Flexibility in Visual Working Memory: Accurate Change Detection in the Face of Irrelevant Variations in Position

PubMed Central

Woodman, Geoffrey F.; Vogel, Edward K.; Luck, Steven J.

2012-01-01

Many recent studies of visual working memory have used change-detection tasks in which subjects view sequential displays and are asked to report whether they are identical or if one object has changed. A key question is whether the memory system used to perform this task is sufficiently flexible to detect changes in object identity independent of spatial transformations, but previous research has yielded contradictory results. To address this issue, the present study compared standard change-detection tasks with tasks in which the objects varied in size or position between successive arrays. Performance was nearly identical across the standard and transformed tasks unless the task implicitly encouraged spatial encoding. These results resolve the discrepancies in prior studies and demonstrate that the visual working memory system can detect changes in object identity across spatial transformations. PMID:22287933

Change detection in satellite images

NASA Astrophysics Data System (ADS)

Thonnessen, U.; Hofele, G.; Middelmann, W.

2005-05-01

Change detection plays an important role in different military areas as strategic reconnaissance, verification of armament and disarmament control and damage assessment. It is the process of identifying differences in the state of an object or phenomenon by observing it at different times. The availability of spaceborne reconnaissance systems with high spatial resolution, multi spectral capabilities, and short revisit times offer new perspectives for change detection. Before performing any kind of change detection it is necessary to separate changes of interest from changes caused by differences in data acquisition parameters. In these cases it is necessary to perform a pre-processing to correct the data or to normalize it. Image registration and, corresponding to this task, the ortho-rectification of the image data is a further prerequisite for change detection. If feasible, a 1-to-1 geometric correspondence should be aspired for. Change detection on an iconic level with a succeeding interpretation of the changes by the observer is often proposed; nevertheless an automatic knowledge-based analysis delivering the interpretation of the changes on a semantic level should be the aim of the future. We present first results of change detection on a structural level concerning urban areas. After pre-processing, the images are segmented in areas of interest and structural analysis is applied to these regions to extract descriptions of urban infrastructure like buildings, roads and tanks of refineries. These descriptions are matched to detect changes and similarities.

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.

The relationship between change detection and recognition of centrally attended objects in motion pictures.

PubMed

Angelone, Bonnie L; Levin, Daniel T; Simons, Daniel J

2003-01-01

Observers typically detect changes to central objects more readily than changes to marginal objects, but they sometimes miss changes to central, attended objects as well. However, even if observers do not report such changes, they may be able to recognize the changed object. In three experiments we explored change detection and recognition memory for several types of changes to central objects in motion pictures. Observers who failed to detect a change still performed at above chance levels on a recognition task in almost all conditions. In addition, observers who detected the change were no more accurate in their recognition than those who did not detect the change. Despite large differences in the detectability of changes across conditions, those observers who missed the change did not vary in their ability to recognize the changing object.

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).

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.

Supporting dynamic change detection: using the right tool for the task.

PubMed

Vallières, Benoît R; Hodgetts, Helen M; Vachon, François; Tremblay, Sébastien

2016-01-01

Detecting task-relevant changes in a visual scene is necessary for successfully monitoring and managing dynamic command and control situations. Change blindness-the failure to notice visual changes-is an important source of human error. Change History EXplicit (CHEX) is a tool developed to aid change detection and maintain situation awareness; and in the current study we test the generality of its ability to facilitate the detection of changes when this subtask is embedded within a broader dynamic decision-making task. A multitasking air-warfare simulation required participants to perform radar-based subtasks, for which change detection was a necessary aspect of the higher-order goal of protecting one's own ship. In this task, however, CHEX rendered the operator even more vulnerable to attentional failures in change detection and increased perceived workload. Such support was only effective when participants performed a change detection task without concurrent subtasks. Results are interpreted in terms of the NSEEV model of attention behavior (Steelman, McCarley, & Wickens, Hum. Factors 53:142-153, 2011; J. Exp. Psychol. Appl. 19:403-419, 2013), and suggest that decision aids for use in multitasking contexts must be designed to fit within the available workload capacity of the user so that they may truly augment cognition.

Accessing long-term memory representations during visual change detection.

PubMed

Beck, Melissa R; van Lamsweerde, Amanda E

2011-04-01

In visual change detection tasks, providing a cue to the change location concurrent with the test image (post-cue) can improve performance, suggesting that, without a cue, not all encoded representations are automatically accessed. Our studies examined the possibility that post-cues can encourage the retrieval of representations stored in long-term memory (LTM). Participants detected changes in images composed of familiar objects. Performance was better when the cue directed attention to the post-change object. Supporting the role of LTM in the cue effect, the effect was similar regardless of whether the cue was presented during the inter-stimulus interval, concurrent with the onset of the test image, or after the onset of the test image. Furthermore, the post-cue effect and LTM performance were similarly influenced by encoding time. These findings demonstrate that monitoring the visual world for changes does not automatically engage LTM retrieval.

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

Detecting correlation changes in multivariate time series: A comparison of four non-parametric change point detection methods.

PubMed

Cabrieto, Jedelyn; Tuerlinckx, Francis; Kuppens, Peter; Grassmann, Mariel; Ceulemans, Eva

2017-06-01

Change point detection in multivariate time series is a complex task since next to the mean, the correlation structure of the monitored variables may also alter when change occurs. DeCon was recently developed to detect such changes in mean and\\or correlation by combining a moving windows approach and robust PCA. However, in the literature, several other methods have been proposed that employ other non-parametric tools: E-divisive, Multirank, and KCP. Since these methods use different statistical approaches, two issues need to be tackled. First, applied researchers may find it hard to appraise the differences between the methods. Second, a direct comparison of the relative performance of all these methods for capturing change points signaling correlation changes is still lacking. Therefore, we present the basic principles behind DeCon, E-divisive, Multirank, and KCP and the corresponding algorithms, to make them more accessible to readers. We further compared their performance through extensive simulations using the settings of Bulteel et al. (Biological Psychology, 98 (1), 29-42, 2014) implying changes in mean and in correlation structure and those of Matteson and James (Journal of the American Statistical Association, 109 (505), 334-345, 2014) implying different numbers of (noise) variables. KCP emerged as the best method in almost all settings. However, in case of more than two noise variables, only DeCon performed adequately in detecting correlation changes.

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

Urban change detection procedures using Landsat digital data

NASA Technical Reports Server (NTRS)

Jensen, J. R.; Toll, D. L.

1982-01-01

Landsat multispectral scanner data was applied to an urban change detection problem in Denver, CO. A dichotomous key yielding ten stages of residential development at the urban fringe was developed. This heuristic model allowed one to identify certain stages of development which are difficult to detect when performing digital change detection using Landsat data. The stages of development were evaluated in terms of their spectral and derived textural characteristics. Landsat band 5 (0.6-0.7 micron) and texture data produced change detection maps which were approximately 81 percent accurate. Results indicated that the stage of development and the spectral/textural features affect the change in the spectral values used for change detection. These preliminary findings will hopefully prove valuable for improved change detection at the urban fringe.

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.

Dissociations of the number and precision of visual short-term memory representations in change detection.

PubMed

Xie, Weizhen; Zhang, Weiwei

2017-11-01

The present study dissociated the number (i.e., quantity) and precision (i.e., quality) of visual short-term memory (STM) representations in change detection using receiver operating characteristic (ROC) and experimental manipulations. Across three experiments, participants performed both recognition and recall tests of visual STM using the change-detection task and the continuous color-wheel recall task, respectively. Experiment 1 demonstrated that the estimates of the number and precision of visual STM representations based on the ROC model of change-detection performance were robustly correlated with the corresponding estimates based on the mixture model of continuous-recall performance. Experiments 2 and 3 showed that the experimental manipulation of mnemonic precision using white-noise masking and the experimental manipulation of the number of encoded STM representations using consolidation masking produced selective effects on the corresponding measures of mnemonic precision and the number of encoded STM representations, respectively, in both change-detection and continuous-recall tasks. Altogether, using the individual-differences (Experiment 1) and experimental dissociation (Experiment 2 and 3) approaches, the present study demonstrated the some-or-none nature of visual STM representations across recall and recognition.

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.

Modeling Patterns of Activities using Activity Curves

PubMed Central

Dawadi, Prafulla N.; Cook, Diane J.; Schmitter-Edgecombe, Maureen

2016-01-01

Pervasive computing offers an unprecedented opportunity to unobtrusively monitor behavior and use the large amount of collected data to perform analysis of activity-based behavioral patterns. In this paper, we introduce the notion of an activity curve, which represents an abstraction of an individual’s normal daily routine based on automatically-recognized activities. We propose methods to detect changes in behavioral routines by comparing activity curves and use these changes to analyze the possibility of changes in cognitive or physical health. We demonstrate our model and evaluate our change detection approach using a longitudinal smart home sensor dataset collected from 18 smart homes with older adult residents. Finally, we demonstrate how big data-based pervasive analytics such as activity curve-based change detection can be used to perform functional health assessment. Our evaluation indicates that correlations do exist between behavior and health changes and that these changes can be automatically detected using smart homes, machine learning, and big data-based pervasive analytics. PMID:27346990

Modeling Patterns of Activities using Activity Curves.

PubMed

Dawadi, Prafulla N; Cook, Diane J; Schmitter-Edgecombe, Maureen

2016-06-01

Pervasive computing offers an unprecedented opportunity to unobtrusively monitor behavior and use the large amount of collected data to perform analysis of activity-based behavioral patterns. In this paper, we introduce the notion of an activity curve , which represents an abstraction of an individual's normal daily routine based on automatically-recognized activities. We propose methods to detect changes in behavioral routines by comparing activity curves and use these changes to analyze the possibility of changes in cognitive or physical health. We demonstrate our model and evaluate our change detection approach using a longitudinal smart home sensor dataset collected from 18 smart homes with older adult residents. Finally, we demonstrate how big data-based pervasive analytics such as activity curve-based change detection can be used to perform functional health assessment. Our evaluation indicates that correlations do exist between behavior and health changes and that these changes can be automatically detected using smart homes, machine learning, and big data-based pervasive analytics.

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.

Limits of Spatial Attention in Three-Dimensional Space and Dual-task Driving Performance

PubMed Central

Andersen, George J.; Ni, Rui; Bian, Zheng; Kang, Julie

2010-01-01

The present study examined the limits of spatial attention while performing two driving relevant tasks that varied in depth. The first task was to maintain a fixed headway distance behind a lead vehicle that varied speed. The second task was to detect a light-change target in an array of lights located above the roadway. In Experiment 1 the light detection task required drivers to encode color and location. The results indicated that reaction time to detect a light-change target increased and accuracy decreased as a function of the horizontal location of the light-change target and as a function of the distance from the driver. In a second experiment the light change task was changed to a singleton search (detect the onset of a yellow light) and the workload of the car following task was systematically varied. The results of Experiment 2 indicated that RT increased as a function of task workload, the 2D position of the light-change target and the distance of the light-change target. A multiple regression analysis indicated that the effect of distance on light detection performance was not due to changes in the projected size of the light target. In Experiment 3 we found that the distance effect in detecting a light change could not be explained by the location of eye fixations. The results demonstrate that when drivers attend to a roadway scene attention is limited in three-dimensional space. These results have important implications for developing tests for assessing crash risk among drivers as well as the design of in vehicle technologies such as head-up displays. PMID:21094336

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.

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

Akcakaya, Murat; Nehorai, Arye; Sen, Satyabrata

Most existing radar algorithms are developed under the assumption that the environment (clutter) is stationary. However, in practice, the characteristics of the clutter can vary enormously depending on the radar-operational scenarios. If unaccounted for, these nonstationary variabilities may drastically hinder the radar performance. Therefore, to overcome such shortcomings, we develop a data-driven method for target detection in nonstationary environments. In this method, the radar dynamically detects changes in the environment and adapts to these changes by learning the new statistical characteristics of the environment and by intelligibly updating its statistical detection algorithm. Specifically, we employ drift detection algorithms to detectmore » changes in the environment; incremental learning, particularly learning under concept drift algorithms, to learn the new statistical characteristics of the environment from the new radar data that become available in batches over a period of time. The newly learned environment characteristics are then integrated in the detection algorithm. Furthermore, we use Monte Carlo simulations to demonstrate that the developed method provides a significant improvement in the detection performance compared with detection techniques that are not aware of the environmental changes.« less

Multi-Temporal Classification and Change Detection Using Uav Images

NASA Astrophysics Data System (ADS)

Makuti, S.; Nex, F.; Yang, M. Y.

2018-05-01

In this paper different methodologies for the classification and change detection of UAV image blocks are explored. UAV is not only the cheapest platform for image acquisition but it is also the easiest platform to operate in repeated data collections over a changing area like a building construction site. Two change detection techniques have been evaluated in this study: the pre-classification and the post-classification algorithms. These methods are based on three main steps: feature extraction, classification and change detection. A set of state of the art features have been used in the tests: colour features (HSV), textural features (GLCM) and 3D geometric features. For classification purposes Conditional Random Field (CRF) has been used: the unary potential was determined using the Random Forest algorithm while the pairwise potential was defined by the fully connected CRF. In the performed tests, different feature configurations and settings have been considered to assess the performance of these methods in such challenging task. Experimental results showed that the post-classification approach outperforms the pre-classification change detection method. This was analysed using the overall accuracy, where by post classification have an accuracy of up to 62.6 % and the pre classification change detection have an accuracy of 46.5 %. These results represent a first useful indication for future works and developments.

Encapsulated Solid-Liquid Phase Change Nanoparticles as Thermal Barcodes for Highly Sensitive Detections of Multiple Lung Cancer Biomarkers

DTIC Science & Technology

2012-10-01

5e. TASK NUMBER LC90061 5f. WORK UNIT NUMBER 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) 8. PERFORMING ORGANIZATION REPORT...transduction mechanism based on solid- liquid phase change nanoparticles works for the detection of multiple proteins. A series of metal and alloy...early stage. With the support from DOD-LCRP, we have proved the new signal transduction mechanism based on solid-liquid phase change nanoparticles works

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.

A novel data-driven learning method for radar target detection in nonstationary environments

DOE PAGES

Akcakaya, Murat; Nehorai, Arye; Sen, Satyabrata

2016-04-12

Most existing radar algorithms are developed under the assumption that the environment (clutter) is stationary. However, in practice, the characteristics of the clutter can vary enormously depending on the radar-operational scenarios. If unaccounted for, these nonstationary variabilities may drastically hinder the radar performance. Therefore, to overcome such shortcomings, we develop a data-driven method for target detection in nonstationary environments. In this method, the radar dynamically detects changes in the environment and adapts to these changes by learning the new statistical characteristics of the environment and by intelligibly updating its statistical detection algorithm. Specifically, we employ drift detection algorithms to detectmore » changes in the environment; incremental learning, particularly learning under concept drift algorithms, to learn the new statistical characteristics of the environment from the new radar data that become available in batches over a period of time. The newly learned environment characteristics are then integrated in the detection algorithm. Furthermore, we use Monte Carlo simulations to demonstrate that the developed method provides a significant improvement in the detection performance compared with detection techniques that are not aware of the environmental changes.« less

On the pilot's behavior of detecting a system parameter change

NASA Technical Reports Server (NTRS)

Morizumi, N.; Kimura, H.

1986-01-01

The reaction of a human pilot, engaged in compensatory control, to a sudden change in the controlled element's characteristics is described. Taking the case where the change manifests itself as a variance change of the monitored signal, it is shown that the detection time, defined to be the time elapsed until the pilot detects the change, is related to the monitored signal and its derivative. Then, the detection behavior is modeled by an optimal controller, an optimal estimator, and a variance-ratio test mechanism that is performed for the monitored signal and its derivative. Results of a digital simulation show that the pilot's detection behavior can be well represented by the model proposed here.

Orienting Attention in Visual Working Memory Reduces Interference from Memory Probes

ERIC Educational Resources Information Center

Makovski, Tal; Sussman, Rachel; Jiang, Yuhong V.

2008-01-01

Given a changing visual environment, and the limited capacity of visual working memory (VWM), the contents of VWM must be in constant flux. Using a change detection task, the authors show that VWM is subject to obligatory updating in the face of new information. Change detection performance is enhanced when the item that may change is…

A Decline in Response Variability Improves Neural Signal Detection during Auditory Task Performance.

PubMed

von Trapp, Gardiner; Buran, Bradley N; Sen, Kamal; Semple, Malcolm N; Sanes, Dan H

2016-10-26

The detection of a sensory stimulus arises from a significant change in neural activity, but a sensory neuron's response is rarely identical to successive presentations of the same stimulus. Large trial-to-trial variability would limit the central nervous system's ability to reliably detect a stimulus, presumably affecting perceptual performance. However, if response variability were to decrease while firing rate remained constant, then neural sensitivity could improve. Here, we asked whether engagement in an auditory detection task can modulate response variability, thereby increasing neural sensitivity. We recorded telemetrically from the core auditory cortex of gerbils, both while they engaged in an amplitude-modulation detection task and while they sat quietly listening to the identical stimuli. Using a signal detection theory framework, we found that neural sensitivity was improved during task performance, and this improvement was closely associated with a decrease in response variability. Moreover, units with the greatest change in response variability had absolute neural thresholds most closely aligned with simultaneously measured perceptual thresholds. Our findings suggest that the limitations imposed by response variability diminish during task performance, thereby improving the sensitivity of neural encoding and potentially leading to better perceptual sensitivity. The detection of a sensory stimulus arises from a significant change in neural activity. However, trial-to-trial variability of the neural response may limit perceptual performance. If the neural response to a stimulus is quite variable, then the response on a given trial could be confused with the pattern of neural activity generated when the stimulus is absent. Therefore, a neural mechanism that served to reduce response variability would allow for better stimulus detection. By recording from the cortex of freely moving animals engaged in an auditory detection task, we found that variability of the neural response becomes smaller during task performance, thereby improving neural detection thresholds. Copyright © 2016 the authors 0270-6474/16/3611097-10$15.00/0.

A Decline in Response Variability Improves Neural Signal Detection during Auditory Task Performance

PubMed Central

Buran, Bradley N.; Sen, Kamal; Semple, Malcolm N.; Sanes, Dan H.

2016-01-01

The detection of a sensory stimulus arises from a significant change in neural activity, but a sensory neuron's response is rarely identical to successive presentations of the same stimulus. Large trial-to-trial variability would limit the central nervous system's ability to reliably detect a stimulus, presumably affecting perceptual performance. However, if response variability were to decrease while firing rate remained constant, then neural sensitivity could improve. Here, we asked whether engagement in an auditory detection task can modulate response variability, thereby increasing neural sensitivity. We recorded telemetrically from the core auditory cortex of gerbils, both while they engaged in an amplitude-modulation detection task and while they sat quietly listening to the identical stimuli. Using a signal detection theory framework, we found that neural sensitivity was improved during task performance, and this improvement was closely associated with a decrease in response variability. Moreover, units with the greatest change in response variability had absolute neural thresholds most closely aligned with simultaneously measured perceptual thresholds. Our findings suggest that the limitations imposed by response variability diminish during task performance, thereby improving the sensitivity of neural encoding and potentially leading to better perceptual sensitivity. SIGNIFICANCE STATEMENT The detection of a sensory stimulus arises from a significant change in neural activity. However, trial-to-trial variability of the neural response may limit perceptual performance. If the neural response to a stimulus is quite variable, then the response on a given trial could be confused with the pattern of neural activity generated when the stimulus is absent. Therefore, a neural mechanism that served to reduce response variability would allow for better stimulus detection. By recording from the cortex of freely moving animals engaged in an auditory detection task, we found that variability of the neural response becomes smaller during task performance, thereby improving neural detection thresholds. PMID:27798189

Energy Change Detection to Assist in Tactical Intelligence Production

DTIC Science & Technology

2009-06-01

COVERED Master’s Thesis 4. TITLE AND SUBTITLE Energy Change Detection to Assist in Tactical Intelligence Production 6. AUTHOR( S ) Derek Anthony Filipe...5. FUNDING NUMBERS 7. PERFORMING ORGANIZATION NAME( S ) AND ADDRESS(ES) Naval Postgraduate School Monterey, CA 93943-5000 8. PERFORMING...ORGANIZATION REPORT NUMBER 9. SPONSORING /MONITORING AGENCY NAME( S ) AND ADDRESS(ES) N/A 10. SPONSORING/MONITORING AGENCY REPORT NUMBER 11

Change Detection Analysis of Water Pollution in Coimbatore Region using Different Color Models

NASA Astrophysics Data System (ADS)

Jiji, G. Wiselin; Devi, R. Naveena

2017-12-01

The data acquired through remote sensing satellites furnish facts about the land and water at varying resolutions and has been widely used for several change detection studies. Apart from the existence of many change detection methodologies and techniques, emergence of new ones continues to subsist. Existing change detection techniques exploit images that are either in gray scale or RGB color model. In this paper we introduced color models for performing change detection for water pollution. Here the polluted lakes are classified and post-classification change detection techniques are applied to RGB images and results obtained are analysed for changes to exist or not. Furthermore RGB images obtained after classification when converted to any of the two color models YCbCr and YIQ is found to produce the same results as that of the RGB model images. Thus it can be concluded that other color models like YCbCr, YIQ can be used as substitution to RGB color model for analysing change detection with regard to water pollution.

Detecting gradual visual changes in colour and brightness agnosia: a double dissociation.

PubMed

Nijboer, Tanja C W; te Pas, Susan F; van der Smagt, Maarten J

2011-03-09

Two patients, one with colour agnosia and one with brightness agnosia, performed a task that required the detection of gradual temporal changes in colour and brightness. The results for these patients, who showed anaverage or an above-average performance on several tasks designed to test low-level colour and luminance (contrast) perception in the spatial domain, yielded a double dissociation; the brightness agnosic patient was within the normal range for the coloured stimuli, but much slower to detect brightness differences, whereas the colour agnosic patient was within the normal range for the achromatic stimuli, but much slower for the coloured stimuli. These results suggest that a modality-specific impairment in the detection of gradual temporal changes might be related to, if not underlie, the phenomenon of visual agnosia.

Expanding Cancer Detection Using Molecular Imprinting for a Novel Point-of-Care Diagnostic Device

NASA Astrophysics Data System (ADS)

Yu, Yingjie; Rafailovich, Miriam; Wang, Yantian; Ranjbaran, Alina; Wang, Tom; Nam, David

2012-02-01

We propose the use of a potentiometric biosensor that incorporates the efficient and specific molecular imprinting (MI) method with a self-assembled monolayer (SAM). We first tested the biosensor using carcinoembryonic antigen, CEA, a biomarker associated with pancreatic cancer. No change in detection efficiency was observed when detection was performed in the presence of 100% serum albumin, indicating that the sensor is able to discriminate for the template analyte even in concentrated solution of similar substances. Computer simulations of the protein structure were performed in order to estimate the changes in morphology and determine the sensitivity of the biosensor to conformational changes in the proteins. We found that even small changes in PH can generate rotation of the surface functional groups, without significant change in the morphology. Yet, the results show that only when the detection and imprinting conditions are similar, robust signals occurs. Hence we concluded that both morphology and surface chemistry play a role in the recognition.

Distinct frontal and amygdala correlates of change detection for facial identity and expression

PubMed Central

Achaibou, Amal; Loth, Eva

2016-01-01

Recruitment of ‘top-down’ frontal attentional mechanisms is held to support detection of changes in task-relevant stimuli. Fluctuations in intrinsic frontal activity have been shown to impact task performance more generally. Meanwhile, the amygdala has been implicated in ‘bottom-up’ attentional capture by threat. Here, 22 adult human participants took part in a functional magnetic resonance change detection study aimed at investigating the correlates of successful (vs failed) detection of changes in facial identity vs expression. For identity changes, we expected prefrontal recruitment to differentiate ‘hit’ from ‘miss’ trials, in line with previous reports. Meanwhile, we postulated that a different mechanism would support detection of emotionally salient changes. Specifically, elevated amygdala activation was predicted to be associated with successful detection of threat-related changes in expression, over-riding the influence of fluctuations in top-down attention. Our findings revealed that fusiform activity tracked change detection across conditions. Ventrolateral prefrontal cortical activity was uniquely linked to detection of changes in identity not expression, and amygdala activity to detection of changes from neutral to fearful expressions. These results are consistent with distinct mechanisms supporting detection of changes in face identity vs expression, the former potentially reflecting top-down attention, the latter bottom-up attentional capture by stimulus emotional salience. PMID:26245835

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

Experimental and environmental factors affect spurious detection of ecological thresholds

USGS Publications Warehouse

Daily, Jonathan P.; Hitt, Nathaniel P.; Smith, David; Snyder, Craig D.

