is minimized due to the high temporal resolution of SEVIRI. This is emphasized by studying the impact of reduced temporal sampling rates taken at typical overpass times of polar-orbiting instruments. In particular cloud optical thickness and cloud water path are very sensitive to the sampling rate, which in our study amounted to systematic deviations of over 10% if only sampled once a day. The CLAAS dataset facilitates many cloud related applications at small spatial scales of a few kilometres and short temporal scales of a few hours. Beyond this, the spatiotemporal characteristics of clouds on diurnal to seasonal, but also on multi-annual scales, can be studied.

CLAAS: the CM SAF cloud property data set using SEVIRI

NASA Astrophysics Data System (ADS)

Stengel, M. S.; Kniffka, A. K.; Meirink, J. F. M.; Lockhoff, M. L.; Tan, J. T.; Hollmann, R. H.

2014-04-01

An 8-year record of satellite-based cloud properties named CLAAS (CLoud property dAtAset using SEVIRI) is presented, which was derived within the EUMETSAT Satellite Application Facility on Climate Monitoring. The data set is based on SEVIRI measurements of the Meteosat Second Generation satellites, of which the visible and near-infrared channels were intercalibrated with MODIS. Applying two state-of-the-art retrieval schemes ensures high accuracy in cloud detection, cloud vertical placement and microphysical cloud properties. These properties were further processed to provide daily to monthly averaged quantities, mean diurnal cycles and monthly histograms. In particular, the per-month histogram information enhances the insight in spatio-temporal variability of clouds and their properties. Due to the underlying intercalibrated measurement record, the stability of the derived cloud properties is ensured, which is exemplarily demonstrated for three selected cloud variables for the entire SEVIRI disc and a European subregion. All data products and processing levels are introduced and validation results indicated. The sampling uncertainty of the averaged products in CLAAS is minimized due to the high temporal resolution of SEVIRI. This is emphasized by studying the impact of reduced temporal sampling rates taken at typical overpass times of polar-orbiting instruments. In particular, cloud optical thickness and cloud water path are very sensitive to the sampling rate, which in our study amounted to systematic deviations of over 10% if only sampled once a day. The CLAAS data set facilitates many cloud related applications at small spatial scales of a few kilometres and short temporal scales of a~few hours. Beyond this, the spatiotemporal characteristics of clouds on diurnal to seasonal, but also on multi-annual scales, can be studied.

Measuring orthometric water heights from lightweight Unmanned Aerial Vehicles (UAVs)

NASA Astrophysics Data System (ADS)

Bandini, Filippo; Olesen, Daniel; Jakobsen, Jakob; Reyna-Gutierrez, Jose Antonio; Bauer-Gottwein, Peter

2016-04-01

A better quantitative understanding of hydrologic processes requires better observations of hydrological variables, such as surface water area, water surface level, its slope and its temporal change. However, ground-based measurements of water heights are restricted to the in-situ measuring stations. Hence, the objective of remote sensing hydrology is to retrieve these hydraulic variables from spaceborne and airborne platforms. The forthcoming Surface Water and Ocean Topography (SWOT) satellite mission will be able to acquire water heights with an expected accuracy of 10 centimeters for rivers that are at least 100 m wide. Nevertheless, spaceborne missions will always face the limitations of: i) a low spatial resolution which makes it difficult to separate water from interfering surrounding areas and a tracking of the terrestrial water bodies not able to detect water heights in small rivers or lakes; ii) a limited temporal resolution which limits the ability to determine rapid temporal changes, especially during extremes. Unmanned Aerial Vehicles (UAVs) are one technology able to fill the gap between spaceborne and ground-based observations, ensuring 1) high spatial resolution; 2) tracking of the water bodies better than any satellite technology; 3) timing of the sampling which only depends on the operator 4) flexibility of the payload. Hence, this study focused on categorizing and testing sensors capable of measuring the range between the UAV and the water surface. The orthometric height of the water surface is then retrieved by subtracting the height above water measured by the sensors from the altitude above sea level retrieved by the onboard GPS. The following sensors were tested: a) a radar, b) a sonar c) a laser digital-camera based prototype developed at Technical University of Denmark. The tested sensors comply with the weight constraint of small UAVs (around 1.5 kg). The sensors were evaluated in terms of accuracy, maximum ranging distance and beam divergence. The sonar demonstrated a maximum ranging distance of 10 m, the laser prototype of 15 m, whilst the radar is potentially able to measure the range to water surface from a height up to 50 m. After numerous test flights above a lake with an approximately horizontal water surface, estimation of orthometric water height error, including overall accuracy of the system GPS-sensors, was possible. The RTK GPS system proved able to deliver a relative vertical accuracy better than 5-7 cm. The radar confirmed to have the best reliability with an accuracy which is generally few cm (0.7-1.3% of the ranging distance). Whereas the accuracy of the sonar and laser varies from few cm (0.7-1.6% of the ranging distance) to some tens of cm because sonar measurements are generally influenced by noise and turbulence generated by the propellers of the UAV and the laser prototype is affected by drone vibrations and water waviness. However, the laser prototype demonstrated the lowest beam divergence, which is required to measure unconventional remote sensing targets, such as sinkholes and Mexican cenotes, and to clearly distinguish between rivers and interfering surroundings, such as riparian vegetation.

