Automatic Processing of Changes in Facial Emotions in Dysphoria: A Magnetoencephalography Study.

PubMed

Xu, Qianru; Ruohonen, Elisa M; Ye, Chaoxiong; Li, Xueqiao; Kreegipuu, Kairi; Stefanics, Gabor; Luo, Wenbo; Astikainen, Piia

2018-01-01

It is not known to what extent the automatic encoding and change detection of peripherally presented facial emotion is altered in dysphoria. The negative bias in automatic face processing in particular has rarely been studied. We used magnetoencephalography (MEG) to record automatic brain responses to happy and sad faces in dysphoric (Beck's Depression Inventory ≥ 13) and control participants. Stimuli were presented in a passive oddball condition, which allowed potential negative bias in dysphoria at different stages of face processing (M100, M170, and M300) and alterations of change detection (visual mismatch negativity, vMMN) to be investigated. The magnetic counterpart of the vMMN was elicited at all stages of face processing, indexing automatic deviance detection in facial emotions. The M170 amplitude was modulated by emotion, response amplitudes being larger for sad faces than happy faces. Group differences were found for the M300, and they were indexed by two different interaction effects. At the left occipital region of interest, the dysphoric group had larger amplitudes for sad than happy deviant faces, reflecting negative bias in deviance detection, which was not found in the control group. On the other hand, the dysphoric group showed no vMMN to changes in facial emotions, while the vMMN was observed in the control group at the right occipital region of interest. Our results indicate that there is a negative bias in automatic visual deviance detection, but also a general change detection deficit in dysphoria.

Unsupervised Multi-Scale Change Detection from SAR Imagery for Monitoring Natural and Anthropogenic Disasters

NASA Astrophysics Data System (ADS)

Ajadi, Olaniyi A.

Radar remote sensing can play a critical role in operational monitoring of natural and anthropogenic disasters. Despite its all-weather capabilities, and its high performance in mapping, and monitoring of change, the application of radar remote sensing in operational monitoring activities has been limited. This has largely been due to: (1) the historically high costs associated with obtaining radar data; (2) slow data processing, and delivery procedures; and (3) the limited temporal sampling that was provided by spaceborne radar-based satellites. Recent advances in the capabilities of spaceborne Synthetic Aperture Radar (SAR) sensors have developed an environment that now allows for SAR to make significant contributions to disaster monitoring. New SAR processing strategies that can take full advantage of these new sensor capabilities are currently being developed. Hence, with this PhD dissertation, I aim to: (i) investigate unsupervised change detection techniques that can reliably extract signatures from time series of SAR images, and provide the necessary flexibility for application to a variety of natural, and anthropogenic hazard situations; (ii) investigate effective methods to reduce the effects of speckle and other noise on change detection performance; (iii) automate change detection algorithms using probabilistic Bayesian inferencing; and (iv) ensure that the developed technology is applicable to current, and future SAR sensors to maximize temporal sampling of a hazardous event. This is achieved by developing new algorithms that rely on image amplitude information only, the sole image parameter that is available for every single SAR acquisition.. The motivation and implementation of the change detection concept are described in detail in Chapter 3. In the same chapter, I demonstrated the technique's performance using synthetic data as well as a real-data application to map wildfire progression. I applied Radiometric Terrain Correction (RTC) to the data to increase the sampling frequency, while the developed multiscale-driven approach reliably identified changes embedded in largely stationary background scenes. With this technique, I was able to identify the extent of burn scars with high accuracy. I further applied the application of the change detection technology to oil spill mapping. The analysis highlights that the approach described in Chapter 3 can be applied to this drastically different change detection problem with only little modification. While the core of the change detection technique remained unchanged, I made modifications to the pre-processing step to enable change detection from scenes of continuously varying background. I introduced the Lipschitz regularity (LR) transformation as a technique to normalize the typically dynamic ocean surface, facilitating high performance oil spill detection independent of environmental conditions during image acquisition. For instance, I showed that LR processing reduces the sensitivity of change detection performance to variations in surface winds, which is a known limitation in oil spill detection from SAR. Finally, I applied the change detection technique to aufeis flood mapping along the Sagavanirktok River. Due to the complex nature of aufeis flooded areas, I substituted the resolution-preserving speckle filter used in Chapter 3 with curvelet filters. In addition to validating the performance of the change detection results, I also provide evidence of the wealth of information that can be extracted about aufeis flooding events once a time series of change detection information was extracted from SAR imagery. A summary of the developed change detection techniques is conducted and suggested future work is presented in Chapter 6.

A Dual-Process Account of Auditory Change Detection

ERIC Educational Resources Information Center

McAnally, Ken I.; Martin, Russell L.; Eramudugolla, Ranmalee; Stuart, Geoffrey W.; Irvine, Dexter R. F.; Mattingley, Jason B.

2010-01-01

Listeners can be "deaf" to a substantial change in a scene comprising multiple auditory objects unless their attention has been directed to the changed object. It is unclear whether auditory change detection relies on identification of the objects in pre- and post-change scenes. We compared the rates at which listeners correctly identify changed…

WeaselBoard :

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

Mulder, John C.; Schwartz, Moses Daniel; Berg, Michael J.

2013-10-01

Critical infrastructures, such as electrical power plants and oil refineries, rely on programmable logic controllers (PLCs) to control essential processes. State of the art security cannot detect attacks on PLCs at the hardware or firmware level. This renders critical infrastructure control systems vulnerable to costly and dangerous attacks. WeaselBoard is a PLC backplane analysis system that connects directly to the PLC backplane to capture backplane communications between modules. WeaselBoard forwards inter-module traffic to an external analysis system that detects changes to process control settings, sensor values, module configuration information, firmware updates, and process control program (logic) updates. WeaselBoard provides zero-daymore » exploit detection for PLCs by detecting changes in the PLC and the process. This approach to PLC monitoring is protected under U.S. Patent Application 13/947,887.« less

Automatic detection of health changes using statistical process control techniques on measured transfer times of elderly.

PubMed

Baldewijns, Greet; Luca, Stijn; Nagels, William; Vanrumste, Bart; Croonenborghs, Tom

2015-01-01

It has been shown that gait speed and transfer times are good measures of functional ability in elderly. However, data currently acquired by systems that measure either gait speed or transfer times in the homes of elderly people require manual reviewing by healthcare workers. This reviewing process is time-consuming. To alleviate this burden, this paper proposes the use of statistical process control methods to automatically detect both positive and negative changes in transfer times. Three SPC techniques: tabular CUSUM, standardized CUSUM and EWMA, known for their ability to detect small shifts in the data, are evaluated on simulated transfer times. This analysis shows that EWMA is the best-suited method with a detection accuracy of 82% and an average detection time of 9.64 days.

Signal processing for non-destructive testing of railway tracks

NASA Astrophysics Data System (ADS)

Heckel, Thomas; Casperson, Ralf; Rühe, Sven; Mook, Gerhard

2018-04-01

Increased speed, heavier loads, altered material and modern drive systems result in an increasing number of rail flaws. The appearance of these flaws also changes continually due to the rapid change in damage mechanisms of modern rolling stock. Hence, interpretation has become difficult when evaluating non-destructive rail testing results. Due to the changed interplay between detection methods and flaws, the recorded signals may result in unclassified types of rail flaws. Methods for automatic rail inspection (according to defect detection and classification) undergo continual development. Signal processing is a key technology to master the challenge of classification and maintain resolution and detection quality, independent of operation speed. The basic ideas of signal processing, based on the Glassy-Rail-Diagram for classification purposes, are presented herein. Examples for the detection of damages caused by rolling contact fatigue also are given, and synergetic effects of combined evaluation of diverse inspection methods are shown.

SSME propellant path leak detection real-time

NASA Technical Reports Server (NTRS)

Crawford, R. A.; Smith, L. M.

1994-01-01

Included are four documents that outline the technical aspects of the research performed on NASA Grant NAG8-140: 'A System for Sequential Step Detection with Application to Video Image Processing'; 'Leak Detection from the SSME Using Sequential Image Processing'; 'Digital Image Processor Specifications for Real-Time SSME Leak Detection'; and 'A Color Change Detection System for Video Signals with Applications to Spectral Analysis of Rocket Engine Plumes'.

Beauty hinders attention switch in change detection: the role of facial attractiveness and distinctiveness.

PubMed

Chen, Wenfeng; Liu, Chang Hong; Nakabayashi, Kazuyo

2012-01-01

Recent research has shown that the presence of a task-irrelevant attractive face can induce a transient diversion of attention from a perceptual task that requires covert deployment of attention to one of the two locations. However, it is not known whether this spontaneous appraisal for facial beauty also modulates attention in change detection among multiple locations, where a slower, and more controlled search process is simultaneously affected by the magnitude of a change and the facial distinctiveness. Using the flicker paradigm, this study examines how spontaneous appraisal for facial beauty affects the detection of identity change among multiple faces. Participants viewed a display consisting of two alternating frames of four faces separated by a blank frame. In half of the trials, one of the faces (target face) changed to a different person. The task of the participant was to indicate whether a change of face identity had occurred. The results showed that (1) observers were less efficient at detecting identity change among multiple attractive faces relative to unattractive faces when the target and distractor faces were not highly distinctive from one another; and (2) it is difficult to detect a change if the new face is similar to the old. The findings suggest that attractive faces may interfere with the attention-switch process in change detection. The results also show that attention in change detection was strongly modulated by physical similarity between the alternating faces. Although facial beauty is a powerful stimulus that has well-demonstrated priority, its influence on change detection is easily superseded by low-level image similarity. The visual system appears to take a different approach to facial beauty when a task requires resource-demanding feature comparisons.

Attention modifies sound level detection in young children.

PubMed

Sussman, Elyse S; Steinschneider, Mitchell

2011-07-01

Have you ever shouted your child's name from the kitchen while they were watching television in the living room to no avail, so you shout their name again, only louder? Yet, still no response. The current study provides evidence that young children process loudness changes differently than pitch changes when they are engaged in another task such as watching a video. Intensity level changes were physiologically detected only when they were behaviorally relevant, but frequency level changes were physiologically detected without task relevance in younger children. This suggests that changes in pitch rather than changes in volume may be more effective in evoking a response when sounds are unexpected. Further, even though behavioral ability may appear to be similar in younger and older children, attention-based physiologic responses differ from automatic physiologic processes in children. Results indicate that 1) the automatic auditory processes leading to more efficient higher-level skills continue to become refined through childhood; and 2) there are different time courses for the maturation of physiological processes encoding the distinct acoustic attributes of sound pitch and sound intensity. The relevance of these findings to sound perception in real-world environments is discussed.

Dynamic Network Change Detection

DTIC Science & Technology

2008-12-01

Change Detection 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 5e. TASK NUMBER 5f. WORK UNIT...Fisher and Mackenzie, 1922). These methods are used in quality engineering to detect small changes in a process (Montgomery, 1991; Ryan , 2000). Larger...Social Network Modeling and Analysis: Workshop Summary and Papers, Ronald Breiger, Kathleen Carley, and Philippa Pattison, (Eds

Effects of capacity limits, memory loss, and sound type in change deafness.

PubMed

Gregg, Melissa K; Irsik, Vanessa C; Snyder, Joel S

2017-11-01

Change deafness, the inability to notice changes to auditory scenes, has the potential to provide insights about sound perception in busy situations typical of everyday life. We determined the extent to which change deafness to sounds is due to the capacity of processing multiple sounds and the loss of memory for sounds over time. We also determined whether these processing limitations work differently for varying types of sounds within a scene. Auditory scenes composed of naturalistic sounds, spectrally dynamic unrecognizable sounds, tones, and noise rhythms were presented in a change-detection task. On each trial, two scenes were presented that were same or different. We manipulated the number of sounds within each scene to measure memory capacity and the silent interval between scenes to measure memory loss. For all sounds, change detection was worse as scene size increased, demonstrating the importance of capacity limits. Change detection to the natural sounds did not deteriorate much as the interval between scenes increased up to 2,000 ms, but it did deteriorate substantially with longer intervals. For artificial sounds, in contrast, change-detection performance suffered even for very short intervals. The results suggest that change detection is generally limited by capacity, regardless of sound type, but that auditory memory is more enduring for sounds with naturalistic acoustic structures.

Brain correlates of automatic visual change detection.

PubMed

Cléry, H; Andersson, F; Fonlupt, P; Gomot, M

2013-07-15

A number of studies support the presence of visual automatic detection of change, but little is known about the brain generators involved in such processing and about the modulation of brain activity according to the salience of the stimulus. The study presented here was designed to locate the brain activity elicited by unattended visual deviant and novel stimuli using fMRI. Seventeen adult participants were presented with a passive visual oddball sequence while performing a concurrent visual task. Variations in BOLD signal were observed in the modality-specific sensory cortex, but also in non-specific areas involved in preattentional processing of changing events. A degree-of-deviance effect was observed, since novel stimuli elicited more activity in the sensory occipital regions and at the medial frontal site than small changes. These findings could be compared to those obtained in the auditory modality and might suggest a "general" change detection process operating in several sensory modalities. Copyright © 2013 Elsevier Inc. All rights reserved.

Grand Challenges Emerging Perspectives For Embedded Processing (BRIEFING CHARTS)

DTIC Science & Technology

2007-03-06

track before detect Small... Track - before - detect (dim targets) Change detection 16Mpixel 2 Hz 1 km2 1 ft res. STAPBOY Φ1 60W .3k$ AMD server 120 W ~.8k...60 X (m) Y ( m ) −50 0 50 −60 −40 −20 0 20 40 60 X (m) Y ( m ) EO/IR Track - before - detect (dim targets) Change detection RISC/DSP AMD

Neural correlates of change detection and change blindness in a working memory task.

PubMed

Pessoa, Luiz; Ungerleider, Leslie G

2004-05-01

Detecting changes in an ever-changing environment is highly advantageous, and this ability may be critical for survival. In the present study, we investigated the neural substrates of change detection in the context of a visual working memory task. Subjects maintained a sample visual stimulus in short-term memory for 6 s, and were asked to indicate whether a subsequent, test stimulus matched or did not match the original sample. To study change detection largely uncontaminated by attentional state, we compared correct change and correct no-change trials at test. Our results revealed that correctly detecting a change was associated with activation of a network comprising parietal and frontal brain regions, as well as activation of the pulvinar, cerebellum, and inferior temporal gyrus. Moreover, incorrectly reporting a change when none occurred led to a very similar pattern of activations. Finally, few regions were differentially activated by trials in which a change occurred but subjects failed to detect it (change blindness). Thus, brain activation was correlated with a subject's report of a change, instead of correlated with the physical change per se. We propose that frontal and parietal regions, possibly assisted by the cerebellum and the pulvinar, might be involved in controlling the deployment of attention to the location of a change, thereby allowing further processing of the visual stimulus. Visual processing areas, such as the inferior temporal gyrus, may be the recipients of top-down feedback from fronto-parietal regions that control the reactive deployment of attention, and thus exhibit increased activation when a change is reported (irrespective of whether it occurred or not). Whereas reporting that a change occurred, be it correctly or incorrectly, was associated with strong activation in fronto-parietal sites, change blindness appears to involve very limited territories.

A network of superconducting gravimeters detects submicrogal coseismic gravity changes.

PubMed

Imanishi, Yuichi; Sato, Tadahiro; Higashi, Toshihiro; Sun, Wenke; Okubo, Shuhei

2004-10-15

With high-resolution continuous gravity recordings from a regional network of superconducting gravimeters, we have detected permanent changes in gravity acceleration associated with a recent large earthquake. Detected changes in gravity acceleration are smaller than 10(-8) meters seconds(-2) (1 micro-Galileo, about 10(-9) times the surface gravity acceleration) and agree with theoretical values calculated from a dislocation model. Superconducting gravimetry can contribute to the studies of secular gravity changes associated with tectonic processes.

Visual long-term memory and change blindness: Different effects of pre- and post-change information on one-shot change detection using meaningless geometric objects.

PubMed

Nishiyama, Megumi; Kawaguchi, Jun

2014-11-01

To clarify the relationship between visual long-term memory (VLTM) and online visual processing, we investigated whether and how VLTM involuntarily affects the performance of a one-shot change detection task using images consisting of six meaningless geometric objects. In the study phase, participants observed pre-change (Experiment 1), post-change (Experiment 2), or both pre- and post-change (Experiment 3) images appearing in the subsequent change detection phase. In the change detection phase, one object always changed between pre- and post-change images and participants reported which object was changed. Results showed that VLTM of pre-change images enhanced the performance of change detection, while that of post-change images decreased accuracy. Prior exposure to both pre- and post-change images did not influence performance. These results indicate that pre-change information plays an important role in change detection, and that information in VLTM related to the current task does not always have a positive effect on performance. Copyright © 2014 Elsevier Inc. All rights reserved.

Trajectory-based change detection for automated characterization of forest disturbance dynamics

Treesearch

Robert E. Kennedy; Warren B. Cohen; Todd A. Schroeder

2007-01-01

Satellite sensors are well suited to monitoring changes on the Earth's surface through provision of consistent and repeatable measurements at a spatial scale appropriate for many processes causing change on the land surface. Here, we describe and test a new conceptual approach to change detection of forests using a dense temporal stack of Landsat Thematic Mapper (...

Sentence-Level Rewriting Detection

ERIC Educational Resources Information Center

Zhang, Fan; Litman, Diane

2014-01-01

Writers usually need iterations of revisions and edits during their writings. To better understand the process of rewriting, we need to know what has changed be-tween the revisions. Prior work mainly focuses on detecting corrections within sentences, which is at the level of words or phrases. This paper proposes to detect revision changes at the…

Processing changes across reading encounters.

PubMed

Levy, B A; Newell, S; Snyder, J; Timmins, K

1986-10-01

Five experiments examined changes in the processing of a text across reading encounters. Experiment 1 showed that reading speed increased systematically across encounters, with no loss in the extensiveness of analyses of the printed text, as indicated by the ability to detect nonword errors embedded within that passage. Experiment 2 replicated this improved reading fluency with experience and showed that it occurred even with typescript changes across trials, thus indicating that a primed visual operations explanation cannot account for the effect. The third and fourth experiments then extended the study of the familiarity effect to higher level processing, as indicated by the detection of word errors. Familiarity facilitated the detection of these violations at the syntactic-semantic levels. Finally, Experiment 5 showed that these higher level violations continued to be well detected over a series of reading encounters with the same text. The results indicate that prior experience improves reading speed, with no attenuation of analysis of the printed words or of the passage's message.

Assessment of Data Fusion Algorithms for Earth Observation Change Detection Processes.

PubMed

Molina, Iñigo; Martinez, Estibaliz; Morillo, Carmen; Velasco, Jesus; Jara, Alvaro

2016-09-30

In this work a parametric multi-sensor Bayesian data fusion approach and a Support Vector Machine (SVM) are used for a Change Detection problem. For this purpose two sets of SPOT5-PAN images have been used, which are in turn used for Change Detection Indices (CDIs) calculation. For minimizing radiometric differences, a methodology based on zonal "invariant features" is suggested. The choice of one or the other CDI for a change detection process is a subjective task as each CDI is probably more or less sensitive to certain types of changes. Likewise, this idea might be employed to create and improve a "change map", which can be accomplished by means of the CDI's informational content. For this purpose, information metrics such as the Shannon Entropy and "Specific Information" have been used to weight the changes and no-changes categories contained in a certain CDI and thus introduced in the Bayesian information fusion algorithm. Furthermore, the parameters of the probability density functions (pdf's) that best fit the involved categories have also been estimated. Conversely, these considerations are not necessary for mapping procedures based on the discriminant functions of a SVM. This work has confirmed the capabilities of probabilistic information fusion procedure under these circumstances.

Detecting the effects of forest harvesting on streamflow using hydrologic model change detection

Treesearch

Nicolas P. Zegre; Nicholas A. Som

2011-01-01

Knowledge of the effects of forest management on hydrology primarily comes from paired-catchment study experiments. This approach has contributed fundamental knowledge of the effects of forest management on hydrology, but results from these studies lack insight into catchment processes. Outlined in this study is an alternative method of change detection that uses a...

The human as a detector of changes in variance and bandwidth

NASA Technical Reports Server (NTRS)

Curry, R. E.; Govindaraj, T.

1977-01-01

The detection of changes in random process variance and bandwidth was studied. Psychophysical thresholds for these two parameters were determined using an adaptive staircase technique for second order random processes at two nominal periods (1 and 3 seconds) and damping ratios (0.2 and 0.707). Thresholds for bandwidth changes were approximately 9% of nominal except for the (3sec,0.2) process which yielded thresholds of 12%. Variance thresholds averaged 17% of nominal except for the (3sec,0.2) process in which they were 32%. Detection times for suprathreshold changes in the parameters may be roughly described by the changes in RMS velocity of the process. A more complex model is presented which consists of a Kalman filter designed for the nominal process using velocity as the input, and a modified Wald sequential test for changes in the variance of the residual. The model predictions agree moderately well with the experimental data. Models using heuristics, e.g. level crossing counters, were also examined and are found to be descriptive but do not afford the unification of the Kalman filter/sequential test model used for changes in mean.

Methods of DNA methylation detection

NASA Technical Reports Server (NTRS)

Maki, Wusi Chen (Inventor); Filanoski, Brian John (Inventor); Mishra, Nirankar (Inventor); Rastogi, Shiva (Inventor)

2010-01-01

The present invention provides for methods of DNA methylation detection. The present invention provides for methods of generating and detecting specific electronic signals that report the methylation status of targeted DNA molecules in biological samples.Two methods are described, direct and indirect detection of methylated DNA molecules in a nano transistor based device. In the direct detection, methylated target DNA molecules are captured on the sensing surface resulting in changes in the electrical properties of a nano transistor. These changes generate detectable electronic signals. In the indirect detection, antibody-DNA conjugates are used to identify methylated DNA molecules. RNA signal molecules are generated through an in vitro transcription process. These RNA molecules are captured on the sensing surface change the electrical properties of nano transistor thereby generating detectable electronic signals.

Spatiotemporal Change Detection Using Landsat Imagery: the Case Study of Karacabey Flooded Forest, Bursa, Turkey

NASA Astrophysics Data System (ADS)

Akay, A. E.; Gencal, B.; Taş, İ.

2017-11-01

This short paper aims to detect spatiotemporal detection of land use/land cover change within Karacabey Flooded Forest region. Change detection analysis applied to Landsat 5 TM images representing July 2000 and a Landsat 8 OLI representing June 2017. Various image processing tools were implemented using ERDAS 9.2, ArcGIS 10.4.1, and ENVI programs to conduct spatiotemporal change detection over these two images such as band selection, corrections, subset, classification, recoding, accuracy assessment, and change detection analysis. Image classification revealed that there are five significant land use/land cover types, including forest, flooded forest, swamp, water, and other lands (i.e. agriculture, sand, roads, settlement, and open areas). The results indicated that there was increase in flooded forest, water, and other lands, while the cover of forest and swamp decreased.

Real-time change and damage detection of landslides and other earth movements threatening public infrastructure.

DOT National Transportation Integrated Search

2012-03-01

construction and maintenance. Repeat surveys using terrestrial laser scanning (TLS, ground-based LiDAR) enable rapid 3D data acquisition to map, see, analyze, and understand the processes generating such problems. Previously, change detection and ana...

The role of auditory transient and deviance processing in distraction of task performance: a combined behavioral and event-related brain potential study

PubMed Central

Berti, Stefan

2013-01-01

Distraction of goal-oriented performance by a sudden change in the auditory environment is an everyday life experience. Different types of changes can be distracting, including a sudden onset of a transient sound and a slight deviation of otherwise regular auditory background stimulation. With regard to deviance detection, it is assumed that slight changes in a continuous sequence of auditory stimuli are detected by a predictive coding mechanisms and it has been demonstrated that this mechanism is capable of distracting ongoing task performance. In contrast, it is open whether transient detection—which does not rely on predictive coding mechanisms—can trigger behavioral distraction, too. In the present study, the effect of rare auditory changes on visual task performance is tested in an auditory-visual cross-modal distraction paradigm. The rare changes are either embedded within a continuous standard stimulation (triggering deviance detection) or are presented within an otherwise silent situation (triggering transient detection). In the event-related brain potentials, deviants elicited the mismatch negativity (MMN) while transients elicited an enhanced N1 component, mirroring pre-attentive change detection in both conditions but on the basis of different neuro-cognitive processes. These sensory components are followed by attention related ERP components including the P3a and the reorienting negativity (RON). This demonstrates that both types of changes trigger switches of attention. Finally, distraction of task performance is observable, too, but the impact of deviants is higher compared to transients. These findings suggest different routes of distraction allowing for the automatic processing of a wide range of potentially relevant changes in the environment as a pre-requisite for adaptive behavior. PMID:23874278

Vehicle tracking using fuzzy-based vehicle detection window with adaptive parameters

NASA Astrophysics Data System (ADS)

Chitsobhuk, Orachat; Kasemsiri, Watjanapong; Glomglome, Sorayut; Lapamonpinyo, Pipatphon

2018-04-01

In this paper, fuzzy-based vehicle tracking system is proposed. The proposed system consists of two main processes: vehicle detection and vehicle tracking. In the first process, the Gradient-based Adaptive Threshold Estimation (GATE) algorithm is adopted to provide the suitable threshold value for the sobel edge detection. The estimated threshold can be adapted to the changes of diverse illumination conditions throughout the day. This leads to greater vehicle detection performance compared to a fixed user's defined threshold. In the second process, this paper proposes the novel vehicle tracking algorithms namely Fuzzy-based Vehicle Analysis (FBA) in order to reduce the false estimation of the vehicle tracking caused by uneven edges of the large vehicles and vehicle changing lanes. The proposed FBA algorithm employs the average edge density and the Horizontal Moving Edge Detection (HMED) algorithm to alleviate those problems by adopting fuzzy rule-based algorithms to rectify the vehicle tracking. The experimental results demonstrate that the proposed system provides the high accuracy of vehicle detection about 98.22%. In addition, it also offers the low false detection rates about 3.92%.

Electrical detection of microwave assisted magnetization reversal by spin pumping

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

Rao, Siddharth; Subhra Mukherjee, Sankha; Elyasi, Mehrdad

2014-03-24

Microwave assisted magnetization reversal has been investigated in a bilayer system of Pt/ferromagnet by detecting a change in the polarity of the spin pumping signal. The reversal process is studied in two material systems, Pt/CoFeB and Pt/NiFe, for different aspect ratios. The onset of the switching behavior is indicated by a sharp transition in the spin pumping voltage. At a threshold value of the external field, the switching process changes from partial to full reversal with increasing microwave power. The proposed method provides a simple way to detect microwave assisted magnetization reversal.

Evaluation of risk and benefit in thermal effusivity sensor for monitoring lubrication process in pharmaceutical product manufacturing.

PubMed

Uchiyama, Jumpei; Kato, Yoshiteru; Uemoto, Yoshifumi

2014-08-01

In the process design of tablet manufacturing, understanding and control of the lubrication process is important from various viewpoints. A detailed analysis of thermal effusivity data in the lubrication process was conducted in this study. In addition, we evaluated the risk and benefit in the lubrication process by a detailed investigation. It was found that monitoring of thermal effusivity detected mainly the physical change of bulk density, which was changed by dispersal of the lubricant and the coating powder particle by the lubricant. The monitoring of thermal effusivity was almost the monitoring of bulk density, thermal effusivity could have a high correlation with tablet hardness. Moreover, as thermal effusivity sensor could detect not only the change of the conventional bulk density but also the fractional change of thermal conductivity and thermal capacity, two-phase progress of lubrication process could be revealed. However, each contribution of density, thermal conductivity, or heat capacity to thermal effusivity has the risk of fluctuation by formulation. After carefully considering the change factor with the risk to be changed by formulation, thermal effusivity sensor can be a useful tool for monitoring as process analytical technology, estimating tablet hardness and investigating the detailed mechanism of the lubrication process.

[Automated identification, interpretation and classification of focal changes in the lungs on the images obtained at computed tomography for lung cancer screening].

PubMed

Barchuk, A A; Podolsky, M D; Tarakanov, S A; Kotsyuba, I Yu; Gaidukov, V S; Kuznetsov, V I; Merabishvili, V M; Barchuk, A S; Levchenko, E V; Filochkina, A V; Arseniev, A I

2015-01-01

This review article analyzes data of literature devoted to the description, interpretation and classification of focal (nodal) changes in the lungs detected by computed tomography of the chest cavity. There are discussed possible criteria for determining the most likely of their character--primary and metastatic tumor processes, inflammation, scarring, and autoimmune changes, tuberculosis and others. Identification of the most characteristic, reliable and statistically significant evidences of a variety of pathological processes in the lungs including the use of modern computer-aided detection and diagnosis of sites will optimize the diagnostic measures and ensure processing of a large volume of medical data in a short time.

The Attentional Boost Effect: Transient increases in attention to one task enhance performance in a second task.

PubMed

Swallow, Khena M; Jiang, Yuhong V

2010-04-01

Recent work on event perception suggests that perceptual processing increases when events change. An important question is how such changes influence the way other information is processed, particularly during dual-task performance. In this study, participants monitored a long series of distractor items for an occasional target as they simultaneously encoded unrelated background scenes. The appearance of an occasional target could have two opposite effects on the secondary task: It could draw attention away from the second task, or, as a change in the ongoing event, it could improve secondary task performance. Results were consistent with the second possibility. Memory for scenes presented simultaneously with the targets was better than memory for scenes that preceded or followed the targets. This effect was observed when the primary detection task involved visual feature oddball detection, auditory oddball detection, and visual color-shape conjunction detection. It was eliminated when the detection task was omitted, and when it required an arbitrary response mapping. The appearance of occasional, task-relevant events appears to trigger a temporal orienting response that facilitates processing of concurrently attended information (Attentional Boost Effect). Copyright 2009 Elsevier B.V. All rights reserved.

The Attentional Boost Effect: Transient Increases in Attention to One Task Enhance Performance in a Second Task

PubMed Central

Swallow, Khena M.; Jiang, Yuhong V.

2009-01-01

Recent work on event perception suggests that perceptual processing increases when events change. An important question is how such changes influence the way other information is processed, particularly during dual-task performance. In this study, participants monitored a long series of distractor items for an occasional target as they simultaneously encoded unrelated background scenes. The appearance of an occasional target could have two opposite effects on the secondary task: It could draw attention away from the second task, or, as a change in the ongoing event, it could improve secondary task performance. Results were consistent with the second possibility. Memory for scenes presented simultaneously with the targets was better than memory for scenes that preceded or followed the targets. This effect was observed when the primary detection task involved visual feature oddball detection, auditory oddball detection, and visual color-shape conjunction detection. It was eliminated when the detection task was omitted, and when it required an arbitrary response mapping. The appearance of occasional, task-relevant events appears to trigger a temporal orienting response that facilitates processing of concurrently attended information (Attentional Boost Effect). PMID:20080232

[Online endpoint detection algorithm for blending process of Chinese materia medica].

PubMed

Lin, Zhao-Zhou; Yang, Chan; Xu, Bing; Shi, Xin-Yuan; Zhang, Zhi-Qiang; Fu, Jing; Qiao, Yan-Jiang

2017-03-01

Blending process, which is an essential part of the pharmaceutical preparation, has a direct influence on the homogeneity and stability of solid dosage forms. With the official release of Guidance for Industry PAT, online process analysis techniques have been more and more reported in the applications in blending process, but the research on endpoint detection algorithm is still in the initial stage. By progressively increasing the window size of moving block standard deviation (MBSD), a novel endpoint detection algorithm was proposed to extend the plain MBSD from off-line scenario to online scenario and used to determine the endpoint in the blending process of Chinese medicine dispensing granules. By online learning of window size tuning, the status changes of the materials in blending process were reflected in the calculation of standard deviation in a real-time manner. The proposed method was separately tested in the blending processes of dextrin and three other extracts of traditional Chinese medicine. All of the results have shown that as compared with traditional MBSD method, the window size changes according to the proposed MBSD method (progressively increasing the window size) could more clearly reflect the status changes of the materials in blending process, so it is suitable for online application. Copyright© by the Chinese Pharmaceutical Association.

Monitoring endemic livestock diseases using laboratory diagnostic data: A simulation study to evaluate the performance of univariate process monitoring control algorithms.

PubMed

Lopes Antunes, Ana Carolina; Dórea, Fernanda; Halasa, Tariq; Toft, Nils

2016-05-01

Surveillance systems are critical for accurate, timely monitoring and effective disease control. In this study, we investigated the performance of univariate process monitoring control algorithms in detecting changes in seroprevalence for endemic diseases. We also assessed the effect of sample size (number of sentinel herds tested in the surveillance system) on the performance of the algorithms. Three univariate process monitoring control algorithms were compared: Shewart p Chart(1) (PSHEW), Cumulative Sum(2) (CUSUM) and Exponentially Weighted Moving Average(3) (EWMA). Increases in seroprevalence were simulated from 0.10 to 0.15 and 0.20 over 4, 8, 24, 52 and 104 weeks. Each epidemic scenario was run with 2000 iterations. The cumulative sensitivity(4) (CumSe) and timeliness were used to evaluate the algorithms' performance with a 1% false alarm rate. Using these performance evaluation criteria, it was possible to assess the accuracy and timeliness of the surveillance system working in real-time. The results showed that EWMA and PSHEW had higher CumSe (when compared with the CUSUM) from week 1 until the end of the period for all simulated scenarios. Changes in seroprevalence from 0.10 to 0.20 were more easily detected (higher CumSe) than changes from 0.10 to 0.15 for all three algorithms. Similar results were found with EWMA and PSHEW, based on the median time to detection. Changes in the seroprevalence were detected later with CUSUM, compared to EWMA and PSHEW for the different scenarios. Increasing the sample size 10 fold halved the time to detection (CumSe=1), whereas increasing the sample size 100 fold reduced the time to detection by a factor of 6. This study investigated the performance of three univariate process monitoring control algorithms in monitoring endemic diseases. It was shown that automated systems based on these detection methods identified changes in seroprevalence at different times. Increasing the number of tested herds would lead to faster detection. However, the practical implications of increasing the sample size (such as the costs associated with the disease) should also be taken into account. Copyright © 2016 Elsevier B.V. All rights reserved.

Assessment of Data Fusion Algorithms for Earth Observation Change Detection Processes

PubMed Central

Molina, Iñigo; Martinez, Estibaliz; Morillo, Carmen; Velasco, Jesus; Jara, Alvaro

2016-01-01

In this work a parametric multi-sensor Bayesian data fusion approach and a Support Vector Machine (SVM) are used for a Change Detection problem. For this purpose two sets of SPOT5-PAN images have been used, which are in turn used for Change Detection Indices (CDIs) calculation. For minimizing radiometric differences, a methodology based on zonal “invariant features” is suggested. The choice of one or the other CDI for a change detection process is a subjective task as each CDI is probably more or less sensitive to certain types of changes. Likewise, this idea might be employed to create and improve a “change map”, which can be accomplished by means of the CDI’s informational content. For this purpose, information metrics such as the Shannon Entropy and “Specific Information” have been used to weight the changes and no-changes categories contained in a certain CDI and thus introduced in the Bayesian information fusion algorithm. Furthermore, the parameters of the probability density functions (pdf’s) that best fit the involved categories have also been estimated. Conversely, these considerations are not necessary for mapping procedures based on the discriminant functions of a SVM. This work has confirmed the capabilities of probabilistic information fusion procedure under these circumstances. PMID:27706048

Plagiarism Detection for Indonesian Language using Winnowing with Parallel Processing

NASA Astrophysics Data System (ADS)

Arifin, Y.; Isa, S. M.; Wulandhari, L. A.; Abdurachman, E.

2018-03-01

The plagiarism has many forms, not only copy paste but include changing passive become active voice, or paraphrasing without appropriate acknowledgment. It happens on all language include Indonesian Language. There are many previous research that related with plagiarism detection in Indonesian Language with different method. But there are still some part that still has opportunity to improve. This research proposed the solution that can improve the plagiarism detection technique that can detect not only copy paste form but more advance than that. The proposed solution is using Winnowing with some addition process in pre-processing stage. With stemming processing in Indonesian Language and generate fingerprint in parallel processing that can saving time processing and produce the plagiarism result on the suspected document.

Land use change detection based on multi-date imagery from different satellite sensor systems

NASA Technical Reports Server (NTRS)

Stow, Douglas A.; Collins, Doretta; Mckinsey, David

1990-01-01

An empirical study is conducted to assess the accuracy of land use change detection using satellite image data acquired ten years apart by sensors with differing spatial resolutions. The primary goals of the investigation were to (1) compare standard change detection methods applied to image data of varying spatial resolution, (2) assess whether to transform the raster grid of the higher resolution image data to that of the lower resolution raster grid or vice versa in the registration process, (3) determine if Landsat/Thermatic Mapper or SPOT/High Resolution Visible multispectral data provide more accurate detection of land use changes when registered to historical Landsat/MSS data. It is concluded that image ratioing of multisensor, multidate satellite data produced higher change detection accuracies than did principal components analysis, and that it is useful as a land use change enhancement method.

Does working memory load facilitate target detection?

PubMed

Fruchtman-Steinbok, Tom; Kessler, Yoav

2016-02-01

Previous studies demonstrated that increasing working memory (WM) load delays performance of a concurrent task, by distracting attention and thus interfering with encoding and maintenance processes. The present study used a version of the change detection task with a target detection requirement during the retention interval. In contrast to the above prediction, target detection was faster following a larger set-size, specifically when presented shortly after the memory array (up to 400 ms). The effect of set-size on target detection was also evident when no memory retention was required. The set-size effect was also found using different modalities. Moreover, it was only observed when the memory array was presented simultaneously, but not sequentially. These results were explained by increased phasic alertness exerted by the larger visual display. The present study offers new evidence of ongoing attentional processes in the commonly-used change detection paradigm. Copyright © 2015 Elsevier B.V. All rights reserved.

Psychophysical Models for Signal Detection with Time Varying Uncertainty. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Gai, E.

1975-01-01

Psychophysical models for the behavior of the human operator in detection tasks which include change in detectability, correlation between observations and deferred decisions are developed. Classical Signal Detection Theory (SDT) is discussed and its emphasis on the sensory processes is contrasted to decision strategies. The analysis of decision strategies utilizes detection tasks with time varying signal strength. The classical theory is modified to include such tasks and several optimal decision strategies are explored. Two methods of classifying strategies are suggested. The first method is similar to the analysis of ROC curves, while the second is based on the relation between the criterion level (CL) and the detectability. Experiments to verify the analysis of tasks with changes of signal strength are designed. The results show that subjects are aware of changes in detectability and tend to use strategies that involve changes in the CL's.

California nearshore processes - ERTS 1. [coastal currents and sediments

NASA Technical Reports Server (NTRS)

Steller, D. D.; Pirie, D. M.

1974-01-01

The detectability of many nearshore processes from ERTS is made possible due to the suspended sediment present in the coastal waters. From viewing and analyzing the California coastal imagery collected during the last year and a half, the overall current patterns and their changes have become evident. It is now possible to map monthly and seasonal changes that occur throughout the year. The original objectives of detecting currents, sediment transport, estuaries and river discharge have now been expanded to include the use of ERTS information in operational problems of the U.S. Army Corps of Engineers. This incorporates the detected nearshore features into planning and organizing shore protection facilities.

Change detection from remotely sensed images: From pixel-based to object-based approaches

NASA Astrophysics Data System (ADS)

Hussain, Masroor; Chen, Dongmei; Cheng, Angela; Wei, Hui; Stanley, David

2013-06-01

The appetite for up-to-date information about earth's surface is ever increasing, as such information provides a base for a large number of applications, including local, regional and global resources monitoring, land-cover and land-use change monitoring, and environmental studies. The data from remote sensing satellites provide opportunities to acquire information about land at varying resolutions and has been widely used for change detection studies. A large number of change detection methodologies and techniques, utilizing remotely sensed data, have been developed, and newer techniques are still emerging. This paper begins with a discussion of the traditionally pixel-based and (mostly) statistics-oriented change detection techniques which focus mainly on the spectral values and mostly ignore the spatial context. This is succeeded by a review of object-based change detection techniques. Finally there is a brief discussion of spatial data mining techniques in image processing and change detection from remote sensing data. The merits and issues of different techniques are compared. The importance of the exponential increase in the image data volume and multiple sensors and associated challenges on the development of change detection techniques are highlighted. With the wide use of very-high-resolution (VHR) remotely sensed images, object-based methods and data mining techniques may have more potential in change detection.

Temporal Processing Ability Is Related to Ear-Asymmetry for Detecting Time Cues in Sound: A Mismatch Negativity (MMN) Study

ERIC Educational Resources Information Center

Todd, Juanita; Finch, Brayden; Smith, Ellen; Budd, Timothy W.; Schall, Ulrich

2011-01-01

Temporal and spectral sound information is processed asymmetrically in the brain with the left-hemisphere showing an advantage for processing the former and the right-hemisphere for the latter. Using monaural sound presentation we demonstrate a context and ability dependent ear-asymmetry in brain measures of temporal change detection. Our measure…

Signal existence verification (SEV) for GPS low received power signal detection using the time-frequency approach.

PubMed

Jan, Shau-Shiun; Sun, Chih-Cheng

2010-01-01

The detection of low received power of global positioning system (GPS) signals in the signal acquisition process is an important issue for GPS applications. Improving the miss-detection problem of low received power signal is crucial, especially for urban or indoor environments. This paper proposes a signal existence verification (SEV) process to detect and subsequently verify low received power GPS signals. The SEV process is based on the time-frequency representation of GPS signal, and it can capture the characteristic of GPS signal in the time-frequency plane to enhance the GPS signal acquisition performance. Several simulations and experiments are conducted to show the effectiveness of the proposed method for low received power signal detection. The contribution of this work is that the SEV process is an additional scheme to assist the GPS signal acquisition process in low received power signal detection, without changing the original signal acquisition or tracking algorithms.

Monitoring sediment transfer processes on the desert margin

NASA Technical Reports Server (NTRS)

Millington, Andrew C.; Arwyn, R. Jones; Quarmby, Neil; Townshend, John R. G.

1987-01-01

LANDSAT Thematic Mapper and Multispectral Scanner data have been used to construct change detection images for three playas in south-central Tunisia. Change detection images have been used to analyze changes in surface reflectance and absorption between wet and dry season (intra-annual change) and between different years (inter-annual change). Change detection imagery has been used to examine geomorphological changes on the playas. Changes in geomorphological phenomena are interpreted from changes in soil and foliar moisture levels, differences in reflectances between different salt and sediments and the spatial expression of geomorphological features. Intra-annual change phenomena that can be detected from multidate imagery are changes in surface moisture, texture and chemical composition, vegetation cover and the extent of aeolian activity. Inter-annual change phenomena are divisible into those restricted to marginal playa facies (sedimentation from sheetwash and alluvial fans, erosion from surface runoff and cliff retreat) and these are found in central playa facies which are related to the internal redistribution of water, salt and sediment.

Design-for-Hardware-Trust Techniques, Detection Strategies and Metrics for Hardware Trojans

DTIC Science & Technology

2015-12-14

down  both  rising  and  falling  transitions.  For  Trojan   detection ,   one   fault ,   slow-­‐to-­‐rise  or   slow-­‐to...in Jan. 2016. Through the course of this project we developed novel hardware Trojan detection techniques based on clock sweeping. The technique takes...algorithms to detect minor changes due to Trojan and compared them with those changes made by process variations. This technique was implemented on

Nonexplicit change detection in complex dynamic settings: what eye movements reveal.

PubMed

Vachon, François; Vallières, Benoît R; Jones, Dylan M; Tremblay, Sébastien

2012-12-01

We employed a computer-controlled command-and-control (C2) simulation and recorded eye movements to examine the extent and nature of the inability to detect critical changes in dynamic displays when change detection is implicit (i.e., requires no explicit report) to the operator's task. Change blindness-the failure to notice significant changes to a visual scene-may have dire consequences on performance in C2 and surveillance operations. Participants performed a radar-based risk-assessment task involving multiple subtasks. Although participants were not required to explicitly report critical changes to the operational display, change detection was critical in informing decision making. Participants' eye movements were used as an index of visual attention across the display. Nonfixated (i.e., unattended) changes were more likely to be missed than were fixated (i.e., attended) changes, supporting the idea that focused attention is necessary for conscious change detection. The finding of significant pupil dilation for changes undetected but fixated suggests that attended changes can nonetheless be missed because of a failure of attentional processes. Change blindness in complex dynamic displays takes the form of failures in establishing task-appropriate patterns of attentional allocation. These findings have implications in the design of change-detection support tools for dynamic displays and work procedure in C2 and surveillance.

External and internal facial features modulate processing of vertical but not horizontal spatial relations.

PubMed

Meinhardt, Günter; Kurbel, David; Meinhardt-Injac, Bozana; Persike, Malte

2018-03-22

Some years ago an asymmetry was reported for the inversion effect for horizontal (H) and vertical (V) relational face manipulations (Goffaux & Rossion, 2007). Subsequent research examined whether a specific disruption of long-range relations underlies the H/V inversion asymmetry (Sekunova & Barton, 2008). Here, we tested how detection of changes in interocular distance (H) and eye height (V) depends on cardinal internal features and external feature surround. Results replicated the H/V inversion asymmetry. Moreover, we found very different face cue dependencies for both change types. Performance and inversion effects did not depend on the presence of other face cues for detecting H changes. In contrast, accuracy for detecting V changes strongly depended on internal and external features, showing cumulative improvement when more cues were added. Inversion effects were generally large, and larger with external feature surround. The cue independence in detecting H relational changes indicates specialized local processing tightly tuned to the eyes region, while the strong cue dependency in detecting V relational changes indicates a global mechanism of cue integration across different face regions. These findings suggest that the H/V asymmetry of the inversion effect rests on an H/V anisotropy of face cue dependency, since only the global V mechanism suffers from disruption of cue integration as the major effect of face inversion. Copyright © 2018. Published by Elsevier Ltd.

Visual search for changes in scenes creates long-term, incidental memory traces.

PubMed

Utochkin, Igor S; Wolfe, Jeremy M

2018-05-01

Humans are very good at remembering large numbers of scenes over substantial periods of time. But how good are they at remembering changes to scenes? In this study, we tested scene memory and change detection two weeks after initial scene learning. In Experiments 1-3, scenes were learned incidentally during visual search for change. In Experiment 4, observers explicitly memorized scenes. At test, after two weeks observers were asked to discriminate old from new scenes, to recall a change that they had detected in the study phase, or to detect a newly introduced change in the memorization experiment. Next, they performed a change detection task, usually looking for the same change as in the study period. Scene recognition memory was found to be similar in all experiments, regardless of the study task. In Experiment 1, more difficult change detection produced better scene memory. Experiments 2 and 3 supported a "depth-of-processing" account for the effects of initial search and change detection on incidental memory for scenes. Of most interest, change detection was faster during the test phase than during the study phase, even when the observer had no explicit memory of having found that change previously. This result was replicated in two of our three change detection experiments. We conclude that scenes can be encoded incidentally as well as explicitly and that changes in those scenes can leave measurable traces even if they are not explicitly recalled.

Neural-Net Processed Characteristic Patterns for Measurement of Structural Integrity of Pressure Cycled Components

NASA Technical Reports Server (NTRS)

Decker, A. J.

2001-01-01

A neural-net inspection process has been combined with a bootstrap training procedure and electronic holography to detect changes or damage in a pressure-cycled International Space Station cold plate to be used for cooling instrumentation. The cold plate was excited to vibrate in a normal mode at low amplitude, and the neural net was trained by example to flag small changes in the mode shape. The NDE (nondestructive-evaluation) technique is straightforward but in its infancy; its applications are ad-hoc and uncalibrated. Nevertheless previous research has shown that the neural net can detect displacement changes to better than 1/100 the maximum displacement amplitude. Development efforts that support the NDE technique are mentioned briefly, followed by descriptions of electronic holography and neural-net processing. The bootstrap training procedure and its application to detection of damage in a pressure-cycled cold plate are discussed. Suggestions for calibrating and quantifying the NDE procedure are presented.

Hardware accelerator design for change detection in smart camera

NASA Astrophysics Data System (ADS)

Singh, Sanjay; Dunga, Srinivasa Murali; Saini, Ravi; Mandal, A. S.; Shekhar, Chandra; Chaudhury, Santanu; Vohra, Anil

2011-10-01

Smart Cameras are important components in Human Computer Interaction. In any remote surveillance scenario, smart cameras have to take intelligent decisions to select frames of significant changes to minimize communication and processing overhead. Among many of the algorithms for change detection, one based on clustering based scheme was proposed for smart camera systems. However, such an algorithm could achieve low frame rate far from real-time requirements on a general purpose processors (like PowerPC) available on FPGAs. This paper proposes the hardware accelerator capable of detecting real time changes in a scene, which uses clustering based change detection scheme. The system is designed and simulated using VHDL and implemented on Xilinx XUP Virtex-IIPro FPGA board. Resulted frame rate is 30 frames per second for QVGA resolution in gray scale.

Variable threshold method for ECG R-peak detection.

PubMed

Kew, Hsein-Ping; Jeong, Do-Un

2011-10-01

In this paper, a wearable belt-type ECG electrode worn around the chest by measuring the real-time ECG is produced in order to minimize the inconvenient in wearing. ECG signal is detected using a potential instrument system. The measured ECG signal is transmits via an ultra low power consumption wireless data communications unit to personal computer using Zigbee-compatible wireless sensor node. ECG signals carry a lot of clinical information for a cardiologist especially the R-peak detection in ECG. R-peak detection generally uses the threshold value which is fixed. There will be errors in peak detection when the baseline changes due to motion artifacts and signal size changes. Preprocessing process which includes differentiation process and Hilbert transform is used as signal preprocessing algorithm. Thereafter, variable threshold method is used to detect the R-peak which is more accurate and efficient than fixed threshold value method. R-peak detection using MIT-BIH databases and Long Term Real-Time ECG is performed in this research in order to evaluate the performance analysis.

Use of an Infrared Thermometer with Laser Targeting in Morphological Scene Change Detection for Fire Detection

NASA Astrophysics Data System (ADS)

Tickle, Andrew J.; Singh, Harjap; Grindley, Josef E.

2013-06-01

Morphological Scene Change Detection (MSCD) is a process typically tasked at detecting relevant changes in a guarded environment for security applications. This can be implemented on a Field Programmable Gate Array (FPGA) by a combination of binary differences based around exclusive-OR (XOR) gates, mathematical morphology and a crucial threshold setting. This is a robust technique and can be applied many areas from leak detection to movement tracking, and further augmented to perform additional functions such as watermarking and facial detection. Fire is a severe problem, and in areas where traditional fire alarm systems are not installed or feasible, it may not be detected until it is too late. Shown here is a way of adapting the traditional Morphological Scene Change Detector (MSCD) with a temperature sensor so if both the temperature sensor and scene change detector are triggered, there is a high likelihood of fire present. Such a system would allow integration into autonomous mobile robots so that not only security patrols could be undertaken, but also fire detection.

Attentional Modulation of Perceptual Comparison for Feature Binding

ERIC Educational Resources Information Center

Kuo, Bo-Cheng; Rotshtein, Pia; Yeh, Yei-Yu

2011-01-01

We investigated the neural correlates of attentional modulation in the perceptual comparison process for detecting feature-binding changes in an event-related functional magnetic resonance imaging (fMRI) experiment. Participants performed a variant of a cued change detection task. They viewed a memory array, a spatial retro-cue, and later a probe…

Change detection from synthetic aperture radar images based on neighborhood-based ratio and extreme learning machine

NASA Astrophysics Data System (ADS)

Gao, Feng; Dong, Junyu; Li, Bo; Xu, Qizhi; Xie, Cui

2016-10-01

Change detection is of high practical value to hazard assessment, crop growth monitoring, and urban sprawl detection. A synthetic aperture radar (SAR) image is the ideal information source for performing change detection since it is independent of atmospheric and sunlight conditions. Existing SAR image change detection methods usually generate a difference image (DI) first and use clustering methods to classify the pixels of DI into changed class and unchanged class. Some useful information may get lost in the DI generation process. This paper proposed an SAR image change detection method based on neighborhood-based ratio (NR) and extreme learning machine (ELM). NR operator is utilized for obtaining some interested pixels that have high probability of being changed or unchanged. Then, image patches centered at these pixels are generated, and ELM is employed to train a model by using these patches. Finally, pixels in both original SAR images are classified by the pretrained ELM model. The preclassification result and the ELM classification result are combined to form the final change map. The experimental results obtained on three real SAR image datasets and one simulated dataset show that the proposed method is robust to speckle noise and is effective to detect change information among multitemporal SAR images.

Method and apparatus for real time weld monitoring

DOEpatents

Leong, Keng H.; Hunter, Boyd V.

1997-01-01

An improved method and apparatus are provided for real time weld monitoring. An infrared signature emitted by a hot weld surface during welding is detected and this signature is compared with an infrared signature emitted by the weld surface during steady state conditions. The result is correlated with weld penetration. The signal processing is simpler than for either UV or acoustic techniques. Changes in the weld process, such as changes in the transmitted laser beam power, quality or positioning of the laser beam, change the resulting weld surface features and temperature of the weld surface, thereby resulting in a change in the direction and amount of infrared emissions. This change in emissions is monitored by an IR sensitive detecting apparatus that is sensitive to the appropriate wavelength region for the hot weld surface.

Parallel detection of violations of color constancy

PubMed Central

Foster, David H.; Nascimento, Sérgio M. C.; Amano, Kinjiro; Arend, Larry; Linnell, Karina J.; Nieves, Juan Luis; Plet, Sabrina; Foster, Jeffrey S.

2001-01-01

The perceived colors of reflecting surfaces generally remain stable despite changes in the spectrum of the illuminating light. This color constancy can be measured operationally by asking observers to distinguish illuminant changes on a scene from changes in the reflecting properties of the surfaces comprising it. It is shown here that during fast illuminant changes, simultaneous changes in spectral reflectance of one or more surfaces in an array of other surfaces can be readily detected almost independent of the numbers of surfaces, suggesting a preattentive, spatially parallel process. This process, which is perfect over a spatial window delimited by the anatomical fovea, may form an early input to a multistage analysis of surface color, providing the visual system with information about a rapidly changing world in advance of the generation of a more elaborate and stable perceptual representation. PMID:11438751

Variance change point detection for fractional Brownian motion based on the likelihood ratio test

NASA Astrophysics Data System (ADS)

Kucharczyk, Daniel; Wyłomańska, Agnieszka; Sikora, Grzegorz

2018-01-01

Fractional Brownian motion is one of the main stochastic processes used for describing the long-range dependence phenomenon for self-similar processes. It appears that for many real time series, characteristics of the data change significantly over time. Such behaviour one can observe in many applications, including physical and biological experiments. In this paper, we present a new technique for the critical change point detection for cases where the data under consideration are driven by fractional Brownian motion with a time-changed diffusion coefficient. The proposed methodology is based on the likelihood ratio approach and represents an extension of a similar methodology used for Brownian motion, the process with independent increments. Here, we also propose a statistical test for testing the significance of the estimated critical point. In addition to that, an extensive simulation study is provided to test the performance of the proposed method.

Attentional Modulation of Change Detection ERP Components by Peripheral Retro-Cueing

PubMed Central

Pazo-Álvarez, Paula; Roca-Fernández, Adriana; Gutiérrez-Domínguez, Francisco-Javier; Amenedo, Elena

2017-01-01

Change detection is essential for visual perception and performance in our environment. However, observers often miss changes that should be easily noticed. A failure in any of the processes involved in conscious detection (encoding the pre-change display, maintenance of that information within working memory, and comparison of the pre and post change displays) can lead to change blindness. Given that unnoticed visual changes in a scene can be easily detected once attention is drawn to them, it has been suggested that attention plays an important role on visual awareness. In the present study, we used behavioral and electrophysiological (ERPs) measures to study whether the manipulation of retrospective spatial attention affects performance and modulates brain activity related to the awareness of a change. To that end, exogenous peripheral cues were presented during the delay period (retro-cues) between the first and the second array using a one-shot change detection task. Awareness of a change was associated with a posterior negative amplitude shift around 228–292 ms (“Visual Awareness Negativity”), which was independent of retrospective spatial attention, as it was elicited to both validly and invalidly cued change trials. Change detection was also associated with a larger positive deflection around 420–580 ms (“Late Positivity”), but only when the peripheral retro-cues correctly predicted the change. Present results confirm that the early and late ERP components related to change detection can be functionally dissociated through manipulations of exogenous retro-cueing using a change blindness paradigm. PMID:28270759

Automated Processing of 2-D Gel Electrophoretograms of Genomic DNA for Hunting Pathogenic DNA Molecular Changes.

PubMed

Takahashi; Nakazawa; Watanabe; Konagaya

1999-01-01

We have developed the automated processing algorithms for 2-dimensional (2-D) electrophoretograms of genomic DNA based on RLGS (Restriction Landmark Genomic Scanning) method, which scans the restriction enzyme recognition sites as the landmark and maps them onto a 2-D electrophoresis gel. Our powerful processing algorithms realize the automated spot recognition from RLGS electrophoretograms and the automated comparison of a huge number of such images. In the final stage of the automated processing, a master spot pattern, on which all the spots in the RLGS images are mapped at once, can be obtained. The spot pattern variations which seemed to be specific to the pathogenic DNA molecular changes can be easily detected by simply looking over the master spot pattern. When we applied our algorithms to the analysis of 33 RLGS images derived from human colon tissues, we successfully detected several colon tumor specific spot pattern changes.

Monitoring gypsy moth defoliation by applying change detection techniques to Landsat imagery

NASA Technical Reports Server (NTRS)

Williams, D. L.; Stauffer, M. L.

1978-01-01

The overall objective of a research effort at NASA's Goddard Space Flight Center is to develop and evaluate digital image processing techniques that will facilitate the assessment of the intensity and spatial distribution of forest insect damage in Northeastern U.S. forests using remotely sensed data from Landsats 1, 2 and C. Automated change detection techniques are presently being investigated as a method of isolating the areas of change in the forest canopy resulting from pest outbreaks. In order to follow the change detection approach, Landsat scene correction and overlay capabilities are utilized to provide multispectral/multitemporal image files of 'defoliation' and 'nondefoliation' forest stand conditions.

Detecting Abrupt Changes in a Piecewise Locally Stationary Time Series

PubMed Central

Last, Michael; Shumway, Robert

2007-01-01

Non-stationary time series arise in many settings, such as seismology, speech-processing, and finance. In many of these settings we are interested in points where a model of local stationarity is violated. We consider the problem of how to detect these change-points, which we identify by finding sharp changes in the time-varying power spectrum. Several different methods are considered, and we find that the symmetrized Kullback-Leibler information discrimination performs best in simulation studies. We derive asymptotic normality of our test statistic, and consistency of estimated change-point locations. We then demonstrate the technique on the problem of detecting arrival phases in earthquakes. PMID:19190715

Change Detection Processing Chain Dedicated to Sentinel Data Time Series. Application to Forest and Water Bodies Monitoring

NASA Astrophysics Data System (ADS)

Perez Saavedra, L.-M.; Mercier, G.; Yesou, H.; Liege, F.; Pasero, G.

2016-08-01

The Copernicus program of ESA and European commission (6 Sentinels Missions, among them Sentinel-1 with Synthetic Aperture Radar sensor and Sentinel-2 with 13-band 10 to 60 meter resolution optical sensors), offers a new opportunity to Earth Observation with high temporal acquisition capability ( 12 days repetitiveness and 5 days in some geographic areas of the world) with high spatial resolution.Due to these high temporal and spatial resolutions, it opens new challenges in several fields such as image processing, new algorithms for Time Series and big data analysis. In addition, these missions will be able to analyze several topics of earth temporal evolution such as crop vegetation, water bodies, Land use and Land Cover (LULC), sea and ice information, etc. This is particularly useful for end users and policy makers to detect early signs of damages, vegetation illness, flooding areas, etc.From the state of the art, one can find algorithms and methods that use a bi-date comparison for change detection [1-3] or time series analysis. Actually, these methods are essentially used for target detection or for abrupt change detection that requires 2 observations only.A Hölder means-based change detection technique has been proposed in [2,3] for high resolution radar images. This so-called MIMOSA technique has been mainly dedicated to man-made change detection in urban areas and CARABAS - II project by using a couple of SAR images. An extension to multitemporal change detection technique has been investigated but its application to land use and cover changes still has to be validated.The Hölder Hp is a Time Series pixel by pixel feature extraction and is defined by:H𝑝[X]=[1/n∑ⁿᵢ₌1 Xᴾᵢ]1/p p∈R Hp[X] : N images * S Bandes * t datesn is the number of images in the time series. N > 2Hp (X) is continuous and monotonic increasing in p for - ∞ < p < ∞

SWCD: a sliding window and self-regulated learning-based background updating method for change detection in videos

NASA Astrophysics Data System (ADS)

Işık, Şahin; Özkan, Kemal; Günal, Serkan; Gerek, Ömer Nezih

2018-03-01

Change detection with background subtraction process remains to be an unresolved issue and attracts research interest due to challenges encountered on static and dynamic scenes. The key challenge is about how to update dynamically changing backgrounds from frames with an adaptive and self-regulated feedback mechanism. In order to achieve this, we present an effective change detection algorithm for pixelwise changes. A sliding window approach combined with dynamic control of update parameters is introduced for updating background frames, which we called sliding window-based change detection. Comprehensive experiments on related test videos show that the integrated algorithm yields good objective and subjective performance by overcoming illumination variations, camera jitters, and intermittent object motions. It is argued that the obtained method makes a fair alternative in most types of foreground extraction scenarios; unlike case-specific methods, which normally fail for their nonconsidered scenarios.

SAR Image Change Detection Based on Fuzzy Markov Random Field Model

NASA Astrophysics Data System (ADS)

Zhao, J.; Huang, G.; Zhao, Z.

2018-04-01

Most existing SAR image change detection algorithms only consider single pixel information of different images, and not consider the spatial dependencies of image pixels. So the change detection results are susceptible to image noise, and the detection effect is not ideal. Markov Random Field (MRF) can make full use of the spatial dependence of image pixels and improve detection accuracy. When segmenting the difference image, different categories of regions have a high degree of similarity at the junction of them. It is difficult to clearly distinguish the labels of the pixels near the boundaries of the judgment area. In the traditional MRF method, each pixel is given a hard label during iteration. So MRF is a hard decision in the process, and it will cause loss of information. This paper applies the combination of fuzzy theory and MRF to the change detection of SAR images. The experimental results show that the proposed method has better detection effect than the traditional MRF method.

Depth of Lexical-Semantic Processing and Sentential Load

ERIC Educational Resources Information Center

Sanford, Alison J. S.; Sanford, Anthony J.; Filik, Ruth; Molle, Jo

2005-01-01

The text-change detection task has been used to show that changes are more readily detected for words that fall under narrow focus than broad focus (Sturt, Sanford, Stewart, & Dawydiak, 2004), and that narrow focus appears to lead to finer semantic distinctions being held in the representation of the word. The present experiments apply the same…

Mistake proofing: changing designs to reduce error

PubMed Central

Grout, J R

2006-01-01

Mistake proofing uses changes in the physical design of processes to reduce human error. It can be used to change designs in ways that prevent errors from occurring, to detect errors after they occur but before harm occurs, to allow processes to fail safely, or to alter the work environment to reduce the chance of errors. Effective mistake proofing design changes should initially be effective in reducing harm, be inexpensive, and easily implemented. Over time these design changes should make life easier and speed up the process. Ideally, the design changes should increase patients' and visitors' understanding of the process. These designs should themselves be mistake proofed and follow the good design practices of other disciplines. PMID:17142609

MODIS NDVI Change Detection Techniques and Products Used in the Near Real Time ForWarn System for Detecting, Monitoring, and Analyzing Regional Forest Disturbances

NASA Technical Reports Server (NTRS)

Spruce, Joseph P.; Hargrove, William; Gasser, Jerry; Smoot, James; Kuper, Philip D.

2014-01-01

This presentation discusses MODIS NDVI change detection methods and products used in the ForWarn Early Warning System (EWS) for near real time (NRT) recognition and tracking of regionally evident forest disturbances throughout the conterminous US (CONUS). The latter has provided NRT forest change products to the forest health protection community since 2010, using temporally processed MODIS Aqua and Terra NDVI time series data to currently compute and post 6 different forest change products for CONUS every 8 days. Multiple change products are required to improve detectability and to more fully assess the nature of apparent disturbances. Each type of forest change product reports per pixel percent change in NDVI for a given 24 day interval, comparing current versus a given historical baseline NDVI. EMODIS 7 day expedited MODIS MOD13 data are used to obtain current and historical NDVIs, respectively. Historical NDVI data is processed with Time Series Product Tool (TSPT); and 2) the Phenological Parameters Estimation Tool (PPET) software. While each change products employ maximum value compositing (MVC) of NDVI, the design of specific products primarily differs in terms of the historical baseline. The three main change products use either 1, 3, or all previous years of MVC NDVI as a baseline. Another product uses an Adaptive Length Compositing (ALC) version of MVC to derive an alternative current NDVI that is the freshest quality NDVI as opposed to merely the MVC NDVI across a 24 day time frame. The ALC approach can improve detection speed by 8 to 16 days. ForWarn also includes 2 change products that improve detectability of forest disturbances in lieu of climatic fluctuations, especially in the spring and fall. One compares current MVC NDVI to the zonal maximum under the curve NDVI per pheno-region cluster class, considering all previous years in the MODIS record. The other compares current maximum NDVI to the mean of maximum NDVI for all previous MODIS years.

Detection of cardiac activity changes from human speech

NASA Astrophysics Data System (ADS)

Tovarek, Jaromir; Partila, Pavol; Voznak, Miroslav; Mikulec, Martin; Mehic, Miralem

2015-05-01

Impact of changes in blood pressure and pulse from human speech is disclosed in this article. The symptoms of increased physical activity are pulse, systolic and diastolic pressure. There are many methods of measuring and indicating these parameters. The measurements must be carried out using devices which are not used in everyday life. In most cases, the measurement of blood pressure and pulse following health problems or other adverse feelings. Nowadays, research teams are trying to design and implement modern methods in ordinary human activities. The main objective of the proposal is to reduce the delay between detecting the adverse pressure and to the mentioned warning signs and feelings. Common and frequent activity of man is speaking, while it is known that the function of the vocal tract can be affected by the change in heart activity. Therefore, it can be a useful parameter for detecting physiological changes. A method for detecting human physiological changes by speech processing and artificial neural network classification is described in this article. The pulse and blood pressure changes was induced by physical exercises in this experiment. The set of measured subjects was formed by ten healthy volunteers of both sexes. None of the subjects was a professional athlete. The process of the experiment was divided into phases before, during and after physical training. Pulse, systolic, diastolic pressure was measured and voice activity was recorded after each of them. The results of this experiment describe a method for detecting increased cardiac activity from human speech using artificial neural network.

Presenting a model for dynamic facial expression changes in detecting drivers' drowsiness.

PubMed

Karchani, Mohsen; Mazloumi, Adel; Saraji, Gebraeil Nasl; Gharagozlou, Faramarz; Nahvi, Ali; Haghighi, Khosro Sadeghniiat; Abadi, Bahador Makki; Foroshani, Abbas Rahimi

2015-01-01

Drowsiness while driving is a major cause of accidents. A driver fatigue detection system that is designed to sound an alarm, when appropriate, can prevent many accidents that sometime leads to the loss of life and property. In this paper, we classify drowsiness detection sensors and their strong and weak points. A compound model is proposed that uses image processing techniques to study the dynamic changes of the face to recognize drowsiness during driving.

Analysis of surface deformation during the eruptive process of El Hierro Island (Canary Islands, Spain): Detection, Evolution and Forecasting.

NASA Astrophysics Data System (ADS)

Berrocoso, M.; Fernandez-Ros, A.; Prates, G.; Martin, M.; Hurtado, R.; Pereda, J.; Garcia, M. J.; Garcia-Cañada, L.; Ortiz, R.; Garcia, A.

2012-04-01

The surface deformation has been an essential parameter for the onset and evolution of the eruptive process of the island of El Hierro (October 2011) as well as for forecasting changes in seismic and volcanic activity during the crisis period. From GNSS-GPS observations the reactivation is early detected by analizing the change in the deformation of the El Hierro Island regional geodynamics. It is found that the surface deformation changes are detected before the occurrence of seismic activity using the station FRON (GRAFCAN). The evolution of the process has been studied by the analysis of time series of topocentric coordinates and the variation of the distance between stations on the island of El Hierro (GRAFCAN station;IGN network; and UCA-CSIC points) and LPAL-IGS station on the island of La Palma. In this work the main methodologies and their results are shown: •The location (and its changes) of the litospheric pressure source obtained by applying the Mogi model. •Kalman filtering technique for high frequency time series, used to make the forecasts issued for volcanic emergency management. •Correlations between deformation of the different GPS stations and their relationship with seismovolcanic settings.

Automatic Co-Registration of QuickBird Data for Change Detection Applications

NASA Technical Reports Server (NTRS)

Bryant, Nevin A.; Logan, Thomas L.; Zobrist, Albert L.

2006-01-01

This viewgraph presentation reviews the use Automatic Fusion of Image Data System (AFIDS) for Automatic Co-Registration of QuickBird Data to ascertain if changes have occurred in images. The process is outlined, and views from Iraq and Los Angelels are shown to illustrate the process.

A landsat data tiling and compositing approach optimized for change detection in the conterminous United States

USGS Publications Warehouse

Nelson, Kurtis; Steinwand, Daniel R.

2015-01-01

Annual disturbance maps are produced by the LANDFIRE program across the conterminous United States (CONUS). Existing LANDFIRE disturbance data from 1999 to 2010 are available and current efforts will produce disturbance data through 2012. A tiling and compositing approach was developed to produce bi-annual images optimized for change detection. A tiled grid of 10,000 × 10,000 30 m pixels was defined for CONUS and adjusted to consolidate smaller tiles along national borders, resulting in 98 non-overlapping tiles. Data from Landsat-5,-7, and -8 were re-projected to the tile extents, masked to remove clouds, shadows, water, and snow/ice, then composited using a cosine similarity approach. The resultant images were used in a change detection algorithm to determine areas of vegetation change. This approach enabled more efficient processing compared to using single Landsat scenes, by taking advantage of overlap between adjacent paths, and allowed an automated system to be developed for the entire process.

Pulsation Detection from Noisy Ultrasound-Echo Moving Images of Newborn Baby Head Using Fourier Transform

NASA Astrophysics Data System (ADS)

Yamada, Masayoshi; Fukuzawa, Masayuki; Kitsunezuka, Yoshiki; Kishida, Jun; Nakamori, Nobuyuki; Kanamori, Hitoshi; Sakurai, Takashi; Kodama, Souichi

1995-05-01

In order to detect pulsation from a series of noisy ultrasound-echo moving images of a newborn baby's head for pediatric diagnosis, a digital image processing system capable of recording at the video rate and processing the recorded series of images was constructed. The time-sequence variations of each pixel value in a series of moving images were analyzed and then an algorithm based on Fourier transform was developed for the pulsation detection, noting that the pulsation associated with blood flow was periodically changed by heartbeat. Pulsation detection for pediatric diagnosis was successfully made from a series of noisy ultrasound-echo moving images of newborn baby's head by using the image processing system and the pulsation detection algorithm developed here.