2012-01-01

Threshold detection methods are increasingly popular for assessing nonlinear responses to environmental change, but their statistical performance remains poorly understood. We simulated linear change in stream benthic macroinvertebrate communities and evaluated the performance of commonly used threshold detection methods based on model fitting (piecewise quantile regression [PQR]), data partitioning (nonparametric change point analysis [NCPA]), and a hybrid approach (significant zero crossings [SiZer]). We demonstrated that false detection of ecological thresholds (type I errors) and inferences on threshold locations are influenced by sample size, rate of linear change, and frequency of observations across the environmental gradient (i.e., sample-environment distribution, SED). However, the relative importance of these factors varied among statistical methods and between inference types. False detection rates were influenced primarily by user-selected parameters for PQR (τ) and SiZer (bandwidth) and secondarily by sample size (for PQR) and SED (for SiZer). In contrast, the location of reported thresholds was influenced primarily by SED. Bootstrapped confidence intervals for NCPA threshold locations revealed strong correspondence to SED. We conclude that the choice of statistical methods for threshold detection should be matched to experimental and environmental constraints to minimize false detection rates and avoid spurious inferences regarding threshold location.

Iconic memory requires attention

PubMed Central

Persuh, Marjan; Genzer, Boris; Melara, Robert D.

2012-01-01

Two experiments investigated whether attention plays a role in iconic memory, employing either a change detection paradigm (Experiment 1) or a partial-report paradigm (Experiment 2). In each experiment, attention was taxed during initial display presentation, focusing the manipulation on consolidation of information into iconic memory, prior to transfer into working memory. Observers were able to maintain high levels of performance (accuracy of change detection or categorization) even when concurrently performing an easy visual search task (low load). However, when the concurrent search was made difficult (high load), observers' performance dropped to almost chance levels, while search accuracy held at single-task levels. The effects of attentional load remained the same across paradigms. The results suggest that, without attention, participants consolidate in iconic memory only gross representations of the visual scene, information too impoverished for successful detection of perceptual change or categorization of features. PMID:22586389

Iconic memory requires attention.

PubMed

Persuh, Marjan; Genzer, Boris; Melara, Robert D

2012-01-01

Two experiments investigated whether attention plays a role in iconic memory, employing either a change detection paradigm (Experiment 1) or a partial-report paradigm (Experiment 2). In each experiment, attention was taxed during initial display presentation, focusing the manipulation on consolidation of information into iconic memory, prior to transfer into working memory. Observers were able to maintain high levels of performance (accuracy of change detection or categorization) even when concurrently performing an easy visual search task (low load). However, when the concurrent search was made difficult (high load), observers' performance dropped to almost chance levels, while search accuracy held at single-task levels. The effects of attentional load remained the same across paradigms. The results suggest that, without attention, participants consolidate in iconic memory only gross representations of the visual scene, information too impoverished for successful detection of perceptual change or categorization of features.

Applications of Graph-Theoretic Tests to Online Change Detection

DTIC Science & Technology

2014-05-09

NUMBER 5f. WORK UNIT NUMBER 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) AND ADDRESS(ES) 8. PERFORMING ORGANIZATION REPORT ...assessment, crime investigation, and environmental field analysis. Our work offers a new tool for change detection that can be employed in real- time in very...this paper such MSTs and bipartite matchings. Ruth (2009) reports run times for MNBM ensembles created using Derigs’ (1998) algorithm on the order of

Guidance of Attention to Objects and Locations by Long-Term Memory of Natural Scenes

ERIC Educational Resources Information Center

Becker, Mark W.; Rasmussen, Ian P.

2008-01-01

Four flicker change-detection experiments demonstrate that scene-specific long-term memory guides attention to both behaviorally relevant locations and objects within a familiar scene. Participants performed an initial block of change-detection trials, detecting the addition of an object to a natural scene. After a 30-min delay, participants…

Implicit Change Identification: A Replication of Fernandez-Duque and Thornton (2003)

ERIC Educational Resources Information Center

Laloyaux, Cedric; Destrebecqz, Arnaud; Cleeremans, Axel

2006-01-01

Using a simple change detection task involving vertical and horizontal stimuli, I. M. Thornton and D. Fernandez-Duque (2000) showed that the implicit detection of a change in the orientation of an item influences performance in a subsequent orientation judgment task. However, S. R. Mitroff, D. J. Simons, and S. L. Franconeri (2002) were not able…

Evaluating the performance of the quick CSF method in detecting contrast sensitivity function changes

PubMed Central

Hou, Fang; Lesmes, Luis Andres; Kim, Woojae; Gu, Hairong; Pitt, Mark A.; Myung, Jay I.; Lu, Zhong-Lin

2016-01-01

The contrast sensitivity function (CSF) has shown promise as a functional vision endpoint for monitoring the changes in functional vision that accompany eye disease or its treatment. However, detecting CSF changes with precision and efficiency at both the individual and group levels is very challenging. By exploiting the Bayesian foundation of the quick CSF method (Lesmes, Lu, Baek, & Albright, 2010), we developed and evaluated metrics for detecting CSF changes at both the individual and group levels. A 10-letter identification task was used to assess the systematic changes in the CSF measured in three luminance conditions in 112 naïve normal observers. The data from the large sample allowed us to estimate the test–retest reliability of the quick CSF procedure and evaluate its performance in detecting CSF changes at both the individual and group levels. The test–retest reliability reached 0.974 with 50 trials. In 50 trials, the quick CSF method can detect a medium 0.30 log unit area under log CSF change with 94.0% accuracy at the individual observer level. At the group level, a power analysis based on the empirical distribution of CSF changes from the large sample showed that a very small area under log CSF change (0.025 log unit) could be detected by the quick CSF method with 112 observers and 50 trials. These results make it plausible to apply the method to monitor the progression of visual diseases or treatment effects on individual patients and greatly reduce the time, sample size, and costs in clinical trials at the group level. PMID:27120074

Change detection and classification in brain MR images using change vector analysis.

PubMed

Simões, Rita; Slump, Cornelis

2011-01-01

The automatic detection of longitudinal changes in brain images is valuable in the assessment of disease evolution and treatment efficacy. Most existing change detection methods that are currently used in clinical research to monitor patients suffering from neurodegenerative diseases--such as Alzheimer's--focus on large-scale brain deformations. However, such patients often have other brain impairments, such as infarcts, white matter lesions and hemorrhages, which are typically overlooked by the deformation-based methods. Other unsupervised change detection algorithms have been proposed to detect tissue intensity changes. The outcome of these methods is typically a binary change map, which identifies changed brain regions. However, understanding what types of changes these regions underwent is likely to provide equally important information about lesion evolution. In this paper, we present an unsupervised 3D change detection method based on Change Vector Analysis. We compute and automatically threshold the Generalized Likelihood Ratio map to obtain a binary change map. Subsequently, we perform histogram-based clustering to classify the change vectors. We obtain a Kappa Index of 0.82 using various types of simulated lesions. The classification error is 2%. Finally, we are able to detect and discriminate both small changes and ventricle expansions in datasets from Mild Cognitive Impairment patients.

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

Algorithms and data structures for automated change detection and classification of sidescan sonar imagery

NASA Astrophysics Data System (ADS)

Gendron, Marlin Lee

During Mine Warfare (MIW) operations, MIW analysts perform change detection by visually comparing historical sidescan sonar imagery (SSI) collected by a sidescan sonar with recently collected SSI in an attempt to identify objects (which might be explosive mines) placed at sea since the last time the area was surveyed. This dissertation presents a data structure and three algorithms, developed by the author, that are part of an automated change detection and classification (ACDC) system. MIW analysts at the Naval Oceanographic Office, to reduce the amount of time to perform change detection, are currently using ACDC. The dissertation introductory chapter gives background information on change detection, ACDC, and describes how SSI is produced from raw sonar data. Chapter 2 presents the author's Geospatial Bitmap (GB) data structure, which is capable of storing information geographically and is utilized by the three algorithms. This chapter shows that a GB data structure used in a polygon-smoothing algorithm ran between 1.3--48.4x faster than a sparse matrix data structure. Chapter 3 describes the GB clustering algorithm, which is the author's repeatable, order-independent method for clustering. Results from tests performed in this chapter show that the time to cluster a set of points is not affected by the distribution or the order of the points. In Chapter 4, the author presents his real-time computer-aided detection (CAD) algorithm that automatically detects mine-like objects on the seafloor in SSI. The author ran his GB-based CAD algorithm on real SSI data, and results of these tests indicate that his real-time CAD algorithm performs comparably to or better than other non-real-time CAD algorithms. The author presents his computer-aided search (CAS) algorithm in Chapter 5. CAS helps MIW analysts locate mine-like features that are geospatially close to previously detected features. A comparison between the CAS and a great circle distance algorithm shows that the CAS performs geospatial searching 1.75x faster on large data sets. Finally, the concluding chapter of this dissertation gives important details on how the completed ACDC system will function, and discusses the author's future research to develop additional algorithms and data structures for ACDC.

Unobtrusive monitoring of computer interactions to detect cognitive status in elders.

PubMed

Jimison, Holly; Pavel, Misha; McKanna, James; Pavel, Jesse

2004-09-01

The U.S. has experienced a rapid growth in the use of computers by elders. E-mail, Web browsing, and computer games are among the most common routine activities for this group of users. In this paper, we describe techniques for unobtrusively monitoring naturally occurring computer interactions to detect sustained changes in cognitive performance. Researchers have demonstrated the importance of the early detection of cognitive decline. Users over the age of 75 are at risk for medically related cognitive problems and confusion, and early detection allows for more effective clinical intervention. In this paper, we present algorithms for inferring a user's cognitive performance using monitoring data from computer games and psychomotor measurements associated with keyboard entry and mouse movement. The inferences are then used to classify significant performance changes, and additionally, to adapt computer interfaces with tailored hints and assistance when needed. These methods were tested in a group of elders in a residential facility.

Acoustic change detection algorithm using an FM radio

NASA Astrophysics Data System (ADS)

Goldman, Geoffrey H.; Wolfe, Owen

2012-06-01

The U.S. Army is interested in developing low-cost, low-power, non-line-of-sight sensors for monitoring human activity. One modality that is often overlooked is active acoustics using sources of opportunity such as speech or music. Active acoustics can be used to detect human activity by generating acoustic images of an area at different times, then testing for changes among the imagery. A change detection algorithm was developed to detect physical changes in a building, such as a door changing positions or a large box being moved using acoustics sources of opportunity. The algorithm is based on cross correlating the acoustic signal measured from two microphones. The performance of the algorithm was shown using data generated with a hand-held FM radio as a sound source and two microphones. The algorithm could detect a door being opened in a hallway.

Anomalies in the detection of change: When changes in sample size are mistaken for changes in proportions.

PubMed

Fiedler, Klaus; Kareev, Yaakov; Avrahami, Judith; Beier, Susanne; Kutzner, Florian; Hütter, Mandy

2016-01-01

Detecting changes, in performance, sales, markets, risks, social relations, or public opinions, constitutes an important adaptive function. In a sequential paradigm devised to investigate detection of change, every trial provides a sample of binary outcomes (e.g., correct vs. incorrect student responses). Participants have to decide whether the proportion of a focal feature (e.g., correct responses) in the population from which the sample is drawn has decreased, remained constant, or increased. Strong and persistent anomalies in change detection arise when changes in proportional quantities vary orthogonally to changes in absolute sample size. Proportional increases are readily detected and nonchanges are erroneously perceived as increases when absolute sample size increases. Conversely, decreasing sample size facilitates the correct detection of proportional decreases and the erroneous perception of nonchanges as decreases. These anomalies are however confined to experienced samples of elementary raw events from which proportions have to be inferred inductively. They disappear when sample proportions are described as percentages in a normalized probability format. To explain these challenging findings, it is essential to understand the inductive-learning constraints imposed on decisions from experience.

Robust Detection of Examinees with Aberrant Answer Changes

ERIC Educational Resources Information Center

Belov, Dmitry I.

2015-01-01

The statistical analysis of answer changes (ACs) has uncovered multiple testing irregularities on large-scale assessments and is now routinely performed at testing organizations. However, AC data has an uncertainty caused by technological or human factors. Therefore, existing statistics (e.g., number of wrong-to-right ACs) used to detect examinees…

Change Detection Algorithms for Surveillance in Visual IoT: A Comparative Study

NASA Astrophysics Data System (ADS)

Akram, Beenish Ayesha; Zafar, Amna; Akbar, Ali Hammad; Wajid, Bilal; Chaudhry, Shafique Ahmad

2018-01-01

The VIoT (Visual Internet of Things) connects virtual information world with real world objects using sensors and pervasive computing. For video surveillance in VIoT, ChD (Change Detection) is a critical component. ChD algorithms identify regions of change in multiple images of the same scene recorded at different time intervals for video surveillance. This paper presents performance comparison of histogram thresholding and classification ChD algorithms using quantitative measures for video surveillance in VIoT based on salient features of datasets. The thresholding algorithms Otsu, Kapur, Rosin and classification methods k-means, EM (Expectation Maximization) were simulated in MATLAB using diverse datasets. For performance evaluation, the quantitative measures used include OSR (Overall Success Rate), YC (Yule's Coefficient) and JC (Jaccard's Coefficient), execution time and memory consumption. Experimental results showed that Kapur's algorithm performed better for both indoor and outdoor environments with illumination changes, shadowing and medium to fast moving objects. However, it reflected degraded performance for small object size with minor changes. Otsu algorithm showed better results for indoor environments with slow to medium changes and nomadic object mobility. k-means showed good results in indoor environment with small object size producing slow change, no shadowing and scarce illumination changes.

The relationship between stereoacuity and stereomotion thresholds.

PubMed

Cumming, B G

1995-01-01

There are in principle at least two binocular sources of information that could be used to determine the motion of an object towards or away from an observer; such motion produces changes in binocular disparities over time and also generates different image velocities in the two eyes. It has been argued in the past that stereomotion is detected by a mechanism that is independent of that which detects static disparities. More recently this conclusion has been questioned. If stereomotion detection in fact depends upon detecting disparities, there should be a clear correlation between static stereo-detection thresholds and stereomotion thresholds. If the systems are separate, there need be no such correlation. Four types of threshold measurement were performed by means of random-dot stereograms: (1) static stereo detection/discrimination; (2) stereomotion detection in random-dot stereograms (temporally uncorrelated); (3) stereomotion detection in temporally correlated random-dot stereograms; and (4) binocular detection of frontoparallel motion. Three normal subjects and five subjects with unusually high stereoacuities were studied. In addition, two manipulations were performed that altered stereomotion thresholds: changes in mean disparity, and image defocus produced by positive spectacle lenses. Across subjects and conditions, stereomotion thresholds were well correlated with stereo-discrimination thresholds. Stereomotion was poorly correlated with binocular frontoparallel-motion thresholds. These results suggest that stereomotion is detected by means of registering changes in the output of the same disparity detectors that are used to detect static disparities.

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.

Detecting Stress Patterns Is Related to Children's Performance on Reading Tasks

ERIC Educational Resources Information Center

Gutierrez-Palma, Nicolas; Raya-Garcia, Manuel; Palma-Reyes, Alfonso

2009-01-01

This paper investigates the relationship between the ability to detect changes in prosody and reading performance in Spanish. Participants were children aged 6-8 years who completed tasks involving reading words, reading pseudowords, stressing pseudowords, and reproducing pseudoword stress patterns. Results showed that the capacity to reproduce…

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.

Techniques for automatic large scale change analysis of temporal multispectral imagery

NASA Astrophysics Data System (ADS)

Mercovich, Ryan A.

Change detection in remotely sensed imagery is a multi-faceted problem with a wide variety of desired solutions. Automatic change detection and analysis to assist in the coverage of large areas at high resolution is a popular area of research in the remote sensing community. Beyond basic change detection, the analysis of change is essential to provide results that positively impact an image analyst's job when examining potentially changed areas. Present change detection algorithms are geared toward low resolution imagery, and require analyst input to provide anything more than a simple pixel level map of the magnitude of change that has occurred. One major problem with this approach is that change occurs in such large volume at small spatial scales that a simple change map is no longer useful. This research strives to create an algorithm based on a set of metrics that performs a large area search for change in high resolution multispectral image sequences and utilizes a variety of methods to identify different types of change. Rather than simply mapping the magnitude of any change in the scene, the goal of this research is to create a useful display of the different types of change in the image. The techniques presented in this dissertation are used to interpret large area images and provide useful information to an analyst about small regions that have undergone specific types of change while retaining image context to make further manual interpretation easier. This analyst cueing to reduce information overload in a large area search environment will have an impact in the areas of disaster recovery, search and rescue situations, and land use surveys among others. By utilizing a feature based approach founded on applying existing statistical methods and new and existing topological methods to high resolution temporal multispectral imagery, a novel change detection methodology is produced that can automatically provide useful information about the change occurring in large area and high resolution image sequences. The change detection and analysis algorithm developed could be adapted to many potential image change scenarios to perform automatic large scale analysis of change.

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.

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

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.

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…

Action change detection in video using a bilateral spatial-temporal constraint

NASA Astrophysics Data System (ADS)

Tian, Jing; Chen, Li

2016-08-01

Action change detection in video aims to detect action discontinuity in video. The silhouettes-based features are desirable for action change detection. This paper studies the problem of silhouette-quality assessment. For that, a non-reference approach without the need for ground truth is proposed in this paper to evaluate the quality of silhouettes, by exploiting both the boundary contrast of the silhouettes in the spatial domain and the consistency of the silhouettes in the temporal domain. This is in contrast to that either only spatial information or only temporal information of silhouettes is exploited in conventional approaches. Experiments are conducted using artificially generated degraded silhouettes to show that the proposed approach outperforms conventional approaches to achieve more accurate quality assessment. Furthermore, experiments are performed to show that the proposed approach is able to improve the accuracy performance of conventional action change approaches in two human action video data-sets. The average runtime of the proposed approach for Weizmann action video data-set is 0.08 second for one frame using Matlab programming language. It is computationally efficient and potential to real-time implementations.

Detection of retinal changes from illumination normalized fundus images using convolutional neural networks

NASA Astrophysics Data System (ADS)

Adal, Kedir M.; van Etten, Peter G.; Martinez, Jose P.; Rouwen, Kenneth; Vermeer, Koenraad A.; van Vliet, Lucas J.

2017-03-01

Automated detection and quantification of spatio-temporal retinal changes is an important step to objectively assess disease progression and treatment effects for dynamic retinal diseases such as diabetic retinopathy (DR). However, detecting retinal changes caused by early DR lesions such as microaneurysms and dot hemorrhages from longitudinal pairs of fundus images is challenging due to intra and inter-image illumination variation between fundus images. This paper explores a method for automated detection of retinal changes from illumination normalized fundus images using a deep convolutional neural network (CNN), and compares its performance with two other CNNs trained separately on color and green channel fundus images. Illumination variation was addressed by correcting for the variability in the luminosity and contrast estimated from a large scale retinal regions. The CNN models were trained and evaluated on image patches extracted from a registered fundus image set collected from 51 diabetic eyes that were screened at two different time-points. The results show that using normalized images yield better performance than color and green channel images, suggesting that illumination normalization greatly facilitates CNNs to quickly and correctly learn distinctive local image features of DR related retinal changes.

Detecting target changes in multiple object tracking with peripheral vision: More pronounced eccentricity effects for changes in form than in motion.

PubMed

Vater, Christian; Kredel, Ralf; Hossner, Ernst-Joachim

2017-05-01

In the current study, dual-task performance is examined with multiple-object tracking as a primary task and target-change detection as a secondary task. The to-be-detected target changes in conditions of either change type (form vs. motion; Experiment 1) or change salience (stop vs. slowdown; Experiment 2), with changes occurring at either near (5°-10°) or far (15°-20°) eccentricities (Experiments 1 and 2). The aim of the study was to test whether changes can be detected solely with peripheral vision. By controlling for saccades and computing gaze distances, we could show that participants used peripheral vision to monitor the targets and, additionally, to perceive changes at both near and far eccentricities. Noticeably, gaze behavior was not affected by the actual target change. Detection rates as well as response times generally varied as a function of change condition and eccentricity, with faster detections for motion changes and near changes. However, in contrast to the effects found for motion changes, sharp declines in detection rates and increased response times were observed for form changes as a function of the eccentricities. This result can be ascribed to properties of the visual system, namely to the limited spatial acuity in the periphery and the comparably receptive motion sensitivity of peripheral vision. These findings show that peripheral vision is functional for simultaneous target monitoring and target-change detection as saccadic information suppression can be avoided and covert attention can be optimally distributed to all targets. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

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.

Priming effects under correct change detection and change blindness.

PubMed

Caudek, Corrado; Domini, Fulvio

2013-03-01

In three experiments, we investigated the priming effects induced by an image change on a successive animate/inanimate decision task. We studied both perceptual (Experiments 1 and 2) and conceptual (Experiment 3) priming effects, under correct change detection and change blindness (CB). Under correct change detection, we found larger positive priming effects on congruent trials for probes representing animate entities than for probes representing artifactual objects. Under CB, we found performance impairment relative to a "no-change" baseline condition. This inhibition effect induced by CB was modulated by the semantic congruency between the changed item and the probe in the case of probe images, but not for probe words. We discuss our results in the context of the literature on the negative priming effect. Copyright © 2012 Elsevier Inc. All rights reserved.

Hyperspectral data collection for the assessment of target detection algorithms: the Viareggio 2013 trial

NASA Astrophysics Data System (ADS)

Rossi, Alessandro; Acito, Nicola; Diani, Marco; Corsini, Giovanni; De Ceglie, Sergio Ugo; Riccobono, Aldo; Chiarantini, Leandro

2014-10-01

Airborne hyperspectral imagery is valuable for military and civilian applications, such as target identification, detection of anomalies and changes within multiple acquisitions. In target detection (TD) applications, the performance assessment of different algorithms is an important and critical issue. In this context, the small number of public available hyperspectral data motivated us to perform an extensive measurement campaign including various operating scenarios. The campaign was organized by CISAM in cooperation with University of Pisa, Selex ES and CSSN-ITE, and it was conducted in Viareggio, Italy in May, 2013. The Selex ES airborne hyperspectral sensor SIM.GA was mounted on board of an airplane to collect images over different sites in the morning and afternoon of two subsequent days. This paper describes the hyperspectral data collection of the trial. Four different sites were set up, representing a complex urban scenario, two parking lots and a rural area. Targets with dimensions comparable to the sensor ground resolution were deployed in the sites to reproduce different operating situations. An extensive ground truth documentation completes the data collection. Experiments to test anomalous change detection techniques were set up changing the position of the deployed targets. Search and rescue scenarios were simulated to evaluate the performance of anomaly detection algorithms. Moreover, the reflectance signatures of the targets were measured on the ground to perform spectral matching in varying atmospheric and illumination conditions. The paper presents some preliminary results that show the effectiveness of hyperspectral data exploitation for the object detection tasks of interest in this work.

Thorough statistical comparison of machine learning regression models and their ensembles for sub-pixel imperviousness and imperviousness change mapping

NASA Astrophysics Data System (ADS)

Drzewiecki, Wojciech

2017-12-01

We evaluated the performance of nine machine learning regression algorithms and their ensembles for sub-pixel estimation of impervious areas coverages from Landsat imagery. The accuracy of imperviousness mapping in individual time points was assessed based on RMSE, MAE and R2. These measures were also used for the assessment of imperviousness change intensity estimations. The applicability for detection of relevant changes in impervious areas coverages at sub-pixel level was evaluated using overall accuracy, F-measure and ROC Area Under Curve. The results proved that Cubist algorithm may be advised for Landsat-based mapping of imperviousness for single dates. Stochastic gradient boosting of regression trees (GBM) may be also considered for this purpose. However, Random Forest algorithm is endorsed for both imperviousness change detection and mapping of its intensity. In all applications the heterogeneous model ensembles performed at least as well as the best individual models or better. They may be recommended for improving the quality of sub-pixel imperviousness and imperviousness change mapping. The study revealed also limitations of the investigated methodology for detection of subtle changes of imperviousness inside the pixel. None of the tested approaches was able to reliably classify changed and non-changed pixels if the relevant change threshold was set as one or three percent. Also for fi ve percent change threshold most of algorithms did not ensure that the accuracy of change map is higher than the accuracy of random classifi er. For the threshold of relevant change set as ten percent all approaches performed satisfactory.

Apparatus for responding to an anomalous change in downhole pressure

DOEpatents

Hall, David R.; Fox, Joe; Wilde, Tyson; Barlow, Jonathan S.