MR-assisted PET Motion Correction for eurological Studies in an Integrated MR-PET Scanner

PubMed Central

Catana, Ciprian; Benner, Thomas; van der Kouwe, Andre; Byars, Larry; Hamm, Michael; Chonde, Daniel B.; Michel, Christian J.; El Fakhri, Georges; Schmand, Matthias; Sorensen, A. Gregory

2011-01-01

Head motion is difficult to avoid in long PET studies, degrading the image quality and offsetting the benefit of using a high-resolution scanner. As a potential solution in an integrated MR-PET scanner, the simultaneously acquired MR data can be used for motion tracking. In this work, a novel data processing and rigid-body motion correction (MC) algorithm for the MR-compatible BrainPET prototype scanner is described and proof-of-principle phantom and human studies are presented. Methods To account for motion, the PET prompts and randoms coincidences as well as the sensitivity data are processed in the line or response (LOR) space according to the MR-derived motion estimates. After sinogram space rebinning, the corrected data are summed and the motion corrected PET volume is reconstructed from these sinograms and the attenuation and scatter sinograms in the reference position. The accuracy of the MC algorithm was first tested using a Hoffman phantom. Next, human volunteer studies were performed and motion estimates were obtained using two high temporal resolution MR-based motion tracking techniques. Results After accounting for the physical mismatch between the two scanners, perfectly co-registered MR and PET volumes are reproducibly obtained. The MR output gates inserted in to the PET list-mode allow the temporal correlation of the two data sets within 0.2 s. The Hoffman phantom volume reconstructed processing the PET data in the LOR space was similar to the one obtained processing the data using the standard methods and applying the MC in the image space, demonstrating the quantitative accuracy of the novel MC algorithm. In human volunteer studies, motion estimates were obtained from echo planar imaging and cloverleaf navigator sequences every 3 seconds and 20 ms, respectively. Substantially improved PET images with excellent delineation of specific brain structures were obtained after applying the MC using these MR-based estimates. Conclusion A novel MR-based MC algorithm was developed for the integrated MR-PET scanner. High temporal resolution MR-derived motion estimates (obtained while simultaneously acquiring anatomical or functional MR data) can be used for PET MC. An MR-based MC has the potential to improve PET as a quantitative method, increasing its reliability and reproducibility which could benefit a large number of neurological applications. PMID:21189415

Accuracy of an unstructured-grid upwind-Euler algorithm for the ONERA M6 wing

NASA Technical Reports Server (NTRS)

Batina, John T.