Recognizing the Operating Hand and the Hand-Changing Process for User Interface Adjustment on Smartphones †

PubMed Central

Guo, Hansong; Huang, He; Huang, Liusheng; Sun, Yu-E

2016-01-01

As the size of smartphone touchscreens has become larger and larger in recent years, operability with a single hand is getting worse, especially for female users. We envision that user experience can be significantly improved if smartphones are able to recognize the current operating hand, detect the hand-changing process and then adjust the user interfaces subsequently. In this paper, we proposed, implemented and evaluated two novel systems. The first one leverages the user-generated touchscreen traces to recognize the current operating hand, and the second one utilizes the accelerometer and gyroscope data of all kinds of activities in the user’s daily life to detect the hand-changing process. These two systems are based on two supervised classifiers constructed from a series of refined touchscreen trace, accelerometer and gyroscope features. As opposed to existing solutions that all require users to select the current operating hand or confirm the hand-changing process manually, our systems follow much more convenient and practical methods and allow users to change the operating hand frequently without any harm to the user experience. We conduct extensive experiments on Samsung Galaxy S4 smartphones, and the evaluation results demonstrate that our proposed systems can recognize the current operating hand and detect the hand-changing process with 94.1% and 93.9% precision and 94.1% and 93.7% True Positive Rates (TPR) respectively, when deciding with a single touchscreen trace or accelerometer-gyroscope data segment, and the False Positive Rates (FPR) are as low as 2.6% and 0.7% accordingly. These two systems can either work completely independently and achieve pretty high accuracies or work jointly to further improve the recognition accuracy. PMID:27556461

Recognizing the Operating Hand and the Hand-Changing Process for User Interface Adjustment on Smartphones.

PubMed

Guo, Hansong; Huang, He; Huang, Liusheng; Sun, Yu-E

2016-08-20

As the size of smartphone touchscreens has become larger and larger in recent years, operability with a single hand is getting worse, especially for female users. We envision that user experience can be significantly improved if smartphones are able to recognize the current operating hand, detect the hand-changing process and then adjust the user interfaces subsequently. In this paper, we proposed, implemented and evaluated two novel systems. The first one leverages the user-generated touchscreen traces to recognize the current operating hand, and the second one utilizes the accelerometer and gyroscope data of all kinds of activities in the user's daily life to detect the hand-changing process. These two systems are based on two supervised classifiers constructed from a series of refined touchscreen trace, accelerometer and gyroscope features. As opposed to existing solutions that all require users to select the current operating hand or confirm the hand-changing process manually, our systems follow much more convenient and practical methods and allow users to change the operating hand frequently without any harm to the user experience. We conduct extensive experiments on Samsung Galaxy S4 smartphones, and the evaluation results demonstrate that our proposed systems can recognize the current operating hand and detect the hand-changing process with 94.1% and 93.9% precision and 94.1% and 93.7% True Positive Rates (TPR) respectively, when deciding with a single touchscreen trace or accelerometer-gyroscope data segment, and the False Positive Rates (FPR) are as low as 2.6% and 0.7% accordingly. These two systems can either work completely independently and achieve pretty high accuracies or work jointly to further improve the recognition accuracy.

Real-time traffic sign recognition based on a general purpose GPU and deep-learning.

PubMed

Lim, Kwangyong; Hong, Yongwon; Choi, Yeongwoo; Byun, Hyeran

2017-01-01

We present a General Purpose Graphics Processing Unit (GPGPU) based real-time traffic sign detection and recognition method that is robust against illumination changes. There have been many approaches to traffic sign recognition in various research fields; however, previous approaches faced several limitations when under low illumination or wide variance of light conditions. To overcome these drawbacks and improve processing speeds, we propose a method that 1) is robust against illumination changes, 2) uses GPGPU-based real-time traffic sign detection, and 3) performs region detecting and recognition using a hierarchical model. This method produces stable results in low illumination environments. Both detection and hierarchical recognition are performed in real-time, and the proposed method achieves 0.97 F1-score on our collective dataset, which uses the Vienna convention traffic rules (Germany and South Korea).

Metacognitive monitoring and control in visual change detection: Implications for situation awareness and cognitive control

PubMed Central

McAnally, Ken I.; Morris, Adam P.; Best, Christopher

2017-01-01

Metacognitive monitoring and control of situation awareness (SA) are important for a range of safety-critical roles (e.g., air traffic control, military command and control). We examined the factors affecting these processes using a visual change detection task that included representative tactical displays. SA was assessed by asking novice observers to detect changes to a tactical display. Metacognitive monitoring was assessed by asking observers to estimate the probability that they would correctly detect a change, either after study of the display and before the change (judgement of learning; JOL) or after the change and detection response (judgement of performance; JOP). In Experiment 1, observers failed to detect some changes to the display, indicating imperfect SA, but JOPs were reasonably well calibrated to objective performance. Experiment 2 examined JOLs and JOPs in two task contexts: with study-time limits imposed by the task or with self-pacing to meet specified performance targets. JOPs were well calibrated in both conditions as were JOLs for high performance targets. In summary, observers had limited SA, but good insight about their performance and learning for high performance targets and allocated study time appropriately. PMID:28915244

Automated terrestrial laser scanning with near-real-time change detection - monitoring of the Séchilienne landslide

NASA Astrophysics Data System (ADS)

Kromer, Ryan A.; Abellán, Antonio; Hutchinson, D. Jean; Lato, Matt; Chanut, Marie-Aurelie; Dubois, Laurent; Jaboyedoff, Michel

2017-05-01

We present an automated terrestrial laser scanning (ATLS) system with automatic near-real-time change detection processing. The ATLS system was tested on the Séchilienne landslide in France for a 6-week period with data collected at 30 min intervals. The purpose of developing the system was to fill the gap of high-temporal-resolution TLS monitoring studies of earth surface processes and to offer a cost-effective, light, portable alternative to ground-based interferometric synthetic aperture radar (GB-InSAR) deformation monitoring. During the study, we detected the flux of talus, displacement of the landslide and pre-failure deformation of discrete rockfall events. Additionally, we found the ATLS system to be an effective tool in monitoring landslide and rockfall processes despite missing points due to poor atmospheric conditions or rainfall. Furthermore, such a system has the potential to help us better understand a wide variety of slope processes at high levels of temporal detail.

Neuromorphic optical sensor chip with color change-intensity change disambiguation

NASA Astrophysics Data System (ADS)

Fu, ZhenHong; Mao, Rui; Cartwright, Alexander N.; Titus, Albert H.

2010-02-01

In this paper, we describe the development of a novel, retina-like neuromorphic chip that has an array of two types of retina 'cells' arranged to mimic the fovea structure in certain animals. One of the two retina cell types performs irradiance detection and the other can perform color detection. Together, via the two parallel pathways the retina chip can perform color change intensity change disambiguation (CCICD). The irradiance detection cell has a wide-dynamic detection range that spans almost 3 orders of magnitude. The color detection cell has a buried double junction (BDJ) photodiode as the photoreceptor followed by two parallel logarithmic I-V convertors. The output from this is a color response which has at least a 50nm resolution for wavelengths from 400nm to 900nm. With these two cells, the array can perform color change -intensity change disambiguation (CCICD) to determine if a change in the output of the irradiance pathway is because of irradiance change, color change, or both. This biological retina-like neuromorphic sensor array is implemented in ON-SEMI 0.5μm technology, a standard CMOS fabrication process available at MOSIS.

The influence of operational and environmental loads on the process of assessing damages in beams

NASA Astrophysics Data System (ADS)

Furdui, H.; Muntean, F.; Minda, A. A.; Praisach, Z. I.; Gillich, N.

2015-07-01

Damage detection methods based on vibration analysis make use of the modal parameter changes. Natural frequencies are the features that can be acquired most simply and inexpensively. But this parameter is influenced by environmental conditions, e.g. temperature and operational loads as additional masses or axial loads induced by restraint displacements. The effect of these factors is not completely known, but in the numerous actual research it is considered that they affect negatively the damage assessment process. This is justified by the small frequency changes occurring due to damage, which can be masked by the frequency shifts due to external loads. The paper intends to clarify the effect of external loads on the natural frequencies of beams and truss elements, and to show in which manner the damage detection process is affected by these loads. The finite element analysis, performed on diverse structures for a large range of temperature values, has shown that the temperature itself has a very limited effect on the frequency changes. Thus, axial forces resulted due to obstructed displacements can influence more substantially the frequency changes. These facts are demonstrated by experimental and theoretical studies. Finally, we succeed to adapt a prior contrived relation providing the frequency changes due to damage in order to fit the case of known external loads. Whereas a new baseline for damage detection was found, considering the effect of temperature and external loads, this process can be performed without other complication.

Development of infant mismatch responses to auditory pattern changes between 2 and 4 months old.

PubMed

He, Chao; Hotson, Lisa; Trainor, Laurel J

2009-02-01

In order to process speech and music, the auditory cortex must learn to process patterns of sounds. Our previous studies showed that with a stream consisting of a repeating (standard) sound, younger infants show an increase in the amplitude of a positive slow wave in response to occasional changes (deviants) in pitch or duration, whereas older infants show a faster negative response that resembles mismatch negativity (MMN) in adults (Trainor et al., 2001, 2003; He et al., 2007). MMN reflects an automatic change-detection process that does not require attention, conscious awareness or behavioural response for its elicitation (Picton et al., 2000; Näätänen et al., 2007). It is an important tool for understanding auditory perception because MMN reflects a change-detection mechanism, and not simply that repetition of a stimulus results in a refractory state of sensory neural circuits while occasional changes to a new sound activate new non-refractory neural circuits (Näätänen et al., 2005). For example, MMN is elicited by a change in the pattern of a repeating note sequence, even when no new notes are introduced that could activate new sensory circuits (Alain et al., 1994, 1999;Schröger et al., 1996). In the present study, we show that in response to a change in the pattern of two repeating tones, MMN in 4-month-olds remains robust whereas the 2-month-old response does not. This indicates that the MMN response to a change in pattern at 4 months reflects the activation of a change-detection mechanism similarly as in adults.

Assessment of landscape change associated with tropical cyclone phenomena in Baja California Sur, Mexico, using satellite remote sensing

NASA Astrophysics Data System (ADS)

Martinez-Gutierrez, Genaro

Baja California Sur (Mexico), as well as mainland Mexico, is affected by tropical cyclone storms, which originate in the eastern north Pacific. Historical records show that Baja has been damaged by intense summer storms. An arid to semiarid climate characterizes the study area, where precipitation mainly occurs during the summer and winter seasons. Natural and anthropogenic changes have impacted the landscape of southern Baja. The present research documents the effects of tropical storms over the southern region of Baja California for a period of approximately twenty-six years. The goal of the research is to demonstrate how remote sensing can be used to detect the important effects of tropical storms including: (a) evaluation of change detection algorithms, and (b) delineating changes to the landscape including coastal modification, fluvial erosion and deposition, vegetation change, river avulsion using change detection algorithms. Digital image processing methods with temporal Landsat satellite remotely sensed data from the North America Landscape Characterization archive (NALC), Thematic Mapper (TM), and Enhanced Thematic Mapper (ETM) images were used to document the landscape change. Two image processing methods were tested including Image differencing (ID), and Principal Component Analysis (PCA). Landscape changes identified with the NALC archive and TM images showed that the major changes included a rapid change of land use in the towns of San Jose del Cabo and Cabo San Lucas between 1973 and 1986. The features detected using the algorithms included flood deposits within the channels of active streams, erosion banks, and new channels caused by channel avulsion. Despite the 19 year period covered by the NALC data and approximately 10 year intervals between acquisition dates, there were changed features that could be identified in the images. The TM images showed that flooding from Hurricane Isis (1998) produced new large deposits within the stream channels. This research has shown that remote sensing based change detection can delineate the effects of flooding on the landscape at scales down to the nominal resolution of the sensor. These findings indicate that many other applications for change detection are both viable and important. These include disaster response, flood hazard planning, geomorphic studies, water supply management in deserts.

The effect of a graphical interpretation of a statistic trend indicator (Trigg's Tracking Variable) on the detection of simulated changes.

PubMed

Kennedy, R R; Merry, A F

2011-09-01

Anaesthesia involves processing large amounts of information over time. One task of the anaesthetist is to detect substantive changes in physiological variables promptly and reliably. It has been previously demonstrated that a graphical trend display of historical data leads to more rapid detection of such changes. We examined the effect of a graphical indication of the magnitude of Trigg's Tracking Variable, a simple statistically based trend detection algorithm, on the accuracy and latency of the detection of changes in a micro-simulation. Ten anaesthetists each viewed 20 simulations with four variables displayed as the current value with a simple graphical trend display. Values for these variables were generated by a computer model, and updated every second; after a period of stability a change occurred to a new random value at least 10 units from baseline. In 50% of the simulations an indication of the rate of change was given by a five level graphical representation of the value of Trigg's Tracking Variable. Participants were asked to indicate when they thought a change was occurring. Changes were detected 10.9% faster with the trend indicator present (mean 13.1 [SD 3.1] cycles vs 14.6 [SD 3.4] cycles, 95% confidence interval 0.4 to 2.5 cycles, P = 0.013. There was no difference in accuracy of detection (median with trend detection 97% [interquartile range 95 to 100%], without trend detection 100% [98 to 100%]), P = 0.8. We conclude that simple statistical trend detection may speed detection of changes during routine anaesthesia, even when a graphical trend display is present.

Diffusion tensor imaging detects age related white matter change over a 2 year follow-up which is associated with working memory decline.

PubMed

Charlton, R A; Schiavone, F; Barrick, T R; Morris, R G; Markus, H S

2010-01-01

Diffusion tensor imaging (DTI) is a sensitive method for detecting white matter damage, and in cross sectional studies DTI measures correlate with age related cognitive decline. However, there are few data on whether DTI can detect age related changes over short time periods and whether such change correlates with cognitive function. In a community sample of 84 middle-aged and elderly adults, MRI and cognitive testing were performed at baseline and after 2 years. Changes in DTI white matter histograms, white matter hyperintensity (WMH) volume and brain volume were determined. Change over time in performance on tests of executive function, working memory and information processing speed were also assessed. Significant change in all MRI measures was detected. For cognition, change was detected for working memory and this correlated with change in DTI only. In a stepwise regression, with change in working memory as the dependent variable, a DTI histogram measure explained 10.8% of the variance in working memory. Change in WMH or brain volume did not contribute to the model. DTI is sensitive to age related change in white matter ultrastructure and appears useful for monitoring age related white matter change even over short time periods.

Exponentially Weighted Moving Average Change Detection Around the Country (and the World)

NASA Astrophysics Data System (ADS)

Brooks, E.; Wynne, R. H.; Thomas, V. A.; Blinn, C. E.; Coulston, J.

2014-12-01

With continuous, freely available moderate-resolution imagery of the Earth's surface available, and with the promise of more imagery to come, change detection based on continuous process models continues to be a major area of research. One such method, exponentially weighted moving average change detection (EWMACD), is based on a mixture of harmonic regression (HR) and statistical quality control, a branch of statistics commonly used to detect aberrations in industrial and medical processes. By using HR to approximate per-pixel seasonal curves, the resulting residuals characterize information about the pixels which stands outside of the periodic structure imposed by HR. Under stable pixels, these residuals behave as might be expected, but in the presence of changes (growth, stress, removal), the residuals clearly show these changes when they are used as inputs into an EWMA chart. In prior work in Alabama, USA, EWMACD yielded an overall accuracy of 85% on a random sample of known thinned stands, in some cases detecting thinnings as sparse as 25% removal. It was also shown to correctly identify the timing of the thinning activity, typically within a single image date of the change. The net result of the algorithm was to produce date-by-date maps of afforestation and deforestation on a variable scale of severity. In other research, EWMACD has also been applied to detect land use and land cover changes in central Java, Indonesia, despite the heavy incidence of clouds and a monsoonal climate. Preliminary results show that EWMACD accurately identifies land use conversion (agricultural to residential, for example) and also identifies neighborhoods where the building density has increased, removing neighborhood vegetation. In both cases, initial results indicate the potential utility of EWMACD to detect both gross and subtle ecosystem disturbance, but further testing across a range of ecosystems and disturbances is clearly warranted.

Presenting a model for dynamic facial expression changes in detecting drivers’ drowsiness

PubMed Central

Karchani, Mohsen; Mazloumi, Adel; Saraji, Gebraeil Nasl; Gharagozlou, Faramarz; Nahvi, Ali; Haghighi, Khosro Sadeghniiat; Abadi, Bahador Makki; Foroshani, Abbas Rahimi

2015-01-01

Drowsiness while driving is a major cause of accidents. A driver fatigue detection system that is designed to sound an alarm, when appropriate, can prevent many accidents that sometime leads to the loss of life and property. In this paper, we classify drowsiness detection sensors and their strong and weak points. A compound model is proposed that uses image processing techniques to study the dynamic changes of the face to recognize drowsiness during driving. PMID:26120417

Information transmission using non-poisson regular firing.

PubMed

Koyama, Shinsuke; Omi, Takahiro; Kass, Robert E; Shinomoto, Shigeru

2013-04-01

In many cortical areas, neural spike trains do not follow a Poisson process. In this study, we investigate a possible benefit of non-Poisson spiking for information transmission by studying the minimal rate fluctuation that can be detected by a Bayesian estimator. The idea is that an inhomogeneous Poisson process may make it difficult for downstream decoders to resolve subtle changes in rate fluctuation, but by using a more regular non-Poisson process, the nervous system can make rate fluctuations easier to detect. We evaluate the degree to which regular firing reduces the rate fluctuation detection threshold. We find that the threshold for detection is reduced in proportion to the coefficient of variation of interspike intervals.

Individual human cell responses to low doses of chemicals studied by synchrotron infrared spectromicroscopy

NASA Astrophysics Data System (ADS)

Holman, Hoi-Ying N.; Goth-Goldstein, Regine; Blakely, Elanor A.; Bjornstad, Kathy; Martin, Michael C.; McKinney, Wayne R.

2000-05-01

Vibrational spectroscopy, when combined with synchrotron radiation-based (SR) microscopy, is a powerful new analytical tool with high spatial resolution for detecting biochemical changes in the individual living cells. In contrast to other microscopy methods that require fixing, drying, staining or labeling, SR-FTIR microscopy probes intact living cells providing a composite view of all of the molecular response and the ability to monitor the response over time in the same cell. Observed spectral changes include all types of lesions induced in that cell as well as cellular responses to external and internal stresses. These spectral changes combined with other analytical tools may provide a fundamental understanding of the key molecular mechanisms induced in response to stresses created by low- doses of chemicals. In this study we used the high spatial - resolution SR-FTIR vibrational spectromicroscopy as a sensitive analytical tool to detect chemical- and radiation- induced changes in individual human cells. Our preliminary spectral measurements indicate that this technique is sensitive enough to detect changes in nucleic acids and proteins of cells treated with environmentally relevant concentrations of dioxin. This technique has the potential to distinguish changes from exogenous or endogenous oxidative processes. Future development of this technique will allow rapid monitoring of cellular processes such as drug metabolism, early detection of disease, bio- compatibility of implant materials, cellular repair mechanisms, self assembly of cellular apparatus, cell differentiation and fetal development.

A Deep Convolutional Coupling Network for Change Detection Based on Heterogeneous Optical and Radar Images.

PubMed

Liu, Jia; Gong, Maoguo; Qin, Kai; Zhang, Puzhao

2018-03-01

We propose an unsupervised deep convolutional coupling network for change detection based on two heterogeneous images acquired by optical sensors and radars on different dates. Most existing change detection methods are based on homogeneous images. Due to the complementary properties of optical and radar sensors, there is an increasing interest in change detection based on heterogeneous images. The proposed network is symmetric with each side consisting of one convolutional layer and several coupling layers. The two input images connected with the two sides of the network, respectively, are transformed into a feature space where their feature representations become more consistent. In this feature space, the different map is calculated, which then leads to the ultimate detection map by applying a thresholding algorithm. The network parameters are learned by optimizing a coupling function. The learning process is unsupervised, which is different from most existing change detection methods based on heterogeneous images. Experimental results on both homogenous and heterogeneous images demonstrate the promising performance of the proposed network compared with several existing approaches.

Urban area delineation and detection of change along the urban-rural boundary as derived from LANDSAT digital data

NASA Technical Reports Server (NTRS)

Christenson, J. W.; Lachowski, H. M.

1977-01-01

LANDSAT digital multispectral scanner data, in conjunction with supporting ground truth, were investigated to determine their utility in delineation of urban-rural boundaries. The digital data for the metropolitan areas of Washington, D. C.; Austin, Texas; and Seattle, Washingtion; were processed using an interactive image processing system. Processing focused on identification of major land cover types typical of the zone of transition from urban to rural landscape, and definition of their spectral signatures. Census tract boundaries were input into the interactive image processing system along with the LANDSAT single and overlayed multiple date MSS data. Results of this investigation indicate that satellite collected information has a practical application to the problem of urban area delineation and to change detection.

The trait of sensory processing sensitivity and neural responses to changes in visual scenes

PubMed Central

Xu, Xiaomeng; Aron, Arthur; Aron, Elaine; Cao, Guikang; Feng, Tingyong; Weng, Xuchu

2011-01-01

This exploratory study examined the extent to which individual differences in sensory processing sensitivity (SPS), a temperament/personality trait characterized by social, emotional and physical sensitivity, are associated with neural response in visual areas in response to subtle changes in visual scenes. Sixteen participants completed the Highly Sensitive Person questionnaire, a standard measure of SPS. Subsequently, they were tested on a change detection task while undergoing functional magnetic resonance imaging (fMRI). SPS was associated with significantly greater activation in brain areas involved in high-order visual processing (i.e. right claustrum, left occipitotemporal, bilateral temporal and medial and posterior parietal regions) as well as in the right cerebellum, when detecting minor (vs major) changes in stimuli. These findings remained strong and significant after controlling for neuroticism and introversion, traits that are often correlated with SPS. These results provide the first evidence of neural differences associated with SPS, the first direct support for the sensory aspect of this trait that has been studied primarily for its social and affective implications, and preliminary evidence for heightened sensory processing in individuals high in SPS. PMID:20203139

Detecting Changes of Thermal Environment over the Bohai Coastal Region by Spectral Change Vector Analysis

NASA Astrophysics Data System (ADS)

Hu, Y.; Jia, G.

2009-12-01

Change vector analysis (CVA) is an effective approach for detecting and characterizing land-cover change by comparing pairs of multi-spectral and multi-temporal datasets over certain area derived from various satellite platforms. NDVI is considered as an effective detector for biophysical changes due to its sensitivity to red and near infrared signals, while land surface temperature (LST) is considered as a valuable indicator for changes of ground thermal conditions. Here we try to apply CVA over satellite derived LST datasets to detect changes of land surface thermal properties parallel to climate change and anthropogenic influence in a city cluster since 2001. In this study, monthly land surface temperature datasets from 2001-2008 derived from MODIS collection 5 were used to examine change pattern of thermal environment over the Bohai coastal region by using spectral change vector analysis. The results from principle component analysis (PCA) for LST show that the PC 1-3 contain over 80% information on monthly variations and these PCA components represent the main processes of land thermal environment change over the study area. Time series of CVA magnitude combined with land cover information show that greatest change occurred in urban and heavily populated area, featured with expansion of urban heat island, while moderate change appeared in grassland area in the north. However few changes were observed over large plain area and forest area. Strong signals also are related to economy level and especially the events of surface cover change, such as emergence of railway and port. Two main processes were also noticed about the changes of thermal environment. First, weak signal was detected in mostly natural area influenced by interannual climate change in temperate broadleaf forest area. Second, land surface temperature changes were controlled by human activities as 1) moderate change of LST happened in grassland influenced by grazing and 2) urban heat island was intensifier in major cities, such as Beijing and Tianjin. Further, the continual drier climate combined with human actions over past fifties years have intensified land thermal pattern change and the continuation will be an important aspects to understand land surface processes and local climate change. Land surface temperature trends from 2000-2008 over the Bohai coastal region

Detecting and Attributing Health Burdens to Climate Change.

PubMed

Ebi, Kristie L; Ogden, Nicholas H; Semenza, Jan C; Woodward, Alistair

2017-08-07

Detection and attribution of health impacts caused by climate change uses formal methods to determine a ) whether the occurrence of adverse health outcomes has changed, and b ) the extent to which that change could be attributed to climate change. There have been limited efforts to undertake detection and attribution analyses in health. Our goal was to show a range of approaches for conducting detection and attribution analyses. Case studies for heatwaves, Lyme disease in Canada, and Vibrio emergence in northern Europe highlight evidence that climate change is adversely affecting human health. Changes in rates and geographic distribution of adverse health outcomes were detected, and, in each instance, a proportion of the observed changes could, in our judgment, be attributed to changes in weather patterns associated with climate change. The results of detection and attribution studies can inform evidence-based risk management to reduce current, and plan for future, changes in health risks associated with climate change. Gaining a better understanding of the size, timing, and distribution of the climate change burden of disease and injury requires reliable long-term data sets, more knowledge about the factors that confound and modify the effects of climate on health, and refinement of analytic techniques for detection and attribution. At the same time, significant advances are possible in the absence of complete data and statistical certainty: there is a place for well-informed judgments, based on understanding of underlying processes and matching of patterns of health, climate, and other determinants of human well-being. https://doi.org/10.1289/EHP1509.

Detecting changes in dynamic and complex acoustic environments

PubMed Central

Boubenec, Yves; Lawlor, Jennifer; Górska, Urszula; Shamma, Shihab; Englitz, Bernhard

2017-01-01

Natural sounds such as wind or rain, are characterized by the statistical occurrence of their constituents. Despite their complexity, listeners readily detect changes in these contexts. We here address the neural basis of statistical decision-making using a combination of psychophysics, EEG and modelling. In a texture-based, change-detection paradigm, human performance and reaction times improved with longer pre-change exposure, consistent with improved estimation of baseline statistics. Change-locked and decision-related EEG responses were found in a centro-parietal scalp location, whose slope depended on change size, consistent with sensory evidence accumulation. The potential's amplitude scaled with the duration of pre-change exposure, suggesting a time-dependent decision threshold. Auditory cortex-related potentials showed no response to the change. A dual timescale, statistical estimation model accounted for subjects' performance. Furthermore, a decision-augmented auditory cortex model accounted for performance and reaction times, suggesting that the primary cortical representation requires little post-processing to enable change-detection in complex acoustic environments. DOI: http://dx.doi.org/10.7554/eLife.24910.001 PMID:28262095

lidar change detection using building models

NASA Astrophysics Data System (ADS)

Kim, Angela M.; Runyon, Scott C.; Jalobeanu, Andre; Esterline, Chelsea H.; Kruse, Fred A.

2014-06-01

Terrestrial LiDAR scans of building models collected with a FARO Focus3D and a RIEGL VZ-400 were used to investigate point-to-point and model-to-model LiDAR change detection. LiDAR data were scaled, decimated, and georegistered to mimic real world airborne collects. Two physical building models were used to explore various aspects of the change detection process. The first model was a 1:250-scale representation of the Naval Postgraduate School campus in Monterey, CA, constructed from Lego blocks and scanned in a laboratory setting using both the FARO and RIEGL. The second model at 1:8-scale consisted of large cardboard boxes placed outdoors and scanned from rooftops of adjacent buildings using the RIEGL. A point-to-point change detection scheme was applied directly to the point-cloud datasets. In the model-to-model change detection scheme, changes were detected by comparing Digital Surface Models (DSMs). The use of physical models allowed analysis of effects of changes in scanner and scanning geometry, and performance of the change detection methods on different types of changes, including building collapse or subsistence, construction, and shifts in location. Results indicate that at low false-alarm rates, the point-to-point method slightly outperforms the model-to-model method. The point-to-point method is less sensitive to misregistration errors in the data. Best results are obtained when the baseline and change datasets are collected using the same LiDAR system and collection geometry.

Real-time traffic sign recognition based on a general purpose GPU and deep-learning

PubMed Central

Hong, Yongwon; Choi, Yeongwoo; Byun, Hyeran

2017-01-01

We present a General Purpose Graphics Processing Unit (GPGPU) based real-time traffic sign detection and recognition method that is robust against illumination changes. There have been many approaches to traffic sign recognition in various research fields; however, previous approaches faced several limitations when under low illumination or wide variance of light conditions. To overcome these drawbacks and improve processing speeds, we propose a method that 1) is robust against illumination changes, 2) uses GPGPU-based real-time traffic sign detection, and 3) performs region detecting and recognition using a hierarchical model. This method produces stable results in low illumination environments. Both detection and hierarchical recognition are performed in real-time, and the proposed method achieves 0.97 F1-score on our collective dataset, which uses the Vienna convention traffic rules (Germany and South Korea). PMID:28264011

Method for early detection of cooling-loss events

DOEpatents

Bermudez, Sergio A.; Hamann, Hendrik; Marianno, Fernando J.

2015-06-30

A method of detecting cooling-loss event early is provided. The method includes defining a relative humidity limit and change threshold for a given space, measuring relative humidity in the given space, determining, with a processing unit, whether the measured relative humidity is within the defined relative humidity limit, generating a warning in an event the measured relative humidity is outside the defined relative humidity limit and determining whether a change in the measured relative humidity is less than the defined change threshold for the given space and generating an alarm in an event the change is greater than the defined change threshold.

Method for early detection of cooling-loss events

DOEpatents

Bermudez, Sergio A.; Hamann, Hendrik F.; Marianno, Fernando J.

2015-12-22

A method of detecting cooling-loss event early is provided. The method includes defining a relative humidity limit and change threshold for a given space, measuring relative humidity in the given space, determining, with a processing unit, whether the measured relative humidity is within the defined relative humidity limit, generating a warning in an event the measured relative humidity is outside the defined relative humidity limit and determining whether a change in the measured relative humidity is less than the defined change threshold for the given space and generating an alarm in an event the change is greater than the defined change threshold.

Fault detection using a two-model test for changes in the parameters of an autoregressive time series

NASA Technical Reports Server (NTRS)

Scholtz, P.; Smyth, P.

1992-01-01

This article describes an investigation of a statistical hypothesis testing method for detecting changes in the characteristics of an observed time series. The work is motivated by the need for practical automated methods for on-line monitoring of Deep Space Network (DSN) equipment to detect failures and changes in behavior. In particular, on-line monitoring of the motor current in a DSN 34-m beam waveguide (BWG) antenna is used as an example. The algorithm is based on a measure of the information theoretic distance between two autoregressive models: one estimated with data from a dynamic reference window and one estimated with data from a sliding reference window. The Hinkley cumulative sum stopping rule is utilized to detect a change in the mean of this distance measure, corresponding to the detection of a change in the underlying process. The basic theory behind this two-model test is presented, and the problem of practical implementation is addressed, examining windowing methods, model estimation, and detection parameter assignment. Results from the five fault-transition simulations are presented to show the possible limitations of the detection method, and suggestions for future implementation are given.

Experimental application of simulation tools for evaluating UAV video change detection

NASA Astrophysics Data System (ADS)

Saur, Günter; Bartelsen, Jan

2015-10-01

Change detection is one of the most important tasks when unmanned aerial vehicles (UAV) are used for video reconnaissance and surveillance. In this paper, we address changes on short time scale, i.e. the observations are taken within time distances of a few hours. Each observation is a short video sequence corresponding to the near-nadir overflight of the UAV above the interesting area and the relevant changes are e.g. recently added or removed objects. The change detection algorithm has to distinguish between relevant and non-relevant changes. Examples for non-relevant changes are versatile objects like trees and compression or transmission artifacts. To enable the usage of an automatic change detection within an interactive workflow of an UAV video exploitation system, an evaluation and assessment procedure has to be performed. Large video data sets which contain many relevant objects with varying scene background and altering influence parameters (e.g. image quality, sensor and flight parameters) including image metadata and ground truth data are necessary for a comprehensive evaluation. Since the acquisition of real video data is limited by cost and time constraints, from our point of view, the generation of synthetic data by simulation tools has to be considered. In this paper the processing chain of Saur et al. (2014) [1] and the interactive workflow for video change detection is described. We have selected the commercial simulation environment Virtual Battle Space 3 (VBS3) to generate synthetic data. For an experimental setup, an example scenario "road monitoring" has been defined and several video clips have been produced with varying flight and sensor parameters and varying objects in the scene. Image registration and change mask extraction, both components of the processing chain, are applied to corresponding frames of different video clips. For the selected examples, the images could be registered, the modelled changes could be extracted and the artifacts of the image rendering considered as noise (slight differences of heading angles, disparity of vegetation, 3D parallax) could be suppressed. We conclude that these image data could be considered to be realistic enough to serve as evaluation data for the selected processing components. Future work will extend the evaluation to other influence parameters and may include the human operator for mission planning and sensor control.

Temporal Forest Change Detection and Forest Health Assessment using Remote Sensing

NASA Astrophysics Data System (ADS)

Ya'acob, Norsuzila; Mohd Azize, Aziean Binti; Anis Mahmon, Nur; Laily Yusof, Azita; Farhana Azmi, Nor; Mustafa, Norfazira

2014-03-01

This paper presents the detection of Angsi and Berembun Reserve Forest change for years 1996 and 2013. Forest is an important part of our ecosystem. The main function is to absorb carbon oxide and produce oxygen in their cycle of photosynthesis to maintain a balance and healthy atmosphere. However, forest changes as time changes. Some changes are necessary as to give way for economic growth. Nevertheless, it is important to monitor forest change so that deforestation and development can be planned and the balance of ecosystem is still preserved. It is important because there are number of unfavorable effects of deforestation that include environmental and economic such as erosion of soil, loss of biodiversity and climate change. The forest change detection can be studied with reference of several satellite images using remote sensing application. Forest change detection is best done with remote sensing due to large and remote study area. The objective of this project is to detect forest change over time and to compare forest health indicated by Normalized Difference Vegetation Index (NDVI) using remote sensing and image processing. The forest under study shows depletion of forest area by 12% and 100% increment of deforestation activities. The NDVI value which is associated with the forest health also shows 13% of reduction.

Effects of wildfire on catchment runoff response: a modeling approach to detect changes in snow-dominated forested catchments

Treesearch

Jan Seibert; Jeffrey J. McDonnell; Richard D. Woodsmith

2010-01-01

Wildfire is an important disturbance affecting hydrological processes through alteration of vegetation cover and soil characteristics. The effects of fire on hydrological systems at the catchment scale are not well known, largely because site specific data from both before and after wildfire are rare. In this study a modelling approach was employed for change detection...

Change detection and change monitoring of natural and man-made features in multispectral and hyperspectral satellite imagery

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

Moody, Daniela Irina

An approach for land cover classification, seasonal and yearly change detection and monitoring, and identification of changes in man-made features may use a clustering of sparse approximations (CoSA) on sparse representations in learned dictionaries. A Hebbian learning rule may be used to build multispectral or hyperspectral, multiresolution dictionaries that are adapted to regional satellite image data. Sparse image representations of pixel patches over the learned dictionaries may be used to perform unsupervised k-means clustering into land cover categories. The clustering process behaves as a classifier in detecting real variability. This approach may combine spectral and spatial textural characteristics to detectmore » geologic, vegetative, hydrologic, and man-made features, as well as changes in these features over time.« less

The Objective Identification and Quantification of Interstitial Lung Abnormalities in Smokers.

PubMed

Ash, Samuel Y; Harmouche, Rola; Ross, James C; Diaz, Alejandro A; Hunninghake, Gary M; Putman, Rachel K; Onieva, Jorge; Martinez, Fernando J; Choi, Augustine M; Lynch, David A; Hatabu, Hiroto; Rosas, Ivan O; Estepar, Raul San Jose; Washko, George R

2017-08-01

Previous investigation suggests that visually detected interstitial changes in the lung parenchyma of smokers are highly clinically relevant and predict outcomes, including death. Visual subjective analysis to detect these changes is time-consuming, insensitive to subtle changes, and requires training to enhance reproducibility. Objective detection of such changes could provide a method of disease identification without these limitations. The goal of this study was to develop and test a fully automated image processing tool to objectively identify radiographic features associated with interstitial abnormalities in the computed tomography scans of a large cohort of smokers. An automated tool that uses local histogram analysis combined with distance from the pleural surface was used to detect radiographic features consistent with interstitial lung abnormalities in computed tomography scans from 2257 individuals from the Genetic Epidemiology of COPD study, a longitudinal observational study of smokers. The sensitivity and specificity of this tool was determined based on its ability to detect the visually identified presence of these abnormalities. The tool had a sensitivity of 87.8% and a specificity of 57.5% for the detection of interstitial lung abnormalities, with a c-statistic of 0.82, and was 100% sensitive and 56.7% specific for the detection of the visual subtype of interstitial abnormalities called fibrotic parenchymal abnormalities, with a c-statistic of 0.89. In smokers, a fully automated image processing tool is able to identify those individuals who have interstitial lung abnormalities with moderate sensitivity and specificity. Copyright © 2017 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Analysis and Implementation of Methodologies for the Monitoring of Changes in Eye Fundus Images

NASA Astrophysics Data System (ADS)

Gelroth, A.; Rodríguez, D.; Salvatelli, A.; Drozdowicz, B.; Bizai, G.

2011-12-01

We present a support system for changes detection in fundus images of the same patient taken at different time intervals. This process is useful for monitoring pathologies lasting for long periods of time, as are usually the ophthalmologic. We propose a flow of preprocessing, processing and postprocessing applied to a set of images selected from a public database, presenting pathological advances. A test interface was developed designed to select the images to be compared in order to apply the different methods developed and to display the results. We measure the system performance in terms of sensitivity, specificity and computation times. We have obtained good results, higher than 84% for the first two parameters and processing times lower than 3 seconds for 512x512 pixel images. For the specific case of detection of changes associated with bleeding, the system responds with sensitivity and specificity over 98%.

A change detection method for remote sensing image based on LBP and SURF feature

NASA Astrophysics Data System (ADS)

Hu, Lei; Yang, Hao; Li, Jin; Zhang, Yun

2018-04-01

Finding the change in multi-temporal remote sensing image is important in many the image application. Because of the infection of climate and illumination, the texture of the ground object is more stable relative to the gray in high-resolution remote sensing image. And the texture features of Local Binary Patterns (LBP) and Speeded Up Robust Features (SURF) are outstanding in extracting speed and illumination invariance. A method of change detection for matched remote sensing image pair is present, which compares the similarity by LBP and SURF to detect the change and unchanged of the block after blocking the image. And region growing is adopted to process the block edge zone. The experiment results show that the method can endure some illumination change and slight texture change of the ground object.

An adaptive confidence limit for periodic non-steady conditions fault detection

NASA Astrophysics Data System (ADS)

Wang, Tianzhen; Wu, Hao; Ni, Mengqi; Zhang, Milu; Dong, Jingjing; Benbouzid, Mohamed El Hachemi; Hu, Xiong

2016-05-01

System monitoring has become a major concern in batch process due to the fact that failure rate in non-steady conditions is much higher than in steady ones. A series of approaches based on PCA have already solved problems such as data dimensionality reduction, multivariable decorrelation, and processing non-changing signal. However, if the data follows non-Gaussian distribution or the variables contain some signal changes, the above approaches are not applicable. To deal with these concerns and to enhance performance in multiperiod data processing, this paper proposes a fault detection method using adaptive confidence limit (ACL) in periodic non-steady conditions. The proposed ACL method achieves four main enhancements: Longitudinal-Standardization could convert non-Gaussian sampling data to Gaussian ones; the multiperiod PCA algorithm could reduce dimensionality, remove correlation, and improve the monitoring accuracy; the adaptive confidence limit could detect faults under non-steady conditions; the fault sections determination procedure could select the appropriate parameter of the adaptive confidence limit. The achieved result analysis clearly shows that the proposed ACL method is superior to other fault detection approaches under periodic non-steady conditions.

An UV-vis spectroelectrochemical approach for rapid detection of phenazines and exploration of their redox characteristics.

PubMed

Chen, Wei; Liu, Xiao-Yang; Qian, Chen; Song, Xiang-Ning; Li, Wen-Wei; Yu, Han-Qing

2015-02-15

Phenazines are widely distributed in the environment and play an important role in various biological processes to facilitate microbial metabolism and electron transfer. In this work, an efficient and reliable spectroelectrochemical method is developed to quantitatively detect 1-hydroxyphenazine (1-OHPZ), a representative phenazine, and explore its redox characteristics. This approach is based on the sensitive absorption change of 1-OHPZ in response to its changes under redox state in rapid electrochemical reduction. The redox reaction of 1-OHPZ in aqueous solution is a proton-coupled electron transfer process, with a reversible one-step 2e(-)/2H(+) transfer reaction. This spectroelectrochemical approach exhibits good linear response covering two magnitudes to 1-OHPZ with a detection limit of 0.48µM, and is successfully applied to detect 1-OHPZ from a mixture of phenazines produced by Pseudomonas aeruginosa cultures. This method might also be applicable in exploring the abundance and redox processes of a wide range of other redox-active molecules in natural and engineered environments. Copyright © 2014 Elsevier B.V. All rights reserved.

Building Development Monitoring in Multitemporal Remotely Sensed Image Pairs with Stochastic Birth-Death Dynamics.

PubMed

Benedek, C; Descombes, X; Zerubia, J

2012-01-01

In this paper, we introduce a new probabilistic method which integrates building extraction with change detection in remotely sensed image pairs. A global optimization process attempts to find the optimal configuration of buildings, considering the observed data, prior knowledge, and interactions between the neighboring building parts. We present methodological contributions in three key issues: 1) We implement a novel object-change modeling approach based on Multitemporal Marked Point Processes, which simultaneously exploits low-level change information between the time layers and object-level building description to recognize and separate changed and unaltered buildings. 2) To answer the challenges of data heterogeneity in aerial and satellite image repositories, we construct a flexible hierarchical framework which can create various building appearance models from different elementary feature-based modules. 3) To simultaneously ensure the convergence, optimality, and computation complexity constraints raised by the increased data quantity, we adopt the quick Multiple Birth and Death optimization technique for change detection purposes, and propose a novel nonuniform stochastic object birth process which generates relevant objects with higher probability based on low-level image features.

Testing for the Presence of Correlation Changes in a Multivariate Time Series: A Permutation Based Approach.

PubMed

Cabrieto, Jedelyn; Tuerlinckx, Francis; Kuppens, Peter; Hunyadi, Borbála; Ceulemans, Eva

2018-01-15

Detecting abrupt correlation changes in multivariate time series is crucial in many application fields such as signal processing, functional neuroimaging, climate studies, and financial analysis. To detect such changes, several promising correlation change tests exist, but they may suffer from severe loss of power when there is actually more than one change point underlying the data. To deal with this drawback, we propose a permutation based significance test for Kernel Change Point (KCP) detection on the running correlations. Given a requested number of change points K, KCP divides the time series into K + 1 phases by minimizing the within-phase variance. The new permutation test looks at how the average within-phase variance decreases when K increases and compares this to the results for permuted data. The results of an extensive simulation study and applications to several real data sets show that, depending on the setting, the new test performs either at par or better than the state-of-the art significance tests for detecting the presence of correlation changes, implying that its use can be generally recommended.

The Comparison of Visual Working Memory Representations with Perceptual Inputs

PubMed Central

Hyun, Joo-seok; Woodman, Geoffrey F.; Vogel, Edward K.; Hollingworth, Andrew

2008-01-01

The human visual system can notice differences between memories of previous visual inputs and perceptions of new visual inputs, but the comparison process that detects these differences has not been well characterized. This study tests the hypothesis that differences between the memory of a stimulus array and the perception of a new array are detected in a manner that is analogous to the detection of simple features in visual search tasks. That is, just as the presence of a task-relevant feature in visual search can be detected in parallel, triggering a rapid shift of attention to the object containing the feature, the presence of a memory-percept difference along a task-relevant dimension can be detected in parallel, triggering a rapid shift of attention to the changed object. Supporting evidence was obtained in a series of experiments that examined manual reaction times, saccadic reaction times, and event-related potential latencies. However, these experiments also demonstrated that a slow, limited-capacity process must occur before the observer can make a manual change-detection response. PMID:19653755

Low temperature detection of phase transitions and relaxation processes in strontium titanate by means of cathodoluminescence

NASA Astrophysics Data System (ADS)

Yang, B.; Townsend, P. D.; Fromknecht, R.

2004-11-01

Cathodoluminescence is an effective tool for investigating phase changes and relaxation processes in insulators and data are presented for strontium titanate. The results demonstrate considerable sensitivity to the origin of the samples as the detailed spectra and intensity changes with temperature are strongly dependent on the growth conditions, trace impurities and radiation induced defects. It is of particular note that in the defective surface layer the normal second-order phase transition cited near 105 K transforms into a sharply defined first-order transition because of the relaxation of the near surface layer in doped crystals. Detection of the other main relaxation stages is also straightforward via intensity and spectral changes. Secondary effects of phase changes incorporated within the surface layers are clearly evident, particularly for the 197 K sublimation of CO2 nanoparticle inclusions.

Research on photodiode detector-based spatial transient light detection and processing system

NASA Astrophysics Data System (ADS)

Liu, Meiying; Wang, Hu; Liu, Yang; Zhao, Hui; Nan, Meng

2016-10-01

In order to realize real-time signal identification and processing of spatial transient light, the features and the energy of the captured target light signal are first described and quantitatively calculated. Considering that the transient light signal has random occurrence, a short duration and an evident beginning and ending, a photodiode detector based spatial transient light detection and processing system is proposed and designed in this paper. This system has a large field of view and is used to realize non-imaging energy detection of random, transient and weak point target under complex background of spatial environment. Weak signal extraction under strong background is difficult. In this paper, considering that the background signal changes slowly and the target signal changes quickly, filter is adopted for signal's background subtraction. A variable speed sampling is realized by the way of sampling data points with a gradually increased interval. The two dilemmas that real-time processing of large amount of data and power consumption required by the large amount of data needed to be stored are solved. The test results with self-made simulative signal demonstrate the effectiveness of the design scheme. The practical system could be operated reliably. The detection and processing of the target signal under the strong sunlight background was realized. The results indicate that the system can realize real-time detection of target signal's characteristic waveform and monitor the system working parameters. The prototype design could be used in a variety of engineering applications.

Enhanced change detection performance reveals improved strategy use in avid action video game players.

PubMed

Clark, Kait; Fleck, Mathias S; Mitroff, Stephen R

2011-01-01

Recent research has shown that avid action video game players (VGPs) outperform non-video game players (NVGPs) on a variety of attentional and perceptual tasks. However, it remains unknown exactly why and how such differences arise; while some prior research has demonstrated that VGPs' improvements stem from enhanced basic perceptual processes, other work indicates that they can stem from enhanced attentional control. The current experiment used a change-detection task to explore whether top-down strategies can contribute to VGPs' improved abilities. Participants viewed alternating presentations of an image and a modified version of the image and were tasked with detecting and localizing the changed element. Consistent with prior claims of enhanced perceptual abilities, VGPs were able to detect the changes while requiring less exposure to the change than NVGPs. Further analyses revealed this improved change detection performance may result from altered strategy use; VGPs employed broader search patterns when scanning scenes for potential changes. These results complement prior demonstrations of VGPs' enhanced bottom-up perceptual benefits by providing new evidence of VGPs' potentially enhanced top-down strategic benefits. Copyright © 2010 Elsevier B.V. All rights reserved.

Automatic Tool Selection in V-bending Processes by Using an Intelligent Collision Detection Algorithm

NASA Astrophysics Data System (ADS)

Salem, A. A.

2017-09-01

V-bending is widely used to produce the sheet metal components. There are global Changes in the shape of the sheet metal component during progressive bending processes. Accordingly, collisions may be occurred between part and tool during bending. Collision-free is considered one of the feasibility conditions of V-bending process planning which the tool selection is verified by the absence of the collisions. This paper proposes an intelligent collision detection algorithm which has the ability to distinguish between 2D bent parts and the other bent parts. Due to this ability, 2D and 3D collision detection subroutines have been developed in the proposed algorithm. This division of algorithm’s subroutines could reduce the computational operations during collisions detecting.

Comprehensive NMR analysis of compositional changes of black garlic during thermal processing.

PubMed

Liang, Tingfu; Wei, Feifei; Lu, Yi; Kodani, Yoshinori; Nakada, Mitsuhiko; Miyakawa, Takuya; Tanokura, Masaru

2015-01-21

Black garlic is a processed food product obtained by subjecting whole raw garlic to thermal processing that causes chemical reactions, such as the Maillard reaction, which change the composition of the garlic. In this paper, we report a nuclear magnetic resonance (NMR)-based comprehensive analysis of raw garlic and black garlic extracts to determine the compositional changes resulting from thermal processing. (1)H NMR spectra with a detailed signal assignment showed that 38 components were altered by thermal processing of raw garlic. For example, the contents of 11 l-amino acids increased during the first step of thermal processing over 5 days and then decreased. Multivariate data analysis revealed changes in the contents of fructose, glucose, acetic acid, formic acid, pyroglutamic acid, cycloalliin, and 5-(hydroxymethyl)furfural (5-HMF). Our results provide comprehensive information on changes in NMR-detectable components during thermal processing of whole garlic.

Motivation enhances visual working memory capacity through the modulation of central cognitive processes.

PubMed

Sanada, Motoyuki; Ikeda, Koki; Kimura, Kenta; Hasegawa, Toshikazu

2013-09-01

Motivation is well known to enhance working memory (WM) capacity, but the mechanism underlying this effect remains unclear. The WM process can be divided into encoding, maintenance, and retrieval, and in a change detection visual WM paradigm, the encoding and retrieval processes can be subdivided into perceptual and central processing. To clarify which of these segments are most influenced by motivation, we measured ERPs in a change detection task with differential monetary rewards. The results showed that the enhancement of WM capacity under high motivation was accompanied by modulations of late central components but not those reflecting attentional control on perceptual inputs across all stages of WM. We conclude that the "state-dependent" shift of motivation impacted the central, rather than the perceptual functions in order to achieve better behavioral performances. Copyright © 2013 Society for Psychophysiological Research.

Comparing single- and dual-process models of memory development.

PubMed

Hayes, Brett K; Dunn, John C; Joubert, Amy; Taylor, Robert

2017-11-01

This experiment examined single-process and dual-process accounts of the development of visual recognition memory. The participants, 6-7-year-olds, 9-10-year-olds and adults, were presented with a list of pictures which they encoded under shallow or deep conditions. They then made recognition and confidence judgments about a list containing old and new items. We replicated the main trends reported by Ghetti and Angelini () in that recognition hit rates increased from 6 to 9 years of age, with larger age changes following deep than shallow encoding. Formal versions of the dual-process high threshold signal detection model and several single-process models (equal variance signal detection, unequal variance signal detection, mixture signal detection) were fit to the developmental data. The unequal variance and mixture signal detection models gave a better account of the data than either of the other models. A state-trace analysis found evidence for only one underlying memory process across the age range tested. These results suggest that single-process memory models based on memory strength are a viable alternative to dual-process models for explaining memory development. © 2016 John Wiley & Sons Ltd.

Decentralized Control of Scheduling in Distributed Systems.

DTIC Science & Technology

1983-03-18

the job scheduling algorithm adapts to the changing busyness of the various hosts in the system. The environment in which the job scheduling entities...resources and processes that constitute the node and a set of interfaces for accessing these processes and resources. The structure of a node could change ...parallel. Chang [CHNG82] has also described some algorithms for detecting properties of general graphs by traversing paths in a graph in parallel. One of

Problem Based Learning: Cognitive and Metacognitive Processes during Problem Analysis.

ERIC Educational Resources Information Center

De Grave, W. S.; And Others

1996-01-01

To investigate whether problem-based learning leads to conceptual change, the cognitive and metacognitive processes of a group of medical students were studied during the problem analysis phase, and their verbal communication and thinking processes were analyzed. Stimulated recall of the thinking process during the discussion detected a conceptual…

Differences in change blindness to real-life scenes in adults with autism spectrum conditions.

PubMed

Ashwin, Chris; Wheelwright, Sally; Baron-Cohen, Simon

2017-01-01

People often fail to detect large changes to visual scenes following a brief interruption, an effect known as 'change blindness'. People with autism spectrum conditions (ASC) have superior attention to detail and better discrimination of targets, and often notice small details that are missed by others. Together these predict people with autism should show enhanced perception of changes in simple change detection paradigms, including reduced change blindness. However, change blindness studies to date have reported mixed results in ASC, which have sometimes included no differences to controls or even enhanced change blindness. Attenuated change blindness has only been reported to date in ASC in children and adolescents, with no study reporting reduced change blindness in adults with ASC. The present study used a change blindness flicker task to investigate the detection of changes in images of everyday life in adults with ASC (n = 22) and controls (n = 22) using a simple change detection task design and full range of original scenes as stimuli. Results showed the adults with ASC had reduced change blindness compared to adult controls for changes to items of marginal interest in scenes, with no group difference for changes to items of central interest. There were no group differences in overall response latencies to correctly detect changes nor in the overall number of missed detections in the experiment. However, the ASC group showed greater missed changes for marginal interest changes of location, showing some evidence of greater change blindness as well. These findings show both reduced change blindness to marginal interest changes in ASC, based on response latencies, as well as greater change blindness to changes of location of marginal interest items, based on detection rates. The findings of reduced change blindness are consistent with clinical reports that people with ASC often notice small changes to less salient items within their environment, and are in-line with theories of enhanced local processing and greater attention to detail in ASC. The findings of lower detection rates for one of the marginal interest conditions may be related to problems in shifting attention or an overly focused attention spotlight.

On improving IED object detection by exploiting scene geometry using stereo processing

NASA Astrophysics Data System (ADS)

van de Wouw, Dennis W. J. M.; Dubbelman, Gijs; de With, Peter H. N.

2015-03-01

Detecting changes in the environment with respect to an earlier data acquisition is important for several applications, such as finding Improvised Explosive Devices (IEDs). We explore and evaluate the benefit of depth sensing in the context of automatic change detection, where an existing monocular system is extended with a second camera in a fixed stereo setup. We then propose an alternative frame registration that exploits scene geometry, in particular the ground plane. Furthermore, change characterization is applied to localized depth maps to distinguish between 3D physical changes and shadows, which solves one of the main challenges of a monocular system. The proposed system is evaluated on real-world acquisitions, containing geo-tagged test objects of 18 18 9 cm up to a distance of 60 meters. The proposed extensions lead to a significant reduction of the false-alarm rate by a factor of 3, while simultaneously improving the detection score with 5%.

Change detection of medical images using dictionary learning techniques and PCA

NASA Astrophysics Data System (ADS)

Nika, Varvara; Babyn, Paul; Zhu, Hongmei

2014-03-01

Automatic change detection methods for identifying the changes of serial MR images taken at different times are of great interest to radiologists. The majority of existing change detection methods in medical imaging, and those of brain images in particular, include many preprocessing steps and rely mostly on statistical analysis of MRI scans. Although most methods utilize registration software, tissue classification remains a difficult and overwhelming task. Recently, dictionary learning techniques are used in many areas of image processing, such as image surveillance, face recognition, remote sensing, and medical imaging. In this paper we present the Eigen-Block Change Detection algorithm (EigenBlockCD). It performs local registration and identifies the changes between consecutive MR images of the brain. Blocks of pixels from baseline scan are used to train local dictionaries that are then used to detect changes in the follow-up scan. We use PCA to reduce the dimensionality of the local dictionaries and the redundancy of data. Choosing the appropriate distance measure significantly affects the performance of our algorithm. We examine the differences between L1 and L2 norms as two possible similarity measures in the EigenBlockCD. We show the advantages of L2 norm over L1 norm theoretically and numerically. We also demonstrate the performance of the EigenBlockCD algorithm for detecting changes of MR images and compare our results with those provided in recent literature. Experimental results with both simulated and real MRI scans show that the EigenBlockCD outperforms the previous methods. It detects clinical changes while ignoring the changes due to patient's position and other acquisition artifacts.

An Evaluation of Psychophysical Models of Auditory Change Perception

PubMed Central

Micheyl, Christophe; Kaernbach, Christian; Demany, Laurent

2009-01-01

In many psychophysical experiments, the participant's task is to detect small changes along a given stimulus dimension, or to identify the direction (e.g., upward vs. downward) of such changes. The results of these experiments are traditionally analyzed using a constant-variance Gaussian (CVG) model or a high-threshold (HT) model. Here, the authors demonstrate that for changes along three basic sound dimensions (frequency, intensity, and amplitude-modulation rate), such models cannot account for the observed relationship between detection thresholds and direction-identification thresholds. It is shown that two alternative models can account for this relationship. One of them is based on the idea of sensory “quanta”; the other assumes that small changes are detected on the basis of Poisson processes with low means. The predictions of these two models are then compared against receiver operating characteristics (ROCs) for the detection of changes in sound intensity. It is concluded that human listeners' perception of small and unidimensional acoustic changes is better described by a discrete-state Poisson model than by the more commonly used CVG model or by the less favored HT and quantum models. PMID:18954215

Slow changing postural cues cancel visual field dependence on self-tilt detection.

PubMed

Scotto Di Cesare, C; Macaluso, T; Mestre, D R; Bringoux, L

2015-01-01

Interindividual differences influence the multisensory integration process involved in spatial perception. Here, we assessed the effect of visual field dependence on self-tilt detection relative to upright, as a function of static vs. slow changing visual or postural cues. To that aim, we manipulated slow rotations (i.e., 0.05° s(-1)) of the body and/or the visual scene in pitch. Participants had to indicate whether they felt being tilted forward at successive angles. Results show that thresholds for self-tilt detection substantially differed between visual field dependent/independent subjects, when only the visual scene was rotated. This difference was no longer present when the body was actually rotated, whatever the visual scene condition (i.e., absent, static or rotated relative to the observer). These results suggest that the cancellation of visual field dependence by dynamic postural cues may rely on a multisensory reweighting process, where slow changing vestibular/somatosensory inputs may prevail over visual inputs. Copyright © 2014 Elsevier B.V. All rights reserved.

Business Process Aware IS Change Management in SMEs

NASA Astrophysics Data System (ADS)

Makna, Janis

Changes in the business process usually require changes in the computer supported information system and, vice versa, changes in the information system almost always cause at least some changes in the business process. In many situations it is not even possible to detect which of those changes are causes and which of them are effects. Nevertheless, it is possible to identify a set of changes that usually happen when one of the elements of the set changes its state. These sets of changes may be used as patterns for situation analysis to anticipate full range of activities to be performed to get the business process and/or information system back to the stable state after it is lost because of the changes in one of the elements. Knowledge about the change pattern gives an opportunity to manage changes of information systems even if business process models and information systems architecture are not neatly documented as is the case in many SMEs. Using change patterns it is possible to know whether changes in information systems are to be expected and how changes in information systems activities, data and users will impact different aspects of the business process supported by the information system.

Posterior Cingulate Cortex: Adapting Behavior to a Changing World

PubMed Central

Pearson, John M.; Heilbronner, Sarah R.; Barack, David L.; Hayden, Benjamin Y.; Platt, Michael L.

2011-01-01

When has the world changed enough to warrant a new approach? The answer depends upon current needs, behavioral flexibility, and prior knowledge about the environment. Formal approaches solve the problem by integrating the recent history of rewards, errors, uncertainty, and context via Bayesian inference to detect changes in the world and alter behavioral policy. Neuronal activity in posterior cingulate cortex (CGp)—a key node in the default network—is known to vary with learning, memory, reward, and task engagement. We propose that these modulations reflect the underlying process of change detection and motivate subsequent shifts in behavior. PMID:21420893

Indirect measures as a signal for evaluative change.

PubMed

Perugini, Marco; Richetin, Juliette; Zogmaister, Cristina

2014-01-01

Implicit and explicit attitudes can be changed by using evaluative learning procedures. In this contribution we investigated an asymmetric effect of order of administration of indirect and direct measures on the detection of evaluative change: A change in explicit attitudes is more likely detected if they are measured after implicit attitudes, whereas these latter change regardless of the order. This effect was demonstrated in two studies (n=270; n=138) using the self-referencing task whereas it was not found in a third study (n=151) that used a supraliminal sequential evaluative conditioning paradigm. In all studies evaluative change was present only for contingency aware participants. We discuss a potential explanation underlying the order of measure effect entailing that, in some circumstances, an indirect measure is not only a measure but also a signal that can be detected through self-perception processes and further elaborated at the propositional level.

Active listening: task-dependent plasticity of spectrotemporal receptive fields in primary auditory cortex.

PubMed

Fritz, Jonathan; Elhilali, Mounya; Shamma, Shihab

2005-08-01

Listening is an active process in which attentive focus on salient acoustic features in auditory tasks can influence receptive field properties of cortical neurons. Recent studies showing rapid task-related changes in neuronal spectrotemporal receptive fields (STRFs) in primary auditory cortex of the behaving ferret are reviewed in the context of current research on cortical plasticity. Ferrets were trained on spectral tasks, including tone detection and two-tone discrimination, and on temporal tasks, including gap detection and click-rate discrimination. STRF changes could be measured on-line during task performance and occurred within minutes of task onset. During spectral tasks, there were specific spectral changes (enhanced response to tonal target frequency in tone detection and discrimination, suppressed response to tonal reference frequency in tone discrimination). However, only in the temporal tasks, the STRF was changed along the temporal dimension by sharpening temporal dynamics. In ferrets trained on multiple tasks, distinctive and task-specific STRF changes could be observed in the same cortical neurons in successive behavioral sessions. These results suggest that rapid task-related plasticity is an ongoing process that occurs at a network and single unit level as the animal switches between different tasks and dynamically adapts cortical STRFs in response to changing acoustic demands.

Enhanced change detection index for disaster response, recovery assessment and monitoring of buildings and critical facilities-A case study for Muzzaffarabad, Pakistan

NASA Astrophysics Data System (ADS)

de Alwis Pitts, Dilkushi A.; So, Emily

2017-12-01

The availability of Very High Resolution (VHR) optical sensors and a growing image archive that is frequently updated, allows the use of change detection in post-disaster recovery and monitoring for robust and rapid results. The proposed semi-automated GIS object-based method uses readily available pre-disaster GIS data and adds existing knowledge into the processing to enhance change detection. It also allows targeting specific types of changes pertaining to similar man-made objects such as buildings and critical facilities. The change detection method is based on pre/post normalized index, gradient of intensity, texture and edge similarity filters within the object and a set of training data. More emphasis is put on the building edges to capture the structural damage in quantifying change after disaster. Once the change is quantified, based on training data, the method can be used automatically to detect change in order to observe recovery over time in potentially large areas. Analysis over time can also contribute to obtaining a full picture of the recovery and development after disaster, thereby giving managers a better understanding of productive management and recovery practices. The recovery and monitoring can be analyzed using the index in zones extending from to epicentre of disaster or administrative boundaries over time.

Unraveling the nature of autism: finding order amid change

PubMed Central

Hellendoorn, Annika; Wijnroks, Lex; Leseman, Paul P. M.

2015-01-01

In this article, we hypothesize that individuals with autism spectrum disorder (ASD) are born with a deficit in invariance detection, which is a learning process whereby people and animals come to attend the relatively stable patterns or structural regularities in the changing stimulus array. This paper synthesizes a substantial body of research which suggests that a deficit in the domain-general perceptual learning process of invariant detection in ASD can lead to a cascade of consequences in different developmental domains. We will outline how this deficit in invariant detection can cause uncertainty, unpredictability, and a lack of control for individuals with ASD and how varying degrees of impairments in this learning process can account for the heterogeneity of the ASD phenotype. We also describe how differences in neural plasticity in ASD underlie the impairments in perceptual learning. The present account offers an alternative to prior theories and contributes to the challenge of understanding the developmental trajectories that result in the variety of autistic behaviors. PMID:25870581

Detecting P and S-wave of Mt. Rinjani seismic based on a locally stationary autoregressive (LSAR) model

NASA Astrophysics Data System (ADS)

Nurhaida, Subanar, Abdurakhman, Abadi, Agus Maman

2017-08-01

Seismic data is usually modelled using autoregressive processes. The aim of this paper is to find the arrival times of the seismic waves of Mt. Rinjani in Indonesia. Kitagawa algorithm's is used to detect the seismic P and S-wave. Householder transformation used in the algorithm made it effectively finding the number of change points and parameters of the autoregressive models. The results show that the use of Box-Cox transformation on the variable selection level makes the algorithm works well in detecting the change points. Furthermore, when the basic span of the subinterval is set 200 seconds and the maximum AR order is 20, there are 8 change points which occur at 1601, 2001, 7401, 7601,7801, 8001, 8201 and 9601. Finally, The P and S-wave arrival times are detected at time 1671 and 2045 respectively using a precise detection algorithm.

Integrating Remote and Social Sensing Data for a Scenario on Secure Societies in Big Data Platform

NASA Astrophysics Data System (ADS)

Albani, Sergio; Lazzarini, Michele; Koubarakis, Manolis; Taniskidou, Efi Karra; Papadakis, George; Karkaletsis, Vangelis; Giannakopoulos, George

2016-08-01

In the framework of the Horizon 2020 project BigDataEurope (Integrating Big Data, Software & Communities for Addressing Europe's Societal Challenges), a pilot for the Secure Societies Societal Challenge was designed considering the requirements coming from relevant stakeholders. The pilot is focusing on the integration in a Big Data platform of data coming from remote and social sensing.The information on land changes coming from the Copernicus Sentinel 1A sensor (Change Detection workflow) is integrated with information coming from selected Twitter and news agencies accounts (Event Detection workflow) in order to provide the user with multiple sources of information.The Change Detection workflow implements a processing chain in a distributed parallel manner, exploiting the Big Data capabilities in place; the Event Detection workflow implements parallel and distributed social media and news agencies monitoring as well as suitable mechanisms to detect and geo-annotate the related events.

Change detection and classification of land cover in multispectral satellite imagery using clustering of sparse approximations (CoSA) over learned feature dictionaries

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

Moody, Daniela I.; Brumby, Steven P.; Rowland, Joel C.

Neuromimetic machine vision and pattern recognition algorithms are of great interest for landscape characterization and change detection in satellite imagery in support of global climate change science and modeling. We present results from an ongoing effort to extend machine vision methods to the environmental sciences, using adaptive sparse signal processing combined with machine learning. A Hebbian learning rule is used to build multispectral, multiresolution dictionaries from regional satellite normalized band difference index data. Land cover labels are automatically generated via our CoSA algorithm: Clustering of Sparse Approximations, using a clustering distance metric that combines spectral and spatial textural characteristics tomore » help separate geologic, vegetative, and hydrologie features. We demonstrate our method on example Worldview-2 satellite images of an Arctic region, and use CoSA labels to detect seasonal surface changes. In conclusion, our results suggest that neuroscience-based models are a promising approach to practical pattern recognition and change detection problems in remote sensing.« less

Change detection and classification of land cover in multispectral satellite imagery using clustering of sparse approximations (CoSA) over learned feature dictionaries

DOE PAGES

Moody, Daniela I.; Brumby, Steven P.; Rowland, Joel C.; ...

2014-10-01

Neuromimetic machine vision and pattern recognition algorithms are of great interest for landscape characterization and change detection in satellite imagery in support of global climate change science and modeling. We present results from an ongoing effort to extend machine vision methods to the environmental sciences, using adaptive sparse signal processing combined with machine learning. A Hebbian learning rule is used to build multispectral, multiresolution dictionaries from regional satellite normalized band difference index data. Land cover labels are automatically generated via our CoSA algorithm: Clustering of Sparse Approximations, using a clustering distance metric that combines spectral and spatial textural characteristics tomore » help separate geologic, vegetative, and hydrologie features. We demonstrate our method on example Worldview-2 satellite images of an Arctic region, and use CoSA labels to detect seasonal surface changes. In conclusion, our results suggest that neuroscience-based models are a promising approach to practical pattern recognition and change detection problems in remote sensing.« less

Planetary-scale surface water detection from space

NASA Astrophysics Data System (ADS)

Donchyts, G.; Baart, F.; Winsemius, H.; Gorelick, N.

2017-12-01

Accurate, efficient and high-resolution methods of surface water detection are needed for a better water management. Datasets on surface water extent and dynamics are crucial for a better understanding of natural and human-made processes, and as an input data for hydrological and hydraulic models. In spite of considerable progress in the harmonization of freely available satellite data, producing accurate and efficient higher-level surface water data products remains very challenging. This presentation will provide an overview of existing methods for surface water extent and change detection from multitemporal and multi-sensor satellite imagery. An algorithm to detect surface water changes from multi-temporal satellite imagery will be demonstrated as well as its open-source implementation (http://aqua-monitor.deltares.nl). This algorithm was used to estimate global surface water changes at high spatial resolution. These changes include climate change, land reclamation, reservoir construction/decommissioning, erosion/accretion, and many other. This presentation will demonstrate how open satellite data and open platforms such as Google Earth Engine have helped with this research.

Individual Human Cell Responses to Low Doses of Chemicals and Radiation Studied by Synchrotron Infrared Spectromicroscopy

NASA Astrophysics Data System (ADS)

Martin, Michael C.; Holman, Hoi-Ying N.; Blakely, Eleanor A.; Goth-Goldstein, Regine; McKinney, Wayne R.

2000-03-01

Vibrational spectroscopy, when combined with synchrotron radiation-based (SR) microscopy, is a powerful new analytical tool with high spatial resolution for detecting biochemical changes in individual living cells. In contrast to other microscopy methods that require fixing, drying, staining or labeling, SR FTIR microscopy probes intact living cells providing a composite view of all of the molecular responses and the ability to monitor the responses over time in the same cell. Observed spectral changes include all types of lesions induced in that cell as well as cellular responses to external and internal stresses. These spectral changes combined with other analytical tools may provide a fundamental understanding of the key molecular mechanisms induced in response to stresses created by low-doses of radiation and chemicals. In this study we used high spatial-resolution SR FTIR vibrational spectromicroscopy at ALS Beamline 1.4.3 as a sensitive analytical tool to detect chemical- and radiation-induced changes in individual human cells. Our preliminary spectral measurements indicate that this technique is sensitive enough to detect changes in nucleic acids and proteins of cells treated with environmentally relevant concentrations of oxidative stresses: bleomycin, hydrogen peroxide, and X-rays. We observe spectral changes that are unique to each exogenous stressor. This technique has the potential to distinguish changes from exogenous or endogenous oxidative processes. Future development of this technique will allow rapid monitoring of cellular processes such as drug metabolism, early detection of disease, bio-compatibility of implant materials, cellular repair mechanisms, self assembly of cellular apparatus, cell differentiation and fetal development.

Monitoring Farmland Loss Caused by Urbanization in Beijing from Modis Time Series Using Hierarchical Hidden Markov Model

NASA Astrophysics Data System (ADS)

Yuan, Y.; Meng, Y.; Chen, Y. X.; Jiang, C.; Yue, A. Z.

2018-04-01

In this study, we proposed a method to map urban encroachment onto farmland using satellite image time series (SITS) based on the hierarchical hidden Markov model (HHMM). In this method, the farmland change process is decomposed into three hierarchical levels, i.e., the land cover level, the vegetation phenology level, and the SITS level. Then a three-level HHMM is constructed to model the multi-level semantic structure of farmland change process. Once the HHMM is established, a change from farmland to built-up could be detected by inferring the underlying state sequence that is most likely to generate the input time series. The performance of the method is evaluated on MODIS time series in Beijing. Results on both simulated and real datasets demonstrate that our method improves the change detection accuracy compared with the HMM-based method.