2010-04-13

A method of responding to an anomalous change in downhole pressure in a bore hole comprises detecting the anomalous change in downhole pressure, sending a signal along the segmented electromagnetic transmission path, receiving the signal, and performing a automated response. The anomalous change in downhole pressure is detected at a first location along a segmented electromagnetic transmission path, and the segmented electromagnetic transmission path is integrated into the tool string. The signal is received by at least one receiver in communication with the segmented electromagnetic transmission path. The automated response is performed along the tool string. Disclosed is an apparatus for responding to an anomalous change in downhole pressure in a downhole tool string, comprising a segmented electromagnetic transmission path connecting one or more receivers and at least one pressure sensor.

Attending to unrelated targets boosts short-term memory for color arrays.

PubMed

Makovski, Tal; Swallow, Khena M; Jiang, Yuhong V

2011-05-01

Detecting a target typically impairs performance in a second, unrelated task. It has been recently reported however, that detecting a target in a stream of distractors can enhance long-term memory of faces and scenes that were presented concurrently with the target (the attentional boost effect). In this study we ask whether target detection also enhances performance in a visual short-term memory task, where capacity limits are severe. Participants performed two tasks at once: a one shot, color change detection task and a letter-detection task. In Experiment 1, a central letter appeared at the same time as 3 or 5 color patches (memory display). Participants encoded the colors and pressed the spacebar if the letter was a T (target). After a short retention interval, a probe display of color patches appeared. Performance on the change detection task was enhanced when a target, rather than a distractor, appeared with the memory display. This effect was not modulated by memory load or the frequency of trials in which a target appeared. However, there was no enhancement when the target appeared at the same time as the probe display (Experiment 2a) or during the memory retention interval (Experiment 2b). Together these results suggest that detecting a target facilitates the encoding of unrelated information into visual short-term memory. Copyright © 2010 Elsevier Ltd. All rights reserved.

Adaptive Framework for Classification and Novel Class Detection over Evolving Data Streams with Limited Labeled Data.

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

Haque, Ahsanul; Khan, Latifur; Baron, Michael

2015-09-01

Most approaches to classifying evolving data streams either divide the stream of data into fixed-size chunks or use gradual forgetting to address the problems of infinite length and concept drift. Finding the fixed size of the chunks or choosing a forgetting rate without prior knowledge about time-scale of change is not a trivial task. As a result, these approaches suffer from a trade-off between performance and sensitivity. To address this problem, we present a framework which uses change detection techniques on the classifier performance to determine chunk boundaries dynamically. Though this framework exhibits good performance, it is heavily dependent onmore » the availability of true labels of data instances. However, labeled data instances are scarce in realistic settings and not readily available. Therefore, we present a second framework which is unsupervised in nature, and exploits change detection on classifier confidence values to determine chunk boundaries dynamically. In this way, it avoids the use of labeled data while still addressing the problems of infinite length and concept drift. Moreover, both of our proposed frameworks address the concept evolution problem by detecting outliers having similar values for the attributes. We provide theoretical proof that our change detection method works better than other state-of-the-art approaches in this particular scenario. Results from experiments on various benchmark and synthetic data sets also show the efficiency of our proposed frameworks.« less

On analyzing colour constancy approach for improving SURF detector performance

NASA Astrophysics Data System (ADS)

Zulkiey, Mohd Asyraf; Zaki, Wan Mimi Diyana Wan; Hussain, Aini; Mustafa, Mohd. Marzuki

2012-04-01

Robust key point detector plays a crucial role in obtaining a good tracking feature. The main challenge in outdoor tracking is the illumination change due to various reasons such as weather fluctuation and occlusion. This paper approaches the illumination change problem by transforming the input image through colour constancy algorithm before applying the SURF detector. Masked grey world approach is chosen because of its ability to perform well under local as well as global illumination change. Every image is transformed to imitate the canonical illuminant and Gaussian distribution is used to model the global change. The simulation results show that the average number of detected key points have increased by 69.92%. Moreover, the average of improved performance cases far out weight the degradation case where the former is improved by 215.23%. The approach is suitable for tracking implementation where sudden illumination occurs frequently and robust key point detection is needed.

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 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.

Change detection for synthetic aperture radar images based on pattern and intensity distinctiveness analysis

NASA Astrophysics Data System (ADS)

Wang, Xiao; Gao, Feng; Dong, Junyu; Qi, Qiang

2018-04-01

Synthetic aperture radar (SAR) image is independent on atmospheric conditions, and it is the ideal image source for change detection. Existing methods directly analysis all the regions in the speckle noise contaminated difference image. The performance of these methods is easily affected by small noisy regions. In this paper, we proposed a novel change detection framework for saliency-guided change detection based on pattern and intensity distinctiveness analysis. The saliency analysis step can remove small noisy regions, and therefore makes the proposed method more robust to the speckle noise. In the proposed method, the log-ratio operator is first utilized to obtain a difference image (DI). Then, the saliency detection method based on pattern and intensity distinctiveness analysis is utilized to obtain the changed region candidates. Finally, principal component analysis and k-means clustering are employed to analysis pixels in the changed region candidates. Thus, the final change map can be obtained by classifying these pixels into changed or unchanged class. The experiment results on two real SAR images datasets have demonstrated the effectiveness of the proposed method.

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.

Changing behavior and accuracy with time on task in mammography screening

NASA Astrophysics Data System (ADS)

Taylor-Phillips, Sian; Jenkinson, David; Stinton, Chris; Wallis, Matthew G.; Clarke, Aileen

2017-03-01

Background: The vigilance decrement and prevalence effect both describe changes to speed and accuracy with time on task. Whilst there is much laboratory based research on these effects, little is known about whether they occur in real world mammography practice. Methods: The Changing Case Order to Optimise Patterns of Performance in Screening (CO-OPS) trial randomised 37,724 batches containing 1.2 million women attending breast screening to intervention or control (222,208 from the Midlands of England). In the control arm the batch was examined in the same order by both readers, in the intervention arm it was examined in a different order by both readers. Time taken, recall decision by both readers, and cancers detected were recorded for each case, and used to examine patterns of performance with time on task. Results: 49,575 women were recalled and 10,484 had cancer detected. Median time taken to examine each case was 35 seconds (out of cases where time taken was 10 minutes or less). The intervention did not affect overall cancer detection rates or recall rates. A more detailed analysis of the Midlands data indicates cancer detection rate did not change when reading up to 60 cases in a batch, but recall rate reduced. Time taken per case reduced with time on task, from a median 41 seconds when examining the second case in the batch to 28.5 seconds examining the 60th case. Conclusion: Reader behavior and performance systematically changes with time on task in breast screening.

Proactive Interference Does Not Meaningfully Distort Visual Working Memory Capacity Estimates in the Canonical Change Detection Task

PubMed Central

Lin, Po-Han; Luck, Steven J.

2012-01-01

The change detection task has become a standard method for estimating the storage capacity of visual working memory. Most researchers assume that this task isolates the properties of an active short-term storage system that can be dissociated from long-term memory systems. However, long-term memory storage may influence performance on this task. In particular, memory traces from previous trials may create proactive interference that sometimes leads to errors, thereby reducing estimated capacity. Consequently, the capacity of visual working memory may be higher than is usually thought, and correlations between capacity and other measures of cognition may reflect individual differences in proactive interference rather than individual differences in the capacity of the short-term storage system. Indeed, previous research has shown that change detection performance can be influenced by proactive interference under some conditions. The purpose of the present study was to determine whether the canonical version of the change detection task – in which the to-be-remembered information consists of simple, briefly presented features – is influenced by proactive interference. Two experiments were conducted using methods that ordinarily produce substantial evidence of proactive interference, but no proactive interference was observed. Thus, the canonical version of the change detection task can be used to assess visual working memory capacity with no meaningful influence of proactive interference. PMID:22403556

Proactive interference does not meaningfully distort visual working memory capacity estimates in the canonical change detection task.

PubMed

Lin, Po-Han; Luck, Steven J

2012-01-01

The change detection task has become a standard method for estimating the storage capacity of visual working memory. Most researchers assume that this task isolates the properties of an active short-term storage system that can be dissociated from long-term memory systems. However, long-term memory storage may influence performance on this task. In particular, memory traces from previous trials may create proactive interference that sometimes leads to errors, thereby reducing estimated capacity. Consequently, the capacity of visual working memory may be higher than is usually thought, and correlations between capacity and other measures of cognition may reflect individual differences in proactive interference rather than individual differences in the capacity of the short-term storage system. Indeed, previous research has shown that change detection performance can be influenced by proactive interference under some conditions. The purpose of the present study was to determine whether the canonical version of the change detection task - in which the to-be-remembered information consists of simple, briefly presented features - is influenced by proactive interference. Two experiments were conducted using methods that ordinarily produce substantial evidence of proactive interference, but no proactive interference was observed. Thus, the canonical version of the change detection task can be used to assess visual working memory capacity with no meaningful influence of proactive interference.

Blindness to a simultaneous change of all elements in a scene, unless there is a change in summary statistics.

PubMed

Saiki, Jun; Holcombe, Alex O

2012-03-06

Sudden change of every object in a display is typically conspicuous. We find however that in the presence of a secondary task, with a display of moving dots, it can be difficult to detect a sudden change in color of all the dots. A field of 200 dots, half red and half green, half moving rightward and half moving leftward, gave the appearance of two surfaces. When all 200 dots simultaneously switched color between red and green, performance in detecting the switch was very poor. A key display characteristic was that the color proportions on each surface (summary statistics) were not affected by the color switch. When the color switch is accompanied by a change in these summary statistics, people perform well in detecting the switch, suggesting that the secondary task does not disrupt the availability of this statistical information. These findings suggest that when the change is missed, the old and new colors were represented, but the color-location pattern (binding of colors to locations) was not represented or not compared. Even after extended viewing, changes to the individual color-location pattern are not available, suggesting that the feeling of seeing these details is misleading.

Building Change Detection from LIDAR Point Cloud Data Based on Connected Component Analysis

NASA Astrophysics Data System (ADS)

Awrangjeb, M.; Fraser, C. S.; Lu, G.

2015-08-01

Building data are one of the important data types in a topographic database. Building change detection after a period of time is necessary for many applications, such as identification of informal settlements. Based on the detected changes, the database has to be updated to ensure its usefulness. This paper proposes an improved building detection technique, which is a prerequisite for many building change detection techniques. The improved technique examines the gap between neighbouring buildings in the building mask in order to avoid under segmentation errors. Then, a new building change detection technique from LIDAR point cloud data is proposed. Buildings which are totally new or demolished are directly added to the change detection output. However, for demolished or extended building parts, a connected component analysis algorithm is applied and for each connected component its area, width and height are estimated in order to ascertain if it can be considered as a demolished or new building part. Finally, a graphical user interface (GUI) has been developed to update detected changes to the existing building map. Experimental results show that the improved building detection technique can offer not only higher performance in terms of completeness and correctness, but also a lower number of undersegmentation errors as compared to its original counterpart. The proposed change detection technique produces no omission errors and thus it can be exploited for enhanced automated building information updating within a topographic database. Using the developed GUI, the user can quickly examine each suggested change and indicate his/her decision with a minimum number of mouse clicks.

Mutation detection for inventories of traffic signs from street-level panoramic images

NASA Astrophysics Data System (ADS)

Hazelhoff, Lykele; Creusen, Ivo; De With, Peter H. N.

2014-03-01

Road safety is positively influenced by both adequate placement and optimal visibility of traffic signs. As their visibility degrades over time due to e.g. aging, vandalism, accidents and vegetation coverage, up-to-date inven­tories of traffic signs are highly attractive for preserving a high road safety. These inventories are performed in a semi-automatic fashion from street-level panoramic images, exploiting object detection and classification tech­niques. Next to performing inventories from scratch, these systems are also exploited for the efficient retrieval of situation changes by comparing the outcome of the automated system to a baseline inventory (e.g. performed in a previous year). This allows for specific manual interactions to the found changes, while skipping all unchanged situations, thereby resulting in a large efficiency gain. This work describes such a mutation detection approach, with special attention to re-identifying previously found signs. Preliminary results on a geographical area con­taining about 425 km of road show that 91.3% of the unchanged signs are re-identified, while the amount of found differences equals about 35% of the number of baseline signs. From these differences, about 50% correspond to physically changed traffic signs, next to false detections, misclassifications and missed signs. As a bonus, our approach directly results in the changed situations, which is beneficial for road sign maintenance.

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).

Two-stage Keypoint Detection Scheme for Region Duplication Forgery Detection in Digital Images.

PubMed

Emam, Mahmoud; Han, Qi; Zhang, Hongli

2018-01-01

In digital image forensics, copy-move or region duplication forgery detection became a vital research topic recently. Most of the existing keypoint-based forgery detection methods fail to detect the forgery in the smooth regions, rather than its sensitivity to geometric changes. To solve these problems and detect points which cover all the regions, we proposed two steps for keypoint detection. First, we employed the scale-invariant feature operator to detect the spatially distributed keypoints from the textured regions. Second, the keypoints from the missing regions are detected using Harris corner detector with nonmaximal suppression to evenly distribute the detected keypoints. To improve the matching performance, local feature points are described using Multi-support Region Order-based Gradient Histogram descriptor. Based on precision-recall rates and commonly tested dataset, comprehensive performance evaluation is performed. The results demonstrated that the proposed scheme has better detection and robustness against some geometric transformation attacks compared with state-of-the-art methods. © 2017 American Academy of Forensic Sciences.

Detection of degenerative change in lateral projection cervical spine x-ray images

NASA Astrophysics Data System (ADS)

Jebri, Beyrem; Phillips, Michael; Knapp, Karen; Appelboam, Andy; Reuben, Adam; Slabaugh, Greg

2015-03-01

Degenerative changes to the cervical spine can be accompanied by neck pain, which can result from narrowing of the intervertebral disc space and growth of osteophytes. In a lateral x-ray image of the cervical spine, degenerative changes are characterized by vertebral bodies that have indistinct boundaries and limited spacing between vertebrae. In this paper, we present a machine learning approach to detect and localize degenerative changes in lateral x-ray images of the cervical spine. Starting from a user-supplied set of points in the center of each vertebral body, we fit a central spline, from which a region of interest is extracted and image features are computed. A Random Forest classifier labels regions as degenerative change or normal. Leave-one-out cross-validation studies performed on a dataset of 103 patients demonstrates performance of above 95% accuracy.

Multiscale-Driven approach to detecting change in Synthetic Aperture Radar (SAR) imagery

NASA Astrophysics Data System (ADS)

Gens, R.; Hogenson, K.; Ajadi, O. A.; Meyer, F. J.; Myers, A.; Logan, T. A.; Arnoult, K., Jr.

2017-12-01

Detecting changes between Synthetic Aperture Radar (SAR) images can be a useful but challenging exercise. SAR with its all-weather capabilities can be an important resource in identifying and estimating the expanse of events such as flooding, river ice breakup, earthquake damage, oil spills, and forest growth, as it can overcome shortcomings of optical methods related to cloud cover. However, detecting change in SAR imagery can be impeded by many factors including speckle, complex scattering responses, low temporal sampling, and difficulty delineating boundaries. In this presentation we use a change detection method based on a multiscale-driven approach. By using information at different resolution levels, we attempt to obtain more accurate change detection maps in both heterogeneous and homogeneous regions. Integrated within the processing flow are processes that 1) improve classification performance by combining Expectation-Maximization algorithms with mathematical morphology, 2) achieve high accuracy in preserving boundaries using measurement level fusion techniques, and 3) combine modern non-local filtering and 2D-discrete stationary wavelet transform to provide robustness against noise. This multiscale-driven approach to change detection has recently been incorporated into the Alaska Satellite Facility (ASF) Hybrid Pluggable Processing Pipeline (HyP3) using radiometrically terrain corrected SAR images. Examples primarily from natural hazards are presented to illustrate the capabilities and limitations of the change detection method.

Minimal time change detection algorithm for reconfigurable control system and application to aerospace

NASA Technical Reports Server (NTRS)

Kim, Sungwan

1994-01-01

System parameters should be tracked on-line to build a reconfigurable control system even though there exists an abrupt change. For this purpose, a new performance index that we are studying is the speed of adaptation- how quickly does the system determine that a change has occurred? In this paper, a new, robust algorithm that is optimized to minimize the time delay in detecting a change for fixed false alarm probability is proposed. Simulation results for the aircraft lateral motion with a known or unknown change in control gain matrices, in the presence of doublet input, indicate that the algorithm works fairly well. One of its distinguishing properties is that detection delay of this algorithm is superior to that of Whiteness Test.

Image Change Detection via Ensemble Learning

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

Martin, Benjamin W; Vatsavai, Raju

2013-01-01

The concept of geographic change detection is relevant in many areas. Changes in geography can reveal much information about a particular location. For example, analysis of changes in geography can identify regions of population growth, change in land use, and potential environmental disturbance. A common way to perform change detection is to use a simple method such as differencing to detect regions of change. Though these techniques are simple, often the application of these techniques is very limited. Recently, use of machine learning methods such as neural networks for change detection has been explored with great success. In this work,more » we explore the use of ensemble learning methodologies for detecting changes in bitemporal synthetic aperture radar (SAR) images. Ensemble learning uses a collection of weak machine learning classifiers to create a stronger classifier which has higher accuracy than the individual classifiers in the ensemble. The strength of the ensemble lies in the fact that the individual classifiers in the ensemble create a mixture of experts in which the final classification made by the ensemble classifier is calculated from the outputs of the individual classifiers. Our methodology leverages this aspect of ensemble learning by training collections of weak decision tree based classifiers to identify regions of change in SAR images collected of a region in the Staten Island, New York area during Hurricane Sandy. Preliminary studies show that the ensemble method has approximately 11.5% higher change detection accuracy than an individual classifier.« less

A Doubly Stochastic Change Point Detection Algorithm for Noisy Biological Signals.

PubMed

Gold, Nathan; Frasch, Martin G; Herry, Christophe L; Richardson, Bryan S; Wang, Xiaogang

2017-01-01

Experimentally and clinically collected time series data are often contaminated with significant confounding noise, creating short, noisy time series. This noise, due to natural variability and measurement error, poses a challenge to conventional change point detection methods. We propose a novel and robust statistical method for change point detection for noisy biological time sequences. Our method is a significant improvement over traditional change point detection methods, which only examine a potential anomaly at a single time point. In contrast, our method considers all suspected anomaly points and considers the joint probability distribution of the number of change points and the elapsed time between two consecutive anomalies. We validate our method with three simulated time series, a widely accepted benchmark data set, two geological time series, a data set of ECG recordings, and a physiological data set of heart rate variability measurements of fetal sheep model of human labor, comparing it to three existing methods. Our method demonstrates significantly improved performance over the existing point-wise detection methods.

Graph-based structural change detection for rotating machinery monitoring

NASA Astrophysics Data System (ADS)

Lu, Guoliang; Liu, Jie; Yan, Peng

2018-01-01

Detection of structural changes is critically important in operational monitoring of a rotating machine. This paper presents a novel framework for this purpose, where a graph model for data modeling is adopted to represent/capture statistical dynamics in machine operations. Meanwhile we develop a numerical method for computing temporal anomalies in the constructed graphs. The martingale-test method is employed for the change detection when making decisions on possible structural changes, where excellent performance is demonstrated outperforming exciting results such as the autoregressive-integrated-moving average (ARIMA) model. Comprehensive experimental results indicate good potentials of the proposed algorithm in various engineering applications. This work is an extension of a recent result (Lu et al., 2017).

Pulmonary-impedance power spectral analysis: A facile means of detecting radiation-induced gastrointestinal distress and performance decrement in man

NASA Technical Reports Server (NTRS)

Rick, R. C.; Lushbaugh, C. C.; Mcdow, E.; Frome, E.

1972-01-01

Changes in respiratory variance revealed by power spectral analysis of the pulmonary impedance pneumogram can be used to detect and measure stresses directly or indirectly affecting human respiratory function. When gastrointestinal distress occurred during a series of 5 total-body exposures of 30 R at a rate of 1.5 R/min, it was accompanied by typical shifts in pulmonary impedance power spectra. These changes did not occur after protracted exposure of 250 R (30 R daily) at 1.5 R/hr that failed to cause radiation sickness. This system for quantitating respiratory effort can also be used to detect alterations in one's ability to perform under controlled exercise conditions.

Change detection in urban and rural driving scenes: Effects of target type and safety relevance on change blindness.

PubMed

Beanland, Vanessa; Filtness, Ashleigh J; Jeans, Rhiannon

2017-03-01

The ability to detect changes is crucial for safe driving. Previous research has demonstrated that drivers often experience change blindness, which refers to failed or delayed change detection. The current study explored how susceptibility to change blindness varies as a function of the driving environment, type of object changed, and safety relevance of the change. Twenty-six fully-licenced drivers completed a driving-related change detection task. Changes occurred to seven target objects (road signs, cars, motorcycles, traffic lights, pedestrians, animals, or roadside trees) across two environments (urban or rural). The contextual safety relevance of the change was systematically manipulated within each object category, ranging from high safety relevance (i.e., requiring a response by the driver) to low safety relevance (i.e., requiring no response). When viewing rural scenes, compared with urban scenes, participants were significantly faster and more accurate at detecting changes, and were less susceptible to "looked-but-failed-to-see" errors. Interestingly, safety relevance of the change differentially affected performance in urban and rural environments. In urban scenes, participants were more efficient at detecting changes with higher safety relevance, whereas in rural scenes the effect of safety relevance has marginal to no effect on change detection. Finally, even after accounting for safety relevance, change blindness varied significantly between target types. Overall the results suggest that drivers are less susceptible to change blindness for objects that are likely to change or move (e.g., traffic lights vs. road signs), and for moving objects that pose greater danger (e.g., wild animals vs. pedestrians). Copyright © 2017 Elsevier Ltd. All rights reserved.

Cognitive performance and age-related changes in the hippocampal proteome.

PubMed

Freeman, W M; VanGuilder, H D; Bennett, C; Sonntag, W E

2009-03-03

Declining cognitive performance is associated with increasing age, even in the absence of overt pathological processes. We and others have reported that declining cognitive performance is associated with age-related changes in brain glucose utilization, long-term potentiation and paired-pulse facilitation, protein expression, neurotransmitter levels, and trophic factors. However, it is unclear whether these changes are causes or symptoms of the underlying alterations in dendritic and synaptic morphology that occur with age. In this study, we examined the hippocampal proteome for age- and cognition-associated changes in behaviorally stratified young and old rats, using two-dimensional in-gel electrophoresis and MS/MS. Comparison of old cognitively intact with old cognitively impaired animals revealed additional changes that would not have been detected otherwise. Interestingly, not all age-related changes in protein expression were associated with cognitive decline, and distinct differences in protein expression were found when comparing old cognitively intact with old cognitively impaired rats. A large number of protein changes with age were related to the glycolysis/gluconeogenesis pathway. In total, the proteomic changes suggest that age-related alterations act synergistically with other perturbations to result in cognitive decline. This study also demonstrates the importance of examining behaviorally-defined animals in proteomic studies, as comparison of young to old animals regardless of behavioral performance would have failed to detect many cognitive impairment-specific protein expression changes evident when behavioral stratification data were used.

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.

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'.

Evaluation of video detection systems, volume 1 : effects of configuration changes in the performance of video detection systems.

DOT National Transportation Integrated Search

2009-10-01

The effects of modifying the configuration of three video detection (VD) systems (Iteris, Autoscope, and Peek) : are evaluated in daytime and nighttime conditions. Four types of errors were used: false, missed, stuck-on, and : dropped calls. The thre...

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.

[The role of sustained attention in shift-contingent change blindness].

PubMed

Nakashima, Ryoichi; Yokosawa, Kazuhiko

2015-02-01

Previous studies of change blindness have examined the effect of temporal factors (e.g., blank duration) on attention in change detection. This study examined the effect of spatial factors (i.e., whether the locations of original and changed objects are the same or different) on attention in change detection, using a shift-contingent change blindness task. We used a flicker paradigm in which the location of a to-be-judged target image was manipulated (shift, no-shift). In shift conditions, the image of an array of objects was spatially shifted so that all objects appeared in new locations; in no-shift conditions, all object images of an array appeared at the same location. The presence of visual stimuli (dots) in the blank display between the two images was.manipulated (dot, no-dot) under the assumption that abrupt onsets of these stimuli would capture attention. Results indicated that change detection performance was improved by exogenous attentional capture in the shift condition. Thus, we suggest that attention can play an important role in change detection during shift-contingent change blindness.

a Framework of Change Detection Based on Combined Morphologica Features and Multi-Index Classification

NASA Astrophysics Data System (ADS)

Li, S.; Zhang, S.; Yang, D.