1991-01-01

Improved algorithms for the solution of the three-dimensional, time-dependent Euler equations are presented for aerodynamic analysis involving unstructured dynamic meshes. The improvements have been developed recently to the spatial and temporal discretizations used by unstructured-grid flow solvers. The spatial discretization involves a flux-split approach that is naturally dissipative and captures shock waves sharply with at most one grid point within the shock structure. The temporal discretization involves either an explicit time-integration scheme using a multistage Runge-Kutta procedure or an implicit time-integration scheme using a Gauss-Seidel relaxation procedure, which is computationally efficient for either steady or unsteady flow problems. With the implicit Gauss-Seidel procedure, very large time steps may be used for rapid convergence to steady state, and the step size for unsteady cases may be selected for temporal accuracy rather than for numerical stability. Steady flow results are presented for both the NACA 0012 airfoil and the Office National d'Etudes et de Recherches Aerospatiales M6 wing to demonstrate applications of the new Euler solvers. The paper presents a description of the Euler solvers along with results and comparisons that assess the capability.

Exogenous temporal cues enhance recognition memory in an object-based manner.

PubMed

Ohyama, Junji; Watanabe, Katsumi

2010-11-01

Exogenous attention enhances the perception of attended items in both a space-based and an object-based manner. Exogenous attention also improves recognition memory for attended items in the space-based mode. However, it has not been examined whether object-based exogenous attention enhances recognition memory. To address this issue, we examined whether a sudden visual change in a task-irrelevant stimulus (an exogenous cue) would affect participants' recognition memory for items that were serially presented around a cued time. The results showed that recognition accuracy for an item was strongly enhanced when the visual cue occurred at the same location and time as the item (Experiments 1 and 2). The memory enhancement effect occurred when the exogenous visual cue and an item belonged to the same object (Experiments 3 and 4) and even when the cue was counterpredictive of the timing of an item to be asked about (Experiment 5). The present study suggests that an exogenous temporal cue automatically enhances the recognition accuracy for an item that is presented at close temporal proximity to the cue and that recognition memory enhancement occurs in an object-based manner.

Quantification of EEG reactivity in comatose patients

PubMed Central

Hermans, Mathilde C.; Westover, M. Brandon; van Putten, Michel J.A.M.; Hirsch, Lawrence J.; Gaspard, Nicolas

2016-01-01

Objective EEG reactivity is an important predictor of outcome in comatose patients. However, visual analysis of reactivity is prone to subjectivity and may benefit from quantitative approaches. Methods In EEG segments recorded during reactivity testing in 59 comatose patients, 13 quantitative EEG parameters were used to compare the spectral characteristics of 1-minute segments before and after the onset of stimulation (spectral temporal symmetry). Reactivity was quantified with probability values estimated using combinations of these parameters. The accuracy of probability values as a reactivity classifier was evaluated against the consensus assessment of three expert clinical electroencephalographers using visual analysis. Results The binary classifier assessing spectral temporal symmetry in four frequency bands (delta, theta, alpha and beta) showed best accuracy (Median AUC: 0.95) and was accompanied by substantial agreement with the individual opinion of experts (Gwet’s AC1: 65–70%), at least as good as inter-expert agreement (AC1: 55%). Probability values also reflected the degree of reactivity, as measured by the inter-experts’ agreement regarding reactivity for each individual case. Conclusion Automated quantitative EEG approaches based on probabilistic description of spectral temporal symmetry reliably quantify EEG reactivity. Significance Quantitative EEG may be useful for evaluating reactivity in comatose patients, offering increased objectivity. PMID:26183757

Individual Differences in Rhythmic Cortical Entrainment Correlate with Predictive Behavior in Sensorimotor Synchronization

PubMed Central

Nozaradan, Sylvie; Peretz, Isabelle; Keller, Peter E.

2016-01-01

The current study aims at characterizing the mechanisms that allow humans to entrain the mind and body to incoming rhythmic sensory inputs in real time. We addressed this unresolved issue by examining the relationship between covert neural processes and overt behavior in the context of musical rhythm. We measured temporal prediction abilities, sensorimotor synchronization accuracy and neural entrainment to auditory rhythms as captured using an EEG frequency-tagging approach. Importantly, movement synchronization accuracy with a rhythmic beat could be explained by the amplitude of neural activity selectively locked with the beat period when listening to the rhythmic inputs. Furthermore, stronger endogenous neural entrainment at the beat frequency was associated with superior temporal prediction abilities. Together, these results reveal a direct link between cortical and behavioral measures of rhythmic entrainment, thus providing evidence that frequency-tagged brain activity has functional relevance for beat perception and synchronization. PMID:26847160

Individual Differences in Rhythmic Cortical Entrainment Correlate with Predictive Behavior in Sensorimotor Synchronization.