Jump-Diffusion models and structural changes for asset forecasting in hydrology

NASA Astrophysics Data System (ADS)

Tranquille Temgoua, André Guy; Martel, Richard; Chang, Philippe J. J.; Rivera, Alfonso

2017-04-01

Impacts of climate change on surface water and groundwater are of concern in many regions of the world since water is an essential natural resource. Jump-Diffusion models are generally used in economics and other related fields but not in hydrology. The potential application could be made for hydrologic data series analysis and forecast. The present study uses Jump-Diffusion models by adding structural changes to detect fluctuations in hydrologic processes in relationship with climate change. The model implicitly assumes that modifications in rivers' flowrates can be divided into three categories: (a) normal changes due to irregular precipitation events especially in tropical regions causing major disturbance in hydrologic processes (this component is modelled by a discrete Brownian motion); (b) abnormal, sudden and non-persistent modifications in hydrologic proceedings are handled by Poisson processes; (c) the persistence of hydrologic fluctuations characterized by structural changes in hydrological data related to climate variability. The objective of this paper is to add structural changes in diffusion models with jumps, in order to capture the persistence of hydrologic fluctuations. Indirectly, the idea is to observe if there are structural changes of discharge/recharge over the study area, and to find an efficient and flexible model able of capturing a wide variety of hydrologic processes. Structural changes in hydrological data are estimated using the method of nonlinear discrete filters via Method of Simulated Moments (MSM). An application is given using sensitive parameters such as baseflow index and recession coefficient to capture discharge/recharge. Historical dataset are examined by the Volume Spread Analysis (VSA) to detect real time and random perturbations in hydrologic processes. The application of the method allows establishing more accurate hydrologic parameters. The impact of this study is perceptible in forecasting floods and groundwater recession. Keywords: hydrologic processes, Jump-Diffusion models, structural changes, forecast, climate change

The Feasibility Evaluation of Land Use Change Detection Using GAOFEN-3 Data

NASA Astrophysics Data System (ADS)

Huang, G.; Sun, Y.; Zhao, Z.

2018-04-01

GaoFen-3 (GF-3) satellite, is the first C band and multi-polarimetric Synthetic Aperture Radar (SAR) satellite in China. In order to explore the feasibility of GF-3 satellite in remote sensing interpretation and land-use remote sensing change detection, taking Guangzhou, China as a study area, the full polarimetric image of GF-3 satellite with 8 m resolution of two temporal as the data source. Firstly, the image is pre-processed by orthorectification, image registration and mosaic, and the land-use remote sensing digital orthophoto map (DOM) in 2017 is made according to the each county. Then the classification analysis and judgment of ground objects on the image are carried out by means of ArcGIS combining with the auxiliary data and using artificial visual interpretation, to determine the area of changes and the category of change objects. According to the unified change information extraction principle to extract change areas. Finally, the change detection results are compared with 3 m resolution TerraSAR-X data and 2 m resolution multi-spectral image, and the accuracy is evaluated. Experimental results show that the accuracy of the GF-3 data is over 75 % in detecting the change of ground objects, and the detection capability of new filling soil is better than that of TerraSAR-X data, verify the detection and monitoring capability of GF-3 data to the change information extraction, also, it shows that GF-3 can provide effective data support for the remote sensing detection of land resources.

Adding temporally localized noise can enhance the contribution of target knowledge on contrast detection.

PubMed

Silvestre, Daphné; Cavanagh, Patrick; Arleo, Angelo; Allard, Rémy

2017-02-01

External noise paradigms are widely used to characterize sensitivity by comparing the effect of a variable on contrast threshold when it is limited by internal versus external noise. A basic assumption of external noise paradigms is that the processing properties are the same in low and high noise. However, recent studies (e.g., Allard & Cavanagh, 2011; Allard & Faubert, 2014b) suggest that this assumption could be violated when using spatiotemporally localized noise (i.e., appearing simultaneously and at the same location as the target) but not when using spatiotemporally extended noise (i.e., continuously displayed, full-screen, dynamic noise). These previous findings may have been specific to the crowding and 0D noise paradigms that were used, so the purpose of the current study is to test if this violation of noise-invariant processing also occurs in a standard contrast detection task in white noise. The rationale of the current study is that local external noise triggers the use of recognition rather than detection and that a recognition process should be more affected by uncertainty about the shape of the target than one involving detection. To investigate the contribution of target knowledge on contrast detection, the effect of orientation uncertainty was evaluated for a contrast detection task in the absence of noise and in the presence of spatiotemporally localized or extended noise. A larger orientation uncertainty effect was observed with temporally localized noise than with temporally extended noise or with no external noise, indicating a change in the nature of the processing for temporally localized noise. We conclude that the use of temporally localized noise in external noise paradigms risks triggering a shift in process, invalidating the noise-invariant processing required for the paradigm. If, instead, temporally extended external noise is used to match the properties of internal noise, no such processing change occurs.

Experimental study of digital image processing techniques for LANDSAT data

NASA Technical Reports Server (NTRS)

Rifman, S. S. (Principal Investigator); Allendoerfer, W. B.; Caron, R. H.; Pemberton, L. J.; Mckinnon, D. M.; Polanski, G.; Simon, K. W.

1976-01-01

The author has identified the following significant results. Results are reported for: (1) subscene registration, (2) full scene rectification and registration, (3) resampling techniques, (4) and ground control point (GCP) extraction. Subscenes (354 pixels x 234 lines) were registered to approximately 1/4 pixel accuracy and evaluated by change detection imagery for three cases: (1) bulk data registration, (2) precision correction of a reference subscene using GCP data, and (3) independently precision processed subscenes. Full scene rectification and registration results were evaluated by using a correlation technique to measure registration errors of 0.3 pixel rms thoughout the full scene. Resampling evaluations of nearest neighbor and TRW cubic convolution processed data included change detection imagery and feature classification. Resampled data were also evaluated for an MSS scene containing specular solar reflections.

Cell-assembly coding in several memory processes.

PubMed

Sakurai, Y

1998-01-01

The present paper discusses why the cell assembly, i.e., an ensemble population of neurons with flexible functional connections, is a tenable view of the basic code for information processes in the brain. The main properties indicating the reality of cell-assembly coding are neurons overlaps among different assemblies and connection dynamics within and among the assemblies. The former can be detected as multiple functions of individual neurons in processing different kinds of information. Individual neurons appear to be involved in multiple information processes. The latter can be detected as changes of functional synaptic connections in processing different kinds of information. Correlations of activity among some of the recorded neurons appear to change in multiple information processes. Recent experiments have compared several different memory processes (tasks) and detected these two main properties, indicating cell-assembly coding of memory in the working brain. The first experiment compared different types of processing of identical stimuli, i.e., working memory and reference memory of auditory stimuli. The second experiment compared identical processes of different types of stimuli, i.e., discriminations of simple auditory, simple visual, and configural auditory-visual stimuli. The third experiment compared identical processes of different types of stimuli with or without temporal processing of stimuli, i.e., discriminations of elemental auditory, configural auditory-visual, and sequential auditory-visual stimuli. Some possible features of the cell-assembly coding, especially "dual coding" by individual neurons and cell assemblies, are discussed for future experimental approaches. Copyright 1998 Academic Press.

Preferential attention to animals and people is independent of the amygdala

PubMed Central

Tsuchiya, Naotsugu; New, Joshua; Hurlemann, Rene; Adolphs, Ralph

2015-01-01

The amygdala is thought to play a critical role in detecting salient stimuli. Several studies have taken ecological approaches to investigating such saliency, and argue for domain-specific effects for processing certain natural stimulus categories, in particular faces and animals. Linking this to the amygdala, neurons in the human amygdala have been found to respond strongly to faces and also to animals. However, the amygdala’s necessary role for such category-specific effects at the behavioral level remains untested. Here we tested four rare patients with bilateral amygdala lesions on an established change-detection protocol. Consistent with prior published studies, healthy controls showed reliably faster and more accurate detection of people and animals, as compared with artifacts and plants. So did all four amygdala patients: there were no differences in phenomenal change blindness, in behavioral reaction time to detect changes or in eye-tracking measures. The findings provide decisive evidence against a critical participation of the amygdala in rapid initial processing of attention to animate stimuli, suggesting that the necessary neural substrates for this phenomenon arise either in other subcortical structures (such as the pulvinar) or within the cortex itself. PMID:24795434

The effects of changes in object location on object identity detection: A simultaneous EEG-fMRI study.

PubMed

Yang, Ping; Fan, Chenggui; Wang, Min; Fogelson, Noa; Li, Ling

2017-08-15

Object identity and location are bound together to form a unique integration that is maintained and processed in visual working memory (VWM). Changes in task-irrelevant object location have been shown to impair the retrieval of memorial representations and the detection of object identity changes. However, the neural correlates of this cognitive process remain largely unknown. In the present study, we aim to investigate the underlying brain activation during object color change detection and the modulatory effects of changes in object location and VWM load. To this end we used simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) recordings, which can reveal the neural activity with both high temporal and high spatial resolution. Subjects responded faster and with greater accuracy in the repeated compared to the changed object location condition, when a higher VWM load was utilized. These results support the spatial congruency advantage theory and suggest that it is more pronounced with higher VWM load. Furthermore, the spatial congruency effect was associated with larger posterior N1 activity, greater activation of the right inferior frontal gyrus (IFG) and less suppression of the right supramarginal gyrus (SMG), when object location was repeated compared to when it was changed. The ERP-fMRI integrative analysis demonstrated that the object location discrimination-related N1 component is generated in the right SMG. Copyright © 2017 Elsevier Inc. All rights reserved.

Temporal integration: intentional sound discrimination does not modulate stimulus-driven processes in auditory event synthesis.

PubMed

Sussman, Elyse; Winkler, István; Kreuzer, Judith; Saher, Marieke; Näätänen, Risto; Ritter, Walter

2002-12-01

Our previous study showed that the auditory context could influence whether two successive acoustic changes occurring within the temporal integration window (approximately 200ms) were pre-attentively encoded as a single auditory event or as two discrete events (Cogn Brain Res 12 (2001) 431). The aim of the current study was to assess whether top-down processes could influence the stimulus-driven processes in determining what constitutes an auditory event. Electroencepholagram (EEG) was recorded from 11 scalp electrodes to frequently occurring standard and infrequently occurring deviant sounds. Within the stimulus blocks, deviants either occurred only in pairs (successive feature changes) or both singly and in pairs. Event-related potential indices of change and target detection, the mismatch negativity (MMN) and the N2b component, respectively, were compared with the simultaneously measured performance in discriminating the deviants. Even though subjects could voluntarily distinguish the two successive auditory feature changes from each other, which was also indicated by the elicitation of the N2b target-detection response, top-down processes did not modify the event organization reflected by the MMN response. Top-down processes can extract elemental auditory information from a single integrated acoustic event, but the extraction occurs at a later processing stage than the one whose outcome is indexed by MMN. Initial processes of auditory event-formation are fully governed by the context within which the sounds occur. Perception of the deviants as two separate sound events (the top-down effects) did not change the initial neural representation of the same deviants as one event (indexed by the MMN), without a corresponding change in the stimulus-driven sound organization.

Land cover change detection of Hatiya Island, Bangladesh, using remote sensing techniques

NASA Astrophysics Data System (ADS)

Kumar, Lalit; Ghosh, Manoj Kumer

2012-01-01

Land cover change is a significant issue for environmental managers for sustainable management. Remote sensing techniques have been shown to have a high probability of recognizing land cover patterns and change detection due to periodic coverage, data integrity, and provision of data in a broad range of the electromagnetic spectrum. We evaluate the applicability of remote sensing techniques for land cover pattern recognition, as well as land cover change detection of the Hatiya Island, Bangladesh, and quantify land cover changes from 1977 to 1999. A supervised classification approach was used to classify Landsat Enhanced Thematic Mapper (ETM), Thematic Mapper (TM), and Multispectral Scanner (MSS) images into eight major land cover categories. We detected major land cover changes over the 22-year study period. During this period, marshy land, mud, mud with small grass, and bare soil had decreased by 85%, 46%, 44%, and 24%, respectively, while agricultural land, medium forest, forest, and settlement had positive changes of 26%, 45%, 363%, and 59%, respectively. The primary drivers of such landscape change were erosion and accretion processes, human pressure, and the reforestation and land reclamation programs of the Bangladesh Government.

Mutual information estimation reveals global associations between stimuli and biological processes

PubMed Central

Suzuki, Taiji; Sugiyama, Masashi; Kanamori, Takafumi; Sese, Jun

2009-01-01

Background Although microarray gene expression analysis has become popular, it remains difficult to interpret the biological changes caused by stimuli or variation of conditions. Clustering of genes and associating each group with biological functions are often used methods. However, such methods only detect partial changes within cell processes. Herein, we propose a method for discovering global changes within a cell by associating observed conditions of gene expression with gene functions. Results To elucidate the association, we introduce a novel feature selection method called Least-Squares Mutual Information (LSMI), which computes mutual information without density estimaion, and therefore LSMI can detect nonlinear associations within a cell. We demonstrate the effectiveness of LSMI through comparison with existing methods. The results of the application to yeast microarray datasets reveal that non-natural stimuli affect various biological processes, whereas others are no significant relation to specific cell processes. Furthermore, we discover that biological processes can be categorized into four types according to the responses of various stimuli: DNA/RNA metabolism, gene expression, protein metabolism, and protein localization. Conclusion We proposed a novel feature selection method called LSMI, and applied LSMI to mining the association between conditions of yeast and biological processes through microarray datasets. In fact, LSMI allows us to elucidate the global organization of cellular process control. PMID:19208155

Post-Disaster Damage Assessment Through Coherent Change Detection on SAR Imagery

NASA Astrophysics Data System (ADS)

Guida, L.; Boccardo, P.; Donevski, I.; Lo Schiavo, L.; Molinari, M. E.; Monti-Guarnieri, A.; Oxoli, D.; Brovelli, M. A.

2018-04-01

Damage assessment is a fundamental step to support emergency response and recovery activities in a post-earthquake scenario. In recent years, UAVs and satellite optical imagery was applied to assess major structural damages before technicians could reach the areas affected by the earthquake. However, bad weather conditions may harm the quality of these optical assessments, thus limiting the practical applicability of these techniques. In this paper, the application of Synthetic Aperture Radar (SAR) imagery is investigated and a novel approach to SAR-based damage assessment is presented. Coherent Change Detection (CCD) algorithms on multiple interferometrically pre-processed SAR images of the area affected by the seismic event are exploited to automatically detect potential damages to buildings and other physical structures. As a case study, the 2016 Central Italy earthquake involving the cities of Amatrice and Accumoli was selected. The main contribution of the research outlined above is the integration of a complex process, requiring the coordination of a variety of methods and tools, into a unitary framework, which allows end-to-end application of the approach from SAR data pre-processing to result visualization in a Geographic Information System (GIS). A prototype of this pipeline was implemented, and the outcomes of this methodology were validated through an extended comparison with traditional damage assessment maps, created through photo-interpretation of high resolution aerial imagery. The results indicate that the proposed methodology is able to perform damage detection with a good level of accuracy, as most of the detected points of change are concentrated around highly damaged buildings.

Evaluation of Earthquake Detection Performance in Terms of Quality and Speed in SEISCOMP3 Using New Modules Qceval, Npeval and Sceval

NASA Astrophysics Data System (ADS)

Roessler, D.; Weber, B.; Ellguth, E.; Spazier, J.

2017-12-01

The geometry of seismic monitoring networks, site conditions and data availability as well as monitoring targets and strategies typically impose trade-offs between data quality, earthquake detection sensitivity, false detections and alert times. Network detection capabilities typically change with alteration of the seismic noise level by human activity or by varying weather and sea conditions. To give helpful information to operators and maintenance coordinators, gempa developed a range of tools to evaluate earthquake detection and network performance including qceval, npeval and sceval. qceval is a module which analyzes waveform quality parameters in real-time and deactivates and reactivates data streams based on waveform quality thresholds for automatic processing. For example, thresholds can be defined for latency, delay, timing quality, spikes and gaps count and rms. As changes in the automatic processing have a direct influence on detection quality and speed, another tool called "npeval" was designed to calculate in real-time the expected time needed to detect and locate earthquakes by evaluating the effective network geometry. The effective network geometry is derived from the configuration of stations participating in the detection. The detection times are shown as an additional layer on the map and updated in real-time as soon as the effective network geometry changes. Yet another new tool, "sceval", is an automatic module which classifies located seismic events (Origins) in real-time. sceval evaluates the spatial distribution of the stations contributing to an Origin. It confirms or rejects the status of Origins, adds comments or leaves the Origin unclassified. The comments are passed to an additional sceval plug-in where the end user can customize event types. This unique identification of real and fake events in earthquake catalogues allows to lower network detection thresholds. In real-time monitoring situations operators can limit the processing to events with unclassified Origins, reducing their workload. Classified Origins can be treated specifically by other procedures. These modules have been calibrated and fully tested by several complex seismic monitoring networks in the region of Indonesia and Northern Chile.

Continuous Change Detection and Classification (CCDC) of Land Cover Using All Available Landsat Data

NASA Astrophysics Data System (ADS)

Zhu, Z.; Woodcock, C. E.

2012-12-01

A new algorithm for Continuous Change Detection and Classification (CCDC) of land cover using all available Landsat data is developed. This new algorithm is capable of detecting many kinds of land cover change as new images are collected and at the same time provide land cover maps for any given time. To better identify land cover change, a two step cloud, cloud shadow, and snow masking algorithm is used for eliminating "noisy" observations. Next, a time series model that has components of seasonality, trend, and break estimates the surface reflectance and temperature. The time series model is updated continuously with newly acquired observations. Due to the high variability in spectral response for different kinds of land cover change, the CCDC algorithm uses a data-driven threshold derived from all seven Landsat bands. When the difference between observed and predicted exceeds the thresholds three consecutive times, a pixel is identified as land cover change. Land cover classification is done after change detection. Coefficients from the time series models and the Root Mean Square Error (RMSE) from model fitting are used as classification inputs for the Random Forest Classifier (RFC). We applied this new algorithm for one Landsat scene (Path 12 Row 31) that includes all of Rhode Island as well as much of Eastern Massachusetts and parts of Connecticut. A total of 532 Landsat images acquired between 1982 and 2011 were processed. During this period, 619,924 pixels were detected to change once (91% of total changed pixels) and 60,199 pixels were detected to change twice (8% of total changed pixels). The most frequent land cover change category is from mixed forest to low density residential which occupies more than 8% of total land cover change pixels.

Different deformation patterns using GPS in the volcanic process of El Hierro (Canary Island) 2011-2013

NASA Astrophysics Data System (ADS)

García-Cañada, Laura; José García-Arias, María; Pereda de Pablo, Jorge; Lamolda, Héctor; López, Carmen

2014-05-01

Ground deformation is one of the most important parameter in volcano monitoring. The detected deformations in volcanic areas can be precursors of a volcanic activity and contribute with useful information to study the evolution of an unrest, eruption or any volcanic process. GPS is the most common technique used to measure volcano deformations. It can be used to detect slow displacement rates or much larger and faster deformations associated with any volcanic process. In volcanoes the deformation is expected to be a mixed of nature; during periods of quiescence it will be slow or not present, while increased activity slow displacement rates can be detected or much larger and faster deformations can be measure due to magma intrusion, for example in the hours to days prior a eruption beginning. In response to the anomalous seismicity detected at El Hierro in July 2011, the Instituto Geográfico Nacional (IGN) improved its volcano monitoring network in the island with continuous GPS that had been used to measure the ground deformation associated with the precursory unrest since summer 2011, submarine eruption (October 2011-March 2012) and the following unrest periods (2012-2013). The continuous GPS time series, together with other techniques, had been used to evaluate the activity and to detect changes in the process. We investigate changes in the direction and module of the deformation obtained by GPS and they show different patterns in every unrest period, very close to the seismicity locations and migrations.

Family involvement in timely detection of changes in health of nursing homes residents: A qualitative exploratory study.

PubMed

Powell, Catherine; Blighe, Alan; Froggatt, Katherine; McCormack, Brendan; Woodward-Carlton, Barbara; Young, John; Robinson, Louise; Downs, Murna

2018-01-01

To explore family perspectives on their involvement in the timely detection of changes in their relatives' health in UK nursing homes. Increasingly, policy attention is being paid to the need to reduce hospitalisations for conditions that, if detected and treated in time, could be managed in the community. We know that family continue to be involved in the care of their family members once they have moved into a nursing home. Little is known, however, about family involvement in the timely detection of changes in health in nursing home residents. Qualitative exploratory study with thematic analysis. A purposive sampling strategy was applied. Fourteen semi-structured one-to-one interviews with family members of people living in 13 different UK nursing homes. Data were collected from November 2015-March 2016. Families were involved in the timely detection of changes in health in three key ways: noticing signs of changes in health, informing care staff about what they noticed and educating care staff about their family members' changes in health. Families suggested they could be supported to detect timely changes in health by developing effective working practices with care staff. Families can provide a special contribution to the process of timely detection in nursing homes. Their involvement needs to be negotiated, better supported, as well as given more legitimacy and structure within the nursing home. Families could provide much needed support to nursing home nurses, care assistants and managers in timely detection of changes in health. This may be achieved through communication about their preferred involvement on a case-by-case basis as well as providing appropriate support or services. © 2017 The Authors. Journal of Clinical Nursing Published by John Wiley & Sons Ltd.

Using phylogeny and functional traits for assessing community assembly along environmental gradients: A deterministic process driven by elevation.

PubMed

Xu, Jinshi; Chen, Yu; Zhang, Lixia; Chai, Yongfu; Wang, Mao; Guo, Yaoxin; Li, Ting; Yue, Ming

2017-07-01

Community assembly processes is the primary focus of community ecology. Using phylogenetic-based and functional trait-based methods jointly to explore these processes along environmental gradients are useful ways to explain the change of assembly mechanisms under changing world. Our study combined these methods to test assembly processes in wide range gradients of elevation and other habitat environmental factors. We collected our data at 40 plots in Taibai Mountain, China, with more than 2,300 m altitude difference in study area and then measured traits and environmental factors. Variance partitioning was used to distinguish the main environment factors leading to phylogeny and traits change among 40 plots. Principal component analysis (PCA) was applied to colligate other environment factors. Community assembly patterns along environmental gradients based on phylogenetic and functional methods were studied for exploring assembly mechanisms. Phylogenetic signal was calculated for each community along environmental gradients in order to detect the variation of trait performance on phylogeny. Elevation showed a better explanatory power than other environment factors for phylogenetic and most traits' variance. Phylogenetic and several functional structure clustered at high elevation while some conserved traits overdispersed. Convergent tendency which might be caused by filtering or competition along elevation was detected based on functional traits. Leaf dry matter content (LDMC) and leaf nitrogen content along PCA 1 axis showed conflicting patterns comparing to patterns showed on elevation. LDMC exhibited the strongest phylogenetic signal. Only the phylogenetic signal of maximum plant height showed explicable change along environmental gradients. Synthesis . Elevation is the best environment factors for predicting phylogeny and traits change. Plant's phylogenetic and some functional structures show environmental filtering in alpine region while it shows different assembly processes in middle- and low-altitude region by different trait/phylogeny. The results highlight deterministic processes dominate community assembly in large-scale environmental gradients. Performance of phylogeny and traits along gradients may be independent with each other. The novel method for calculating functional structure which we used in this study and the focus of phylogenetic signal change along gradients may provide more useful ways to detect community assembly mechanisms.

ADAPTIVE WATER SENSOR SIGNAL PROCESSING: EXPERIMENTAL RESULTS AND IMPLICATIONS FOR ONLINE CONTAMINANT WARNING SYSTEMS

EPA Science Inventory

A contaminant detection technique and its optimization algorithms have two principal functions. One is the adaptive signal treatment that suppresses background noise and enhances contaminant signals, leading to a promising detection of water quality changes at a false rate as low...

Cross-modal detection using various temporal and spatial configurations.

PubMed

Schirillo, James A

2011-01-01

To better understand temporal and spatial cross-modal interactions, two signal detection experiments were conducted in which an auditory target was sometimes accompanied by an irrelevant flash of light. In the first, a psychometric function for detecting a unisensory auditory target in varying signal-to-noise ratios (SNRs) was derived. Then auditory target detection was measured while an irrelevant light was presented with light/sound stimulus onset asynchronies (SOAs) between 0 and ±700 ms. When the light preceded the sound by 100 ms or was coincident, target detection (d') improved for low SNR conditions. In contrast, for larger SOAs (350 and 700 ms), the behavioral gain resulted from a change in both d' and response criterion (β). However, when the light followed the sound, performance changed little. In the second experiment, observers detected multimodal target sounds at eccentricities of ±8°, and ±24°. Sensitivity benefits occurred at both locations, with a larger change at the more peripheral location. Thus, both temporal and spatial factors affect signal detection measures, effectively parsing sensory and decision-making processes.

Building Change Detection from Harvey using Unmanned Aerial System (UAS)

NASA Astrophysics Data System (ADS)

Chang, A.; Yeom, J.; Jung, J.; Choi, I.

2017-12-01

Unmanned Aerial System (UAS) is getting to be the most important technique in recent days since the fine spatial and high temporal resolution data previously unobtainable from traditional remote sensing platforms. Advanced UAS data can provide a great opportunity for disaster monitoring. Especially, building change detection is the one of the most important topics for damage assessment and recovery from disasters. This study is proposing a method to monitor building change with UAS data for Holiday Beach in Texas, where was directly hit by Harvey on 25 August 2017. This study adopted 3D change detection to monitor building damage and recovery levels with building height as well as natural color information. We used a rotorcraft UAS to collect RGB data twice on 9 September and 18 October 2017 after the hurricane. The UAS data was processed using Agisoft Photoscan Pro Software to generate super high resolution dataset including orthomosaic, DSM (Digital Surface Model), and 3D point cloud. We compared the processed dataset with an airborne image considerable as before-hurricane data, which was acquired on January 2016. Building damage and recovery levels were determined by height and color change. The result will show that UAS data is useful to assess building damage and recovery for affected area by the natural disaster such as Harvey.

[Application of optical flow dynamic texture in land use/cover change detection].

PubMed

Yan, Li; Gong, Yi-Long; Zhang, Yi; Duan, Wei

2014-11-01

In the present study, a novel change detection approach for high resolution remote sensing images is proposed based on the optical flow dynamic texture (OFDT), which could achieve the land use & land cover change information automatically with a dynamic description of ground-object changes. This paper describes the ground-object gradual change process from the principle using optical flow theory, which breaks the ground-object sudden change hypothesis in remote sensing change detection methods in the past. As the steps of this method are simple, it could be integrated in the systems and software such as Land Resource Management and Urban Planning software that needs to find ground-object changes. This method takes into account the temporal dimension feature between remote sensing images, which provides a richer set of information for remote sensing change detection, thereby improving the status that most of the change detection methods are mainly dependent on the spatial dimension information. In this article, optical flow dynamic texture is the basic reflection of changes, and it is used in high resolution remote sensing image support vector machine post-classification change detection, combined with spectral information. The texture in the temporal dimension which is considered in this article has a smaller amount of data than most of the textures in the spatial dimensions. The highly automated texture computing has only one parameter to set, which could relax the onerous manual evaluation present status. The effectiveness of the proposed approach is evaluated with the 2011 and 2012 QuickBird datasets covering Duerbert Mongolian Autonomous County of Daqing City, China. Then, the effects of different optical flow smooth coefficient and the impact on the description of the ground-object changes in the method are deeply analyzed: The experiment result is satisfactory, with an 87.29% overall accuracy and an 0.850 7 Kappa index, and the method achieves better performance than the post-classification change detection methods using spectral information only.

A magnetic/fluorometric bimodal sensor based on a carbon dots-MnO2 platform for glutathione detection

NASA Astrophysics Data System (ADS)

Xu, Yang; Chen, Xi; Chai, Ran; Xing, Chengfen; Li, Huanrong; Yin, Xue-Bo

2016-07-01

A novel magnetic/fluorometric bimodal sensor was built from carbon dots (CDs) and MnO2. The resulting sensor was sensitive to glutathione (GSH), leading to apparent enhancement of magnetic resonance (MR) and fluorescence signals along with visual changes. The bimodal detection strategy is based on the decomposition of the CDs-MnO2 through a redox reaction between GSH and MnO2. This process causes the transformation from non-MR-active MnO2 to MR-active Mn2+, and is accompanied by fluorescence restoration of CDs. Compared with a range of other CDs, the polyethylenimine (PEI) passivated CDs (denoted as pCDs) were suitable for detection due to their positive surface potential. Cross-validation between MR and fluorescence provided detailed information regarding the MnO2 reduction process, and revealed the three distinct stages of the redox process. Thus, the design of a CD-based sensor for the magnetic/fluorometric bimodal detection of GSH was emphasized for the first time. This platform showed a detection limit of 0.6 μM with a linear range of 1-200 μM in the fluorescence mode, while the MR mode exhibited a linear range of 5-200 μM and a GSH detection limit of 2.8 μM with a visible change being observed rapidly at 1 μM in the MR images. Furthermore, the introduction of the MR mode allowed the biothiols to be easily identified. The integration of CD fluorescence with an MR response was demonstrated to be promising for providing detailed information and discriminating power, and therefore extend the application of CDs in sensing and imaging.A novel magnetic/fluorometric bimodal sensor was built from carbon dots (CDs) and MnO2. The resulting sensor was sensitive to glutathione (GSH), leading to apparent enhancement of magnetic resonance (MR) and fluorescence signals along with visual changes. The bimodal detection strategy is based on the decomposition of the CDs-MnO2 through a redox reaction between GSH and MnO2. This process causes the transformation from non-MR-active MnO2 to MR-active Mn2+, and is accompanied by fluorescence restoration of CDs. Compared with a range of other CDs, the polyethylenimine (PEI) passivated CDs (denoted as pCDs) were suitable for detection due to their positive surface potential. Cross-validation between MR and fluorescence provided detailed information regarding the MnO2 reduction process, and revealed the three distinct stages of the redox process. Thus, the design of a CD-based sensor for the magnetic/fluorometric bimodal detection of GSH was emphasized for the first time. This platform showed a detection limit of 0.6 μM with a linear range of 1-200 μM in the fluorescence mode, while the MR mode exhibited a linear range of 5-200 μM and a GSH detection limit of 2.8 μM with a visible change being observed rapidly at 1 μM in the MR images. Furthermore, the introduction of the MR mode allowed the biothiols to be easily identified. The integration of CD fluorescence with an MR response was demonstrated to be promising for providing detailed information and discriminating power, and therefore extend the application of CDs in sensing and imaging. Electronic supplementary information (ESI) available. See DOI: 10.1039/c6nr03129c

Methodology for Evaluating Raw Material Changes to RSRM Elastomeric Insulation Materials

NASA Technical Reports Server (NTRS)

Mildenhall, Scott D.; McCool, Alex (Technical Monitor)

2001-01-01

The Reusable Solid Rocket Motor (RSRM) uses asbestos and silicon dioxide filled acrylonitrile butadiene rubber (AS-NBR) as the primary internal insulation to protect the case from heat. During the course of the RSRM Program, several changes have been made to the raw materials and processing of the AS-NBR elastomeric insulation material. These changes have been primarily caused by raw materials becoming obsolete. In addition, some process changes have been implemented that were deemed necessary to improve the quality and consistency of the AS-NBR insulation material. Each change has been evaluated using unique test efforts customized to determine the potential impacts of the specific raw material or process change. Following the evaluations, the various raw material and process changes were successfully implemented with no detectable effect on the performance of the AS-NBR insulation. This paper will discuss some of the raw material and process changes evaluated, the methodology used in designing the unique test plans, and the general evaluation results. A summary of the change history of RSRM AS-NBR internal insulation is also presented.

Detection of kinetic change points in piece-wise linear single molecule motion

NASA Astrophysics Data System (ADS)

Hill, Flynn R.; van Oijen, Antoine M.; Duderstadt, Karl E.

2018-03-01

Single-molecule approaches present a powerful way to obtain detailed kinetic information at the molecular level. However, the identification of small rate changes is often hindered by the considerable noise present in such single-molecule kinetic data. We present a general method to detect such kinetic change points in trajectories of motion of processive single molecules having Gaussian noise, with a minimum number of parameters and without the need of an assumed kinetic model beyond piece-wise linearity of motion. Kinetic change points are detected using a likelihood ratio test in which the probability of no change is compared to the probability of a change occurring, given the experimental noise. A predetermined confidence interval minimizes the occurrence of false detections. Applying the method recursively to all sub-regions of a single molecule trajectory ensures that all kinetic change points are located. The algorithm presented allows rigorous and quantitative determination of kinetic change points in noisy single molecule observations without the need for filtering or binning, which reduce temporal resolution and obscure dynamics. The statistical framework for the approach and implementation details are discussed. The detection power of the algorithm is assessed using simulations with both single kinetic changes and multiple kinetic changes that typically arise in observations of single-molecule DNA-replication reactions. Implementations of the algorithm are provided in ImageJ plugin format written in Java and in the Julia language for numeric computing, with accompanying Jupyter Notebooks to allow reproduction of the analysis presented here.

Robust drone detection for day/night counter-UAV with static VIS and SWIR cameras

NASA Astrophysics Data System (ADS)

Müller, Thomas

2017-05-01

Recent progress in the development of unmanned aerial vehicles (UAVs) has led to more and more situations in which drones like quadrocopters or octocopters pose a potential serious thread or could be used as a powerful tool for illegal activities. Therefore, counter-UAV systems are required in a lot of applications to detect approaching drones as early as possible. In this paper, an efficient and robust algorithm is presented for UAV detection using static VIS and SWIR cameras. Whereas VIS cameras with a high resolution enable to detect UAVs in the daytime in further distances, surveillance at night can be performed with a SWIR camera. First, a background estimation and structural adaptive change detection process detects movements and other changes in the observed scene. Afterwards, the local density of changes is computed used for background density learning and to build up the foreground model which are compared in order to finally get the UAV alarm result. The density model is used to filter out noise effects, on the one hand. On the other hand, moving scene parts like moving leaves in the wind or driving cars on a street can easily be learned in order to mask such areas out and suppress false alarms there. This scene learning is done automatically simply by processing without UAVs in order to capture the normal situation. The given results document the performance of the presented approach in VIS and SWIR in different situations.

Applying shot boundary detection for automated crystal growth analysis during in situ transmission electron microscope experiments

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

Moeglein, W. A.; Griswold, R.; Mehdi, B. L.

In-situ (scanning) transmission electron microscopy (S/TEM) is being developed for numerous applications in the study of nucleation and growth under electrochemical driving forces. For this type of experiment, one of the key parameters is to identify when nucleation initiates. Typically the process of identifying the moment that crystals begin to form is a manual process requiring the user to perform an observation and respond accordingly (adjust focus, magnification, translate the stage etc.). However, as the speed of the cameras being used to perform these observations increases, the ability of a user to “catch” the important initial stage of nucleation decreasesmore » (there is more information that is available in the first few milliseconds of the process). Here we show that video shot boundary detection (SBD) can automatically detect frames where a change in the image occurs. We show that this method can be applied to quickly and accurately identify points of change during crystal growth. This technique allows for automated segmentation of a digital stream for further analysis and the assignment of arbitrary time stamps for the initiation of processes that are independent of the user’s ability to observe and react.« less

Research on a Defects Detection Method in the Ferrite Phase Shifter Cementing Process Based on a Multi-Sensor Prognostic and Health Management (PHM) System.

PubMed

Wan, Bo; Fu, Guicui; Li, Yanruoyue; Zhao, Youhu

2016-08-10

The cementing manufacturing process of ferrite phase shifters has the defect that cementing strength is insufficient and fractures always appear. A detection method of these defects was studied utilizing the multi-sensors Prognostic and Health Management (PHM) theory. Aiming at these process defects, the reasons that lead to defects are analyzed in this paper. In the meanwhile, the key process parameters were determined and Differential Scanning Calorimetry (DSC) tests during the cure process of resin cementing were carried out. At the same time, in order to get data on changing cementing strength, multiple-group cementing process tests of different key process parameters were designed and conducted. A relational model of cementing strength and cure temperature, time and pressure was established, by combining data of DSC and process tests as well as based on the Avrami formula. Through sensitivity analysis for three process parameters, the on-line detection decision criterion and the process parameters which have obvious impact on cementing strength were determined. A PHM system with multiple temperature and pressure sensors was established on this basis, and then, on-line detection, diagnosis and control for ferrite phase shifter cementing process defects were realized. It was verified by subsequent process that the on-line detection system improved the reliability of the ferrite phase shifter cementing process and reduced the incidence of insufficient cementing strength defects.

Latent change models of adult cognition: are changes in processing speed and working memory associated with changes in episodic memory?

PubMed

Hertzog, Christopher; Dixon, Roger A; Hultsch, David F; MacDonald, Stuart W S

2003-12-01

The authors used 6-year longitudinal data from the Victoria Longitudinal Study (VLS) to investigate individual differences in amount of episodic memory change. Latent change models revealed reliable individual differences in cognitive change. Changes in episodic memory were significantly correlated with changes in other cognitive variables, including speed and working memory. A structural equation model for the latent change scores showed that changes in speed and working memory predicted changes in episodic memory, as expected by processing resource theory. However, these effects were best modeled as being mediated by changes in induction and fact retrieval. Dissociations were detected between cross-sectional ability correlations and longitudinal changes. Shuffling the tasks used to define the Working Memory latent variable altered patterns of change correlations.

The Role of Facial Microexpression State (FMES) Change in the Process of Conceptual Conflict

ERIC Educational Resources Information Center

Chiu, Mei-Hung; Chou, Chin-Cheng; Wu, Wen-Lung; Liaw, Hongming

2014-01-01

This paper explores whether facial microexpression state (FMES) changes can be used to identify moments of conceptual conflict, one of the pathways to conceptual change. It is known that when the preconditions of conceptual conflicts are met and conceptual conflicts are detected in students, it is then possible for conceptual change to take place.…

Novel image processing approach to detect malaria

NASA Astrophysics Data System (ADS)

Mas, David; Ferrer, Belen; Cojoc, Dan; Finaurini, Sara; Mico, Vicente; Garcia, Javier; Zalevsky, Zeev

2015-09-01

In this paper we present a novel image processing algorithm providing good preliminary capabilities for in vitro detection of malaria. The proposed concept is based upon analysis of the temporal variation of each pixel. Changes in dark pixels mean that inter cellular activity happened, indicating the presence of the malaria parasite inside the cell. Preliminary experimental results involving analysis of red blood cells being either healthy or infected with malaria parasites, validated the potential benefit of the proposed numerical approach.

Recurrent neural network based virtual detection line

NASA Astrophysics Data System (ADS)

Kadikis, Roberts

2018-04-01

The paper proposes an efficient method for detection of moving objects in the video. The objects are detected when they cross a virtual detection line. Only the pixels of the detection line are processed, which makes the method computationally efficient. A Recurrent Neural Network processes these pixels. The machine learning approach allows one to train a model that works in different and changing outdoor conditions. Also, the same network can be trained for various detection tasks, which is demonstrated by the tests on vehicle and people counting. In addition, the paper proposes a method for semi-automatic acquisition of labeled training data. The labeling method is used to create training and testing datasets, which in turn are used to train and evaluate the accuracy and efficiency of the detection method. The method shows similar accuracy as the alternative efficient methods but provides greater adaptability and usability for different tasks.

A theoretical Gaussian framework for anomalous change detection in hyperspectral images

NASA Astrophysics Data System (ADS)

Acito, Nicola; Diani, Marco; Corsini, Giovanni

2017-10-01

Exploitation of temporal series of hyperspectral images is a relatively new discipline that has a wide variety of possible applications in fields like remote sensing, area surveillance, defense and security, search and rescue and so on. In this work, we discuss how images taken at two different times can be processed to detect changes caused by insertion, deletion or displacement of small objects in the monitored scene. This problem is known in the literature as anomalous change detection (ACD) and it can be viewed as the extension, to the multitemporal case, of the well-known anomaly detection problem in a single image. In fact, in both cases, the hyperspectral images are processed blindly in an unsupervised manner and without a-priori knowledge about the target spectrum. We introduce the ACD problem using an approach based on the statistical decision theory and we derive a common framework including different ACD approaches. Particularly, we clearly define the observation space, the data statistical distribution conditioned to the two competing hypotheses and the procedure followed to come with the solution. The proposed overview places emphasis on techniques based on the multivariate Gaussian model that allows a formal presentation of the ACD problem and the rigorous derivation of the possible solutions in a way that is both mathematically more tractable and easier to interpret. We also discuss practical problems related to the application of the detectors in the real world and present affordable solutions. Namely, we describe the ACD processing chain including the strategies that are commonly adopted to compensate pervasive radiometric changes, caused by the different illumination/atmospheric conditions, and to mitigate the residual geometric image co-registration errors. Results obtained on real freely available data are discussed in order to test and compare the methods within the proposed general framework.

Change Detection by Rhesus Monkeys (Macaca mulatta) and Pigeons (Columba livia)

PubMed Central

Elmore, L. Caitlin; Magnotti, John F.; Katz, Jeffrey S.; Wright, Anthony A.

2012-01-01

Two monkeys learned a color change-detection task where two colored circles (selected from a 4-color set) were presented on a 4×4 invisible matrix. Following a delay, the correct response was to touch the changed colored circle. The monkeys' learning, color transfer, and delay transfer were compared to a similar experiment with pigeons. Monkeys, like pigeons, showed full transfer to four novel colors, and to delays as long as 6.4 s, suggesting they remembered the colors as opposed to perceptual based attentional capture process that may work at very short delays. The monkeys and pigeons were further tested to compare transfer to other dimensions. Monkeys transferred to shape and location changes, unlike the pigeons, but neither species transferred to size changes. Thus, monkeys were less restricted in their domain to detect change than pigeons, but both species learned the basic task and appear suitable for comparative studies of visual short-term memory. PMID:22428982

Asynchronous Processing of a Constellation of Geostationary and Polar-Orbiting Satellites for Fire Detection and Smoke Estimation

NASA Astrophysics Data System (ADS)

Hyer, E. J.; Peterson, D. A.; Curtis, C. A.; Schmidt, C. C.; Hoffman, J.; Prins, E. M.

2014-12-01

The Fire Locating and Monitoring of Burning Emissions (FLAMBE) system converts satellite observations of thermally anomalous pixels into spatially and temporally continuous estimates of smoke release from open biomass burning. This system currently processes data from a constellation of 5 geostationary and 2 polar-orbiting sensors. Additional sensors, including NPP VIIRS and the imager on the Korea COMS-1 geostationary satellite, will soon be added. This constellation experiences schedule changes and outages of various durations, making the set of available scenes for fire detection highly variable on an hourly and daily basis. Adding to the complexity, the latency of the satellite data is variable between and within sensors. FLAMBE shares with many fire detection systems the goal of detecting as many fires as possible as early as possible, but the FLAMBE system must also produce a consistent estimate of smoke production with minimal artifacts from the changing constellation. To achieve this, NRL has developed a system of asynchronous processing and cross-calibration that permits satellite data to be used as it arrives, while preserving the consistency of the smoke emission estimates. This talk describes the asynchronous data ingest methodology, including latency statistics for the constellation. We also provide an overview and show results from the system we have developed to normalize multi-sensor fire detection for consistency.

Zeptomole Detection Scheme Based on Levitation Coordinate Measurements of a Single Microparticle in a Coupled Acoustic-Gravitational Field.

PubMed

Miyagawa, Akihisa; Harada, Makoto; Okada, Tetsuo

2018-02-06

We present a novel analytical principle in which an analyte (according to its concentration) induces a change in the density of a microparticle, which is measured as a vertical coordinate in a coupled acoustic-gravitational (CAG) field. The density change is caused by the binding of gold nanoparticles (AuNP's) on a polystyrene (PS) microparticle through avidin-biotin association. The density of a 10-μm PS particle increases by 2% when 500 100-nm AuNP's are bound to the PS. The CAG can detect this density change as a 5-10 μm shift of the levitation coordinate of the PS. This approach, which allows us to detect 700 AuNP's bound to a PS particle, is utilized to detect biotin in solution. Biotin is detectable at a picomolar level. The reaction kinetics plays a significant role in the entire process. The kinetic aspects are also quantitatively discussed based on the levitation behavior of the PS particles in the CAG field.

Age and Visual Information Processing.

ERIC Educational Resources Information Center

Gummerman, Kent; And Others

This paper reports on three studies concerned with aspects of human visual information processing. Study I was an effort to measure the duration of iconic storage using a partial report method in children ranging in age from 6 to 13 years. Study II was designed to detect age related changes in the rate of processing (perceptually encoding) letters…

Applying Statistical Process Control to Clinical Data: An Illustration.

ERIC Educational Resources Information Center

Pfadt, Al; And Others

1992-01-01

Principles of statistical process control are applied to a clinical setting through the use of control charts to detect changes, as part of treatment planning and clinical decision-making processes. The logic of control chart analysis is derived from principles of statistical inference. Sample charts offer examples of evaluating baselines and…

A Hopfield neural network for image change detection.

PubMed

Pajares, Gonzalo

2006-09-01

This paper outlines an optimization relaxation approach based on the analog Hopfield neural network (HNN) for solving the image change detection problem between two images. A difference image is obtained by subtracting pixel by pixel both images. The network topology is built so that each pixel in the difference image is a node in the network. Each node is characterized by its state, which determines if a pixel has changed. An energy function is derived, so that the network converges to stable states. The analog Hopfield's model allows each node to take on analog state values. Unlike most widely used approaches, where binary labels (changed/unchanged) are assigned to each pixel, the analog property provides the strength of the change. The main contribution of this paper is reflected in the customization of the analog Hopfield neural network to derive an automatic image change detection approach. When a pixel is being processed, some existing image change detection procedures consider only interpixel relations on its neighborhood. The main drawback of such approaches is the labeling of this pixel as changed or unchanged according to the information supplied by its neighbors, where its own information is ignored. The Hopfield model overcomes this drawback and for each pixel allows a tradeoff between the influence of its neighborhood and its own criterion. This is mapped under the energy function to be minimized. The performance of the proposed method is illustrated by comparative analysis against some existing image change detection methods.

The development of real-time stability supports visual working memory performance: Young children's feature binding can be improved through perceptual structure.

PubMed

Simmering, Vanessa R; Wood, Chelsey M

2017-08-01

Working memory is a basic cognitive process that predicts higher-level skills. A central question in theories of working memory development is the generality of the mechanisms proposed to explain improvements in performance. Prior theories have been closely tied to particular tasks and/or age groups, limiting their generalizability. The cognitive dynamics theory of visual working memory development has been proposed to overcome this limitation. From this perspective, developmental improvements arise through the coordination of cognitive processes to meet demands of different behavioral tasks. This notion is described as real-time stability, and can be probed through experiments that assess how changing task demands impact children's performance. The current studies test this account by probing visual working memory for colors and shapes in a change detection task that compares detection of changes to new features versus swaps in color-shape binding. In Experiment 1, 3- to 4-year-old children showed impairments specific to binding swaps, as predicted by decreased real-time stability early in development; 5- to 6-year-old children showed a slight advantage on binding swaps, but 7- to 8-year-old children and adults showed no difference across trial types. Experiment 2 tested the proposed explanation of young children's binding impairment through added perceptual structure, which supported the stability and precision of feature localization in memory-a process key to detecting binding swaps. This additional structure improved young children's binding swap detection, but not new-feature detection or adults' performance. These results provide further evidence for the cognitive dynamics and real-time stability explanation of visual working memory development. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

An Investigation of Automatic Change Detection for Topographic Map Updating

NASA Astrophysics Data System (ADS)

Duncan, P.; Smit, J.

2012-08-01

Changes to the landscape are constantly occurring and it is essential for geospatial and mapping organisations that these changes are regularly detected and captured, so that map databases can be updated to reflect the current status of the landscape. The Chief Directorate of National Geospatial Information (CD: NGI), South Africa's national mapping agency, currently relies on manual methods of detecting changes and capturing these changes. These manual methods are time consuming and labour intensive, and rely on the skills and interpretation of the operator. It is therefore necessary to move towards more automated methods in the production process at CD: NGI. The aim of this research is to do an investigation into a methodology for automatic or semi-automatic change detection for the purpose of updating topographic databases. The method investigated for detecting changes is through image classification as well as spatial analysis and is focussed on urban landscapes. The major data input into this study is high resolution aerial imagery and existing topographic vector data. Initial results indicate the traditional pixel-based image classification approaches are unsatisfactory for large scale land-use mapping and that object-orientated approaches hold more promise. Even in the instance of object-oriented image classification generalization of techniques on a broad-scale has provided inconsistent results. A solution may lie with a hybrid approach of pixel and object-oriented techniques.

Noise Trauma-Induced Behavioral Gap Detection Deficits Correlate with Reorganization of Excitatory and Inhibitory Local Circuits in the Inferior Colliculus and Are Prevented by Acoustic Enrichment

PubMed Central

Zhang-Hooks, Ying-Xin; Roos, Hannah

2017-01-01

Hearing loss leads to a host of cellular and synaptic changes in auditory brain areas that are thought to give rise to auditory perception deficits such as temporal processing impairments, hyperacusis, and tinnitus. However, little is known about possible changes in synaptic circuit connectivity that may underlie these hearing deficits. Here, we show that mild hearing loss as a result of brief noise exposure leads to a pronounced reorganization of local excitatory and inhibitory circuits in the mouse inferior colliculus. The exact nature of these reorganizations correlated with the presence or absence of the animals' impairments in detecting brief sound gaps, a commonly used behavioral sign for tinnitus in animal models. Mice with gap detection deficits (GDDs) showed a shift in the balance of synaptic excitation and inhibition that was present in both glutamatergic and GABAergic neurons, whereas mice without GDDs showed stable excitation–inhibition balances. Acoustic enrichment (AE) with moderate intensity, pulsed white noise immediately after noise trauma prevented both circuit reorganization and GDDs, raising the possibility of using AE immediately after cochlear damage to prevent or alleviate the emergence of central auditory processing deficits. SIGNIFICANCE STATEMENT Noise overexposure is a major cause of central auditory processing disorders, including tinnitus, yet the changes in synaptic connectivity underlying these disorders remain poorly understood. Here, we find that brief noise overexposure leads to distinct reorganizations of excitatory and inhibitory synaptic inputs onto glutamatergic and GABAergic neurons and that the nature of these reorganizations correlates with animals' impairments in detecting brief sound gaps, which is often considered a sign of tinnitus. Acoustic enrichment immediately after noise trauma prevents circuit reorganizations and gap detection deficits, highlighting the potential for using sound therapy soon after cochlear damage to prevent the development of central processing deficits. PMID:28583912

PSO-based methods for medical image registration and change assessment of pigmented skin

NASA Astrophysics Data System (ADS)

Kacenjar, Steve; Zook, Matthew; Balint, Michael

2011-03-01

There are various scientific and technological areas in which it is imperative to rapidly detect and quantify changes in imagery over time. In fields such as earth remote sensing, aerospace systems, and medical imaging, searching for timedependent, regional changes across deformable topographies is complicated by varying camera acquisition geometries, lighting environments, background clutter conditions, and occlusion. Under these constantly-fluctuating conditions, the use of standard, rigid-body registration approaches often fail to provide sufficient fidelity to overlay image scenes together. This is problematic because incorrect assessments of the underlying changes of high-level topography can result in systematic errors in the quantification and classification of interested areas. For example, in the current naked-eye detection strategies of melanoma, a dermatologist often uses static morphological attributes to identify suspicious skin lesions for biopsy. This approach does not incorporate temporal changes which suggest malignant degeneration. By performing the co-registration of time-separated skin imagery, a dermatologist may more effectively detect and identify early morphological changes in pigmented lesions; enabling the physician to detect cancers at an earlier stage resulting in decreased morbidity and mortality. This paper describes an image processing system which will be used to detect changes in the characteristics of skin lesions over time. The proposed system consists of three main functional elements: 1.) coarse alignment of timesequenced imagery, 2.) refined alignment of local skin topographies, and 3.) assessment of local changes in lesion size. During the coarse alignment process, various approaches can be used to obtain a rough alignment, including: 1.) a manual landmark/intensity-based registration method1, and 2.) several flavors of autonomous optical matched filter methods2. These procedures result in the rough alignment of a patient's back topography. Since the skin is a deformable membrane, this process only provides an initial condition for subsequent refinements in aligning the localized topography of the skin. To achieve a refined enhancement, a Particle Swarm Optimizer (PSO) is used to optimally determine the local camera models associated with a generalized geometric transform. Here the optimization process is driven using the minimization of entropy between the multiple time-separated images. Once the camera models are corrected for local skin deformations, the images are compared using both pixel-based and regional-based methods. Limits on the detectability of change are established by the fidelity to which the algorithm corrects for local skin deformation and background alterations. These limits provide essential information in establishing early-warning thresholds for Melanoma detection. Key to this work is the development of a PSO alignment algorithm to perform the refined alignment in local skin topography between the time sequenced imagery (TSI). Test and validation of this alignment process is achieved using a forward model producing known geometric artifacts in the images and afterwards using a PSO algorithm to demonstrate the ability to identify and correct for these artifacts. Specifically, the forward model introduces local translational, rotational, and magnification changes within the image. These geometric modifiers are expected during TSI acquisition because of logistical issues to precisely align the patient to the image recording geometry and is therefore of paramount importance to any viable image registration system. This paper shows that the PSO alignment algorithm is effective in autonomously determining and mitigating these geometric modifiers. The degree of efficacy is measured by several statistically and morphologically based pre-image filtering operations applied to the TSI imagery before applying the PSO alignment algorithm. These trade studies show that global image threshold binarization provides rapid and superior convergence characteristics relative to that of morphologically based methods.

Geomorphological change detection of fluvial processes of lower Siret channel using LIDAR data

NASA Astrophysics Data System (ADS)

Niculita, Mihai; Obreja, Florin; Boca, Bogdan

2015-04-01

Geomorphological change detection is a relatively new method risen from the availability of high resolution multitemporal DEMs (James et. al., 2011; Brodu & Lague, 2012; Barnhart & Crosby, 2013). The main issue in regard with this method is the identification of real change, given by geomorphologic processes, and not by the noise, method artefacts, vegetation or various other errors (Wheaton et. al., 2009). We present the results of geomorphological change detection applied to a part of the lower Siret river channel (from 60 to 140 km above the Siret-Dunăre confluence, between Adjud and Namoloasa). The data sources used were LIDAR DEMs provided by the Siret and Prut-Barlad Water Administrations, one version for 2008, at 2 m resolution, and the other at 0.5 m resolution for 2012. The geomorphological change detection was performed at a resolution of 2 m using the methodology of Wheaton et. al., 2009, on 4 sites with a cumulated length of 47 km, with 41.6 km covering meandering channels and 5.4 km Movileni anthropic lake shore. In the studied period (2008-2012), two major flood events were registered, one in 2008 and the other in 2010 (Olariu et. al., 2009, Serbu et. al., 2009, Nedelcu et. al., 2011). The geomorphological change detection approach managed to outline the presence and the rate of process (expressed as volumetric change) for: channel erosion, channel aggradation, lateral migration of river bank, meander migration, lake bank erosion, alluvial fan deposition and anthropic excavation of channel and river bank. Barnhart T.B., Crosby B.T., 2013. Comparing Two Methods of Surface Change Detection on an Evolving Thermokarst Using High-Temporal-Frequency Terrestrial Laser Scanning, Selawik River, Alaska. Remote Sensing, 5:2813-23937. Brodu N, Lague D. 2012. 3D Terrestrial LiDAR data classification of complex natural scenes using a multi-scale dimensionality criterion: applications in geomorphology, ISPRS journal of Photogrammmetry and Remote Sensing, 68:121-134. Lague D., Brodu N., Leroux J., 2013. Accurate 3D comparison of complex topography with terrestrial laser scanner: application to the Rangitikei canyon (N-Z), ISPRS journal of Photogrammmetry and Remote Sensing, 80:10-26. James L.A., Hodgson M.E., Ghoshal S., Latiolais M.M., 2012. Geomorphic change detection using historic maps and DEM differencing: the temporal dimension of geospatial analysis. Geomorphology, 137:181-198. Nedelcu G., Borcan M., Branescu E., Petre C., Teleanu B., Preda A., Murafa R., 2011. Exceptional floods from the years 2008 and 2010 in Siret river basin, Proceedings of the Annual Scientific Conference of National Romanian Institute of Hydrology and Water Administration, 1-3 November 2011. (in Romanian) Olariu P., Obreja F., Obreja I., 2009. Some aspects regarding the sediment transit from Trotus catchment and lower sector of Siret river during the exceptional floods from 1991 and 2005, Annals of Stefan cel Mare University of Suceava, XVIII:93-104.(in Romanian) Serbu M., Obreja F., Olariu P., 2009. The 2008 floods from upper Siret catchment. Causes, effects, evaluation, Hidrotechnics, 54(12):1-38. (in Romanian) Wheaton J.M., Brasington J., Darby S., Sear D., 2009. Accounting for uncertainty in DEMs from repeat topographic surveys: improved sediment budgets. Earth Surface Processes and Landforms, 35(2):136-156.

A statistical method (cross-validation) for bone loss region detection after spaceflight

PubMed Central

Zhao, Qian; Li, Wenjun; Li, Caixia; Chu, Philip W.; Kornak, John; Lang, Thomas F.

2010-01-01

Astronauts experience bone loss after the long spaceflight missions. Identifying specific regions that undergo the greatest losses (e.g. the proximal femur) could reveal information about the processes of bone loss in disuse and disease. Methods for detecting such regions, however, remains an open problem. This paper focuses on statistical methods to detect such regions. We perform statistical parametric mapping to get t-maps of changes in images, and propose a new cross-validation method to select an optimum suprathreshold for forming clusters of pixels. Once these candidate clusters are formed, we use permutation testing of longitudinal labels to derive significant changes. PMID:20632144

Unsupervised Change Detection for Geological and Ecological Monitoring via Remote Sensing: Application on a Volcanic Area

NASA Astrophysics Data System (ADS)

Falco, N.; Pedersen, G. B. M.; Vilmunandardóttir, O. K.; Belart, J. M. M. C.; Sigurmundsson, F. S.; Benediktsson, J. A.

2016-12-01

The project "Environmental Mapping and Monitoring of Iceland by Remote Sensing (EMMIRS)" aims at providing fast and reliable mapping and monitoring techniques on a big spatial scale with a high temporal resolution of the Icelandic landscape. Such mapping and monitoring will be crucial to both mitigate and understand the scale of processes and their often complex interlinked feedback mechanisms.In the EMMIRS project, the Hekla volcano area is one of the main sites under study, where the volcanic eruptions, extreme weather and human activities had an extensive impact on the landscape degradation. The development of innovative remote sensing approaches to compute earth observation variables as automatically as possible is one of the main tasks of the EMMIRS project. Furthermore, a temporal remote sensing archive is created and composed by images acquired by different sensors (Landsat, RapidEye, ASTER and SPOT5). Moreover, historical aerial stereo photos allowed decadal reconstruction of the landscape by reconstruction of digital elevation models. Here, we propose a novel architecture for automatic unsupervised change detection analysis able to ingest multi-source data in order to detect landscape changes in the Hekla area. The change detection analysis is based on multi-scale analysis, which allows the identification of changes at different level of abstraction, from pixel-level to region-level. For this purpose, operators defined in mathematical morphology framework are implemented to model the contextual information, represented by the neighbour system of a pixel, allowing the identification of changes related to both geometrical and spectral domains. Automatic radiometric normalization strategy is also implemented as pre-processing step, aiming at minimizing the effect of different acquisition conditions. The proposed architecture is tested on multi-temporal data sets acquired over different time periods coinciding with the last three eruptions (1980-1981, 1991, 2000) occurred on Hekla volcano. The results reveal emplacement of new lava flows and the initial vegetation succession, providing insightful information on the evolving of vegetation in such environment. Shadow and snow patch changes are resolved in post-processing by exploiting the available spectral information.

Intelligent Processing of Ferroelectric Thin Films

DTIC Science & Technology

1994-05-31

unsatisfactory. To detect the electroopic effects of thin films deposited on opaque substrates a waveguide refractometry of category 3 was reported. An advantage...of the waveguide refractometry is its capability of resolving the change in ordinary index from the change in the extraordinary index. Some successes

Broad attention to multiple individual objects may facilitate change detection with complex auditory scenes.

PubMed

Irsik, Vanessa C; Vanden Bosch der Nederlanden, Christina M; Snyder, Joel S

2016-11-01

Attention and other processing constraints limit the perception of objects in complex scenes, which has been studied extensively in the visual sense. We used a change deafness paradigm to examine how attention to particular objects helps and hurts the ability to notice changes within complex auditory scenes. In a counterbalanced design, we examined how cueing attention to particular objects affected performance in an auditory change-detection task through the use of valid or invalid cues and trials without cues (Experiment 1). We further examined how successful encoding predicted change-detection performance using an object-encoding task and we addressed whether performing the object-encoding task along with the change-detection task affected performance overall (Experiment 2). Participants had more error for invalid compared to valid and uncued trials, but this effect was reduced in Experiment 2 compared to Experiment 1. When the object-encoding task was present, listeners who completed the uncued condition first had less overall error than those who completed the cued condition first. All participants showed less change deafness when they successfully encoded change-relevant compared to irrelevant objects during valid and uncued trials. However, only participants who completed the uncued condition first also showed this effect during invalid cue trials, suggesting a broader scope of attention. These findings provide converging evidence that attention to change-relevant objects is crucial for successful detection of acoustic changes and that encouraging broad attention to multiple objects is the best way to reduce change deafness. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Pitch discrimination accuracy in musicians vs nonmusicians: an event-related potential and behavioral study.

PubMed

Tervaniemi, Mari; Just, Viola; Koelsch, Stefan; Widmann, Andreas; Schröger, Erich

2005-02-01

Previously, professional violin players were found to automatically discriminate tiny pitch changes, not discriminable by nonmusicians. The present study addressed the pitch processing accuracy in musicians with expertise in playing a wide selection of instruments (e.g., piano; wind and string instruments). Of specific interest was whether also musicians with such divergent backgrounds have facilitated accuracy in automatic and/or attentive levels of auditory processing. Thirteen professional musicians and 13 nonmusicians were presented with frequent standard sounds and rare deviant sounds (0.8, 2, or 4% higher in frequency). Auditory event-related potentials evoked by these sounds were recorded while first the subjects read a self-chosen book and second they indicated behaviorally the detection of sounds with deviant frequency. Musicians detected the pitch changes faster and more accurately than nonmusicians. The N2b and P3 responses recorded during attentive listening had larger amplitude in musicians than in nonmusicians. Interestingly, the superiority in pitch discrimination accuracy in musicians over nonmusicians was observed not only with the 0.8% but also with the 2% frequency changes. Moreover, also nonmusicians detected quite reliably the smallest pitch changes of 0.8%. However, the mismatch negativity (MMN) and P3a recorded during a reading condition did not differentiate musicians and nonmusicians. These results suggest that musical expertise may exert its effects merely at attentive levels of processing and not necessarily already at the preattentive levels.

Changes in acoustic features and their conjunctions are processed by separate neuronal populations.

PubMed

Takegata, R; Huotilainen, M; Rinne, T; Näätänen, R; Winkler, I

2001-03-05

We investigated the relationship between the neuronal populations involved in detecting change in two acoustic features and their conjunction. Equivalent current dipole (ECD) models of the magnetic mismatch negativity (MMNm) generators were calculated for infrequent changes in pitch, perceived sound source location, and the conjunction of these two features. All of these three changes elicited MMNms that were generated in the vicinity of auditory cortex. The location of the ECD best describing the MMNm to the conjunction deviant was anterior to those for the MMNm responses elicited by either one of the constituent features. The present data thus suggest that at least partially separate neuronal populations are involved in detecting change in acoustic features and feature conjunctions.

Detection and Monitoring of Small-Scale Mining Operations in the Eastern Democratic Republic of the Congo (DRC) Using Multi-Temporal, Multi-Sensor Remote Sensing Data

NASA Astrophysics Data System (ADS)

Walther, Christian; Frei, Michaela

2017-04-01

Mining of so-called "conflict minerals" is often related with small-scale mining activities. The here discussed activities are located in forested areas in the eastern DRC, which are often remote, difficult to access and insecure for traditional geological field inspection. In order to accelerate their CTC (Certified Trading Chain)-certification process, remote sensing data are used for detection and monitoring of these small-scale mining operations. This requires a high image acquisition frequency due to mining site relocations and for compensation of year-round high cloud coverage, especially for optical data evaluation. Freely available medium resolution optical data of Sentinel-2 and Landsat-8 as well as SAR data of Sentinel-1 are used for detecting small mining targets with a minimum size of approximately 0.5 km2. The developed method enables a robust multi-temporal detection of mining sites, monitoring of mining site spatio-temporal relocations and environmental changes. Since qualitative and quantitative comparable results are generated, the followed change detection approach is objective and transparent and may push the certification process forward.

Candidate Electrophysiological Endophenotypes of Hyper-Reactivity to Change in Autism

ERIC Educational Resources Information Center

Gomot, Marie; Blanc, Romuald; Clery, Helen; Roux, Sylvie; Barthelemy, Catherine; Bruneau, Nicole

2011-01-01

Although resistance to change is a main feature of autism, the brain processes underlying this aspect of the disorder remain poorly understood. The aims of this study were to examine neural basis of auditory change-detection in children with autism spectrum disorders (ASD; N = 27) through electrophysiological patterns (MMN, P3a) and to test…

Online Adaboost-Based Parameterized Methods for Dynamic Distributed Network Intrusion Detection.

PubMed

Hu, Weiming; Gao, Jun; Wang, Yanguo; Wu, Ou; Maybank, Stephen

2014-01-01

Current network intrusion detection systems lack adaptability to the frequently changing network environments. Furthermore, intrusion detection in the new distributed architectures is now a major requirement. In this paper, we propose two online Adaboost-based intrusion detection algorithms. In the first algorithm, a traditional online Adaboost process is used where decision stumps are used as weak classifiers. In the second algorithm, an improved online Adaboost process is proposed, and online Gaussian mixture models (GMMs) are used as weak classifiers. We further propose a distributed intrusion detection framework, in which a local parameterized detection model is constructed in each node using the online Adaboost algorithm. A global detection model is constructed in each node by combining the local parametric models using a small number of samples in the node. This combination is achieved using an algorithm based on particle swarm optimization (PSO) and support vector machines. The global model in each node is used to detect intrusions. Experimental results show that the improved online Adaboost process with GMMs obtains a higher detection rate and a lower false alarm rate than the traditional online Adaboost process that uses decision stumps. Both the algorithms outperform existing intrusion detection algorithms. It is also shown that our PSO, and SVM-based algorithm effectively combines the local detection models into the global model in each node; the global model in a node can handle the intrusion types that are found in other nodes, without sharing the samples of these intrusion types.

VHR satellite multitemporal data to extract cultural landscape changes in the roman site of Grumentum

NASA Astrophysics Data System (ADS)

masini, nicola; Lasaponara, Rosa

2013-04-01

The papers deals with the use of VHR satellite multitemporal data set to extract cultural landscape changes in the roman site of Grumentum Grumentum is an ancient town, 50 km south of Potenza, located near the roman road of Via Herculea which connected the Venusia, in the north est of Basilicata, with Heraclea in the Ionian coast. The first settlement date back to the 6th century BC. It was resettled by the Romans in the 3rd century BC. Its urban fabric which evidences a long history from the Republican age to late Antiquity (III BC-V AD) is composed of the typical urban pattern of cardi and decumani. Its excavated ruins include a large amphitheatre, a theatre, the thermae, the Forum and some temples. There are many techniques nowadays available to capture and record differences in two or more images. In this paper we focus and apply the two main approaches which can be distinguished into : (i) unsupervised and (ii) supervised change detection methods. Unsupervised change detection methods are generally based on the transformation of the two multispectral images in to a single band or multiband image which are further analyzed to identify changes Unsupervised change detection techniques are generally based on three basic steps (i) the preprocessing step, (ii) a pixel-by-pixel comparison is performed, (iii). Identification of changes according to the magnitude an direction (positive /negative). Unsupervised change detection are generally based on the transformation of the two multispectral images into a single band or multiband image which are further analyzed to identify changes. Than the separation between changed and unchanged classes is obtained from the magnitude of the resulting spectral change vectors by means of empirical or theoretical well founded approaches Supervised change detection methods are generally based on supervised classification methods, which require the availability of a suitable training set for the learning process of the classifiers. Unsupervised change detection techniques are generally based on three basic steps (i) the preprocessing step, (ii) supervised classification is performed on the single dates or on the map obtained as the difference of two dates, (iii). Identification of changes according to the magnitude an direction (positive /negative). Supervised change detection are generally based on supervised classification methods, which require the availability of a suitable training set for the learning process of the classifiers, therefore these algorithms require a preliminary knowledge necessary: (i) to generate representative parameters for each class of interest; and (ii) to carry out the training stage Advantages and disadvantages of the supervised and unsupervised approaches are discuss. Finally results from the the satellite multitemporal dataset was also integrated with aerial photos from historical archive in order to expand the time window of the investigation and capture landscape changes occurred from the Agrarian Reform, in the 50s, up today.

Fiber optic fluid detector

DOEpatents

Angel, S.M.

1987-02-27

Particular gases or liquids are detected with a fiber optic element having a cladding or coating of a material which absorbs the fluid or fluids and which exhibits a change of an optical property, such as index of refraction, light transmissiveness or fluoresence emission, for example, in response to absorption of the fluid. The fluid is sensed by directing light into the fiber optic element and detecting changes in the light, such as exit angle changes for example, that result from the changed optical property of the coating material. The fluid detector may be used for such purposes as sensing toxic or explosive gases in the atmosphere, measuring ground water contamination or monitoring fluid flows in industrial processes, among other uses. 10 figs.

Electrification processes and lightning generation in volcanic plumes—observations from recent eruptions

NASA Astrophysics Data System (ADS)

Van Eaton, A. R.; Smith, C. M.; Schneider, D. J.

2017-12-01

Lightning in volcanic plumes provides a promising way to monitor ash-producing eruptions and investigate their dynamics. Among the many methods of lightning detection are global networks of sensors that detect electromagnetic radiation in the very low frequency band (3-30 kHz), including the World Wide Lightning Location Network. These radio waves propagate thousands of kilometers at the speed of light, providing an opportunity for rapid detection of explosive volcanism anywhere in the world. Lightning is particularly valuable as a near real-time indicator of ash-rich plumes that are hazardous to aviation. Yet many fundamental questions remain. Under what conditions does electrical activity in volcanic plumes become powerful, detectable lightning? And conversely, can we use lightning to illuminate eruption processes and hazards? This study highlights recent observations from the eruptions of Redoubt (Alaska, 2009), Kelud (Indonesia, 2014), Calbuco (Chile, 2015), and Bogoslof (Alaska, 2017) to examine volcanic lighting from a range of eruption styles (Surtseyan to Plinian) and mass eruption rates from 10^5 to 10^8 kg/s. It is clear that lightning stroke-rates do not scale in a simple way with mass eruption rate or plume height across different eruptions. However, relative changes in electrical activity through individual eruptions relate to changes in eruptive intensity, ice content, and volcanic plume processes (fall vs. flow).

Time Series UAV Image-Based Point Clouds for Landslide Progression Evaluation Applications

PubMed Central

Moussa, Adel; El-Sheimy, Naser; Habib, Ayman

2017-01-01

Landslides are major and constantly changing threats to urban landscapes and infrastructure. It is essential to detect and capture landslide changes regularly. Traditional methods for monitoring landslides are time-consuming, costly, dangerous, and the quality and quantity of the data is sometimes unable to meet the necessary requirements of geotechnical projects. This motivates the development of more automatic and efficient remote sensing approaches for landslide progression evaluation. Automatic change detection involving low-altitude unmanned aerial vehicle image-based point clouds, although proven, is relatively unexplored, and little research has been done in terms of accounting for volumetric changes. In this study, a methodology for automatically deriving change displacement rates, in a horizontal direction based on comparisons between extracted landslide scarps from multiple time periods, has been developed. Compared with the iterative closest projected point (ICPP) registration method, the developed method takes full advantage of automated geometric measuring, leading to fast processing. The proposed approach easily processes a large number of images from different epochs and enables the creation of registered image-based point clouds without the use of extensive ground control point information or further processing such as interpretation and image correlation. The produced results are promising for use in the field of landslide research. PMID:29057847

Time Series UAV Image-Based Point Clouds for Landslide Progression Evaluation Applications.