2017-09-01

Remote sensing images are particularly well suited for analysis of land cover change. In this paper, we present a new framework for detection of changing land cover using satellite imagery. Morphological features and a multi-index are used to extract typical objects from the imagery, including vegetation, water, bare land, buildings, and roads. Our method, based on connected domains, is different from traditional methods; it uses image segmentation to extract morphological features, while the enhanced vegetation index (EVI), the differential water index (NDWI) are used to extract vegetation and water, and a fragmentation index is used to the correct extraction results of water. HSV transformation and threshold segmentation extract and remove the effects of shadows on extraction results. Change detection is performed on these results. One of the advantages of the proposed framework is that semantic information is extracted automatically using low-level morphological features and indexes. Another advantage is that the proposed method detects specific types of change without any training samples. A test on ZY-3 images demonstrates that our framework has a promising capability to detect change.

Impact of three task demand factors on simulated unmanned system intelligence, surveillance, and reconnaissance operations.

PubMed

Abich, Julian; Reinerman-Jones, Lauren; Matthews, Gerald

2017-06-01

The present study investigated how three task demand factors influenced performance, subjective workload and stress of novice intelligence, surveillance, and reconnaissance operators within a simulation of an unmanned ground vehicle. Manipulations were task type, dual-tasking and event rate. Participants were required to discriminate human targets within a street scene from a direct video feed (threat detection [TD] task) and detect changes in symbols presented in a map display (change detection [CD] task). Dual-tasking elevated workload and distress, and impaired performance for both tasks. However, with increasing event rate, CD task deteriorated, but TD improved. Thus, standard workload models provide a better guide to evaluating the demands of abstract symbols than to processing realistic human characters. Assessment of stress and workload may be especially important in the design and evaluation of systems in which human character critical signals must be detected in video images. Practitioner Summary: This experiment assessed subjective workload and stress during threat and CD tasks performed alone and in combination. Results indicated an increase in event rate led to significant improvements in performance during TD, but decrements during CD, yet both had associated increases in workload and engagement.

Detecting temporal changes in acoustic scenes: The variable benefit of selective attention.

PubMed

Demany, Laurent; Bayle, Yann; Puginier, Emilie; Semal, Catherine

2017-09-01

Four experiments investigated change detection in acoustic scenes consisting of a sum of five amplitude-modulated pure tones. As the tones were about 0.7 octave apart and were amplitude-modulated with different frequencies (in the range 2-32 Hz), they were perceived as separate streams. Listeners had to detect a change in the frequency (experiments 1 and 2) or the shape (experiments 3 and 4) of the modulation of one of the five tones, in the presence of an informative cue orienting selective attention either before the scene (pre-cue) or after it (post-cue). The changes left intensity unchanged and were not detectable in the spectral (tonotopic) domain. Performance was much better with pre-cues than with post-cues. Thus, change deafness was manifest in the absence of an appropriate focusing of attention when the change occurred, even though the streams and the changes to be detected were acoustically very simple (in contrast to the conditions used in previous demonstrations of change deafness). In one case, the results were consistent with a model based on the assumption that change detection was possible if and only if attention was endogenously focused on a single tone. However, it was also found that changes resulting in a steepening of amplitude rises were to some extent able to draw attention exogenously. Change detection was not markedly facilitated when the change produced a discontinuity in the modulation domain, contrary to what could be expected from the perspective of predictive coding. Copyright © 2017 Elsevier B.V. All rights reserved.

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

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

Uav-Based 3d Urban Environment Monitoring

NASA Astrophysics Data System (ADS)

Boonpook, Wuttichai; Tan, Yumin; Liu, Huaqing; Zhao, Binbin; He, Lingfeng

2018-04-01

Unmanned Aerial Vehicle (UAV) based remote sensing can be used to make three-dimensions (3D) mapping with great flexibility, besides the ability to provide high resolution images. In this paper we propose a quick-change detection method on UAV images by combining altitude from Digital Surface Model (DSM) and texture analysis from images. Cases of UAV images with and without georeferencing are both considered. Research results show that the accuracy of change detection can be enhanced with georeferencing procedure, and the accuracy and precision of change detection on UAV images which are collected both vertically and obliquely but without georeferencing also have a good performance.

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.

Fast and Robust Segmentation and Classification for Change Detection in Urban Point Clouds

NASA Astrophysics Data System (ADS)

Roynard, X.; Deschaud, J.-E.; Goulette, F.

2016-06-01

Change detection is an important issue in city monitoring to analyse street furniture, road works, car parking, etc. For example, parking surveys are needed but are currently a laborious task involving sending operators in the streets to identify the changes in car locations. In this paper, we propose a method that performs a fast and robust segmentation and classification of urban point clouds, that can be used for change detection. We apply this method to detect the cars, as a particular object class, in order to perform parking surveys automatically. A recently proposed method already addresses the need for fast segmentation and classification of urban point clouds, using elevation images. The interest to work on images is that processing is much faster, proven and robust. However there may be a loss of information in complex 3D cases: for example when objects are one above the other, typically a car under a tree or a pedestrian under a balcony. In this paper we propose a method that retain the three-dimensional information while preserving fast computation times and improving segmentation and classification accuracy. It is based on fast region-growing using an octree, for the segmentation, and specific descriptors with Random-Forest for the classification. Experiments have been performed on large urban point clouds acquired by Mobile Laser Scanning. They show that the method is as fast as the state of the art, and that it gives more robust results in the complex 3D cases.

The aftermath of memory retrieval for recycling visual working memory representations.

PubMed

Park, Hyung-Bum; Zhang, Weiwei; Hyun, Joo-Seok

2017-07-01

We examined the aftermath of accessing and retrieving a subset of information stored in visual working memory (VWM)-namely, whether detection of a mismatch between memory and perception can impair the original memory of an item while triggering recognition-induced forgetting for the remaining, untested items. For this purpose, we devised a consecutive-change detection task wherein two successive testing probes were displayed after a single set of memory items. Across two experiments utilizing different memory-testing methods (whole vs. single probe), we observed a reliable pattern of poor performance in change detection for the second test when the first test had exhibited a color change. The impairment after a color change was evident even when the same memory item was repeatedly probed; this suggests that an attention-driven, salient visual change made it difficult to reinstate the previously remembered item. The second change detection, for memory items untested during the first change detection, was also found to be inaccurate, indicating that recognition-induced forgetting had occurred for the unprobed items in VWM. In a third experiment, we conducted a task that involved change detection plus continuous recall, wherein a memory recall task was presented after the change detection task. The analyses of the distributions of recall errors with a probabilistic mixture model revealed that the memory impairments from both visual changes and recognition-induced forgetting are explained better by the stochastic loss of memory items than by their degraded resolution. These results indicate that attention-driven visual change and recognition-induced forgetting jointly influence the "recycling" of VWM representations.

12 CFR 391.23 - Duties of card issuers regarding changes of address.

Code of Federal Regulations, 2012 CFR

2012-01-01

... detect relevant Red Flags that may arise in the performance of the service provider's activities, and... or creditor detects a fraud or active duty alert; (c) Implementing any requirements for furnishers of..., App. Appendix to Subpart C of Part 391—Interagency Guidelines on Identity Theft Detection, Prevention...

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.

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.

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.

The internal and external responsiveness of Functional Assessment of Cancer Therapy-Prostate (FACT-P) and Short Form-12 Health Survey version 2 (SF-12 v2) in patients with prostate cancer.

PubMed

Choi, Edmond P H; Wong, Carlos K H; Wan, Eric Y F; Tsu, James H L; Chin, W Y; Kung, Kenny; Yiu, M K

2016-09-01

To examine the responsiveness of Functional Assessment of Cancer Therapy-Prostate (FACT-P) and Short Form-12 Health Survey version 2 (SF-12 v2) in prostate cancer patients because there is a lack of evidence to support their responsiveness in this patient population. One hundred sixty-eight subjects with prostate cancer were surveyed at baseline and at 6 months using the SF-12 v2 and FACT-P version 4. Internal responsiveness was assessed using paired t test and generalized estimating equation. External responsiveness was evaluated using receiver operating characteristic curve analysis. The internal responsiveness of the FACT-P and SF-12 v2 to detect positive change was satisfactory. The FACT-P and SF-12 v2 could not detect negative change. The FACT-P and the SF-12 v2 performed the best in distinguishing between improved general health and worsened general health. The FACT-P performed better in distinguishing between unchanged general health and worsened general health. The SF-12 v2 performed better in distinguishing between unchanged general health and improved general health. Positive change detected by these measures should be interpreted with caution as they might be too responsive to detect "noise," which is not clinically significant. The ability of the FACT-P and the SF-12 v2 to detect negative change was disappointing. The internal and external responsiveness of the social well-being of the FACT-P cannot be supported, suggesting that it is not suitable to longitudinally monitor the social component of HRQOL in prostate cancer patients. The study suggested that generic and disease-specific measures should be used together to complement each other.

Guidance of attention to objects and locations by long-term memory of natural scenes.

PubMed

Becker, Mark W; Rasmussen, Ian P

2008-11-01

Four flicker change-detection experiments demonstrate that scene-specific long-term memory guides attention to both behaviorally relevant locations and objects within a familiar scene. Participants performed an initial block of change-detection trials, detecting the addition of an object to a natural scene. After a 30-min delay, participants performed an unanticipated 2nd block of trials. When the same scene occurred in the 2nd block, the change within the scene was (a) identical to the original change, (b) a new object appearing in the original change location, (c) the same object appearing in a new location, or (d) a new object appearing in a new location. Results suggest that attention is rapidly allocated to previously relevant locations and then to previously relevant objects. This pattern of locations dominating objects remained when object identity information was made more salient. Eye tracking verified that scene memory results in more direct scan paths to previously relevant locations and objects. This contextual guidance suggests that a high-capacity long-term memory for scenes is used to insure that limited attentional capacity is allocated efficiently rather than being squandered.

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).

Reinforcement learning and counterfactual reasoning explain adaptive behavior in a changing environment.

PubMed

Zhang, Yunfeng; Paik, Jaehyon; Pirolli, Peter

2015-04-01

Animals routinely adapt to changes in the environment in order to survive. Though reinforcement learning may play a role in such adaptation, it is not clear that it is the only mechanism involved, as it is not well suited to producing rapid, relatively immediate changes in strategies in response to environmental changes. This research proposes that counterfactual reasoning might be an additional mechanism that facilitates change detection. An experiment is conducted in which a task state changes over time and the participants had to detect the changes in order to perform well and gain monetary rewards. A cognitive model is constructed that incorporates reinforcement learning with counterfactual reasoning to help quickly adjust the utility of task strategies in response to changes. The results show that the model can accurately explain human data and that counterfactual reasoning is key to reproducing the various effects observed in this change detection paradigm. Copyright © 2015 Cognitive Science Society, Inc.

The fate of object memory traces under change detection and change blindness.

PubMed

Busch, Niko A

2013-07-03

Observers often fail to detect substantial changes in a visual scene. This so-called change blindness is often taken as evidence that visual representations are sparse and volatile. This notion rests on the assumption that the failure to detect a change implies that representations of the changing objects are lost all together. However, recent evidence suggests that under change blindness, object memory representations may be formed and stored, but not retrieved. This study investigated the fate of object memory representations when changes go unnoticed. Participants were presented with scenes consisting of real world objects, one of which changed on each trial, while recording event-related potentials (ERPs). Participants were first asked to localize where the change had occurred. In an additional recognition task, participants then discriminated old objects, either from the pre-change or the post-change scene, from entirely new objects. Neural traces of object memories were studied by comparing ERPs for old and novel objects. Participants performed poorly in the detection task and often failed to recognize objects from the scene, especially pre-change objects. However, a robust old/novel effect was observed in the ERP, even when participants were change blind and did not recognize the old object. This implicit memory trace was found both for pre-change and post-change objects. These findings suggest that object memories are stored even under change blindness. Thus, visual representations may not be as sparse and volatile as previously thought. Rather, change blindness may point to a failure to retrieve and use these representations for change detection. Copyright © 2013 Elsevier B.V. All rights reserved.

Unsupervised change detection of multispectral images based on spatial constraint chi-squared transform and Markov random field model

NASA Astrophysics Data System (ADS)

Shi, Aiye; Wang, Chao; Shen, Shaohong; Huang, Fengchen; Ma, Zhenli

2016-10-01

Chi-squared transform (CST), as a statistical method, can describe the difference degree between vectors. The CST-based methods operate directly on information stored in the difference image and are simple and effective methods for detecting changes in remotely sensed images that have been registered and aligned. However, the technique does not take spatial information into consideration, which leads to much noise in the result of change detection. An improved unsupervised change detection method is proposed based on spatial constraint CST (SCCST) in combination with a Markov random field (MRF) model. First, the mean and variance matrix of the difference image of bitemporal images are estimated by an iterative trimming method. In each iteration, spatial information is injected to reduce scattered changed points (also known as "salt and pepper" noise). To determine the key parameter confidence level in the SCCST method, a pseudotraining dataset is constructed to estimate the optimal value. Then, the result of SCCST, as an initial solution of change detection, is further improved by the MRF model. The experiments on simulated and real multitemporal and multispectral images indicate that the proposed method performs well in comprehensive indices compared with other methods.

Convolutional neural network features based change detection in satellite images

NASA Astrophysics Data System (ADS)

Mohammed El Amin, Arabi; Liu, Qingjie; Wang, Yunhong

2016-07-01

With the popular use of high resolution remote sensing (HRRS) satellite images, a huge research efforts have been placed on change detection (CD) problem. An effective feature selection method can significantly boost the final result. While hand-designed features have proven difficulties to design features that effectively capture high and mid-level representations, the recent developments in machine learning (Deep Learning) omit this problem by learning hierarchical representation in an unsupervised manner directly from data without human intervention. In this letter, we propose approaching the change detection problem from a feature learning perspective. A novel deep Convolutional Neural Networks (CNN) features based HR satellite images change detection method is proposed. The main guideline is to produce a change detection map directly from two images using a pretrained CNN. This method can omit the limited performance of hand-crafted features. Firstly, CNN features are extracted through different convolutional layers. Then, a concatenation step is evaluated after an normalization step, resulting in a unique higher dimensional feature map. Finally, a change map was computed using pixel-wise Euclidean distance. Our method has been validated on real bitemporal HRRS satellite images according to qualitative and quantitative analyses. The results obtained confirm the interest of the proposed method.

Oil Spill Detection and Tracking Using Lipschitz Regularity and Multiscale Techniques in Synthetic Aperture Radar Imagery

NASA Astrophysics Data System (ADS)

Ajadi, O. A.; Meyer, F. J.

2014-12-01

Automatic oil spill detection and tracking from Synthetic Aperture Radar (SAR) images is a difficult task, due in large part to the inhomogeneous properties of the sea surface, the high level of speckle inherent in SAR data, the complexity and the highly non-Gaussian nature of amplitude information, and the low temporal sampling that is often achieved with SAR systems. This research presents a promising new oil spill detection and tracking method that is based on time series of SAR images. Through the combination of a number of advanced image processing techniques, the develop approach is able to mitigate some of these previously mentioned limitations of SAR-based oil-spill detection and enables fully automatic spill detection and tracking across a wide range of spatial scales. The method combines an initial automatic texture analysis with a consecutive change detection approach based on multi-scale image decomposition. The first step of the approach, a texture transformation of the original SAR images, is performed in order to normalize the ocean background and enhance the contrast between oil-covered and oil-free ocean surfaces. The Lipschitz regularity (LR), a local texture parameter, is used here due to its proven ability to normalize the reflectivity properties of ocean water and maximize the visibly of oil in water. To calculate LR, the images are decomposed using two-dimensional continuous wavelet transform (2D-CWT), and transformed into Holder space to measure LR. After texture transformation, the now normalized images are inserted into our multi-temporal change detection algorithm. The multi-temporal change detection approach is a two-step procedure including (1) data enhancement and filtering and (2) multi-scale automatic change detection. The performance of the developed approach is demonstrated by an application to oil spill areas in the Gulf of Mexico. In this example, areas affected by oil spills were identified from a series of ALOS PALSAR images acquired in 2010. The comparison showed exceptional performance of our method. This method can be applied to emergency management and decision support systems with a need for real-time data, and it shows great potential for rapid data analysis in other areas, including volcano detection, flood boundaries, forest health, and wildfires.

Spectrotemporal Modulation Detection and Speech Perception by Cochlear Implant Users

PubMed Central

Won, Jong Ho; Moon, Il Joon; Jin, Sunhwa; Park, Heesung; Woo, Jihwan; Cho, Yang-Sun; Chung, Won-Ho; Hong, Sung Hwa

2015-01-01

Spectrotemporal modulation (STM) detection performance was examined for cochlear implant (CI) users. The test involved discriminating between an unmodulated steady noise and a modulated stimulus. The modulated stimulus presents frequency modulation patterns that change in frequency over time. In order to examine STM detection performance for different modulation conditions, two different temporal modulation rates (5 and 10 Hz) and three different spectral modulation densities (0.5, 1.0, and 2.0 cycles/octave) were employed, producing a total 6 different STM stimulus conditions. In order to explore how electric hearing constrains STM sensitivity for CI users differently from acoustic hearing, normal-hearing (NH) and hearing-impaired (HI) listeners were also tested on the same tasks. STM detection performance was best in NH subjects, followed by HI subjects. On average, CI subjects showed poorest performance, but some CI subjects showed high levels of STM detection performance that was comparable to acoustic hearing. Significant correlations were found between STM detection performance and speech identification performance in quiet and in noise. In order to understand the relative contribution of spectral and temporal modulation cues to speech perception abilities for CI users, spectral and temporal modulation detection was performed separately and related to STM detection and speech perception performance. The results suggest that that slow spectral modulation rather than slow temporal modulation may be important for determining speech perception capabilities for CI users. Lastly, test–retest reliability for STM detection was good with no learning. The present study demonstrates that STM detection may be a useful tool to evaluate the ability of CI sound processing strategies to deliver clinically pertinent acoustic modulation information. PMID:26485715

Comparative study of performance of neutral axis tracking based damage detection

NASA Astrophysics Data System (ADS)

Soman, R.; Malinowski, P.; Ostachowicz, W.

2015-07-01

This paper presents a comparative study of a novel SHM technique for damage isolation. The performance of the Neutral Axis (NA) tracking based damage detection strategy is compared to other popularly used vibration based damage detection methods viz. ECOMAC, Mode Shape Curvature Method and Strain Flexibility Index Method. The sensitivity of the novel method is compared under changing ambient temperature conditions and in the presence of measurement noise. Finite Element Analysis (FEA) of the DTU 10 MW Wind Turbine was conducted to compare the local damage identification capability of each method and the results are presented. Under the conditions examined, the proposed method was found to be robust to ambient condition changes and measurement noise. The damage identification in some is either at par with the methods mentioned in the literature or better under the investigated damage scenarios.

Lamb wave-based damage quantification and probability of detection modeling for fatigue life assessment of riveted lap joint

NASA Astrophysics Data System (ADS)

He, Jingjing; Wang, Dengjiang; Zhang, Weifang

2015-03-01

This study presents an experimental and modeling study for damage detection and quantification in riveted lap joints. Embedded lead zirconate titanate piezoelectric (PZT) ceramic wafer-type sensors are employed to perform in-situ non-destructive testing during fatigue cyclical loading. A multi-feature integration method is developed to quantify the crack size using signal features of correlation coefficient, amplitude change, and phase change. In addition, probability of detection (POD) model is constructed to quantify the reliability of the developed sizing method. Using the developed crack size quantification method and the resulting POD curve, probabilistic fatigue life prediction can be performed to provide comprehensive information for decision-making. The effectiveness of the overall methodology is demonstrated and validated using several aircraft lap joint specimens from different manufactures and under different loading conditions.

[Usefullness of transesophageal echocardiography in early detection of coronary spasm].

PubMed

Sagara, M; Haraguchi, M; Hamu, Y; Isowaki, S; Yoshimura, N

1996-04-01

Intraoperative transesophageal echocardiography (TEE) was performed on a 62-year-old man who underwent abdominal aortic replacement for abdominal aortic aneurysm under general anesthesia combined with epidural anesthesia. Coronary artery spasm occurred after unexpected massive hemorrhage, and TEE showed hypokinesis in the posterior-inferior left ventricular wall. The changes in TEE preceded the ST elevation in the ECG. Bolus infusion of isosorbide dinitrate and continuous infusion of nitroglycerin alleviated these changes. TEE enabled us to detect and evaluate coronary spasm before the appearance of ST changes in ECG.

Adaptive Detection and ISI Mitigation for Mobile Molecular Communication.

PubMed

Chang, Ge; Lin, Lin; Yan, Hao

2018-03-01

Current studies on modulation and detection schemes in molecular communication mainly focus on the scenarios with static transmitters and receivers. However, mobile molecular communication is needed in many envisioned applications, such as target tracking and drug delivery. Until now, investigations about mobile molecular communication have been limited. In this paper, a static transmitter and a mobile bacterium-based receiver performing random walk are considered. In this mobile scenario, the channel impulse response changes due to the dynamic change of the distance between the transmitter and the receiver. Detection schemes based on fixed distance fail in signal detection in such a scenario. Furthermore, the intersymbol interference (ISI) effect becomes more complex due to the dynamic character of the signal which makes the estimation and mitigation of the ISI even more difficult. In this paper, an adaptive ISI mitigation method and two adaptive detection schemes are proposed for this mobile scenario. In the proposed scheme, adaptive ISI mitigation, estimation of dynamic distance, and the corresponding impulse response reconstruction are performed in each symbol interval. Based on the dynamic channel impulse response in each interval, two adaptive detection schemes, concentration-based adaptive threshold detection and peak-time-based adaptive detection, are proposed for signal detection. Simulations demonstrate that the ISI effect is significantly reduced and the adaptive detection schemes are reliable and robust for mobile molecular communication.

Deficits in visual working-memory capacity and general cognition in African Americans with psychosis.

PubMed

Mathias, Samuel R; Knowles, Emma E M; Barrett, Jennifer; Beetham, Tamara; Leach, Olivia; Buccheri, Sebastiano; Aberizk, Katrina; Blangero, John; Poldrack, Russell A; Glahn, David C

2018-03-01

On average, patients with psychosis perform worse than controls on visual change-detection tasks, implying that psychosis is associated with reduced capacity of visual working memory (WM). In the present study, 79 patients diagnosed with various psychotic disorders and 166 controls, all African Americans, completed a change-detection task and several other neurocognitive measures. The aims of the study were to (1) determine whether we could observe a between-group difference in performance on the change-detection task in this sample; (2) establish whether such a difference could be specifically attributed to reduced WM capacity (k); and (3) estimate k in the context of the general cognitive deficit in psychosis. Consistent with previous studies, patients performed worse than controls on the change-detection task, on average. Bayesian hierarchical cognitive modeling of the data suggested that this between-group difference was driven by reduced k in patients, rather than differences in other psychologically meaningful model parameters (guessing behavior and lapse rate). Using the same modeling framework, we estimated the effect of psychosis on k while controlling for general intellectual ability (g, obtained from the other neurocognitive measures). The results suggested that reduced k in patients was stronger than predicted by the between-group difference in g. Moreover, a mediation analysis suggested that the relationship between psychosis and g (i.e., the general cognitive deficit) was mediated by k. The results were consistent with the idea that reduced k is a specific deficit in psychosis, which contributes to the general cognitive deficit. Copyright © 2017 Elsevier B.V. All rights reserved.

Sensitivity to change in cognitive performance and mood measures of energy and fatigue in response to differing doses of caffeine or breakfast.

PubMed

Maridakis, Victor; Herring, Matthew P; O'Connor, Patrick J

2009-01-01

This double-blind, placebo-controlled, within-subjects (N = 18) experiment compared the sensitivity to change of cognitive performance and mood measures of mental energy following consumption of either 100 or 200-mg caffeine or a 440-calorie breakfast. Breakfast and 200-mg caffeine improved mood and cognitive performance. The sensitivity to change of the measures did not differ in response to any treatment (all p values > .05). The mood and cognitive measures of mental energy used here have similar sensitivity to detecting change in response to a moderate dose of caffeine and breakfast consumption.

Removing Parallax-Induced False Changes in Change Detection

DTIC Science & Technology

2014-03-27

viii Figure Page 11 Three hypothetical ROC curves. The probability of detection (PD) is plotted against the probability of false alarm ( PFA ) based on...red and green) approach the value of PD = 1 and PFA = 0, the detector performance is said to improve. . . . . . . . . . . . . . . . 32 12 Possible... sorption are commonly among those with low SNRs as the gases and vapor in the atmosphere between the (airborne) sensor and the ground plane tend to

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.