PubMed

Nozaradan, Sylvie; Peretz, Isabelle; Keller, Peter E

2016-02-05

The current study aims at characterizing the mechanisms that allow humans to entrain the mind and body to incoming rhythmic sensory inputs in real time. We addressed this unresolved issue by examining the relationship between covert neural processes and overt behavior in the context of musical rhythm. We measured temporal prediction abilities, sensorimotor synchronization accuracy and neural entrainment to auditory rhythms as captured using an EEG frequency-tagging approach. Importantly, movement synchronization accuracy with a rhythmic beat could be explained by the amplitude of neural activity selectively locked with the beat period when listening to the rhythmic inputs. Furthermore, stronger endogenous neural entrainment at the beat frequency was associated with superior temporal prediction abilities. Together, these results reveal a direct link between cortical and behavioral measures of rhythmic entrainment, thus providing evidence that frequency-tagged brain activity has functional relevance for beat perception and synchronization.

Earth Rotation Dynamics: Review and Prospects

NASA Technical Reports Server (NTRS)

Chao, Benjamin F.

2004-01-01

Modem space geodetic measurement of Earth rotation variations, particularly by means of the VLBI technique, has over the years allowed studies of Earth rotation dynamics to advance in ever-increasing precision, accuracy, and temporal resolution. A review will be presented on our understanding of the geophysical and climatic causes, or "excitations", for length-of-day change, polar motion, and nutations. These excitations sources come from mass transports that constantly take place in the Earth system comprised of the atmosphere, hydrosphere, cryosphere, lithosphere, mantle, and the cores. In this sense, together with other space geodetic measurements of time-variable gravity and geocenter motion, Earth rotation variations become a remote-sensing tool for the integral of all mass transports, providing valuable information about the latter on a wide range of spatial and temporal scales. Future prospects with respect to geophysical studies with even higher accuracy and resolution will be discussed.

The Lambert-Beer law in time domain form and its application.

PubMed

Mosorov, Volodymyr

2017-10-01

The majority of current radioisotope gauges utilize measurements of intensity for a chosen sampling time interval using a detector. Such an approach has several disadvantages: temporal resolution of the gauge is fixed and the accuracy of the measurements is not the same for different count rate. The solution can be the use of a stronger radioactive source, but it will be conflicted with ALARA (As Low As Reasonably Achievable) principle. Therefore, the article presents an alternative approach which is based on modified Lambert-Beer law. The basis of the approach is the registration of time intervals instead of the registration of counts. It allows to increase the temporal resolution of a gauge without the necessity of using a stronger radioactive source and the accuracy of the measurements will not depend on count rate. Copyright © 2017 Elsevier Ltd. All rights reserved.

Perception of time in microgravity and hypergravity during parabolic flight.

PubMed

Clément, Gilles

2018-03-07

We explored the effect of gravity on the accuracy for estimating durations of 3.5, 7, and 14 s. Experiments were performed on board an Airbus A310 during parabolic flights eliciting repeated exposures to short periods of 0, 1, and 1.8 g. Two methods for obtaining duration estimates were used, reproduction and production of duration, in two conditions: a control counting condition and a concurrent reading condition. Simple reaction times were also measured to assess attention. The results showed that the temporal accuracies during the reproduction task in the concurrent reading condition were significantly underestimated in 0 g compared with 1 g. Reaction times were also longer in 0 g. However, there was no difference in duration estimates in the production tasks. These results suggest that the temporal underestimation in 0 g is caused by decreased selective attention and impaired retrieval of information in episodic memory.