PubMed

Al-Rawabdeh, Abdulla; Moussa, Adel; Foroutan, Marzieh; El-Sheimy, Naser; Habib, Ayman

2017-10-18

Landslides are major and constantly changing threats to urban landscapes and infrastructure. It is essential to detect and capture landslide changes regularly. Traditional methods for monitoring landslides are time-consuming, costly, dangerous, and the quality and quantity of the data is sometimes unable to meet the necessary requirements of geotechnical projects. This motivates the development of more automatic and efficient remote sensing approaches for landslide progression evaluation. Automatic change detection involving low-altitude unmanned aerial vehicle image-based point clouds, although proven, is relatively unexplored, and little research has been done in terms of accounting for volumetric changes. In this study, a methodology for automatically deriving change displacement rates, in a horizontal direction based on comparisons between extracted landslide scarps from multiple time periods, has been developed. Compared with the iterative closest projected point (ICPP) registration method, the developed method takes full advantage of automated geometric measuring, leading to fast processing. The proposed approach easily processes a large number of images from different epochs and enables the creation of registered image-based point clouds without the use of extensive ground control point information or further processing such as interpretation and image correlation. The produced results are promising for use in the field of landslide research.

Implication of relationship between natural impacts and land use/land cover (LULC) changes of urban area in Mongolia

NASA Astrophysics Data System (ADS)

Gantumur, Byambakhuu; Wu, Falin; Zhao, Yan; Vandansambuu, Battsengel; Dalaibaatar, Enkhjargal; Itiritiphan, Fareda; Shaimurat, Dauryenbyek

2017-10-01

Urban growth can profoundly alter the urban landscape structure, ecosystem processes, and local climates. Timely and accurate information on the status and trends of urban ecosystems is critical to develop strategies for sustainable development and to improve the urban residential environment and living quality. Ulaanbaatar city was urbanized very rapidly caused by herders and farmers, many of them migrating from rural places, have played a big role in this urban expansion (sprawl). Today, 1.3 million residents for about 40% of total population are living in the Ulaanbaatar region. Those human activities influenced stronger to green environments. Therefore, the aim of this study is determined to change detection of land use/land cover (LULC) and estimating their areas for the trend of future by remote sensing and statistical methods. The implications of analysis were provided by change detection methods of LULC, remote sensing spectral indices including normalized difference vegetation index (NDVI), normalized difference water index (NDWI) and normalized difference built-up index (NDBI). In addition, it can relate to urban heat island (UHI) provided by Land surface temperature (LST) with local climate issues. Statistical methods for image processing used to define relations between those spectral indices and change detection images and regression analysis for time series trend in future. Remote sensing data are used by Landsat (TM/ETM+/OLI) satellite images over the period between 1990 and 2016 by 5 years. The advantages of this study are very useful remote sensing approaches with statistical analysis and important to detecting changes of LULC. The experimental results show that the LULC changes can image on the present and after few years and determined relations between impacts of environmental conditions.

A novelty detection diagnostic methodology for gearboxes operating under fluctuating operating conditions using probabilistic techniques

NASA Astrophysics Data System (ADS)

Schmidt, S.; Heyns, P. S.; de Villiers, J. P.

2018-02-01

In this paper, a fault diagnostic methodology is developed which is able to detect, locate and trend gear faults under fluctuating operating conditions when only vibration data from a single transducer, measured on a healthy gearbox are available. A two-phase feature extraction and modelling process is proposed to infer the operating condition and based on the operating condition, to detect changes in the machine condition. Information from optimised machine and operating condition hidden Markov models are statistically combined to generate a discrepancy signal which is post-processed to infer the condition of the gearbox. The discrepancy signal is processed and combined with statistical methods for automatic fault detection and localisation and to perform fault trending over time. The proposed methodology is validated on experimental data and a tacholess order tracking methodology is used to enhance the cost-effectiveness of the diagnostic methodology.

Method of evaluating, expanding, and collapsing connectivity regions within dynamic systems

DOEpatents

Bailey, David A [Schenectady, NY

2004-11-16

An automated process defines and maintains connectivity regions within a dynamic network. The automated process requires an initial input of a network component around which a connectivity region will be defined. The process automatically and autonomously generates a region around the initial input, stores the region's definition, and monitors the network for a change. Upon detecting a change in the network, the effect is evaluated, and if necessary the regions are adjusted and redefined to accommodate the change. Only those regions of the network affected by the change will be updated. This process eliminates the need for an operator to manually evaluate connectivity regions within a network. Since the automated process maintains the network, the reliance on an operator is minimized; thus, reducing the potential for operator error. This combination of region maintenance and reduced operator reliance, results in a reduction of overall error.

Late Pleistocene - Holocene surface processes and landscape evolution in the central Swiss Alps

NASA Astrophysics Data System (ADS)

Boxleitner, Max; Musso, Alessandra; Waroszewski, Jarosław; Malkiewicz, Małgorzata; Maisch, Max; Dahms, Dennis; Brandová, Dagmar; Christl, Marcus; de Castro Portes, Raquel; Egli, Markus

2017-10-01

The European Alps are a geomorphologically active region and experience a number of gravity-driven hillslope processes. Soil and landscape formation in the Alps has consequently undergone several minor and major traceable changes of developmental trajectories during the Holocene. Soil development is hypothesised to be often non-linear with time and characterised by stages of progressive and regressive evolution caused by upbuilding (formation, profile deepening) and erosion (profile shallowing). Several cold and warm climate phases are identified during the Holocene but it is largely unknown which effects these might have had on slope processes. By using datable moraines (10Be) and mires (14C), we have constructed a temporal framework for these processes. Using the geochemical imprint of mires in the Alpine setting of the Göschener-valley of the Central Swiss Alps, we reconstructed general (mostly erosional) landscape processes for the last ca. 10 ka. As this is the type locality for the Göschener cold phase, we assumed that this phase (Göschener cold phase I and II 1.5 and 2.5 ka BP) should have left easily recognizable traits. After deglaciation (11-12 ka BP), soil evolution was progressive. Beginning around 8 ka BP, we detect a distinct increase in erosion here, together with a vegetation change (towards tundra vegetation) and the highest measured rates of carbon sequestration. Other phases of high geomorphic activity were recognised ca. 5-6 ka BP, 4 ka BP and, to a lesser extent, 1-3 ka ago. The cold phase at 5-6 ka BP corresponds to a less distinct change in vegetation and lessened erosion. Human impact is increasingly obvious since about 2.4 ka BP which overlaps with the Göschener cold phase. Nonetheless, erosion processes were not extraordinarily high during this period and a climate effect cannot be distinguished. We detect evidence of increasing human disturbance (regressive soil evolution) for about the last 1 ka. We also detect an increase in dust flux during the last ca. 4-5 ka, presumably due to the landscape change(s) in the Sahara during this time.

Modelling spatiotemporal change using multidimensional arrays Meng

NASA Astrophysics Data System (ADS)

Lu, Meng; Appel, Marius; Pebesma, Edzer

2017-04-01

The large variety of remote sensors, model simulations, and in-situ records provide great opportunities to model environmental change. The massive amount of high-dimensional data calls for methods to integrate data from various sources and to analyse spatiotemporal and thematic information jointly. An array is a collection of elements ordered and indexed in arbitrary dimensions, which naturally represent spatiotemporal phenomena that are identified by their geographic locations and recording time. In addition, array regridding (e.g., resampling, down-/up-scaling), dimension reduction, and spatiotemporal statistical algorithms are readily applicable to arrays. However, the role of arrays in big geoscientific data analysis has not been systematically studied: How can arrays discretise continuous spatiotemporal phenomena? How can arrays facilitate the extraction of multidimensional information? How can arrays provide a clean, scalable and reproducible change modelling process that is communicable between mathematicians, computer scientist, Earth system scientist and stakeholders? This study emphasises on detecting spatiotemporal change using satellite image time series. Current change detection methods using satellite image time series commonly analyse data in separate steps: 1) forming a vegetation index, 2) conducting time series analysis on each pixel, and 3) post-processing and mapping time series analysis results, which does not consider spatiotemporal correlations and ignores much of the spectral information. Multidimensional information can be better extracted by jointly considering spatial, spectral, and temporal information. To approach this goal, we use principal component analysis to extract multispectral information and spatial autoregressive models to account for spatial correlation in residual based time series structural change modelling. We also discuss the potential of multivariate non-parametric time series structural change methods, hierarchical modelling, and extreme event detection methods to model spatiotemporal change. We show how array operations can facilitate expressing these methods, and how the open-source array data management and analytics software SciDB and R can be used to scale the process and make it easily reproducible.

Optics-Only Calibration of a Neural-Net Based Optical NDE Method for Structural Health Monitoring

NASA Technical Reports Server (NTRS)

Decker, Arthur J.

2004-01-01

A calibration process is presented that uses optical measurements alone to calibrate a neural-net based NDE method. The method itself detects small changes in the vibration mode shapes of structures. The optics-only calibration process confirms previous work that the sensitivity to vibration-amplitude changes can be as small as 10 nanometers. A more practical value in an NDE service laboratory is shown to be 50 nanometers. Both model-generated and experimental calibrations are demonstrated using two implementations of the calibration technique. The implementations are based on previously published demonstrations of the NDE method and an alternative calibration procedure that depends on comparing neural-net and point sensor measurements. The optics-only calibration method, unlike the alternative method, does not require modifications of the structure being tested or the creation of calibration objects. The calibration process can be used to test improvements in the NDE process and to develop a vibration-mode-independence of damagedetection sensitivity. The calibration effort was intended to support NASA s objective to promote safety in the operations of ground test facilities or aviation safety, in general, by allowing the detection of the gradual onset of structural changes and damage.

Single-molecule detection of dihydroazulene photo-thermal reaction using break junction technique

NASA Astrophysics Data System (ADS)

Huang, Cancan; Jevric, Martyn; Borges, Anders; Olsen, Stine T.; Hamill, Joseph M.; Zheng, Jue-Ting; Yang, Yang; Rudnev, Alexander; Baghernejad, Masoud; Broekmann, Peter; Petersen, Anne Ugleholdt; Wandlowski, Thomas; Mikkelsen, Kurt V.; Solomon, Gemma C.; Brøndsted Nielsen, Mogens; Hong, Wenjing

2017-05-01

Charge transport by tunnelling is one of the most ubiquitous elementary processes in nature. Small structural changes in a molecular junction can lead to significant difference in the single-molecule electronic properties, offering a tremendous opportunity to examine a reaction on the single-molecule scale by monitoring the conductance changes. Here, we explore the potential of the single-molecule break junction technique in the detection of photo-thermal reaction processes of a photochromic dihydroazulene/vinylheptafulvene system. Statistical analysis of the break junction experiments provides a quantitative approach for probing the reaction kinetics and reversibility, including the occurrence of isomerization during the reaction. The product ratios observed when switching the system in the junction does not follow those observed in solution studies (both experiment and theory), suggesting that the junction environment was perturbing the process significantly. This study opens the possibility of using nano-structured environments like molecular junctions to tailor product ratios in chemical reactions.

On the Role of Urban and Vegetative Land Cover in the Identification of Tornado Damage Using Dual-Resolution Multispectral Satellite Imagery

NASA Astrophysics Data System (ADS)

Kingfield, D.; de Beurs, K.

2014-12-01

It has been demonstrated through various case studies that multispectral satellite imagery can be utilized in the identification of damage caused by a tornado through the change detection process. This process involves the difference in returned surface reflectance between two images and is often summarized through a variety of ratio-based vegetation indices (VIs). Land cover type plays a large contributing role in the change detection process as the reflectance properties of vegetation can vary based on several factors (e.g. species, greenness, density). Consequently, this provides the possibility for a variable magnitude of loss, making certain land cover regimes less reliable in the damage identification process. Furthermore, the tradeoff between sensor resolution and orbital return period may also play a role in the ability to detect catastrophic loss. Moderate resolution imagery (e.g. Moderate Resolution Imaging Spectroradiometer (MODIS)) provides relatively coarse surface detail with a higher update rate which could hinder the identification of small regions that underwent a dynamic change. Alternatively, imagery with higher spatial resolution (e.g. Landsat) have a longer temporal return period between successive images which could result in natural recovery underestimating the absolute magnitude of damage incurred. This study evaluates the role of land cover type and sensor resolution on four high-end (EF3+) tornado events occurring in four different land cover groups (agriculture, forest, grassland, urban) in the spring season. The closest successive clear images from both Landsat 5 and MODIS are quality controlled for each case. Transacts of surface reflectance across a homogenous land cover type both inside and outside the damage swath are extracted. These metrics are synthesized through the calculation of six different VIs to rank the calculated change metrics by land cover type, sensor resolution and VI.

Comparison of the sensitivity to change of the Functional Independence Measure with the Assessment of Motor and Process Skills within different rehabilitation populations.

PubMed

Choo, Silvana X; Stratford, Paul; Richardson, Julie; Bosch, Jackie; Pettit, Susan M; Ansley, Barbara J; Harris, Jocelyn E

2017-09-10

To determine whether there was a difference in the sensitivity to change of the subscales of the Functional Independence Measure and the Assessment of Motor and Process Skills within three different post-acute inpatient rehabilitation populations. We conducted retrospective chart review of patients consecutively admitted to inpatient rehabilitation units, with both admission and discharge Functional Independence Measure and Assessment of Motor and Process Skills scores. A total of 276 participants were included and categorized into diagnostic groups (orthopedic, oncology, and geriatric). Within group, sensitivity to change was evaluated for the subscales of each measure by calculating the difference in standardized response means (SRM) and 95% confidence intervals (CI). The Functional Independence Measure motor subscale was more sensitive to change than the Assessment of Motor and Process Skills in the orthopedic and geriatric groups (SRM difference  = 1.53 [95% CI 0.93, 2.3] and 0.65 [95% CI 0.3, 1.02], respectively) but not in the oncology group (SRM difference  = 0.42 [95% CI -0.2, 1.04]). For the cognitive subscales, the Assessment of Motor and Process Skills was more sensitive to change than the Functional Independence Measure in all three groups (SRM difference  = 0.38 [95% CI 004, 0.74], 0.65 [95% CI 0.45, 0.90], and 1.15 [95% CI 0.77, 1.69] for orthopedic, geriatric, and oncology, respectively). The Functional Independence Measure is a mandated measure for all rehabilitation units in Canada. As the cognitive subscale of the Assessment of Motor and Process Skills is more sensitive to change than the Functional Independence Measure, we recommend also administering the Assessment of Motor and Process Skills to better detect changes in the cognitive aspect of function. Implications for rehabilitation When deciding between the Functional Independence Measure or the Assessment of Motor and Process Skills, it is important to consider whether patients' functional status is expected to change similarly or differently. The difference in sensitivity to change between the subscales of the two outcome measures varies with the characteristics of change (similar or different) in patients' functional status. We recommend using the Assessment of Motor and Process Skills, along with the Functional Independence Measure, for patients who are expected to make similar amounts of change in functional status, as the cognitive subscale of the Assessment of Motor and Process Skills is more sensitive to change and can better detect changes in the cognitive aspect of functioning. For patients whose functional status are expected to change differently (diverse diagnoses), the Functional Independence Measure may be more useful as the motor subscale was more sensitive to change when comparing between rehabilitation populations.

Change detection of medical images using dictionary learning techniques and principal component analysis.

PubMed

Nika, Varvara; Babyn, Paul; Zhu, Hongmei

2014-07-01

Automatic change detection methods for identifying the changes of serial MR images taken at different times are of great interest to radiologists. The majority of existing change detection methods in medical imaging, and those of brain images in particular, include many preprocessing steps and rely mostly on statistical analysis of magnetic resonance imaging (MRI) scans. Although most methods utilize registration software, tissue classification remains a difficult and overwhelming task. Recently, dictionary learning techniques are being used in many areas of image processing, such as image surveillance, face recognition, remote sensing, and medical imaging. We present an improved version of the EigenBlockCD algorithm, named the EigenBlockCD-2. The EigenBlockCD-2 algorithm performs an initial global registration and identifies the changes between serial MR images of the brain. Blocks of pixels from a baseline scan are used to train local dictionaries to detect changes in the follow-up scan. We use PCA to reduce the dimensionality of the local dictionaries and the redundancy of data. Choosing the appropriate distance measure significantly affects the performance of our algorithm. We examine the differences between [Formula: see text] and [Formula: see text] norms as two possible similarity measures in the improved EigenBlockCD-2 algorithm. We show the advantages of the [Formula: see text] norm over the [Formula: see text] norm both theoretically and numerically. We also demonstrate the performance of the new EigenBlockCD-2 algorithm for detecting changes of MR images and compare our results with those provided in the recent literature. Experimental results with both simulated and real MRI scans show that our improved EigenBlockCD-2 algorithm outperforms the previous methods. It detects clinical changes while ignoring the changes due to the patient's position and other acquisition artifacts.

Development of compact slip detection sensor using dielectric elastomer

NASA Astrophysics Data System (ADS)

Choi, Jae-young; Hwang, Do-Yeon; Kim, Baek-chul; Moon, Hyungpil; Choi, Hyouk Ryeol; Koo, Ja Choon

2015-04-01

In this paper, we developed a resistance tactile sensor that can detect a slip on the surface of sensor structure. The presented sensor device has fingerprint-like structures that are similar with the role of the humans finger print. The resistance slip sensor that the novel developed uses acrylo-nitrile butadiene rubber (NBR) as a dielectric substrate and graphene as an electrode material. We can measure the slip as the structure of sensor makes a deformation and it changes the resistance through forming a new conductive route. To manufacture our sensor, we developed a new imprint process. By using this process, we can produce sensor with micro unit structure. To verify effectiveness of the proposed slip detection, experiment using prototype of resistance slip sensor is conducted with an algorithm to detect slip and slip is successfully detected. We will discuss the slip detection properties.

Detecting regional patterns of changing CO2 flux in Alaska

PubMed Central

Parazoo, Nicholas C.; Wofsy, Steven C.; Koven, Charles D.; Sweeney, Colm; Lawrence, David M.; Lindaas, Jakob; Chang, Rachel Y.-W.; Miller, Charles E.

2016-01-01

With rapid changes in climate and the seasonal amplitude of carbon dioxide (CO2) in the Arctic, it is critical that we detect and quantify the underlying processes controlling the changing amplitude of CO2 to better predict carbon cycle feedbacks in the Arctic climate system. We use satellite and airborne observations of atmospheric CO2 with climatically forced CO2 flux simulations to assess the detectability of Alaskan carbon cycle signals as future warming evolves. We find that current satellite remote sensing technologies can detect changing uptake accurately during the growing season but lack sufficient cold season coverage and near-surface sensitivity to constrain annual carbon balance changes at regional scale. Airborne strategies that target regular vertical profile measurements within continental interiors are more sensitive to regional flux deeper into the cold season but currently lack sufficient spatial coverage throughout the entire cold season. Thus, the current CO2 observing network is unlikely to detect potentially large CO2 sources associated with deep permafrost thaw and cold season respiration expected over the next 50 y. Although continuity of current observations is vital, strategies and technologies focused on cold season measurements (active remote sensing, aircraft, and tall towers) and systematic sampling of vertical profiles across continental interiors over the full annual cycle are required to detect the onset of carbon release from thawing permafrost. PMID:27354511

Detecting regional patterns of changing CO 2 flux in Alaska

DOE PAGES

Parazoo, Nicholas C.; Commane, Roisin; Wofsy, Steven C.; ...

2016-06-27

With rapid changes in climate and the seasonal amplitude of carbon dioxide (CO 2) in the Arctic, it is critical that we detect and quantify the underlying processes controlling the changing amplitude of CO 2 to better predict carbon cycle feedbacks in the Arctic climate system. We use satellite and airborne observations of atmospheric CO 2 with climatically forced CO 2 flux simulations to assess the detectability of Alaskan carbon cycle signals as future warming evolves. We find that current satellite remote sensing technologies can detect changing uptake accurately during the growing season but lack sufficient cold season coverage andmore » near-surface sensitivity to constrain annual carbon balance changes at regional scale. Airborne strategies that target regular vertical profile measurements within continental interiors are more sensitive to regional flux deeper into the cold season but currently lack sufficient spatial coverage throughout the entire cold season. Thus, the current CO 2 observing network is unlikely to detect potentially large CO 2 sources associated with deep permafrost thaw and cold season respiration expected over the next 50 y. In conclusion, although continuity of current observations is vital, strategies and technologies focused on cold season measurements (active remote sensing, aircraft, and tall towers) and systematic sampling of vertical profiles across continental interiors over the full annual cycle are required to detect the onset of carbon release from thawing permafrost.« less

An Efficient High-performance Liquid Chromatography Combined with Electrospray Ionization Tandem Mass Spectrometry Method to Elaborate the Changes of Components Between the Raw and Processed Radix Aconitum kusnezoffii

PubMed Central

Wang, Beibei; Ji, Jiaojiao; Zhao, Shuang; Dong, Jie; Tan, Peng; Na, Shengsang; Liu, Yonggang

2016-01-01

Background: Crude radix Aconitum kusnezoffii (RAK) has great toxicity. Traditional Chinese medicine practice proved that processing may decrease its toxicity. In our previous study, we had established a new method of RAK processing (Paozhi). However, the mechanism is yet not perfect. Objective: To explore the related mechanism of processing through comparing the chemical contents. Materials and Methods: A new processing method of RAK named stoving (Hong Zhi) was used. In particular, RAK was stored at 110°C for 8 h, and then high performance liquid chromatography combined with electrospray ionization tandem mass spectrometry (HPLC-ESI-MSn) was developed for the detection of the alkaloids of the crude and processed RAK decoction pieces. Results: Thirty components of the crude RAK were discovered, among which, 23 alkaloids were identified. Meanwhile, 23 ingredients were detected in the processed RAK decoction pieces, among which, 20 alkaloids were determined yet. By comparison, eight alkaloids were found in both crude and processed RAK decoction pieces, 15 alkaloids were not found in the crude RAK, however, 10 new constituents yield after processing, which are 10-OH-hypaconine, 10-OH-mesaconine, isomer of bullatine A, 14-benzoyl-10-OH-mesaconine, 14-benzoyl-10-OH-aconine, 14-benzoyl-10-OH-hypaconine, dehydrated aconitine, 14-benzoylaconine, chuanfumine, dehydrated mesaconitine. Conclusion: The present study showed that significant change of alkaloids was detected in RAK before and after processing. Among them, the highly toxic diester alkaloids decreased and the less toxic monoester alkaloids increased. Moreover, the concentration changes significantly. HPLC-ESI-MSn are Efficient to elaborate the mechanism of reduction of toxicity and enhancement efficacy after processing. SUMMARY Stoving is a simple and effective method for the processing of radix Aconitum kusnezoffii.In the positive mode, the characteristic fragmentations of Aconitum alkaloids were obtained.The highly toxic alkaloids have decreased, and the new constituents appeared, which has explained successfully the processing mechanism of radix Aconitum kusnezoffii in chemistry. PMID:27019554

Single-trial lie detection using a combined fNIRS-polygraph system

PubMed Central

Bhutta, M. Raheel; Hong, Melissa J.; Kim, Yun-Hee; Hong, Keum-Shik

2015-01-01

Deception is a human behavior that many people experience in daily life. It involves complex neuronal activities in addition to several physiological changes in the body. A polygraph, which can measure some of the physiological responses from the body, has been widely employed in lie-detection. Many researchers, however, believe that lie detection can become more precise if the neuronal changes that occur in the process of deception can be isolated and measured. In this study, we combine both measures (i.e., physiological and neuronal changes) for enhanced lie-detection. Specifically, to investigate the deception-related hemodynamic response, functional near-infrared spectroscopy (fNIRS) is applied at the prefrontal cortex besides a commercially available polygraph system. A mock crime scenario with a single-trial stimulus is set up as a deception protocol. The acquired data are classified into “true” and “lie” classes based on the fNIRS-based hemoglobin-concentration changes and polygraph-based physiological signal changes. Linear discriminant analysis is utilized as a classifier. The results indicate that the combined fNIRS-polygraph system delivers much higher classification accuracy than that of a singular system. This study demonstrates a plausible solution toward single-trial lie-detection by combining fNIRS and the polygraph. PMID:26082733

Anomaly Detection in Dynamic Networks

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

Turcotte, Melissa

2014-10-14

Anomaly detection in dynamic communication networks has many important security applications. These networks can be extremely large and so detecting any changes in their structure can be computationally challenging; hence, computationally fast, parallelisable methods for monitoring the network are paramount. For this reason the methods presented here use independent node and edge based models to detect locally anomalous substructures within communication networks. As a first stage, the aim is to detect changes in the data streams arising from node or edge communications. Throughout the thesis simple, conjugate Bayesian models for counting processes are used to model these data streams. Amore » second stage of analysis can then be performed on a much reduced subset of the network comprising nodes and edges which have been identified as potentially anomalous in the first stage. The first method assumes communications in a network arise from an inhomogeneous Poisson process with piecewise constant intensity. Anomaly detection is then treated as a changepoint problem on the intensities. The changepoint model is extended to incorporate seasonal behavior inherent in communication networks. This seasonal behavior is also viewed as a changepoint problem acting on a piecewise constant Poisson process. In a static time frame, inference is made on this extended model via a Gibbs sampling strategy. In a sequential time frame, where the data arrive as a stream, a novel, fast Sequential Monte Carlo (SMC) algorithm is introduced to sample from the sequence of posterior distributions of the change points over time. A second method is considered for monitoring communications in a large scale computer network. The usage patterns in these types of networks are very bursty in nature and don’t fit a Poisson process model. For tractable inference, discrete time models are considered, where the data are aggregated into discrete time periods and probability models are fitted to the communication counts. In a sequential analysis, anomalous behavior is then identified from outlying behavior with respect to the fitted predictive probability models. Seasonality is again incorporated into the model and is treated as a changepoint model on the transition probabilities of a discrete time Markov process. Second stage analytics are then developed which combine anomalous edges to identify anomalous substructures in the network.« less

Bridging consciousness and cognition in memory and perception: evidence for both state and strength processes.

PubMed

Aly, Mariam; Yonelinas, Andrew P

2012-01-01

Subjective experience indicates that mental states are discrete, in the sense that memories and perceptions readily come to mind in some cases, but are entirely unavailable to awareness in others. However, a long history of psychophysical research has indicated that the discrete nature of mental states is largely epiphenomenal and that mental processes vary continuously in strength. We used a novel combination of behavioral methodologies to examine the processes underlying perception of complex images: (1) analysis of receiver operating characteristics (ROCs), (2) a modification of the change-detection flicker paradigm, and (3) subjective reports of conscious experience. These methods yielded converging results showing that perceptual judgments reflect the combined, yet functionally independent, contributions of two processes available to conscious experience: a state process of conscious perception and a strength process of knowing; processes that correspond to recollection and familiarity in long-term memory. In addition, insights from the perception experiments led to the discovery of a new recollection phenomenon in a long-term memory change detection paradigm. The apparent incompatibility between subjective experience and theories of cognition can be understood within a unified state-strength framework that links consciousness to cognition across the domains of perception and memory.

Bridging Consciousness and Cognition in Memory and Perception: Evidence for Both State and Strength Processes

PubMed Central

Aly, Mariam; Yonelinas, Andrew P.

2012-01-01

Subjective experience indicates that mental states are discrete, in the sense that memories and perceptions readily come to mind in some cases, but are entirely unavailable to awareness in others. However, a long history of psychophysical research has indicated that the discrete nature of mental states is largely epiphenomenal and that mental processes vary continuously in strength. We used a novel combination of behavioral methodologies to examine the processes underlying perception of complex images: (1) analysis of receiver operating characteristics (ROCs), (2) a modification of the change-detection flicker paradigm, and (3) subjective reports of conscious experience. These methods yielded converging results showing that perceptual judgments reflect the combined, yet functionally independent, contributions of two processes available to conscious experience: a state process of conscious perception and a strength process of knowing; processes that correspond to recollection and familiarity in long-term memory. In addition, insights from the perception experiments led to the discovery of a new recollection phenomenon in a long-term memory change detection paradigm. The apparent incompatibility between subjective experience and theories of cognition can be understood within a unified state-strength framework that links consciousness to cognition across the domains of perception and memory. PMID:22272314

Dimension-based attention in visual short-term memory.

PubMed

Pilling, Michael; Barrett, Doug J K

2016-07-01

We investigated how dimension-based attention influences visual short-term memory (VSTM). This was done through examining the effects of cueing a feature dimension in two perceptual comparison tasks (change detection and sameness detection). In both tasks, a memory array and a test array consisting of a number of colored shapes were presented successively, interleaved by a blank interstimulus interval (ISI). In Experiment 1 (change detection), the critical event was a feature change in one item across the memory and test arrays. In Experiment 2 (sameness detection), the critical event was the absence of a feature change in one item across the two arrays. Auditory cues indicated the feature dimension (color or shape) of the critical event with 80 % validity; the cues were presented either prior to the memory array, during the ISI, or simultaneously with the test array. In Experiment 1, the cue validity influenced sensitivity only when the cue was given at the earliest position; in Experiment 2, the cue validity influenced sensitivity at all three cue positions. We attributed the greater effectiveness of top-down guidance by cues in the sameness detection task to the more active nature of the comparison process required to detect sameness events (Hyun, Woodman, Vogel, Hollingworth, & Luck, Journal of Experimental Psychology: Human Perception and Performance, 35; 1140-1160, 2009).

Low-cost label-free electrical detection of artificial DNA nanostructures using solution-processed oxide thin-film transistors.

PubMed

Kim, Si Joon; Jung, Joohye; Lee, Keun Woo; Yoon, Doo Hyun; Jung, Tae Soo; Dugasani, Sreekantha Reddy; Park, Sung Ha; Kim, Hyun Jae

2013-11-13

A high-sensitivity, label-free method for detecting deoxyribonucleic acid (DNA) using solution-processed oxide thin-film transistors (TFTs) was developed. Double-crossover (DX) DNA nanostructures with different concentrations of divalent Cu ion (Cu(2+)) were immobilized on an In-Ga-Zn-O (IGZO) back-channel surface, which changed the electrical performance of the IGZO TFTs. The detection mechanism of the IGZO TFT-based DNA biosensor is attributed to electron trapping and electrostatic interactions caused by negatively charged phosphate groups on the DNA backbone. Furthermore, Cu(2+) in DX DNA nanostructures generates a current path when a gate bias is applied. The direct effect on the electrical response implies that solution-processed IGZO TFTs could be used to realize low-cost and high-sensitivity DNA biosensors.

Wavelet-based higher-order neural networks for mine detection in thermal IR imagery

NASA Astrophysics Data System (ADS)

Baertlein, Brian A.; Liao, Wen-Jiao

2000-08-01

An image processing technique is described for the detection of miens in RI imagery. The proposed technique is based on a third-order neural network, which processes the output of a wavelet packet transform. The technique is inherently invariant to changes in signature position, rotation and scaling. The well-known memory limitations that arise with higher-order neural networks are addressed by (1) the data compression capabilities of wavelet packets, (2) protections of the image data into a space of similar triangles, and (3) quantization of that 'triangle space'. Using these techniques, image chips of size 28 by 28, which would require 0(109) neural net weights, are processed by a network having 0(102) weights. ROC curves are presented for mine detection in real and simulated imagery.

Application of Ensemble Detection and Analysis to Modeling Uncertainty in Non Stationary Process

NASA Technical Reports Server (NTRS)

Racette, Paul

2010-01-01

Characterization of non stationary and nonlinear processes is a challenge in many engineering and scientific disciplines. Climate change modeling and projection, retrieving information from Doppler measurements of hydrometeors, and modeling calibration architectures and algorithms in microwave radiometers are example applications that can benefit from improvements in the modeling and analysis of non stationary processes. Analyses of measured signals have traditionally been limited to a single measurement series. Ensemble Detection is a technique whereby mixing calibrated noise produces an ensemble measurement set. The collection of ensemble data sets enables new methods for analyzing random signals and offers powerful new approaches to studying and analyzing non stationary processes. Derived information contained in the dynamic stochastic moments of a process will enable many novel applications.

Evaluation on levels and conversion profiles of DON, 3-ADON, and 15-ADON during bread making process.

PubMed

Wu, Li; Wang, Bujun

2015-10-15

The present study investigated the changes and conversion profiles of DON, its conjugations 3-ADON, and 15-ADON during bread making process, by spiking targeted mycotoxin standards to Fusarium mycotoxins-free wheat flour. No significant (p < 0.05) changes of DON levels were observed during dough preparation stages, including kneading, fermentation, and proofing. A reduction of DON level ranged from 4% to 14% was observed during baking process. The main thermal degradation products of DON, namely norDON A, B, C, and F were detected in the bread crust. Regarding ADONs, decreases of 20-40% for 3-ADON and 28-60% for 15-ADON were found during fermentation stage, and further losses of ADONs were observed after proofing process. Although ADONs levels gained an increase after baking. This study demonstrated that ADONs were converted to DON, while no ADONs were detectable in DON spiked samples during bread making process. The mechanism that ADONs could be converted into DON is unclear so far. Copyright © 2015. Published by Elsevier Ltd.

LWIR hyperspectral change detection for target acquisition and situation awareness in urban areas

NASA Astrophysics Data System (ADS)

Dekker, Rob J.; Schwering, Piet B. W.; Benoist, Koen W.; Pignatti, Stefano; Santini, Federico; Friman, Ola

2013-05-01

This paper studies change detection of LWIR (Long Wave Infrared) hyperspectral imagery. Goal is to improve target acquisition and situation awareness in urban areas with respect to conventional techniques. Hyperspectral and conventional broadband high-spatial-resolution data were collected during the DUCAS trials in Zeebrugge, Belgium, in June 2011. LWIR data were acquired using the ITRES Thermal Airborne Spectrographic Imager TASI-600 that operates in the spectral range of 8.0-11.5 μm (32 band configuration). Broadband data were acquired using two aeroplanemounted FLIR SC7000 MWIR cameras. Acquisition of the images was around noon. To limit the number of false alarms due to atmospheric changes, the time interval between the images is less than 2 hours. Local co-registration adjustment was applied to compensate for misregistration errors in the order of a few pixels. The targets in the data that will be analysed in this paper are different kinds of vehicles. Change detection algorithms that were applied and evaluated are Euclidean distance, Mahalanobis distance, Chronochrome (CC), Covariance Equalisation (CE), and Hyperbolic Anomalous Change Detection (HACD). Based on Receiver Operating Characteristics (ROC) we conclude that LWIR hyperspectral has an advantage over MWIR broadband change detection. The best hyperspectral detector is HACD because it is most robust to noise. MWIR high spatial-resolution broadband results show that it helps to apply a false alarm reduction strategy based on spatial processing.

A stretchable strain sensor based on a metal nanoparticle thin film for human motion detection

NASA Astrophysics Data System (ADS)

Lee, Jaehwan; Kim, Sanghyeok; Lee, Jinjae; Yang, Daejong; Park, Byong Chon; Ryu, Seunghwa; Park, Inkyu

2014-09-01

Wearable strain sensors for human motion detection are being highlighted in various fields such as medical, entertainment and sports industry. In this paper, we propose a new type of stretchable strain sensor that can detect both tensile and compressive strains and can be fabricated by a very simple process. A silver nanoparticle (Ag NP) thin film patterned on the polydimethylsiloxane (PDMS) stamp by a single-step direct transfer process is used as the strain sensing material. The working principle is the change in the electrical resistance caused by the opening/closure of micro-cracks under mechanical deformation. The fabricated stretchable strain sensor shows highly sensitive and durable sensing performances in various tensile/compressive strains, long-term cyclic loading and relaxation tests. We demonstrate the applications of our stretchable strain sensors such as flexible pressure sensors and wearable human motion detection devices with high sensitivity, response speed and mechanical robustness.Wearable strain sensors for human motion detection are being highlighted in various fields such as medical, entertainment and sports industry. In this paper, we propose a new type of stretchable strain sensor that can detect both tensile and compressive strains and can be fabricated by a very simple process. A silver nanoparticle (Ag NP) thin film patterned on the polydimethylsiloxane (PDMS) stamp by a single-step direct transfer process is used as the strain sensing material. The working principle is the change in the electrical resistance caused by the opening/closure of micro-cracks under mechanical deformation. The fabricated stretchable strain sensor shows highly sensitive and durable sensing performances in various tensile/compressive strains, long-term cyclic loading and relaxation tests. We demonstrate the applications of our stretchable strain sensors such as flexible pressure sensors and wearable human motion detection devices with high sensitivity, response speed and mechanical robustness. Electronic supplementary information (ESI) available. See DOI: 10.1039/c4nr03295k

ADAR2 induces reproducible changes in sequence and abundance of mature microRNAs in the mouse brain

PubMed Central

Vesely, Cornelia; Tauber, Stefanie; Sedlazeck, Fritz J.; Tajaddod, Mansoureh; von Haeseler, Arndt; Jantsch, Michael F.

2014-01-01

Adenosine deaminases that act on RNA (ADARs) deaminate adenosines to inosines in double-stranded RNAs including miRNA precursors. A to I editing is widespread and required for normal life. By comparing deep sequencing data of brain miRNAs from wild-type and ADAR2 deficient mouse strains, we detect editing sites and altered miRNA processing at high sensitivity. We detect 48 novel editing events in miRNAs. Some editing events reach frequencies of up to 80%. About half of all editing events depend on ADAR2 while some miRNAs are preferentially edited by ADAR1. Sixty-four percent of all editing events are located within the seed region of mature miRNAs. For the highly edited miR-3099, we experimentally prove retargeting of the edited miRNA to novel 3′ UTRs. We show further that an abundant editing event in miR-497 promotes processing by Drosha of the corresponding pri-miRNA. We also detect reproducible changes in the abundance of specific miRNAs in ADAR2-deficient mice that occur independent of adjacent A to I editing events. This indicates that ADAR2 binding but not editing of miRNA precursors may influence their processing. Correlating with changes in miRNA abundance we find misregulation of putative targets of these miRNAs in the presence or absence of ADAR2. PMID:25260591

A statistical power analysis of woody carbon flux from forest inventory data

Treesearch

James A. Westfall; Christopher W. Woodall; Mark A. Hatfield

2013-01-01

At a national scale, the carbon (C) balance of numerous forest ecosystem C pools can be monitored using a stock change approach based on national forest inventory data. Given the potential influence of disturbance events and/or climate change processes, the statistical detection of changes in forest C stocks is paramount to maintaining the net sequestration status of...

Odor Signals of Immune Activation and CNS Inflammation

DTIC Science & Technology

2014-12-01

inflammation results in detectable alteration of body odor and that traumatic brain injury (TBI) might similarly produce volatile metabolites specific to...Because both LPS and TBI elicit inflammatory processes and LPS-induced inflammation induces body odor changes, we hypothesized that (1) TBI would...induce a distinct change in body odor and (2) this change would resemble the change induced by LPS. Mice receiving surgery and lateral fluid percussion

Automated baseline change detection -- Phases 1 and 2. Final report

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

Byler, E.

1997-10-31

The primary objective of this project is to apply robotic and optical sensor technology to the operational inspection of mixed toxic and radioactive waste stored in barrels, using Automated Baseline Change Detection (ABCD), based on image subtraction. Absolute change detection is based on detecting any visible physical changes, regardless of cause, between a current inspection image of a barrel and an archived baseline image of the same barrel. Thus, in addition to rust, the ABCD system can also detect corrosion, leaks, dents, and bulges. The ABCD approach and method rely on precise camera positioning and repositioning relative to the barrelmore » and on feature recognition in images. The ABCD image processing software was installed on a robotic vehicle developed under a related DOE/FETC contract DE-AC21-92MC29112 Intelligent Mobile Sensor System (IMSS) and integrated with the electronics and software. This vehicle was designed especially to navigate in DOE Waste Storage Facilities. Initial system testing was performed at Fernald in June 1996. After some further development and more extensive integration the prototype integrated system was installed and tested at the Radioactive Waste Management Facility (RWMC) at INEEL beginning in April 1997 through the present (November 1997). The integrated system, composed of ABCD imaging software and IMSS mobility base, is called MISS EVE (Mobile Intelligent Sensor System--Environmental Validation Expert). Evaluation of the integrated system in RWMC Building 628, containing approximately 10,000 drums, demonstrated an easy to use system with the ability to properly navigate through the facility, image all the defined drums, and process the results into a report delivered to the operator on a GUI interface and on hard copy. Further work is needed to make the brassboard system more operationally robust.« less

Rate change detection of frequency modulated signals: developmental trends.

PubMed

Cohen-Mimran, Ravit; Sapir, Shimon

2011-08-26

The aim of this study was to examine developmental trends in rate change detection of auditory rhythmic signals (repetitive sinusoidally frequency modulated tones). Two groups of children (9-10 years old and 11-12 years old) and one group of young adults performed a rate change detection (RCD) task using three types of stimuli. The rate of stimulus modulation was either constant (CR), raised by 1 Hz in the middle of the stimulus (RR1) or raised by 2 Hz in the middle of the stimulus (RR2). Performance on the RCD task significantly improved with age. Also, the different stimuli showed different developmental trajectories. When the RR2 stimulus was used, results showed adult-like performance by the age of 10 years but when the RR1 stimulus was used performance continued to improve beyond 12 years of age. Rate change detection of repetitive sinusoidally frequency modulated tones show protracted development beyond the age of 12 years. Given evidence for abnormal processing of auditory rhythmic signals in neurodevelopmental conditions, such as dyslexia, the present methodology might help delineate the nature of these conditions.

Diffusion tensor MRI shows progressive changes in the hippocampus and dentate gyrus after status epilepticus in rat - histological validation with Fourier-based analysis.

PubMed

Salo, Raimo A; Miettinen, Tuukka; Laitinen, Teemu; Gröhn, Olli; Sierra, Alejandra

2017-05-15

Imaging markers for monitoring disease progression, recovery, and treatment efficacy are a major unmet need for many neurological diseases, including epilepsy. Recent evidence suggests that diffusion tensor imaging (DTI) provides high microstructural contrast even outside major white matter tracts. We hypothesized that in vivo DTI could detect progressive microstructural changes in the dentate gyrus and the hippocampal CA3bc in the rat brain after status epilepticus (SE). To test this hypothesis, we induced SE with systemic kainic acid or pilocarpine in adult male Wistar rats and subsequently scanned them using in vivo DTI at five time-points: prior to SE, and 10, 20, 34, and 79 days post SE. In order to tie the DTI findings to changes in the tissue microstructure, myelin- and glial fibrillary acidic protein (GFAP)-stained sections from the same animals underwent Fourier analysis. We compared the Fourier analysis parameters, anisotropy index and angle of myelinated axons or astrocyte processes, to corresponding DTI parameters, fractional anisotropy (FA) and the orientation angle of the principal eigenvector. We found progressive detectable changes in DTI parameters in both the dentate gyrus (FA, axial diffusivity [D || ], linear anisotropy [CL] and spherical anisotropy [CS], p<0.001, linear mixed-effects model [LMEM]) and the CA3bc (FA, D || , CS, and angle, p<0.001, LMEM; CL and planar anisotropy [CP], p<0.01, LMEM) post SE. The Fourier analysis revealed that both myelinated axons and astrocyte processes played a role in the water diffusion anisotropy changes detected by DTI in individual portions of the dentate gyrus (suprapyramidal blade, mid-portion, and infrapyramidal blade). In the whole dentate gyrus, myelinated axons markedly contributed to the water diffusion changes. In CA3bc as well as in CA3b and CA3c, both myelinated axons and astrocyte processes contributed to water diffusion anisotropy and orientation. Our study revealed that DTI is a promising method for noninvasive detection of microstructural alterations in the hippocampus proper. These alterations may be potential imaging markers for epileptogenesis. Copyright © 2017 Elsevier Inc. All rights reserved.

Automatic detection of surface changes on Mars - a status report

NASA Astrophysics Data System (ADS)

Sidiropoulos, Panagiotis; Muller, Jan-Peter

2016-10-01

Orbiter missions have acquired approximately 500,000 high-resolution visible images of the Martian surface, covering an area approximately 6 times larger than the overall area of Mars. This data abundance allows the scientific community to examine the Martian surface thoroughly and potentially make exciting new discoveries. However, the increased data volume, as well as its complexity, generate problems at the data processing stages, which are mainly related to a number of unresolved issues that batch-mode planetary data processing presents. As a matter of fact, the scientific community is currently struggling to scale the common ("one-at-a-time" processing of incoming products by expert scientists) paradigm to tackle the large volumes of input data. Moreover, expert scientists are more or less forced to use complex software in order to extract input information for their research from raw data, even though they are not data scientists themselves.Our work within the STFC and EU FP7 i-Mars projects aims at developing automated software that will process all of the acquired data, leaving domain expert planetary scientists to focus on their final analysis and interpretation. Moreover, after completing the development of a fully automated pipeline that processes automatically the co-registration of high-resolution NASA images to ESA/DLR HRSC baseline, our main goal has shifted to the automated detection of surface changes on Mars. In particular, we are developing a pipeline that uses as an input multi-instrument image pairs, which are processed by an automated pipeline, in order to identify changes that are correlated with Mars surface dynamic phenomena. The pipeline has currently been tested in anger on 8,000 co-registered images and by the time of DPS/EPSC we expect to have processed many tens of thousands of image pairs, producing a set of change detection results, a subset of which will be shown in the presentation.The research leading to these results has received funding from the STFC "MSSL Consolidated Grant under "Planetary Surface Data Mining" ST/K000977/1 and partial support from the European Union's Seventh Framework Programme (FP7/2007-2013) under iMars grant agreement number 607379

Interoperable cross-domain semantic and geospatial framework for automatic change detection

NASA Astrophysics Data System (ADS)

Kuo, Chiao-Ling; Hong, Jung-Hong

2016-01-01

With the increasingly diverse types of geospatial data established over the last few decades, semantic interoperability in integrated applications has attracted much interest in the field of Geographic Information System (GIS). This paper proposes a new strategy and framework to process cross-domain geodata at the semantic level. This framework leverages the semantic equivalence of concepts between domains through bridge ontology and facilitates the integrated use of different domain data, which has been long considered as an essential superiority of GIS, but is impeded by the lack of understanding about the semantics implicitly hidden in the data. We choose the task of change detection to demonstrate how the introduction of ontology concept can effectively make the integration possible. We analyze the common properties of geodata and change detection factors, then construct rules and summarize possible change scenario for making final decisions. The use of topographic map data to detect changes in land use shows promising success, as far as the improvement of efficiency and level of automation is concerned. We believe the ontology-oriented approach will enable a new way for data integration across different domains from the perspective of semantic interoperability, and even open a new dimensionality for the future GIS.

Context-aided analysis of community evolution in networks

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

Pallotta, Giuliana; Konjevod, Goran; Cadena, Jose

Here, we are interested in detecting and analyzing global changes in dynamic networks (networks that evolve with time). More precisely, we consider changes in the activity distribution within the network, in terms of density (ie, edge existence) and intensity (ie, edge weight). Detecting change in local properties, as well as individual measurements or metrics, has been well studied and often reduces to traditional statistical process control. In contrast, detecting change in larger scale structure of the network is more challenging and not as well understood. We address this problem by proposing a framework for detecting change in network structure basedmore » on separate pieces: a probabilistic model for partitioning nodes by their behavior, a label-unswitching heuristic, and an approach to change detection for sequences of complex objects. We examine the performance of one instantiation of such a framework using mostly previously available pieces. The dataset we use for these investigations is the publicly available New York City Taxi and Limousine Commission dataset covering all taxi trips in New York City since 2009. Using it, we investigate the evolution of an ensemble of networks under different spatiotemporal resolutions. We identify the community structure by fitting a weighted stochastic block model. In conclusion, we offer insights on different node ranking and clustering methods, their ability to capture the rhythm of life in the Big Apple, and their potential usefulness in highlighting changes in the underlying network structure.« less

Context-aided analysis of community evolution in networks

DOE PAGES

Pallotta, Giuliana; Konjevod, Goran; Cadena, Jose; ...

2017-09-15

Here, we are interested in detecting and analyzing global changes in dynamic networks (networks that evolve with time). More precisely, we consider changes in the activity distribution within the network, in terms of density (ie, edge existence) and intensity (ie, edge weight). Detecting change in local properties, as well as individual measurements or metrics, has been well studied and often reduces to traditional statistical process control. In contrast, detecting change in larger scale structure of the network is more challenging and not as well understood. We address this problem by proposing a framework for detecting change in network structure basedmore » on separate pieces: a probabilistic model for partitioning nodes by their behavior, a label-unswitching heuristic, and an approach to change detection for sequences of complex objects. We examine the performance of one instantiation of such a framework using mostly previously available pieces. The dataset we use for these investigations is the publicly available New York City Taxi and Limousine Commission dataset covering all taxi trips in New York City since 2009. Using it, we investigate the evolution of an ensemble of networks under different spatiotemporal resolutions. We identify the community structure by fitting a weighted stochastic block model. In conclusion, we offer insights on different node ranking and clustering methods, their ability to capture the rhythm of life in the Big Apple, and their potential usefulness in highlighting changes in the underlying network structure.« less

Process Model Improvement for Source Code Plagiarism Detection in Student Programming Assignments

ERIC Educational Resources Information Center

Kermek, Dragutin; Novak, Matija

2016-01-01

In programming courses there are various ways in which students attempt to cheat. The most commonly used method is copying source code from other students and making minimal changes in it, like renaming variable names. Several tools like Sherlock, JPlag and Moss have been devised to detect source code plagiarism. However, for larger student…

Contribution to the spectroscopic study of cytostatics molecules

NASA Astrophysics Data System (ADS)

Staicu, Angela; Pascu, Mihail-Lucian; Mogos, Ioan; Enescu, Mironel; Truica, Sorina; Voicu, Letitia; Gazdaru, Doina M.; Radu, Alina; Gazdaru, S.

2001-06-01

The effect of UV irradiation of methotrexate was investigated by steady state absorption and fluorescence spectroscopy. Major modifications on absorption bands were detected upon irradiation fluence greater than 59J/cm2. In addition the irradiated solutions become strongly fluorescent. The detected changes are not linear with the exposure time suggesting that the photo-induced chemical processes are complex.

Classification of multispectral or hyperspectral satellite imagery using clustering of sparse approximations on sparse representations in learned dictionaries obtained using efficient convolutional sparse coding

DOEpatents

Moody, Daniela; Wohlberg, Brendt

2018-01-02

An approach for land cover classification, seasonal and yearly change detection and monitoring, and identification of changes in man-made features may use a clustering of sparse approximations (CoSA) on sparse representations in learned dictionaries. The learned dictionaries may be derived using efficient convolutional sparse coding to build multispectral or hyperspectral, multiresolution dictionaries that are adapted to regional satellite image data. Sparse image representations of images over the learned dictionaries may be used to perform unsupervised k-means clustering into land cover categories. The clustering process behaves as a classifier in detecting real variability. This approach may combine spectral and spatial textural characteristics to detect geologic, vegetative, hydrologic, and man-made features, as well as changes in these features over time.

Geodynamics and temporal variations in the gravity field

NASA Technical Reports Server (NTRS)

Mcadoo, D. C.; Wagner, C. A.

1989-01-01

Just as the Earth's surface deforms tectonically, so too does the gravity field evolve with time. Now that precise geodesy is yielding observations of these deformations it is important that concomitant, temporal changes in the gravity field be monitored. Although these temporal changes are minute they are observable: changes in the J2 component of the gravity field were inferred from satellite (LAGEOS) tracking data; changes in other components of the gravity field would likely be detected by Geopotential Research Mission (GRM), a proposed but unapproved NASA gravity field mission. Satellite gradiometers were also proposed for high-precision gravity field mapping. Using simple models of geodynamic processes such as viscous postglacial rebound of the solid Earth, great subduction zone earthquakes and seasonal glacial mass fluctuations, we predict temporal changes in gravity gradients at spacecraft altitudes. It was found that these proposed gravity gradient satellite missions should have sensitivities equal to or better than 10(exp -4) E in order to reliably detect these changes. It was also found that satellite altimetry yields little promise of useful detection of time variations in gravity.

Data on green tea flavor determinantes as affected by cultivars and manufacturing processes.

PubMed

Han, Zhuo-Xiao; Rana, Mohammad M; Liu, Guo-Feng; Gao, Ming-Jun; Li, Da-Xiang; Wu, Fu-Guang; Li, Xin-Bao; Wan, Xiao-Chun; Wei, Shu

2017-02-01

This paper presents data related to an article entitled "Green tea flavor determinants and their changes over manufacturing processes" (Han et al., 2016) [1]. Green tea samples were prepared with steaming and pan firing treatments from the tender leaves of tea cultivars 'Bai-Sang Cha' ('BAS') and 'Fuding-Dabai Cha' ('FUD'). Aroma compounds from the tea infusions were detected and quantified using HS-SPME coupled with GC/MS. Sensory evaluation was also made for characteristic tea flavor. The data shows the abundances of the detected aroma compounds, their threshold values and odor characteristics in the two differently processed tea samples as well as two different cultivars.

Updating National Topographic Data Base Using Change Detection Methods

NASA Astrophysics Data System (ADS)

Keinan, E.; Felus, Y. A.; Tal, Y.; Zilberstien, O.; Elihai, Y.

2016-06-01

The traditional method for updating a topographic database on a national scale is a complex process that requires human resources, time and the development of specialized procedures. In many National Mapping and Cadaster Agencies (NMCA), the updating cycle takes a few years. Today, the reality is dynamic and the changes occur every day, therefore, the users expect that the existing database will portray the current reality. Global mapping projects which are based on community volunteers, such as OSM, update their database every day based on crowdsourcing. In order to fulfil user's requirements for rapid updating, a new methodology that maps major interest areas while preserving associated decoding information, should be developed. Until recently, automated processes did not yield satisfactory results, and a typically process included comparing images from different periods. The success rates in identifying the objects were low, and most were accompanied by a high percentage of false alarms. As a result, the automatic process required significant editorial work that made it uneconomical. In the recent years, the development of technologies in mapping, advancement in image processing algorithms and computer vision, together with the development of digital aerial cameras with NIR band and Very High Resolution satellites, allow the implementation of a cost effective automated process. The automatic process is based on high-resolution Digital Surface Model analysis, Multi Spectral (MS) classification, MS segmentation, object analysis and shape forming algorithms. This article reviews the results of a novel change detection methodology as a first step for updating NTDB in the Survey of Israel.

Detection and measurement of the intracellular calcium variation in follicular cells.

PubMed

Herrera-Navarro, Ana M; Terol-Villalobos, Iván R; Jiménez-Hernández, Hugo; Peregrina-Barreto, Hayde; Gonzalez-Barboza, José-Joel

2014-01-01

This work presents a new method for measuring the variation of intracellular calcium in follicular cells. The proposal consists in two stages: (i) the detection of the cell's nuclei and (ii) the analysis of the fluorescence variations. The first stage is performed via watershed modified transformation, where the process of labeling is controlled. The detection process uses the contours of the cells as descriptors, where they are enhanced with a morphological filter that homogenizes the luminance variation of the image. In the second stage, the fluorescence variations are modeled as an exponential decreasing function, where the fluorescence variations are highly correlated with the changes of intracellular free Ca(2+). Additionally, it is introduced a new morphological called medium reconstruction process, which helps to enhance the data for the modeling process. This filter exploits the undermodeling and overmodeling properties of reconstruction operators, such that it preserves the structure of the original signal. Finally, an experimental process shows evidence of the capabilities of the proposal.

Detection and Measurement of the Intracellular Calcium Variation in Follicular Cells

PubMed Central

Herrera-Navarro, Ana M.; Terol-Villalobos, Iván R.; Jiménez-Hernández, Hugo; Peregrina-Barreto, Hayde; Gonzalez-Barboza, José-Joel

2014-01-01

This work presents a new method for measuring the variation of intracellular calcium in follicular cells. The proposal consists in two stages: (i) the detection of the cell's nuclei and (ii) the analysis of the fluorescence variations. The first stage is performed via watershed modified transformation, where the process of labeling is controlled. The detection process uses the contours of the cells as descriptors, where they are enhanced with a morphological filter that homogenizes the luminance variation of the image. In the second stage, the fluorescence variations are modeled as an exponential decreasing function, where the fluorescence variations are highly correlated with the changes of intracellular free Ca2+. Additionally, it is introduced a new morphological called medium reconstruction process, which helps to enhance the data for the modeling process. This filter exploits the undermodeling and overmodeling properties of reconstruction operators, such that it preserves the structure of the original signal. Finally, an experimental process shows evidence of the capabilities of the proposal. PMID:25342958

Change detection on UGV patrols with respect to a reference tour using VIS imagery

NASA Astrophysics Data System (ADS)

Müller, Thomas

2015-05-01

Autonomous driving robots (UGVs, Unmanned Ground Vehicles) equipped with visual-optical (VIS) cameras offer a high potential to automatically detect suspicious occurrences and dangerous or threatening situations on patrol. In order to explore this potential, the scene of interest is recorded first on a reference tour representing the 'everything okay' situation. On further patrols changes are detected with respect to the reference in a two step processing scheme. In the first step, an image retrieval is done to find the reference images that are closest to the current camera image on patrol. This is done efficiently based on precalculated image-to-image registrations of the reference by optimizing image overlap in a local reference search (after a global search when that is needed). In the second step, a robust spatio-temporal change detection is performed that widely compensates 3-D parallax according to variations of the camera position. Various results document the performance of the presented approach.

Automatic detection of Floating Ice at Antarctic Continental Margin from Remotely Sensed Image with Object-oriented Matching

NASA Astrophysics Data System (ADS)

Zhao, Z.

2011-12-01

Changes in ice sheet and floating ices around that have great significance for global change research. In the context of global warming, rapidly changing of Antarctic continental margin, caving of ice shelves, movement of iceberg are all closely related to climate change and ocean circulation. Using automatic change detection technology to rapid positioning the melting Region of Polar ice sheet and the location of ice drift would not only strong support for Global Change Research but also lay the foundation for establishing early warning mechanism for melting of the polar ice and Ice displacement. This paper proposed an automatic change detection method using object-based segmentation technology. The process includes three parts: ice extraction using image segmentation, object-baed ice tracking, change detection based on similarity matching. An approach based on similarity matching of eigenvector is proposed in this paper, which used area, perimeter, Hausdorff distance, contour, shape and other information of each ice-object. Different time of LANDSAT ETM+ data, Chinese environment disaster satellite HJ1B date, MODIS 1B date are used to detect changes of Floating ice at Antarctic continental margin respectively. We select different time of ETM+ data(January 7, 2003 and January 16, 2003) with the area around Antarctic continental margin near the Lazarev Bay, which is from 70.27454853 degrees south latitude, longitude 12.38573410 degrees to 71.44474167 degrees south latitude, longitude 10.39252222 degrees,included 11628 sq km of Antarctic continental margin area, as a sample. Then we can obtain the area of floating ices reduced 371km2, and the number of them reduced 402 during the time. In addition, the changes of all the floating ices around the margin region of Antarctic within 1200 km are detected using MODIS 1B data. During the time from January 1, 2008 to January 7, 2008, the floating ice area decreased by 21644732 km2, and the number of them reduced by 83080. The results show that the object-based information extraction algorithm can obtain more precise details of a single object, while the change detection method based on similarity matching can effectively tracking the change of floating ice.

Process monitoring in intensive care with the use of cumulative expected minus observed mortality and risk-adjusted P charts.

PubMed

Cockings, Jerome G L; Cook, David A; Iqbal, Rehana K

2006-02-01

A health care system is a complex adaptive system. The effect of a single intervention, incorporated into a complex clinical environment, may be different from that expected. A national database such as the Intensive Care National Audit & Research Centre (ICNARC) Case Mix Programme in the UK represents a centralised monitoring, surveillance and reporting system for retrospective quality and comparative audit. This can be supplemented with real-time process monitoring at a local level for continuous process improvement, allowing early detection of the impact of both unplanned and deliberately imposed changes in the clinical environment. Demographic and UK Acute Physiology and Chronic Health Evaluation II (APACHE II) data were prospectively collected on all patients admitted to a UK regional hospital between 1 January 2003 and 30 June 2004 in accordance with the ICNARC Case Mix Programme. We present a cumulative expected minus observed (E-O) plot and the risk-adjusted p chart as methods of continuous process monitoring. We describe the construction and interpretation of these charts and show how they can be used to detect planned or unplanned organisational process changes affecting mortality outcomes. Five hundred and eighty-nine adult patients were included. The overall death rate was 0.78 of predicted. Calibration showed excess survival in ranges above 30% risk of death. The E-O plot confirmed a survival above that predicted. Small transient variations were seen in the slope that could represent random effects, or real but transient changes in the quality of care. The risk-adjusted p chart showed several observations below the 2 SD control limits of the expected mortality rate. These plots provide rapid analysis of risk-adjusted performance suitable for local application and interpretation. The E-O chart provided rapid easily visible feedback of changes in risk-adjusted mortality, while the risk-adjusted p chart allowed statistical evaluation. Local analysis of risk-adjusted mortality data with an E-O plot and a risk-adjusted p chart is feasible and allows the rapid detection of changes in risk-adjusted outcome of intensive care patients. This complements the centralised national database, which is more archival and comparative in nature.

Observing Active Volcanism on Earth and Beyond With an Autonomous Science Investigation Capability

NASA Astrophysics Data System (ADS)

Davies, A. G.; Mjolsness, E. D.; Fink, W.; Castano, R.; Park, H. G.; Zak, M.; Burl, M. C.

2001-12-01

Operational constraints imposed by restricted downlink and long communication delays make autonomous systems a necessity for exploring dynamic processes in the Solar System and beyond. Our objective is to develop an onboard, modular, automated science analysis tool that will autonomously detect unexpected events, identify rare events at predicted sites, quantify the processes under study, and prioritize the science data and analyses as they are collected. A primary target for this capability is terrestrial active volcanism. Our integrated, science-driven command and control package represents the next stage of the automatic monitoring of volcanic activity pioneered by GOES. The resulting system will maximize science return from day-to-day instrument use and provide immediate reaction to capture the fullest information from infrequent events. For example, a sensor suite consisting of a Galileo-like multi-filter visible wavelength camera and an infrared spectrometer, can acquire high-spatial resolution data of eruptions of lava and volcanic plumes and identify large concentrations of volcanic SO2. After image/spectrum formation, software is applied to the data which is capable of change detection (in the visible and infrared), feature identification (both in imagery and spectra), and novelty detection. In this particular case, the latter module detects change in the parameter space of an advanced multi-component black-body volcanic thermal emission model by means of a novel technique called the "Grey-Box" method which analyzes time series data through a combination of deterministic and stochastic models. This approach can be demonstrated using data obtained by the Galileo spacecraft of ionian volcanism. The system autonomously identifies the most scientifically important targets and prioritizes data and analyses for return. All of these techniques have been successfully demonstrated in laboratory experiments, and are ready to be tested in an operational environment. After identification of a target of interest, an onboard planner prioritizes resources to obtain the best possible dataset of the identified process. We emphasize that the software is modular. The change detection and feature identification modules can be applied to any imaged dataset, and are not confined to volcanic targets. Applications are therefore widespread, across all NASA Enterprises. Examples include detection and quantification of extraterrestrial volcanism (Io, Triton), the monitoring of features in planetary atmospheres (Earth, Gas Giants), the ebb and flow of ices (Earth, Mars), asteriod, comet and supernova detection, change detection in magnetic fields, and identification of structure within radio outbursts.

Agricultural land change in the Carpathian ecoregion after the breakdown of socialism and expansion of the European Union

NASA Astrophysics Data System (ADS)

Griffiths, Patrick; Müller, Daniel; Kuemmerle, Tobias; Hostert, Patrick

2013-12-01

Widespread changes of agricultural land use occurred in Eastern Europe since the collapse of socialism and the European Union’s eastward expansion, but the rates and patterns of recent land changes remain unclear. Here we assess agricultural land change for the entire Carpathian ecoregion in Eastern Europe at 30 m spatial resolution with Landsat data and for two change periods, between 1985-2000 and 2000-2010. The early period is characterized by post-socialist transition processes, the late period by an increasing influence of EU politics in the region. For mapping and change detection, we use a machine learning approach (random forests) on image composites and variance metrics which were derived from the full decadal archive of Landsat imagery. Our results suggest that cropland abandonment was the most prevalent change process, but we also detected considerable areas of grassland conversion and forest expansion on non-forest land. Cropland abandonment was most extensive during the transition period and predominantly occurred in marginal areas with low suitability for agriculture. Conversely, we observed substantial recultivation of formerly abandoned cropland in high-value agricultural areas since 2000. Hence, market forces increasingly adjust socialist legacies of land expansive production and agricultural land use clusters in favorable areas while marginal lands revert to forest.

Optical method and apparatus for detection of defects and microstructural changes in ceramics and ceramic coatings

DOEpatents

Ellingson, William A.; Todd, Judith A.; Sun, Jiangang

2001-01-01

Apparatus detects defects and microstructural changes in hard translucent materials such as ceramic bulk compositions and ceramic coatings such as after use under load conditions. The beam from a tunable laser is directed onto the sample under study and light reflected by the sample is directed to two detectors, with light scattered with a small scatter angle directed to a first detector and light scattered with a larger scatter angle directed to a second detector for monitoring the scattering surface. The sum and ratio of the two detector outputs respectively provide a gray-scale, or "sum" image, and an indication of the lateral spread of the subsurface scatter, or "ratio" image. This two detector system allows for very high speed crack detection for on-line, real-time inspection of damage in ceramic components. Statistical image processing using a digital image processing approach allows for the quantative discrimination of the presence and distribution of small flaws in a sample while improving detection reliability. The tunable laser allows for the penetration of the sample to detect defects from the sample's surface to the laser's maximum depth of penetration. A layered optical fiber directs the incoming laser beam to the sample and transmits each scattered signal to a respective one of the two detectors.

Effect of thermal processing during yogurt production upon the detection of staphylococcal enterotoxin B.

PubMed

Principato, Maryann; Boyle, Thomas; Njoroge, Joyce; Jones, Robert L; O'Donnell, Michael

2009-10-01

This research was conducted to examine the inherent properties of yogurt contaminated with staphylococcal enterotoxin B (SEB). Two types of yogurts were produced for this study. Type I yogurts were produced by adding SEB at the start of yogurt production, and type II yogurts were produced by adding SEB after the milk base had been boiled. Biochemical characteristics inherent to yogurt, including pH, lactic acid and acetaldehyde concentrations, were analyzed weekly for each batch beginning at a time just after production and throughout a storage period of at least 4 weeks. The presence of toxin during yogurt production did not result in any significant biochemical or physical changes in yogurt. However, we were unable to detect SEB toxin in type I yogurt using a commercially available enzyme-linked immunosorbent assay (ELISA). In contrast, SEB was easily detectable by our ELISA in type II yogurt samples. Higher levels of SEB were recovered from type II yogurt that had been stored for 1 week than from type II yogurt that had been stored for any other length of time. These results indicate that the biochemical characteristics of yogurt did not change significantly (relative to control yogurt) in the presence of either thermally processed SEB or native SEB. However, the ability to detect SEB by ELISA was dependent on whether the toxin had been processed.

Task demands determine comparison strategy in whole probe change detection.

PubMed

Udale, Rob; Farrell, Simon; Kent, Chris

2018-05-01

Detecting a change in our visual world requires a process that compares the external environment (test display) with the contents of memory (study display). We addressed the question of whether people strategically adapt the comparison process in response to different decision loads. Study displays of 3 colored items were presented, followed by 'whole-display' probes containing 3 colored shapes. Participants were asked to decide whether any probed items contained a new feature. In Experiments 1-4, irrelevant changes to the probed item's locations or feature bindings influenced memory performance, suggesting that participants employed a comparison process that relied on spatial locations. This finding occurred irrespective of whether participants were asked to decide about the whole display, or only a single cued item within the display. In Experiment 5, when the base-rate of changes in the nonprobed items increased (increasing the incentive to use the cue effectively), participants were not influenced by irrelevant changes in location or feature bindings. In addition, we observed individual differences in the use of spatial cues. These results suggest that participants can flexibly switch between spatial and nonspatial comparison strategies, depending on interactions between individual differences and task demand factors. These findings have implications for models of visual working memory that assume that the comparison between study and test obligatorily relies on accessing visual features via their binding to location. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Absence of both auditory evoked potentials and auditory percepts dependent on timing cues.

PubMed

Starr, A; McPherson, D; Patterson, J; Don, M; Luxford, W; Shannon, R; Sininger, Y; Tonakawa, L; Waring, M

1991-06-01

An 11-yr-old girl had an absence of sensory components of auditory evoked potentials (brainstem, middle and long-latency) to click and tone burst stimuli that she could clearly hear. Psychoacoustic tests revealed a marked impairment of those auditory perceptions dependent on temporal cues, that is, lateralization of binaural clicks, change of binaural masked threshold with changes in signal phase, binaural beats, detection of paired monaural clicks, monaural detection of a silent gap in a sound, and monaural threshold elevation for short duration tones. In contrast, auditory functions reflecting intensity or frequency discriminations (difference limens) were only minimally impaired. Pure tone audiometry showed a moderate (50 dB) bilateral hearing loss with a disproportionate severe loss of word intelligibility. Those auditory evoked potentials that were preserved included (1) cochlear microphonics reflecting hair cell activity; (2) cortical sustained potentials reflecting processing of slowly changing signals; and (3) long-latency cognitive components (P300, processing negativity) reflecting endogenous auditory cognitive processes. Both the evoked potential and perceptual deficits are attributed to changes in temporal encoding of acoustic signals perhaps occurring at the synapse between hair cell and eighth nerve dendrites. The results from this patient are discussed in relation to previously published cases with absent auditory evoked potentials and preserved hearing.

Mapping Changes and Damages in Areas of Conflict: From Archive C-Band SAR Data to New HR X-Band Imagery, Towards the Sentinels

NASA Astrophysics Data System (ADS)

Tapete, Deodato; Cigna, Francesca; Donoghue, Daniel N. M.; Philip, Graham

2015-05-01

On the turn of radar space science with the recent launch of Sentinel-1A, we investigate how to better exploit the opportunities offered by large C-band SAR archives and increasing datasets of HR to VHR X-band data, to map changes and damages in urban and rural areas affected by conflicts. We implement a dual approach coupling multi-interferogram processing and amplitude change detection, to assess the impact of the recent civil war on the city of Homs, Western Syria, and the surrounding semi-arid landscape. More than 280,000 coherent pixels are retrieved from Small BAseline Subset (SBAS) processing of the 8year-long ENVISAT ASAR IS2 archive, to quantify land subsidence due to pre-war water abstraction in rural areas. Damages in Homs are detected by analysing the changes of SAR backscattering (σ0), comparing 3m-resolution StripMap TerraSAR-X pairs from 2009 to 2014. Pre-war alteration is differentiated from war-related damages via operator-driven interpretation of the σ0 patterns.

The signature of undetected change: an exploratory electrotomographic investigation of gradual change blindness.

PubMed

Kiat, John E; Dodd, Michael D; Belli, Robert F; Cheadle, Jacob E

2018-05-01

Neuroimaging-based investigations of change blindness, a phenomenon in which seemingly obvious changes in visual scenes fail to be detected, have significantly advanced our understanding of visual awareness. The vast majority of prior investigations, however, utilize paradigms involving visual disruptions (e.g., intervening blank screens, saccadic movements, "mudsplashes"), making it difficult to isolate neural responses toward visual changes cleanly. To address this issue in this present study, high-density EEG data (256 channel) were collected from 25 participants using a paradigm in which visual changes were progressively introduced into detailed real-world scenes without the use of visual disruption. Oscillatory activity associated with undetected changes was contrasted with activity linked to their absence using standardized low-resolution brain electromagnetic tomography (sLORETA). Although an insufficient number of detections were present to allow for analysis of actual change detection, increased beta-2 activity in the right inferior parietal lobule (rIPL), a region repeatedly associated with change blindness in disruption paradigms, followed by increased theta activity in the right superior temporal gyrus (rSTG) was noted in undetected visual change responses relative to the absence of change. We propose the rIPL beta-2 activity to be associated with orienting attention toward visual changes, with the subsequent rise in rSTG theta activity being potentially linked with updating preconscious perceptual memory representations. NEW & NOTEWORTHY This study represents the first neuroimaging-based investigation of gradual change blindness, a visual phenomenon that has significant potential to shed light on the processes underlying visual detection and conscious perception. The use of gradual change materials is reflective of real-world visual phenomena and allows for cleaner isolation of signals associated with the neural registration of change relative to the use of abrupt change transients.