Nano-particle enhanced impedimetric biosensor for detedtion of foodborne pathogens

NASA Astrophysics Data System (ADS)

Kim, G.; Om, A. S.; Mun, J. H.

2007-03-01

Recent outbreaks of foodborne illness have been increased the need for rapid and sensitive methods for detection of these pathogens. Conventional methods for pathogens detection and identification involve prolonged multiple enrichment steps. Even though some immunological rapid assays are available, these assays still need enrichment steps result in delayed detection. Biosensors have shown great potential for rapid detection of foodborne pathogens. They are capable of direct monitoring the antigen-antibody reactions in real time. Among the biosensors, impedimetric biosensors have been widely adapted as an analysis tool for the study of various biological binding reactions because of their high sensitivity and reagentless operation. In this study a nanoparticle-enhanced impedimetric biosensor for Salmonella enteritidis detection was developed which detected impedance changes caused by the attachment of the cells to the anti-Salmonella antibodies immobilized on interdigitated gold electrodes. Successive immobilization of neutravidin followed by anti-Salmonella antibodies was performed to the sensing area to create a biological detection surface. To enhance the impedance responses generated by antigen-antibody reactions, anti-Salmonella antibody conjugated nanoparticles were introduced on the sensing area. Using a portable impedance analyzer, the impedance across the interdigital electrodes was measured after the series of antigen-antibody bindings. Bacteria cells present in solution attached to capture antibodies and became tethered to the sensor surface. Attached bacteria cells changed the dielectric constant of the media between the electrodes thereby causing a change in measured impedance. Optimum input frequency was determined by analyzing frequency characteristics of the biosensor over ranges of applied frequencies from 10 Hz to 400 Hz. At 100 Hz of input frequency, the biosensor was most sensitive to the changes of the bacteria concentration and this frequency was used for the detection experiments. The biosensor was able to detect 106 CFU/mL in phosphate buffered saline (PBS) with a detection time of 3 minutes. Additional use of nanoparticles significantly enhanced the detection performance. By using the nanoparticles the biosensor could detect 104 CFU/mL of Salmonella enteritidis in PBS and 105 CFU/mL of cells in milk.

Hands-on resonance-enhanced photoacoustic detection

NASA Astrophysics Data System (ADS)

Euler, Manfred

2001-10-01

The design of an improved photoacoustic converter cell using kitchen equipment is described. It operates by changing manually the Helmholtz resonance frequency of bottles by adjusting the distance between the bottleneck and the outer ear. The experiment helps to gain insights in ear performance, in photoacoustic detection methods, in resonance phenomena and their role for detecting small periodic signals in the presence of noise.

A joint estimation detection of Glaucoma progression in 3D spectral domain optical coherence tomography optic nerve head images

NASA Astrophysics Data System (ADS)

Belghith, Akram; Bowd, Christopher; Weinreb, Robert N.; Zangwill, Linda M.

2014-03-01

Glaucoma is an ocular disease characterized by distinctive changes in the optic nerve head (ONH) and visual field. Glaucoma can strike without symptoms and causes blindness if it remains without treatment. Therefore, early disease detection is important so that treatment can be initiated and blindness prevented. In this context, important advances in technology for non-invasive imaging of the eye have been made providing quantitative tools to measure structural changes in ONH topography, an essential element for glaucoma detection and monitoring. 3D spectral domain optical coherence tomography (SD-OCT), an optical imaging technique, has been commonly used to discriminate glaucomatous from healthy subjects. In this paper, we present a new framework for detection of glaucoma progression using 3D SD-OCT images. In contrast to previous works that the retinal nerve fiber layer (RNFL) thickness measurement provided by commercially available spectral-domain optical coherence tomograph, we consider the whole 3D volume for change detection. To integrate a priori knowledge and in particular the spatial voxel dependency in the change detection map, we propose the use of the Markov Random Field to handle a such dependency. To accommodate the presence of false positive detection, the estimated change detection map is then used to classify a 3D SDOCT image into the "non-progressing" and "progressing" glaucoma classes, based on a fuzzy logic classifier. We compared the diagnostic performance of the proposed framework to existing methods of progression detection.

A joint estimation detection of Glaucoma progression in 3D spectral domain optical coherence tomography optic nerve head images.

PubMed

Belghith, Akram; Bowd, Christopher; Weinreb, Robert N; Zangwill, Linda M

2014-03-18

Glaucoma is an ocular disease characterized by distinctive changes in the optic nerve head (ONH) and visual field. Glaucoma can strike without symptoms and causes blindness if it remains without treatment. Therefore, early disease detection is important so that treatment can be initiated and blindness prevented. In this context, important advances in technology for non-invasive imaging of the eye have been made providing quantitative tools to measure structural changes in ONH topography, an essential element for glaucoma detection and monitoring. 3D spectral domain optical coherence tomography (SD-OCT), an optical imaging technique, has been commonly used to discriminate glaucomatous from healthy subjects. In this paper, we present a new framework for detection of glaucoma progression using 3D SD-OCT images. In contrast to previous works that the retinal nerve fiber layer (RNFL) thickness measurement provided by commercially available spectral-domain optical coherence tomograph, we consider the whole 3D volume for change detection. To integrate a priori knowledge and in particular the spatial voxel dependency in the change detection map, we propose the use of the Markov Random Field to handle a such dependency. To accommodate the presence of false positive detection, the estimated change detection map is then used to classify a 3D SDOCT image into the "non-progressing" and "progressing" glaucoma classes, based on a fuzzy logic classifier. We compared the diagnostic performance of the proposed framework to existing methods of progression detection.

Spatially-Aware Temporal Anomaly Mapping of Gamma Spectra

NASA Astrophysics Data System (ADS)

Reinhart, Alex; Athey, Alex; Biegalski, Steven

2014-06-01

For security, environmental, and regulatory purposes it is useful to continuously monitor wide areas for unexpected changes in radioactivity. We report on a temporal anomaly detection algorithm which uses mobile detectors to build a spatial map of background spectra, allowing sensitive detection of any anomalies through many days or months of monitoring. We adapt previously-developed anomaly detection methods, which compare spectral shape rather than count rate, to function with limited background data, allowing sensitive detection of small changes in spectral shape from day to day. To demonstrate this technique we collected daily observations over the period of six weeks on a 0.33 square mile research campus and performed source injection simulations.

Moving human full body and body parts detection, tracking, and applications on human activity estimation, walking pattern and face recognition

NASA Astrophysics Data System (ADS)

Chen, Hai-Wen; McGurr, Mike

2016-05-01

We have developed a new way for detection and tracking of human full-body and body-parts with color (intensity) patch morphological segmentation and adaptive thresholding for security surveillance cameras. An adaptive threshold scheme has been developed for dealing with body size changes, illumination condition changes, and cross camera parameter changes. Tests with the PETS 2009 and 2014 datasets show that we can obtain high probability of detection and low probability of false alarm for full-body. Test results indicate that our human full-body detection method can considerably outperform the current state-of-the-art methods in both detection performance and computational complexity. Furthermore, in this paper, we have developed several methods using color features for detection and tracking of human body-parts (arms, legs, torso, and head, etc.). For example, we have developed a human skin color sub-patch segmentation algorithm by first conducting a RGB to YIQ transformation and then applying a Subtractive I/Q image Fusion with morphological operations. With this method, we can reliably detect and track human skin color related body-parts such as face, neck, arms, and legs. Reliable body-parts (e.g. head) detection allows us to continuously track the individual person even in the case that multiple closely spaced persons are merged. Accordingly, we have developed a new algorithm to split a merged detection blob back to individual detections based on the detected head positions. Detected body-parts also allow us to extract important local constellation features of the body-parts positions and angles related to the full-body. These features are useful for human walking gait pattern recognition and human pose (e.g. standing or falling down) estimation for potential abnormal behavior and accidental event detection, as evidenced with our experimental tests. Furthermore, based on the reliable head (face) tacking, we have applied a super-resolution algorithm to enhance the face resolution for improved human face recognition performance.

Effects of divided attention and operating room noise on perception of pulse oximeter pitch changes: a laboratory study.

PubMed

Stevenson, Ryan A; Schlesinger, Joseph J; Wallace, Mark T

2013-02-01

Anesthesiology requires performing visually oriented procedures while monitoring auditory information about a patient's vital signs. A concern in operating room environments is the amount of competing information and the effects that divided attention has on patient monitoring, such as detecting auditory changes in arterial oxygen saturation via pulse oximetry. The authors measured the impact of visual attentional load and auditory background noise on the ability of anesthesia residents to monitor the pulse oximeter auditory display in a laboratory setting. Accuracies and response times were recorded reflecting anesthesiologists' abilities to detect changes in oxygen saturation across three levels of visual attention in quiet and with noise. Results show that visual attentional load substantially affects the ability to detect changes in oxygen saturation concentrations conveyed by auditory cues signaling 99 and 98% saturation. These effects are compounded by auditory noise, up to a 17% decline in performance. These deficits are seen in the ability to accurately detect a change in oxygen saturation and in speed of response. Most anesthesia accidents are initiated by small errors that cascade into serious events. Lack of monitor vigilance and inattention are two of the more commonly cited factors. Reducing such errors is thus a priority for improving patient safety. Specifically, efforts to reduce distractors and decrease background noise should be considered during induction and emergence, periods of especially high risk, when anesthesiologists has to attend to many tasks and are thus susceptible to error.

[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.

Modeling the Performance of Direct-Detection Doppler Lidar Systems in Real Atmospheres

NASA Technical Reports Server (NTRS)

McGill, Matthew J.; Hart, William D.; McKay, Jack A.; Spinhirne, James D.

1999-01-01

Previous modeling of the performance of spaceborne direct-detection Doppler lidar systems has assumed extremely idealized atmospheric models. Here we develop a technique for modeling the performance of these systems in a more realistic atmosphere, based on actual airborne lidar observations. The resulting atmospheric model contains cloud and aerosol variability that is absent in other simulations of spaceborne Doppler lidar instruments. To produce a realistic simulation of daytime performance, we include solar radiance values that are based on actual measurements and are allowed to vary as the viewing scene changes. Simulations are performed for two types of direct-detection Doppler lidar systems: the double-edge and the multi-channel techniques. Both systems were optimized to measure winds from Rayleigh backscatter at 355 nm. Simulations show that the measurement uncertainty during daytime is degraded by only about 10-20% compared to nighttime performance, provided a proper solar filter is included in the instrument design.

Modeling the performance of direct-detection Doppler lidar systems including cloud and solar background variability.

PubMed

McGill, M J; Hart, W D; McKay, J A; Spinhirne, J D

1999-10-20

Previous modeling of the performance of spaceborne direct-detection Doppler lidar systems assumed extremely idealized atmospheric models. Here we develop a technique for modeling the performance of these systems in a more realistic atmosphere, based on actual airborne lidar observations. The resulting atmospheric model contains cloud and aerosol variability that is absent in other simulations of spaceborne Doppler lidar instruments. To produce a realistic simulation of daytime performance, we include solar radiance values that are based on actual measurements and are allowed to vary as the viewing scene changes. Simulations are performed for two types of direct-detection Doppler lidar system: the double-edge and the multichannel techniques. Both systems were optimized to measure winds from Rayleigh backscatter at 355 nm. Simulations show that the measurement uncertainty during daytime is degraded by only approximately 10-20% compared with nighttime performance, provided that a proper solar filter is included in the instrument design.

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.

Short-term change detection for UAV video

NASA Astrophysics Data System (ADS)

Saur, Günter; Krüger, Wolfgang

2012-11-01

In the last years, there has been an increased use of unmanned aerial vehicles (UAV) for video reconnaissance and surveillance. An important application in this context is change detection in UAV video data. Here we address short-term change detection, in which the time between observations ranges from several minutes to a few hours. We distinguish this task from video motion detection (shorter time scale) and from long-term change detection, based on time series of still images taken between several days, weeks, or even years. Examples for relevant changes we are looking for are recently parked or moved vehicles. As a pre-requisite, a precise image-to-image registration is needed. Images are selected on the basis of the geo-coordinates of the sensor's footprint and with respect to a certain minimal overlap. The automatic imagebased fine-registration adjusts the image pair to a common geometry by using a robust matching approach to handle outliers. The change detection algorithm has to distinguish between relevant and non-relevant changes. Examples for non-relevant changes are stereo disparity at 3D structures of the scene, changed length of shadows, and compression or transmission artifacts. To detect changes in image pairs we analyzed image differencing, local image correlation, and a transformation-based approach (multivariate alteration detection). As input we used color and gradient magnitude images. To cope with local misalignment of image structures we extended the approaches by a local neighborhood search. The algorithms are applied to several examples covering both urban and rural scenes. The local neighborhood search in combination with intensity and gradient magnitude differencing clearly improved the results. Extended image differencing performed better than both the correlation based approach and the multivariate alternation detection. The algorithms are adapted to be used in semi-automatic workflows for the ABUL video exploitation system of Fraunhofer IOSB, see Heinze et. al. 2010.1 In a further step we plan to incorporate more information from the video sequences to the change detection input images, e.g., by image enhancement or by along-track stereo which are available in the ABUL system.

Detecting event-related changes in organizational networks using optimized neural network models.

PubMed

Li, Ze; Sun, Duoyong; Zhu, Renqi; Lin, Zihan

2017-01-01

Organizational external behavior changes are caused by the internal structure and interactions. External behaviors are also known as the behavioral events of an organization. Detecting event-related changes in organizational networks could efficiently be used to monitor the dynamics of organizational behaviors. Although many different methods have been used to detect changes in organizational networks, these methods usually ignore the correlation between the internal structure and external events. Event-related change detection considers the correlation and could be used for event recognition based on social network modeling and supervised classification. Detecting event-related changes could be effectively useful in providing early warnings and faster responses to both positive and negative organizational activities. In this study, event-related change in an organizational network was defined, and artificial neural network models were used to quantitatively determine whether and when a change occurred. To achieve a higher accuracy, Back Propagation Neural Networks (BPNNs) were optimized using Genetic Algorithms (GAs) and Particle Swarm Optimization (PSO). We showed the feasibility of the proposed method by comparing its performance with that of other methods using two cases. The results suggested that the proposed method could identify organizational events based on a correlation between the organizational networks and events. The results also suggested that the proposed method not only has a higher precision but also has a better robustness than the previously used techniques.

Detecting event-related changes in organizational networks using optimized neural network models

PubMed Central

Sun, Duoyong; Zhu, Renqi; Lin, Zihan

2017-01-01

Organizational external behavior changes are caused by the internal structure and interactions. External behaviors are also known as the behavioral events of an organization. Detecting event-related changes in organizational networks could efficiently be used to monitor the dynamics of organizational behaviors. Although many different methods have been used to detect changes in organizational networks, these methods usually ignore the correlation between the internal structure and external events. Event-related change detection considers the correlation and could be used for event recognition based on social network modeling and supervised classification. Detecting event-related changes could be effectively useful in providing early warnings and faster responses to both positive and negative organizational activities. In this study, event-related change in an organizational network was defined, and artificial neural network models were used to quantitatively determine whether and when a change occurred. To achieve a higher accuracy, Back Propagation Neural Networks (BPNNs) were optimized using Genetic Algorithms (GAs) and Particle Swarm Optimization (PSO). We showed the feasibility of the proposed method by comparing its performance with that of other methods using two cases. The results suggested that the proposed method could identify organizational events based on a correlation between the organizational networks and events. The results also suggested that the proposed method not only has a higher precision but also has a better robustness than the previously used techniques. PMID:29190799

Human performance measuring device

NASA Technical Reports Server (NTRS)

Michael, J.; Scow, J.

1970-01-01

Complex coordinator, consisting of operator control console, recorder, subject display panel, and limb controls, measures human performance by testing perceptual and motor skills. Device measures psychophysiological functions in drug and environmental studies, and is applicable to early detection of psychophysiological body changes.

Testing visual short-term memory of pigeons (Columba livia) and a rhesus monkey (Macaca mulatta) with a location change detection task.

PubMed

Leising, Kenneth J; Elmore, L Caitlin; Rivera, Jacquelyne J; Magnotti, John F; Katz, Jeffrey S; Wright, Anthony A

2013-09-01

Change detection is commonly used to assess capacity (number of objects) of human visual short-term memory (VSTM). Comparisons with the performance of non-human animals completing similar tasks have shown similarities and differences in object-based VSTM, which is only one aspect ("what") of memory. Another important aspect of memory, which has received less attention, is spatial short-term memory for "where" an object is in space. In this article, we show for the first time that a monkey and pigeons can be accurately trained to identify location changes, much as humans do, in change detection tasks similar to those used to test object capacity of VSTM. The subject's task was to identify (touch/peck) an item that changed location across a brief delay. Both the monkey and pigeons showed transfer to delays longer than the training delay, to greater and smaller distance changes than in training, and to novel colors. These results are the first to demonstrate location-change detection in any non-human species and encourage comparative investigations into the nature of spatial and visual short-term memory.

Remote Leak Detection: Indirect Thermal Technique

NASA Technical Reports Server (NTRS)

Clements, Sandra

2002-01-01

Remote sensing technologies are being considered for efficient, low cost gas leak detection. Eleven specific techniques have been identified for further study and evaluation of several of these is underway. The Indirect Thermal Technique is one of the techniques that is being explored. For this technique, an infrared camera is used to detect the temperature change of a pipe or fitting at the site of a gas leak. This temperature change is caused by the change in temperature of the gas expanding from the leak site. During the 10-week NFFP program, the theory behind the technique was further developed, experiments were performed to determine the conditions for which the technique might be viable, and a proof-of-concept system was developed and tested in the laboratory.

Cell biomechanics and its applications in human disease diagnosis

NASA Astrophysics Data System (ADS)

Nematbakhsh, Yasaman; Lim, Chwee Teck

2015-04-01

Certain diseases are known to cause changes in the physical and biomechanical properties of cells. These include cancer, malaria, and sickle cell anemia among others. Typically, such physical property changes can result in several fold increases or decreases in cell stiffness, which are significant and can result in severe pathology and eventual catastrophic breakdown of the bodily functions. While there are developed biochemical and biological assays to detect the onset or presence of diseases, there is always a need to develop more rapid, precise, and sensitive methods to detect and diagnose diseases. Biomechanical property changes can play a significant role in this regard. As such, research into disease biomechanics can not only give us an in-depth knowledge of the mechanisms underlying disease progression, but can also serve as a powerful tool for detection and diagnosis. This article provides some insights into opportunities for how significant changes in cellular mechanical properties during onset or progression of a disease can be utilized as useful means for detection and diagnosis. We will also showcase several technologies that have already been developed to perform such detection and diagnosis.

A new method of scoring radiographic change in rheumatoid arthritis.

PubMed

Rau, R; Wassenberg, S; Herborn, G; Stucki, G; Gebler, A

1998-11-01

To test the reliability and to define the minimal detectable change of a new radiographic scoring method in rheumatoid arthritis (RA). Following the recommendations of an expert panel a new radiographic scoring method was defined. It scores 38 joints [all proximal interphalangeal (PIP) and metacarpophalangeal joints, 4 sites in the wrists, IP of the great toes, and metatarsophalangeals 2 to 5], regarding only the amount of joint surface destruction on a 0 to 5 scale for each joint. Each grade represents 20% of joint surface destruction. The method was tested by 5 readers on a set of 7 serial radiographs of hands and forefeet of 20 patients with progressive and destructive RA. Analysis of variance was performed, as it provides the best information about the capability of a method to detect real change and to define its sensitivity according to the minimal detectable change. Analysis of variance proved a high probability that the readers found real change with a ratio of intrapatient to intrareader standard deviation of 2.6. It also confirmed that one reader could detect a change of 3.5% of the total score with a probability of 95% and that different readers agreed upon a change of 4.6%. Inexperienced readers performed with comparable results to experienced readers. The time required for the reading averaged less than 10 minutes for the scoring of one set. The new radiographic scoring method proved to be reliable, precise, and easy to learn, with reasonable cost. Compared to published data, it may provide better results than the widely used Larsen score. These features favor our new method for use in clinical trials and in longterm observational studies in RA.

Evidence Integration in Natural Acoustic Textures during Active and Passive Listening

PubMed Central

Rupp, Andre; Celikel, Tansu

2018-01-01

Abstract Many natural sounds can be well described on a statistical level, for example, wind, rain, or applause. Even though the spectro-temporal profile of these acoustic textures is highly dynamic, changes in their statistics are indicative of relevant changes in the environment. Here, we investigated the neural representation of change detection in natural textures in humans, and specifically addressed whether active task engagement is required for the neural representation of this change in statistics. Subjects listened to natural textures whose spectro-temporal statistics were modified at variable times by a variable amount. Subjects were instructed to either report the detection of changes (active) or to passively listen to the stimuli. A subset of passive subjects had performed the active task before (passive-aware vs passive-naive). Psychophysically, longer exposure to pre-change statistics was correlated with faster reaction times and better discrimination performance. EEG recordings revealed that the build-up rate and size of parieto-occipital (PO) potentials reflected change size and change time. Reduced effects were observed in the passive conditions. While P2 responses were comparable across conditions, slope and height of PO potentials scaled with task involvement. Neural source localization identified a parietal source as the main contributor of change-specific potentials, in addition to more limited contributions from auditory and frontal sources. In summary, the detection of statistical changes in natural acoustic textures is predominantly reflected in parietal locations both on the skull and source level. The scaling in magnitude across different levels of task involvement suggests a context-dependent degree of evidence integration. PMID:29662943

Evidence Integration in Natural Acoustic Textures during Active and Passive Listening.

PubMed

Górska, Urszula; Rupp, Andre; Boubenec, Yves; Celikel, Tansu; Englitz, Bernhard

2018-01-01

Many natural sounds can be well described on a statistical level, for example, wind, rain, or applause. Even though the spectro-temporal profile of these acoustic textures is highly dynamic, changes in their statistics are indicative of relevant changes in the environment. Here, we investigated the neural representation of change detection in natural textures in humans, and specifically addressed whether active task engagement is required for the neural representation of this change in statistics. Subjects listened to natural textures whose spectro-temporal statistics were modified at variable times by a variable amount. Subjects were instructed to either report the detection of changes (active) or to passively listen to the stimuli. A subset of passive subjects had performed the active task before (passive-aware vs passive-naive). Psychophysically, longer exposure to pre-change statistics was correlated with faster reaction times and better discrimination performance. EEG recordings revealed that the build-up rate and size of parieto-occipital (PO) potentials reflected change size and change time. Reduced effects were observed in the passive conditions. While P2 responses were comparable across conditions, slope and height of PO potentials scaled with task involvement. Neural source localization identified a parietal source as the main contributor of change-specific potentials, in addition to more limited contributions from auditory and frontal sources. In summary, the detection of statistical changes in natural acoustic textures is predominantly reflected in parietal locations both on the skull and source level. The scaling in magnitude across different levels of task involvement suggests a context-dependent degree of evidence integration.

Large capacity storage of integrated objects before change blindness.

PubMed

Landman, Rogier; Spekreijse, Henk; Lamme, Victor A F

2003-01-01

Normal people have a strikingly low ability to detect changes in a visual scene. This has been taken as evidence that the brain represents only a few objects at a time, namely those currently in the focus of attention. In the present study, subjects were asked to detect changes in the orientation of rectangular figures in a textured display across a 1600 ms gray interval. In the first experiment, change detection improved when the location of a possible change was cued during the interval. The cue remained effective during the entire interval, but after the interval, it was ineffective, suggesting that an initially large representation was overwritten by the post-change display. To control for an effect of light intensity during the interval on the decay of the representation, we compared performance with a gray or a white interval screen in a second experiment. We found no difference between these conditions. In the third experiment, attention was occasionally misdirected during the interval by first cueing the wrong figure, before cueing the correct figure. This did not compromise performance compared to a single cue, indicating that when an item is attentionally selected, the representation of yet unchosen items remains available. In the fourth experiment, the cue was shown to be effective when changes in figure size and orientation were randomly mixed. At the time the cue appeared, subjects could not know whether size or orientation would change, therefore these results suggest that the representation contains features in their 'bound' state. Together, these findings indicate that change blindness involves overwriting of a large capacity representation by the post-change display.

Detection of small orientation changes and the precision of visual working memory.