The Temporal Dynamics of Visual Search: Evidence for Parallel Processing in Feature and Conjunction Searches

PubMed Central

McElree, Brian; Carrasco, Marisa

2012-01-01

Feature and conjunction searches have been argued to delineate parallel and serial operations in visual processing. The authors evaluated this claim by examining the temporal dynamics of the detection of features and conjunctions. The 1st experiment used a reaction time (RT) task to replicate standard mean RT patterns and to examine the shapes of the RT distributions. The 2nd experiment used the response-signal speed–accuracy trade-off (SAT) procedure to measure discrimination (asymptotic detection accuracy) and detection speed (processing dynamics). Set size affected discrimination in both feature and conjunction searches but affected detection speed only in the latter. Fits of models to the SAT data that included a serial component overpredicted the magnitude of the observed dynamics differences. The authors concluded that both features and conjunctions are detected in parallel. Implications for the role of attention in visual processing are discussed. PMID:10641310

On the correct use of stepped-sine excitations for the measurement of time-varying bioimpedance.

PubMed

Louarroudi, E; Sanchez, B

2017-02-01

When a linear time-varying (LTV) bioimpedance is measured using stepped-sine excitations, a compromise must be made: the temporal distortions affecting the data depend on the experimental time, which in turn sets the data accuracy and limits the temporal bandwidth of the system that needs to be measured. Here, the experimental time required to measure linear time-invariant bioimpedance with a specified accuracy is analyzed for different stepped-sine excitation setups. We provide simple equations that allow the reader to know whether LTV bioimpedance can be measured through repeated time- invariant stepped-sine experiments. Bioimpedance technology is on the rise thanks to a plethora of healthcare monitoring applications. The results presented can help to avoid distortions in the data while measuring accurately non-stationary physiological phenomena. The impact of the work presented is broad, including the potential of enhancing bioimpedance studies and healthcare devices using bioimpedance technology.

Earth Rotational Variations Excited by Geophysical Fluids

NASA Technical Reports Server (NTRS)

Chao, Benjamin F.

2004-01-01

Modern space geodetic measurement of Earth rotation variations, particularly by means of the VLBI technique, has over the years allowed studies of Earth rotation dynamics to advance in ever-increasing precision, accuracy, and temporal resolution. A review will be presented on our understanding of the geophysical and climatic causes, or "excitations". for length-of-day change, polar motion, and nutations. These excitations sources come from mass transports that constantly take place in the Earth system comprised of the atmosphere, hydrosphere, cryosphere, lithosphere, mantle, and the cores. In this sense, together with other space geodetic measurements of time-variable gravity and geocenter motion, Earth rotation variations become a remote-sensing tool for the integral of all mass transports, providing valuable information about the latter on a wide range of spatial and temporal scales. Future prospects with respect to geophysical studies with even higher accuracy and resolution will be discussed.

Supervised Learning in Spiking Neural Networks for Precise Temporal Encoding

PubMed Central

Gardner, Brian; Grüning, André

2016-01-01

Precise spike timing as a means to encode information in neural networks is biologically supported, and is advantageous over frequency-based codes by processing input features on a much shorter time-scale. For these reasons, much recent attention has been focused on the development of supervised learning rules for spiking neural networks that utilise a temporal coding scheme. However, despite significant progress in this area, there still lack rules that have a theoretical basis, and yet can be considered biologically relevant. Here we examine the general conditions under which synaptic plasticity most effectively takes place to support the supervised learning of a precise temporal code. As part of our analysis we examine two spike-based learning methods: one of which relies on an instantaneous error signal to modify synaptic weights in a network (INST rule), and the other one relying on a filtered error signal for smoother synaptic weight modifications (FILT rule). We test the accuracy of the solutions provided by each rule with respect to their temporal encoding precision, and then measure the maximum number of input patterns they can learn to memorise using the precise timings of individual spikes as an indication of their storage capacity. Our results demonstrate the high performance of the FILT rule in most cases, underpinned by the rule’s error-filtering mechanism, which is predicted to provide smooth convergence towards a desired solution during learning. We also find the FILT rule to be most efficient at performing input pattern memorisations, and most noticeably when patterns are identified using spikes with sub-millisecond temporal precision. In comparison with existing work, we determine the performance of the FILT rule to be consistent with that of the highly efficient E-learning Chronotron rule, but with the distinct advantage that our FILT rule is also implementable as an online method for increased biological realism. PMID:27532262

Supervised Learning in Spiking Neural Networks for Precise Temporal Encoding.