Real-time DNA Amplification and Detection System Based on a CMOS Image Sensor.

PubMed

Wang, Tiantian; Devadhasan, Jasmine Pramila; Lee, Do Young; Kim, Sanghyo

2016-01-01

In the present study, we developed a polypropylene well-integrated complementary metal oxide semiconductor (CMOS) platform to perform the loop mediated isothermal amplification (LAMP) technique for real-time DNA amplification and detection simultaneously. An amplification-coupled detection system directly measures the photon number changes based on the generation of magnesium pyrophosphate and color changes. The photon number decreases during the amplification process. The CMOS image sensor observes the photons and converts into digital units with the aid of an analog-to-digital converter (ADC). In addition, UV-spectral studies, optical color intensity detection, pH analysis, and electrophoresis detection were carried out to prove the efficiency of the CMOS sensor based the LAMP system. Moreover, Clostridium perfringens was utilized as proof-of-concept detection for the new system. We anticipate that this CMOS image sensor-based LAMP method will enable the creation of cost-effective, label-free, optical, real-time and portable molecular diagnostic devices.

Cost-effective sampling of (137)Cs-derived net soil redistribution: part 2 - estimating the spatial mean change over time.

PubMed

Chappell, A; Li, Y; Yu, H Q; Zhang, Y Z; Li, X Y

2015-06-01

The caesium-137 ((137)Cs) technique for estimating net, time-integrated soil redistribution by the processes of wind, water and tillage is increasingly being used with repeated sampling to form a baseline to evaluate change over small (years to decades) timeframes. This interest stems from knowledge that since the 1950s soil redistribution has responded dynamically to different phases of land use change and management. Currently, there is no standard approach to detect change in (137)Cs-derived net soil redistribution and thereby identify the driving forces responsible for change. We outline recent advances in space-time sampling in the soil monitoring literature which provide a rigorous statistical and pragmatic approach to estimating the change over time in the spatial mean of environmental properties. We apply the space-time sampling framework, estimate the minimum detectable change of net soil redistribution and consider the information content and cost implications of different sampling designs for a study area in the Chinese Loess Plateau. Three phases (1954-1996, 1954-2012 and 1996-2012) of net soil erosion were detectable and attributed to well-documented historical change in land use and management practices in the study area and across the region. We recommend that the design for space-time sampling is considered carefully alongside cost-effective use of the spatial mean to detect and correctly attribute cause of change over time particularly across spatial scales of variation. Copyright © 2015 Elsevier Ltd. All rights reserved.

Mismatch negativity to acoustical illusion of beat: how and where the change detection takes place?

PubMed

Chakalov, Ivan; Paraskevopoulos, Evangelos; Wollbrink, Andreas; Pantev, Christo

2014-10-15

In case of binaural presentation of two tones with slightly different frequencies the structures of brainstem can no longer follow the interaural time differences (ITD) resulting in an illusionary perception of beat corresponding to frequency difference between the two prime tones. Hence, the beat-frequency does not exist in the prime tones presented to either ear. This study used binaural beats to explore the nature of acoustic deviance detection in humans by means of magnetoencephalography (MEG). Recent research suggests that the auditory change detection is a multistage process. To test this, we employed 26 Hz-binaural beats in a classical oddball paradigm. However, the prime tones (250 Hz and 276 Hz) were switched between the ears in the case of the deviant-beat. Consequently, when the deviant is presented, the cochleae and auditory nerves receive a "new afferent", although the standards and the deviants are heard identical (26 Hz-beats). This allowed us to explore the contribution of auditory periphery to change detection process, and furthermore, to evaluate its influence on beats-related auditory steady-state responses (ASSRs). LORETA-source current density estimates of the evoked fields in a typical mismatch negativity time-window (MMN) and the subsequent difference-ASSRs were determined and compared. The results revealed an MMN generated by a complex neural network including the right parietal lobe and the left middle frontal gyrus. Furthermore, difference-ASSR was generated in the paracentral gyrus. Additionally, psychophysical measures showed no perceptual difference between the standard- and deviant-beats when isolated by noise. These results suggest that the auditory periphery has an important contribution to novelty detection already at sub-cortical level. Overall, the present findings support the notion of hierarchically organized acoustic novelty detection system. Copyright © 2014 Elsevier Inc. All rights reserved.

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

Coble, Jamie; Orton, Christopher; Schwantes, Jon

Abstract—The Multi-Isotope Process (MIP) Monitor provides an efficient approach to monitoring the process conditions in used nuclear fuel reprocessing facilities to support process verification and validation. The MIP Monitor applies multivariate analysis to gamma spectroscopy of reprocessing streams in order to detect small changes in the gamma spectrum, which may indicate changes in process conditions. This research extends the MIP Monitor by characterizing a used fuel sample after initial dissolution according to the type of reactor of origin (pressurized or boiling water reactor), initial enrichment, burn up, and cooling time. Simulated gamma spectra were used to develop and test threemore » fuel characterization algorithms. The classification and estimation models employed are based on the partial least squares regression (PLS) algorithm. A PLS discriminate analysis model was developed which perfectly classified reactor type. Locally weighted PLS models were fitted on-the-fly to estimate continuous fuel characteristics. Burn up was predicted within 0.1% root mean squared percent error (RMSPE) and both cooling time and initial enrichment within approximately 2% RMSPE. This automated fuel characterization can be used to independently verify operator declarations of used fuel characteristics and inform the MIP Monitor anomaly detection routines at later stages of the fuel reprocessing stream to improve sensitivity to changes in operational parameters and material diversions.« less

Trial-Level Regressor Modulation for Functional Magnetic Resonance Imaging Designs Requiring Strict Periodicity of Stimulus Presentations: Illustrated Using a Go/No-Go Task

PubMed Central

Motes, Michael A; Rao, Neena K; Shokri-Kojori, Ehsan; Chiang, Hsueh-Sheng; Kraut, Michael A; Hart, John

2017-01-01

Computer-based assessment of many cognitive processes (eg, anticipatory and response readiness processes) requires the use of invariant stimulus display times (SDT) and intertrial intervals (ITI). Although designs with invariant SDTs and ITIs have been used in functional magnetic resonance imaging (fMRI) research, such designs are problematic for fMRI studies because of collinearity issues. This study examined regressor modulation with trial-level reaction times (RT) as a method for improving signal detection in a go/no-go task with invariant SDTs and ITIs. The effects of modulating the go regressor were evaluated with respect to the detection of BOLD signal-change for the no-go condition. BOLD signal-change to no-go stimuli was examined when the go regressor was based on a (a) canonical hemodynamic response function (HRF), (b) RT-based amplitude-modulated (AM) HRF, and (c) RT-based amplitude and duration modulated (A&DM) HRF. Reaction time–based modulation reduced the collinearity between the go and no-go regressors, with A&DM producing the greatest reductions in correlations between the regressors, and greater reductions in the correlations between regressors were associated with longer mean RTs and greater RT variability. Reaction time–based modulation increased statistical power for detecting group-level no-go BOLD signal-change across a broad set of brain regions. The findings show the efficacy of using regressor modulation to increase power in detecting BOLD signal-change in fMRI studies in which circumstances dictate the use of temporally invariant stimulus presentations. PMID:29276390

Trial-Level Regressor Modulation for Functional Magnetic Resonance Imaging Designs Requiring Strict Periodicity of Stimulus Presentations: Illustrated Using a Go/No-Go Task.

PubMed

Motes, Michael A; Rao, Neena K; Shokri-Kojori, Ehsan; Chiang, Hsueh-Sheng; Kraut, Michael A; Hart, John

2017-01-01

Computer-based assessment of many cognitive processes (eg, anticipatory and response readiness processes) requires the use of invariant stimulus display times (SDT) and intertrial intervals (ITI). Although designs with invariant SDTs and ITIs have been used in functional magnetic resonance imaging (fMRI) research, such designs are problematic for fMRI studies because of collinearity issues. This study examined regressor modulation with trial-level reaction times (RT) as a method for improving signal detection in a go / no-go task with invariant SDTs and ITIs. The effects of modulating the go regressor were evaluated with respect to the detection of BOLD signal-change for the no-go condition. BOLD signal-change to no-go stimuli was examined when the go regressor was based on a (a) canonical hemodynamic response function (HRF), (b) RT-based amplitude-modulated (AM) HRF, and (c) RT-based amplitude and duration modulated (A&DM) HRF. Reaction time-based modulation reduced the collinearity between the go and no-go regressors, with A&DM producing the greatest reductions in correlations between the regressors, and greater reductions in the correlations between regressors were associated with longer mean RTs and greater RT variability. Reaction time-based modulation increased statistical power for detecting group-level no-go BOLD signal-change across a broad set of brain regions. The findings show the efficacy of using regressor modulation to increase power in detecting BOLD signal-change in fMRI studies in which circumstances dictate the use of temporally invariant stimulus presentations.

Automatic Detection of Storm Damages Using High-Altitude Photogrammetric Imaging

NASA Astrophysics Data System (ADS)

Litkey, P.; Nurminen, K.; Honkavaara, E.

2013-05-01

The risks of storms that cause damage in forests are increasing due to climate change. Quickly detecting fallen trees, assessing the amount of fallen trees and efficiently collecting them are of great importance for economic and environmental reasons. Visually detecting and delineating storm damage is a laborious and error-prone process; thus, it is important to develop cost-efficient and highly automated methods. Objective of our research project is to investigate and develop a reliable and efficient method for automatic storm damage detection, which is based on airborne imagery that is collected after a storm. The requirements for the method are the before-storm and after-storm surface models. A difference surface is calculated using two DSMs and the locations where significant changes have appeared are automatically detected. In our previous research we used four-year old airborne laser scanning surface model as the before-storm surface. The after-storm DSM was provided from the photogrammetric images using the Next Generation Automatic Terrain Extraction (NGATE) algorithm of Socet Set software. We obtained 100% accuracy in detection of major storm damages. In this investigation we will further evaluate the sensitivity of the storm-damage detection process. We will investigate the potential of national airborne photography, that is collected at no-leaf season, to automatically produce a before-storm DSM using image matching. We will also compare impact of the terrain extraction algorithm to the results. Our results will also promote the potential of national open source data sets in the management of natural disasters.

Clustering analysis of moving target signatures

NASA Astrophysics Data System (ADS)

Martone, Anthony; Ranney, Kenneth; Innocenti, Roberto

2010-04-01

Previously, we developed a moving target indication (MTI) processing approach to detect and track slow-moving targets inside buildings, which successfully detected moving targets (MTs) from data collected by a low-frequency, ultra-wideband radar. Our MTI algorithms include change detection, automatic target detection (ATD), clustering, and tracking. The MTI algorithms can be implemented in a real-time or near-real-time system; however, a person-in-the-loop is needed to select input parameters for the clustering algorithm. Specifically, the number of clusters to input into the cluster algorithm is unknown and requires manual selection. A critical need exists to automate all aspects of the MTI processing formulation. In this paper, we investigate two techniques that automatically determine the number of clusters: the adaptive knee-point (KP) algorithm and the recursive pixel finding (RPF) algorithm. The KP algorithm is based on a well-known heuristic approach for determining the number of clusters. The RPF algorithm is analogous to the image processing, pixel labeling procedure. Both algorithms are used to analyze the false alarm and detection rates of three operational scenarios of personnel walking inside wood and cinderblock buildings.

Higher Throughput Calorimetry: Opportunities, Approaches and Challenges

PubMed Central

Recht, Michael I.; Coyle, Joseph E.; Bruce, Richard H.

2010-01-01

Higher throughput thermodynamic measurements can provide value in structure-based drug discovery during fragment screening, hit validation, and lead optimization. Enthalpy can be used to detect and characterize ligand binding, and changes that affect the interaction of protein and ligand can sometimes be detected more readily from changes in the enthalpy of binding than from the corresponding free-energy changes or from protein-ligand structures. Newer, higher throughput calorimeters are being incorporated into the drug discovery process. Improvements in titration calorimeters come from extensions of a mature technology and face limitations in scaling. Conversely, array calorimetry, an emerging technology, shows promise for substantial improvements in throughput and material utilization, but improved sensitivity is needed. PMID:20888754

Stress Analyzer

NASA Technical Reports Server (NTRS)

1990-01-01

SPATE 900 Dynamic Stress Analyzer is an acronym for Stress Pattern Analysis by Thermal Emission. It detects stress-induced temperature changes in a structure and indicates the degree of stress. Ometron, Inc.'s SPATE 9000 consists of a scan unit and a data display. The scan unit contains an infrared channel focused on the test structure to collect thermal radiation, and a visual channel used to set up the scan area and interrogate the stress display. Stress data is produced by detecting minute temperature changes, down to one-thousandth of a degree Centigrade, resulting from the application to the structure of dynamic loading. The electronic data processing system correlates the temperature changes with a reference signal to determine stress level.

The analysis of the pilot's cognitive and decision processes

NASA Technical Reports Server (NTRS)

Curry, R. E.

1975-01-01

Articles are presented on pilot performance in zero-visibility precision approach, failure detection by pilots during automatic landing, experiments in pilot decision-making during simulated low visibility approaches, a multinomial maximum likelihood program, and a random search algorithm for laboratory computers. Other topics discussed include detection of system failures in multi-axis tasks and changes in pilot workload during an instrument landing.

Role of EEG as Biomarker in the Early Detection and Classification of Dementia

PubMed Central

Al-Qazzaz, Noor Kamal; Ali, Sawal Hamid Bin MD.; Ahmad, Siti Anom; Chellappan, Kalaivani; Islam, Md. Shabiul; Escudero, Javier

2014-01-01

The early detection and classification of dementia are important clinical support tasks for medical practitioners in customizing patient treatment programs to better manage the development and progression of these diseases. Efforts are being made to diagnose these neurodegenerative disorders in the early stages. Indeed, early diagnosis helps patients to obtain the maximum treatment benefit before significant mental decline occurs. The use of electroencephalogram as a tool for the detection of changes in brain activities and clinical diagnosis is becoming increasingly popular for its capabilities in quantifying changes in brain degeneration in dementia. This paper reviews the role of electroencephalogram as a biomarker based on signal processing to detect dementia in early stages and classify its severity. The review starts with a discussion of dementia types and cognitive spectrum followed by the presentation of the effective preprocessing denoising to eliminate possible artifacts. It continues with a description of feature extraction by using linear and nonlinear techniques, and it ends with a brief explanation of vast variety of separation techniques to classify EEG signals. This paper also provides an idea from the most popular studies that may help in diagnosing dementia in early stages and classifying through electroencephalogram signal processing and analysis. PMID:25093211

Role of EEG as biomarker in the early detection and classification of dementia.

PubMed

Al-Qazzaz, Noor Kamal; Ali, Sawal Hamid Bin Md; Ahmad, Siti Anom; Chellappan, Kalaivani; Islam, Md Shabiul; Escudero, Javier

2014-01-01

The early detection and classification of dementia are important clinical support tasks for medical practitioners in customizing patient treatment programs to better manage the development and progression of these diseases. Efforts are being made to diagnose these neurodegenerative disorders in the early stages. Indeed, early diagnosis helps patients to obtain the maximum treatment benefit before significant mental decline occurs. The use of electroencephalogram as a tool for the detection of changes in brain activities and clinical diagnosis is becoming increasingly popular for its capabilities in quantifying changes in brain degeneration in dementia. This paper reviews the role of electroencephalogram as a biomarker based on signal processing to detect dementia in early stages and classify its severity. The review starts with a discussion of dementia types and cognitive spectrum followed by the presentation of the effective preprocessing denoising to eliminate possible artifacts. It continues with a description of feature extraction by using linear and nonlinear techniques, and it ends with a brief explanation of vast variety of separation techniques to classify EEG signals. This paper also provides an idea from the most popular studies that may help in diagnosing dementia in early stages and classifying through electroencephalogram signal processing and analysis.

Modular fluorescence complementation sensors for live cell detection of epigenetic signals at endogenous genomic sites.

PubMed

Lungu, Cristiana; Pinter, Sabine; Broche, Julian; Rathert, Philipp; Jeltsch, Albert

2017-09-21

Investigation of the fundamental role of epigenetic processes requires methods for the locus-specific detection of epigenetic modifications in living cells. Here, we address this urgent demand by developing four modular fluorescence complementation-based epigenetic biosensors for live-cell microscopy applications. These tools combine engineered DNA-binding proteins with domains recognizing defined epigenetic marks, both fused to non-fluorescent fragments of a fluorescent protein. The presence of the epigenetic mark at the target DNA sequence leads to the reconstitution of a functional fluorophore. With this approach, we could for the first time directly detect DNA methylation and histone 3 lysine 9 trimethylation at endogenous genomic sites in live cells and follow dynamic changes in these marks upon drug treatment, induction of epigenetic enzymes and during the cell cycle. We anticipate that this versatile technology will improve our understanding of how specific epigenetic signatures are set, erased and maintained during embryonic development or disease onset.Tools for imaging epigenetic modifications can shed light on the regulation of epigenetic processes. Here, the authors present a fluorescence complementation approach for detection of DNA and histone methylation at endogenous genomic sites allowing following of dynamic changes of these marks by live-cell microscopy.

Quantifying landscape change in an arctic coastal lowland using repeat airborne LiDAR

USGS Publications Warehouse

Jones, Benjamin M.; Stoker, Jason M.; Gibbs, Ann E.; Grosse, Guido; Romanovsky, Vladimir E.; Douglas, Thomas A.; Kinsman, Nichole E.M.; Richmond, Bruce M.

2013-01-01

Increases in air, permafrost, and sea surface temperature, loss of sea ice, the potential for increased wave energy, and higher river discharge may all be interacting to escalate erosion of arctic coastal lowland landscapes. Here we use airborne light detection and ranging (LiDAR) data acquired in 2006 and 2010 to detect landscape change in a 100 km2 study area on the Beaufort Sea coastal plain of northern Alaska. We detected statistically significant change (99% confidence interval), defined as contiguous areas (>10 m2) that had changed in height by at least 0.55 m, in 0.3% of the study region. Erosional features indicative of ice-rich permafrost degradation were associated with ice-bonded coastal, river, and lake bluffs, frost mounds, ice wedges, and thermo-erosional gullies. These features accounted for about half of the area where vertical change was detected. Inferred thermo-denudation and thermo-abrasion of coastal and river bluffs likely accounted for the dominant permafrost-related degradational processes with respect to area (42%) and volume (51%). More than 300 thermokarst pits significantly subsided during the study period, likely as a result of storm surge flooding of low-lying tundra (<1.4 m asl) as well as the lasting impact of warm summers in the late-1980s and mid-1990s. Our results indicate that repeat airborne LiDAR can be used to detect landscape change in arctic coastal lowland regions at large spatial scales over sub-decadal time periods.

Monitoring change in mountainous dry-heath vegetation at a regional scale using multitemporal Landsat TM data.

PubMed

Nordberg, Maj-Liz; Evertson, Joakim

2003-12-01

Vegetation cover-change analysis requires selection of an appropriate set of variables for measuring and characterizing change. Satellite sensors like Landsat TM offer the advantages of wide spatial coverage while providing land-cover information. This facilitates the monitoring of surface processes. This study discusses change detection in mountainous dry-heath communities in Jämtland County, Sweden, using satellite data. Landsat-5 TM and Landsat-7 ETM+ data from 1984, 1994 and 2000, respectively, were used. Different change detection methods were compared after the images had been radiometrically normalized, georeferenced and corrected for topographic effects. For detection of the classes change--no change the NDVI image differencing method was the most accurate with an overall accuracy of 94% (K = 0.87). Additional change information was extracted from an alternative method called NDVI regression analysis and vegetation change in 3 categories within mountainous dry-heath communities were detected. By applying a fuzzy set thresholding technique the overall accuracy was improved from of 65% (K = 0.45) to 74% (K = 0.59). The methods used generate a change product showing the location of changed areas in sensitive mountainous heath communities, and it also indicates the extent of the change (high, moderate and unchanged vegetation cover decrease). A total of 17% of the dry and extremely dry-heath vegetation within the study area has changed between 1984 and 2000. On average 4% of the studied heath communities have been classified as high change, i.e. have experienced "high vegetation cover decrease" during the period. The results show that the low alpine zone of the southern part of the study area shows the highest amount of "high vegetation cover decrease". The results also show that the main change occurred between 1994 and 2000.

Evaluation of short-term changes of hydrological response in mountainous basins of the Vitim Plateau (Russia) after forest fires based on data analysis and hydrological modelling

NASA Astrophysics Data System (ADS)

Semenova, O. M.; Lebedeva, L. S.; Nesterova, N. V.; Vinogradova, T. A.

2015-06-01

Twelve mountainous basins of the Vitim Plateau (Eastern Siberia, Russia) with areas ranging from 967 to 18 200 km2 affected by extensive fires in 2003 (from 13 to 78% of burnt area) were delineated based on MODIS Burned Area Product. The studied area is characterized by scarcity of hydrometeorological observations and complex hydrological processes. Combined analysis of monthly series of flow and precipitation was conducted to detect short-term fire impact on hydrological response of the basins. The idea of basin-analogues which have significant correlation of flow with "burnt" watersheds in stationary (pre-fire) period with the assumption that fire impact produced an outlier of established dependence was applied. Available data allowed for qualitative detection of fire-induced changes at two basins from twelve studied. Summer flow at the Amalat and Vitimkan Rivers (22 and 78% proportion of burnt area in 2003, respectively) increased by 40-50% following the fire.The impact of fire on flow from the other basins was not detectable.The hydrological model Hydrograph was applied to simulate runoff formation processes for stationary pre-fire and non-stationary post-fire conditions. It was assumed that landscape properties changed after the fire suggest a flow increase. These changes were used to assess the model parameters which allowed for better model performance in the post-fire period.

Automatic detection of slight parameter changes associated to complex biomedical signals using multiresolution q-entropy1.

PubMed

Torres, M E; Añino, M M; Schlotthauer, G

2003-12-01

It is well known that, from a dynamical point of view, sudden variations in physiological parameters which govern certain diseases can cause qualitative changes in the dynamics of the corresponding physiological process. The purpose of this paper is to introduce a technique that allows the automated temporal localization of slight changes in a parameter of the law that governs the nonlinear dynamics of a given signal. This tool takes, from the multiresolution entropies, the ability to show these changes as statistical variations at each scale. These variations are held in the corresponding principal component. Appropriately combining these techniques with a statistical changes detector, a complexity change detection algorithm is obtained. The relevance of the approach, together with its robustness in the presence of moderate noise, is discussed in numerical simulations and the automatic detector is applied to real and simulated biological signals.

Automatic Detection of Optic Disc in Retinal Image by Using Keypoint Detection, Texture Analysis, and Visual Dictionary Techniques

PubMed Central

Bayır, Şafak

2016-01-01

With the advances in the computer field, methods and techniques in automatic image processing and analysis provide the opportunity to detect automatically the change and degeneration in retinal images. Localization of the optic disc is extremely important for determining the hard exudate lesions or neovascularization, which is the later phase of diabetic retinopathy, in computer aided eye disease diagnosis systems. Whereas optic disc detection is fairly an easy process in normal retinal images, detecting this region in the retinal image which is diabetic retinopathy disease may be difficult. Sometimes information related to optic disc and hard exudate information may be the same in terms of machine learning. We presented a novel approach for efficient and accurate localization of optic disc in retinal images having noise and other lesions. This approach is comprised of five main steps which are image processing, keypoint extraction, texture analysis, visual dictionary, and classifier techniques. We tested our proposed technique on 3 public datasets and obtained quantitative results. Experimental results show that an average optic disc detection accuracy of 94.38%, 95.00%, and 90.00% is achieved, respectively, on the following public datasets: DIARETDB1, DRIVE, and ROC. PMID:27110272

Land-cover change detection

USGS Publications Warehouse

Chen, Xuexia; Giri, Chandra; Vogelmann, James

2012-01-01

Land cover is the biophysical material on the surface of the earth. Land-cover types include grass, shrubs, trees, barren, water, and man-made features. Land cover changes continuously.  The rate of change can be either dramatic and abrupt, such as the changes caused by logging, hurricanes and fire, or subtle and gradual, such as regeneration of forests and damage caused by insects (Verbesselt et al., 2001).  Previous studies have shown that land cover has changed dramatically during the past sevearal centuries and that these changes have severely affected our ecosystems (Foody, 2010; Lambin et al., 2001). Lambin and Strahlers (1994b) summarized five types of cause for land-cover changes: (1) long-term natural changes in climate conditions, (2) geomorphological and ecological processes, (3) human-induced alterations of vegetation cover and landscapes, (4) interannual climate variability, and (5) human-induced greenhouse effect.  Tools and techniques are needed to detect, describe, and predict these changes to facilitate sustainable management of natural resources.

Pitch Processing in Tonal-Language-Speaking Children with Autism: An Event-Related Potential Study

ERIC Educational Resources Information Center

Yu, Luodi; Fan, Yuebo; Deng, Zhizhou; Huang, Dan; Wang, Suiping; Zhang, Yang

2015-01-01

The present study investigated pitch processing in Mandarin-speaking children with autism using event-related potential measures. Two experiments were designed to test how acoustic, phonetic and semantic properties of the stimuli contributed to the neural responses for pitch change detection and involuntary attentional orienting. In comparison…

Multi-temporal database of High Resolution Stereo Camera (HRSC) images - Alpha version

NASA Astrophysics Data System (ADS)

Erkeling, G.; Luesebrink, D.; Hiesinger, H.; Reiss, D.; Jaumann, R.

2014-04-01

Image data transmitted to Earth by Martian spacecraft since the 1970s, for example by Mariner and Viking, Mars Global Surveyor (MGS), Mars Express (MEx) and the Mars Reconnaissance Orbiter (MRO) showed, that the surface of Mars has changed dramatically and actually is continually changing [e.g., 1-8]. The changes are attributed to a large variety of atmospherical, geological and morphological processes, including eolian processes [9,10], mass wasting processes [11], changes of the polar caps [12] and impact cratering processes [13]. In addition, comparisons between Mariner, Viking and Mars Global Surveyor images suggest that more than one third of the Martian surface has brightened or darkened by at least 10% [6]. Albedo changes can have effects on the global heat balance and the circulation of winds, which can result in further surface changes [14-15]. The High Resolution Stereo Camera (HRSC) [16,17] on board Mars Express (MEx) covers large areas at high resolution and is therefore suited to detect the frequency, extent and origin of Martian surface changes. Since 2003 HRSC acquires highresolution images of the Martian surface and contributes to Martian research, with focus on the surface morphology, the geology and mineralogy, the role of liquid water on the surface and in the atmosphere, on volcanism, as well as on the proposed climate change throughout the Martian history and has improved our understanding of the evolution of Mars significantly [18-21]. The HRSC data are available at ESA's Planetary Science Archive (PSA) as well as through the NASA Planetary Data System (PDS). Both data platforms are frequently used by the scientific community and provide additional software and environments to further generate map-projected and geometrically calibrated HRSC data. However, while previews of the images are available, there is no possibility to quickly and conveniently see the spatial and temporal availability of HRSC images in a specific region, which is important to detect the surface changes that occurred between two or more images.

How mechanisms of perceptual decision-making affect the psychometric function

PubMed Central

Gold, Joshua I.; Ding, Long

2012-01-01

Psychometric functions are often interpreted in the context of Signal Detection Theory, which emphasizes a distinction between sensory processing and non-sensory decision rules in the brain. This framework has helped to relate perceptual sensitivity to the “neurometric” sensitivity of sensory-driven neural activity. However, perceptual sensitivity, as interpreted via Signal Detection Theory, is based on not just how the brain represents relevant sensory information, but also how that information is read out to form the decision variable to which the decision rule is applied. Here we discuss recent advances in our understanding of this readout process and describe its effects on the psychometric function. In particular, we show that particular aspects of the readout process can have specific, identifiable effects on the threshold, slope, upper asymptote, time dependence, and choice dependence of psychometric functions. To illustrate these points, we emphasize studies of perceptual learning that have identified changes in the readout process that can lead to changes in these aspects of the psychometric function. We also discuss methods that have been used to distinguish contributions of the sensory representation versus its readout to psychophysical performance. PMID:22609483

Color is processed less efficiently than orientation in change detection but more efficiently in visual search.

PubMed

Huang, Liqiang

2015-05-01

Basic visual features (e.g., color, orientation) are assumed to be processed in the same general way across different visual tasks. Here, a significant deviation from this assumption was predicted on the basis of the analysis of stimulus spatial structure, as characterized by the Boolean-map notion. If a task requires memorizing the orientations of a set of bars, then the map consisting of those bars can be readily used to hold the overall structure in memory and will thus be especially useful. If the task requires visual search for a target, then the map, which contains only an overall structure, will be of little use. Supporting these predictions, the present study demonstrated that in comparison to stimulus colors, bar orientations were processed more efficiently in change-detection tasks but less efficiently in visual search tasks (Cohen's d = 4.24). In addition to offering support for the role of the Boolean map in conscious access, the present work also throws doubts on the generality of processing visual features. © The Author(s) 2015.

Ten Years of Land Cover Change on the California Coast Detected using Landsat Satellite Image Analysis

NASA Technical Reports Server (NTRS)

Potter, Christopher S.

2013-01-01

Landsat satellite imagery was analyzed to generate a detailed record of 10 years of vegetation disturbance and regrowth for Pacific coastal areas of Marin and San Francisco Counties. The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) methodology, a transformation of Tasseled-Cap data space, was applied to detected changes in perennial coastal shrubland, woodland, and forest cover from 1999 to 2009. Results showed several principal points of interest, within which extensive contiguous areas of similar LEDAPS vegetation change (either disturbed or restored) were detected. Regrowth areas were delineated as burned forest areas in the Point Reyes National Seashore (PRNS) from the 1995 Vision Fire. LEDAPS-detected disturbance patterns on Inverness Ridge, PRNS in areas observed with dieback of tanoak and bay laurel trees was consistent with defoliation by sudden oak death (Phytophthora ramorum). LEDAPS regrowth pixels were detected over much of the predominantly grassland/herbaceous cover of the Olema Valley ranchland near PRNS. Extensive restoration of perennial vegetation cover on Crissy Field, Baker Beach and Lobos Creek dunes in San Francisco was identified. Based on these examples, the LEDAPS methodology will be capable of fulfilling much of the need for continual, low-cost monitoring of emerging changes to coastal ecosystems.

Family History of Alzheimer's Disease is Associated with Impaired Perceptual Discrimination of Novel Objects.

PubMed

Mason, Emily J; Hussey, Erin P; Molitor, Robert J; Ko, Philip C; Donahue, Manus J; Ally, Brandon A

2017-01-01

Early detection may be the key to developing therapies that will combat Alzheimer's disease (AD). It has been consistently demonstrated that one of the main pathologies of AD, tau, is present in the brain decades before a clinical diagnosis. Tau pathology follows a stereotypical route through the medial temporal lobe beginning in the entorhinal and perirhinal cortices. If early pathology leads to very subtle changes in behavior, it may be possible to detect these changes in subjects years before a clinical diagnosis can currently be made. We aimed to discover if cognitively normal middle-aged adults (40-60 years old) at increased risk for AD due to family history would have impaired performance on a cognitive task known to challenge the perirhinal cortex. Using an oddity detection task, we found that subjects with a family history of AD had lowered accuracy without demonstrating differences in rate of acquisition. There were no differences between subjects' medial temporal lobe volume or cortical thickness, indicating that the changes in behavior were not due to significant atrophy. These results demonstrate that subtle changes in perceptual processing are detectable years before a typical diagnosis even when there are no differences detectable in structural imaging data. Anatomically-targeted cognitive testing may be useful in identifying subjects in the earliest stages of AD.

Change detection over Sokolov open-pit mining area, Czech Republic, using multi-temporal HyMAP data (2009-2010)

NASA Astrophysics Data System (ADS)

Adar, S.; Notesco, G.; Brook, A.; Livne, I.; Rojik, P.; Kopacková, V.; Zelenkova, K.; Misurec, J.; Bourguignon, A.; Chevrel, S.; Ehrler, C.; Fisher, C.; Hanus, J.; Shkolnisky, Y.; Ben Dor, E.

2011-11-01

Two HyMap images acquired over the same lignite open-pit mining site in Sokolov, Czech Republic, during the summers of 2009 and 2010 (12 months apart), were investigated in this study. The site selected for this research is one of three test sites (the others being in South Africa and Kyrgyzstan) within the framework of the EO-MINERS FP7 Project (http://www.eo-miners.eu). The goal of EO-MINERS is to "integrate new and existing Earth Observation tools to improve best practice in mining activities and to reduce the mining related environmental and societal footprint". Accordingly, the main objective of the current study was to develop hyperspectral-based means for the detection of small spectral changes and to relate these changes to possible degradation or reclamation indicators of the area under investigation. To ensure significant detection of small spectral changes, the temporal domain was investigated along with careful generation of reflectance information. Thus, intensive spectroradiometric ground measurements were carried out to ensure calibration and validation aspects during both overflights. The performance of these corrections was assessed using the Quality Indicators setup developed under a different FP7 project-EUFAR (http://www.eufar.net), which helped select the highest quality data for further work. This approach allows direct distinction of the real information from noise. The reflectance images were used as input for the application of spectral-based change-detection algorithms and indices to account for small and reliable changes. The related algorithms were then developed and applied on a pixel-by-pixel basis to map spectral changes over the space of a year. Using field spectroscopy and ground truth measurements on both overpass dates, it was possible to explain the results and allocate spatial kinetic processes of the environmental changes during the time elapsed between the flights. It was found, for instance, that significant spectral changes are capable of revealing mineral processes, vegetation status and soil formation long before these are apparent to the naked eye. Further study is being conducted under the above initiative to extend this approach to other mining areas worldwide and to improve the robustness of the developed algorithm.

Applications of a morphological scene change detection (MSCD) for visual leak and failure identification in process and chemical engineering

NASA Astrophysics Data System (ADS)

Tickle, Andrew J.; Harvey, Paul K.; Smith, Jeremy S.

2010-10-01

Morphological Scene Change Detection (MSCD) is a process typically tasked at detecting relevant changes in a guarded environment for security applications. This can be implemented on a Field Programmable Gate Array (FPGA) by a combination of binary differences based around exclusive-OR (XOR) gates, mathematical morphology and a crucial threshold setting. The additional ability to set up the system in virtually any location due to the FPGA makes it ideal for insertion into an autonomous mobile robot for patrol duties. However, security is not the only potential of this robust algorithm. This paper details how such a system can be used for the detection of leaks in piping for use in the process and chemical industries and could be deployed as stated in the above manner. The test substance in this work was water, which was pumped either as a liquid or as low pressure steam through a simple pipe configuration with holes at set points to simulate the leaks. These holes were situated randomly at either the center of a pipe (in order to simulate an impact to it) or at a joint or corner (to simulate a failed weld). Imagery of the resultant leaks, which were visualised as drips or the accumulation of steam, which where analysed using MATLAB to determine their pixel volume in order to calibrate the trigger for the MSCD. The triggering mechanism is adaptive to make it possible in theory for the type of leak to be determined by the number of pixels in the threshold of the image and a numerical output signal to state which of the leak situations is being observed. The system was designed using the DSP Builder package from Altera so that its graphical nature is easily comprehensible to the non-embedded system designer. Furthermore, all the data from the DSP Builder simulation underwent verification against MATLAB comparisons using the image processing toolbox in order to validate the results.

TU-C-BRE-05: Clinical Implications of AAA Commissioning Errors and Ability of Common Commissioning ' Credentialing Procedures to Detect Them

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

McVicker, A; Oldham, M; Yin, F

2014-06-15

Purpose: To test the ability of the TG-119 commissioning process and RPC credentialing to detect errors in the commissioning process for a commercial Treatment Planning System (TPS). Methods: We introduced commissioning errors into the commissioning process for the Anisotropic Analytical Algorithm (AAA) within the Eclipse TPS. We included errors in Dosimetric Leaf Gap (DLG), electron contamination, flattening filter material, and beam profile measurement with an inappropriately large farmer chamber (simulated using sliding window smoothing of profiles). We then evaluated the clinical impact of these errors on clinical intensity modulated radiation therapy (IMRT) plans (head and neck, low and intermediate riskmore » prostate, mesothelioma, and scalp) by looking at PTV D99, and mean and max OAR dose. Finally, for errors with substantial clinical impact we determined sensitivity of the RPC IMRT film analysis at the midpoint between PTV and OAR using a 4mm distance to agreement metric, and of a 7% TLD dose comparison. We also determined sensitivity of the 3 dose planes of the TG-119 C-shape IMRT phantom using gamma criteria of 3% 3mm. Results: The largest clinical impact came from large changes in the DLG with a change of 1mm resulting in up to a 5% change in the primary PTV D99. This resulted in a discrepancy in the RPC TLDs in the PTVs and OARs of 7.1% and 13.6% respectively, which would have resulted in detection. While use of incorrect flattening filter caused only subtle errors (<1%) in clinical plans, the effect was most pronounced for the RPC TLDs in the OARs (>6%). Conclusion: The AAA commissioning process within the Eclipse TPS is surprisingly robust to user error. When errors do occur, the RPC and TG-119 commissioning credentialing criteria are effective at detecting them; however OAR TLDs are the most sensitive despite the RPC currently excluding them from analysis.« less

Remote detection of mental workload changes using cardiac parameters assessed with a low-cost webcam.

PubMed

Bousefsaf, Frédéric; Maaoui, Choubeila; Pruski, Alain

2014-10-01

We introduce a new framework for detecting mental workload changes using video frames obtained from a low-cost webcam. Image processing in addition to a continuous wavelet transform filtering method were developed and applied to remove major artifacts and trends on raw webcam photoplethysmographic signals. The measurements are performed on human faces. To induce stress, we have employed a computerized and interactive Stroop color word test on a set composed by twelve participants. The electrodermal activity of the participants was recorded and compared to the mental workload curve assessed by merging two parameters derived from the pulse rate variability and photoplethysmographic amplitude fluctuations, which reflect peripheral vasoconstriction changes. The results exhibit strong correlation between the two measurement techniques. This study offers further support for the applicability of mental workload detection by remote and low-cost means, providing an alternative to conventional contact techniques. Copyright © 2014 Elsevier Ltd. All rights reserved.

First experience with Remote Sensing methods and selected sensors in the monitoring of mining areas - a case study of the Belchatow open cast mine

NASA Astrophysics Data System (ADS)

Wajs, Jaroslaw

2018-01-01

The paper presents satellite imagery from active SENTINEL-1A and passive SENTINEL-2A/2B sensors for their application in the monitoring of mining areas focused on detecting land changes. Multispectral scenes of SENTINEL-2A/2B have allowed for detecting changes in land-cover near the region of interest (ROI), i.e. the Szczercow dumping site in the Belchatow open cast lignite mine, central Poland, Europe. Scenes from SENTINEL-1A/1B satellite have also been used in the research. Processing of the SLC signal enabled creating a return intensity map in VV polarization. The obtained SAR scene was reclassified and shows a strong return signal from the dumping site and the open pit. This fact may be used in detection and monitoring of changes occurring within the analysed engineering objects.

Temporally selective attention modulates early perceptual processing: event-related potential evidence.

PubMed

Sanders, Lisa D; Astheimer, Lori B

2008-05-01

Some of the most important information we encounter changes so rapidly that our perceptual systems cannot process all of it in detail. Spatially selective attention is critical for perception when more information than can be processed in detail is presented simultaneously at distinct locations. When presented with complex, rapidly changing information, listeners may need to selectively attend to specific times rather than to locations. We present evidence that listeners can direct selective attention to time points that differ by as little as 500 msec, and that doing so improves target detection, affects baseline neural activity preceding stimulus presentation, and modulates auditory evoked potentials at a perceptually early stage. These data demonstrate that attentional modulation of early perceptual processing is temporally precise and that listeners can flexibly allocate temporally selective attention over short intervals, making it a viable mechanism for preferentially processing the most relevant segments in rapidly changing streams.

Testing the implicit processing hypothesis of precognitive dream experience.

PubMed

Valášek, Milan; Watt, Caroline; Hutton, Jenny; Neill, Rebecca; Nuttall, Rachel; Renwick, Grace

2014-08-01

Seemingly precognitive (prophetic) dreams may be a result of one's unconscious processing of environmental cues and having an implicit inference based on these cues manifest itself in one's dreams. We present two studies exploring this implicit processing hypothesis of precognitive dream experience. Study 1 investigated the relationship between implicit learning, transliminality, and precognitive dream belief and experience. Participants completed the Serial Reaction Time task and several questionnaires. We predicted a positive relationship between the variables. With the exception of relationships between transliminality and precognitive dream belief and experience, this prediction was not supported. Study 2 tested the hypothesis that differences in the ability to notice subtle cues explicitly might account for precognitive dream beliefs and experiences. Participants completed a modified version of the flicker paradigm. We predicted a negative relationship between the ability to explicitly detect changes and precognitive dream variables. This relationship was not found. There was also no relationship between precognitive dream belief and experience and implicit change detection. Copyright © 2014 Elsevier Inc. All rights reserved.

A Consensus Approach to Investigate Undergraduate Pharmacy Students’ Experience of Interprofessional Education

PubMed Central

Obara, Ilona; Paterson, Alastair; Nazar, Zachariah; Portlock, Jane; Husband, Andrew

2017-01-01

Objective. To assess the development of knowledge, attitudes, and behaviors for collaborative practice among first-year pharmacy students following completion of interprofessional education. Methods. A mixed-methods strategy was employed to detect student self-reported change in knowledge, attitudes, and behaviors. Validated survey tools were used to assess student perception and attitudes. The Nominal Group Technique (NGT) was used to capture student reflections and provide peer discussion on the individual IPE sessions. Results. The validated survey tools did not detect any change in students’ attitudes and perceptions. The NGT succeeded in providing a milieu for participating students to reflect on their IPE experiences. The peer review process allowed students to compare their initial perceptions and reactions and renew their reflections on the learning experience. Conclusion. The NGT process has provided the opportunity to assess the student experience through the reflective process that was enriched via peer discussion. Students have demonstrated more positive attitudes and behaviors toward interprofessional working through IPE. PMID:28381886

Label-free visualization of collagen in submucosa as a potential diagnostic marker for early detection of colorectal cancer

NASA Astrophysics Data System (ADS)

Qiu, Jingting; Yang, Yinghong; Jiang, Weizhong; Feng, Changyin; Chen, Zhifen; Guan, Guoxian; Zhu, Xiaoqin; Zhuo, Shuangmu; Chen, Jianxin

2014-09-01

The collagen signature in colorectal submucosa is changed due to remodeling of the extracellular matrix during the malignant process and plays an important role in noninvasive early detection of human colorectal cancer. In this work, multiphoton microscopy (MPM) was used to monitor the changes of collagen in normal colorectal submucosa (NCS) and cancerous colorectal submucosa (CCS). What's more, the collagen content was quantitatively measured. It was found that in CCS the morphology of collagen becomes much looser and the collagen content is significantly reduced compared to NCS. These results suggest that MPM has the ability to provide collagen signature as a potential diagnostic marker for early detection of colorectal cancer.

Low-Rank Matrix Recovery Approach for Clutter Rejection in Real-Time IR-UWB Radar-Based Moving Target Detection

PubMed Central

Sabushimike, Donatien; Na, Seung You; Kim, Jin Young; Bui, Ngoc Nam; Seo, Kyung Sik; Kim, Gil Gyeom

2016-01-01

The detection of a moving target using an IR-UWB Radar involves the core task of separating the waves reflected by the static background and by the moving target. This paper investigates the capacity of the low-rank and sparse matrix decomposition approach to separate the background and the foreground in the trend of UWB Radar-based moving target detection. Robust PCA models are criticized for being batched-data-oriented, which makes them inconvenient in realistic environments where frames need to be processed as they are recorded in real time. In this paper, a novel method based on overlapping-windows processing is proposed to cope with online processing. The method consists of processing a small batch of frames which will be continually updated without changing its size as new frames are captured. We prove that RPCA (via its Inexact Augmented Lagrange Multiplier (IALM) model) can successfully separate the two subspaces, which enhances the accuracy of target detection. The overlapping-windows processing method converges on the optimal solution with its batch counterpart (i.e., processing batched data with RPCA), and both methods prove the robustness and efficiency of the RPCA over the classic PCA and the commonly used exponential averaging method. PMID:27598159

Fiber optic fluid detector

DOEpatents

Angel, S. Michael

1989-01-01

Particular gases or liquids are detected with a fiber optic element (11, 11a to 11j) having a cladding or coating of a material (23, 23a to 23j) which absorbs the fluid or fluids and which exhibits a change of an optical property, such as index of refraction, light transmissiveness or fluoresence emission, for example, in response to absorption of the fluid. The fluid is sensed by directing light into the fiber optic element and detecting changes in the light, such as exit angle changes for example, that result from the changed optical property of the coating material. The fluid detector (24, 24a to 24j) may be used for such purposes as sensing toxic or explosive gases in the atmosphere, measuring ground water contamination or monitoring fluid flows in industrial processes, among other uses.

Selective and reusable iron(II)-based molecular sensor for the vapor-phase detection of alcohols.

PubMed

Naik, Anil D; Robeyns, Koen; Meunier, Christophe F; Léonard, Alexandre F; Rotaru, Aurelian; Tinant, Bernard; Filinchuk, Yaroslav; Su, Bao Lian; Garcia, Yann

2014-02-03

A mononuclear iron(II) neutral complex (1) is screened for sensing abilities for a wide spectrum of chemicals and to evaluate the response function toward physical perturbation like temperature and mechanical stress. Interestingly, 1 precisely detects methanol among an alcohol series. The sensing process is visually detectable, fatigue-resistant, highly selective, and reusable. The sensing ability is attributed to molecular sieving and subsequent spin-state change of iron centers, after a crystal-to-crystal transformation.

Early Detection of Breast Cancer by Using Handycam Camera Manipulation as Thermal Camera Imaging with Images Processing Method

NASA Astrophysics Data System (ADS)

Riantana, R.; Arie, B.; Adam, M.; Aditya, R.; Nuryani; Yahya, I.

2017-02-01

One important thing to pay attention for detecting breast cancer is breast temperature changes. Indications symptoms of breast tissue abnormalities marked by a rise in temperature of the breast. Handycam in night vision mode interferences by external infrared can penetrate into the skin better and can make an infrared image becomes clearer. The program is capable to changing images from a camcorder into a night vision thermal image by breaking RGB into Grayscale matrix structure. The matrix rearranged in the new matrix with double data type so that it can be processed into contour color chart to differentiate the distribution of body temperature. In this program are also features of contrast scale setting of the image is processed so that the color can be set as desired. There was Also a contrast adjustment feature inverse scale that is useful to reverse the color scale so that colors can be changed opposite. There is improfile function used to retrieves the intensity values of pixels along a line what we want to show the distribution of intensity in a graph of relationship between the intensity and the pixel coordinates.

Detecting regular sound changes in linguistics as events of concerted evolution

DOE PAGES

Hruschka, Daniel  J.; Branford, Simon; Smith, Eric  D.; ...

2014-12-18

Background: Concerted evolution is normally used to describe parallel changes at different sites in a genome, but it is also observed in languages where a specific phoneme changes to the same other phoneme in many words in the lexicon—a phenomenon known as regular sound change. We develop a general statistical model that can detect concerted changes in aligned sequence data and apply it to study regular sound changes in the Turkic language family. Results: Linguistic evolution, unlike the genetic substitutional process, is dominated by events of concerted evolutionary change. Our model identified more than 70 historical events of regular soundmore » change that occurred throughout the evolution of the Turkic language family, while simultaneously inferring a dated phylogenetic tree. Including regular sound changes yielded an approximately 4-fold improvement in the characterization of linguistic change over a simpler model of sporadic change, improved phylogenetic inference, and returned more reliable and plausible dates for events on the phylogenies. The historical timings of the concerted changes closely follow a Poisson process model, and the sound transition networks derived from our model mirror linguistic expectations. Conclusions: We demonstrate that a model with no prior knowledge of complex concerted or regular changes can nevertheless infer the historical timings and genealogical placements of events of concerted change from the signals left in contemporary data. Our model can be applied wherever discrete elements—such as genes, words, cultural trends, technologies, or morphological traits—can change in parallel within an organism or other evolving group.« less

Detecting regular sound changes in linguistics as events of concerted evolution.

PubMed

Hruschka, Daniel J; Branford, Simon; Smith, Eric D; Wilkins, Jon; Meade, Andrew; Pagel, Mark; Bhattacharya, Tanmoy

2015-01-05

Concerted evolution is normally used to describe parallel changes at different sites in a genome, but it is also observed in languages where a specific phoneme changes to the same other phoneme in many words in the lexicon—a phenomenon known as regular sound change. We develop a general statistical model that can detect concerted changes in aligned sequence data and apply it to study regular sound changes in the Turkic language family. Linguistic evolution, unlike the genetic substitutional process, is dominated by events of concerted evolutionary change. Our model identified more than 70 historical events of regular sound change that occurred throughout the evolution of the Turkic language family, while simultaneously inferring a dated phylogenetic tree. Including regular sound changes yielded an approximately 4-fold improvement in the characterization of linguistic change over a simpler model of sporadic change, improved phylogenetic inference, and returned more reliable and plausible dates for events on the phylogenies. The historical timings of the concerted changes closely follow a Poisson process model, and the sound transition networks derived from our model mirror linguistic expectations. We demonstrate that a model with no prior knowledge of complex concerted or regular changes can nevertheless infer the historical timings and genealogical placements of events of concerted change from the signals left in contemporary data. Our model can be applied wherever discrete elements—such as genes, words, cultural trends, technologies, or morphological traits—can change in parallel within an organism or other evolving group. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Detecting regular sound changes in linguistics as events of concerted evolution

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

Hruschka, Daniel  J.; Branford, Simon; Smith, Eric  D.

Background: Concerted evolution is normally used to describe parallel changes at different sites in a genome, but it is also observed in languages where a specific phoneme changes to the same other phoneme in many words in the lexicon—a phenomenon known as regular sound change. We develop a general statistical model that can detect concerted changes in aligned sequence data and apply it to study regular sound changes in the Turkic language family. Results: Linguistic evolution, unlike the genetic substitutional process, is dominated by events of concerted evolutionary change. Our model identified more than 70 historical events of regular soundmore » change that occurred throughout the evolution of the Turkic language family, while simultaneously inferring a dated phylogenetic tree. Including regular sound changes yielded an approximately 4-fold improvement in the characterization of linguistic change over a simpler model of sporadic change, improved phylogenetic inference, and returned more reliable and plausible dates for events on the phylogenies. The historical timings of the concerted changes closely follow a Poisson process model, and the sound transition networks derived from our model mirror linguistic expectations. Conclusions: We demonstrate that a model with no prior knowledge of complex concerted or regular changes can nevertheless infer the historical timings and genealogical placements of events of concerted change from the signals left in contemporary data. Our model can be applied wherever discrete elements—such as genes, words, cultural trends, technologies, or morphological traits—can change in parallel within an organism or other evolving group.« less

Detection of low-amplitude in vivo intrinsic signals from an optical imager of retinal function

NASA Astrophysics Data System (ADS)

Barriga, Eduardo S.; T'so, Dan; Pattichis, Marios; Kwon, Young; Kardon, Randy; Abramoff, Michael; Soliz, Peter

2006-02-01

In the early stages of some retinal diseases, such as glaucoma, loss of retinal activity may be difficult to detect with today's clinical instruments. Many of today's instruments focus on detecting changes in anatomical structures, such as the nerve fiber layer. Our device, which is based on a modified fundus camera, seeks to detect changes in optical signals that reflect functional changes in the retina. The functional imager uses a patterned stimulus at wavelength of 535nm. An intrinsic functional signal is collected at a near infrared wavelength. Measured changes in reflectance in response to the visual stimulus are on the order of 0.1% to 1% of the total reflected intensity level, which makes the functional signal difficult to detect by standard methods because it is masked by other physiological signals and by imaging system noise. In this paper, we analyze the video sequences from a set of 60 experiments with different patterned stimuli from cats. Using a set of statistical techniques known as Independent Component Analysis (ICA), we estimate the signals present in the videos. Through controlled simulation experiments, we quantify the limits of signal strength in order to detect the physiological signal of interest. The results of the analysis show that, in principle, signal levels of 0.1% (-30dB) can be detected. The study found that in 86% of the animal experiments the patterned stimuli effects on the retina can be detected and extracted. The analysis of the different responses extracted from the videos can give an insight of the functional processes present during the stimulation of the retina.

Volumetric Forest Change Detection Through Vhr Satellite Imagery

NASA Astrophysics Data System (ADS)

Akca, Devrim; Stylianidis, Efstratios; Smagas, Konstantinos; Hofer, Martin; Poli, Daniela; Gruen, Armin; Sanchez Martin, Victor; Altan, Orhan; Walli, Andreas; Jimeno, Elisa; Garcia, Alejandro

2016-06-01

Quick and economical ways of detecting of planimetric and volumetric changes of forest areas are in high demand. A research platform, called FORSAT (A satellite processing platform for high resolution forest assessment), was developed for the extraction of 3D geometric information from VHR (very-high resolution) imagery from satellite optical sensors and automatic change detection. This 3D forest information solution was developed during a Eurostars project. FORSAT includes two main units. The first one is dedicated to the geometric and radiometric processing of satellite optical imagery and 2D/3D information extraction. This includes: image radiometric pre-processing, image and ground point measurement, improvement of geometric sensor orientation, quasiepipolar image generation for stereo measurements, digital surface model (DSM) extraction by using a precise and robust image matching approach specially designed for VHR satellite imagery, generation of orthoimages, and 3D measurements in single images using mono-plotting and in stereo images as well as triplets. FORSAT supports most of the VHR optically imagery commonly used for civil applications: IKONOS, OrbView - 3, SPOT - 5 HRS, SPOT - 5 HRG, QuickBird, GeoEye-1, WorldView-1/2, Pléiades 1A/1B, SPOT 6/7, and sensors of similar type to be expected in the future. The second unit of FORSAT is dedicated to 3D surface comparison for change detection. It allows users to import digital elevation models (DEMs), align them using an advanced 3D surface matching approach and calculate the 3D differences and volume changes between epochs. To this end our 3D surface matching method LS3D is being used. FORSAT is a single source and flexible forest information solution with a very competitive price/quality ratio, allowing expert and non-expert remote sensing users to monitor forests in three and four dimensions from VHR optical imagery for many forest information needs. The capacity and benefits of FORSAT have been tested in six case studies located in Austria, Cyprus, Spain, Switzerland and Turkey, using optical data from different sensors and with the purpose to monitor forest with different geometric characteristics. The validation run on Cyprus dataset is reported and commented.

A robust object-based shadow detection method for cloud-free high resolution satellite images over urban areas and water bodies

NASA Astrophysics Data System (ADS)

Tatar, Nurollah; Saadatseresht, Mohammad; Arefi, Hossein; Hadavand, Ahmad

2018-06-01

Unwanted contrast in high resolution satellite images such as shadow areas directly affects the result of further processing in urban remote sensing images. Detecting and finding the precise position of shadows is critical in different remote sensing processing chains such as change detection, image classification and digital elevation model generation from stereo images. The spectral similarity between shadow areas, water bodies, and some dark asphalt roads makes the development of robust shadow detection algorithms challenging. In addition, most of the existing methods work on pixel-level and neglect the contextual information contained in neighboring pixels. In this paper, a new object-based shadow detection framework is introduced. In the proposed method a pixel-level shadow mask is built by extending established thresholding methods with a new C4 index which enables to solve the ambiguity of shadow and water bodies. Then the pixel-based results are further processed in an object-based majority analysis to detect the final shadow objects. Four different high resolution satellite images are used to validate this new approach. The result shows the superiority of the proposed method over some state-of-the-art shadow detection method with an average of 96% in F-measure.

An Adaptive Technique for a Redundant-Sensor Navigation System. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Chien, T. T.

1972-01-01

An on-line adaptive technique is developed to provide a self-contained redundant-sensor navigation system with a capability to utilize its full potentiality in reliability and performance. The gyro navigation system is modeled as a Gauss-Markov process, with degradation modes defined as changes in characteristics specified by parameters associated with the model. The adaptive system is formulated as a multistage stochastic process: (1) a detection system, (2) an identification system and (3) a compensation system. It is shown that the sufficient statistics for the partially observable process in the detection and identification system is the posterior measure of the state of degradation, conditioned on the measurement history.

Automated detection of slum area change in Hyderabad, India using multitemporal satellite imagery

NASA Astrophysics Data System (ADS)

Kit, Oleksandr; Lüdeke, Matthias

2013-09-01

This paper presents an approach to automated identification of slum area change patterns in Hyderabad, India, using multi-year and multi-sensor very high resolution satellite imagery. It relies upon a lacunarity-based slum detection algorithm, combined with Canny- and LSD-based imagery pre-processing routines. This method outputs plausible and spatially explicit slum locations for the whole urban agglomeration of Hyderabad in years 2003 and 2010. The results indicate a considerable growth of area occupied by slums between these years and allow identification of trends in slum development in this urban agglomeration.

From Google Maps to a fine-grained catalog of street trees

NASA Astrophysics Data System (ADS)

Branson, Steve; Wegner, Jan Dirk; Hall, David; Lang, Nico; Schindler, Konrad; Perona, Pietro

2018-01-01

Up-to-date catalogs of the urban tree population are of importance for municipalities to monitor and improve quality of life in cities. Despite much research on automation of tree mapping, mainly relying on dedicated airborne LiDAR or hyperspectral campaigns, tree detection and species recognition is still mostly done manually in practice. We present a fully automated tree detection and species recognition pipeline that can process thousands of trees within a few hours using publicly available aerial and street view images of Google MapsTM. These data provide rich information from different viewpoints and at different scales from global tree shapes to bark textures. Our work-flow is built around a supervised classification that automatically learns the most discriminative features from thousands of trees and corresponding, publicly available tree inventory data. In addition, we introduce a change tracker that recognizes changes of individual trees at city-scale, which is essential to keep an urban tree inventory up-to-date. The system takes street-level images of the same tree location at two different times and classifies the type of change (e.g., tree has been removed). Drawing on recent advances in computer vision and machine learning, we apply convolutional neural networks (CNN) for all classification tasks. We propose the following pipeline: download all available panoramas and overhead images of an area of interest, detect trees per image and combine multi-view detections in a probabilistic framework, adding prior knowledge; recognize fine-grained species of detected trees. In a later, separate module, track trees over time, detect significant changes and classify the type of change. We believe this is the first work to exploit publicly available image data for city-scale street tree detection, species recognition and change tracking, exhaustively over several square kilometers, respectively many thousands of trees. Experiments in the city of Pasadena, California, USA show that we can detect >70% of the street trees, assign correct species to >80% for 40 different species, and correctly detect and classify changes in >90% of the cases.

Using Machine Learning for Advanced Anomaly Detection and Classification

NASA Astrophysics Data System (ADS)

Lane, B.; Poole, M.; Camp, M.; Murray-Krezan, J.

2016-09-01

Machine Learning (ML) techniques have successfully been used in a wide variety of applications to automatically detect and potentially classify changes in activity, or a series of activities by utilizing large amounts data, sometimes even seemingly-unrelated data. The amount of data being collected, processed, and stored in the Space Situational Awareness (SSA) domain has grown at an exponential rate and is now better suited for ML. This paper describes development of advanced algorithms to deliver significant improvements in characterization of deep space objects and indication and warning (I&W) using a global network of telescopes that are collecting photometric data on a multitude of space-based objects. The Phase II Air Force Research Laboratory (AFRL) Small Business Innovative Research (SBIR) project Autonomous Characterization Algorithms for Change Detection and Characterization (ACDC), contracted to ExoAnalytic Solutions Inc. is providing the ability to detect and identify photometric signature changes due to potential space object changes (e.g. stability, tumble rate, aspect ratio), and correlate observed changes to potential behavioral changes using a variety of techniques, including supervised learning. Furthermore, these algorithms run in real-time on data being collected and processed by the ExoAnalytic Space Operations Center (EspOC), providing timely alerts and warnings while dynamically creating collection requirements to the EspOC for the algorithms that generate higher fidelity I&W. This paper will discuss the recently implemented ACDC algorithms, including the general design approach and results to date. The usage of supervised algorithms, such as Support Vector Machines, Neural Networks, k-Nearest Neighbors, etc., and unsupervised algorithms, for example k-means, Principle Component Analysis, Hierarchical Clustering, etc., and the implementations of these algorithms is explored. Results of applying these algorithms to EspOC data both in an off-line "pattern of life" analysis as well as using the algorithms on-line in real-time, meaning as data is collected, will be presented. Finally, future work in applying ML for SSA will be discussed.

Brain Structure-function Couplings (FY11)

DTIC Science & Technology

2012-01-01

influence time-evolving models of global brain function and dynamic changes in cognitive performance. Both structural and functional connections change on...Artifact Resistant Measure to Detect Cognitive EEG Activity During Locomotion. Journal of NeuroEngineering and Rehabilitation, submitted. 10...Specifically, identifying the communication between brain regions that occurs during tasks may provide information regarding the cognitive processes involved in

Real-time biscuit tile image segmentation method based on edge detection.

PubMed

Matić, Tomislav; Aleksi, Ivan; Hocenski, Željko; Kraus, Dieter

2018-05-01

In this paper we propose a novel real-time Biscuit Tile Segmentation (BTS) method for images from ceramic tile production line. BTS method is based on signal change detection and contour tracing with a main goal of separating tile pixels from background in images captured on the production line. Usually, human operators are visually inspecting and classifying produced ceramic tiles. Computer vision and image processing techniques can automate visual inspection process if they fulfill real-time requirements. Important step in this process is a real-time tile pixels segmentation. BTS method is implemented for parallel execution on a GPU device to satisfy the real-time constraints of tile production line. BTS method outperforms 2D threshold-based methods, 1D edge detection methods and contour-based methods. Proposed BTS method is in use in the biscuit tile production line. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Comparing Automatic CME Detections in Multiple LASCO and SECCHI Catalogs

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

Hess, Phillip; Colaninno, Robin C., E-mail: phillip.hess.ctr@nrl.navy.mil, E-mail: robin.colaninno@nrl.navy.mil

With the creation of numerous automatic detection algorithms, a number of different catalogs of coronal mass ejections (CMEs) spanning the entirety of the Solar and Heliospheric Observatory ( SOHO ) Large Angle Spectrometric Coronagraph (LASCO) mission have been created. Some of these catalogs have been further expanded for use on data from the Solar Terrestrial Earth Observatory ( STEREO ) Sun Earth Connection Coronal and Heliospheric Investigation (SECCHI) as well. We compare the results from different automatic detection catalogs (Solar Eruption Event Detection System (SEEDS), Computer Aided CME Tracking (CACTus), and Coronal Image Processing (CORIMP)) to ensure the consistency ofmore » detections in each. Over the entire span of the LASCO catalogs, the automatic catalogs are well correlated with one another, to a level greater than 0.88. Focusing on just periods of higher activity, these correlations remain above 0.7. We establish the difficulty in comparing detections over the course of LASCO observations due to the change in the instrument image cadence in 2010. Without adjusting catalogs for the cadence, CME detection rates show a large spike in cycle 24, despite a notable drop in other indices of solar activity. The output from SEEDS, using a consistent image cadence, shows that the CME rate has not significantly changed relative to sunspot number in cycle 24. These data, and mass calculations from CORIMP, lead us to conclude that any apparent increase in CME rate is a result of the change in cadence. We study detection characteristics of CMEs, discussing potential physical changes in events between cycles 23 and 24. We establish that, for detected CMEs, physical parameters can also be sensitive to the cadence.« less

Dielectric characterization of neutralized and nonneutralized chitosan upon drying.

PubMed

Viciosa, M T; Dionísio, M; Mano, J F

2006-02-15

Isothermal dielectric loss spectra of neutralized and nonneutralized chitosan were acquired in successive runs from -130 degrees C up to increasing final temperatures, in a frequency range between 20 Hz and 1 MHz. Essentially, three relaxation processes were detected in the temperature range covered: (i) a beta-wet process, detected when the sample has a higher water content that vanishes after heating to 150 degrees C; (ii) a beta process, which is located at temperatures below 0 degrees C, becoming better defined and maintaining its location after annealing at 150 degrees C independently of the protonation state of the amino side group; and (iii) a sigma process that deviates to higher temperatures with drying, being more mobile in the nonneutralized form. Moreover, in dried neutralized chitosan, a fourth process was detected in the low frequency side of the secondary beta process that diminishes after annealing. Whether this process is a distinct relaxation of the dried polymer or a deviated beta-wet process due to the loss of water residues achieved by annealing is not straightforward. Only beta and sigma processes persist after annealing at 150 degrees C. The changes in molecular mobility upon drying of these two relaxation processes were evaluated. Copyright (c) 2005 Wiley Periodicals, Inc.

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

Musgrove, Cameron H.; West, James C.

Missing samples within synthetic aperture radar data result in image distortions. For coherent data products, such as coherent change detection and interferometric processing, the image distortion can be devastating to these second order products, resulting in missed detections and inaccurate height maps. Earlier approaches to repair the coherent data products focus upon reconstructing the missing data samples. This study demonstrates that reconstruction is not necessary to restore the quality of the coherent data products.

Joint Services Electronics Program.

DTIC Science & Technology

1987-10-15

semiconductor perturb the index of refraction which can be detected in a Nomarski -type optical interferometer. For example, we have demonstrated the real-time...probe relies on a different physical effect and operates by interferometrically detecting the phase change induced in an optical beam by the presence of... interferometric diameter measurement system to monitor the growth process, has been in operation for . several years. The focussing optics and pulling mechanisms

Land use mapping and modelling for the Phoenix Quadrangle

NASA Technical Reports Server (NTRS)

Place, J. L. (Principal Investigator)

1973-01-01

The author has identified the following significant results. The land use of the Phoenix Quadrangle in Arizona had been mapped previously from aerial photographs and recorded in a computer data bank. During the ERTS-1 experiment, changes in land use were detected using only the ERTS-1 images. The I2S color additive viewer was used as the principal image enhancement tool, operated in a multispectral mode. Hard copy color composite images of the best multiband combinations from ERTS-1 were made by photographic and diazo processes. The I2S viewer was also used to enhance changes between successive images by quick flip techniques or by registering with different color filters. More recently, a Bausch and Lomb zoom transferscope has been used for the same purpose. Improved interpretation of land use change resulted, and a map of changes within the Phoenix Quadrangle was compiled. The first level of a proposed standard land use classification system was sucessfully used. ERTS-1 underflight photography was used to check the accuracy of the ERTS-1 image interpretation. It was found that the total areas of change detected in the photos were comparable with the total areas of change detected in the ERTS-1 images.

Quantifying Standing Dead Tree Volume and Structural Loss with Voxelized Terrestrial Lidar Data

NASA Astrophysics Data System (ADS)

Popescu, S. C.; Putman, E.

2017-12-01

Standing dead trees (SDTs) are an important forest component and impact a variety of ecosystem processes, yet the carbon pool dynamics of SDTs are poorly constrained in terrestrial carbon cycling models. The ability to model wood decay and carbon cycling in relation to detectable changes in tree structure and volume over time would greatly improve such models. The overall objective of this study was to provide automated aboveground volume estimates of SDTs and automated procedures to detect, quantify, and characterize structural losses over time with terrestrial lidar data. The specific objectives of this study were: 1) develop an automated SDT volume estimation algorithm providing accurate volume estimates for trees scanned in dense forests; 2) develop an automated change detection methodology to accurately detect and quantify SDT structural loss between subsequent terrestrial lidar observations; and 3) characterize the structural loss rates of pine and oak SDTs in southeastern Texas. A voxel-based volume estimation algorithm, "TreeVolX", was developed and incorporates several methods designed to robustly process point clouds of varying quality levels. The algorithm operates on horizontal voxel slices by segmenting the slice into distinct branch or stem sections then applying an adaptive contour interpolation and interior filling process to create solid reconstructed tree models (RTMs). TreeVolX estimated large and small branch volume with an RMSE of 7.3% and 13.8%, respectively. A voxel-based change detection methodology was developed to accurately detect and quantify structural losses and incorporated several methods to mitigate the challenges presented by shifting tree and branch positions as SDT decay progresses. The volume and structural loss of 29 SDTs, composed of Pinus taeda and Quercus stellata, were successfully estimated using multitemporal terrestrial lidar observations over elapsed times ranging from 71 - 753 days. Pine and oak structural loss rates were characterized by estimating the amount of volumetric loss occurring in 20 equal-interval height bins of each SDT. Results showed that large pine snags exhibited more rapid structural loss in comparison to medium-sized oak snags in this study.

Minor Body Surveyor: A Multi-Object, High Speed, Spectro-Photometer Space Mission System Employing Wide-Area Intelligent Change Detection

NASA Astrophysics Data System (ADS)

Kaplan, M. L.; van Cleve, J. E.; Alcock, C.

2003-12-01

Detection and characterization of the small bodies of the outer solar system presents unique challenges to terrestrial based sensing systems, principally the inverse 4th power decrease of reflected and thermal signals with target distance from the Sun. These limits are surpassed by new techniques [1,2,3] employing star-object occultation event sensing, which are capable of detecting sub-kilometer objects in the Kuiper Belt and Oort cloud. This poster will present an instrument and space mission concept based on adaptations of the NASA Discovery Kepler program currently in development at Ball Aerospace and Technologies Corp. Instrument technologies to enable this space science mission are being pursued and will be described. In particular, key attributes of an optimized payload include the ability to provide: 1) Coarse spectral resolution (using an objective spectrometer approach) 2) Wide FOV, simultaneous object monitoring (up to 150,000 stars employing select data regions within a large focal plane mosaic) 3) Fast temporal frame integration and readout architectures (10 to 50 msec for each monitored object) 4) Real-time, intelligent change detection processing (to limit raw data volumes) The Minor Body Surveyor combines the focal plane and processing technology elements into a densely packaged format to support general space mission issues of mass and power consumption, as well as telemetry resources. Mode flexibility is incorporated into the real-time processing elements to allow for either temporal (Occultations) or spatial (Moving targets) change detection. In addition, a basic image capture mode is provided for general pointing and field reference measurements. The overall space mission architecture is described as well. [1] M. E. Bailey. Can 'Invisible' Bodies be Observed in the Solar System. Nature, 259:290-+, January 1976. [2] T. S. Axelrod, C. Alcock, K. H. Cook, and H.-S. Park. A Direct Census of the Oort Cloud with a Robotic Telescope. In ASP Conf. Ser. 34: Robotic Telescopes in the 1990s, pages 171-181, 1992. [3] F. Roques and M. Moncuquet. A Detection Method for Small Kuiper Belt Objects: The Search for Stellar Occultations. Icarus, 147:530-544, October 2000.