PubMed

Salmela, Viljami R; Saarinen, Jussi

2013-01-14

We investigated the precision of orientation representations with two tasks, change detection and recall. Previously change detection has been measured only with relatively large orientation changes compared to psychophysical thresholds. In the first experiment, we measured the observers' ability (d') to detect small changes in orientation (5-30°) with 1-4 Gabor items. With one item even a 10° change was well detected (average d'=2.5). As the amount of change increased to 30°, the d' increased to 5.2. When the number of items was increased, the d's gradually decreased. In the second experiment, we used a recall task and the observers adjusted the orientation of a probe Gabor to match the orientation of a Gabor held in the memory. The standard deviation (s.d.) of errors was calculated from the Gaussian distribution fitted to the data. As the number of items increased from 1 to 6, the s.d. increased from 8.6° to 19.6°. Even with six items, the observers did not make any random adjustments. The results show a square root relation between the d'/s.d. and the number of items. The d' in change detection is directly proportional to the square root of (1/n) and the orientation change. The increase of the s.d. in recall task is inversely proportional to square root of (1/n). The results suggest that limited resources and precision of representations, without additional assumptions, determine the memory performance. Copyright © 2012 Elsevier Ltd. All rights reserved.

A robust multi-kernel change detection framework for detecting leaf beetle defoliation using Landsat 7 ETM+ data

NASA Astrophysics Data System (ADS)

Anees, Asim; Aryal, Jagannath; O'Reilly, Małgorzata M.; Gale, Timothy J.; Wardlaw, Tim

2016-12-01

A robust non-parametric framework, based on multiple Radial Basic Function (RBF) kernels, is proposed in this study, for detecting land/forest cover changes using Landsat 7 ETM+ images. One of the widely used frameworks is to find change vectors (difference image) and use a supervised classifier to differentiate between change and no-change. The Bayesian Classifiers e.g. Maximum Likelihood Classifier (MLC), Naive Bayes (NB), are widely used probabilistic classifiers which assume parametric models, e.g. Gaussian function, for the class conditional distributions. However, their performance can be limited if the data set deviates from the assumed model. The proposed framework exploits the useful properties of Least Squares Probabilistic Classifier (LSPC) formulation i.e. non-parametric and probabilistic nature, to model class posterior probabilities of the difference image using a linear combination of a large number of Gaussian kernels. To this end, a simple technique, based on 10-fold cross-validation is also proposed for tuning model parameters automatically instead of selecting a (possibly) suboptimal combination from pre-specified lists of values. The proposed framework has been tested and compared with Support Vector Machine (SVM) and NB for detection of defoliation, caused by leaf beetles (Paropsisterna spp.) in Eucalyptus nitens and Eucalyptus globulus plantations of two test areas, in Tasmania, Australia, using raw bands and band combination indices of Landsat 7 ETM+. It was observed that due to multi-kernel non-parametric formulation and probabilistic nature, the LSPC outperforms parametric NB with Gaussian assumption in change detection framework, with Overall Accuracy (OA) ranging from 93.6% (κ = 0.87) to 97.4% (κ = 0.94) against 85.3% (κ = 0.69) to 93.4% (κ = 0.85), and is more robust to changing data distributions. Its performance was comparable to SVM, with added advantages of being probabilistic and capable of handling multi-class problems naturally with its original formulation.

Expanding Cancer Detection Using Molecular Imprinting for a Novel Point-of-Care Diagnostic Device

NASA Astrophysics Data System (ADS)

Yu, Yingjie; Rafailovich, Miriam; Wang, Yantian; Kang, Yeona; Zhang, Lingxi; Rigas, Basil; Division of Gastroenterology, School of Medicine Team

2013-03-01

We propose the use of a potentiometric biosensor that incorporates the efficient and specific molecular imprinting (MI) method with a self-assembled monolayer (SAM). We first tested the biosensor using carcinoembryonic antigen, CEA, a biomarker associated with pancreatic cancer. No change in detection efficiency was observed, indicating that the sensor is able to discriminate for the template analyte even in concentrated solution of similar substances. In addition, we use biosensor to discriminate normal fibrinogen and damaged fibrinogen, which is critical for the detection of bleeding disorder. Computer simulations of the protein structure were performed in order to estimate the changes in morphology and determine the sensitivity of the biosensor to conformational changes in the proteins. We found that even small changes in PH can generate rotation of the surface functional groups. Yet, the results show that only when the detection and imprinting conditions are similar, robust signals occurs. Hence we concluded that both morphology and surface chemistry play a role in the recognition.

Sensitivity of photoacoustic microscopy

PubMed Central

Yao, Junjie; Wang, Lihong V.

2014-01-01

Building on its high spatial resolution, deep penetration depth and excellent image contrast, 3D photoacoustic microscopy (PAM) has grown tremendously since its first publication in 2005. Integrating optical excitation and acoustic detection, PAM has broken through both the optical diffusion and optical diffraction limits. PAM has 100% relative sensitivity to optical absorption (i.e., a given percentage change in the optical absorption coefficient yields the same percentage change in the photoacoustic amplitude), and its ultimate detection sensitivity is limited only by thermal noise. Focusing on the engineering aspects of PAM, this Review discusses the detection sensitivity of PAM, compares the detection efficiency of different PAM designs, and summarizes the imaging performance of various endogenous and exogenous contrast agents. It then describes representative PAM applications with high detection sensitivity, and outlines paths to further improvement. PMID:25302158

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.

The Effect of Local Orientation Change on the Detection of Contours Defined by Constant Curvature: Psychophysics and Image Statistics.

PubMed

Khuu, Sieu K; Cham, Joey; Hayes, Anthony

2016-01-01

In the present study, we investigated the detection of contours defined by constant curvature and the statistics of curved contours in natural scenes. In Experiment 1, we examined the degree to which human sensitivity to contours is affected by changing the curvature angle and disrupting contour curvature continuity by varying the orientation of end elements. We find that (1) changing the angle of contour curvature decreased detection performance, while (2) end elements oriented in the direction (i.e., clockwise) of curvature facilitated contour detection regardless of the curvature angle of the contour. In Experiment 2 we further established that the relative effect of end-element orientation on contour detection was not only dependent on their orientation (collinear or cocircular), but also their spatial separation from the contour, and whether the contour shape was curved or not (i.e., C-shaped or S-shaped). Increasing the spatial separation of end-elements reduced contour detection performance regardless of their orientation or the contour shape. However, at small separations, cocircular end-elements facilitated the detection of C-shaped contours, but not S-shaped contours. The opposite result was observed for collinear end-elements, which improved the detection of S- shaped, but not C-shaped contours. These dissociative results confirmed that the visual system specifically codes contour curvature, but the association of contour elements occurs locally. Finally, we undertook an analysis of natural images that mapped contours with a constant angular change and determined the frequency of occurrence of end elements with different orientations. Analogous to our behavioral data, this image analysis revealed that the mapped end elements of constantly curved contours are likely to be oriented clockwise to the angle of curvature. Our findings indicate that the visual system is selectively sensitive to contours defined by constant curvature and that this might reflect the properties of curved contours in natural images.

Pavlovian conditioning enhances resistance to disruption of dogs performing an odor discrimination.

PubMed

Hall, Nathaniel J; Smith, David W; Wynne, Clive D L

2015-05-01

Domestic dogs are used to aid in the detection of a variety of substances such as narcotics and explosives. Under real-world detection situations there are many variables that may disrupt the dog's performance. Prior research on behavioral momentum theory suggests that higher rates of reinforcement produce greater resistance to disruption, and that this is heavily influenced by the stimulus-reinforcer relationship. The present study tests the Pavlovian interpretation of resistance to change using dogs engaged in an odor discrimination task. Dogs were trained on two odor discriminations that alternated every six trials akin to a multiple schedule in which the reinforcement probability for a correct response was always 1. Dogs then received several sessions of either odor Pavlovian conditioning to the S+ of one odor discrimination (Pavlovian group) or explicitly unpaired exposure to the S+ of one odor discrimination (Unpaired group). The remaining odor discrimination pair for each dog always remained an unexposed control. Resistance to disruption was assessed under presession feeding, a food-odor disruptor condition, and extinction, with baseline sessions intervening between disruption conditions. Equivalent baseline detection rates were observed across experimental groups and odorant pairs. Under disruption conditions, Pavlovian conditioning led to enhanced resistance to disruption of detection performance compared to the unexposed control odor discrimination. Unpaired odor conditioning did not influence resistance to disruption. These results suggest that changes in Pavlovian contingencies are sufficient to influence resistance to change. © Society for the Experimental Analysis of Behavior.

Cerebral oxygenation in traumatic brain injury; Can a non-invasive frequency domain near-infrared spectroscopy device detect changes in brain tissue oxygen tension as well as the established invasive monitor?

PubMed

Davies, David James; Clancy, Michael; Dehghani, Hamid; Lucas, Samuel John Edwin; Forcione, Mario; Yakoub, Kamal Makram; Belli, Antonio

2018-06-07

The cost and highly invasive nature of brain monitoring modality in traumatic brain injury patients currently restrict its utility to specialist neurological intensive care settings. We aim to test the abilities of a frequency domain near-infrared spectroscopy (FD-NIRS) device in predicting changes in invasively measured brain tissue oxygen tension. Individuals admitted to a United Kingdom specialist major trauma centre were contemporaneously monitored with an FD-NIRS device and invasively measured brain tissue oxygen tension probe. Area under the curve receiver operating characteristic (AUROC) statistical analysis was utilised to assess the predictive power of FD-NIRS in detecting both moderate and severe hypoxia (20 and 10 mmHg, respectively), as measured invasively. 16 individuals were prospectively recruited to the investigation. Severe hypoxic episodes were detected in 9 of these individuals, with the NIRS demonstrating a broad range of predictive abilities (AUROC 0.68-0.88) from relatively poor to good. Moderate hypoxic episodes were detected in seven individuals with similar predictive performance (AUROC 0.576 - 0.905). A variable performance in the predictive powers of this FD-NIRS device to detect changes in brain tissue oxygen was demonstrated. Consequently, this enhanced NIRS technology has not demonstrated sufficient ability to replace the established invasive measurement.

Sensitivity to change in cognitive performance and mood measures of energy and fatigue in response to morning caffeine alone or in combination with carbohydrate.

PubMed

Maridakis, Victor; O'Connor, Patrick J; Tomporowski, Phillip D

2009-01-01

This double-blind, placebo-controlled, within-subjects (N = 17) experiment compared the sensitivity to change of the cognitive performance and mood measures of mental energy following consumption of either a moderate dose of caffeine (200 mg), a small amount of carbohydrate (50 g white bread), or both. Caffeine improved mood and performance. The sensitivity to change of the mood and cognitive measures did not differ in response to the three treatments (all p values > .05). The mood and cognitive measures of mental energy used here have similar sensitivity to detecting change in response to caffeine and carbohydrate.

Transcranial alternating current stimulation modulates auditory temporal resolution in elderly people.

PubMed

Baltus, Alina; Vosskuhl, Johannes; Boetzel, Cindy; Herrmann, Christoph Siegfried

2018-05-13

Recent research provides evidence for a functional role of brain oscillations for perception. For example, auditory temporal resolution seems to be linked to individual gamma frequency of auditory cortex. Individual gamma frequency not only correlates with performance in between-channel gap detection tasks but can be modulated via auditory transcranial alternating current stimulation. Modulation of individual gamma frequency is accompanied by an improvement in gap detection performance. Aging changes electrophysiological frequency components and sensory processing mechanisms. Therefore, we conducted a study to investigate the link between individual gamma frequency and gap detection performance in elderly people using auditory transcranial alternating current stimulation. In a within-subject design, twelve participants were electrically stimulated with two individualized transcranial alternating current stimulation frequencies: 3 Hz above their individual gamma frequency (experimental condition) and 4 Hz below their individual gamma frequency (control condition) while they were performing a between-channel gap detection task. As expected, individual gamma frequencies correlated significantly with gap detection performance at baseline and in the experimental condition, transcranial alternating current stimulation modulated gap detection performance. In the control condition, stimulation did not modulate gap detection performance. In addition, in elderly, the effect of transcranial alternating current stimulation on auditory temporal resolution seems to be dependent on endogenous frequencies in auditory cortex: elderlies with slower individual gamma frequencies and lower auditory temporal resolution profit from auditory transcranial alternating current stimulation and show increased gap detection performance during stimulation. Our results strongly suggest individualized transcranial alternating current stimulation protocols for successful modulation of performance. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

The Detection and Photometric Redshift Determination of Distant Galaxies using SIRTF's Infrared Array Camera

NASA Technical Reports Server (NTRS)

Simpson, C.; Eisenhardt, P.

1998-01-01

We investigate the ability of the Space Infrared Telescope Facility's Infrared Array Camera to detect distant (z3) galaxies and measure their photometric redshifts. Our analysis shows that changing the original long wavelength filter specifications provides significant improvements in performance in this and other areas.

Precursory Slope Deformation around Landslide Area Detected by Insar Throughout Japan

NASA Astrophysics Data System (ADS)

Nakano, T.; Wada, K.; Yamanaka, M.; Kamiya, I.; Nakajima, H.

2016-06-01

Interferometric Synthetic Aperture Radar (InSAR) technique is able to detect a slope deformation around landslide (e.g., Singhroy et al., 2004; Une et al., 2008; Riedel and Walther, 2008; Sato et al., 2014). Geospatial Information Authority (GSI) of Japan has been performing the InSAR analysis regularly by using ALOS/PALSAR data and ALOS-2/PALSAR-2 data throughout Japan. There are a lot of small phase change sites except for crustal deformation with earthquake or volcano activity in the InSAR imagery. Most of the phase change sites are located in landslide area. We conducted field survey at the 10 sites of those phase change sites. As a result, we identified deformation of artificial structures or linear depressions caused by mass movement at the 9 sites. This result indicates that InSAR technique can detect on the continual deformation of landslide block for several years. GSI of Japan will continue to perform the InSAR analysis throughout Japan. Therefore, we will be able to observe and monitor precursory slope deformation around landslide areas throughout Japan.

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.

Detection of target-probe oligonucleotide hybridization using synthetic nanopore resistive pulse sensing.

PubMed

Booth, Marsilea Adela; Vogel, Robert; Curran, James M; Harbison, SallyAnn; Travas-Sejdic, Jadranka

2013-07-15

Despite the plethora of DNA sensor platforms available, a portable, sensitive, selective and economic sensor able to rival current fluorescence-based techniques would find use in many applications. In this research, probe oligonucleotide-grafted particles are used to detect target DNA in solution through a resistive pulse nanopore detection technique. Using carbodiimide chemistry, functionalized probe DNA strands are attached to carboxylated dextran-based magnetic particles. Subsequent incubation with complementary target DNA yields a change in surface properties as the two DNA strands hybridize. Particle-by-particle analysis with resistive pulse sensing is performed to detect these changes. A variable pressure method allows identification of changes in the surface charge of particles. As proof-of-principle, we demonstrate that target hybridization is selectively detected at micromolar concentrations (nanomoles of target) using resistive pulse sensing, confirmed by fluorescence and phase analysis light scattering as complementary techniques. The advantages, feasibility and limitations of using resistive pulse sensing for sample analysis are discussed. Copyright © 2013 Elsevier B.V. All rights reserved.

Performance analysis and an assessment of operational issues of Ya-21U

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

Paramonov, D.V.; El-Genk, M.S.

1996-03-01

Extensive testing of the Soviet made TOPAZ-II space nuclear power system unit designated {open_quote}{open_quote}Ya-21U{close_quote}{close_quote} was conducted both in the USSR (1989{endash}1990) and in the US (August 1993 to March 1995). The unit underwent a total of 15 tests for a cumulative test/operation time of almost 8000 hours. These tests included steady-state operation at different power levels, fast startups and power optimizations. Leaks were detected in some of the Thermionic Fuel Elements (TFEs) after the first test in the US. These leaks that facilitated air incursion into the interelectrode gap caused operational changes in both electric power and conversion efficiency andmore » changed the optimum cesium pressure and load voltage. Additional changes in operational performance were detected following shock and vibration tests performed in August 1994. Test data was examined and analyzed to assess the performance of not only individual TFEs, and also the whole Ya-21U unit, and identify causes for measured operational performance changes; most probable causes were identified and discussed. The Ya-21U unit remained operational throughout extensive testing for 8000 hours at conditions far exceeding the design limits of the TOPAZ-II system. No single TFE was damaged during testing and measured operational performance changes were uniform among working section TFEs. In addition to providing a unique knowledge base for future development and operation of thermionic power systems, the test results testify to the reliability and ruggedness of the TOPAZ-II system design. {copyright} {ital 1996 American Institute of Physics.}« less

Assessing cognitive dysfunction in Parkinson's disease: An online tool to detect visuo‐perceptual deficits

PubMed Central

Schwarzkopf, Dietrich S.; Bahrami, Bahador; Fleming, Stephen M.; Jackson, Ben M.; Goch, Tristam J. C.; Saygin, Ayse P.; Miller, Luke E.; Pappa, Katerina; Pavisic, Ivanna; Schade, Rachel N.; Noyce, Alastair J.; Crutch, Sebastian J.; O'Keeffe, Aidan G.; Schrag, Anette E.; Morris, Huw R.

2018-01-01

ABSTRACT Background: People with Parkinson's disease (PD) who develop visuo‐perceptual deficits are at higher risk of dementia, but we lack tests that detect subtle visuo‐perceptual deficits and can be performed by untrained personnel. Hallucinations are associated with cognitive impairment and typically involve perception of complex objects. Changes in object perception may therefore be a sensitive marker of visuo‐perceptual deficits in PD. Objective: We developed an online platform to test visuo‐perceptual function. We hypothesised that (1) visuo‐perceptual deficits in PD could be detected using online tests, (2) object perception would be preferentially affected, and (3) these deficits would be caused by changes in perception rather than response bias. Methods: We assessed 91 people with PD and 275 controls. Performance was compared using classical frequentist statistics. We then fitted a hierarchical Bayesian signal detection theory model to a subset of tasks. Results: People with PD were worse than controls at object recognition, showing no deficits in other visuo‐perceptual tests. Specifically, they were worse at identifying skewed images (P < .0001); at detecting hidden objects (P = .0039); at identifying objects in peripheral vision (P < .0001); and at detecting biological motion (P = .0065). In contrast, people with PD were not worse at mental rotation or subjective size perception. Using signal detection modelling, we found this effect was driven by change in perceptual sensitivity rather than response bias. Conclusions: Online tests can detect visuo‐perceptual deficits in people with PD, with object recognition particularly affected. Ultimately, visuo‐perceptual tests may be developed to identify at‐risk patients for clinical trials to slow PD dementia. © 2018 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society. PMID:29473691

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.

Assessment and improvement of statistical tools for comparative proteomics analysis of sparse data sets with few experimental replicates.

PubMed

Schwämmle, Veit; León, Ileana Rodríguez; Jensen, Ole Nørregaard

2013-09-06

Large-scale quantitative analyses of biological systems are often performed with few replicate experiments, leading to multiple nonidentical data sets due to missing values. For example, mass spectrometry driven proteomics experiments are frequently performed with few biological or technical replicates due to sample-scarcity or due to duty-cycle or sensitivity constraints, or limited capacity of the available instrumentation, leading to incomplete results where detection of significant feature changes becomes a challenge. This problem is further exacerbated for the detection of significant changes on the peptide level, for example, in phospho-proteomics experiments. In order to assess the extent of this problem and the implications for large-scale proteome analysis, we investigated and optimized the performance of three statistical approaches by using simulated and experimental data sets with varying numbers of missing values. We applied three tools, including standard t test, moderated t test, also known as limma, and rank products for the detection of significantly changing features in simulated and experimental proteomics data sets with missing values. The rank product method was improved to work with data sets containing missing values. Extensive analysis of simulated and experimental data sets revealed that the performance of the statistical analysis tools depended on simple properties of the data sets. High-confidence results were obtained by using the limma and rank products methods for analyses of triplicate data sets that exhibited more than 1000 features and more than 50% missing values. The maximum number of differentially represented features was identified by using limma and rank products methods in a complementary manner. We therefore recommend combined usage of these methods as a novel and optimal way to detect significantly changing features in these data sets. This approach is suitable for large quantitative data sets from stable isotope labeling and mass spectrometry experiments and should be applicable to large data sets of any type. An R script that implements the improved rank products algorithm and the combined analysis is available.

Early Detection of Physical Activity for People With Type 1 Diabetes Mellitus.

PubMed

Dasanayake, Isuru S; Bevier, Wendy C; Castorino, Kristin; Pinsker, Jordan E; Seborg, Dale E; Doyle, Francis J; Dassau, Eyal

2015-06-30

Early detection of exercise in individuals with type 1 diabetes mellitus (T1DM) may allow changes in therapy to prevent hypoglycemia. Currently there is limited experience with automated methods that detect the onset and end of exercise in this population. We sought to develop a novel method to quickly and reliably detect the onset and end of exercise in these individuals before significant changes in blood glucose (BG) occur. Sixteen adults with T1DM were studied as outpatients using a diary, accelerometer, heart rate monitor, and continuous glucose monitor for 2 days. These data were used to develop a principal component analysis based exercise detection method. Subjects also performed 60 and 30 minute exercise sessions at 30% and 50% predicted heart rate reserve (HRR), respectively. The detection method was applied to the exercise sessions to determine how quickly the detection of start and end of exercise occurred relative to change in BG. Mild 30% HRR and moderate 50% HRR exercise onset was identified in 6 ± 3 and 5 ± 2 (mean ± SD) minutes, while completion was detected in 3 ± 8 and 6 ± 5 minutes, respectively. BG change from start of exercise to detection time was 1 ± 6 and -1 ± 3 mg/dL, and, from the end of exercise to detection time was 6 ± 4 and -17 ± 13 mg/dL, respectively, for the 2 exercise sessions. False positive and negative ratios were 4 ± 2% and 21 ± 22%. The novel method for exercise detection identified the onset and end of exercise in approximately 5 minutes, with an average BG change of only -6 mg/dL. © 2015 Diabetes Technology Society.

Video change detection for fixed wing UAVs

NASA Astrophysics Data System (ADS)

Bartelsen, Jan; Müller, Thomas; Ring, Jochen; Mück, Klaus; Brüstle, Stefan; Erdnüß, Bastian; Lutz, Bastian; Herbst, Theresa

2017-10-01

In this paper we proceed the work of Bartelsen et al.1 We present the draft of a process chain for an image based change detection which is designed for videos acquired by fixed wing unmanned aerial vehicles (UAVs). From our point of view, automatic video change detection for aerial images can be useful to recognize functional activities which are typically caused by the deployment of improvised explosive devices (IEDs), e.g. excavations, skid marks, footprints, left-behind tooling equipment, and marker stones. Furthermore, in case of natural disasters, like flooding, imminent danger can be recognized quickly. Due to the necessary flight range, we concentrate on fixed wing UAVs. Automatic change detection can be reduced to a comparatively simple photogrammetric problem when the perspective change between the "before" and "after" image sets is kept as small as possible. Therefore, the aerial image acquisition demands a mission planning with a clear purpose including flight path and sensor configuration. While the latter can be enabled simply by a fixed and meaningful adjustment of the camera, ensuring a small perspective change for "before" and "after" videos acquired by fixed wing UAVs is a challenging problem. Concerning this matter, we have performed tests with an advanced commercial off the shelf (COTS) system which comprises a differential GPS and autopilot system estimating the repetition accuracy of its trajectory. Although several similar approaches have been presented,23 as far as we are able to judge, the limits for this important issue are not estimated so far. Furthermore, we design a process chain to enable the practical utilization of video change detection. It consists of a front-end of a database to handle large amounts of video data, an image processing and change detection implementation, and the visualization of the results. We apply our process chain on the real video data acquired by the advanced COTS fixed wing UAV and synthetic data. For the image processing and change detection, we use the approach of Muller.4 Although it was developed for unmanned ground vehicles (UGVs), it enables a near real time video change detection for aerial videos. Concluding, we discuss the demands on sensor systems in the matter of change detection.

Adaptive Automation for Human Supervision of Multiple Uninhabited Vehicles: Effects on Change Detection, Situation Awareness, and Mental Workload

DTIC Science & Technology

2009-01-01

transient was present. BASELINE EXPERIMENT Methods Participants Sixteen young adults (9 women , 7 men ) aged 18–26 years (mean = 20.5) partic- ipated...Sixteen young adults (8 women , 8 men ) aged 18–28 years (mean = 21.9) partici- pated. The experiment lasted approximately 2 hours and participants were...based on the operator’s change detection performance. Mis- sion scenarios involved supervision of multiple UVs and required multitasking . Effects of

In situ detection of porosity initiation during aluminum thin film anodizing

NASA Astrophysics Data System (ADS)

Van Overmeere, Quentin; Nysten, Bernard; Proost, Joris

2009-02-01

High-resolution curvature measurements have been performed in situ during aluminum thin film anodizing in sulfuric acid. A well-defined transition in the rate of internal stress-induced curvature change is shown to allow for the accurate, real-time detection of porosity initiation. The validity of this in situ diagnostic tool was confirmed by a quantitative analysis of the spectral density distributions of the anodized surfaces. These were obtained by analyzing ex situ atomic force microscopy images of surfaces anodized for different times, and allowed to correlate the in situ detected transition in the rate of curvature change with the appearance of porosity.