PubMed

Gardner, Brian; Grüning, André

2016-01-01

Precise spike timing as a means to encode information in neural networks is biologically supported, and is advantageous over frequency-based codes by processing input features on a much shorter time-scale. For these reasons, much recent attention has been focused on the development of supervised learning rules for spiking neural networks that utilise a temporal coding scheme. However, despite significant progress in this area, there still lack rules that have a theoretical basis, and yet can be considered biologically relevant. Here we examine the general conditions under which synaptic plasticity most effectively takes place to support the supervised learning of a precise temporal code. As part of our analysis we examine two spike-based learning methods: one of which relies on an instantaneous error signal to modify synaptic weights in a network (INST rule), and the other one relying on a filtered error signal for smoother synaptic weight modifications (FILT rule). We test the accuracy of the solutions provided by each rule with respect to their temporal encoding precision, and then measure the maximum number of input patterns they can learn to memorise using the precise timings of individual spikes as an indication of their storage capacity. Our results demonstrate the high performance of the FILT rule in most cases, underpinned by the rule's error-filtering mechanism, which is predicted to provide smooth convergence towards a desired solution during learning. We also find the FILT rule to be most efficient at performing input pattern memorisations, and most noticeably when patterns are identified using spikes with sub-millisecond temporal precision. In comparison with existing work, we determine the performance of the FILT rule to be consistent with that of the highly efficient E-learning Chronotron rule, but with the distinct advantage that our FILT rule is also implementable as an online method for increased biological realism.

Ionospheric effects in uncalibrated phase delay estimation and ambiguity-fixed PPP based on raw observable model

NASA Astrophysics Data System (ADS)

Gu, Shengfeng; Shi, Chuang; Lou, Yidong; Liu, Jingnan

2015-05-01

Zero-difference (ZD) ambiguity resolution (AR) reveals the potential to further improve the performance of precise point positioning (PPP). Traditionally, PPP AR is achieved by Melbourne-Wübbena and ionosphere-free combinations in which the ionosphere effect are removed. To exploit the ionosphere characteristics, PPP AR with L1 and L2 raw observable has also been developed recently. In this study, we apply this new approach in uncalibrated phase delay (UPD) generation and ZD AR and compare it with the traditional model. The raw observable processing strategy treats each ionosphere delay as an unknown parameter. In this manner, both a priori ionosphere correction model and its spatio-temporal correlation can be employed as constraints to improve the ambiguity resolution. However, theoretical analysis indicates that for the wide-lane (WL) UPD retrieved from L1/L2 ambiguities to benefit from this raw observable approach, high precision ionosphere correction of better than 0.7 total electron content unit (TECU) is essential. This conclusion is then confirmed with over 1 year data collected at about 360 stations. Firstly, both global and regional ionosphere model were generated and evaluated, the results of which demonstrated that, for large-scale ionosphere modeling, only an accuracy of 3.9 TECU can be achieved on average for the vertical delays, and this accuracy can be improved to about 0.64 TECU when dense network is involved. Based on these ionosphere products, WL/narrow-lane (NL) UPDs are then extracted with the raw observable model. The NL ambiguity reveals a better stability and consistency compared to traditional approach. Nonetheless, the WL ambiguity can be hardly improved even constrained with the high spatio-temporal resolution ionospheric corrections. By applying both these approaches in PPP-RTK, it is interesting to find that the traditional model is more efficient in AR as evidenced by the shorter time to first fix, while the three-dimensional positioning accuracy of the RAW model outperforms the combination model by about . This reveals that, with the current ionosphere models, there is actually no optimal strategy for the dual-frequency ZD ambiguity resolution, and the combination approach and raw approach each has merits and demerits.