Study the sensitivity of molecular functional groups to bioethanol processing in lipid biopolymer of co-products using DRIFT molecular spectroscopy

NASA Astrophysics Data System (ADS)

Yu, Peiqiang

2011-11-01

To date, there is no study on bioethanol processing-induced changes in molecular structural profiles mainly related to lipid biopolymer. The objectives of this study were to: (1) determine molecular structural changes of lipid related functional groups in the co-products that occurred during bioethanol processing; (2) relatively quantify the antisymmetric CH 3 and CH 2 (ca. 2959 and 2928 cm -1, respectively), symmetric CH 3 and CH 2 (ca. 2871 and 2954 cm -1, respectively) functional groups, carbonyl C dbnd O ester (ca. 1745 cm -1) and unsaturated groups (CH attached to C dbnd C) (ca. 3007 cm -1) spectral intensities as well as their ratios of antisymmetric CH 3 to antisymmetric CH 2, and (3) illustrate the molecular spectral analyses as a research tool to detect for the sensitivity of individual moleculars to the bioethanol processing in a complex plant-based feed and food system without spectral parameterization. The hypothesis of this study was that bioethanol processing changed the molecular structure profiles in the co-products as opposed to original cereal grains. These changes could be detected by infrared molecular spectroscopy and will be related to nutrient utilization. The results showed that bioethanol processing had effects on the functional groups spectral profiles in the co-products. It was found that the CH 3-antisymmetric to CH 2-antisymmetric stretching intensity ratio was changed. The spectral features of carbonyl C dbnd O ester group and unsaturated group were also different. Since the different types of cereal grains (wheat vs. corn) had different sensitivity to the bioethanol processing, the spectral patterns and band component profiles differed between their co-products (wheat DDGS vs. corn DDGS). The multivariate molecular spectral analyses, cluster analysis and principal component analysis of original spectra (without spectral parameterization), distinguished the structural differences between the wheat and wheat DDGS and between the corn and corn DDGS in the antisymmetric and symmetric CH 3 and CH 2 spectral region (ca. 2994-2800 cm -1) and unsaturated group band region (3025-2996 cm -1). Further study is needed to quantify molecular structural changes in relation to nutrient utilization of lipid biopolymer.

Effect of the crushing process on Raman analyses: consequences for the Mars 2018 mission

NASA Astrophysics Data System (ADS)

Foucher, F.; López Reyes, G.; Bost, N.; Rull, F.; Rüßmann, P.; Westall, F.

2012-04-01

The Pasteur payload of the international 2018 Mars mission comprises a Raman spectrometer as part of its instrument suite. Analyses with this instrument will be made on crushed samples. The crushing process will cause loss of important structural context and could change the physical properties of the studied materials resulting in misinterpretation of the data. We therefore investigated the influence of granulometry on the Raman spectrum of various minerals and rocks using laboratory equipment and the Raman instrument being developed for the Pasteur payload. The aim was to determine what influence the crushing process could have on the correct identification of rocks and minerals and the detection of possible traces of life. Whatever the sample type, our study shows that the crushing process leads to a strong increase in the background level and to a decrease in the signal/noise ratio. This effect is all the more important when the grain size is small. Moreover, for certain minerals, the Raman spectra can be significantly modified: the peaks are shifted and broadened and new peaks can appear, implying a change in the crystal structure of the material. This effect is mainly due to the decrease of the thermal diffusion in the powder which leads to an increase in the heat induced by the laser. Since mineral identification using Raman spectroscopy is made by comparison with database spectra, this kind of change could lead to misinterpretation of the spectra and thus must be taken into account during the in situ investigation. The loss of texture is also shown to complicate identification of rocks with subsequent consequences for the eventual detection and interpretation of past traces of life. On the other hand, mixing of the components in the powder facilitates the detection of minor phases.

AIDE - Advanced Intrusion Detection Environment

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

Smith, Cathy L.

2013-04-28

Would you like to know when someone has dropped an undesirable executable binary on our system? What about something less malicious such as a software installation by a user? What about the user who decides to install a newer version of mod_perl or PHP on your web server without letting you know beforehand? Or even something as simple as when an undocumented config file change is made by another member of the admin group? Do you even want to know about all the changes that happen on a daily basis on your server? The purpose of an intrusion detection systemmore » (IDS) is to detect unauthorized, possibly malicious activity. The purpose of a host-based IDS, or file integrity checker, is check for unauthorized changes to key system files, binaries, libraries, and directories on the system. AIDE is an Open Source file and directory integrity checker. AIDE will let you know when a file or directory has been added, deleted, modified. It is included with the Red Hat Enterprise 6. It is available for other Linux distros. This is a case study describing the process of configuring AIDE on an out of the box RHEL6 installation. Its goal is to illustrate the thinking and the process by which a useful AIDE configuration is built.« less

Integrated Optoelectronics for Parallel Microbioanalysis

NASA Technical Reports Server (NTRS)

Stirbl, Robert; Moynihan, Philip; Bearman, Gregory; Lane, Arthur

2003-01-01

Miniature, relatively inexpensive microbioanalytical systems ("laboratory-on-achip" devices) have been proposed for the detection of hazardous microbes and toxic chemicals. Each system of this type would include optoelectronic sensors and sensor-output-processing circuitry that would simultaneously look for the optical change, fluorescence, delayed fluorescence, or phosphorescence signatures from multiple redundant sites that have interacted with the test biomolecules in order to detect which one(s) was present in a given situation. These systems could be used in a variety of settings that could include doctors offices, hospitals, hazardous-material laboratories, biological-research laboratories, military operations, and chemical-processing plants.

Levee Monitoring with Radar Remote Sensing

NASA Technical Reports Server (NTRS)

Jones, Cathleen E.

2012-01-01

Topics in this presentation are: 1. Overview of radar remote sensing 2. Surface change detection with Differential Interferometric Radar Processing 3. Study of the Sacramento - San Joaquin levees 4. Mississippi River Levees during the Spring 2011 floods.

Development of a database and processing method for detecting hematotoxicity adverse drug events.

PubMed

Shimai, Yoshie; Takeda, Toshihiro; Manabe, Shirou; Teramoto, Kei; Mihara, Naoki; Matsumura, Yasushi

2015-01-01

Adverse events are detected by monitoring the patient's status, including blood test results. However, it is difficult to identify all adverse events based on recognition by individual doctors. We developed a system that can be used to detect hematotoxicity adverse events according to blood test results recorded in an electronic medical record system. The blood test results were graded based on Common Terminology Criteria for Adverse Events (CTCAE) and changes in the blood test results (Up, Down, Flat) were assessed according to the variation in the grade. The changes in the blood test and injection data were stored in a database. By comparing the date of injection and start and end dates of the change in the blood test results, adverse events related to a designated drug were detected. Using this method, we searched for the occurrence of serious adverse events (CTCAE Grades 3 or 4) concerning WBC, ALT and creatinine related to paclitaxel at Osaka University Hospital. The rate of occurrence of a decreased WBC count, increased ALT level and increased creatinine level was 36.0%, 0.6% and 0.4%, respectively. This method is useful for detecting and estimating the rate of occurrence of hematotoxicity adverse drug events.

Sensor data monitoring and decision level fusion scheme for early fire detection

NASA Astrophysics Data System (ADS)

Rizogiannis, Constantinos; Thanos, Konstantinos Georgios; Astyakopoulos, Alkiviadis; Kyriazanos, Dimitris M.; Thomopoulos, Stelios C. A.

2017-05-01

The aim of this paper is to present the sensor monitoring and decision level fusion scheme for early fire detection which has been developed in the context of the AF3 Advanced Forest Fire Fighting European FP7 research project, adopted specifically in the OCULUS-Fire control and command system and tested during a firefighting field test in Greece with prescribed real fire, generating early-warning detection alerts and notifications. For this purpose and in order to improve the reliability of the fire detection system, a two-level fusion scheme is developed exploiting a variety of observation solutions from air e.g. UAV infrared cameras, ground e.g. meteorological and atmospheric sensors and ancillary sources e.g. public information channels, citizens smartphone applications and social media. In the first level, a change point detection technique is applied to detect changes in the mean value of each measured parameter by the ground sensors such as temperature, humidity and CO2 and then the Rate-of-Rise of each changed parameter is calculated. In the second level the fire event Basic Probability Assignment (BPA) function is determined for each ground sensor using Fuzzy-logic theory and then the corresponding mass values are combined in a decision level fusion process using Evidential Reasoning theory to estimate the final fire event probability.

Adult Age Differences in Categorization and Multiple-Cue Judgment

ERIC Educational Resources Information Center

Mata, Rui; von Helversen, Bettina; Karlsson, Linnea; Cupper, Lutz

2012-01-01

We often need to infer unknown properties of objects from observable ones, just like detectives must infer guilt from observable clues and behavior. But how do inferential processes change with age? We examined young and older adults' reliance on rule-based and similarity-based processes in an inference task that can be considered either a…

Multicolor Upconversion Nanoprobes Based on a Dual Luminescence Resonance Energy Transfer Assay for Simultaneous Detection and Bioimaging of [Ca2+ ]i and pHi in Living Cells.

PubMed

Song, Xinyue; Yue, Zihong; Zhang, Jiayu; Jiang, Yanxialei; Wang, Zonghua; Zhang, Shusheng

2018-04-25

Intracellular [Ca 2+ ] i and pH i have a close relationship, and their abnormal levels can result in cell dysfunction and accompanying diseases. Thus, simultaneous determination of [Ca 2+ ] i and pH i can more accurately investigate complex biological processes in an integrated platform. Herein, multicolor upconversion nanoparticles (UCNPs) were prepared with the advantages of no spectral overlapping, single NIR excitation wavelengths, and greater tissue penetration depth. The upconversion nanoprobes were easily prepared by the attachment of two fluorescent dyes, Fluo-4 and SNARF-4F. Based on the dual luminescence resonance energy transfer (LRET) process, the blue and green fluorescence of the UCNPs were specially quenched and selectively recovered after the detachment and/or absorbance change of the attached fluorescent dyes, enabling dual detection. Importantly, the developed nanoprobe could successfully be applied for the detection of [Ca 2+ ] i and pH i change in adenosine triphosphate (ATP) and ethylene glycol tetraacetic acid (EGTA) stimulation in living cells. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Hybrid online sensor error detection and functional redundancy for systems with time-varying parameters.

PubMed

Feng, Jianyuan; Turksoy, Kamuran; Samadi, Sediqeh; Hajizadeh, Iman; Littlejohn, Elizabeth; Cinar, Ali

2017-12-01

Supervision and control systems rely on signals from sensors to receive information to monitor the operation of a system and adjust manipulated variables to achieve the control objective. However, sensor performance is often limited by their working conditions and sensors may also be subjected to interference by other devices. Many different types of sensor errors such as outliers, missing values, drifts and corruption with noise may occur during process operation. A hybrid online sensor error detection and functional redundancy system is developed to detect errors in online signals, and replace erroneous or missing values detected with model-based estimates. The proposed hybrid system relies on two techniques, an outlier-robust Kalman filter (ORKF) and a locally-weighted partial least squares (LW-PLS) regression model, which leverage the advantages of automatic measurement error elimination with ORKF and data-driven prediction with LW-PLS. The system includes a nominal angle analysis (NAA) method to distinguish between signal faults and large changes in sensor values caused by real dynamic changes in process operation. The performance of the system is illustrated with clinical data continuous glucose monitoring (CGM) sensors from people with type 1 diabetes. More than 50,000 CGM sensor errors were added to original CGM signals from 25 clinical experiments, then the performance of error detection and functional redundancy algorithms were analyzed. The results indicate that the proposed system can successfully detect most of the erroneous signals and substitute them with reasonable estimated values computed by functional redundancy system.

A colorimetric detection of acrylamide in potato chips based on nucleophile-initiated thiol-ene Michael addition.

PubMed

Hu, Qinqin; Fu, Yingchun; Xu, Xiahong; Qiao, Zhaohui; Wang, Ronghui; Zhang, Ying; Li, Yanbin

2016-02-07

Acrylamide (AA), a neurotoxin and a potential carcinogen, has been found in various thermally processed foods such as potato chips, biscuits, and coffee. Simple, cost-effective, and sensitive methods for the rapid detection of AA are needed to ensure food safety. Herein, a novel colorimetric method was proposed for the visual detection of AA based on a nucleophile-initiated thiol-ene Michael addition reaction. Gold nanoparticles (AuNPs) were aggregated by glutathione (GSH) because of a ligand-replacement, accompanied by a color change from red to purple. In the presence of AA, after the thiol-ene Michael addition reaction between GSH and AA with the catalysis of a nucleophile, the sulfhydryl group of GSH was consumed by AA, which hindered the subsequent ligand-replacement and the aggregation of AuNPs. Therefore, the concentration of AA could be determined by the visible color change caused by dispersion/aggregation of AuNPs. This new method showed high sensitivity with a linear range from 0.1 μmol L(-1) to 80 μmol L(-1) and a detection limit of 28.6 nmol L(-1), and especially revealed better selectivity than the fluorescence sensing method reported previously. Moreover, this new method was used to detect AA in potato chips with a satisfactory result in comparison with the standard methods based on chromatography, which indicated that the colorimetric method can be expanded for the rapid detection of AA in thermally processed foods.

Event Detection for Hydrothermal Plumes: A case study at Grotto Vent

NASA Astrophysics Data System (ADS)

Bemis, K. G.; Ozer, S.; Xu, G.; Rona, P. A.; Silver, D.

2012-12-01

Evidence is mounting that geologic events such as volcanic eruptions (and intrusions) and earthquakes (near and far) influence the flow rates and temperatures of hydrothermal systems. Connecting such suppositions to observations of hydrothermal output is challenging, but new ongoing time series have the potential to capture such events. This study explores using activity detection, a technique modified from computer vision, to identify pre-defined events within an extended time series recorded by COVIS (Cabled Observatory Vent Imaging Sonar) and applies it to a time series, with gaps, from Sept 2010 to the present; available measurements include plume orientation, plume rise rate, and diffuse flow area at the NEPTUNE Canada Observatory at Grotto Vent, Main Endeavour Field, Juan de Fuca Ridge. Activity detection is the process of finding a pattern (activity) in a data set containing many different types of patterns. Among many approaches proposed to model and detect activities, we have chosen a graph-based technique, Petri Nets, as they do not require training data to model the activity. They use the domain expert's knowledge to build the activity as a combination of feature states and their transitions (actions). Starting from a conceptual model of how hydrothermal plumes respond to daily tides, we have developed a Petri Net based detection algorithm that identifies deviations from the specified response. Initially we assumed that the orientation of the plume would change smoothly and symmetrically in a consistent daily pattern. However, results indicate that the rate of directional changes varies. The present Petri Net detects unusually large and rapid changes in direction or amount of bending; however inspection of Figure 1 suggests that many of the events detected may be artifacts resulting from gaps in the data or from the large temporal spacing. Still, considerable complexity overlies the "normal" tidal response pattern (the data has a dominant frequency of ~12.9 hours). We are in the process of defining several events of particular scientific interest: 1) transient behavioral changes associated with atmospheric storms, earthquakes or volcanic intrusions or eruptions, 2) mutual interaction of neighboring plumes on each other's behavior, and 3) rapid shifts in plume direction that indicate the presence of unusual currents or changes in currents. We will query the existing data to see if these relationships are ever observed as well as testing our understanding of the "normal" pattern of response to tidal currents.Figure 1. Arrows indicate plume orientation at a given time (time axis in days after 9/29/10) and stars indicate times when orientation changes rapidly.

Operating principles and detection characteristics of the Visible and Near-Infrared Imaging Spectrometer in the Chang'e-3

NASA Astrophysics Data System (ADS)

He, Zhi-Ping; Wang, Bin-Yong; Lü, Gang; Li, Chun-Lai; Yuan, Li-Yin; Xu, Rui; Liu, Bin; Chen, Kai; Wang, Jian-Yu

2014-12-01

The Visible and Near-Infrared Imaging Spectrometer (VNIS), using two acousto-optic tunable filters as dispersive components, consists of a VIS/NIR imaging spectrometer (0.45-0.95 μm), a shortwave IR spectrometer (0.9-2.4 μm) and a calibration unit with dust-proofing functionality. The VNIS was utilized to detect the spectrum of the lunar surface and achieve in-orbit calibration, which satisfied the requirements for scientific detection. Mounted at the front of the Yutu rover, lunar objects that are detected with the VNIS with a 45° visual angle to obtain spectra and geometrical data in order to analyze the mineral composition of the lunar surface. After landing successfully on the Moon, the VNIS performed several explorations and calibrations, and obtained several spectral images and spectral reflectance curves of the lunar soil in the region of Mare Imbrium. This paper describes the working principle and detection characteristics of the VNIS and provides a reference for data processing and scientific applications.

A laser scanning confocal imaging-surface plasmon resonance system application in real time detection of antibody-antigen interaction

NASA Astrophysics Data System (ADS)

Zhang, H. Y.; Yang, L. Q.; Liu, W. M.

2011-12-01

The laser scanning confocal microscope (LSCM) offers several advantages over conventional optical microscopy, but most LSCM work is qualitative analysis and it is very hard to achieve quantitative detection directly with the changing of the fluorescent intensity. A new real time sensor system for the antibody-antigen interaction detection was built integrating with a LSCM and a wavelength-dependent surface plasmon resonance (SPR) sensor. The system was applied to detect the bonding process of human IgG and fluorescent-labeled affinity purified antibody in real time. The fluorescence images changing is well with that of SPR wavelengths in real time, and the trend of the resonance wavelength shift with the concentrations of antibody is similar to that of the fluorescent intensity changing. The results show that SPR makes up the short of quantificational analysis with LSCM with the high spatial resolution. The sensor system shows the merits of the of the LSCM and SPR synergetic application, which are of great importance for practical application in biosensor and life science for interesting local interaction.

Multi-temporal change image inference towards false alarms reduction for an operational photogrammetric rockfall detection system

NASA Astrophysics Data System (ADS)

Partsinevelos, Panagiotis; Kallimani, Christina; Tripolitsiotis, Achilleas

2015-06-01

Rockfall incidents affect civil security and hamper the sustainable growth of hard to access mountainous areas due to casualties, injuries and infrastructure loss. Rockfall occurrences cannot be easily prevented, whereas previous studies for rockfall multiple sensor early detection systems have focused on large scale incidents. However, even a single rock may cause the loss of a human life along transportation routes thus, it is highly important to establish methods for the early detection of small-scale rockfall incidents. Terrestrial photogrammetric techniques are prone to a series of errors leading to false alarm incidents, including vegetation, wind, and non relevant change in the scene under consideration. In this study, photogrammetric monitoring of rockfall prone slopes is established and the resulting multi-temporal change imagery is processed in order to minimize false alarm incidents. Integration of remote sensing imagery analysis techniques is hereby applied to enhance early detection of a rockfall. Experimental data demonstrated that an operational system able to identify a 10-cm rock movement within a 10% false alarm rate is technically feasible.

Implications of Climate Change for State Bioassessment ...

EPA Pesticide Factsheets

This draft report uses biological data collected by four states in wadeable rivers and streams to examine the components of state and tribal bioassessment and biomonitoring programs that may be vulnerable to climate change. The study investigates the potential to identify biological response signals to climate change within existing bioassessment data sets; analyzes how biological responses can be categorized and interpreted; and assesses how they may influence decision-making processes. The analyses suggest that several biological indicators may be used to detect climate change effects and such indicators can be used by state bioassessment programs to document changes at high-quality reference sites. The study investigates the potential to identify biological response signals to climate change within existing bioassessment data sets; analyzes how biological responses can be categorized and interpreted; and assesses how they may influence decision-making processes.

Occupancy change detection system and method

DOEpatents

Bruemmer, David J [Idaho Falls, ID; Few, Douglas A [Idaho Falls, ID

2009-09-01

A robot platform includes perceptors, locomotors, and a system controller. The system controller executes instructions for producing an occupancy grid map of an environment around the robot, scanning the environment to generate a current obstacle map relative to a current robot position, and converting the current obstacle map to a current occupancy grid map. The instructions also include processing each grid cell in the occupancy grid map. Within the processing of each grid cell, the instructions include comparing each grid cell in the occupancy grid map to a corresponding grid cell in the current occupancy grid map. For grid cells with a difference, the instructions include defining a change vector for each changed grid cell, wherein the change vector includes a direction from the robot to the changed grid cell and a range from the robot to the changed grid cell.

Space and Time Resolved Detection of Platelet Activation and von Willebrand Factor Conformational Changes in Deep Suspensions.

PubMed

Biasetti, Jacopo; Sampath, Kaushik; Cortez, Angel; Azhir, Alaleh; Gilad, Assaf A; Kickler, Thomas S; Obser, Tobias; Ruggeri, Zaverio M; Katz, Joseph

2017-01-01

Tracking cells and proteins' phenotypic changes in deep suspensions is critical for the direct imaging of blood-related phenomena in in vitro replica of cardiovascular systems and blood-handling devices. This paper introduces fluorescence imaging techniques for space and time resolved detection of platelet activation, von Willebrand factor (VWF) conformational changes, and VWF-platelet interaction in deep suspensions. Labeled VWF, platelets, and VWF-platelet strands are suspended in deep cuvettes, illuminated, and imaged with a high-sensitivity EM-CCD camera, allowing detection using an exposure time of 1 ms. In-house postprocessing algorithms identify and track the moving signals. Recombinant VWF-eGFP (rVWF-eGFP) and VWF labeled with an FITC-conjugated polyclonal antibody are employed. Anti-P-Selectin FITC-conjugated antibodies and the calcium-sensitive probe Indo-1 are used to detect activated platelets. A positive correlation between the mean number of platelets detected per image and the percentage of activated platelets determined through flow cytometry is obtained, validating the technique. An increase in the number of rVWF-eGFP signals upon exposure to shear stress demonstrates the technique's ability to detect breakup of self-aggregates. VWF globular and unfolded conformations and self-aggregation are also observed. The ability to track the size and shape of VWF-platelet strands in space and time provides means to detect pro- and antithrombotic processes.

Environmental monitoring and assessment of landscape dynamics in southern coast of the Caspian Sea through intensity analysis and imprecise land-use data.

PubMed

Hasani, Mohammad; Sakieh, Yousef; Dezhkam, Sadeq; Ardakani, Tahereh; Salmanmahiny, Abdolrassoul

2017-04-01

A hierarchical intensity analysis of land-use change is applied to evaluate the dynamics of a coupled urban coastal system in Rasht County, Iran. Temporal land-use layers of 1987, 1999, and 2011 are employed, while spatial accuracy metrics are only available for 2011 data (overall accuracy of 94%). The errors in 1987 and 1999 layers are unknown, which can influence the accuracy of temporal change information. Such data were employed to examine the size and the type of errors that could justify deviations from uniform change intensities. Accordingly, errors comprising 3.31 and 7.47% of 1999 and 2011 maps, respectively, could explain all differences from uniform gains and errors including 5.21 and 1.81% of 1987 and 1999 maps, respectively, could explain all deviations from uniform losses. Additional historical information is also applied for uncertainty assessment and to separate probable map errors from actual land-use changes. In this regard, historical processes in Rasht County can explain different types of transition that are either consistent or inconsistent to known processes. The intensity analysis assisted in identification of systematic transitions and detection of competitive categories, which cannot be investigated through conventional change detection methods. Based on results, built-up area is the most active gaining category in the area and wetland category with less areal extent is more sensitive to intense land-use change processes. Uncertainty assessment results also indicated that there are no considerable classification errors in temporal land-use data and these imprecise layers can reliably provide implications for informed decision making.

ECG Based Heart Arrhythmia Detection Using Wavelet Coherence and Bat Algorithm

NASA Astrophysics Data System (ADS)

Kora, Padmavathi; Sri Rama Krishna, K.

2016-12-01

Atrial fibrillation (AF) is a type of heart abnormality, during the AF electrical discharges in the atrium are rapid, results in abnormal heart beat. The morphology of ECG changes due to the abnormalities in the heart. This paper consists of three major steps for the detection of heart diseases: signal pre-processing, feature extraction and classification. Feature extraction is the key process in detecting the heart abnormality. Most of the ECG detection systems depend on the time domain features for cardiac signal classification. In this paper we proposed a wavelet coherence (WTC) technique for ECG signal analysis. The WTC calculates the similarity between two waveforms in frequency domain. Parameters extracted from WTC function is used as the features of the ECG signal. These features are optimized using Bat algorithm. The Levenberg Marquardt neural network classifier is used to classify the optimized features. The performance of the classifier can be improved with the optimized features.

Investigation of the detection of shallow tunnels using electromagnetic and seismic waves

NASA Astrophysics Data System (ADS)

Counts, Tegan; Larson, Gregg; Gürbüz, Ali Cafer; McClellan, James H.; Scott, Waymond R., Jr.

2007-04-01

Multimodal detection of subsurface targets such as tunnels, pipes, reinforcement bars, and structures has been investigated using both ground-penetrating radar (GPR) and seismic sensors with signal processing techniques to enhance localization capabilities. Both systems have been tested in bi-static configurations but the GPR has been expanded to a multi-static configuration for improved performance. The use of two compatible sensors that sense different phenomena (GPR detects changes in electrical properties while the seismic system measures mechanical properties) increases the overall system's effectiveness in a wider range of soils and conditions. Two experimental scenarios have been investigated in a laboratory model with nearly homogeneous sand. Images formed from the raw data have been enhanced using beamforming inversion techniques and Hough Transform techniques to specifically address the detection of linear targets. The processed data clearly indicate the locations of the buried targets of various sizes at a range of depths.

The Value of Long-Term Research at the Five USGS WEBB Catchments

NASA Astrophysics Data System (ADS)

Shanley, J. B.; Murphy, S. F.; Scholl, M. A.; Wickland, K.; Aulenbach, B. T.; Hunt, R.; Clow, D. W.

2017-12-01

Long-term catchment studies are sentinel sites for detecting, documenting, and understanding ecosystem processes and environmental change. The small catchment approach fosters in-depth site-based hydrological, biogeochemical, and ecological process understanding, while a collective network of catchment observatories offers a broader context to synthesize understanding across a range of climates and geologies. The USGS Water, Energy, and Biogeochemical Budgets (WEBB) program is a network of five sites established in 1991 to assess the impact of climate and environmental change on hydrology and biogeochemistry. Like other networks, such as the USDA - Forest Service Experimental Forests and the Czech Geomon network, WEBB exploits gradients of climate, geology, and topography to understand controls on biogeochemical processes. We present examples from each site and some cross-site syntheses to demonstrate how WEBB has advanced catchment science and informed resource management and policy. WEBB has relied on strong academic partnerships, providing long-term continuity for shorter-term academic grants, which have offered rich graduate educational opportunities. Like other sites and networks, the long-term datasets and process understanding of WEBB provide context to detect and interpret change. Without this backdrop, we have no baseline to quantify effects of droughts, floods, and extreme events, and no test sites to validate process-based models. In an era of lean budgets for science funding, the long-term continuity of WEBB and other catchment networks is in jeopardy, as is the critical scientific value and societal benefits they embody.

Changes in the Response Properties of Inferior Colliculus Neurons Relating to Tinnitus

PubMed Central

Berger, Joel I.; Coomber, Ben; Wells, Tobias T.; Wallace, Mark N.; Palmer, Alan R.

2014-01-01

Tinnitus is often identified in animal models by using the gap prepulse inhibition of acoustic startle. Impaired gap detection following acoustic over-exposure (AOE) is thought to be caused by tinnitus “filling in” the gap, thus, reducing its salience. This presumably involves altered perception, and could conceivably be caused by changes at the level of the neocortex, i.e., cortical reorganization. Alternatively, reduced gap detection ability might reflect poorer temporal processing in the brainstem, caused by AOE; in which case, impaired gap detection would not be a reliable indicator of tinnitus. We tested the latter hypothesis by examining gap detection in inferior colliculus (IC) neurons following AOE. Seven of nine unilaterally noise-exposed guinea pigs exhibited behavioral evidence of tinnitus. In these tinnitus animals, neural gap detection thresholds (GDTs) in the IC significantly increased in response to broadband noise stimuli, but not to pure tones or narrow-band noise. In addition, when IC neurons were sub-divided according to temporal response profile (onset vs. sustained firing patterns), we found a significant increase in the proportion of onset-type responses after AOE. Importantly, however, GDTs were still considerably shorter than gap durations commonly used in objective behavioral tests for tinnitus. These data indicate that the neural changes observed in the IC are insufficient to explain deficits in behavioral gap detection that are commonly attributed to tinnitus. The subtle changes in IC neuron response profiles following AOE warrant further investigation. PMID:25346722

Direct detection of a transport-blocking trap in a nanoscaled silicon single-electron transistor by radio-frequency reflectometry

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

Villis, B. J.; Sanquer, M.; Jehl, X.

2014-06-09

The continuous downscaling of transistors results in nanoscale devices which require fewer and fewer charged carriers for their operation. The ultimate charge controlled device, the single-electron transistor (SET), controls the transfer of individual electrons. It is also the most sensitive electrometer, and as a result the electron transport through it can be dramatically affected by nearby charges. Standard direct-current characterization techniques, however, are often unable to unambiguously detect and resolve the origin of the observed changes in SET behavior arising from changes in the charge state of a capacitively coupled trap. Using a radio-frequency (RF) reflectometry technique, we are ablemore » to unequivocally detect this process, in very close agreement with modeling of the trap's occupation probability.« less

Changes in laboratory test results and diagnostic imaging presentation before the detection of occupational cholangiocarcinoma.

PubMed

Kubo, Shoji; Takemura, Shigekazu; Sakata, Chikaharu; Urata, Yorihisa; Nishioka, Takayoshi; Nozawa, Akinori; Kinoshita, Masahiko; Hamano, Genya; Nakanuma, Yasuni; Endo, Ginji

2014-01-01

A cholangiocarcinoma outbreak among workers of an offset color proof-printing department in a printing company was recently reported. It is important to understand the clinical course leading to occupational cholangiocarcinoma development for investigation of the carcinogenesis process and for surveillance and early detection. We evaluated the changes in laboratory test results and diagnostic imaging presentation before the detection of cholangiocarcinoma. We investigated the changes in laboratory test results and diagnostic imaging presentation before the detection of cholangiocarcinoma in 2 patients because the data were available. Results The clinical courses observed in the 2 participating patients showed persistent elevation of serum γ-glutamyl transpeptidase levels with or without elevated serum levels of alanine aminotransferase and/or aspartate aminotransferase before cholangiocarcinoma detection. Dilatation of the bile ducts without tumor-induced stenosis was observed several years before cholangiocarcinoma detection and progressed gradually in both patients. The serum concentration of carbohydrate 19-9 also increased prior to cholangiocarcinoma detection in both patients. Eventually, observation of stenosis of the bile duct and a space-occupying lesion strongly suggested cholangiocarcinoma. Pathological examination of the resected specimens showed chronic bile duct injury and neoplastic lesions, such as "biliary intraepithelial neoplasia" and "intraductal papillary neoplasm of the bile duct" in various sites of the bile ducts, particularly in the dilated bile ducts. The changes in laboratory test results and diagnostic imaging might be related to the development of cholangiocarcinoma. It is important to monitor diagnostic imaging presentation and laboratory test results in workers with extended exposure to organic solvents.

"Change deafness" arising from inter-feature masking within a single auditory object.

PubMed

Barascud, Nicolas; Griffiths, Timothy D; McAlpine, David; Chait, Maria

2014-03-01

Our ability to detect prominent changes in complex acoustic scenes depends not only on the ear's sensitivity but also on the capacity of the brain to process competing incoming information. Here, employing a combination of psychophysics and magnetoencephalography (MEG), we investigate listeners' sensitivity in situations when two features belonging to the same auditory object change in close succession. The auditory object under investigation is a sequence of tone pips characterized by a regularly repeating frequency pattern. Signals consisted of an initial, regularly alternating sequence of three short (60 msec) pure tone pips (in the form ABCABC…) followed by a long pure tone with a frequency that is either expected based on the on-going regular pattern ("LONG expected"-i.e., "LONG-expected") or constitutes a pattern violation ("LONG-unexpected"). The change in LONG-expected is manifest as a change in duration (when the long pure tone exceeds the established duration of a tone pip), whereas the change in LONG-unexpected is manifest as a change in both the frequency pattern and a change in the duration. Our results reveal a form of "change deafness," in that although changes in both the frequency pattern and the expected duration appear to be processed effectively by the auditory system-cortical signatures of both changes are evident in the MEG data-listeners often fail to detect changes in the frequency pattern when that change is closely followed by a change in duration. By systematically manipulating the properties of the changing features and measuring behavioral and MEG responses, we demonstrate that feature changes within the same auditory object, which occur close together in time, appear to compete for perceptual resources.

Spatio-Semantic Comparison of Large 3d City Models in Citygml Using a Graph Database

NASA Astrophysics Data System (ADS)

Nguyen, S. H.; Yao, Z.; Kolbe, T. H.

2017-10-01

A city may have multiple CityGML documents recorded at different times or surveyed by different users. To analyse the city's evolution over a given period of time, as well as to update or edit the city model without negating modifications made by other users, it is of utmost importance to first compare, detect and locate spatio-semantic changes between CityGML datasets. This is however difficult due to the fact that CityGML elements belong to a complex hierarchical structure containing multi-level deep associations, which can basically be considered as a graph. Moreover, CityGML allows multiple syntactic ways to define an object leading to syntactic ambiguities in the exchange format. Furthermore, CityGML is capable of including not only 3D urban objects' graphical appearances but also their semantic properties. Since to date, no known algorithm is capable of detecting spatio-semantic changes in CityGML documents, a frequent approach is to replace the older models completely with the newer ones, which not only costs computational resources, but also loses track of collaborative and chronological changes. Thus, this research proposes an approach capable of comparing two arbitrarily large-sized CityGML documents on both semantic and geometric level. Detected deviations are then attached to their respective sources and can easily be retrieved on demand. As a result, updating a 3D city model using this approach is much more efficient as only real changes are committed. To achieve this, the research employs a graph database as the main data structure for storing and processing CityGML datasets in three major steps: mapping, matching and updating. The mapping process transforms input CityGML documents into respective graph representations. The matching process compares these graphs and attaches edit operations on the fly. Found changes can then be executed using the Web Feature Service (WFS), the standard interface for updating geographical features across the web.

Structural-change localization and monitoring through a perturbation-based inverse problem.

PubMed

Roux, Philippe; Guéguen, Philippe; Baillet, Laurent; Hamze, Alaa

2014-11-01

Structural-change detection and characterization, or structural-health monitoring, is generally based on modal analysis, for detection, localization, and quantification of changes in structure. Classical methods combine both variations in frequencies and mode shapes, which require accurate and spatially distributed measurements. In this study, the detection and localization of a local perturbation are assessed by analysis of frequency changes (in the fundamental mode and overtones) that are combined with a perturbation-based linear inverse method and a deconvolution process. This perturbation method is applied first to a bending beam with the change considered as a local perturbation of the Young's modulus, using a one-dimensional finite-element model for modal analysis. Localization is successful, even for extended and multiple changes. In a second step, the method is numerically tested under ambient-noise vibration from the beam support with local changes that are shifted step by step along the beam. The frequency values are revealed using the random decrement technique that is applied to the time-evolving vibrations recorded by one sensor at the free extremity of the beam. Finally, the inversion method is experimentally demonstrated at the laboratory scale with data recorded at the free end of a Plexiglas beam attached to a metallic support.

Motion-based video monitoring for early detection of livestock diseases: The case of African swine fever

PubMed Central

Martínez-Avilés, Marta; Ivorra, Benjamin; Martínez-López, Beatriz; Ramos, Ángel Manuel; Sánchez-Vizcaíno, José Manuel

2017-01-01

Early detection of infectious diseases can substantially reduce the health and economic impacts on livestock production. Here we describe a system for monitoring animal activity based on video and data processing techniques, in order to detect slowdown and weakening due to infection with African swine fever (ASF), one of the most significant threats to the pig industry. The system classifies and quantifies motion-based animal behaviour and daily activity in video sequences, allowing automated and non-intrusive surveillance in real-time. The aim of this system is to evaluate significant changes in animals’ motion after being experimentally infected with ASF virus. Indeed, pig mobility declined progressively and fell significantly below pre-infection levels starting at four days after infection at a confidence level of 95%. Furthermore, daily motion decreased in infected animals by approximately 10% before the detection of the disease by clinical signs. These results show the promise of video processing techniques for real-time early detection of livestock infectious diseases. PMID:28877181

Generation and coherent detection of QPSK signal using a novel method of digital signal processing

NASA Astrophysics Data System (ADS)

Zhao, Yuan; Hu, Bingliang; He, Zhen-An; Xie, Wenjia; Gao, Xiaohui

2018-02-01

We demonstrate an optical quadrature phase-shift keying (QPSK) signal transmitter and an optical receiver for demodulating optical QPSK signal with homodyne detection and digital signal processing (DSP). DSP on the homodyne detection scheme is employed without locking the phase of the local oscillator (LO). In this paper, we present an extracting one-dimensional array of down-sampling method for reducing unwanted samples of constellation diagram measurement. Such a novel scheme embodies the following major advantages over the other conventional optical QPSK signal detection methods. First, this homodyne detection scheme does not need strict requirement on LO in comparison with linear optical sampling, such as having a flat spectral density and phase over the spectral support of the source under test. Second, the LabVIEW software is directly used for recovering the QPSK signal constellation without employing complex DSP circuit. Third, this scheme is applicable to multilevel modulation formats such as M-ary PSK and quadrature amplitude modulation (QAM) or higher speed signals by making minor changes.

3D change detection at street level using mobile laser scanning point clouds and terrestrial images

NASA Astrophysics Data System (ADS)

Qin, Rongjun; Gruen, Armin

2014-04-01

Automatic change detection and geo-database updating in the urban environment are difficult tasks. There has been much research on detecting changes with satellite and aerial images, but studies have rarely been performed at the street level, which is complex in its 3D geometry. Contemporary geo-databases include 3D street-level objects, which demand frequent data updating. Terrestrial images provides rich texture information for change detection, but the change detection with terrestrial images from different epochs sometimes faces problems with illumination changes, perspective distortions and unreliable 3D geometry caused by the lack of performance of automatic image matchers, while mobile laser scanning (MLS) data acquired from different epochs provides accurate 3D geometry for change detection, but is very expensive for periodical acquisition. This paper proposes a new method for change detection at street level by using combination of MLS point clouds and terrestrial images: the accurate but expensive MLS data acquired from an early epoch serves as the reference, and terrestrial images or photogrammetric images captured from an image-based mobile mapping system (MMS) at a later epoch are used to detect the geometrical changes between different epochs. The method will automatically mark the possible changes in each view, which provides a cost-efficient method for frequent data updating. The methodology is divided into several steps. In the first step, the point clouds are recorded by the MLS system and processed, with data cleaned and classified by semi-automatic means. In the second step, terrestrial images or mobile mapping images at a later epoch are taken and registered to the point cloud, and then point clouds are projected on each image by a weighted window based z-buffering method for view dependent 2D triangulation. In the next step, stereo pairs of the terrestrial images are rectified and re-projected between each other to check the geometrical consistency between point clouds and stereo images. Finally, an over-segmentation based graph cut optimization is carried out, taking into account the color, depth and class information to compute the changed area in the image space. The proposed method is invariant to light changes, robust to small co-registration errors between images and point clouds, and can be applied straightforwardly to 3D polyhedral models. This method can be used for 3D street data updating, city infrastructure management and damage monitoring in complex urban scenes.

Road sign recognition with fuzzy adaptive pre-processing models.

PubMed

Lin, Chien-Chuan; Wang, Ming-Shi

2012-01-01

A road sign recognition system based on adaptive image pre-processing models using two fuzzy inference schemes has been proposed. The first fuzzy inference scheme is to check the changes of the light illumination and rich red color of a frame image by the checking areas. The other is to check the variance of vehicle's speed and angle of steering wheel to select an adaptive size and position of the detection area. The Adaboost classifier was employed to detect the road sign candidates from an image and the support vector machine technique was employed to recognize the content of the road sign candidates. The prohibitory and warning road traffic signs are the processing targets in this research. The detection rate in the detection phase is 97.42%. In the recognition phase, the recognition rate is 93.04%. The total accuracy rate of the system is 92.47%. For video sequences, the best accuracy rate is 90.54%, and the average accuracy rate is 80.17%. The average computing time is 51.86 milliseconds per frame. The proposed system can not only overcome low illumination and rich red color around the road sign problems but also offer high detection rates and high computing performance.

Road Sign Recognition with Fuzzy Adaptive Pre-Processing Models

PubMed Central

Lin, Chien-Chuan; Wang, Ming-Shi

2012-01-01

A road sign recognition system based on adaptive image pre-processing models using two fuzzy inference schemes has been proposed. The first fuzzy inference scheme is to check the changes of the light illumination and rich red color of a frame image by the checking areas. The other is to check the variance of vehicle's speed and angle of steering wheel to select an adaptive size and position of the detection area. The Adaboost classifier was employed to detect the road sign candidates from an image and the support vector machine technique was employed to recognize the content of the road sign candidates. The prohibitory and warning road traffic signs are the processing targets in this research. The detection rate in the detection phase is 97.42%. In the recognition phase, the recognition rate is 93.04%. The total accuracy rate of the system is 92.47%. For video sequences, the best accuracy rate is 90.54%, and the average accuracy rate is 80.17%. The average computing time is 51.86 milliseconds per frame. The proposed system can not only overcome low illumination and rich red color around the road sign problems but also offer high detection rates and high computing performance. PMID:22778650

Recent research on inherent molecular structure, physiochemical properties, and bio-functions of food and feed-type Avena sativa oats and processing-induced changes revealed with molecular microspectroscopic techniques

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

Prates, Luciana Louzada; Yu, Peiqiang

Avena sativa oat is a cereal widely used as human food and livestock feed. However, the low metabolized energy and the rapid rumen degradations of protein and starch have limited the use of A. sativa oat grains. To overcome this disadvantage, new A. sativa oat varieties have been developed. Additionally, heat-related processing has been performed to decrease the degradation rate and improve the absorption of amino acids in the small intestine. The nutritive value is reflected by both chemical composition and inherent molecular structure conformation. However, the traditional wet chemical analysis is not able to detect the inherent molecular structuresmore » within an intact tissue. The advanced synchrotron-radiation and globar-based molecular microspectroscopy have been developed recently and applied to study internal molecular structures and the processing induced structure changes in A. sativa oats and reveal how molecular structure changes in relation to nutrient availability. This review aimed to obtain the recent information regarding physiochemical properties, molecular structures, metabolic characteristics of protein, and the heat-induced changes in new A. sativa oat varieties. The use of the advanced vibrational molecular spectroscopy was emphasized, synchrotron- and globar-based (micro)spectroscopy, to reveal the inherent structure of A. sativa oats at cellular and molecular levels and to reveal the heat processing effect on the degradation characteristics and the protein molecular structure in A. sativa oats. The relationship between nutrient availability and protein molecular inherent structure was also presented. Information described in this review gives better insight in the physiochemical properties, molecular structure, and the heat-induced changes in A. sativa oat detected with advanced molecular spectroscopic techniques in combinination with conventional nutrition study techniques.« less

An efficient transmission power control scheme for temperature variation in wireless sensor networks.

PubMed

Lee, Jungwook; Chung, Kwangsue

2011-01-01

Wireless sensor networks collect data from several nodes dispersed at remote sites. Sensor nodes can be installed in harsh environments such as deserts, cities, and indoors, where the link quality changes considerably over time. Particularly, changes in transmission power may be caused by temperature, humidity, and other factors. In order to compensate for link quality changes, existing schemes detect the link quality changes between nodes and control transmission power through a series of feedback processes, but these approaches can cause heavy overhead with the additional control packets needed. In this paper, the change of the link quality according to temperature is examined through empirical experimentation. A new power control scheme combining both temperature-aware link quality compensation and a closed-loop feedback process to adapt to link quality changes is proposed. We prove that the proposed scheme effectively adapts the transmission power to the changing link quality with less control overhead and energy consumption.

SuBSENSE: a universal change detection method with local adaptive sensitivity.

PubMed

St-Charles, Pierre-Luc; Bilodeau, Guillaume-Alexandre; Bergevin, Robert

2015-01-01

Foreground/background segmentation via change detection in video sequences is often used as a stepping stone in high-level analytics and applications. Despite the wide variety of methods that have been proposed for this problem, none has been able to fully address the complex nature of dynamic scenes in real surveillance tasks. In this paper, we present a universal pixel-level segmentation method that relies on spatiotemporal binary features as well as color information to detect changes. This allows camouflaged foreground objects to be detected more easily while most illumination variations are ignored. Besides, instead of using manually set, frame-wide constants to dictate model sensitivity and adaptation speed, we use pixel-level feedback loops to dynamically adjust our method's internal parameters without user intervention. These adjustments are based on the continuous monitoring of model fidelity and local segmentation noise levels. This new approach enables us to outperform all 32 previously tested state-of-the-art methods on the 2012 and 2014 versions of the ChangeDetection.net dataset in terms of overall F-Measure. The use of local binary image descriptors for pixel-level modeling also facilitates high-speed parallel implementations: our own version, which used no low-level or architecture-specific instruction, reached real-time processing speed on a midlevel desktop CPU. A complete C++ implementation based on OpenCV is available online.

Nationwide Hybrid Change Detection of Buildings

NASA Astrophysics Data System (ADS)

Hron, V.; Halounova, L.

2016-06-01

The Fundamental Base of Geographic Data of the Czech Republic (hereinafter FBGD) is a national 2D geodatabase at a 1:10,000 scale with more than 100 geographic objects. This paper describes the design of the permanent updating mechanism of buildings in FBGD. The proposed procedure belongs to the category of hybrid change detection (HCD) techniques which combine pixel-based and object-based evaluation. The main sources of information for HCD are cadastral information and bi-temporal vertical digital aerial photographs. These photographs have great information potential because they contain multispectral, position and also elevation information. Elevation information represents a digital surface model (DSM) which can be obtained using the image matching technique. Pixel-based evaluation of bi-temporal DSMs enables fast localization of places with potential building changes. These coarse results are subsequently classified through the object-based image analysis (OBIA) using spectral, textural and contextual features and GIS tools. The advantage of the two-stage evaluation is the pre-selection of locations where image segmentation (a computationally demanding part of OBIA) is performed. It is not necessary to apply image segmentation to the entire scene, but only to the surroundings of detected changes, which contributes to significantly faster processing and lower hardware requirements. The created technology is based on open-source software solutions that allow easy portability on multiple computers and parallelization of processing. This leads to significant savings of financial resources which can be expended on the further development of FBGD.

Development of a widefield reflectance and fluorescence imaging device for the detection of skin and oral cancer

NASA Astrophysics Data System (ADS)

Pratavieira, S.; Santos, P. L. A.; Bagnato, V. S.; Kurachi, C.

2009-06-01

Oral and skin cancers constitute a major global health problem that cause great impact in patients. The most common screening method for oral cancer is visual inspection and palpation of the mouth. Visual examination relies heavily on the experience and skills of the physician to identify and delineate early premalignant and cancer changes, which is not simple due to the similar characteristics of early stage cancers and benign lesions. Optical imaging has the potential to address these clinical challenges. Contrast between normal and neoplastic areas may be increased, distinct to the conventional white light, when using illumination and detection conditions. Reflectance imaging can detect local changes in tissue scattering and absorption and fluorescence imaging can probe changes in the biochemical composition. These changes have shown to be indicatives of malignant progression. Widefield optical imaging systems are interesting because they may enhance the screening ability in large regions allowing the discrimination and the delineation of neoplastic and potentially of occult lesions. Digital image processing allows the combination of autofluorescence and reflectance images in order to objectively identify and delineate the peripheral extent of neoplastic lesions in the skin and oral cavity. Combining information from different imaging modalities has the potential of increasing diagnostic performance, due to distinct provided information. A simple widefiled imaging device based on fluorescence and reflectance modes together with a digital image processing was assembled and its performance tested in an animal study.

Mediterranean dunes on the go: Evidence from a short term study on coastal herbaceous vegetation

NASA Astrophysics Data System (ADS)

Prisco, Irene; Stanisci, Angela; Acosta, Alicia T. R.

2016-12-01

Detailed monitoring studies on permanent sites are a promising tool for an accurate evaluation of short, medium or long term vegetation dynamics. This work aims to evaluate short-term changes in coastal dune herbaceous plant species and EU Habitats through a multi-temporal analysis using permanent vegetation transects. In particular, (I) we analyze changes in species richness of coastal habitats; (II) we identify changes in plant cover of selected focal plants; and (III) we relate the changes to selected climatic variables and erosion/accretion processes. We selected one of the Italian's peninsula best preserved coastal dune areas (ca. 50 km along the Adriatic sea) with a relatively homogeneous coastal zonation and low anthropic pressure but with different erosion/accretion processes. We explored changes in richness over time using generalized linear models (GLMs). We identified different ecological guilds: focal, ruderal and alien plant species and investigated temporal trends in these guilds' species richness. We also applied GLMs to determine how plant cover of the most important focal species have changed over time. Overall, in this study we observed that the influence of climatic variables was relatively small. However, we found remarkable different trends in response to erosion/accretion processes both at community and at species level. Thus, our results highlight the importance of coastal dynamics in preserving not only coastal vegetation zonation, but also species richness and focal species cover. Moreover, we identified the dune grasslands as the most sensitive habitat for detecting the influence of climatic variables throughout a short term monitoring survey. Information from this study provides useful insights for detecting changes in vegetation, for establishing habitat protection priorities and for improving conservation efforts for these fragile ecosystems.

Avionics-compatible video facial cognizer for detection of pilot incapacitation.

PubMed

Steffin, Morris

2006-01-01

High-acceleration loss of consciousness is a serious problem for military pilots. In this laboratory, a video cognizer has been developed that in real time detects facial changes closely coupled to the onset of loss of consciousness. Efficient algorithms are compatible with video digital signal processing hardware and are thus configurable on an autonomous single board that generates alarm triggers to activate autopilot, and is avionics-compatible.

Searching for structural medium changes during the 2011 El Hierro (Spain) submarine eruption

NASA Astrophysics Data System (ADS)

Sánchez-Pastor, Pilar S.; Schimmel, Martin; López, Carmen

2017-04-01

Submarine volcanic eruptions are often difficult to study due to their restricted access that usually inhibits direct observations. That happened with the 2011 El Hierro eruption, which is the first eruption that has been tracked in real time in Canary Islands. For instance, despite the real-time tracking it was not possible to determine the exact end of the eruption. Besides, volcanic eruptions involve many dynamic (physical and chemical) processes, which cause structural changes in the surrounding medium that we expect to observe and monitor through passive seismic approaches. The purpose of this study is to detect and analyse these changes as well as to search for precursory signals to the eruption itself using ambient noise auto and cross-correlations. We employ different correlation strategies (classical and phase cross-correlation) and apply them to field data recorded by the IGN network during 2011 and 2012. The different preprocessing and processing steps are tested and compared to better understand the data, to find the robust signatures, and to define a routine work procedure. One of the problems we face is the presence of volcanic tremors, which cause a varying seismic response that we can not attribute to structural changes. So far, structural changes could not be detected unambiguously and we present our ongoing research in this field.

Detecting Land-Use Change and On-Farm Investments at the Plot Scale

NASA Astrophysics Data System (ADS)

Burney, J. A.; Goldblatt, R.; Amezaga, K. Y.; Sanford, L.; Nichols, M. M.

2017-12-01

The ability to remotely monitor agro-ecosystems over large spatial scales, at high spatial and temporal resolution, promises to open new and previously un-tractable lines of inquiry about the relationships between management practices, welfare, and resilience in coupled human-natural systems. We use several sources of remotely sensed data (from vegetation indices to synthetic aperture radar) and new analysis methods to infer when and where land-use and management changes take place at the farm level, including processes leading to degradation, like overgrazing or tree removal, as well as processes intended to boost resilience, like irrigation and conservation agriculture. Here, we first show how ecosystem health metrics can be used as indicators of both poverty and vulnerability. This is especially important because many other remotely-sensed economic proxies exhibit hysteresis in one direction; that is, they may respond quickly to positive income shocks (e.g., a change in income may rapidly lead to more construction and an expansion of the urban environment), but little if at all to negative shocks (a drop in income does not lead to deconstruction of buildings). We then present results from three field projects that show how these techniques can be used to detect management changes — reflecting changes in household welfare — in both field and quasi/natural experiments.

Features of Changing Microwave Radiation from Loaded Rock in Elastic Phase

NASA Astrophysics Data System (ADS)

Wu, Lixin; Mao, Wenfei; Huang, Jianwei; Liu, Shanjun; Xu, Zhongying

2017-04-01

Since the discovery of satellite infrared anomaly occurred before some earthquake by Russian geo-scientists in 1980's, both satellite remote sensing on seismic activities and experimental infrared detection on rock physics in process of rock loading were undertaken in many counties including China, Japan, Europe nations and United States. Infrared imager and spectrum instruments were applied to detect the changed infrared radiation from loaded rock to fracturing, which lead to the development of Remote Sensing Rock Mechanics. However, the change of microwave radiation from loaded rock was not so much studied, even if abnormal changes of microwave brightness temperature (MBT) preceding some large earthquakes were observed by satellite sensors such as AMSR-E on boarded Aqua. To monitor rock hazards, seismic activities, and to make earthquake precautions by via of microwave detection or microwave remote sensing, it is fairly demanded to explore the laws of microwave radiation variation with changed stress and to uncover the rock physics. We developed a large scale rock loading system with capability of 500 tons and 10 tons of load, respectively, at two horizontal loading head, and designed a group of microwave detectors in C, K, and Ka bands. To investigate the changed microwave radiation from loaded granite and sandstone in its elastics deformation phase, the first horizontal stress was circularly applied on rock samples of size 10×30×60cm3 at a constant second horizontal stress, and the changes microwave radiation was detected by the detectors hanged overhead the rock sample. The experiments were conducted outdoor at nighttime to keep off environmental radiation and to simulate the satellite observation conditions in background of cool sky. The first horizontal stress and the microwave radiations were synchronically detected and recorded. After reducing the random noise of detected microwave signals with wavelet method, we found the MBT increase with stress rising and decrease with stress dropping, and the correlation factor (R2) of MBT-stress reached 0.88. The experiments and results revealed an important rock physical phenomenon of rock dielectric property changing with stress, which leads to detectable MBT variation.

Visual encoding and fixation target selection in free viewing: presaccadic brain potentials

PubMed Central

Nikolaev, Andrey R.; Jurica, Peter; Nakatani, Chie; Plomp, Gijs; van Leeuwen, Cees

2013-01-01

In scrutinizing a scene, the eyes alternate between fixations and saccades. During a fixation, two component processes can be distinguished: visual encoding and selection of the next fixation target. We aimed to distinguish the neural correlates of these processes in the electrical brain activity prior to a saccade onset. Participants viewed color photographs of natural scenes, in preparation for a change detection task. Then, for each participant and each scene we computed an image heat map, with temperature representing the duration and density of fixations. The temperature difference between the start and end points of saccades was taken as a measure of the expected task-relevance of the information concentrated in specific regions of a scene. Visual encoding was evaluated according to whether subsequent change was correctly detected. Saccades with larger temperature difference were more likely to be followed by correct detection than ones with smaller temperature differences. The amplitude of presaccadic activity over anterior brain areas was larger for correct detection than for detection failure. This difference was observed for short “scrutinizing” but not for long “explorative” saccades, suggesting that presaccadic activity reflects top-down saccade guidance. Thus, successful encoding requires local scanning of scene regions which are expected to be task-relevant. Next, we evaluated fixation target selection. Saccades “moving up” in temperature were preceded by presaccadic activity of higher amplitude than those “moving down”. This finding suggests that presaccadic activity reflects attention deployed to the following fixation location. Our findings illustrate how presaccadic activity can elucidate concurrent brain processes related to the immediate goal of planning the next saccade and the larger-scale goal of constructing a robust representation of the visual scene. PMID:23818877

[Modern Views on Children's Interstitial Lung Disease].

PubMed

Boĭtsova, E V; Beliashova, M A; Ovsiannikov, D Iu

2015-01-01

Interstitial lung diseases (ILD, diffuse lung diseases) are a heterogeneous group of diseases in which a pathological process primarily involved alveoli and perialveolar interstitium, resulting in impaired gas exchange, restrictive changes of lung ventilation function and diffuse interstitial changes detectable by X-ray. Children's interstitial lung diseases is an topical problem ofpediatricpulmonoogy. The article presents current information about classification, epidemiology, clinical presentation, diagnostics, treatment and prognosis of these rare diseases. The article describes the differences in the structure, pathogenesis, detection of various histological changes in children's ILD compared with adult patients with ILD. Authors cite an instance of registers pediatric patients with ILD. The clinical semiotics of ILD, the possible results of objective research, the frequency of symptoms, the features of medical history, the changes detected on chest X-rays, CT semiotics described in detail. Particular attention was paid to interstitial lung diseases, occurring mainly in newborns and children during the first two years of life, such as congenital deficiencies of surfactant proteins, neuroendocrine cell hyperplasia of infancy, pulmonary interstitial glycogenosis. The diagnostic program for children's ILD, therapy options are presented in this article.

Statistical methods for change-point detection in surface temperature records

NASA Astrophysics Data System (ADS)

Pintar, A. L.; Possolo, A.; Zhang, N. F.

2013-09-01

We describe several statistical methods to detect possible change-points in a time series of values of surface temperature measured at a meteorological station, and to assess the statistical significance of such changes, taking into account the natural variability of the measured values, and the autocorrelations between them. These methods serve to determine whether the record may suffer from biases unrelated to the climate signal, hence whether there may be a need for adjustments as considered by M. J. Menne and C. N. Williams (2009) "Homogenization of Temperature Series via Pairwise Comparisons", Journal of Climate 22 (7), 1700-1717. We also review methods to characterize patterns of seasonality (seasonal decomposition using monthly medians or robust local regression), and explain the role they play in the imputation of missing values, and in enabling robust decompositions of the measured values into a seasonal component, a possible climate signal, and a station-specific remainder. The methods for change-point detection that we describe include statistical process control, wavelet multi-resolution analysis, adaptive weights smoothing, and a Bayesian procedure, all of which are applicable to single station records.

Object form discontinuity facilitates displacement discrimination across saccades.

PubMed

Demeyer, Maarten; De Graef, Peter; Wagemans, Johan; Verfaillie, Karl

2010-06-01

Stimulus displacements coinciding with a saccadic eye movement are poorly detected by human observers. In recent years, converging evidence has shown that this phenomenon does not result from poor transsaccadic retention of presaccadic stimulus position information, but from the visual system's efforts to spatially align presaccadic and postsaccadic perception on the basis of visual landmarks. It is known that this process can be disrupted, and transsaccadic displacement detection performance can be improved, by briefly blanking the stimulus display during and immediately after the saccade. In the present study, we investigated whether this improvement could also follow from a discontinuity in the task-irrelevant form of the displaced stimulus. We observed this to be the case: Subjects more accurately identified the direction of intrasaccadic displacements when the displaced stimulus simultaneously changed form, compared to conditions without a form change. However, larger improvements were still observed under blanking conditions. In a second experiment, we show that facilitation induced by form changes and blanks can combine. We conclude that a strong assumption of visual stability underlies the suppression of transsaccadic change detection performance, the rejection of which generalizes from stimulus form to stimulus position.

Sing that Tune: Infants’ Perception of Melody and Lyrics and the Facilitation of Phonetic Recognition in Songs

PubMed Central

Lebedeva, Gina C.; Kuhl, Patricia K.

2010-01-01

To better understand how infants process complex auditory input, this study investigated whether 11-month-old infants perceive the pitch (melodic) or the phonetic (lyric) components within songs as more salient, and whether melody facilitates phonetic recognition. Using a preferential looking paradigm, uni-dimensional and multi-dimensional songs were tested; either the pitch or syllable order of the stimuli varied. As a group, infants detected a change in pitch order in a 4-note sequence when the syllables were redundant (Experiment 1), but did not detect the identical pitch change with variegated syllables (Experiment 2). Infants were better able to detect a change in syllable order in a sung sequence (Experiment 2) than the identical syllable change in a spoken sequence (Experiment 1). These results suggest that by 11 months, infants cannot “ignore” phonetic information in the context of perceptually salient pitch variation. Moreover, the increased phonetic recognition in song contexts mirrors findings that demonstrate advantages of infant-directed speech. Findings are discussed in terms of how stimulus complexity interacts with the perception of sung speech in infancy. PMID:20472295

Quantitative kinetic analysis of lung nodules by temporal subtraction technique in dynamic chest radiography with a flat panel detector

NASA Astrophysics Data System (ADS)

Tsuchiya, Yuichiro; Kodera, Yoshie; Tanaka, Rie; Sanada, Shigeru

2007-03-01

Early detection and treatment of lung cancer is one of the most effective means to reduce cancer mortality; chest X-ray radiography has been widely used as a screening examination or health checkup. The new examination method and the development of computer analysis system allow obtaining respiratory kinetics by the use of flat panel detector (FPD), which is the expanded method of chest X-ray radiography. Through such changes functional evaluation of respiratory kinetics in chest has become available. Its introduction into clinical practice is expected in the future. In this study, we developed the computer analysis algorithm for the purpose of detecting lung nodules and evaluating quantitative kinetics. Breathing chest radiograph obtained by modified FPD was converted into 4 static images drawing the feature, by sequential temporal subtraction processing, morphologic enhancement processing, kinetic visualization processing, and lung region detection processing, after the breath synchronization process utilizing the diaphragmatic analysis of the vector movement. The artificial neural network used to analyze the density patterns detected the true nodules by analyzing these static images, and drew their kinetic tracks. For the algorithm performance and the evaluation of clinical effectiveness with 7 normal patients and simulated nodules, both showed sufficient detecting capability and kinetic imaging function without statistically significant difference. Our technique can quantitatively evaluate the kinetic range of nodules, and is effective in detecting a nodule on a breathing chest radiograph. Moreover, the application of this technique is expected to extend computer-aided diagnosis systems and facilitate the development of an automatic planning system for radiation therapy.

New Optical Methods for Liveness Detection on Fingers

PubMed Central

Dolezel, Michal; Vana, Jan; Brezinova, Eva; Yim, Jaegeol; Shim, Kyubark

2013-01-01

This paper is devoted to new optical methods, which are supposed to be used for liveness detection on fingers. First we describe the basics about fake finger use in fingerprint recognition process and the possibilities of liveness detection. Then we continue with introducing three new liveness detection methods, which we developed and tested in the scope of our research activities—the first one is based on measurement of the pulse, the second one on variations of optical characteristics caused by pressure change, and the last one is based on reaction of skin to illumination with different wavelengths. The last part deals with the influence of skin diseases on fingerprint recognition, especially on liveness detection. PMID:24151584

Quantification of storm-induced bathymetric change in a back-barrier estuary

USGS Publications Warehouse

Ganju, Neil K.; Suttles, Steven E.; Beudin, Alexis; Nowacki, Daniel J.; Miselis, Jennifer L.; Andrews, Brian D.

2017-01-01

Geomorphology is a fundamental control on ecological and economic function of estuaries. However, relative to open coasts, there has been little quantification of storm-induced bathymetric change in back-barrier estuaries. Vessel-based and airborne bathymetric mapping can cover large areas quickly, but change detection is difficult because measurement errors can be larger than the actual changes over the storm timescale. We quantified storm-induced bathymetric changes at several locations in Chincoteague Bay, Maryland/Virginia, over the August 2014 to July 2015 period using fixed, downward-looking altimeters and numerical modeling. At sand-dominated shoal sites, measurements showed storm-induced changes on the order of 5 cm, with variability related to stress magnitude and wind direction. Numerical modeling indicates that the predominantly northeasterly wind direction in the fall and winter promotes southwest-directed sediment transport, causing erosion of the northern face of sandy shoals; southwesterly winds in the spring and summer lead to the opposite trend. Our results suggest that storm-induced estuarine bathymetric change magnitudes are often smaller than those detectable with methods such as LiDAR. More precise fixed-sensor methods have the ability to elucidate the geomorphic processes responsible for modulating estuarine bathymetry on the event and seasonal timescale, but are limited spatially. Numerical modeling enables interpretation of broad-scale geomorphic processes and can be used to infer the long-term trajectory of estuarine bathymetric change due to episodic events, when informed by fixed-sensor methods.

How mechanisms of perceptual decision-making affect the psychometric function.

PubMed

Gold, Joshua I; Ding, Long

2013-04-01

Psychometric functions are often interpreted in the context of Signal Detection Theory, which emphasizes a distinction between sensory processing and non-sensory decision rules in the brain. This framework has helped to relate perceptual sensitivity to the "neurometric" sensitivity of sensory-driven neural activity. However, perceptual sensitivity, as interpreted via Signal Detection Theory, is based on not just how the brain represents relevant sensory information, but also how that information is read out to form the decision variable to which the decision rule is applied. Here we discuss recent advances in our understanding of this readout process and describe its effects on the psychometric function. In particular, we show that particular aspects of the readout process can have specific, identifiable effects on the threshold, slope, upper asymptote, time dependence, and choice dependence of psychometric functions. To illustrate these points, we emphasize studies of perceptual learning that have identified changes in the readout process that can lead to changes in these aspects of the psychometric function. We also discuss methods that have been used to distinguish contributions of the sensory representation versus its readout to psychophysical performance. Copyright © 2012 Elsevier Ltd. All rights reserved.

Tracking serum antibody response to viral antigens with arrayed imaging reflectometry

NASA Astrophysics Data System (ADS)

Mace, Charles R.; Rose, Robert C.; Miller, Benjamin L.

2009-02-01

Arrayed Imaging Reflectometry, or "AIR", is a new label-free technique for detecting proteins that relies on bindinginduced changes in the response of an antireflective coating on the surface of a silicon ship. Because the technique provides high sensitivity, excellent dynamic range, and readily integrates with standard silicon wafer processing technology, it is an exceptionally attractive platform on which to build systems for detecting proteins in complex solutions. In our early research, we used AIR chips bearing secreted receptor proteins from enteropathogenic E. coli to develop sensors for this pathogen. Recently, we have been exploring an alternative strategy: Rather than detecting the pathogen directly, can one immobilize antigens from a pathogen, and employ AIR to detect antibody responses to those antigens? Such a strategy would provide enhanced sensitivity for pathogen detection (as the immune system essentially amplifies the "signal" caused by the presence of an organism to which it responds), and would also potentially prove useful in the process of vaccine development. We describe herein preliminary results in the application of such a strategy to the detection of antibodies to human papillomavirus (HPV).

Probing the size of proteins with glass nanopores

NASA Astrophysics Data System (ADS)

Steinbock, L. J.; Krishnan, S.; Bulushev, R. D.; Borgeaud, S.; Blokesch, M.; Feletti, L.; Radenovic, A.

2014-11-01

Single molecule studies using nanopores have gained attention due to the ability to sense single molecules in aqueous solution without the need to label them. In this study, short DNA molecules and proteins were detected with glass nanopores, whose sensitivity was enhanced by electron reshaping which decreased the nanopore diameter and created geometries with a reduced sensing length. Further, proteins having molecular weights (MW) ranging from 12 kDa to 480 kDa were detected, which showed that their corresponding current peak amplitude changes according to their MW. In the case of the 12 kDa ComEA protein, its DNA-binding properties to an 800 bp long DNA molecule was investigated. Moreover, the influence of the pH on the charge of the protein was demonstrated by showing a change in the translocation direction. This work emphasizes the wide spectrum of detectable molecules using nanopores from glass nanocapillaries, which stand out because of their inexpensive, lithography-free, and rapid manufacturing process.Single molecule studies using nanopores have gained attention due to the ability to sense single molecules in aqueous solution without the need to label them. In this study, short DNA molecules and proteins were detected with glass nanopores, whose sensitivity was enhanced by electron reshaping which decreased the nanopore diameter and created geometries with a reduced sensing length. Further, proteins having molecular weights (MW) ranging from 12 kDa to 480 kDa were detected, which showed that their corresponding current peak amplitude changes according to their MW. In the case of the 12 kDa ComEA protein, its DNA-binding properties to an 800 bp long DNA molecule was investigated. Moreover, the influence of the pH on the charge of the protein was demonstrated by showing a change in the translocation direction. This work emphasizes the wide spectrum of detectable molecules using nanopores from glass nanocapillaries, which stand out because of their inexpensive, lithography-free, and rapid manufacturing process. Electronic supplementary information (ESI) available. See DOI: 10.1039/c4nr05001k

Role of the neostriatal dopaminergic activity in sequencing and selecting behavioural strategies: facilitation of processes involved in selecting the best strategy in a stressful situation.

PubMed

Cools, A R

1980-10-01

The purpose of this study was to detect the behavioural effect of drug-induced changes in the neostriatal dopaminergic activity upon the degree of intrinsic (self-generated) and extrinsic (externally produced) constraints on the selection of behavioural patterns in rats. Both systemic and neostriatal injections of extremely low doses of apomorphine and haloperidol were used to change the neostriatal dopaminergic activity. Behavioural changes were observed in (a) an open-field test, (b) a so-called 'swimming without escape' test, (c) a so-called 'swimming with escape' test, and (d) a test to detect deficiencies in sensory, motor and sensorimotor capacities required to perform both swimming tests. Evidence is found that the neostriatum, especially the neostriatal, dopaminergic activity determines the animal's ability to select the best strategy in a stressful situation by modifying the process of switching strategies under pressure of factors intrinsic to the organism: neither sensory neglect nor inability to initiate voluntary movements underlay the observed phenomena. It is suggested that the neostriatum determines the individual flexibility to cope with available sensory information.

Rhodamine-based fluorescent probe for direct bio-imaging of lysosomal pH changes.

PubMed

Shi, Xue-Lin; Mao, Guo-Jiang; Zhang, Xiao-Bing; Liu, Hong-Wen; Gong, Yi-Jun; Wu, Yong-Xiang; Zhou, Li-Yi; Zhang, Jing; Tan, Weihong

2014-12-01

Intracellular pH plays a pivotal role in various biological processes. In eukaryotic cells, lysosomes contain numerous enzymes and proteins exhibiting a variety of activities and functions at acidic pH (4.5-5.5), and abnormal variation in the lysosomal pH causes defects in lysosomal function. Thus, it is important to investigate lysosomal pH in living cells to understand its physiological and pathological processes. In this work, we designed a one-step synthesized rhodamine derivative (RM) with morpholine as a lysosomes tracker, to detect lysosomal pH changes with high sensitivity, high selectivity, high photostability and low cytotoxicity. The probe RM shows a 140-fold fluorescence enhancement over a pH range from 7.4 to 4.5 with a pKa value of 5.23. Importantly, RM can detect the chloroquine-induced lysosomal pH increase and monitor the dexamethasone-induced lysosomal pH changes during apoptosis in live cells. All these features demonstrate its value of practical application in biological systems. Copyright © 2014 Elsevier B.V. All rights reserved.

An information-based approach to change-point analysis with applications to biophysics and cell biology.

PubMed

Wiggins, Paul A

2015-07-21

This article describes the application of a change-point algorithm to the analysis of stochastic signals in biological systems whose underlying state dynamics consist of transitions between discrete states. Applications of this analysis include molecular-motor stepping, fluorophore bleaching, electrophysiology, particle and cell tracking, detection of copy number variation by sequencing, tethered-particle motion, etc. We present a unified approach to the analysis of processes whose noise can be modeled by Gaussian, Wiener, or Ornstein-Uhlenbeck processes. To fit the model, we exploit explicit, closed-form algebraic expressions for maximum-likelihood estimators of model parameters and estimated information loss of the generalized noise model, which can be computed extremely efficiently. We implement change-point detection using the frequentist information criterion (which, to our knowledge, is a new information criterion). The frequentist information criterion specifies a single, information-based statistical test that is free from ad hoc parameters and requires no prior probability distribution. We demonstrate this information-based approach in the analysis of simulated and experimental tethered-particle-motion data. Copyright © 2015 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Use of a commercial wind SODAR for measuring wake vortices

DOT National Transportation Integrated Search

2006-05-01

This paper describes the application of a commercial wind SODAR (SOnic Detection : And Ranging) to the measurement of aircraft wake vortices. Changes in data collection and : processing were required to extract vortex location and circulation from th...