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

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.

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.

The Critical Power Model as a Potential Tool for Anti-doping

PubMed Central

Puchowicz, Michael J.; Mizelman, Eliran; Yogev, Assaf; Koehle, Michael S.; Townsend, Nathan E.; Clarke, David C.

2018-01-01

Existing doping detection strategies rely on direct and indirect biochemical measurement methods focused on detecting banned substances, their metabolites, or biomarkers related to their use. However, the goal of doping is to improve performance, and yet evidence from performance data is not considered by these strategies. The emergence of portable sensors for measuring exercise intensities and of player tracking technologies may enable the widespread collection of performance data. How these data should be used for doping detection is an open question. Herein, we review the basis by which performance models could be used for doping detection, followed by critically reviewing the potential of the critical power (CP) model as a prototypical performance model that could be used in this regard. Performance models are mathematical representations of performance data specific to the athlete. Some models feature parameters with physiological interpretations, changes to which may provide clues regarding the specific doping method. The CP model is a simple model of the power-duration curve and features two physiologically interpretable parameters, CP and W′. We argue that the CP model could be useful for doping detection mainly based on the predictable sensitivities of its parameters to ergogenic aids and other performance-enhancing interventions. However, our argument is counterbalanced by the existence of important limitations and unresolved questions that need to be addressed before the model is used for doping detection. We conclude by providing a simple worked example showing how it could be used and propose recommendations for its implementation. PMID:29928234

Dissociable loss of the representations in visual short-term memory.

PubMed

Li, Jie

2016-01-01

The present study investigated in what manner the information in visual short-term memory (VSTM) is lost. Participants memorized four items, one of which was given higher priority later by a retro-cue. Then participants were required to detect a possible change, which could be either a large or small change, occurred to one of the items. The results showed that the detection performance for the small change of the uncued items was poorer than the cued item, yet large change that occurred to all four memory items could be detected perfectly, indicating that the uncued representations lost some detailed information yet still had some basic features retained in VSTM. The present study suggests that after being encoded into VSTM, the information is not lost in an object-based manner; rather, features of an item are still dissociable, so that they can be lost separately.

Method and apparatus for inspecting reflection masks for defects

DOEpatents

Bokor, Jeffrey; Lin, Yun

2003-04-29

An at-wavelength system for extreme ultraviolet lithography mask blank defect detection is provided. When a focused beam of wavelength 13 nm is incident on a defective region of a mask blank, three possible phenomena can occur. The defect will induce an intensity reduction in the specularly reflected beam, scatter incoming photons into an off-specular direction, and change the amplitude and phase of the electric field at the surface which can be monitored through the change in the photoemission current. The magnitude of these changes will depend on the incident beam size, and the nature, extent and size of the defect. Inspection of the mask blank is performed by scanning the mask blank with 13 nm light focused to a spot a few .mu.m in diameter, while measuring the reflected beam intensity (bright field detection), the scattered beam intensity (dark-field detection) and/or the change in the photoemission current.

The importance of aerodynamics for prosthetic limb design used by competitive cyclists with an amputation: An introduction.

PubMed

Dyer, Bryce

2015-06-01

This study introduces the importance of the aerodynamics to prosthetic limb design for athletes with either a lower-limb or upper-limb amputation. The study comprises two elements: 1) An initial experiment investigating the stability of outdoor velodrome-based field tests, and 2) An experiment evaluating the application of outdoor velodrome aerodynamic field tests to detect small-scale changes in aerodynamic drag respective of prosthetic limb componentry changes. An outdoor field-testing method is used to detect small and repeatable changes in the aerodynamic drag of an able-bodied cyclist. These changes were made at levels typical of alterations in prosthetic componentry. The field-based test method of assessment is used at a smaller level of resolution than previously reported. With a carefully applied protocol, the field test method proved to be statistically stable. The results of the field test experiments demonstrate a noticeable change in overall athlete performance. Aerodynamic refinement of artificial limbs is worthwhile for athletes looking to maximise their competitive performance. A field-testing method illustrates the importance of the aerodynamic optimisation of prosthetic limb components. The field-testing protocol undertaken in this study gives an accessible and affordable means of doing so by prosthetists and sports engineers. Using simple and accessible field-testing methods, this exploratory experiment demonstrates how small changes to riders' equipment, consummate of the scale of a small change in prosthetics componentry, can affect the performance of an athlete. Prosthetists should consider such opportunities for performance enhancement when possible. © The International Society for Prosthetics and Orthotics 2014.

Can spectro-temporal complexity explain the autistic pattern of performance on auditory tasks?

PubMed

Samson, Fabienne; Mottron, Laurent; Jemel, Boutheina; Belin, Pascal; Ciocca, Valter

2006-01-01

To test the hypothesis that level of neural complexity explain the relative level of performance and brain activity in autistic individuals, available behavioural, ERP and imaging findings related to the perception of increasingly complex auditory material under various processing tasks in autism were reviewed. Tasks involving simple material (pure tones) and/or low-level operations (detection, labelling, chord disembedding, detection of pitch changes) show a superior level of performance and shorter ERP latencies. In contrast, tasks involving spectrally- and temporally-dynamic material and/or complex operations (evaluation, attention) are poorly performed by autistics, or generate inferior ERP activity or brain activation. Neural complexity required to perform auditory tasks may therefore explain pattern of performance and activation of autistic individuals during auditory tasks.

A Framework for Detecting Glaucomatous Progression in the Optic Nerve Head of an Eye using Proper Orthogonal Decomposition

PubMed Central

Balasubramanian, Madhusudhanan; Žabić, Stanislav; Bowd, Christopher; Thompson, Hilary W.; Wolenski, Peter; Iyengar, S. Sitharama; Karki, Bijaya B.; Zangwill, Linda M.

2009-01-01

Glaucoma is the second leading cause of blindness worldwide. Often the optic nerve head (ONH) glaucomatous damage and ONH changes occur prior to visual field loss and are observable in vivo. Thus, digital image analysis is a promising choice for detecting the onset and/or progression of glaucoma. In this work, we present a new framework for detecting glaucomatous changes in the ONH of an eye using the method of proper orthogonal decomposition (POD). A baseline topograph subspace was constructed for each eye to describe the structure of the ONH of the eye at a reference/baseline condition using POD. Any glaucomatous changes in the ONH of the eye present during a follow-up exam were estimated by comparing the follow-up ONH topography with its baseline topograph subspace representation. Image correspondence measures of L1 and L2 norms, correlation, and image Euclidean distance (IMED) were used to quantify the ONH changes. An ONH topographic library built from the Louisiana State University Experimental Glaucoma study was used to evaluate the performance of the proposed method. The area under the receiver operating characteristic curves (AUC) were used to compare the diagnostic performance of the POD induced parameters with the parameters of Topographic Change Analysis (TCA) method. The IMED and L2 norm parameters in the POD framework provided the highest AUC of 0.94 at 10° field of imaging and 0.91 at 15° field of imaging compared to the TCA parameters with an AUC of 0.86 and 0.88 respectively. The proposed POD framework captures the instrument measurement variability and inherent structure variability and shows promise for improving our ability to detect glaucomatous change over time in glaucoma management. PMID:19369163

Effects of Stereoscopic Depth on Vigilance Performance and Cerebral Hemodynamics.

PubMed

Greenlee, Eric T; Funke, Gregory J; Warm, Joel S; Finomore, Victor S; Patterson, Robert E; Barnes, Laura E; Funke, Matthew E; Vidulich, Michael A

2015-09-01

We tested the possibility that monitoring a display wherein critical signals for detection were defined by a stereoscopic three-dimensional (3-D) image might be more resistant to the vigilance decrement, and to temporal declines in cerebral blood flow velocity (CBFV), than monitoring a display featuring a customary two-dimensional (2-D) image. Hancock has asserted that vigilance studies typically employ stimuli for detection that do not exemplify those that occur in the natural world. As a result, human performance is suboptimal. From this perspective, tasks that better approximate perception in natural environments should enhance performance efficiency. To test that possibility, we made use of stereopsis, an important means by which observers interact with their everyday surroundings. Observers monitored a circular display in which a vertical line was embedded. Critical signals for detection in a 2-D condition were instances in which the line was rotated clockwise from vertical. In a 3-D condition, critical signals were cases in which the line appeared to move outward toward the observer. The overall level of signal detection and the stability of detection over time were greater when observers monitored for 3-D changes in target depth compared to 2-D changes in target orientation. However, the 3-D display did not retard the temporal decline in CBFV. These results provide the initial demonstration that 3-D displays can enhance performance in vigilance tasks. The use of 3-D displays may be productive in augmenting system reliability when operator vigilance is vital. © 2015, Human Factors and Ergonomics Society.

An evidence accumulation model for conflict detection performance in a simulated air traffic control task.

PubMed

Neal, Andrew; Kwantes, Peter J

2009-04-01

The aim of this article is to develop a formal model of conflict detection performance. Our model assumes that participants iteratively sample evidence regarding the state of the world and accumulate it over time. A decision is made when the evidence reaches a threshold that changes over time in response to the increasing urgency of the task. Two experiments were conducted to examine the effects of conflict geometry and timing on response proportions and response time. The model is able to predict the observed pattern of response times, including a nonmonotonic relationship between distance at point of closest approach and response time, as well as effects of angle of approach and relative velocity. The results demonstrate that evidence accumulation models provide a good account of performance on a conflict detection task. Evidence accumulation models are a form of dynamic signal detection theory, allowing for the analysis of response times as well as response proportions, and can be used for simulating human performance on dynamic decision tasks.

Phenobarbital reduces EEG amplitude and propagation of neonatal seizures but does not alter performance of automated seizure detection.

PubMed

Mathieson, Sean R; Livingstone, Vicki; Low, Evonne; Pressler, Ronit; Rennie, Janet M; Boylan, Geraldine B

2016-10-01

Phenobarbital increases electroclinical uncoupling and our preliminary observations suggest it may also affect electrographic seizure morphology. This may alter the performance of a novel seizure detection algorithm (SDA) developed by our group. The objectives of this study were to compare the morphology of seizures before and after phenobarbital administration in neonates and to determine the effect of any changes on automated seizure detection rates. The EEGs of 18 term neonates with seizures both pre- and post-phenobarbital (524 seizures) administration were studied. Ten features of seizures were manually quantified and summary measures for each neonate were statistically compared between pre- and post-phenobarbital seizures. SDA seizure detection rates were also compared. Post-phenobarbital seizures showed significantly lower amplitude (p<0.001) and involved fewer EEG channels at the peak of seizure (p<0.05). No other features or SDA detection rates showed a statistical difference. These findings show that phenobarbital reduces both the amplitude and propagation of seizures which may help to explain electroclinical uncoupling of seizures. The seizure detection rate of the algorithm was unaffected by these changes. The results suggest that users should not need to adjust the SDA sensitivity threshold after phenobarbital administration. Copyright © 2016 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

CNV-TV: a robust method to discover copy number variation from short sequencing reads.

PubMed

Duan, Junbo; Zhang, Ji-Gang; Deng, Hong-Wen; Wang, Yu-Ping

2013-05-02

Copy number variation (CNV) is an important structural variation (SV) in human genome. Various studies have shown that CNVs are associated with complex diseases. Traditional CNV detection methods such as fluorescence in situ hybridization (FISH) and array comparative genomic hybridization (aCGH) suffer from low resolution. The next generation sequencing (NGS) technique promises a higher resolution detection of CNVs and several methods were recently proposed for realizing such a promise. However, the performances of these methods are not robust under some conditions, e.g., some of them may fail to detect CNVs of short sizes. There has been a strong demand for reliable detection of CNVs from high resolution NGS data. A novel and robust method to detect CNV from short sequencing reads is proposed in this study. The detection of CNV is modeled as a change-point detection from the read depth (RD) signal derived from the NGS, which is fitted with a total variation (TV) penalized least squares model. The performance (e.g., sensitivity and specificity) of the proposed approach are evaluated by comparison with several recently published methods on both simulated and real data from the 1000 Genomes Project. The experimental results showed that both the true positive rate and false positive rate of the proposed detection method do not change significantly for CNVs with different copy numbers and lengthes, when compared with several existing methods. Therefore, our proposed approach results in a more reliable detection of CNVs than the existing methods.

Magnetic resonance imaging is more sensitive than radiographs in detecting change in size of erosions in rheumatoid arthritis.

PubMed

Chen, Timothy S; Crues, John V; Ali, Muhammad; Troum, Orrin M

2006-10-01

To evaluate the technological performance of magnetic resonance imaging (MRI) with respect to projection radiography by determining the incidence of changes in the size of individual bone lesions in inflammatory arthritis, using serial high-resolution in-office MRI over short time intervals (8 months average followup), and by comparing the sensitivity of 3-view projection radiography with in-office MRI for detecting changes in size and number of individual erosions. MR examinations of the wrists and second and third metacarpophalangeal joints were performed using a portable in-office MR system in a total of 405 patients with inflammatory arthritis, from one rheumatologist's practice, who were undergoing aggressive disease modifying antirheumatic drug therapy. Of the patients, 156 were imaged at least twice, allowing evaluation of 246 followup examinations (mean followup interval of 8 months over a 2-year period). Baseline and followup plain radiographs were obtained in 165 patient intervals. Patients refused radiographic examination on 81 followup visits. MRI demonstrated no detectable changes in 124 of the 246 (50%) followup MRI examinations. An increase in the size or number of erosions was demonstrated in 74 (30%) examinations, a decrease in the size or number of erosions in 36 (15%), and both increases and decreases in erosions were seen in 11 (4%). In the 165 studies with followup radiographic comparisons, only one examination (0.8%) showed an erosion not seen on the prior examination and one (0.8%) showed an increase in a previously noted erosion. We showed that high-resolution in-office MRI with an average followup of 8 months detects changes in bony disease in 50% of compliant patients during aggressive treatment for inflammatory arthritis in a single rheumatologist's office practice. Plain radiography is insensitive for detecting changes in bone erosions for this patient population in this time frame.

Object-based change detection: dimension of damage in residential areas of Abu Suruj, Sudan

NASA Astrophysics Data System (ADS)

Demharter, Timo; Michel, Ulrich; Ehlers, Manfred; Reinartz, Peter

2011-11-01

Given the importance of Change Detection, especially in the field of crisis management, this paper discusses the advantage of object-based Change Detection. This project and the used methods give an opportunity to coordinate relief actions strategically. The principal objective of this project was to develop an algorithm which allows to detect rapidly damaged and destroyed buildings in the area of Abu Suruj. This Sudanese village is located in West-Darfur and has become the victim of civil war. The software eCognition Developer was used to per-form an object-based Change Detection on two panchromatic Quickbird 2 images from two different time slots. The first image shows the area before, the second image shows the area after the massacres in this region. Seeking a classification for the huts of the Sudanese town Abu Suruj was reached by first segmenting the huts and then classifying them on the basis of geo-metrical and brightness-related values. The huts were classified as "new", "destroyed" and "preserved" with the help of a automated algorithm. Finally the results were presented in the form of a map which displays the different conditions of the huts. The accuracy of the project is validated by an accuracy assessment resulting in an Overall Classification Accuracy of 90.50 percent. These change detection results allow aid organizations to provide quick and efficient help where it is needed the most.

Boosting instance prototypes to detect local dermoscopic features.

PubMed

Situ, Ning; Yuan, Xiaojing; Zouridakis, George

2010-01-01

Local dermoscopic features are useful in many dermoscopic criteria for skin cancer detection. We address the problem of detecting local dermoscopic features from epiluminescence (ELM) microscopy skin lesion images. We formulate the recognition of local dermoscopic features as a multi-instance learning (MIL) problem. We employ the method of diverse density (DD) and evidence confidence (EC) function to convert MIL to a single-instance learning (SIL) problem. We apply Adaboost to improve the classification performance with support vector machines (SVMs) as the base classifier. We also propose to boost the selection of instance prototypes through changing the data weights in the DD function. We validate the methods on detecting ten local dermoscopic features from a dataset with 360 images. We compare the performance of the MIL approach, its boosting version, and a baseline method without using MIL. Our results show that boosting can provide performance improvement compared to the other two methods.

CMOS capacitive biosensors for highly sensitive biosensing applications.

PubMed

Chang, An-Yu; Lu, Michael S-C

2013-01-01

Magnetic microbeads are widely used in biotechnology and biomedical research for manipulation and detection of cells and biomolecules. Most lab-on-chip systems capable of performing manipulation and detection require external instruments to perform one of the functions, leading to increased size and cost. This work aims at developing an integrated platform to perform these two functions by implementing electromagnetic microcoils and capacitive biosensors on a CMOS (complementary metal oxide semiconductor) chip. Compared to most magnetic-type sensors, our detection method requires no externally applied magnetic fields and the associated fabrication is less complicated. In our experiment, microbeads coated with streptavidin were driven to the sensors located in the center of microcoils with functionalized anti-streptavidin antibody. Detection of a single microbead was successfully demonstrated using a capacitance-to-frequency readout. The average capacitance changes for the experimental and control groups were -5.3 fF and -0.2 fF, respectively.

CRF-Based Model for Instrument Detection and Pose Estimation in Retinal Microsurgery.

PubMed

Alsheakhali, Mohamed; Eslami, Abouzar; Roodaki, Hessam; Navab, Nassir

2016-01-01

Detection of instrument tip in retinal microsurgery videos is extremely challenging due to rapid motion, illumination changes, the cluttered background, and the deformable shape of the instrument. For the same reason, frequent failures in tracking add the overhead of reinitialization of the tracking. In this work, a new method is proposed to localize not only the instrument center point but also its tips and orientation without the need of manual reinitialization. Our approach models the instrument as a Conditional Random Field (CRF) where each part of the instrument is detected separately. The relations between these parts are modeled to capture the translation, rotation, and the scale changes of the instrument. The tracking is done via separate detection of instrument parts and evaluation of confidence via the modeled dependence functions. In case of low confidence feedback an automatic recovery process is performed. The algorithm is evaluated on in vivo ophthalmic surgery datasets and its performance is comparable to the state-of-the-art methods with the advantage that no manual reinitialization is needed.

THE SCREENING AND RANKING ALGORITHM FOR CHANGE-POINTS DETECTION IN MULTIPLE SAMPLES

PubMed Central

Song, Chi; Min, Xiaoyi; Zhang, Heping

2016-01-01

The chromosome copy number variation (CNV) is the deviation of genomic regions from their normal copy number states, which may associate with many human diseases. Current genetic studies usually collect hundreds to thousands of samples to study the association between CNV and diseases. CNVs can be called by detecting the change-points in mean for sequences of array-based intensity measurements. Although multiple samples are of interest, the majority of the available CNV calling methods are single sample based. Only a few multiple sample methods have been proposed using scan statistics that are computationally intensive and designed toward either common or rare change-points detection. In this paper, we propose a novel multiple sample method by adaptively combining the scan statistic of the screening and ranking algorithm (SaRa), which is computationally efficient and is able to detect both common and rare change-points. We prove that asymptotically this method can find the true change-points with almost certainty and show in theory that multiple sample methods are superior to single sample methods when shared change-points are of interest. Additionally, we report extensive simulation studies to examine the performance of our proposed method. Finally, using our proposed method as well as two competing approaches, we attempt to detect CNVs in the data from the Primary Open-Angle Glaucoma Genes and Environment study, and conclude that our method is faster and requires less information while our ability to detect the CNVs is comparable or better. PMID:28090239

Self-checking self-repairing computer nodes using the mirror processor

NASA Technical Reports Server (NTRS)

Tamir, Yuval

1992-01-01

Circuitry added to fault-tolerant systems for concurrent error deduction usually reduces performance. Using a technique called micro rollback, it is possible to eliminate most of the performance penalty of concurrent error detection. Error detection is performed in parallel with intermodule communication, and erroneous state changes are later undone. The author reports on the design and implementation of a VLSI RISC microprocessor, called the Mirror Processor (MP), which is capable of micro rollback. In order to achieve concurrent error detection, two MP chips operate in lockstep, comparing external signals and a signature of internal signals every clock cycle. If a mismatch is detected, both processors roll back to the beginning of the cycle when the error occurred. In some cases the erroneous state is corrected by copying a value from the fault-free processor to the faulty processor. The architecture, microarchitecture, and VLSI implementation of the MP, emphasizing its error-detection, error-recovery, and self-diagnosis capabilities, are described.

Longitudinal Change Detected by Spectral Domain Optical Coherence Tomography in the Optic Nerve Head and Peripapillary Retina in Experimental Glaucoma

PubMed Central

Strouthidis, Nicholas G.; Fortune, Brad; Yang, Hongli; Sigal, Ian A.

2011-01-01

Purpose. To investigate whether longitudinal changes deep within the optic nerve head (ONH) are detectable by spectral domain optical coherence tomography (SDOCT) in experimental glaucoma (EG) and whether these changes are detectable at the onset of Heidelberg Retina Tomography (HRT; Heidelberg Engineering, Heidelberg, Germany)–defined surface topography depression. Methods. Longitudinal SDOCT imaging (Spectralis; Heidelberg Engineering) was performed in both eyes of nine rhesus macaques every 1 to 3 weeks. One eye of each underwent trabecular laser-induced IOP elevation. Four masked operators delineated internal limiting membrane (ILM), retinal nerve fiber layer (RNFL), Bruch's membrane/retinal pigment epithelium (BM/RPE), neural canal opening (NCO), and anterior lamina cribrosa surface (ALCS) by using custom software. Longitudinal changes were assessed and compared between the EG and control (nonlasered) eyes at the onset of HRT-detected surface depression (follow-up 1; [FU1]) and at the most recent image (follow-up 2; [FU2]). Results. Mean IOP in EG eyes was 7.1 to 24.6 mm Hg at FU1 and 13.5 to 31.9 mm Hg at FU2. In control eyes, the mean IOP was 7.2 to 12.6 mm Hg (FU1) and 8.9 to 16.0 mm Hg (FU2). At FU1, neuroretinal rim decreased and ALCS depth increased significantly (paired t-test, P < 0.01); no change in RNFL thickness was detected. At FU2, however, significant prelaminar tissue thinning, posterior displacement of NCO, and RNFL thinning were observed. Conclusions. Longitudinal SDOCT imaging can detect deep ONH changes in EG eyes, the earliest of which are present at the onset of HRT-detected ONH surface height depression. These parameters represent realistic targets for SDOCT detection of glaucomatous progression in human subjects. PMID:21217108

Rapid systematic assessment of the detection and attribution of regional anthropogenic climate change

NASA Astrophysics Data System (ADS)

Stone, Dáithí A.; Hansen, Gerrit

2016-09-01

Despite being a well-established research field, the detection and attribution of observed climate change to anthropogenic forcing is not yet provided as a climate service. One reason for this is the lack of a methodology for performing tailored detection and attribution assessments on a rapid time scale. Here we develop such an approach, based on the translation of quantitative analysis into the "confidence" language employed in recent Assessment Reports of the Intergovernmental Panel on Climate Change. While its systematic nature necessarily ignores some nuances examined in detailed expert assessments, the approach nevertheless goes beyond most detection and attribution studies in considering contributors to building confidence such as errors in observational data products arising from sparse monitoring networks. When compared against recent expert assessments, the results of this approach closely match those of the existing assessments. Where there are small discrepancies, these variously reflect ambiguities in the details of what is being assessed, reveal nuances or limitations of the expert assessments, or indicate limitations of the accuracy of the sort of systematic approach employed here. Deployment of the method on 116 regional assessments of recent temperature and precipitation changes indicates that existing rules of thumb concerning the detectability of climate change ignore the full range of sources of uncertainty, most particularly the importance of adequate observational monitoring.

Statistical power to detect change in a mangrove shoreline fish community adjacent to a nuclear power plant.

PubMed

Dolan, T E; Lynch, P D; Karazsia, J L; Serafy, J E

2016-03-01

An expansion is underway of a nuclear power plant on the shoreline of Biscayne Bay, Florida, USA. While the precise effects of its construction and operation are unknown, impacts on surrounding marine habitats and biota are considered by experts to be likely. The objective of the present study was to determine the adequacy of an ongoing monitoring survey of fish communities associated with mangrove habitats directly adjacent to the power plant to detect fish community changes, should they occur, at three spatial scales. Using seasonally resolved data recorded during 532 fish surveys over an 8-year period, power analyses were performed for four mangrove fish metrics (fish diversity, fish density, and the occurrence of two ecologically important fish species: gray snapper (Lutjanus griseus) and goldspotted killifish (Floridichthys carpio). Results indicated that the monitoring program at current sampling intensity allows for detection of <33% changes in fish density and diversity metrics in both the wet and the dry season in the two larger study areas. Sampling effort was found to be insufficient in either season to detect changes at this level (<33%) in species-specific occurrence metrics for the two fish species examined. The option of supplementing ongoing, biological monitoring programs for improved, focused change detection deserves consideration from both ecological and cost-benefit perspectives.