Automatic Derivation of Forest Cover and Forest Cover Change Using Dense Multi-Temporal Time Series Data from Landsat and SPOT 5 Take5

NASA Astrophysics Data System (ADS)

Storch, Cornelia; Wagner, Thomas; Ramminger, Gernot; Pape, Marlon; Ott, Hannes; Hausler, Thomas; Gomez, Sharon

2016-08-01

The paper presents a description of the methods development for an automated processing chain for the classification of Forest Cover and Change based on high resolution multi-temporal time series Landsat and SPOT5Take5 data with focus on the dry forest ecosystems of Africa. The method has been developed within the European Space Agency (ESA) funded Global monitoring for Environment and Security Service Element for Forest Monitoring (GSE FM) project on dry forest areas; the demonstration site selected was in Malawi. The methods are based on the principles of a robust, but still flexible monitoring system, to cope with most complex Earth Observation (EO) data scenarios, varying in terms of data quality, source, accuracy, information content, completeness etc. The method allows automated tracking of change dates, data gap filling and takes into account phenology, seasonality of tree species with respect to leaf fall and heavy cloud cover during the rainy season.

Spatiotemporal earthquake clusters along the North Anatolian fault zone offshore Istanbul

USGS Publications Warehouse

Bulut, Fatih; Ellsworth, William L.; Bohnhoff, Marco; Aktar, Mustafa; Dresen, Georg

2011-01-01

We investigate earthquakes with similar waveforms in order to characterize spatiotemporal microseismicity clusters within the North Anatolian fault zone (NAFZ) in northwest Turkey along the transition between the 1999 ??zmit rupture zone and the Marmara Sea seismic gap. Earthquakes within distinct activity clusters are relocated with cross-correlation derived relative travel times using the double difference method. The spatiotemporal distribution of micro earthquakes within individual clusters is resolved with relative location accuracy comparable to or better than the source size. High-precision relative hypocenters define the geometry of individual fault patches, permitting a better understanding of fault kinematics and their role in local-scale seismotectonics along the region of interest. Temporal seismic sequences observed in the eastern Sea of Marmara region suggest progressive failure of mostly nonoverlapping areas on adjacent fault patches and systematic migration of microearthquakes within clusters during the progressive failure of neighboring fault patches. The temporal distributions of magnitudes as well as the number of events follow swarmlike behavior rather than a mainshock/aftershock pattern.

A Constellation of CubeSat InSAR Sensors for Rapid-Revisit Surface Deformation Studies

NASA Astrophysics Data System (ADS)

Wye, L.; Lee, S.; Yun, S. H.; Zebker, H. A.; Stock, J. D.; Wicks, C. W., Jr.; Doe, R.

2016-12-01

The 2007 NRC Decadal Survey for Earth Sciences highlights three major Earth surface deformation themes: 1) solid-earth hazards and dynamics; 2) human health and security; and 3) land-use change, ecosystem dynamics and biodiversity. Space-based interferometric synthetic aperture radar (InSAR) is a key change detection tool for addressing these themes. Here, we describe the mission and radar payload design for a constellation of S-band InSAR sensors specifically designed to provide the global, high temporal resolution, sub-cm level deformation accuracy needed to address some of the major Earth system goals. InSAR observations with high temporal resolution are needed to properly monitor certain nonlinearly time-varying features (e.g., unstable volcanoes, active fault lines, and heavily-used groundwater or hydrocarbon reservoirs). Good temporal coverage is also needed to reduce atmospheric artifacts by allowing multiple acquisitions to be averaged together, since each individual SAR measurement is corrupted by up to several cm of atmospheric noise. A single InSAR platform is limited in how often it can observe a given scene without sacrificing global spatial coverage. Multiple InSAR platforms provide the spatial-temporal flexibility required to maximize the science return. However, building and launching multiple InSAR platforms is cost-prohibitive for traditional satellites. SRI International (SRI) and our collaborators are working to exploit developments in nanosatellite technology, in particular the emergence of the CubeSat standard, to provide high-cadence InSAR capabilities in an affordable package. The CubeSat Imaging Radar for Earth Science (CIRES) subsystem, a prototype SAR elec­tronics package developed by SRI with support from a 2014 NASA ESTO ACT award, is specifically scaled to be a drop-in radar solution for resource-limited delivery systems like CubeSats and small airborne vehicles. Here, we present our mission concept and flow-down requirements for a constellation of 6U InSAR sensors that individually approach the performance capabilities of existing instruments, but collectively surpass the temporal coverage capabilities of single-platform sensors. We discuss the key applications addressed by this constellation and the capabilities that the constellation enables.