A Search for Temporal Changes on Pluto and Charon

NASA Astrophysics Data System (ADS)

Hofgartner, Jason D.; Buratti, Bonnie J.; Devins, Spencer; Beyer, Ross A.; Schenk, Paul M.; Stern, S. Alan; Weaver, Harold A.; Olkin, Catherine; Cheng, Andrew F.; Ennico, Kimberly; Lauer, Tod R.; Spencer, John R.; Young, Leslie; New Horizons Science Team

2017-10-01

A search for temporal changes on Pluto and Charon was motivated by (1) the discovery of young surfaces in the Pluto system that imply ongoing or recent geologic activity, (2) the detection of active plumes on Triton during the Voyager 2 flyby, and (3) the abundant and detailed information that observing geologic processes in action provides about the processes. A thorough search for temporal changes using New Horizons images was completed. Images that covered the same region were blinked and manually inspected for any differences in appearance. The search included full-disk images such that all illuminated regions of both bodies were investigated and also higher resolution images such that parts of the encounter hemispheres were investigated at finer spatial scales. Changes of appearance between different images were observed but in all cases were attributed to variability of the imaging parameters (especially geometry) or artifacts. No differences of appearance that are strongly indicative of a temporal change were found on the surface or in the atmosphere of either Pluto or Charon. Limits on temporal changes as a function of spatial scale and temporal interval during the New Horizons encounter are determined. The longest time interval constraint is one Pluto/Charon rotation period (~6.4 Earth days). Contrast reversal and high-phase bright features that change in appearance with solar phase angle are identified. The change of appearance of these features is most likely due to the change in phase angle rather than a temporal change. Had active plumes analogous to the plumes discovered on Triton been present on the encounter hemispheres of either Pluto or Charon, they would have been detected. Several dark streak features that may be deposits from past plumes are identified. The absence of active plumes may be due to temporal variability or because the process that generates Triton’s plumes does not occur on Pluto.

Evaluate ERTS imagery for mapping and detection of changes of snowcover on land and on glaciers

NASA Technical Reports Server (NTRS)

Meier, M. F. (Principal Investigator)

1973-01-01

The author has identified the following significant results. A possibly more accurate method to determine snowcover area change has been tried; snowcover area change over periods of an ERTS-1 cycle are very useful in determining energy balances over regional areas and to determine snow depth as a function of altitude. Also since shadow and cloud cover areas are highlighted this method may be a step toward more complete machine processing.

The impact of using mature compost on nitrous oxide emission and the denitrifier community in the cattle manure composting process.

PubMed

Maeda, Koki; Morioka, Riki; Hanajima, Dai; Osada, Takashi

2010-01-01

The diversity and dynamics of the denitrifying genes (nirS, nirK, and nosZ) encoding nitrite reductase and nitrous oxide (N(2)O) reductase in the dairy cattle manure composting process were investigated. A mixture of dried grass with a cattle manure compost pile and a mature compost-added pile were used, and denaturing gradient gel electrophoresis was used for denitrifier community analysis. The diversity of nirK and nosZ genes significantly changed in the initial stage of composting. These variations might have been induced by the high temperature. The diversity of nirK was constant after the initial variation. On the other hand, the diversity of nosZ changed in the latter half of the process, a change which might have been induced by the accumulation of nitrate and nitrite. The nirS gene fragments could not be detected. The use of mature compost that contains nitrate and nitrite promoted the N(2)O emission and significantly affected the variation of nosZ diversity in the initial stage of composting, but did not affect the variation of nirK diversity. Many Pseudomonas-like nirK and nosZ gene fragments were detected in the stage in which N(2)O was actively emitted.

Process Mining for Individualized Behavior Modeling Using Wireless Tracking in Nursing Homes

PubMed Central

Fernández-Llatas, Carlos; Benedi, José-Miguel; García-Gómez, Juan M.; Traver, Vicente

2013-01-01

The analysis of human behavior patterns is increasingly used for several research fields. The individualized modeling of behavior using classical techniques requires too much time and resources to be effective. A possible solution would be the use of pattern recognition techniques to automatically infer models to allow experts to understand individual behavior. However, traditional pattern recognition algorithms infer models that are not readily understood by human experts. This limits the capacity to benefit from the inferred models. Process mining technologies can infer models as workflows, specifically designed to be understood by experts, enabling them to detect specific behavior patterns in users. In this paper, the eMotiva process mining algorithms are presented. These algorithms filter, infer and visualize workflows. The workflows are inferred from the samples produced by an indoor location system that stores the location of a resident in a nursing home. The visualization tool is able to compare and highlight behavior patterns in order to facilitate expert understanding of human behavior. This tool was tested with nine real users that were monitored for a 25-week period. The results achieved suggest that the behavior of users is continuously evolving and changing and that this change can be measured, allowing for behavioral change detection. PMID:24225907

Spotlight SAR interferometry for terrain elevation mapping and interferometric change detection

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

Eichel, P.H.; Ghiglia, D.C.; Jakowatz, C.V. Jr.

1996-02-01

In this report, we employ an approach quite different from any previous work; we show that a new methodology leads to a simpler and clearer understanding of the fundamental principles of SAR interferometry. This methodology also allows implementation of an important collection mode that has not been demonstrated to date. Specifically, we introduce the following six new concepts for the processing of interferometric SAR (INSAR) data: (1) processing using spotlight mode SAR imaging (allowing ultra-high resolution), as opposed to conventional strip-mapping techniques; (2) derivation of the collection geometry constraints required to avoid decorrelation effects in two-pass INSAR; (3) derivation ofmore » maximum likelihood estimators for phase difference and the change parameter employed in interferometric change detection (ICD); (4) processing for the two-pass case wherein the platform ground tracks make a large crossing angle; (5) a robust least-squares method for two-dimensional phase unwrapping formulated as a solution to Poisson`s equation, instead of using traditional path-following techniques; and (6) the existence of a simple linear scale factor that relates phase differences between two SAR images to terrain height. We show both theoretical analysis, as well as numerous examples that employ real SAR collections to demonstrate the innovations listed above.« less

A matter of time: improvement of visual temporal processing during training-induced restoration of light detection performance

PubMed Central

Poggel, Dorothe A.; Treutwein, Bernhard; Sabel, Bernhard A.; Strasburger, Hans

2015-01-01

The issue of how basic sensory and temporal processing are related is still unresolved. We studied temporal processing, as assessed by simple visual reaction times (RT) and double-pulse resolution (DPR), in patients with partial vision loss after visual pathway lesions and investigated whether vision restoration training (VRT), a training program designed to improve light detection performance, would also affect temporal processing. Perimetric and campimetric visual field tests as well as maps of DPR thresholds and RT were acquired before and after a 3 months training period with VRT. Patient performance was compared to that of age-matched healthy subjects. Intact visual field size increased during training. Averaged across the entire visual field, DPR remained constant while RT improved slightly. However, in transition zones between the blind and intact areas (areas of residual vision) where patients had shown between 20 and 80% of stimulus detection probability in pre-training visual field tests, both DPR and RT improved markedly. The magnitude of improvement depended on the defect depth (or degree of intactness) of the respective region at baseline. Inter-individual training outcome variability was very high, with some patients showing little change and others showing performance approaching that of healthy controls. Training-induced improvement of light detection in patients with visual field loss thus generalized to dynamic visual functions. The findings suggest that similar neural mechanisms may underlie the impairment and subsequent training-induced functional recovery of both light detection and temporal processing. PMID:25717307

Spatial early warning signals in a lake manipulation

USGS Publications Warehouse

Butitta, Vince L.; Carpenter, Stephen R.; Loken, Luke; Pace, Michael L.; Stanley, Emily H.

2017-01-01

Rapid changes in state have been documented for many of Earth's ecosystems. Despite a growing toolbox of methods for detecting declining resilience or early warning indicators (EWIs) of ecosystem transitions, these methods have rarely been evaluated in whole-ecosystem trials using reference ecosystems. In this study, we experimentally tested EWIs of cyanobacteria blooms based on changes in the spatial structure of a lake. We induced a cyanobacteria bloom by adding nutrients to an experimental lake and mapped fine-resolution spatial patterning of cyanobacteria using a mobile sensor platform. Prior to the bloom, we detected theoretically predicted spatial EWIs based on variance and spatial autocorrelation, as well as a new index based on the extreme values. Changes in EWIs were not discernible in an unenriched reference lake. Despite the fluid environment of a lake where spatial heterogeneity driven by biological processes may be overwhelmed by physical mixing, spatial EWIs detected an approaching bloom suggesting the utility of spatial metrics for signaling ecological thresholds.

Development of a stable and sensitive semiconductor detector by using a mixture of lead(II) iodide and lead monoxide for NDT radiation dose detection

NASA Astrophysics Data System (ADS)

Heo, Y. J.; Kim, K. T.; Han, M. J.; Moon, C. W.; Kim, J. E.; Park, J. K.; Park, S. K.

2018-03-01

Recently, high-energy radiation has been widely used in various industrial fields, including the medical industry, and increasing research efforts have been devoted to the development of radiation detectors to be used with high-energy radiation. In particular, nondestructive industrial applications use high-energy radiation for ships and multilayered objects for accurate inspection. Therefore, it is crucial to verify the accuracy of radiation dose measurements and evaluate the precision and reproducibility of the radiation output dose. Representative detectors currently used for detecting the dose in high-energy regions include Si diodes, diamond diodes, and ionization chambers. However, the process of preparing these detectors is complex in addition to the processes of conducting dosimetric measurements, analysis, and evaluation. Furthermore, the minimum size that can be prepared for a detector is limited. In the present study, the disadvantages of original detectors are compensated by the development of a detector made of a mixture of polycrystalline PbI2 and PbO powder, which are both excellent semiconducting materials suitable for detecting high-energy gamma rays and X-rays. The proposed detector shows characteristics of excellent reproducibility and stable signal detection in response to the changes in energy, and was analyzed for its applicability. Moreover, the detector was prepared through a simple process of particle-in-binder to gain control over the thickness and meet the specific value designated by the user. A mixture mass ratio with the highest reproducibility was determined through reproducibility testing with respect to changes in the photon energy. The proposed detector was evaluated for its detection response characteristics with respect to high-energy photon beam, in terms of dose-rate dependence, sensitivity, and linearity evaluation. In the reproducibility assessment, the detector made with 15 wt% PbO powder showed the best characteristics of 0.59% and 0.25% at 6 and 15 MV, respectively. Based on its selection in the reproducibility assessment, the 15 wt% PbO detector showed no dependence on the dose-rate changes, with R-SD < 1%. Finally, a coefficient of determination of 1 in the linearity assessment demonstrated very good linearity with regards to changes in dose. These results demonstrate the applicability and usefulness of the proposed detector made from a mixture of PbI2 and PbO semiconductors.

Neuroimaging Evidence for 2 Types of Plasticity in Association with Visual Perceptual Learning.

PubMed

Shibata, Kazuhisa; Sasaki, Yuka; Kawato, Mitsuo; Watanabe, Takeo

2016-09-01

Visual perceptual learning (VPL) is long-term performance improvement as a result of perceptual experience. It is unclear whether VPL is associated with refinement in representations of the trained feature (feature-based plasticity), improvement in processing of the trained task (task-based plasticity), or both. Here, we provide empirical evidence that VPL of motion detection is associated with both types of plasticity which occur predominantly in different brain areas. Before and after training on a motion detection task, subjects' neural responses to the trained motion stimuli were measured using functional magnetic resonance imaging. In V3A, significant response changes after training were observed specifically to the trained motion stimulus but independently of whether subjects performed the trained task. This suggests that the response changes in V3A represent feature-based plasticity in VPL of motion detection. In V1 and the intraparietal sulcus, significant response changes were found only when subjects performed the trained task on the trained motion stimulus. This suggests that the response changes in these areas reflect task-based plasticity. These results collectively suggest that VPL of motion detection is associated with the 2 types of plasticity, which occur in different areas and therefore have separate mechanisms at least to some degree. © The Author 2016. Published by Oxford University Press.

Task effects on BOLD signal correlates of implicit syntactic processing

PubMed Central

Caplan, David

2010-01-01

BOLD signal was measured in sixteen participants who made timed font change detection judgments in visually presented sentences that varied in syntactic structure and the order of animate and inanimate nouns. Behavioral data indicated that sentences were processed to the level of syntactic structure. BOLD signal increased in visual association areas bilaterally and left supramarginal gyrus in the contrast of sentences with object- and subject-extracted relative clauses without font changes in which the animacy order of the nouns biased against the syntactically determined meaning of the sentence. This result differs from the findings in a non-word detection task (Caplan et al, 2008a), in which the same contrast led to increased BOLD signal in the left inferior frontal gyrus. The difference in areas of activation indicates that the sentences were processed differently in the two tasks. These differences were further explored in an eye tracking study using the materials in the two tasks. Issues pertaining to how parsing and interpretive operations are affected by a task that is being performed, and how this might affect BOLD signal correlates of syntactic contrasts, are discussed. PMID:20671983

Task effects on BOLD signal correlates of implicit syntactic processing.

PubMed

Caplan, David

2010-07-01

BOLD signal was measured in sixteen participants who made timed font change detection judgments in visually presented sentences that varied in syntactic structure and the order of animate and inanimate nouns. Behavioral data indicated that sentences were processed to the level of syntactic structure. BOLD signal increased in visual association areas bilaterally and left supramarginal gyrus in the contrast of sentences with object- and subject-extracted relative clauses without font changes in which the animacy order of the nouns biased against the syntactically determined meaning of the sentence. This result differs from the findings in a non-word detection task (Caplan et al, 2008a), in which the same contrast led to increased BOLD signal in the left inferior frontal gyrus. The difference in areas of activation indicates that the sentences were processed differently in the two tasks. These differences were further explored in an eye tracking study using the materials in the two tasks. Issues pertaining to how parsing and interpretive operations are affected by a task that is being performed, and how this might affect BOLD signal correlates of syntactic contrasts, are discussed.

Alternation blindness in the representation of binary sequences.

PubMed

Yu, Ru Qi; Osherson, Daniel; Zhao, Jiaying

2018-03-01

Binary information is prevalent in the environment and contains 2 distinct outcomes. Binary sequences consist of a mixture of alternation and repetition. Understanding how people perceive such sequences would contribute to a general theory of information processing. In this study, we examined how people process alternation and repetition in binary sequences. Across 4 paradigms involving estimation, working memory, change detection, and visual search, we found that the number of alternations is underestimated compared with repetitions (Experiment 1). Moreover, recall for binary sequences deteriorates as the sequence alternates more (Experiment 2). Changes in bits are also harder to detect as the sequence alternates more (Experiment 3). Finally, visual targets superimposed on bits of a binary sequence take longer to process as alternation increases (Experiment 4). Overall, our results indicate that compared with repetition, alternation in a binary sequence is less salient in the sense of requiring more attention for successful encoding. The current study thus reveals the cognitive constraints in the representation of alternation and provides a new explanation for the overalternation bias in randomness perception. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

The rat approximates an ideal detector of changes in rates of reward: implications for the law of effect.

PubMed

Gallistel, C R; Mark, T A; King, A P; Latham, P E

2001-10-01

Rats responded on 2 levers delivering brain stimulation reward on concurrent variable interval schedules. Following many successive sessions with unchanging relative rates of reward, subjects adjusted to an eventual change slowly and showed spontaneous reversions at the beginning of subsequent sessions. When changes in rates of reward occurred between and within every session, subjects adjusted to them about as rapidly as they could in principle do so, as shown by comparison to a Bayesian model of an ideal detector. This and other features of the adjustments to frequent changes imply that the behavioral effect of reinforcement depends on the subject's perception of incomes and changes in incomes rather than on the strengthening and weakening of behaviors in accord with their past effects or expected results. Models for the process by which perceived incomes determine stay durations and for the process that detects changes in rates are developed.

Environmental mapping and monitoring of Iceland by remote sensing (EMMIRS)

NASA Astrophysics Data System (ADS)

Pedersen, Gro B. M.; Vilmundardóttir, Olga K.; Falco, Nicola; Sigurmundsson, Friðþór S.; Rustowicz, Rose; Belart, Joaquin M.-C.; Gísladóttir, Gudrun; Benediktsson, Jón A.

2016-04-01

Iceland is exposed to rapid and dynamic landscape changes caused by natural processes and man-made activities, which impact and challenge the country. Fast and reliable mapping and monitoring techniques are needed on a big spatial scale. However, currently there is lack of operational advanced information processing techniques, which are needed for end-users to incorporate remote sensing (RS) data from multiple data sources. Hence, the full potential of the recent RS data explosion is not being fully exploited. The project Environmental Mapping and Monitoring of Iceland by Remote Sensing (EMMIRS) bridges the gap between advanced information processing capabilities and end-user mapping of the Icelandic environment. This is done by a multidisciplinary assessment of two selected remote sensing super sites, Hekla and Öræfajökull, which encompass many of the rapid natural and man-made landscape changes that Iceland is exposed to. An open-access benchmark repository of the two remote sensing supersites is under construction, providing high-resolution LIDAR topography and hyperspectral data for land-cover and landform classification. Furthermore, a multi-temporal and multi-source archive stretching back to 1945 allows a decadal evaluation of landscape and ecological changes for the two remote sensing super sites by the development of automated change detection techniques. The development of innovative pattern recognition and machine learning-based approaches to image classification and change detection is one of the main tasks of the EMMIRS project, aiming to extract and compute earth observation variables as automatically as possible. Ground reference data collected through a field campaign will be used to validate the implemented methods, which outputs are then inferred with geological and vegetation models. Here, preliminary results of an automatic land-cover classification based on hyperspectral image analysis are reported. Furthermore, the EMMIRS project investigates the complex landscape dynamics between geological and ecological processes. This is done through cross-correlation of mapping results and implementation of modelling techniques that simulate geological and ecological processes in order to extrapolate the landscape evolution

A qualitative study of contextual factors' impact on measures to reduce surgery cancellations.

PubMed

Hovlid, Einar; Bukve, Oddbjørn

2014-05-13

Contextual factors influence quality improvement outcomes. Understanding this influence is important when adapting and implementing interventions and translating improvements into new settings. To date, there is limited knowledge about how contextual factors influence quality improvement processes. In this study, we explore how contextual factors affected measures to reduce surgery cancellations, which are a persistent problem in healthcare. We discuss the usefulness of the theoretical framework provided by the model for understanding success in quality (MUSIQ) for this kind of research. We performed a qualitative case study at Førde Hospital, Norway, where we had previously demonstrated a reduction in surgery cancellations. We interviewed 20 clinicians and performed content analysis to explore how contextual factors affected measures to reduce cancellations of planned surgeries. We identified three common themes concerning how contextual factors influenced the change process: 1) identifying a need to change, 2) facilitating system-wide improvement, and 3) leader involvement and support. Input from patients helped identify a need to change and contributed to the consensus that change was necessary. Reducing cancellations required improving the clinical system. This improvement process was based on a strategy that emphasized the involvement of frontline clinicians in detecting and improving system problems. Clinicians shared information about their work by participating in improvement teams to develop a more complete understanding of the clinical system and its interdependencies. This new understanding allowed clinicians to detect system problems and design adequate interventions. Middle managers' participation in the improvement teams and in regular work processes was important for successfully implementing and adapting interventions. Contextual factors interacted with one another and with the interventions to facilitate changes in the clinical system, reducing surgery cancellations. The MUSIQ framework is useful for exploring how contextual factors influence the improvement process and how they influence one another. Discussing data in relation to a theoretical framework can promote greater uniformity in reporting findings, facilitating knowledge-building across studies.

Successful Detection of Floods in Real Time Onboard EO1 Through NASA's ST6 Autonomous Sciencecraft Experiment (ASE)

NASA Astrophysics Data System (ADS)

Ip, F.; Dohm, J. M.; Baker, V. R.; Castano, R.; Cichy, B.; Chien, S.; Davies, A.; Doggett, T.; Greeley, R.

2004-12-01

For the first time, a spacecraft has the ability to autonomously detect and react to flood events. Flood detection and the investigation of flooding dynamics in real time from space have never been done before at least not until now. Part of the challenge for the hydrological community has been the difficulty of obtaining cloud-free scenes from orbit at sufficient temporal and spatial resolutions to accurately assess flooding. In addition, the large spatial extent of drainage networks coupled with the size of the data sets necessary to be downlinked from satellites add to the difficulty of monitoring flooding from space. Technology developed as part of the Autonomous Sciencecraft Experiment (ASE) creates the new capability to autonomously detect, assess, and react to dynamic events, thereby enabling the monitoring of transient processes such as flooding in real time. In addition to being able to autonomously process the imaged data onboard the spacecraft for the first time and search the data for specific spectral features, the ASE Science Team has developed and tested change detection algorithms for the Hyperion spectrometer on EO-1. For flood events, if a change is detected in the onboard processed image (i.e. an increase in the number of ¡wet¡" pixels relative to a baseline image where the system is in normal flow condition or relatively dry), the spacecraft is autonomously retasked to obtain additional scenes. For instance, in February 2004 a rare flooding of the Australian Diamantina River was captured by EO-1. In addition, in August during ASE onboard testing a Zambezi River scene in Central Africa was successfully triggered by the classifier to autonomously take another observation. Yet another successful trigger-response flooding test scenario of the Yellow River in China was captured by ASE on 8/18/04. These exciting results pave the way for future smart reconnaissance missions of transient processes on Earth and beyond. Acknowledgments: We are grateful to the City of Tucson and Tucson Water for their support and cooperation.

Change detection in the dynamics of an intracellular protein synthesis model using nonlinear Kalman filtering.

PubMed

Rigatos, Gerasimos G; Rigatou, Efthymia G; Djida, Jean Daniel

2015-10-01

A method for early diagnosis of parametric changes in intracellular protein synthesis models (e.g. the p53 protein - mdm2 inhibitor model) is developed with the use of a nonlinear Kalman Filtering approach (Derivative-free nonlinear Kalman Filter) and of statistical change detection methods. The intracellular protein synthesis dynamic model is described by a set of coupled nonlinear differential equations. It is shown that such a dynamical system satisfies differential flatness properties and this allows to transform it, through a change of variables (diffeomorphism), to the so-called linear canonical form. For the linearized equivalent of the dynamical system, state estimation can be performed using the Kalman Filter recursion. Moreover, by applying an inverse transformation based on the previous diffeomorphism it becomes also possible to obtain estimates of the state variables of the initial nonlinear model. By comparing the output of the Kalman Filter (which is assumed to correspond to the undistorted dynamical model) with measurements obtained from the monitored protein synthesis system, a sequence of differences (residuals) is obtained. The statistical processing of the residuals with the use of x2 change detection tests, can provide indication within specific confidence intervals about parametric changes in the considered biological system and consequently indications about the appearance of specific diseases (e.g. malignancies).

Understanding the impacts of climate change and human activities on streamflow: a case study of the Soan River basin, Pakistan

NASA Astrophysics Data System (ADS)

Shahid, Muhammad; Cong, Zhentao; Zhang, Danwu

2017-09-01

Climate change and land use change are the two main factors that can alter the catchment hydrological process. The objective of this study is to evaluate the relative contribution of climate change and land use change to runoff change of the Soan River basin. The Mann-Kendal and the Pettit tests are used to find out the trends and change point in hydroclimatic variables during the period 1983-2012. Two different approaches including the abcd hydrological model and the Budyko framework are then used to quantify the impact of climate change and land use change on streamflow. The results from both methods are consistent and show that annual runoff has significantly decreased with a change point around 1997. The decrease in precipitation and increases in potential evapotranspiration contribute 68% of the detected change while the rest of the detected change is due to land use change. The land use change acquired from Landsat shows that during post-change period, the agriculture has increased in the Soan basin, which is in line with the positive contribution of land use change to runoff decrease. This study concludes that aforementioned methods performed well in quantifying the relative contribution of land use change and climate change to runoff change.

Differential Equation Models for Sharp Threshold Dynamics

DTIC Science & Technology

2012-08-01

dynamics, and the Lanchester model of armed conflict, where the loss of a key capability drastically changes dynamics. We derive and demonstrate a step...dynamics using differential equations. 15. SUBJECT TERMS Differential Equations, Markov Population Process, S-I-R Epidemic, Lanchester Model 16...infection, where a detection event drastically changes dynamics, and the Lanchester model of armed conflict, where the loss of a key capability

A space-time look at two-phase estimation for improved annual inventory estimates

Treesearch

Jay Breidt; Jean Opsomer; Xiyue Liao; Gretchen Moisen

2015-01-01

Over the past several years, three sets of new temporal remote sensing data have become available improving FIA’s ability to detect, characterize and forecast land cover changes. First, historic Landsat data has been processed for the conterminous US to provide disturbance history, agents of change, and fitted spectral trajectories annually over the last 30+ years at...

[Development of an automated processing method to detect coronary motion for coronary magnetic resonance angiography].

PubMed

Asou, Hiroya; Imada, N; Sato, T

2010-06-20

On coronary MR angiography (CMRA), cardiac motions worsen the image quality. To improve the image quality, detection of cardiac especially for individual coronary motion is very important. Usually, scan delay and duration were determined manually by the operator. We developed a new evaluation method to calculate static time of individual coronary artery. At first, coronary cine MRI was taken at the level of about 3 cm below the aortic valve (80 images/R-R). Chronological change of the signals were evaluated with Fourier transformation of each pixel of the images were done. Noise reduction with subtraction process and extraction process were done. To extract higher motion such as coronary arteries, morphological filter process and labeling process were added. Using these imaging processes, individual coronary motion was extracted and individual coronary static time was calculated automatically. We compared the images with ordinary manual method and new automated method in 10 healthy volunteers. Coronary static times were calculated with our method. Calculated coronary static time was shorter than that of ordinary manual method. And scan time became about 10% longer than that of ordinary method. Image qualities were improved in our method. Our automated detection method for coronary static time with chronological Fourier transformation has a potential to improve the image quality of CMRA and easy processing.

A modeling-based assessment of acousto-optic sensing for monitoring high-intensity focused ultrasound lesion formation

NASA Astrophysics Data System (ADS)

Adams, Matthew Tyler

Real-time acousto-optic (AO) sensing---a dual-wave modality that combines ultrasound with diffuse light to probe the optical properties of turbid media---has been demonstrated to non-invasively detect changes in ex vivo tissue optical properties during high-intensity focused ultrasound (HIFU) exposure. The AO signal indicates the onset of lesion formation and predicts resulting lesion volumes. Although proof-of-concept experiments have been successful, many of the underlying parameters and mechanisms affecting thermally induced optical property changes and the AO detectability of HIFU lesion formation are not well understood. In thesis, a numerical simulation was developed to model the AO sensing process and capture the relevant acoustic, thermal, and optical transport processes. The simulation required data that described how optical properties changed with heating. Experiments were carried out where excised chicken breast was exposed to thermal bath heating and changes in the optical absorption and scattering spectra (500 nm--1100 nm) were measured using a scanning spectrophotometer and an integrating sphere assembly. Results showed that the standard thermal dose model currently used for guiding HIFU treatments needs to be adjusted to describe thermally induced optical property changes. To model the entire AO process, coupled models were used for ultrasound propagation, tissue heating, and diffusive light transport. The angular spectrum method was used to model the acoustic field from the HIFU source. Spatial-temporal temperature elevations induced by the absorption of ultrasound were modeled using a finite-difference time-domain solution to the Pennes bioheat equation. The thermal dose model was then used to determine optical properties based on the temperature history. The diffuse optical field in the tissue was then calculated using a GPU-accelerated Monte Carlo algorithm, which accounted for light-sound interactions and AO signal detection. The simulation was used to determine the optimal design for an AO guided HIFU system by evaluating the robustness of the systems signal to changes in tissue thickness, lesion optical contrast, and lesion location. It was determined that AO sensing is a clinically viable technique for guiding the ablation of large volumes and that real-time sensing may be feasible in the breast and prostate.

Ten Years of Vegetation Change in Northern California Marshlands Detected using Landsat Satellite Image Analysis

NASA Technical Reports Server (NTRS)

Potter, Christopher

2013-01-01

The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) methodology was applied to detected changes in perennial vegetation cover at marshland sites in Northern California reported to have undergone restoration between 1999 and 2009. Results showed extensive contiguous areas of restored marshland plant cover at 10 of the 14 sites selected. Gains in either woody shrub cover and/or from recovery of herbaceous cover that remains productive and evergreen on a year-round basis could be mapped out from the image results. However, LEDAPS may not be highly sensitive changes in wetlands that have been restored mainly with seasonal herbaceous cover (e.g., vernal pools), due to the ephemeral nature of the plant greenness signal. Based on this evaluation, the LEDAPS methodology would be capable of fulfilling a pressing need for consistent, continual, low-cost monitoring of changes in marshland ecosystems of the Pacific Flyway.

An integration time adaptive control method for atmospheric composition detection of occultation

NASA Astrophysics Data System (ADS)

Ding, Lin; Hou, Shuai; Yu, Fei; Liu, Cheng; Li, Chao; Zhe, Lin

2018-01-01

When sun is used as the light source for atmospheric composition detection, it is necessary to image sun for accurate identification and stable tracking. In the course of 180 second of the occultation, the magnitude of sun light intensity through the atmosphere changes greatly. It is nearly 1100 times illumination change between the maximum atmospheric and the minimum atmospheric. And the process of light change is so severe that 2.9 times per second of light change can be reached. Therefore, it is difficult to control the integration time of sun image camera. In this paper, a novel adaptive integration time control method for occultation is presented. In this method, with the distribution of gray value in the image as the reference variable, and the concepts of speed integral PID control, the integration time adaptive control problem of high frequency imaging. The large dynamic range integration time automatic control in the occultation can be achieved.

Ventral and Dorsal Visual Stream Contributions to the Perception of Object Shape and Object Location

PubMed Central

Zachariou, Valentinos; Klatzky, Roberta; Behrmann, Marlene

2017-01-01

Growing evidence suggests that the functional specialization of the two cortical visual pathways may not be as distinct as originally proposed. Here, we explore possible contributions of the dorsal “where/how” visual stream to shape perception and, conversely, contributions of the ventral “what” visual stream to location perception in human adults. Participants performed a shape detection task and a location detection task while undergoing fMRI. For shape detection, comparable BOLD activation in the ventral and dorsal visual streams was observed, and the magnitude of this activation was correlated with behavioral performance. For location detection, cortical activation was significantly stronger in the dorsal than ventral visual pathway and did not correlate with the behavioral outcome. This asymmetry in cortical profile across tasks is particularly noteworthy given that the visual input was identical and that the tasks were matched for difficulty in performance. We confirmed the asymmetry in a subsequent psychophysical experiment in which participants detected changes in either object location or shape, while ignoring the other, task-irrelevant dimension. Detection of a location change was slowed by an irrelevant shape change matched for difficulty, but the reverse did not hold. We conclude that both ventral and dorsal visual streams contribute to shape perception, but that location processing appears to be essentially a function of the dorsal visual pathway. PMID:24001005

Mitigating Effects of Missing Data for SAR Coherent Images

DOE PAGES

Musgrove, Cameron H.; West, James C.

2017-01-01

Missing samples within synthetic aperture radar data result in image distortions. For coherent data products, such as coherent change detection and interferometric processing, the image distortion can be devastating to these second order products, resulting in missed detections and inaccurate height maps. Earlier approaches to repair the coherent data products focus upon reconstructing the missing data samples. This study demonstrates that reconstruction is not necessary to restore the quality of the coherent data products.

Rapid Development of New Protein Biosensors Utilizing Peptides Obtained via Phage Display

DTIC Science & Technology

2011-10-01

removal of loosely bound peptide or the viscosity/density change of solutions. ALT sensor operation QCM , CV and EIS measurements validated the formation...manuscript, we demonstrate this process from start to finish to create a new biosensor for the detection of ALT. Figure 6. Sensor operation. A) QCM ...peptides, peptide synthesis with a terminal thiol, QCM in-situ monitoring of peptide immobilization, and sensor detection using electrochemical techniques

Coherent Change Detection: Theoretical Description and Experimental Results

DTIC Science & Technology

2006-08-01

373–376. 47. S. M. Kay, Fundamentals of statistic signal processing. Vol 2. Detection theory. Pren- tice Hall, 1998. 48. H . Anton and C . Rorres ...Proceedings of the 1998 International Geoscience and Remote Sensing Symposium, vol. 5, 1998, pp. 2451–2453. 9. C . V. Jakowatz Jr., D. E. Wahl, P. H . Eichel...dissertation, School of Electrical and Electronic Engineering, The University of Adelaide, 2004. 20. C . H . Gierull, Statistics of SAR interferograms

An improved method for precise automatic co-registration of moderate and high-resolution spacecraft imagery

NASA Technical Reports Server (NTRS)

Bryant, Nevin A.; Logan, Thomas L.; Zobrist, Albert L.

2006-01-01

Improvements to the automated co-registration and change detection software package, AFIDS (Automatic Fusion of Image Data System) has recently completed development for and validation by NGA/GIAT. The improvements involve the integration of the AFIDS ultra-fine gridding technique for horizontal displacement compensation with the recently evolved use of Rational Polynomial Functions/ Coefficients (RPFs/RPCs) for image raster pixel position to Latitude/Longitude indexing. Mapping and orthorectification (correction for elevation effects) of satellite imagery defies exact projective solutions because the data are not obtained from a single point (like a camera), but as a continuous process from the orbital path. Standard image processing techniques can apply approximate solutions, but advances in the state-of-the-art had to be made for precision change-detection and time-series applications where relief offsets become a controlling factor. The earlier AFIDS procedure required the availability of a camera model and knowledge of the satellite platform ephemeredes. The recent design advances connect the spacecraft sensor Rational Polynomial Function, a deductively developed model, with the AFIDS ultrafine grid, an inductively developed representation of the relationship raster pixel position to latitude /longitude. As a result, RPCs can be updated by AFIDS, a situation often necessary due to the accuracy limits of spacecraft navigation systems. An example of precision change detection will be presented from Quickbird.

Granger causality analysis reveals distinct spatio-temporal connectivity patterns in motor and perceptual visuo-spatial working memory.

PubMed

Protopapa, Foteini; Siettos, Constantinos I; Evdokimidis, Ioannis; Smyrnis, Nikolaos

2014-01-01

We employed spectral Granger causality analysis on a full set of 56 electroencephalographic recordings acquired during the execution of either a 2D movement pointing or a perceptual (yes/no) change detection task with memory and non-memory conditions. On the basis of network characteristics across frequency bands, we provide evidence for the full dissociation of the corresponding cognitive processes. Movement-memory trial types exhibited higher degree nodes during the first 2 s of the delay period, mainly at central, left frontal and right-parietal areas. Change detection-memory trial types resulted in a three-peak temporal pattern of the total degree with higher degree nodes emerging mainly at central, right frontal, and occipital areas. Functional connectivity networks resulting from non-memory trial types were characterized by more sparse structures for both tasks. The movement-memory trial types encompassed an apparent coarse flow from frontal to parietal areas while the opposite flow from occipital, parietal to central and frontal areas was evident for the change detection-memory trial types. The differences among tasks and conditions were more profound in α (8-12 Hz) and β (12-30 Hz) and less in γ (30-45 Hz) band. Our results favor the hypothesis which considers spatial working memory as a by-product of specific mental processes that engages common brain areas under different network organizations.

Investigation of ultrahigh sensitivity in GaInAsP nanolaser biosensor

NASA Astrophysics Data System (ADS)

Saijo, Yoshito; Watanabe, Takumi; Hasegawa, Yu; Nishijima, Yoshiaki; Baba, Toshihiko

2018-02-01

We have developed GaInAsP semiconductor photonic crystal nanolaser biosensor and demonstrated the detection of ultralow-concentration (fM to aM) proteins and deoxyribonucleic acids (DNAs) adsorbed on the device surface. In general, this type of photonic sensors exploiting optical resonance has been considered to detect the refractive index of biomolecules via the wavelength shift. However, this principle cannot explain the detection of such ultralowconcentration. Therefore, we investigated another candidate principle, i.e., ion sensitivity. We consider such a process that 1) the electric charge of biomolecules changes the nanolaser's surface charge, 2) the Schottky barrier near the semiconductor surface is increased or decreased, 3) the distribution of photopumped carriers is modified by the barrier, 4) the refractive index of the semiconductor is changed by the carrier effects, and 5) the laser wavelength shifts. To confirm this process, we electrochemically measured the zeta and flatband potentials when charged electrolyte polymers were adsorbed in water. We clearly observed that these potentials temporally behaved consistently with that of the laser wavelength, which suggests that polymers significantly acted on the Schottky barrier. The same behaviors were also observed for the adsorption of 1 fM DNA. We consider that a limited number of charged DNA changed the surface functional group of the entire device surface. Such charge effects will be the key that achieves the ultrahigh sensitivity in the nanolaser biosensor.

Application research on land use remote sensing dynamic monitoring: A case study of Anning district, Lanzhou

NASA Astrophysics Data System (ADS)

Zhu, Yunqiang; Zhu, Huazhong; Lu, Heli; Ni, Jianguang; Zhu, Shaoxia

2005-10-01

Remote sensing dynamic monitoring of land use can detect the change information of land use and update the current land use map, which is important for rational utilization and scientific management of land resources. This paper discusses the technological procedure of remote sensing dynamic monitoring of land use including the process of remote sensing images, the extraction of annual change information of land use, field survey, indoor post processing and accuracy assessment. Especially, we emphasize on comparative research on the choice of remote sensing rectifying models, image fusion algorithms and accuracy assessment methods. Taking Anning district in Lanzhou as an example, we extract the land use change information of the district during 2002-2003, access monitoring accuracy and analyze the reason of land use change.

Multi-vehicle detection with identity awareness using cascade Adaboost and Adaptive Kalman filter for driver assistant system.

PubMed

Wang, Baofeng; Qi, Zhiquan; Chen, Sizhong; Liu, Zhaodu; Ma, Guocheng

2017-01-01

Vision-based vehicle detection is an important issue for advanced driver assistance systems. In this paper, we presented an improved multi-vehicle detection and tracking method using cascade Adaboost and Adaptive Kalman filter(AKF) with target identity awareness. A cascade Adaboost classifier using Haar-like features was built for vehicle detection, followed by a more comprehensive verification process which could refine the vehicle hypothesis in terms of both location and dimension. In vehicle tracking, each vehicle was tracked with independent identity by an Adaptive Kalman filter in collaboration with a data association approach. The AKF adaptively adjusted the measurement and process noise covariance through on-line stochastic modelling to compensate the dynamics changes. The data association correctly assigned different detections with tracks using global nearest neighbour(GNN) algorithm while considering the local validation. During tracking, a temporal context based track management was proposed to decide whether to initiate, maintain or terminate the tracks of different objects, thus suppressing the sparse false alarms and compensating the temporary detection failures. Finally, the proposed method was tested on various challenging real roads, and the experimental results showed that the vehicle detection performance was greatly improved with higher accuracy and robustness.

The role of convexity in perception of symmetry and in visual short-term memory.

PubMed

Bertamini, Marco; Helmy, Mai Salah; Hulleman, Johan

2013-01-01

Visual perception of shape is affected by coding of local convexities and concavities. For instance, a recent study reported that deviations from symmetry carried by convexities were easier to detect than deviations carried by concavities. We removed some confounds and extended this work from a detection of reflection of a contour (i.e., bilateral symmetry), to a detection of repetition of a contour (i.e., translational symmetry). We tested whether any convexity advantage is specific to bilateral symmetry in a two-interval (Experiment 1) and a single-interval (Experiment 2) detection task. In both, we found a convexity advantage only for repetition. When we removed the need to choose which region of the contour to monitor (Experiment 3) the effect disappeared. In a second series of studies, we again used shapes with multiple convex or concave features. Participants performed a change detection task in which only one of the features could change. We did not find any evidence that convexities are special in visual short-term memory, when the to-be-remembered features only changed shape (Experiment 4), when they changed shape and changed from concave to convex and vice versa (Experiment 5), or when these conditions were mixed (Experiment 6). We did find a small advantage for coding convexity as well as concavity over an isolated (and thus ambiguous) contour. The latter is consistent with the known effect of closure on processing of shape. We conclude that convexity plays a role in many perceptual tasks but that it does not have a basic encoding advantage over concavity.

Object-Based Change Detection Using High-Resolution Remotely Sensed Data and GIS

NASA Astrophysics Data System (ADS)

Sofina, N.; Ehlers, M.

2012-08-01

High resolution remotely sensed images provide current, detailed, and accurate information for large areas of the earth surface which can be used for change detection analyses. Conventional methods of image processing permit detection of changes by comparing remotely sensed multitemporal images. However, for performing a successful analysis it is desirable to take images from the same sensor which should be acquired at the same time of season, at the same time of a day, and - for electro-optical sensors - in cloudless conditions. Thus, a change detection analysis could be problematic especially for sudden catastrophic events. A promising alternative is the use of vector-based maps containing information about the original urban layout which can be related to a single image obtained after the catastrophe. The paper describes a methodology for an object-based search of destroyed buildings as a consequence of a natural or man-made catastrophe (e.g., earthquakes, flooding, civil war). The analysis is based on remotely sensed and vector GIS data. It includes three main steps: (i) generation of features describing the state of buildings; (ii) classification of building conditions; and (iii) data import into a GIS. One of the proposed features is a newly developed 'Detected Part of Contour' (DPC). Additionally, several features based on the analysis of textural information corresponding to the investigated vector objects are calculated. The method is applied to remotely sensed images of areas that have been subjected to an earthquake. The results show the high reliability of the DPC feature as an indicator for change.

A comparison of moving object detection methods for real-time moving object detection

NASA Astrophysics Data System (ADS)

Roshan, Aditya; Zhang, Yun

2014-06-01

Moving object detection has a wide variety of applications from traffic monitoring, site monitoring, automatic theft identification, face detection to military surveillance. Many methods have been developed across the globe for moving object detection, but it is very difficult to find one which can work globally in all situations and with different types of videos. The purpose of this paper is to evaluate existing moving object detection methods which can be implemented in software on a desktop or laptop, for real time object detection. There are several moving object detection methods noted in the literature, but few of them are suitable for real time moving object detection. Most of the methods which provide for real time movement are further limited by the number of objects and the scene complexity. This paper evaluates the four most commonly used moving object detection methods as background subtraction technique, Gaussian mixture model, wavelet based and optical flow based methods. The work is based on evaluation of these four moving object detection methods using two (2) different sets of cameras and two (2) different scenes. The moving object detection methods have been implemented using MatLab and results are compared based on completeness of detected objects, noise, light change sensitivity, processing time etc. After comparison, it is observed that optical flow based method took least processing time and successfully detected boundary of moving objects which also implies that it can be implemented for real-time moving object detection.

Monitoring gully change: A comparison of airborne and terrestrial laser scanning using a case study from Aratula, Queensland

NASA Astrophysics Data System (ADS)

Goodwin, Nicholas R.; Armston, John D.; Muir, Jasmine; Stiller, Issac

2017-04-01

Airborne laser scanning (ALS) and terrestrial laser scanning (TLS) technologies capture spatially detailed estimates of surface topography and when collected multi-temporally can be used to assess geomorphic change. The sensitivity and repeatability of ALS measurements to characterise geomorphic change in topographically complex environments such as gullies; however, remains an area lacking quantitative research. In this study, we captured coincident ALS and TLS datasets to assess their ability and synergies to detect geomorphic change for a gully located in Aratula, southeast Queensland, Australia. We initially used the higher spatial density and ranging accuracy of TLS to provide an assessment of the Digital Elevation Models (DEM) derived from ALS within a gully environment. Results indicated mean residual errors of 0.13 and 0.09 m along with standard deviation (SD) of residual errors of 0.20 and 0.16 m using pixel sizes of 0.5 and 1.0 m, respectively. The positive mean residual errors confirm that TLS data consistently detected deeper sections of the gully than ALS. We also compared the repeatability of ALS and TLS for characterising gully morphology. This indicated that the sensitivity to detect change using ALS is substantially lower than TLS, as expected, and that the ALS survey characteristics influence the ability to detect change. Notably, we found that using one ALS transect (mean density of 5 points / m2) as opposed to three transects increased the SD of residual error by approximately 30%. The supplied classification of ALS ground points was also demonstrated to misclassify gully features as non-ground, with minimum elevation filtering found to provide a more accurate DEM of the gully. The number and placement of terrestrial laser scans were also found to influence the derived DEMs. Furthermore, we applied change detection using two ALS data captures over a four year period and four TLS field surveys over an eight month period. This demonstrated that ALS can detect large scale erosional changes with head cutting of gully branches migrating approximately 10 m upslope. In comparison, TLS captured smaller scale intra-annual erosional patterns largely undetectable by the ALS dataset with a large rainfall event coinciding with the highest volumetric change (net change > 46 m3). Overall, these findings reaffirm the importance of quantifying DEM errors and demonstrate that ALS is unlikely to detect subtle geomorphic changes (< 0.45 m) potentially missing significant sediment change. TLS was able to detect more subtle intra-annual changes but was limited in its spatial coverage. This suggests TLS and ALS surveys are complementary technologies and when used together can provide a more detailed understanding of gully processes at different temporal and spatial scales, provided the inherent errors are taken into account.

Acetylcholine Release in Prefrontal Cortex Promotes Gamma Oscillations and Theta–Gamma Coupling during Cue Detection

PubMed Central

Hetrick, Vaughn L.; Berke, Joshua D.

2017-01-01

The capacity for using external cues to guide behavior (“cue detection”) constitutes an essential aspect of attention and goal-directed behavior. The cortical cholinergic input system, via phasic increases in prefrontal acetylcholine release, plays an essential role in attention by mediating such cue detection. However, the relationship between cholinergic signaling during cue detection and neural activity dynamics in prefrontal networks remains unclear. Here we combined subsecond measures of cholinergic signaling, neurophysiological recordings, and cholinergic receptor blockade to delineate the cholinergic contributions to prefrontal oscillations during cue detection in rats. We first confirmed that detected cues evoke phasic acetylcholine release. These cholinergic signals were coincident with increased neuronal synchrony across several frequency bands and the emergence of theta–gamma coupling. Muscarinic and nicotinic cholinergic receptors both contributed specifically to gamma synchrony evoked by detected cues, but the effects of blocking the two receptor subtypes were dissociable. Blocking nicotinic receptors primarily attenuated high-gamma oscillations occurring during the earliest phases of the cue detection process, while muscarinic (M1) receptor activity was preferentially involved in the transition from high to low gamma power that followed and corresponded to the mobilization of networks involved in cue-guided decision making. Detected cues also promoted coupling between gamma and theta oscillations, and both nicotinic and muscarinic receptor activity contributed to this process. These results indicate that acetylcholine release coordinates neural oscillations during the process of cue detection. SIGNIFICANCE STATEMENT The capacity of learned cues to direct attention and guide responding (“cue detection”) is a key component of goal-directed behavior. Rhythmic neural activity and increases in acetylcholine release in the prefrontal cortex contribute to this process; however, the relationship between these neuronal mechanisms is not well understood. Using a combination of in vivo neurochemistry, neurophysiology, and pharmacological methods, we demonstrate that cue-evoked acetylcholine release, through distinct actions at both nicotinic and muscarinic receptors, triggers a procession of neural oscillations that map onto the multiple stages of cue detection. Our data offer new insights into cholinergic function by revealing the temporally orchestrated changes in prefrontal network synchrony modulated by acetylcholine release during cue detection. PMID:28213446

The Dynamic Range Paradox: A Central Auditory Model of Intensity Change Detection

PubMed Central

Simpson, Andrew J.R.; Reiss, Joshua D.

2013-01-01

In this paper we use empirical loudness modeling to explore a perceptual sub-category of the dynamic range problem of auditory neuroscience. Humans are able to reliably report perceived intensity (loudness), and discriminate fine intensity differences, over a very large dynamic range. It is usually assumed that loudness and intensity change detection operate upon the same neural signal, and that intensity change detection may be predicted from loudness data and vice versa. However, while loudness grows as intensity is increased, improvement in intensity discrimination performance does not follow the same trend and so dynamic range estimations of the underlying neural signal from loudness data contradict estimations based on intensity just-noticeable difference (JND) data. In order to account for this apparent paradox we draw on recent advances in auditory neuroscience. We test the hypothesis that a central model, featuring central adaptation to the mean loudness level and operating on the detection of maximum central-loudness rate of change, can account for the paradoxical data. We use numerical optimization to find adaptation parameters that fit data for continuous-pedestal intensity change detection over a wide dynamic range. The optimized model is tested on a selection of equivalent pseudo-continuous intensity change detection data. We also report a supplementary experiment which confirms the modeling assumption that the detection process may be modeled as rate-of-change. Data are obtained from a listening test (N = 10) using linearly ramped increment-decrement envelopes applied to pseudo-continuous noise with an overall level of 33 dB SPL. Increments with half-ramp durations between 5 and 50,000 ms are used. The intensity JND is shown to increase towards long duration ramps (p<10−6). From the modeling, the following central adaptation parameters are derived; central dynamic range of 0.215 sones, 95% central normalization, and a central loudness JND constant of 5.5×10−5 sones per ms. Through our findings, we argue that loudness reflects peripheral neural coding, and the intensity JND reflects central neural coding. PMID:23536749

Micro-topographic hydrologic variability due to vegetation acclimation under climate change

NASA Astrophysics Data System (ADS)

Le, P. V.; Kumar, P.

2012-12-01

Land surface micro-topography and vegetation cover have fundamental effects on the land-atmosphere interactions. The altered temperature and precipitation variability associated with climate change will affect the water and energy processes both directly and that mediated through vegetation. Since climate change induces vegetation acclimation that leads to shifts in evapotranspiration and heat fluxes, it further modifies microclimate and near-surface hydrological processes. In this study, we investigate the impacts of vegetation acclimation to climate change on micro-topographic hydrologic variability. The ability to accurately predict these impacts requires the simultaneous considerations of biochemical, ecophysiological and hydrological processes. A multilayer canopy-root-soil system model coupled with a conjunctive surface-subsurface flow model is used to capture the acclimatory responses and analyze the changes in dynamics of structure and connectivity of micro-topographic storage and in magnitudes of runoff. The study is performed using Light Detection and Ranging (LiDAR) topographic data in the Birds Point-New Madrid floodway in Missouri, U.S.A. The result indicates that both climate change and its associated vegetation acclimation play critical roles in altering the micro-topographic hydrological responses.

The Detection and Characterization of Urbanization, Industrialization, and Longwall Mining Impacts on Forest Ecosystems Through the Use of GiS and Remote Sensing Techniques

NASA Astrophysics Data System (ADS)

Pfeil-McCullough, Erin Kathleen

Urbanization has far reaching and significant effects on forest ecosystems, directly through urban development and indirectly through supportive processes such as coal mining and agriculture. Urban processes modify the landscape leading to altered hillslope hydrology, increased disturbance, and the introduction of non-native forest pathogens. This dissertation addresses several challenges in our ability to detect these urbanization impacts on forests via geospatial analyses. The role of forests in urban hydrological processes has been extensively studied, but the impacts of urbanized hydrology on forests remain poorly examined. This dissertation documented impacts to hydrology and forests at variety of temporal and spatial scales: 1) A geospatial comparison of the historic and contemporary forests of Allegheny County, Pennsylvania revealed substantial shifts in tree species, but less change in the species soil moisture preference. These results document additional evidence that increased heterogeneity in urban soil moisture alters forest structure. 2) To examine soil moisture changes, impacts of longwall mine subsidence were assessed by using a Landsat based canopy moisture index and hot spot analysis tools at the forest patch scale. Declines in forest canopy moisture were detected over longwall mines as mining progressed through time, and results contradicted assumptions that the hydrological impacts overlying LMS recover within 4-5 years following subsidence of undermined land. 3) Utilizing a landslide susceptibility model (SINMAP), increases in landslide susceptibility were predicted in Pittsburgh, PA based on several scenarios of ash tree loss to the emerald ash borer (EAB), a bark beetle that rapidly kills ash trees. This model provides a tool to predict changes in landslide susceptibility following tree loss, increasing the understanding of urban forest function and its role in slope stability. Detecting how urbanized hydrology impacts forest health, function, and development is fundamental to sustaining the services forests provide. Results from this dissertation will ultimately allow improvements in the management and protection of both trees and water resources in urban systems and beyond.

Vegetation extraction from high-resolution satellite imagery using the Normalized Difference Vegetation Index (NDVI)

NASA Astrophysics Data System (ADS)

AlShamsi, Meera R.

2016-10-01

Over the past years, there has been various urban development all over the UAE. Dubai is one of the cities that experienced rapid growth in both development and population. That growth can have a negative effect on the surrounding environment. Hence, there has been a necessity to protect the environment from these fast pace changes. One of the major impacts this growth can have is on vegetation. As technology is evolving day by day, there is a possibility to monitor changes that are happening on different areas in the world using satellite imagery. The data from these imageries can be utilized to identify vegetation in different areas of an image through a process called vegetation detection. Being able to detect and monitor vegetation is very beneficial for municipal planning and management, and environment authorities. Through this, analysts can monitor vegetation growth in various areas and analyze these changes. By utilizing satellite imagery with the necessary data, different types of vegetation can be studied and analyzed, such as parks, farms, and artificial grass in sports fields. In this paper, vegetation features are detected and extracted through SAFIY system (i.e. the Smart Application for Feature extraction and 3D modeling using high resolution satellite ImagerY) by using high-resolution satellite imagery from DubaiSat-2 and DEIMOS-2 satellites, which provide panchromatic images of 1m resolution and spectral bands (red, green, blue and near infrared) of 4m resolution. SAFIY system is a joint collaboration between MBRSC and DEIMOS Space UK. It uses image-processing algorithms to extract different features (roads, water, vegetation, and buildings) to generate vector maps data. The process to extract green areas (vegetation) utilize spectral information (such as, the red and near infrared bands) from the satellite images. These detected vegetation features will be extracted as vector data in SAFIY system and can be updated and edited by end-users, such as governmental entities and municipalities.

An optimal repartitioning decision policy

NASA Technical Reports Server (NTRS)

Nicol, D. M.; Reynolds, P. F., Jr.

1986-01-01

A central problem to parallel processing is the determination of an effective partitioning of workload to processors. The effectiveness of any given partition is dependent on the stochastic nature of the workload. The problem of determining when and if the stochastic behavior of the workload has changed enough to warrant the calculation of a new partition is treated. The problem is modeled as a Markov decision process, and an optimal decision policy is derived. Quantification of this policy is usually intractable. A heuristic policy which performs nearly optimally is investigated empirically. The results suggest that the detection of change is the predominant issue in this problem.

Face Processing: Models For Recognition

NASA Astrophysics Data System (ADS)

Turk, Matthew A.; Pentland, Alexander P.

1990-03-01

The human ability to process faces is remarkable. We can identify perhaps thousands of faces learned throughout our lifetime and read facial expression to understand such subtle qualities as emotion. These skills are quite robust, despite sometimes large changes in the visual stimulus due to expression, aging, and distractions such as glasses or changes in hairstyle or facial hair. Computers which model and recognize faces will be useful in a variety of applications, including criminal identification, human-computer interface, and animation. We discuss models for representing faces and their applicability to the task of recognition, and present techniques for identifying faces and detecting eye blinks.

Time course of right ventricular pressure-overload induced myocardial fibrosis: relationship to changes in fibroblast postsynthetic procollagen processing.

PubMed

Baicu, Catalin F; Li, Jiayu; Zhang, Yuhua; Kasiganesan, Harinath; Cooper, George; Zile, Michael R; Bradshaw, Amy D

2012-11-01

Myocardial fibrillar collagen is considered an important determinant of increased ventricular stiffness in pressure-overload (PO)-induced cardiac hypertrophy. Chronic PO was created in feline right ventricles (RV) by pulmonary artery banding (PAB) to define the time course of changes in fibrillar collagen content after PO using a nonrodent model and to determine whether this time course was dependent on changes in fibroblast function. Total, soluble, and insoluble collagen (hydroxyproline), collagen volume fraction (CVF), and RV end-diastolic pressure were assessed 2 days and 1, 2, 4, and 10 wk following PAB. Fibroblast function was assessed by quantitating the product of postsynthetic processing, insoluble collagen, and levels of SPARC (secreted protein acidic and rich in cysteine), a protein that affects procollagen processing. RV hypertrophic growth was complete 2 wk after PAB. Changes in RV collagen content did not follow the same time course. Two weeks after PAB, there were elevations in total collagen (control RV: 8.84 ± 1.03 mg/g vs. 2-wk PAB: 11.50 ± 0.78 mg/g); however, increased insoluble fibrillar collagen, as measured by CVF, was not detected until 4 wk after PAB (control RV CVF: 1.39 ± 0.25% vs. 4-wk PAB: 4.18 ± 0.87%). RV end-diastolic pressure was unchanged at 2 wk, but increased until 4 wk after PAB. RV fibroblasts isolated after 2-wk PAB had no changes in either insoluble collagen or SPARC expression; however, increases in insoluble collagen and in levels of SPARC were detected in RV fibroblasts from 4-wk PAB. Therefore, the time course of PO-induced RV hypertrophy differs significantly from myocardial fibrosis and diastolic dysfunction. These temporal differences appear dependent on changes in fibroblast function.

Time course of right ventricular pressure-overload induced myocardial fibrosis: relationship to changes in fibroblast postsynthetic procollagen processing

PubMed Central

Baicu, Catalin F.; Li, Jiayu; Zhang, Yuhua; Kasiganesan, Harinath; Cooper, George; Zile, Michael R.

2012-01-01

Myocardial fibrillar collagen is considered an important determinant of increased ventricular stiffness in pressure-overload (PO)-induced cardiac hypertrophy. Chronic PO was created in feline right ventricles (RV) by pulmonary artery banding (PAB) to define the time course of changes in fibrillar collagen content after PO using a nonrodent model and to determine whether this time course was dependent on changes in fibroblast function. Total, soluble, and insoluble collagen (hydroxyproline), collagen volume fraction (CVF), and RV end-diastolic pressure were assessed 2 days and 1, 2, 4, and 10 wk following PAB. Fibroblast function was assessed by quantitating the product of postsynthetic processing, insoluble collagen, and levels of SPARC (secreted protein acidic and rich in cysteine), a protein that affects procollagen processing. RV hypertrophic growth was complete 2 wk after PAB. Changes in RV collagen content did not follow the same time course. Two weeks after PAB, there were elevations in total collagen (control RV: 8.84 ± 1.03 mg/g vs. 2-wk PAB: 11.50 ± 0.78 mg/g); however, increased insoluble fibrillar collagen, as measured by CVF, was not detected until 4 wk after PAB (control RV CVF: 1.39 ± 0.25% vs. 4-wk PAB: 4.18 ± 0.87%). RV end-diastolic pressure was unchanged at 2 wk, but increased until 4 wk after PAB. RV fibroblasts isolated after 2-wk PAB had no changes in either insoluble collagen or SPARC expression; however, increases in insoluble collagen and in levels of SPARC were detected in RV fibroblasts from 4-wk PAB. Therefore, the time course of PO-induced RV hypertrophy differs significantly from myocardial fibrosis and diastolic dysfunction. These temporal differences appear dependent on changes in fibroblast function. PMID:22942178

Visual Analysis for Detection and Quantification of Pseudomonas cichorii Disease Severity in Tomato Plants.

PubMed

Rajendran, Dhinesh Kumar; Park, Eunsoo; Nagendran, Rajalingam; Hung, Nguyen Bao; Cho, Byoung-Kwan; Kim, Kyung-Hwan; Lee, Yong Hoon

2016-08-01

Pathogen infection in plants induces complex responses ranging from gene expression to metabolic processes in infected plants. In spite of many studies on biotic stress-related changes in host plants, little is known about the metabolic and phenotypic responses of the host plants to Pseudomonas cichorii infection based on image-based analysis. To investigate alterations in tomato plants according to disease severity, we inoculated plants with different cell densities of P. cichorii using dipping and syringe infiltration methods. High-dose inocula (≥ 10(6) cfu/ml) induced evident necrotic lesions within one day that corresponded to bacterial growth in the infected tissues. Among the chlorophyll fluorescence parameters analyzed, changes in quantum yield of PSII (ΦPSII) and non-photochemical quenching (NPQ) preceded the appearance of visible symptoms, but maximum quantum efficiency of PSII (Fv/Fm) was altered well after symptom development. Visible/near infrared and chlorophyll fluorescence hyperspectral images detected changes before symptom appearance at low-density inoculation. The results of this study indicate that the P. cichorii infection severity can be detected by chlorophyll fluorescence assay and hyperspectral images prior to the onset of visible symptoms, indicating the feasibility of early detection of diseases. However, to detect disease development by hyperspectral imaging, more detailed protocols and analyses are necessary. Taken together, change in chlorophyll fluorescence is a good parameter for early detection of P. cichorii infection in tomato plants. In addition, image-based visualization of infection severity before visual damage appearance will contribute to effective management of plant diseases.

Optical Fiber On-Line Detection System for Non-Touch Monitoring Roller Shape

NASA Astrophysics Data System (ADS)

Guo, Y.; Wang, Y. T.

2006-10-01

Basing on the principle of reflective displacement fiber-optic sensor, a high accuracy non-touch on-line optical fiber measurement system for roller shape is presented. The principle and composition of the detection system and the operation process are expatiated also. By using a novel probe of three optical fibers in equal transverse space, the effects of fluctuations in the light source, reflective changing of target surface and the intensity losses in the fiber lines are automatically compensated. Meantime, an optical fiber sensor model of correcting static error based on BP artificial neural network (ANN) is set up. Also by using interpolation method and value filtering to process the signals, effectively reduce the influence of random noise and the vibration of the roller bearing. So enhance the accuracy and resolution remarkably. Experiment proves that the accuracy of the system reach to the demand of practical production process, it provides a new method for the high speed, accurate and automatic on line detection of the mill roller shape.

Detection of intensity bursts using Hawkes processes: An application to high-frequency financial data

NASA Astrophysics Data System (ADS)

Rambaldi, Marcello; Filimonov, Vladimir; Lillo, Fabrizio

2018-03-01

Given a stationary point process, an intensity burst is defined as a short time period during which the number of counts is larger than the typical count rate. It might signal a local nonstationarity or the presence of an external perturbation to the system. In this paper we propose a procedure for the detection of intensity bursts within the Hawkes process framework. By using a model selection scheme we show that our procedure can be used to detect intensity bursts when both their occurrence time and their total number is unknown. Moreover, the initial time of the burst can be determined with a precision given by the typical interevent time. We apply our methodology to the midprice change in foreign exchange (FX) markets showing that these bursts are frequent and that only a relatively small fraction is associated with news arrival. We show lead-lag relations in intensity burst occurrence across different FX rates and we discuss their relation with price jumps.

Identifying the fingerprints of the anthropogenic component of land use/land cover changes on regional climate of the USA high plains

NASA Astrophysics Data System (ADS)

Mutiibwa, D.; Irmak, S.

2011-12-01

The majority of recent climate change studies have largely focused on detection and attribution of anthropogenic forcings of greenhouse gases, aerosols, stratospheric and tropospheric ozone. However, there is growing evidence that land cover/land use (LULC) change can significantly impact atmospheric processes from local to regional weather and climate variability. Human activities such as conversion of natural ecosystem to croplands and urban-centers, deforestation and afforestation impact biophysical properties of the land surfaces including albedo, energy balance, moisture-holding capacity of soil, and surface roughness. Alterations in these properties affect the heat and moisture exchanges between the land surface and atmospheric boundary layer, and ultimately impact the climate system. The challenge is to demonstrate that LULC changes produce a signal that can be discerned from natural climate noise. In this study, we attempt to detect the signature of anthropogenic forcing of LULC change on climate on regional scale. The signal projector investigated for detecting the signature of LULC changes on regional climate of the High Plains of the USA is the Normalized Difference Vegetation Index (NDVI). NDVI is an indicator that captures short and long-term geographical distribution of vegetation surfaces. The study develops an enhanced signal processing procedure to maximize the signal to noise ratio by introducing a pre-filtering technique of ARMA processes on the investigated climate and signal variables, before applying the optimal fingerprinting technique to detect the signals of LULC changes on observed climate, temperature, in the High Plains. The intent is to filter out as much noise as possible while still retaining the essential features of the signal by making use of the known characteristics of the noise and the anticipated signal. The study discusses the approach of identifying and suppressing the autocorrelation in optimal fingerprint analysis by applying linear transformation of ARMA processes to the analysis variables. With the assumption that natural climate variability is a near stationary process, the pre-filters are developed to generate stationary residuals. The High Plains region although impacted by droughts over the last three decades has had an increase in agricultural lands, both irrigated and non-irrigated. The study shows that for the most part of the High Plains region there is significant influence of evaporative cooling on regional climate during the summer months. As the vegetation coverage increases coupled with increased in irrigation application, the regional daytime surface energy in summer is increasingly redistributed into latent heat flux which increases the effect of evaporative cooling on summer temperatures. We included the anthropogenic forcing of CO2 on regional climate with the main purpose of surpassing the radiative heating effect of greenhouse gases from natural climate noise, to enhance the LULC signal-to-noise ratio. The warming signal due to greenhouse gas forcing is observed to be weakest in the central part of the High Plains. The results showed that the CO2 signal in the region was weak or is being surpassed by the evaporative cooling effect.

Computed Tomography For Internal Inspection Of Castings

NASA Technical Reports Server (NTRS)

Hanna, Timothy L.

1995-01-01

Computed tomography used to detect internal flaws in metal castings before machining and otherwise processing them into finished parts. Saves time and money otherwise wasted on machining and other processing of castings eventually rejected because of internal defects. Knowledge of internal defects gained by use of computed tomography also provides guidance for changes in foundry techniques, procedures, and equipment to minimize defects and reduce costs.

Diurnal changes in ocean color sensed in satellite imagery

NASA Astrophysics Data System (ADS)

Arnone, Robert; Vandermuelen, Ryan; Soto, Inia; Ladner, Sherwin; Ondrusek, Michael; Yang, Haoping

2017-07-01

Measurements of diurnal changes in ocean color in turbid coastal regions in the Gulf of Mexico were characterized using above water spectral radiometry from a National Aeronautics and Space Administration (aerosol robotic network-WaveCIS CSI-06) site that can provide 8 to 10 observations per day. Satellite capability to detect diurnal changes in ocean color was characterized using hourly overlapping afternoon orbits of the visual infrared imaging radiometer suite (VIIRS) Suomi National Polar-orbiting Partnership ocean color sensor and validated with in situ observations. The monthly cycle of diurnal changes was investigated for different water masses using VIIRS overlaps. Results showed the capability of satellite observations to monitor hourly color changes in coastal regions that can be impacted by vertical movement of optical layers, in response to tides, resuspension, and river plume dispersion. The spatial variability of VIIRS diurnal changes showed the occurrence and displacement of phytoplankton blooming and decaying processes. The diurnal change in ocean color was above 20%, which represents a 30% change in chlorophyll-a. Seasonal changes in diurnal ocean color for different water masses suggest differences in summer and winter responses to surface processes. The diurnal changes observed using satellite ocean color can be used to define the following: surface processes associated with biological activity, vertical changes in optical depth, and advection of water masses.

Interfacial nano-mixing in a miniaturised platform enables signal enhancement and in situ detection of cancer biomarkers.

PubMed

Wuethrich, Alain; Sina, Abu Ali Ibn; Ahmed, Mostak; Lin, Ting-Yun; Carrascosa, Laura G; Trau, Matt

2018-06-14

Interfacial biosensing performs the detection of biomolecules at the bare-metal interface for disease diagnosis by comparing how biological species derived from patients and healthy individuals interact with bare metal surfaces. This technique retrieves clinicopathological information without complex surface functionalisation which is a major limitation of conventional techniques. However, it is still challenging to detect subtle molecular changes by interfacial biosensing, and the detection often requires prolonged sensing times due to the slow diffusion process of the biomolecules towards the sensor surface. Herein, we report on a novel strategy for interfacial biosensing which involves in situ electrochemical detection under the action of an electric field-induced nanoscopic flow at nanometre distance to the sensing surface. This nanomixing significantly increases target adsorption, reduces sensing time, and enables the detection of small molecular changes with enhanced sensitivity. Using a multiplex electrochemical microdevice that enables nanomixing and in situ label-free electrochemical detection, we demonstrate the detection of multiple cancer biomarkers on the same device. We present data for the detection of aberrant phosphorylation in the EGFR protein and hypermethylation in the EN1 gene region. Our method significantly shortens the assay period (from 40 min and 20 min to 3 minutes for protein and DNA, respectively), increases the sensitivity by up to two orders of magnitude, and improves detection specificity.

"It was like reading a detective novel": Using PAR to work together for culture change.

PubMed

Fortune, Darla; McKeown, Janet; Dupuis, Sherry; de Witt, Lorna

2015-08-01

Participatory action research (PAR), with its focus on engagement and collaboration, is uniquely suited to enhancing culture change initiatives in dementia care. Yet, there is limited literature of its application to culture change approaches in care settings, and even less in dementia specific care contexts. To address these gaps in the literature, the purpose of this paper is to examine the complexities of a PAR project aimed at changing the culture of dementia care in two diverse dementia care settings, including a long term care (LTC) and community care setting. Drawing from data gathered throughout the PAR process, we unpack the challenges experienced by participants working together to guide culture change within their respective care settings. These challenges include: overextending selves through culture change participation; fluctuating group membership; feeling uncertainty, confusion and apprehension about the process; frustratingly slow process; and seeking diverse group representation in decision making. We also highlight the potential for appreciative inquiry (AI) to be integrated with PAR to guide a process whereby participants involved in culture change initiatives can develop strategies to mitigate challenges they experience. We view the challenges and strategies shared here as being constructive to would-be culture change agents and hope this paper will move others to consider the use of PAR when engaging in culture change initiatives. Copyright © 2015 Elsevier Inc. All rights reserved.

Onboard Radar Processing Development for Rapid Response Applications

NASA Technical Reports Server (NTRS)

Lou, Yunling; Chien, Steve; Clark, Duane; Doubleday, Josh; Muellerschoen, Ron; Wang, Charles C.

2011-01-01

We are developing onboard processor (OBP) technology to streamline data acquisition on-demand and explore the potential of the L-band SAR instrument onboard the proposed DESDynI mission and UAVSAR for rapid response applications. The technology would enable the observation and use of surface change data over rapidly evolving natural hazards, both as an aid to scientific understanding and to provide timely data to agencies responsible for the management and mitigation of natural disasters. We are adapting complex science algorithms for surface water extent to detect flooding, snow/water/ice classification to assist in transportation/ shipping forecasts, and repeat-pass change detection to detect disturbances. We are near completion of the development of a custom FPGA board to meet the specific memory and processing needs of L-band SAR processor algorithms and high speed interfaces to reformat and route raw radar data to/from the FPGA processor board. We have also developed a high fidelity Matlab model of the SAR processor that is modularized and parameterized for ease to prototype various SAR processor algorithms targeted for the FPGA. We will be testing the OBP and rapid response algorithms with UAVSAR data to determine the fidelity of the products.

An energy- and depth-dependent model for x-ray imaging

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

Gallas, Brandon D.; Boswell, Jonathan S.; Badano, Aldo

In this paper, we model an x-ray imaging system, paying special attention to the energy- and depth-dependent characteristics of the inputs and interactions: x rays are polychromatic, interaction depth and conversion to optical photons is energy-dependent, optical scattering and the collection efficiency depend on the depth of interaction. The model we construct is a random function of the point process that begins with the distribution of x rays incident on the phosphor and ends with optical photons being detected by the active area of detector pixels to form an image. We show how the point-process representation can be used tomore » calculate the characteristic statistics of the model. We then simulate a Gd{sub 2}O{sub 2}S:Tb phosphor, estimate its characteristic statistics, and proceed with a signal-detection experiment to investigate the impact of the pixel fill factor on detecting spherical calcifications (the signal). The two extremes possible from this experiment are that SNR{sup 2} does not change with fill factor or changes in proportion to fill factor. In our results, the impact of fill factor is between these extremes, and depends on the diameter of the signal.« less

Frequency modulation detection in cochlear implant subjects

NASA Astrophysics Data System (ADS)

Chen, Hongbin; Zeng, Fan-Gang

2004-10-01

Frequency modulation (FM) detection was investigated in acoustic and electric hearing to characterize cochlear-implant subjects' ability to detect dynamic frequency changes and to assess the relative contributions of temporal and spectral cues to frequency processing. Difference limens were measured for frequency upward sweeps, downward sweeps, and sinusoidal FM as a function of standard frequency and modulation rate. In electric hearing, factors including electrode position and stimulation level were also studied. Electric hearing data showed that the difference limen increased monotonically as a function of standard frequency regardless of the modulation type, the modulation rate, the electrode position, and the stimulation level. In contrast, acoustic hearing data showed that the difference limen was nearly a constant as a function of standard frequency. This difference was interpreted to mean that temporal cues are used only at low standard frequencies and at low modulation rates. At higher standard frequencies and modulation rates, the reliance on the place cue is increased, accounting for the better performance in acoustic hearing than for electric hearing with single-electrode stimulation. The present data suggest a speech processing strategy that encodes slow frequency changes using lower stimulation rates than those typically employed by contemporary cochlear-implant speech processors. .

Advanced image collection, information extraction, and change detection in support of NN-20 broad area search and analysis

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

Petrie, G.M.; Perry, E.M.; Kirkham, R.R.

1997-09-01

This report describes the work performed at the Pacific Northwest National Laboratory (PNNL) for the U.S. Department of Energy`s Office of Nonproliferation and National Security, Office of Research and Development (NN-20). The work supports the NN-20 Broad Area Search and Analysis, a program initiated by NN-20 to improve the detection and classification of undeclared weapons facilities. Ongoing PNNL research activities are described in three main components: image collection, information processing, and change analysis. The Multispectral Airborne Imaging System, which was developed to collect georeferenced imagery in the visible through infrared regions of the spectrum, and flown on a light aircraftmore » platform, will supply current land use conditions. The image information extraction software (dynamic clustering and end-member extraction) uses imagery, like the multispectral data collected by the PNNL multispectral system, to efficiently generate landcover information. The advanced change detection uses a priori (benchmark) information, current landcover conditions, and user-supplied rules to rank suspect areas by probable risk of undeclared facilities or proliferation activities. These components, both separately and combined, provide important tools for improving the detection of undeclared facilities.« less

Long-term changes of the glacial seismicity: case study from Spitsbergen

NASA Astrophysics Data System (ADS)

Gajek, Wojciech; Trojanowski, Jacek; Malinowski, Michał

2016-04-01

Changes in global temperature balance have proved to have a major impact on the cryosphere, and therefore withdrawing glaciers are the symbol of the warming climate. Our study focuses on year-to-year changes in glacier-generated seismicity. We have processed 7-year long continuous seismological data recorded by the HSP broadband station located in the proximity of Hansbreen glacier (Hornsund, southern Spitsbergen), obtaining seismic activity distribution between 2008 and 2014. We developed a new fuzzy logic algorithm to distinguish between glacier- and non-glacier-origin events. The algorithm takes into account the frequency of seismic signal and the energy flow in certain time interval. Our research has revealed that the number of detected glacier-origin events over last two years has doubled. Annual events distribution correlates well with temperature and precipitation curves, illustrating characteristic yearlong behaviour of glacier seismic activity. To further support our observations, we have analysed 5-year long distribution of glacier-origin tremors detected in the vicinity of the Kronebreen glacier using KBS broadband station located in Ny-Ålesund (western Spitsbergen). We observe a steady increase in the number of detected events. detected each year, however not as significant as for Hornsund dataset.

Just one look: Direct gaze briefly disrupts visual working memory.

PubMed

Wang, J Jessica; Apperly, Ian A

2017-04-01

Direct gaze is a salient social cue that affords rapid detection. A body of research suggests that direct gaze enhances performance on memory tasks (e.g., Hood, Macrae, Cole-Davies, & Dias, Developmental Science, 1, 67-71, 2003). Nonetheless, other studies highlight the disruptive effect direct gaze has on concurrent cognitive processes (e.g., Conty, Gimmig, Belletier, George, & Huguet, Cognition, 115(1), 133-139, 2010). This discrepancy raises questions about the effects direct gaze may have on concurrent memory tasks. We addressed this topic by employing a change detection paradigm, where participants retained information about the color of small sets of agents. Experiment 1 revealed that, despite the irrelevance of the agents' eye gaze to the memory task at hand, participants were worse at detecting changes when the agents looked directly at them compared to when the agents looked away. Experiment 2 showed that the disruptive effect was relatively short-lived. Prolonged presentation of direct gaze led to recovery from the initial disruption, rather than a sustained disruption on change detection performance. The present study provides the first evidence that direct gaze impairs visual working memory with a rapidly-developing yet short-lived effect even when there is no need to attend to agents' gaze.

[Denaturation of egg antigens by cooking].

PubMed

Watanabe, Hiroko; Akaboshi, Chie; Sekido, Haruko; Tanaka, Kouki; Tanaka, Kazuko; Shimojo, Naoki

2012-01-01

Changes in egg protein contents by cooking were measured with an ELISA kit using Tris-HCl buffer in model foods including cake, meatballs, pasta and pudding made with whole egg, egg-white and egg-yolk. The egg protein contents were lowest in the deep-fried model foods of cakes and meatballs. Ovalbumin (OVA) was undetectable (<1 µg/g) and ovomucoid (OVM) was lowest in pouched meatballs, suggesting that processing temperature and uniform heat-treatment affect the detection of egg protein. Furthermore, egg protein contents were below 6 µg/g in the pouched meatballs and pasta made with egg-yolk, and OVA and OVM were not detected by Western blotting analysis with human IgE from patients' serum. On the other hand, processed egg proteins were detected with an ELISA kit using a surfactant and reductant in the extract buffer.

Auditory-Motor Rhythms and Speech Processing in French and German Listeners

PubMed Central

Falk, Simone; Volpi-Moncorger, Chloé; Dalla Bella, Simone

2017-01-01

Moving to a speech rhythm can enhance verbal processing in the listener by increasing temporal expectancies (Falk and Dalla Bella, 2016). Here we tested whether this hypothesis holds for prosodically diverse languages such as German (a lexical stress-language) and French (a non-stress language). Moreover, we examined the relation between motor performance and the benefits for verbal processing as a function of language. Sixty-four participants, 32 German and 32 French native speakers detected subtle word changes in accented positions in metrically structured sentences to which they previously tapped with their index finger. Before each sentence, they were cued by a metronome to tap either congruently (i.e., to accented syllables) or incongruently (i.e., to non-accented parts) to the following speech stimulus. Both French and German speakers detected words better when cued to tap congruently compared to incongruent tapping. Detection performance was predicted by participants' motor performance in the non-verbal cueing phase. Moreover, tapping rate while participants tapped to speech predicted detection differently for the two language groups, in particular in the incongruent tapping condition. We discuss our findings in light of the rhythmic differences of both languages and with respect to recent theories of expectancy-driven and multisensory speech processing. PMID:28443036

Detection and attribution of streamflow timing changes to climate change in the Western United States

USGS Publications Warehouse

Hidalgo, H.G.; Das, T.; Dettinger, M.D.; Cayan, D.R.; Pierce, D.W.; Barnett, T.P.; Bala, G.; Mirin, A.; Wood, A.W.; Bonfils, Celine; Santer, B.D.; Nozawa, T.

2009-01-01

This article applies formal detection and attribution techniques to investigate the nature of observed shifts in the timing of streamflow in the western United States. Previous studies have shown that the snow hydrology of the western United States has changed in the second half of the twentieth century. Such changes manifest themselves in the form of more rain and less snow, in reductions in the snow water contents, and in earlier snowmelt and associated advances in streamflow "center" timing (the day in the "water-year" on average when half the water-year flow at a point has passed). However, with one exception over a more limited domain, no other study has attempted to formally attribute these changes to anthropogenic increases of greenhouse gases in the atmosphere. Using the observations together with a set of global climate model simulations and a hydrologic model (applied to three major hydrological regions of the western United States_the California region, the upper Colorado River basin, and the Columbia River basin), it is found that the observed trends toward earlier "center" timing of snowmelt-driven streamflows in the western United States since 1950 are detectably different from natural variability (significant at the p < 0.05 level). Furthermore, the nonnatural parts of these changes can be attributed confidently to climate changes induced by anthropogenic greenhouse gases, aerosols, ozone, and land use. The signal from the Columbia dominates the analysis, and it is the only basin that showed a detectable signal when the analysis was performed on individual basins. It should be noted that although climate change is an important signal, other climatic processes have also contributed to the hydrologic variability of large basins in the western United States. ?? 2009 American Meteorological Society.

2.5D change detection from satellite imagery to monitor small-scale mining activities in the Democratic Republic of the Congo

NASA Astrophysics Data System (ADS)

Kranz, Olaf; Lang, Stefan; Schoepfer, Elisabeth

2017-09-01

Mining natural resources serve fundamental societal needs or commercial interests, but it may well turn into a driver of violence and regional instability. In this study, very high resolution (VHR) optical stereo satellite data are analysed to monitor processes and changes in one of the largest artisanal and small-scale mining sites in the Democratic Republic of the Congo, which is among the world's wealthiest countries in exploitable minerals To identify the subtle structural changes, the applied methodological framework employs object-based change detection (OBCD) based on optical VHR data and generated digital surface models (DSM). Results prove the DSM-based change detection approach enhances the assessment gained from sole 2D analyses by providing valuable information about changes in surface structure or volume. Land cover changes as analysed by OBCD reveal an increase in bare soil area by a rate of 47% between April 2010 and September 2010, followed by a significant decrease of 47.5% until March 2015. Beyond that, DSM differencing enabled the characterisation of small-scale features such as pits and excavations. The presented Earth observation (EO)-based monitoring of mineral exploitation aims at a better understanding of the relations between resource extraction and conflict, and thus providing relevant information for potential mitigation strategies and peace building.

A Micro-Resonant Gas Sensor with Nanometer Clearance between the Pole Plates

PubMed Central

Xu, Lizhong

2018-01-01

In micro-resonant gas sensors, the capacitive detection is widely used because of its simple structure. However, its shortcoming is a weak signal output caused by a small capacitance change. Here, we reduced the initial clearance between the pole plates to the nanometer level, and increased the capacitance between the pole plates and its change during resonator vibration. We propose a fabricating process of the micro-resonant gas sensor by which the initial clearance between the pole plates is reduced to the nanometer level and a micro-resonant gas sensor with 200 nm initial clearance is fabricated. With this sensor, the resonant frequency shifts were measured when they were exposed to several different vapors, and high detection accuracies were obtained. The detection accuracy with respect to ethanol vapor was 0.4 ppm per Hz shift, and the detection accuracy with respect to hydrogen and ammonias vapors was 3 ppm and 0.5 ppm per Hz shift, respectively. PMID:29373546

A Micro-Resonant Gas Sensor with Nanometer Clearance between the Pole Plates.

PubMed

Fu, Xiaorui; Xu, Lizhong

2018-01-26

In micro-resonant gas sensors, the capacitive detection is widely used because of its simple structure. However, its shortcoming is a weak signal output caused by a small capacitance change. Here, we reduced the initial clearance between the pole plates to the nanometer level, and increased the capacitance between the pole plates and its change during resonator vibration. We propose a fabricating process of the micro-resonant gas sensor by which the initial clearance between the pole plates is reduced to the nanometer level and a micro-resonant gas sensor with 200 nm initial clearance is fabricated. With this sensor, the resonant frequency shifts were measured when they were exposed to several different vapors, and high detection accuracies were obtained. The detection accuracy with respect to ethanol vapor was 0.4 ppm per Hz shift, and the detection accuracy with respect to hydrogen and ammonias vapors was 3 ppm and 0.5 ppm per Hz shift, respectively.

Applying the Quadruple Process Model to Evaluate Change in Implicit Attitudinal Responses During Therapy for Panic Disorder

PubMed Central

Clerkin, Elise M.; Fisher, Christopher R.; Sherman, Jeffrey W.; Teachman, Bethany A.

2013-01-01

Objective This study explored the automatic and controlled processes that may influence performance on an implicit measure across cognitive-behavioral group therapy for panic disorder. Method The Quadruple Process model was applied to error scores from an Implicit Association Test evaluating associations between the concepts Me (vs. Not Me) + Calm (vs. Panicked) to evaluate four distinct processes: Association Activation, Detection, Guessing, and Overcoming Bias. Parameter estimates were calculated in the panic group (n=28) across each treatment session where the IAT was administered, and at matched times when the IAT was completed in the healthy control group (n=31). Results Association Activation for Me + Calm became stronger over treatment for participants in the panic group, demonstrating that it is possible to change automatically activated associations in memory (vs. simply overriding those associations) in a clinical sample via therapy. As well, the Guessing bias toward the calm category increased over treatment for participants in the panic group. Conclusions This research evaluates key tenets about the role of automatic processing in cognitive models of anxiety, and emphasizes the viability of changing the actual activation of automatic associations in the context of treatment, versus only changing a person’s ability to use reflective processing to overcome biased automatic processing. PMID:24275066

Research on filling process of fuel and oxidant during detonation based on absorption spectrum technology

NASA Astrophysics Data System (ADS)

Lv, Xiao-Jing; Li, Ning; Weng, Chun-Sheng

2014-12-01

Research on detonation process is of great significance for the control optimization of pulse detonation engine. Based on absorption spectrum technology, the filling process of fresh fuel and oxidant during detonation is researched. As one of the most important products, H2O is selected as the target of detonation diagnosis. Fiber distributed detonation test system is designed to enable the detonation diagnosis under adverse conditions in detonation process. The test system is verified to be reliable. Laser signals at different working frequency (5Hz, 10Hz and 20Hz) are detected. Change of relative laser intensity in one detonation circle is analyzed. The duration of filling process is inferred from the change of laser intensity, which is about 100~110ms. The peak of absorption spectrum is used to present the concentration of H2O during the filling process of fresh fuel and oxidant. Absorption spectrum is calculated, and the change of absorption peak is analyzed. Duration of filling process calculated with absorption peak consisted with the result inferred from the change of relative laser intensity. The pulse detonation engine worked normally and obtained the maximum thrust at 10Hz under experiment conditions. The results are verified through H2O gas concentration monitoring during detonation.

Effect of Processing Intensity on Immunologically Active Bovine Milk Serum Proteins.

PubMed

Brick, Tabea; Ege, Markus; Boeren, Sjef; Böck, Andreas; von Mutius, Erika; Vervoort, Jacques; Hettinga, Kasper

2017-08-31

Consumption of raw cow's milk instead of industrially processed milk has been reported to protect children from developing asthma, allergies, and respiratory infections. Several heat-sensitive milk serum proteins have been implied in this effect though unbiased assessment of milk proteins in general is missing. The aim of this study was to compare the native milk serum proteome between raw cow's milk and various industrially applied processing methods, i.e., homogenization, fat separation, pasteurization, ultra-heat treatment (UHT), treatment for extended shelf-life (ESL), and conventional boiling. Each processing method was applied to the same three pools of raw milk. Levels of detectable proteins were quantified by liquid chromatography/tandem mass spectrometry following filter aided sample preparation. In total, 364 milk serum proteins were identified. The 140 proteins detectable in 66% of all samples were entered in a hierarchical cluster analysis. The resulting proteomics pattern separated mainly as high (boiling, UHT, ESL) versus no/low heat treatment (raw, skimmed, pasteurized). Comparing these two groups revealed 23 individual proteins significantly reduced by heating, e.g., lactoferrin (log2-fold change = -0.37, p = 0.004), lactoperoxidase (log2-fold change = -0.33, p = 0.001), and lactadherin (log2-fold change = -0.22, p = 0.020). The abundance of these heat sensitive proteins found in higher quantity in native cow's milk compared to heat treated milk, renders them potential candidates for protection from asthma, allergies, and respiratory infections.

[Application of hyperspectral remote sensing in research on ecological boundary in north farming-pasturing transition in China].

PubMed

Wang, Hong-Mei; Wang, Kun; Xie, Ying-Zhong

2009-06-01

Studies of ecological boundaries are important and have become a rapidly evolving part of contemporary ecology. The ecotones are dynamic and play several functional roles in ecosystem dynamics, and the changes in their locations can be used as an indicator of environment changes, and for these reasons, ecotones have recently become a focus of investigation of landscape ecology and global climate change. As the interest in ecotone increases, there is an increased need for formal techniques to detect it. Hence, to better study and understand the functional roles and dynamics of ecotones in ecosystem, we need quantitative methods to characterize them. In the semi-arid region of northern China, there exists a farming-pasturing transition resulting from grassland reclamation and deforestation. With the fragmentation of grassland landscape, the structure and function of the grassland ecosystem are changing. Given this perspective; new-image processing approaches are needed to focus on transition themselves. Hyperspectral remote sensing data, compared with wide-band remote sensing data, has the advantage of high spectral resolution. Hyperspectral remote sensing can be used to visualize transitional zones and to detect ecotone based on surface properties (e. g. vegetation, soil type, and soil moisture etc). In this paper, the methods of hyperspectral remote sensing information processing, spectral analysis and its application in detecting the vegetation classifications, vegetation growth state, estimating the canopy biochemical characteristics, soil moisture, soil organic matter etc are reviewed in detail. Finally the paper involves further application of hyperspectral remote sensing information in research on local climate in ecological boundary in north farming-pasturing transition in China.

The effect of distraction on change detection in crowded acoustic scenes.

PubMed

Petsas, Theofilos; Harrison, Jemma; Kashino, Makio; Furukawa, Shigeto; Chait, Maria

2016-11-01

In this series of behavioural experiments we investigated the effect of distraction on the maintenance of acoustic scene information in short-term memory. Stimuli are artificial acoustic 'scenes' composed of several (up to twelve) concurrent tone-pip streams ('sources'). A gap (1000 ms) is inserted partway through the 'scene'; Changes in the form of an appearance of a new source or disappearance of an existing source, occur after the gap in 50% of the trials. Listeners were instructed to monitor the unfolding 'soundscapes' for these events. Distraction was measured by presenting distractor stimuli during the gap. Experiments 1 and 2 used a dual task design where listeners were required to perform a task with varying attentional demands ('High Demand' vs. 'Low Demand') on brief auditory (Experiment 1a) or visual (Experiment 1b) signals presented during the gap. Experiments 2 and 3 required participants to ignore distractor sounds and focus on the change detection task. Our results demonstrate that the maintenance of scene information in short-term memory is influenced by the availability of attentional and/or processing resources during the gap, and that this dependence appears to be modality specific. We also show that these processes are susceptible to bottom up driven distraction even in situations when the distractors are not novel, but occur on each trial. Change detection performance is systematically linked with the, independently determined, perceptual salience of the distractor sound. The findings also demonstrate that the present task may be a useful objective means for determining relative perceptual salience. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Mineralogical Characterization of Navajo Sandstone Iron Oxide Concretions Using QEMSCAN and Reflectance Spectroscopy; Analogue for Martian Diagenetic Processes

NASA Astrophysics Data System (ADS)

Potter, S. L.; Chan, M. A.; Petersen, E. U.

2008-03-01

The Navajo Sandstone concretions were evaluated to detect mineralogical changes and chemical gradients. Sequential relationships suggest an evolution of phases of cements. The Mars "blueberries" may have a similar evolution of cements.

Interdisciplinary Coordination Reviews: A Process to Reduce Construction Costs.

ERIC Educational Resources Information Center

Fewell, Dennis A.

1998-01-01

Interdisciplinary Coordination design review is instrumental in detecting coordination errors and omissions in construction documents. Cleansing construction documents of interdisciplinary coordination errors reduces time extensions, the largest source of change orders, and limits exposure to liability claims. Improving the quality of design…

Combining Microdialysis and Electrophysiology in Cerebral Cortex to Delineate Functional Implications of Acetylcholine Gradients

NASA Astrophysics Data System (ADS)

Nelson, Kari L.

The neuronal network in cerebral cortex is a dynamic system that can undergo changes in collective neural activity as the organism changes its behavior. For example, during sleep and quiet restful awake state, many neurons tend to fire together in synchrony. In contrast, during alert awake states, firing patterns of neurons tend to be more asynchronous, firing more independently. These changes in population-level synchrony are defined as changes in cortical state. Response to sensory input is state-dependent, i.e., change in cortical state can impact the sensory information processing in cortex and introduce trial-to-trial variability in response to the same repeated stimuli. How the brain maintains reliable perception in spite of such trial-to-trial variability is a longstanding important question in neuroscience research. This dissertation is centered on two hypotheses. The first hypothesis is that different parts of the cortex can be in different states simultaneously. The second hypothesis is that inhomogeneity in cortical states can benefit the system by enabling the cortical network to maintain reliable sensory detection. If one part of the system is in a state that is not good for detection, then another part of the system could be in a different state that is good for detection, thus compensating and maintaining good detection for the system as a whole. These hypotheses were tested on anesthetized rats and awake mice. In anesthetized rats, cholinergic neuromodulation via microdialysis (muD) probes was used to induce cortical state changes in the somatosensory barrel cortex. Changes in cortical state and response to whisker stimulus was recorded with a microelectrode array (MEA). In awake mice, nucleus basalis was optogenetically stimulated by inserting an optic fiber in basal forebrain and response to visual stimulus was analyzed. The results demonstrated heterogeneity in cortical state across the spatial extent of cortical network. Changes in sensory response followed this heterogeneity and sensory detection was not reliable at the level of single neurons or small regions of cortex. The greater population of neurons, on the other hand, maintained reliable sensory detection, suggesting that heterogeneous state can be functionally beneficial for the cortical network.

Measuring and Monitoring Long Term Disaster Recovery Using Remote Sensing: A Case Study of Post Katrina New Orleans

NASA Astrophysics Data System (ADS)

Archer, Reginald S.

This research focuses on measuring and monitoring long term recovery progress from the impacts of Hurricane Katrina on New Orleans, LA. Remote sensing has frequently been used for emergency response and damage assessment after natural disasters. However, techniques for analysis of long term disaster recovery using remote sensing have not been widely explored. With increased availability and lower costs, remote sensing offers an objective perspective, systematic and repeatable analysis, and provides a substitute to multiple site visits. In addition, remote sensing allows access to large geographical areas and areas where ground access may be disrupted, restricted or denied. This dissertation addressed the primary difficulties involved in the development of change detection methods capable of detecting changes experienced by disaster recovery indicators. Maximum likelihood classification and post-classification change detection were applied to multi-temporal high resolution aerial images to quantitatively measure the progress of recovery. Images were classified to automatically identify disaster recovery indicators and exploit the indicators that are visible within each image. The spectral analysis demonstrated that employing maximum likelihood classification to high resolution true color aerial images performed adequately and provided a good indication of spectral pattern recognition, despite the limited spectral information. Applying the change detection to the classified images was effective for determining the temporal trajectory of indicators categorized as blue tarps, FEMA trailers, houses, vegetation, bare earth and pavement. The results of the post classification change detection revealed a dominant change trajectory from bluetarp to house, as damaged houses became permanently repaired. Specifically, the level of activity of blue tarps, housing, vegetation, FEMA trailers (temporary housing) pavement and bare earth were derived from aerial image processing to measure and monitor the progress of recovery. Trajectories of recovery for each individual indicator were examined to provide a better understanding of activity during reconstruction. A collection of spatial metrics was explored in order to identify spatial patterns and characterize classes in terms of patches of pixels. One of the key findings of the spatial analysis is that patch shapes were more complex in the presence of debris and damaged or destroyed buildings. The combination of spectral, temporal, and spatial analysis provided a satisfactory, though limited, solution to the question of whether remote sensing alone, can be used to quantitatively assess and monitor the progress of long term recovery following a major disaster. The research described in this dissertation provided a detailed illustration of the level of activity experienced by different recovery indicators during the long term recovery process. It also addressed the primary difficulties involved in the development of change detection methods capable of detecting changes experienced by disaster recovery indicators identified from classified high resolution true color aerial imagery. The results produced in this research demonstrate that the observed trajectories for actual indicators of recovery indicate different levels of recovery activity even within the same community. The level of activity of the long term reconstruction phase observed in the Kates model is not consistent with the level of activity of key recovery indicators in the Lower 9th Ward during the same period. Used in the proper context, these methods and results provide decision making information for determining resources. KEYWORDS: Change detection, classification, Katrina, New Orleans, remote sensing, disaster recovery, spatial metrics

Time to learn: evidence for two types of attentional guidance in contextual cueing.

PubMed

Ogawa, Hirokazu; Watanabe, Katsumi

2010-01-01

Repetition of the same spatial configurations of a search display implicitly facilitates performance of a visual-search task when the target location in the display is fixed. The improvement of performance is referred to as contextual cueing. We examined whether the association process between target location and surrounding configuration of distractors occurs during active search or at the instant the target is found. To dissociate these two processes, we changed the surrounding configuration of the distractors at the instant of target detection so that the layout where the participants had searched for the target and the layout presented at the instant of target detection differed. The results demonstrated that both processes are responsible for the contextual-cueing effect, but they differ in the accuracies of attentional guidance and their time courses, suggesting that two different types of attentional-guidance processes may be involved in contextual cueing.

Effect of the crushing process on Raman analyses: consequences for the Mars 2018 mission

NASA Astrophysics Data System (ADS)

Foucher, Frédéric; Westall, Frances; Bost, Nicolas; Rull, Fernando; Lopez-Reyes, Guillermo; Rüßmann, Philipp

2012-07-01

The payload of the 2018 Mars mission will comprise a Raman spectrometer as part of its instrument suite. Analyses with this instrument will be made on crushed samples. The crushing process will cause loss of important structural context and could change the physical properties of the studied materials resulting in misinterpretation of the data. We therefore investigated the influence of granulometry on the Raman spectrum of various minerals and rocks using laboratory equipment and the RLS Raman instrument being developed for the Pasteur payload of the ExoMars mission. The aim was to determine what influence the crushing process could have on the correct identification of rocks and minerals and the detection of possible traces of life. Whatever the sample type, our study shows that the crushing process leads to a strong increase in the background level and to a decrease in the signal/noise ratio. Moreover, for certain minerals, the Raman spectra can be significantly modified: the peaks are shifted and broadened and new peaks can appear. Since mineral identification using Raman spectroscopy is made by comparison with database spectra, this kind of change could lead to misinterpretation of the spectra and thus must be taken into account during the in situ investigation. However, the results obtained with the ExoMars instrument showed that, probably due to its irradiance and resolution characteristics, these effects are relatively limited and most of the time not observed with the RLS instrument. Finally, the loss of texture associated with the crushing process is shown to complicate identification of rocks with subsequent consequences for the eventual detection and interpretation of past traces of life. But, on the other hand, it is shown that the mixing of the components in the powder could facilitate the detection of minor phases.

Image denoising based on noise detection

NASA Astrophysics Data System (ADS)

Jiang, Yuanxiang; Yuan, Rui; Sun, Yuqiu; Tian, Jinwen

2018-03-01

Because of the noise points in the images, any operation of denoising would change the original information of non-noise pixel. A noise detection algorithm based on fractional calculus was proposed to denoise in this paper. Convolution of the image was made to gain direction gradient masks firstly. Then, the mean gray was calculated to obtain the gradient detection maps. Logical product was made to acquire noise position image next. Comparisons in the visual effect and evaluation parameters after processing, the results of experiment showed that the denoising algorithms based on noise were better than that of traditional methods in both subjective and objective aspects.

Orthorectified High Resolution Multispectral Imagery for Application to Change Detection and Analysis

NASA Technical Reports Server (NTRS)

Benkelman, Cody A.

1997-01-01

The project team has outlined several technical objectives which will allow the companies to improve on their current capabilities. These include modifications to the imaging system, enabling it to operate more cost effectively and with greater ease of use, automation of the post-processing software to mosaic and orthorectify the image scenes collected, and the addition of radiometric calibration to greatly aid in the ability to perform accurate change detection. Business objectives include fine tuning of the market plan plus specification of future product requirements, expansion of sales activities (including identification of necessary additional resources required to meet stated revenue objectives), development of a product distribution plan, and implementation of a world wide sales effort.

Image change detection systems, methods, and articles of manufacture

DOEpatents

Jones, James L.; Lassahn, Gordon D.; Lancaster, Gregory D.

2010-01-05

Aspects of the invention relate to image change detection systems, methods, and articles of manufacture. According to one aspect, a method of identifying differences between a plurality of images is described. The method includes loading a source image and a target image into memory of a computer, constructing source and target edge images from the source and target images to enable processing of multiband images, displaying the source and target images on a display device of the computer, aligning the source and target edge images, switching displaying of the source image and the target image on the display device, to enable identification of differences between the source image and the target image.

Automated detection of changes in sequential color ocular fundus images

NASA Astrophysics Data System (ADS)

Sakuma, Satoshi; Nakanishi, Tadashi; Takahashi, Yasuko; Fujino, Yuichi; Tsubouchi, Tetsuro; Nakanishi, Norimasa

1998-06-01

A recent trend is the automatic screening of color ocular fundus images. The examination of such images is used in the early detection of several adult diseases such as hypertension and diabetes. Since this type of examination is easier than CT, costs less, and has no harmful side effects, it will become a routine medical examination. Normal ocular fundus images are found in more than 90% of all people. To deal with the increasing number of such images, this paper proposes a new approach to process them automatically and accurately. Our approach, based on individual comparison, identifies changes in sequential images: a previously diagnosed normal reference image is compared to a non- diagnosed image.

A nontoxic, photostable and high signal-to-noise ratio mitochondrial probe with mitochondrial membrane potential and viscosity detectivity

NASA Astrophysics Data System (ADS)

Chen, Yanan; Qi, Jianguo; Huang, Jing; Zhou, Xiaomin; Niu, Linqiang; Yan, Zhijie; Wang, Jianhong

2018-01-01

Herein, we reported a yellow emission probe 1-methyl-4-(6-morpholino-1, 3-dioxo-1H-benzo[de]isoquinolin-2(3H)-yl) pyridin-1-ium iodide which could specifically stain mitochondria in living immortalized and normal cells. In comparison to the common mitochondria tracker (Mitotracker Deep Red, MTDR), this probe was nontoxic, photostable and ultrahigh signal-to-noise ratio, which could real-time monitor mitochondria for a long time. Moreover, this probe also showed high sensitivity towards mitochondrial membrane potential and intramitochondrial viscosity change. Consequently, this probe was used for imaging mitochondria, detecting changes in mitochondrial membrane potential and intramitochondrial viscosity in physiological and pathological processes.

Detection and Monitoring of Toxic Chemical at Ultra Trace Level by Utilizing Doped Nanomaterial

PubMed Central

Khan, Sher Bahadar; Rahman, Mohammed M.; Akhtar, Kalsoom; Asiri, Abdullah M.

2014-01-01

Composite nanoparticles were synthesized by eco-friendly hydrothermal process and characterized by different spectroscopic techniques. All the spectroscopic techniques suggested the synthesis of well crystalline optically active composite nanoparticles with average diameter of ∼30 nm. The synthesized nanoparticles were applied for the development of chemical sensor which was fabricated by coating the nanoparticles on silver electrode for the recognition of phthalimide using simple I–V technique. The developed sensor exhibited high sensitivity (1.7361 µA.mM−1.cm−2), lower detection limit (8.0 µM) and long range of detection (77.0 µM to 0.38 M). Further the resistances of composite nanoparticles based sensor was found to be 2.7 MΩ which change from 2.7 to 1.7 with change in phthalimide concentration. The major advantages of the designed sensor over existing sensors are its simple technique, low cost, lower detection limit, high sensitivity and long range of detection. It can detect phthalimide even at trace level and sense over wide range of concentrations. Therefore the composite nanoparticals would be a better choice for the fabrication of phthalimide chemical sensor and would be time and cost substituted implement for environmental safety. PMID:25329666

Influence of incident angle on the decoding in laser polarization encoding guidance

NASA Astrophysics Data System (ADS)

Zhou, Muchun; Chen, Yanru; Zhao, Qi; Xin, Yu; Wen, Hongyuan

2009-07-01

Dynamic detection of polarization states is very important for laser polarization coding guidance systems. In this paper, a set of dynamic polarization decoding and detection system used in laser polarization coding guidance was designed. Detection process of the normal incident polarized light is analyzed with Jones Matrix; the system can effectively detect changes in polarization. Influence of non-normal incident light on performance of polarization decoding and detection system is studied; analysis showed that changes in incident angle will have a negative impact on measure results, the non-normal incident influence is mainly caused by second-order birefringence and polarization sensitivity effect generated in the phase delay and beam splitter prism. Combined with Fresnel formula, decoding errors of linearly polarized light, elliptically polarized light and circularly polarized light with different incident angles into the detector are calculated respectively, the results show that the decoding errors increase with increase of incident angle. Decoding errors have relations with geometry parameters, material refractive index of wave plate, polarization beam splitting prism. Decoding error can be reduced by using thin low-order wave-plate. Simulation of detection of polarized light with different incident angle confirmed the corresponding conclusions.

A Motion Detection Algorithm Using Local Phase Information

PubMed Central

Lazar, Aurel A.; Ukani, Nikul H.; Zhou, Yiyin

2016-01-01

Previous research demonstrated that global phase alone can be used to faithfully represent visual scenes. Here we provide a reconstruction algorithm by using only local phase information. We also demonstrate that local phase alone can be effectively used to detect local motion. The local phase-based motion detector is akin to models employed to detect motion in biological vision, for example, the Reichardt detector. The local phase-based motion detection algorithm introduced here consists of two building blocks. The first building block measures/evaluates the temporal change of the local phase. The temporal derivative of the local phase is shown to exhibit the structure of a second order Volterra kernel with two normalized inputs. We provide an efficient, FFT-based algorithm for implementing the change of the local phase. The second processing building block implements the detector; it compares the maximum of the Radon transform of the local phase derivative with a chosen threshold. We demonstrate examples of applying the local phase-based motion detection algorithm on several video sequences. We also show how the locally detected motion can be used for segmenting moving objects in video scenes and compare our local phase-based algorithm to segmentation achieved with a widely used optic flow algorithm. PMID:26880882

A survey of design methods for failure detection in dynamic systems

NASA Technical Reports Server (NTRS)

Willsky, A. S.

1975-01-01

A number of methods for detecting abrupt changes (such as failures) in stochastic dynamical systems are surveyed. The class of linear systems is concentrated on but the basic concepts, if not the detailed analyses, carry over to other classes of systems. The methods surveyed range from the design of specific failure-sensitive filters, to the use of statistical tests on filter innovations, to the development of jump process formulations. Tradeoffs in complexity versus performance are discussed.

Improvement of statistical methods for detecting anomalies in climate and environmental monitoring systems

NASA Astrophysics Data System (ADS)

Yakunin, A. G.; Hussein, H. M.

2018-01-01

The article shows how the known statistical methods, which are widely used in solving financial problems and a number of other fields of science and technology, can be effectively applied after minor modification for solving such problems in climate and environment monitoring systems, as the detection of anomalies in the form of abrupt changes in signal levels, the occurrence of positive and negative outliers and the violation of the cycle form in periodic processes.

Circulating microRNAs as Biomarkers for Detection of Autologous Blood Transfusion

PubMed Central

Leuenberger, Nicolas; Schumacher, Yorck Olaf; Pradervand, Sylvain; Sander, Thomas; Saugy, Martial; Pottgiesser, Torben

2013-01-01

MicroRNAs (miRNAs) are small non-coding RNAs that regulate various biological processes. Cell-free miRNAs measured in blood plasma have emerged as specific and sensitive markers of physiological processes and disease. In this study, we investigated whether circulating miRNAs can serve as biomarkers for the detection of autologous blood transfusion, a major doping technique that is still undetectable. Plasma miRNA levels were analyzed using high-throughput quantitative real-time PCR. Plasma samples were obtained before and at several time points after autologous blood transfusion (blood bag storage time 42 days) in 10 healthy subjects and 10 controls without transfusion. Other serum markers of erythropoiesis were determined in the same samples. Our results revealed a distinct change in the pattern of circulating miRNAs. Ten miRNAs were upregulated in transfusion samples compared with control samples. Among these, miR-30b, miR-30c, and miR-26b increased significantly and showed a 3.9-, 4.0-, and 3.0-fold change, respectively. The origin of these miRNAs was related to pulmonary and liver tissues. Erythropoietin (EPO) concentration decreased after blood reinfusion. A combination of miRNAs and EPO measurement in a mathematical model enhanced the efficiency of autologous transfusion detection through miRNA analysis. Therefore, our results lay the foundation for the development of miRNAs as novel blood-based biomarkers to detect autologous transfusion. PMID:23840438

Detection of the Number of Changes in a Display in Working Memory

ERIC Educational Resources Information Center

Cowan, Nelson; Hardman, Kyle; Saults, J. Scott; Blume, Christopher L.; Clark, Katherine M.; Sunday, Mackenzie A.

2016-01-01

Here we examine a new task to assess working memory for visual arrays in which the participant must judge how many items changed from a studied array to a test array. As a clue to processing, on some trials in the first 2 experiments, participants carried out a metamemory judgment in which they were to decide how many items were in working memory.…

Non-intrusive appliance monitor apparatus

DOEpatents

Hart, George W.; Kern, Jr., Edward C.; Schweppe, Fred C.

1989-08-15

A non-intrusive monitor of energy consumption of residential appliances is described in which sensors, coupled to the power circuits entering a residence, supply analog voltage and current signals which are converted to digital format and processed to detect changes in certain residential load parameters, i.e., admittance. Cluster analysis techniques are employed to group change measurements into certain categories, and logic is applied to identify individual appliances and the energy consumed by each.

Acetylcholine Release in Prefrontal Cortex Promotes Gamma Oscillations and Theta-Gamma Coupling during Cue Detection.

PubMed

Howe, William M; Gritton, Howard J; Lusk, Nicholas A; Roberts, Erik A; Hetrick, Vaughn L; Berke, Joshua D; Sarter, Martin

2017-03-22

The capacity for using external cues to guide behavior ("cue detection") constitutes an essential aspect of attention and goal-directed behavior. The cortical cholinergic input system, via phasic increases in prefrontal acetylcholine release, plays an essential role in attention by mediating such cue detection. However, the relationship between cholinergic signaling during cue detection and neural activity dynamics in prefrontal networks remains unclear. Here we combined subsecond measures of cholinergic signaling, neurophysiological recordings, and cholinergic receptor blockade to delineate the cholinergic contributions to prefrontal oscillations during cue detection in rats. We first confirmed that detected cues evoke phasic acetylcholine release. These cholinergic signals were coincident with increased neuronal synchrony across several frequency bands and the emergence of theta-gamma coupling. Muscarinic and nicotinic cholinergic receptors both contributed specifically to gamma synchrony evoked by detected cues, but the effects of blocking the two receptor subtypes were dissociable. Blocking nicotinic receptors primarily attenuated high-gamma oscillations occurring during the earliest phases of the cue detection process, while muscarinic (M1) receptor activity was preferentially involved in the transition from high to low gamma power that followed and corresponded to the mobilization of networks involved in cue-guided decision making. Detected cues also promoted coupling between gamma and theta oscillations, and both nicotinic and muscarinic receptor activity contributed to this process. These results indicate that acetylcholine release coordinates neural oscillations during the process of cue detection. SIGNIFICANCE STATEMENT The capacity of learned cues to direct attention and guide responding ("cue detection") is a key component of goal-directed behavior. Rhythmic neural activity and increases in acetylcholine release in the prefrontal cortex contribute to this process; however, the relationship between these neuronal mechanisms is not well understood. Using a combination of in vivo neurochemistry, neurophysiology, and pharmacological methods, we demonstrate that cue-evoked acetylcholine release, through distinct actions at both nicotinic and muscarinic receptors, triggers a procession of neural oscillations that map onto the multiple stages of cue detection. Our data offer new insights into cholinergic function by revealing the temporally orchestrated changes in prefrontal network synchrony modulated by acetylcholine release during cue detection. Copyright © 2017 the authors 0270-6474/17/373215-16$15.00/0.

Process thresholds: Report of Working Group Number 3

NASA Technical Reports Server (NTRS)

Williams, R. S., Jr.

1985-01-01

The Process Thresholds Working Group concerned itself with whether a geomorphic process to be monitored on satellite imagery must be global, regional, or local in its effect on the landscape. It was pointed out that major changes in types and magnitudes of processes operating in an area are needed to be detectable on a global scale. It was concluded from a review of geomorphic studies which used satellite images that they do record change in landscape over time (on a time-lapse basis) as a result of one or more processes. In fact, this may be one of the most important attributes of space imagery, in that one can document land form changes in the form of a permanent historical record. The group also discussed the important subject of the acquisition of basic data sets by different satellite imaging systems. Geomorphologists already have available one near-global basis data set resulting from the early LANDSAT program, especially images acquired by LANDSATs 1 and 2. Such historic basic data sets can serve as a benchmark for comparison with landscape changes that take place in the future. They can also serve as a benchmark for comparison with landscape changes that have occurred in the past (as recorded) by images, photography and maps.

Study on environment detection and appraisement of mining area with RS

NASA Astrophysics Data System (ADS)

Yang, Fengjie; Hou, Peng; Zhou, Guangzhu; Li, Qingting; Wang, Jie; Cheng, Jianguang

2006-12-01

In this paper, the big coal mining area Yanzhou is selected as the typical research area. According to the special dynamic change characteristic of the environment in the mining area, the environmental dynamic changes are timely monitored with the remote sensing detection technology. Environmental special factors, such as vegetation, water, air, land-over, are extracted by the professional remote sensing image processing software, then the spatial information is managed and analyzed in the geographical information system (GIS) software. As the result, the dynamic monitor and query for change information is achieved, and the special environmental factor dynamic change maps are protracted. On the base of the data coming from the remote sensing image, GIS and the traditional environment monitoring, the environmental quality is appraised with the method of indistinct matrix analysis, the multi-index and the analytical hierarchy process. At last, those provide the credible science foundation for the local environment appraised and the sustained development. In addition, this paper apply the hyper spectrum graphs by the FieldSpec Pro spectroradiometer, together with the analytical data from environmental chemical, to study the growth of vegetation which were seed in the land-over consisting of gangue, which is a new method to study the impact to vegetation that are growing in the soil.

A quantitative and non-contact technique to characterise microstructural variations of skin tissues during photo-damaging process based on Mueller matrix polarimetry.

PubMed

Dong, Yang; He, Honghui; Sheng, Wei; Wu, Jian; Ma, Hui

2017-10-31

Skin tissue consists of collagen and elastic fibres, which are highly susceptible to damage when exposed to ultraviolet radiation (UVR), leading to skin aging and cancer. However, a lack of non-invasive detection methods makes determining the degree of UVR damage to skin in real time difficult. As one of the fundamental features of light, polarization can be used to develop imaging techniques capable of providing structural information about tissues. In particular, Mueller matrix polarimetry is suitable for detecting changes in collagen and elastic fibres. Here, we demonstrate a novel, quantitative, non-contact and in situ technique based on Mueller matrix polarimetry for monitoring the microstructural changes of skin tissues during UVR-induced photo-damaging. We measured the Mueller matrices of nude mouse skin samples, then analysed the transformed parameters to characterise microstructural changes during the skin photo-damaging and self-repairing processes. Comparisons between samples with and without the application of a sunscreen showed that the Mueller matrix-derived parameters are potential indicators for fibrous microstructure in skin tissues. Histological examination and Monte Carlo simulations confirmed the relationship between the Mueller matrix parameters and changes to fibrous structures. This technique paves the way for non-contact evaluation of skin structure in cosmetics and dermatological health.

Coupling p+n Field-Effect Transistor Circuits for Low Concentration Methane Gas Detection

PubMed Central

Zhou, Xinyuan; Yang, Liping; Bian, Yuzhi; Ma, Xiang; Chen, Yunfa

2018-01-01

Nowadays, the detection of low concentration combustible methane gas has attracted great concern. In this paper, a coupling p+n field effect transistor (FET) amplification circuit is designed to detect methane gas. By optimizing the load resistance (RL), the response to methane of the commercial MP-4 sensor can be magnified ~15 times using this coupling circuit. At the same time, it decreases the limit of detection (LOD) from several hundred ppm to ~10 ppm methane, with the apparent response of 7.0 ± 0.2 and voltage signal of 1.1 ± 0.1 V. This is promising for the detection of trace concentrations of methane gas to avoid an accidental explosion because its lower explosion limit (LEL) is ~5%. The mechanism of this coupling circuit is that the n-type FET firstly generates an output voltage (VOUT) amplification process caused by the gate voltage-induced resistance change of the FET. Then, the p-type FET continues to amplify the signal based on the previous VOUT amplification process. PMID:29509659

Coupling p+n Field-Effect Transistor Circuits for Low Concentration Methane Gas Detection.

PubMed

Zhou, Xinyuan; Yang, Liping; Bian, Yuzhi; Ma, Xiang; Han, Ning; Chen, Yunfa

2018-03-06

Nowadays, the detection of low concentration combustible methane gas has attracted great concern. In this paper, a coupling p+n field effect transistor (FET) amplification circuit is designed to detect methane gas. By optimizing the load resistance ( R L ), the response to methane of the commercial MP-4 sensor can be magnified ~15 times using this coupling circuit. At the same time, it decreases the limit of detection (LOD) from several hundred ppm to ~10 ppm methane, with the apparent response of 7.0 ± 0.2 and voltage signal of 1.1 ± 0.1 V. This is promising for the detection of trace concentrations of methane gas to avoid an accidental explosion because its lower explosion limit (LEL) is ~5%. The mechanism of this coupling circuit is that the n-type FET firstly generates an output voltage ( V OUT ) amplification process caused by the gate voltage-induced resistance change of the FET. Then, the p-type FET continues to amplify the signal based on the previous V OUT amplification process.

Interactive Computing and Processing of NASA Land Surface Observations Using Google Earth Engine

NASA Technical Reports Server (NTRS)

Molthan, Andrew; Burks, Jason; Bell, Jordan

2016-01-01

Google's Earth Engine offers a "big data" approach to processing large volumes of NASA and other remote sensing products. h\\ps://earthengine.google.com/ Interfaces include a Javascript or Python-based API, useful for accessing and processing over large periods of record for Landsat and MODIS observations. Other data sets are frequently added, including weather and climate model data sets, etc. Demonstrations here focus on exploratory efforts to perform land surface change detection related to severe weather, and other disaster events.

Interfaces detection after corneal refractive surgery by low coherence optical interferometry

PubMed Central

Verrier, I.; Veillas, C.; Lépine, T.; Nguyen, F.; Thuret, G.; Gain, P.

2010-01-01

The detection of refractive corneal surgery by LASIK, during the storage of corneas in Eye Banks will become a challenge when the numerous operated patients will arrive at the age of cornea donation. The subtle changes of corneal structure and refraction are highly suspected to negatively influence clinical results in recipients of such corneas. In order to detect LASIK cornea interfaces we developed a low coherence interferometry technique using a broadband continuum source. Real time signal recording, without moving any optical elements and without need of a Fourier Transform operation, combined with good measurement resolution is the main asset of this interferometer. The associated numerical processing is based on a method initially used in astronomy and offers an optimal correlation signal without the necessity to image the whole cornea that is time consuming. The detection of corneal interfaces - both outer and inner surface and the buried interface corresponding to the surgical wound – is then achieved directly by the innovative combination of interferometry and this original numerical process. PMID:21258562

Closed-Loop Process Control for Electron Beam Freeform Fabrication and Deposition Processes

NASA Technical Reports Server (NTRS)

Taminger, Karen M. (Inventor); Hofmeister, William H. (Inventor); Martin, Richard E. (Inventor); Hafley, Robert A. (Inventor)

2013-01-01

A closed-loop control method for an electron beam freeform fabrication (EBF(sup 3)) process includes detecting a feature of interest during the process using a sensor(s), continuously evaluating the feature of interest to determine, in real time, a change occurring therein, and automatically modifying control parameters to control the EBF(sup 3) process. An apparatus provides closed-loop control method of the process, and includes an electron gun for generating an electron beam, a wire feeder for feeding a wire toward a substrate, wherein the wire is melted and progressively deposited in layers onto the substrate, a sensor(s), and a host machine. The sensor(s) measure the feature of interest during the process, and the host machine continuously evaluates the feature of interest to determine, in real time, a change occurring therein. The host machine automatically modifies control parameters to the EBF(sup 3) apparatus to control the EBF(sup 3) process in a closed-loop manner.

Potential of different mechanical and thermal treatments to control off-flavour generation in broccoli puree.

PubMed

Koutidou, Maria; Grauwet, Tara; Van Loey, Ann; Acharya, Parag

2017-02-15

The aim of this study was scientifically investigate the impact of the sequence of different thermo-mechanical treatments on the volatile profile of differently processed broccoli puree, and to investigate if any relationship persists between detected off-flavour changes and microstructural changes as a function of selected process conditions. Comparison of the headspace GC-MS fingerprinting of the differently processed broccoli purees revealed that an adequate combination of processing steps allows to reduce the level of off-flavour volatiles. Moreover, applying mechanical processing before or after the thermal processing at 90°C determines the pattern of broccoli tissue disruption, resulting into different microstructures and various enzymatic reactions inducing volatile generation. These results may aid the identification of optimal process conditions generating a reduced level of off-flavour in processed broccoli. In this way, broccoli can be incorporated as a food ingredient into mixed food products with limited implications on sensorial consumer acceptance. Copyright © 2016 Elsevier Ltd. All rights reserved.

Integrating SAR and derived products into operational volcano monitoring and decision support systems

NASA Astrophysics Data System (ADS)

Meyer, F. J.; McAlpin, D. B.; Gong, W.; Ajadi, O.; Arko, S.; Webley, P. W.; Dehn, J.

2015-02-01

Remote sensing plays a critical role in operational volcano monitoring due to the often remote locations of volcanic systems and the large spatial extent of potential eruption pre-cursor signals. Despite the all-weather capabilities of radar remote sensing and its high performance in monitoring of change, the contribution of radar data to operational monitoring activities has been limited in the past. This is largely due to: (1) the high costs associated with radar data; (2) traditionally slow data processing and delivery procedures; and (3) the limited temporal sampling provided by spaceborne radars. With this paper, we present new data processing and data integration techniques that mitigate some of these limitations and allow for a meaningful integration of radar data into operational volcano monitoring decision support systems. Specifically, we present fast data access procedures as well as new approaches to multi-track processing that improve near real-time data access and temporal sampling of volcanic systems with SAR data. We introduce phase-based (coherent) and amplitude-based (incoherent) change detection procedures that are able to extract dense time series of hazard information from these data. For a demonstration, we present an integration of our processing system with an operational volcano monitoring system that was developed for use by the Alaska Volcano Observatory (AVO). Through an application to a historic eruption, we show that the integration of SAR into systems such as AVO can significantly improve the ability of operational systems to detect eruptive precursors. Therefore, the developed technology is expected to improve operational hazard detection, alerting, and management capabilities.

RNA-Seq analysis reveals new evidence for inflammation-related changes in aged kidney

PubMed Central

Park, Daeui; Kim, Byoung-Chul; Kim, Chul-Hong; Choi, Yeon Ja; Jeong, Hyoung Oh; Kim, Mi Eun; Lee, Jun Sik; Park, Min Hi; Chung, Ki Wung; Kim, Dae Hyun; Lee, Jaewon; Im, Dong-Soon; Yoon, Seokjoo; Lee, Sunghoon; Yu, Byung Pal; Bhak, Jong; Chung, Hae Young

2016-01-01

Age-related dysregulated inflammation plays an essential role as a major risk factor underlying the pathophysiological aging process. To better understand how inflammatory processes are related to aging at the molecular level, we sequenced the transcriptome of young and aged rat kidney using RNA-Seq to detect known genes, novel genes, and alternative splicing events that are differentially expressed. By comparing young (6 months of age) and old (25 months of age) rats, we detected 722 up-regulated genes and 111 down-regulated genes. In the aged rats, we found 32 novel genes and 107 alternatively spliced genes. Notably, 6.6% of the up-regulated genes were related to inflammation (P < 2.2 × 10−16, Fisher exact t-test); 15.6% were novel genes with functional protein domains (P = 1.4 × 10−5); and 6.5% were genes showing alternative splicing events (P = 3.3 × 10−4). Based on the results of pathway analysis, we detected the involvement of inflammation-related pathways such as cytokines (P = 4.4 × 10−16), which were found up-regulated in the aged rats. Furthermore, an up-regulated inflammatory gene analysis identified the involvement of transcription factors, such as STAT4, EGR1, and FOSL1, which regulate cancer as well as inflammation in aging processes. Thus, RNA changes in these pathways support their involvement in the pro-inflammatory status during aging. We propose that whole RNA-Seq is a useful tool to identify novel genes and alternative splicing events by documenting broadly implicated inflammation-related genes involved in aging processes. PMID:27153548

Use of uterine electromyography to diagnose term and preterm labor

PubMed Central

LUCOVNIK, MIHA; KUON, RUBEN J.; CHAMBLISS, LINDA R.; MANER, WILLIAM L.; SHI, SHAO-QING; SHI, LEILI; BALDUCCI, JAMES; GARFIELD, ROBERT E.

2011-01-01

Current methodologies to assess the process of labor, such as tocodynamometry or intrauterine pressure catheters, fetal fibronectin, cervical length measurement and digital cervical examination, have several major drawbacks. They only measure the onset of labor indirectly and do not detect cellular changes characteristic of true labor. Consequently, their predictive values for term or preterm delivery are poor. Uterine contractions are a result of the electrical activity within the myometrium. Measurement of uterine electromyography (EMG) has been shown to detect contractions as accurately as the currently used methods. In addition, changes in cell excitability and coupling required for effective contractions that lead to delivery are reflected in changes of several EMG parameters. Use of uterine EMG can help to identify patients in true labor better than any other method presently employed in the clinic. PMID:21241260

A novel reaction-based colorimetric and ratiometric fluorescent sensor for cyanide anion with a large emission shift and high selectivity.

PubMed

Wang, Shaodan; Fei, Xiaoliang; Guo, Jing; Yang, Qingbiao; Li, Yaoxian; Song, Yan

2016-01-01

A hybrid carbazole-hemicyanine dye (Cac) has been developed as a novel colorimetric and ratiometric fluorescent sensor for cyanide detection. Upon treatment with cyanide, Cac displayed a remarkable fluorescence ratiometric response, with the emission wavelength displaying a very large emission shift (214 nm). The detection of cyanide was performed via the nucleophilic addition of cyanide anion to the indolium group of the sensor, which resulted in the blocking of the intramolecular charge transfer (ICT) process in the sensor, inducing a ratiometric fluorescence change and simultaneously an obvious color change. Furthermore, competitive anions did not showed any significant changes both in color and emission intensity ratio (I381/I595), indicating the high selectivity of the sensor to CN(-). Copyright © 2015 Elsevier B.V. All rights reserved.

Imaging, object detection, and change detection with a polarized multistatic GPR array

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

Beer, N. Reginald; Paglieroni, David W.

A polarized detection system performs imaging, object detection, and change detection factoring in the orientation of an object relative to the orientation of transceivers. The polarized detection system may operate on one of several modes of operation based on whether the imaging, object detection, or change detection is performed separately for each transceiver orientation. In combined change mode, the polarized detection system performs imaging, object detection, and change detection separately for each transceiver orientation, and then combines changes across polarizations. In combined object mode, the polarized detection system performs imaging and object detection separately for each transceiver orientation, and thenmore » combines objects across polarizations and performs change detection on the result. In combined image mode, the polarized detection system performs imaging separately for each transceiver orientation, and then combines images across polarizations and performs object detection followed by change detection on the result.« less

Spatial Probability Dynamically Modulates Visual Target Detection in Chickens

PubMed Central

Sridharan, Devarajan; Ramamurthy, Deepa L.; Knudsen, Eric I.

2013-01-01

The natural world contains a rich and ever-changing landscape of sensory information. To survive, an organism must be able to flexibly and rapidly locate the most relevant sources of information at any time. Humans and non-human primates exploit regularities in the spatial distribution of relevant stimuli (targets) to improve detection at locations of high target probability. Is the ability to flexibly modify behavior based on visual experience unique to primates? Chickens (Gallus domesticus) were trained on a multiple alternative Go/NoGo task to detect a small, briefly-flashed dot (target) in each of the quadrants of the visual field. When targets were presented with equal probability (25%) in each quadrant, chickens exhibited a distinct advantage for detecting targets at lower, relative to upper, hemifield locations. Increasing the probability of presentation in the upper hemifield locations (to 80%) dramatically improved detection performance at these locations to be on par with lower hemifield performance. Finally, detection performance in the upper hemifield changed on a rapid timescale, improving with successive target detections, and declining with successive detections at the diagonally opposite location in the lower hemifield. These data indicate the action of a process that in chickens, as in primates, flexibly and dynamically modulates detection performance based on the spatial probabilities of sensory stimuli as well as on recent performance history. PMID:23734188

An Online 3D Database System for Endangered Architectural and Archaeological Heritage in the South-Eastern Mediterranean

NASA Astrophysics Data System (ADS)

Abate, D.; Avgousti, A.; Faka, M.; Hermon, S.; Bakirtzis, N.; Christofi, P.

2017-10-01

This study compares performance of aerial image based point clouds (IPCs) and light detection and ranging (LiDAR) based point clouds in detection of thinnings and clear cuts in forests. IPCs are an appealing method to update forest resource data, because of their accuracy in forest height estimation and cost-efficiency of aerial image acquisition. We predicted forest changes over a period of three years by creating difference layers that displayed the difference in height or volume between the initial and subsequent time points. Both IPCs and LiDAR data were used in this process. The IPCs were constructed with the Semi-Global Matching (SGM) algorithm. Difference layers were constructed by calculating differences in fitted height or volume models or in canopy height models (CHMs) from both time points. The LiDAR-derived digital terrain model (DTM) was used to scale heights to above ground level. The study area was classified in logistic regression into the categories ClearCut, Thinning or NoChange with the values from the difference layers. We compared the predicted changes with the true changes verified in the field, and obtained at best a classification accuracy for clear cuts 93.1 % with IPCs and 91.7 % with LiDAR data. However, a classification accuracy for thinnings was only 8.0 % with IPCs. With LiDAR data 41.4 % of thinnings were detected. In conclusion, the LiDAR data proved to be more accurate method to predict the minor changes in forests than IPCs, but both methods are useful in detection of major changes.

The potential of GRACE gravimetry to detect the heavy rainfall-induced impoundment of a small reservoir in the upper Yellow River

NASA Astrophysics Data System (ADS)

Yi, Shuang; Song, Chunqiao; Wang, Qiuyu; Wang, Linsong; Heki, Kosuke; Sun, Wenke

2017-08-01

Artificial reservoirs are important indicators of anthropogenic impacts on environments, and their cumulative influences on the local water storage will change the gravity signal. However, because of their small signal size, such gravity changes are seldom studied using satellite gravimetry from the Gravity Recovery and Climate Experiment (GRACE). Here we investigate the ability of GRACE to detect water storage changes in the Longyangxia Reservoir (LR), which is situated in the upper main stem of the Yellow River. Three different GRACE solutions from the CSR, GFZ, and JPL with three different processing filters are compared here. We find that heavy precipitation in the summer of 2005 caused the LR water storage to increase by 37.9 m in height, which is equivalent to 13.0 Gt in mass, and that the CSR solutions with a DDK4 filter show the best performance in revealing the synthetic gravity signals. We also obtain 109 pairs of reservoir inundation area measurements from satellite imagery and water level changes from laser altimetry and in situ observations to derive the area-height ratios for the LR. The root mean square of GRACE series in the LR is reduced by 39% after removing synthetic signals caused by mass changes in the LR or by 62% if the GRACE series is further smoothed. We conclude that GRACE data show promising potential in detecting water storage changes in this ˜400 km2 reservoir and that a small signal size is not a restricting factor for detection using GRACE data.

Comparison of Seasonal Terrestrial Water Storage Variations from GRACE with Groundwater-level Measurements from the High Plains Aquifer (USA)

NASA Technical Reports Server (NTRS)

Strassberg, Gil; Scanlon, Bridget R.; Rodell, Matthew

2007-01-01

This study presents the first direct comparison of variations in seasonal GWS derived from GRACE TWS and simulated SM with GW-level measurements in a semiarid region. Results showed that variations in GWS and SM are the main sources controlling TWS changes over the High Plains, with negligible storage changes from surface water, snow, and biomass. Seasonal variations in GRACE TWS compare favorably with combined GWS from GW-level measurements (total 2,700 wells, average 1,050 GW-level measurements per season) and simulated SM from the Noah land surface model (R = 0.82, RMSD = 33 mm). Estimated uncertainty in seasonal GRACE-derived TWS is 8 mm, and estimated uncertainty in TWS changes is 11 mm. Estimated uncertainty in SM changes is 11 mm and combined uncertainty for TWS-SM changes is 15 mm. Seasonal TWS changes are detectable in 7 out of 9 monitored periods and maximum changes within a year (e.g. between winter and summer) are detectable in all 5 monitored periods. Grace-derived GWS calculated from TWS-SM generally agrees with estimates based on GW-level measurements (R = 0.58, RMSD = 33 mm). Seasonal TWS-SM changes are detectable in 5 out of the 9 monitored periods and maximum changes are detectable in all 5 monitored periods. Good correspondence between GRACE data and GW-level measurements from the intensively monitored High Plains aquifer validates the potential for using GRACE TWS and simulated SM to monitor GWS changes and aquifer depletion in semiarid regions subjected to intensive irrigation pumpage. This method can be used to monitor regions where large-scale aquifer depletion is ongoing, and in situ measurements are limited, such as the North China Plain or western India. This potential should be enhanced by future advances in GRACE processing, which will improve the spatial and temporal resolution of TWS changes, and will further increase applicability of GRACE data for monitoring GWS.

Long-term Satellite NDVI Data Sets: Evaluating Their Ability to Detect Ecosystem Functional Changes in South America.

PubMed

Baldi, Germán; Nosetto, Marcelo D; Aragón, Roxana; Aversa, Fernando; Paruelo, José M; Jobbágy, Esteban G

2008-09-03

In the last decades, South American ecosystems underwent important functional modifications due to climate alterations and direct human intervention on land use and land cover. Among remotely sensed data sets, NOAA-AVHRR "Normalized Difference Vegetation Index" (NDVI) represents one of the most powerful tools to evaluate these changes thanks to their extended temporal coverage. In this paper we explored the possibilities and limitations of three commonly used NOAA-AVHRR NDVI series (PAL, GIMMS and FASIR) to detect ecosystem functional changes in the South American continent. We performed pixel-based linear regressions for four NDVI variables (average annual, maximum annual, minimum annual and intra-annual coefficient of variation) for the 1982-1999 period and (1) analyzed the convergences and divergences of significant multi-annual trends identified across all series, (2) explored the degree of aggregation of the trends using the O-ring statistic, and (3) evaluated observed trends using independent information on ecosystem functional changes in five focal regions. Several differences arose in terms of the patterns of change (the sign, localization and total number of pixels with changes). FASIR presented the highest proportion of changing pixels (32.7%) and GIMMS the lowest (16.2%). PAL and FASIR data sets showed the highest agreement, with a convergence of detected trends on 71.2% of the pixels. Even though positive and negative changes showed substantial spatial aggregation, important differences in the scale of aggregation emerged among the series, with GIMMS showing the smaller scale (≤11 pixels). The independent evaluations suggest higher accuracy in the detection of ecosystem changes among PAL and FASIR series than with GIMMS, as they detected trends that match expected shifts. In fact, this last series eliminated most of the long term patterns over the continent. For example, in the "Eastern Paraguay" and "Uruguay River margins" focal regions, the extensive changes due to land use and land cover change expansion were detected by PAL and FASIR, but completely ignored by GIMMS. Although the technical explanation of the differences remains unclear and needs further exploration, we found that the evaluation of this type of remote sensing tools should not only be focused at the level of assumptions (i.e. physical or mathematical aspects of image processing), but also at the level of results (i.e. contrasting observed patterns with independent proofs of change). We finally present the online collaborative initiative "Land ecosystem change utility for South America", which facilitates this type of evaluations and helps to identify the most important functional changes of the continent.

Long-term Satellite NDVI Data Sets: Evaluating Their Ability to Detect Ecosystem Functional Changes in South America

PubMed Central

Baldi, Germán; Nosetto, Marcelo D.; Aragón, Roxana; Aversa, Fernando; Paruelo, José M.; Jobbágy, Esteban G.

2008-01-01

In the last decades, South American ecosystems underwent important functional modifications due to climate alterations and direct human intervention on land use and land cover. Among remotely sensed data sets, NOAA-AVHRR “Normalized Difference Vegetation Index” (NDVI) represents one of the most powerful tools to evaluate these changes thanks to their extended temporal coverage. In this paper we explored the possibilities and limitations of three commonly used NOAA-AVHRR NDVI series (PAL, GIMMS and FASIR) to detect ecosystem functional changes in the South American continent. We performed pixel-based linear regressions for four NDVI variables (average annual, maximum annual, minimum annual and intra-annual coefficient of variation) for the 1982-1999 period and (1) analyzed the convergences and divergences of significant multi-annual trends identified across all series, (2) explored the degree of aggregation of the trends using the O-ring statistic, and (3) evaluated observed trends using independent information on ecosystem functional changes in five focal regions. Several differences arose in terms of the patterns of change (the sign, localization and total number of pixels with changes). FASIR presented the highest proportion of changing pixels (32.7%) and GIMMS the lowest (16.2%). PAL and FASIR data sets showed the highest agreement, with a convergence of detected trends on 71.2% of the pixels. Even though positive and negative changes showed substantial spatial aggregation, important differences in the scale of aggregation emerged among the series, with GIMMS showing the smaller scale (≤11 pixels). The independent evaluations suggest higher accuracy in the detection of ecosystem changes among PAL and FASIR series than with GIMMS, as they detected trends that match expected shifts. In fact, this last series eliminated most of the long term patterns over the continent. For example, in the “Eastern Paraguay” and “Uruguay River margins” focal regions, the extensive changes due to land use and land cover change expansion were detected by PAL and FASIR, but completely ignored by GIMMS. Although the technical explanation of the differences remains unclear and needs further exploration, we found that the evaluation of this type of remote sensing tools should not only be focused at the level of assumptions (i.e. physical or mathematical aspects of image processing), but also at the level of results (i.e. contrasting observed patterns with independent proofs of change). We finally present the online collaborative initiative “Land ecosystem change utility for South America”, which facilitates this type of evaluations and helps to identify the most important functional changes of the continent. PMID:27873821

a New Process-Oriented and Spatiotemporal Data Model for GIS Data

NASA Astrophysics Data System (ADS)

Shen, Y.

2018-04-01

With the rapid development of wireless sensor and information technology, there is a trend of transition from "digital monitoring" to "intelligence monitoring" advancing process. The traditional model cannot completely match the dynamic data to accurately describe changes of geographical and environmental changes. In this paper, we try to build a process-oriented and real-time spatiotemporal data model to meet the demands. With various types of monitoring devices, detection methods and the utilization of new technologies, the model can simulate the possible waterlog area in a specific year by analyzing the given data. By testing and modifying the spatiotemporal model, we can come to a rational conclusion that our model can forecast the actual situation in certain extent.

Generalizing on best practices in image processing: a model for promoting research integrity: Commentary on: Avoiding twisted pixels: ethical guidelines for the appropriate use and manipulation of scientific digital images.

PubMed

Benos, Dale J; Vollmer, Sara H

2010-12-01

Modifying images for scientific publication is now quick and easy due to changes in technology. This has created a need for new image processing guidelines and attitudes, such as those offered to the research community by Doug Cromey (Cromey 2010). We suggest that related changes in technology have simplified the task of detecting misconduct for journal editors as well as researchers, and that this simplification has caused a shift in the responsibility for reporting misconduct. We also argue that the concept of best practices in image processing can serve as a general model for education in best practices in research.

Full genome virus detection in fecal samples using sensitive nucleic acid preparation, deep sequencing, and a novel iterative sequence classification algorithm.

PubMed

Cotten, Matthew; Oude Munnink, Bas; Canuti, Marta; Deijs, Martin; Watson, Simon J; Kellam, Paul; van der Hoek, Lia

2014-01-01

We have developed a full genome virus detection process that combines sensitive nucleic acid preparation optimised for virus identification in fecal material with Illumina MiSeq sequencing and a novel post-sequencing virus identification algorithm. Enriched viral nucleic acid was converted to double-stranded DNA and subjected to Illumina MiSeq sequencing. The resulting short reads were processed with a novel iterative Python algorithm SLIM for the identification of sequences with homology to known viruses. De novo assembly was then used to generate full viral genomes. The sensitivity of this process was demonstrated with a set of fecal samples from HIV-1 infected patients. A quantitative assessment of the mammalian, plant, and bacterial virus content of this compartment was generated and the deep sequencing data were sufficient to assembly 12 complete viral genomes from 6 virus families. The method detected high levels of enteropathic viruses that are normally controlled in healthy adults, but may be involved in the pathogenesis of HIV-1 infection and will provide a powerful tool for virus detection and for analyzing changes in the fecal virome associated with HIV-1 progression and pathogenesis.

Full Genome Virus Detection in Fecal Samples Using Sensitive Nucleic Acid Preparation, Deep Sequencing, and a Novel Iterative Sequence Classification Algorithm

PubMed Central

Cotten, Matthew; Oude Munnink, Bas; Canuti, Marta; Deijs, Martin; Watson, Simon J.; Kellam, Paul; van der Hoek, Lia

2014-01-01

We have developed a full genome virus detection process that combines sensitive nucleic acid preparation optimised for virus identification in fecal material with Illumina MiSeq sequencing and a novel post-sequencing virus identification algorithm. Enriched viral nucleic acid was converted to double-stranded DNA and subjected to Illumina MiSeq sequencing. The resulting short reads were processed with a novel iterative Python algorithm SLIM for the identification of sequences with homology to known viruses. De novo assembly was then used to generate full viral genomes. The sensitivity of this process was demonstrated with a set of fecal samples from HIV-1 infected patients. A quantitative assessment of the mammalian, plant, and bacterial virus content of this compartment was generated and the deep sequencing data were sufficient to assembly 12 complete viral genomes from 6 virus families. The method detected high levels of enteropathic viruses that are normally controlled in healthy adults, but may be involved in the pathogenesis of HIV-1 infection and will provide a powerful tool for virus detection and for analyzing changes in the fecal virome associated with HIV-1 progression and pathogenesis. PMID:24695106

Multilayer Markov Random Field models for change detection in optical remote sensing images

NASA Astrophysics Data System (ADS)

Benedek, Csaba; Shadaydeh, Maha; Kato, Zoltan; Szirányi, Tamás; Zerubia, Josiane

2015-09-01

In this paper, we give a comparative study on three Multilayer Markov Random Field (MRF) based solutions proposed for change detection in optical remote sensing images, called Multicue MRF, Conditional Mixed Markov model, and Fusion MRF. Our purposes are twofold. On one hand, we highlight the significance of the focused model family and we set them against various state-of-the-art approaches through a thematic analysis and quantitative tests. We discuss the advantages and drawbacks of class comparison vs. direct approaches, usage of training data, various targeted application fields and different ways of Ground Truth generation, meantime informing the Reader in which roles the Multilayer MRFs can be efficiently applied. On the other hand we also emphasize the differences between the three focused models at various levels, considering the model structures, feature extraction, layer interpretation, change concept definition, parameter tuning and performance. We provide qualitative and quantitative comparison results using principally a publicly available change detection database which contains aerial image pairs and Ground Truth change masks. We conclude that the discussed models are competitive against alternative state-of-the-art solutions, if one uses them as pre-processing filters in multitemporal optical image analysis. In addition, they cover together a large range of applications, considering the different usage options of the three approaches.