Why do temporal generalization gradients change when people make decisions as quickly as possible?

PubMed

Klapproth, Florian; Wearden, John H

2011-08-01

Three experiments investigated temporal generalization performance under conditions in which participants were instructed to make their decisions as quickly as possible (speed), or were allowed to take their time (accuracy). A previous study (Klapproth & Müller, 2008) had shown that under speeded conditions people were more likely to confuse durations shorter than the standard with the standard than in the accuracy conditions, and a possible explanation of this result is that longer stimulus durations are "truncated" (i.e., people make a judgement about them before they have terminated, thereby shortening their effective duration) and that these truncated durations affect the standard used for the task. Experiment 1 investigated performance under speed and accuracy conditions when comparison durations were close to the standard or further away. No performance difference was found as a function of stimulus spacing, even though responses occurred on average before the longest durations had terminated, but this lack of effect was attributed to "task difficulty" effects changing decision thresholds. In Experiment 2, the standard duration was either the longest or the shortest duration in the comparison set, and differences between speed and accuracy groups occurred only when the comparisons were longer than the standard, supporting the "truncation" hypothesis. A third experiment showed that differences between speed and accuracy groups only occurred if some memory of the standard that was valid for more than one trial was used. In general, the results suggest that the generalization gradient shifts in speeded conditions occur because of truncation of longer comparison durations, which influences the effective standard used for the task.

An advanced scanning method for space-borne hyper-spectral imaging system

NASA Astrophysics Data System (ADS)

Wang, Yue-ming; Lang, Jun-Wei; Wang, Jian-Yu; Jiang, Zi-Qing

2011-08-01

Space-borne hyper-spectral imagery is an important means for the studies and applications of earth science. High cost efficiency could be acquired by optimized system design. In this paper, an advanced scanning method is proposed, which contributes to implement both high temporal and spatial resolution imaging system. Revisit frequency and effective working time of space-borne hyper-spectral imagers could be greatly improved by adopting two-axis scanning system if spatial resolution and radiometric accuracy are not harshly demanded. In order to avoid the quality degradation caused by image rotation, an idea of two-axis rotation has been presented based on the analysis and simulation of two-dimensional scanning motion path and features. Further improvement of the imagers' detection ability under the conditions of small solar altitude angle and low surface reflectance can be realized by the Ground Motion Compensation on pitch axis. The structure and control performance are also described. An intelligent integration technology of two-dimensional scanning and image motion compensation is elaborated in this paper. With this technology, sun-synchronous hyper-spectral imagers are able to pay quick visit to hot spots, acquiring both high spatial and temporal resolution hyper-spectral images, which enables rapid response of emergencies. The result has reference value for developing operational space-borne hyper-spectral imagers.

Multi-Temporal Land Cover Classification with Sequential Recurrent Encoders

NASA Astrophysics Data System (ADS)

Rußwurm, Marc; Körner, Marco

2018-03-01

Earth observation (EO) sensors deliver data with daily or weekly temporal resolution. Most land use and land cover (LULC) approaches, however, expect cloud-free and mono-temporal observations. The increasing temporal capabilities of today's sensors enables the use of temporal, along with spectral and spatial features. Domains, such as speech recognition or neural machine translation, work with inherently temporal data and, today, achieve impressive results using sequential encoder-decoder structures. Inspired by these sequence-to-sequence models, we adapt an encoder structure with convolutional recurrent layers in order to approximate a phenological model for vegetation classes based on a temporal sequence of Sentinel 2 (S2) images. In our experiments, we visualize internal activations over a sequence of cloudy and non-cloudy images and find several recurrent cells, which reduce the input activity for cloudy observations. Hence, we assume that our network has learned cloud-filtering schemes solely from input data, which could alleviate the need for tedious cloud-filtering as a preprocessing step for many EO approaches. Moreover, using unfiltered temporal series of top-of-atmosphere (TOA) reflectance data, we achieved in our experiments state-of-the-art classification accuracies on a large number of crop classes with minimal preprocessing compared to other classification approaches.