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.

Reliability, standard error, and minimum detectable change of clinical pressure pain threshold testing in people with and without acute neck pain.

PubMed

Walton, David M; Macdermid, Joy C; Nielson, Warren; Teasell, Robert W; Chiasson, Marco; Brown, Lauren

2011-09-01

Clinical measurement. To evaluate the intrarater, interrater, and test-retest reliability of an accessible digital algometer, and to determine the minimum detectable change in normal healthy individuals and a clinical population with neck pain. Pressure pain threshold testing may be a valuable assessment and prognostic indicator for people with neck pain. To date, most of this research has been completed using algometers that are too resource intensive for routine clinical use. Novice raters (physiotherapy students or clinical physiotherapists) were trained to perform algometry testing over 2 clinically relevant sites: the angle of the upper trapezius and the belly of the tibialis anterior. A convenience sample of normal healthy individuals and a clinical sample of people with neck pain were tested by 2 different raters (all participants) and on 2 different days (healthy participants only). Intraclass correlation coefficient (ICC), standard error of measurement, and minimum detectable change were calculated. A total of 60 healthy volunteers and 40 people with neck pain were recruited. Intrarater reliability was almost perfect (ICC = 0.94-0.97), interrater reliability was substantial to near perfect (ICC = 0.79-0.90), and test-retest reliability was substantial (ICC = 0.76-0.79). Smaller change was detectable in the trapezius compared to the tibialis anterior. This study provides evidence that novice raters can perform digital algometry with adequate reliability for research and clinical use in people with and without neck pain.

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).

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.

Glider communications and controls for the sea sentry mission.

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

Feddema, John Todd; Dohner, Jeffrey Lynn

2005-03-01

This report describes a system level study on the use of a swarm of sea gliders to detect, confirm and kill littoral submarine threats. The report begins with a description of the problem and derives the probability of detecting a constant speed threat without networking. It was concluded that glider motion does little to improve this probability unless the speed of a glider is greater than the speed of the threat. Therefore, before detection, the optimal character for a swarm of gliders is simply to lie in wait for the detection of a threat. The report proceeds by describing themore » effect of noise on the localization of a threat once initial detection is achieved. This noise is estimated as a function of threat location relative to the glider and is temporally reduced through the use of an information or Kalman filtering. In the next section, the swarm probability of confirming and killing a threat is formulated. Results are compared to a collection of stationary sensors. These results show that once a glider has the ability to move faster than the threat, the performance of the swarm is equal to the performance of a stationary swarm of gliders with confirmation and kill ranges equal to detection range. Moreover, at glider speeds greater than the speed of the threat, swarm performance becomes a weak function of speed. At these speeds swarm performance is dominated by detection range. Therefore, to future enhance swarm performance or to reduce the number of gliders required for a given performance, detection range must be increased. Communications latency is also examined. It was found that relatively large communication delays did little to change swarm performance. Thus gliders may come to the surface and use SATCOMS to effectively communicate in this application.« less

Development of auditory event-related potentials in infants prenatally exposed to methadone.

PubMed

Paul, Jonathan A; Logan, Beth A; Krishnan, Ramesh; Heller, Nicole A; Morrison, Deborah G; Pritham, Ursula A; Tisher, Paul W; Troese, Marcia; Brown, Mark S; Hayes, Marie J

2014-07-01

Developmental features of the P2 auditory ERP in a change detection paradigm were examined in infants prenatally exposed to methadone. Opiate dependent pregnant women maintained on methadone replacement therapy were recruited during pregnancy (N = 60). Current and historical alcohol and substance use, SES, and psychiatric status were assessed with a maternal interview during the third trimester. Medical records were used to collect information regarding maternal medications, monthly urinalysis, and breathalyzer to confirm comorbid drug and alcohol exposures. Between birth and 4 months infant ERP change detection performance was evaluated on one occasion with the oddball paradigm (.2 probability oddball) using pure-tone stimuli (standard = 1 kHz and oddball = 2 kHz frequency) at midline electrode sites, Fz, Cz, Pz. Infant groups were examined in the following developmental windows: 4-15, 16-32, or 33-120 days PNA. Older groups showed increased P2 amplitude at Fz and effective change detection performance at P2 not seen in the newborn group. Developmental maturation of amplitude and stimulus discrimination for P2 has been reported in developing infants at all of the ages tested and data reported here in the older infants are consistent with typical development. However, it has been previously reported that the P2 amplitude difference is detectable in neonates; therefore, absence of a difference in P2 amplitude between stimuli in the 4-15 days group may represent impaired ERP performance by neonatal abstinence syndrome or prenatal methadone exposure. © 2013 Wiley Periodicals, Inc.

Meaningful change and responsiveness in common physical performance measures in older adults.

PubMed

Perera, Subashan; Mody, Samir H; Woodman, Richard C; Studenski, Stephanie A

2006-05-01

To estimate the magnitude of small meaningful and substantial individual change in physical performance measures and evaluate their responsiveness. Secondary data analyses using distribution- and anchor-based methods to determine meaningful change. Secondary analysis of data from an observational study and clinical trials of community-dwelling older people and subacute stroke survivors. Older adults with mobility disabilities in a strength training trial (n=100), subacute stroke survivors in an intervention trial (n=100), and a prospective cohort of community-dwelling older people (n=492). Gait speed, Short Physical Performance Battery (SPPB), 6-minute-walk distance (6MWD), and self-reported mobility. Most small meaningful change estimates ranged from 0.04 to 0.06 m/s for gait speed, 0.27 to 0.55 points for SPPB, and 19 to 22 m for 6MWD. Most substantial change estimates ranged from 0.08 to 0.14 m/s for gait speed, 0.99 to 1.34 points for SPPB, and 47 to 49 m for 6MWD. Based on responsiveness indices, per-group sample sizes for clinical trials ranged from 13 to 42 for substantial change and 71 to 161 for small meaningful change. Best initial estimates of small meaningful change are near 0.05 m/s for gait speed, 0.5 points for SPPB, and 20 m for 6MWD and of substantial change are near 0.10 m/s for gait speed, 1.0 point for SPPB, and 50 m for 6MWD. For clinical use, substantial change in these measures and small change in gait speed and 6MWD, but not SPPB, are detectable. For research use, these measures yield feasible sample sizes for detecting meaningful change.

A Multi-Week Behavioral Sampling Tag for Sound Effects Studies: Design Trade-Offs and Prototype Evaluation

DTIC Science & Technology

2013-09-30

performance of algorithms detecting dives, strokes , clicks, respiration and gait changes. (ii) Calibration errors: Size and power constraints in...acceptance parameters used to detect and classify events. For example, swim stroke detection requires parameters defining the minimum magnitude and the min...and max duration of a stroke . Species dependent parameters can be selected from existing DTAG data but other parameters depend on the size of the

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

Pattern-histogram-based temporal change detection using personal chest radiographs

NASA Astrophysics Data System (ADS)

Ugurlu, Yucel; Obi, Takashi; Hasegawa, Akira; Yamaguchi, Masahiro; Ohyama, Nagaaki

1999-05-01

An accurate and reliable detection of temporal changes from a pair of images has considerable interest in the medical science. Traditional registration and subtraction techniques can be applied to extract temporal differences when,the object is rigid or corresponding points are obvious. However, in radiological imaging, loss of the depth information, the elasticity of object, the absence of clearly defined landmarks and three-dimensional positioning differences constraint the performance of conventional registration techniques. In this paper, we propose a new method in order to detect interval changes accurately without using an image registration technique. The method is based on construction of so-called pattern histogram and comparison procedure. The pattern histogram is a graphic representation of the frequency counts of all allowable patterns in the multi-dimensional pattern vector space. K-means algorithm is employed to partition pattern vector space successively. Any differences in the pattern histograms imply that different patterns are involved in the scenes. In our experiment, a pair of chest radiographs of pneumoconiosis is employed and the changing histogram bins are visualized on both of the images. We found that the method can be used as an alternative way of temporal change detection, particularly when the precise image registration is not available.

An ontology-based annotation of cardiac implantable electronic devices to detect therapy changes in a national registry.

PubMed

Rosier, Arnaud; Mabo, Philippe; Chauvin, Michel; Burgun, Anita

2015-05-01

The patient population benefitting from cardiac implantable electronic devices (CIEDs) is increasing. This study introduces a device annotation method that supports the consistent description of the functional attributes of cardiac devices and evaluates how this method can detect device changes from a CIED registry. We designed the Cardiac Device Ontology, an ontology of CIEDs and device functions. We annotated 146 cardiac devices with this ontology and used it to detect therapy changes with respect to atrioventricular pacing, cardiac resynchronization therapy, and defibrillation capability in a French national registry of patients with implants (STIDEFIX). We then analyzed a set of 6905 device replacements from the STIDEFIX registry. Ontology-based identification of therapy changes (upgraded, downgraded, or similar) was accurate (6905 cases) and performed better than straightforward analysis of the registry codes (F-measure 1.00 versus 0.75 to 0.97). This study demonstrates the feasibility and effectiveness of ontology-based functional annotation of devices in the cardiac domain. Such annotation allowed a better description and in-depth analysis of STIDEFIX. This method was useful for the automatic detection of therapy changes and may be reused for analyzing data from other device registries.

A preliminary evaluation of land use mapping and change detection capabilities using an ERTS image covering a portion of the CARETS region

NASA Technical Reports Server (NTRS)

Fitzpatrick, K. A.; Lins, H. F., Jr.

1972-01-01

The author has identified the following significant results. A preliminary study on the capabilities of ERTS data in land use mapping and change detection was carried out in the area around Frederick County, Maryland, which lies in the northwest corner of the Central Atlantic Regional Ecological Test Site. The investigation has revealed that Level 1 (of the Anderson classification system) land use mapping can be performed and that, in some cases, land undergoing change can be identified. Results to date suggest that more work should be done in areas where land use changes are known to exist, in order to establish some form of base for recognizing the spectral signature indicative of change areas.

Detection of urban expansion in an urban-rural landscape with multitemporal QuickBird images

PubMed Central

Lu, Dengsheng; Hetrick, Scott; Moran, Emilio; Li, Guiying

2011-01-01

Accurately detecting urban expansion with remote sensing techniques is a challenge due to the complexity of urban landscapes. This paper explored methods for detecting urban expansion with multitemporal QuickBird images in Lucas do Rio Verde, Mato Grosso, Brazil. Different techniques, including image differencing, principal component analysis (PCA), and comparison of classified impervious surface images with the matched filtering method, were used to examine urbanization detection. An impervious surface image classified with the hybrid method was used to modify the urbanization detection results. As a comparison, the original multispectral image and segmentation-based mean-spectral images were used during the detection of urbanization. This research indicates that the comparison of classified impervious surface images with matched filtering method provides the best change detection performance, followed by the image differencing method based on segmentation-based mean spectral images. The PCA is not a good method for urban change detection in this study. Shadows and high spectral variation within the impervious surfaces represent major challenges to the detection of urban expansion when high spatial resolution images are used. PMID:21799706

Adjusting the specificity of an engine map based on the sensitivity of an engine control parameter relative to a performance variable

DOEpatents

Jiang, Li; Lee, Donghoon; Yilmaz, Hakan; Stefanopoulou, Anna

2014-10-28

Methods and systems for engine control optimization are provided. A first and a second operating condition of a vehicle engine are detected. An initial value is identified for a first and a second engine control parameter corresponding to a combination of the detected operating conditions according to a first and a second engine map look-up table. The initial values for the engine control parameters are adjusted based on a detected engine performance variable to cause the engine performance variable to approach a target value. A first and a second sensitivity of the engine performance variable are determined in response to changes in the engine control parameters. The first engine map look-up table is adjusted when the first sensitivity is greater than a threshold, and the second engine map look-up table is adjusted when the second sensitivity is greater than a threshold.

Change of search time and non-search time in X-ray baggage screening due to training.

PubMed

Koller, Saskia M; Drury, Colin G; Schwaninger, Adrian

2009-06-01

As found in studies of aircraft structural inspection, the time used for judging if a part of an aircraft shows tiny cracks is composed of search time, used for actively scanning, and non-search time, used for matching and decision while fixating a region of interest (Drury et al. 1997). These findings can be applied to detection of threats by X-ray screening of passenger bags at airports. To investigate whether search time and non-search time change when an experienced screener is given additional training in recognising threat objects in passenger bags, data from a European airport were analysed. A comparison of detection performance and reaction time between two large groups of screeners, one trained for 6 months, shows a large impact of training on overall performance and on both search and non-search components of the task. There was also a small but consistent decline in performance measures with screener age. This study shows a way to localise the effect of training on threat detection performance for aviation security screening. Analysis of the time needed for screening each passenger bag showed that training had a significant effect, particularly on the non-search part of the searching process (i.e. identification, recognition, decision, response execution, etc.).

Performance of laser Doppler velocimeter with polydisperse seed particles in high speed flows

NASA Technical Reports Server (NTRS)

Samimy, M.; Bhattacharyya, S.; Abu-Hijleh, B. A./K.

1988-01-01

The flowfield behind an oblique shock wave, where the LDV measured velocities are seed particle size dependent, was used to investigate the effects of LDV system parameters on the range of detectable polydisperse seed particles. The parameters included frequency shifting, laser power, scattered signal amplification level, and number of required fringe crossings. The results showed that with polydisperse seed particles ranging from 0.1 to 4.0 microns available in the flow, the average diameter of the detected particles could change from 0.2 to 3.0 microns by changing different LDV system parameters. The effects of this shift in the range of detectable particles on the frequency response of LDV was discussed.

Performance of laser Doppler velocimeter with polydisperse seed particles in high-speed flows

NASA Technical Reports Server (NTRS)

Samimy, M.; Abu-Hijleh, B. A. K.

1989-01-01

The flowfield behind an oblique shock wave, where the LDV measured velocities are seed-particle-size dependent, was used to investigate the effects of LDV system parameters on the range of detectable polydisperse seed particles. The parameters included frequency shifting, laser power, scattered signal amplification level, and number of required fringe crossings. The results showed that with polydisperse seed particles ranging from 0.1 to 4.0 microns available in the flow, the average diameter of the detected particles could change from 0.2 to 3.0 microns by changing different LDV system parameters. The effects of this shift in the range of detectable particles on the frequency response of LDV are discussed.

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.

Nondestructive examination of decarburised layer of steels using eddy current and magnetic Barkhausen noise testing techniques

NASA Astrophysics Data System (ADS)

Falahat, S.; Ghanei, S.; Kashefi, M.

2018-04-01

Eddy current and Barkhausen noise nondestructive testing techniques were considered to evaluate the magnetic properties of the decarburised steels as a function of microstructure. To make changes in decarburising depth, carbon steel samples were austenitised at 890 °C for 120-270 min. Considering different decarburised depths, height, position and width of the noise profiles were extracted in order to analyse the magnetic Barkhausen noise measurements. Next, the eddy current test was performed to detect the changes in the microstructure through decarburising of the steel taking into account the impedance variations. According to the results, both techniques allow us to detect changes in the magnetic properties of the decarburised steels and link them with their microstructural changes, nondestructively.

Detection of changes in bone quality of osteoporotic model induced by sciatic nerve resection by using Raman spectroscopy

NASA Astrophysics Data System (ADS)

Ishimaru, Yasumitsu; Oshima, Yusuke; Imai, Yuuki; Iimura, Tadahiro; Takanezawa, Sota; Hino, Kazunori; Miura, Hiromasa

2018-02-01

To detect the bone quality loss in osteoporosis, we performed Raman spectroscopic analysis of sciatic nerve resection (NX) mice. Eight months after surgery, lower limbs were collected from the mice and fixed with 70% ethanol. Raman spectra of anterior cortical surface of the proximal tibia at 5 points in each bone were measured by RENISHAW inVia Raman Microscope. Excitation wave length was 785 nm. We also performed DXA and micro CT measurement to confirm the bone mineral density and bone microstructure in the osteoporotic model induced by sciatic nerve resection. In the result of Raman spectroscopy, we detected changes of Raman peak intensity ratio in carbonate/phosphate, mineral/combined proline and hydroxyproline and mineral/phenylalanine. In addition, in the result of micro CT, we found significant changes in VOX BV/TV, Trabecular number, thickness, cancellous bone mineral density, cortical thickness and cortical bone mineral density. The results suggest that not only the bone mineral density but also bone quality reduced in the NX mice. We conclude that Raman spectroscopy is a useful for bone quality assessment as a complementary technique for conventional diagnostics.

Analysis of Movement, Orientation and Rotation-Based Sensing for Phone Placement Recognition

PubMed Central

Durmaz Incel, Ozlem

2015-01-01

Phone placement, i.e., where the phone is carried/stored, is an important source of information for context-aware applications. Extracting information from the integrated smart phone sensors, such as motion, light and proximity, is a common technique for phone placement detection. In this paper, the efficiency of an accelerometer-only solution is explored, and it is investigated whether the phone position can be detected with high accuracy by analyzing the movement, orientation and rotation changes. The impact of these changes on the performance is analyzed individually and both in combination to explore which features are more efficient, whether they should be fused and, if yes, how they should be fused. Using three different datasets, collected from 35 people from eight different positions, the performance of different classification algorithms is explored. It is shown that while utilizing only motion information can achieve accuracies around 70%, this ratio increases up to 85% by utilizing information also from orientation and rotation changes. The performance of an accelerometer-only solution is compared to solutions where linear acceleration, gyroscope and magnetic field sensors are used, and it is shown that the accelerometer-only solution performs as well as utilizing other sensing information. Hence, it is not necessary to use extra sensing information where battery power consumption may increase. Additionally, I explore the impact of the performed activities on position recognition and show that the accelerometer-only solution can achieve 80% recognition accuracy with stationary activities where movement data are very limited. Finally, other phone placement problems, such as in-pocket and on-body detections, are also investigated, and higher accuracies, ranging from 88% to 93%, are reported, with an accelerometer-only solution. PMID:26445046

Analysis of Movement, Orientation and Rotation-Based Sensing for Phone Placement Recognition.

PubMed

Incel, Ozlem Durmaz

2015-10-05

Phone placement, i.e., where the phone is carried/stored, is an important source of information for context-aware applications. Extracting information from the integrated smart phone sensors, such as motion, light and proximity, is a common technique for phone placement detection. In this paper, the efficiency of an accelerometer-only solution is explored, and it is investigated whether the phone position can be detected with high accuracy by analyzing the movement, orientation and rotation changes. The impact of these changes on the performance is analyzed individually and both in combination to explore which features are more efficient, whether they should be fused and, if yes, how they should be fused. Using three different datasets, collected from 35 people from eight different positions, the performance of different classification algorithms is explored. It is shown that while utilizing only motion information can achieve accuracies around 70%, this ratio increases up to 85% by utilizing information also from orientation and rotation changes. The performance of an accelerometer-only solution is compared to solutions where linear acceleration, gyroscope and magnetic field sensors are used, and it is shown that the accelerometer-only solution performs as well as utilizing other sensing information. Hence, it is not necessary to use extra sensing information where battery power consumption may increase. Additionally, I explore the impact of the performed activities on position recognition and show that the accelerometer-only solution can achieve 80% recognition accuracy with stationary activities where movement data are very limited. Finally, other phone placement problems, such as in-pocket and on-body detections, are also investigated, and higher accuracies, ranging from 88% to 93%, are reported, with an accelerometer-only solution.

Study on thin wideband applicator for detecting blood characteristics in human body

NASA Astrophysics Data System (ADS)

Bamba, Kazuki; Kuki, Takao; Nikawa, Yoshio

2016-11-01

Preventive care as well as early detection method and monitoring technique for diseases are highly attracted attention to increase quality of life. Noninvasive measurement method for blood characteristics in body is expected by patients with kidney dysfunction. Complex permittivity of blood is changed a few present at 6GHz. This change is caused by the change of water and albumin contents in blood. In this study, to detect blood characteristics in human body, experiments with phantom model has been performed using thin wideband applicator for examining microwave transmission up to 6GHz. The thin wideband applicator has advantages for detecting living body information in detail. The thin wideband applicator is designed based on Antipodal Vivaldi Antenna and is not required any balun and is very easy handling. Using developed Antipodal Vivaldi Antenna, transmission coefficient can be obtained as a function of thickness of phantom model with high sensitivity. Using this method, highly sensitive sensor for obtaining characteristics of blood in body can be developed.

The role of visual attention in predicting driving impairment in older adults.

PubMed

Hoffman, Lesa; McDowd, Joan M; Atchley, Paul; Dubinsky, Richard

2005-12-01

This study evaluated the role of visual attention (as measured by the DriverScan change detection task and the Useful Field of View Test [UFOV]) in the prediction of driving impairment in 155 adults between the ages of 63 and 87. In contrast to previous research, participants were not oversampled for visual impairment or history of automobile accidents. Although a history of automobile accidents within the past 3 years could not be predicted using any variable, driving performance in a low-fidelity simulator could be significantly predicted by performance in the change detection task and by the divided and selection attention subtests of the UFOV in structural equation models. The sensitivity and specificity of each measure in identifying at-risk drivers were also evaluated with receiver operating characteristic curves.

Sensitivity to change of the field-based Wheelchair Mobility Performance Test in wheelchair basketball.

PubMed

de Witte, Annemarie M H; Sjaarda, Fleur; Helleman, Jochem; Berger, Monique A M; van der Woude, Lucas H V; Hoozemans, Marco J M

2018-06-15

The Wheelchair Mobility Performance (WMP) test is a reliable and valid measure to assess mobility performance in wheelchair basketball. The aim of this study was to examine the sensitivity to change of the WMP test by manipulating wheelchair configurations. Sixteen wheelchair basketball players performed the WMP test 3 times in their own wheelchair: (i) without adjustments ("control condition"); (ii) with 10 kg additional mass ("weighted condition"); and (iii) with 50% reduced tyre pressure ("tyre condition"). The outcome measure was time (s). If paired t-tests were significant (p <0.05) and differences between conditions were larger than the standard error of measurement, the effect sizes (ES) were used to evaluate the sensitivity to change. ES values ≥0.2 were regarded as sensitive to change. The overall performance times for the manipulations were significantly higher than the control condition, with mean differences of 4.40 s (weight - control, ES = 0.44) and 2.81 s (tyre - control, ES = 0.27). The overall performance time on the WMP test was judged as sensitive to change. For 8 of the 15 separate tasks on the WMP test, the tasks were judged as sensitive to change for at least one of the manipulations. The WMP test can detect change in mobility performance when wheelchair configurations are manipulated.

Denaturing high-performance liquid chromatography for mutation detection and genotyping.

PubMed

Fackenthal, Donna Lee; Chen, Pei Xian; Howe, Ted; Das, Soma

2013-01-01

Denaturing high-performance liquid chromatography (DHPLC) is an accurate and efficient screening technique used for detecting DNA sequence changes by heteroduplex analysis. It can also be used for genotyping of single nucleotide polymorphisms (SNPs). The high sensitivity of DHPLC has made this technique one of the most reliable approaches to mutation analysis and, therefore, used in various areas of genetics, both in the research and clinical arena. This chapter describes the methods used for mutation detection analysis and the genotyping of SNPs by DHPLC on the WAVE™ system from Transgenomic Inc. ("WAVE" and "DNASep" are registered trademarks, and "Navigator" is a trademark, of Transgenomic, used with permission. All other trademarks are property of the respective owners).

Investigations related to evaluation of ultramicrofluorometer

NASA Technical Reports Server (NTRS)

Whitcomb, B.

1981-01-01

High resolution emission and excitation fluorescent spectra were obtained for several samples in an effort to determine the optimum operational design for the instrument. The instrument was used to determine the required nature of a sample which could be detected, and in so doing, several different sample preparation techniques were considered. Numerous experiments were performed to determine the capabilities of the instrument with regard to the detection of suitably prepared virus specimens. Significant results were obtained in several areas. The fluorescent spectra indicated that substantial changes in the laser might be used advantageously to greatly improve the performance of the instrument. In the existing configuration, the instrument was shown to be capable of detecting the presence of suitably prepared virus samples.

Enhanced visual performance in obsessive compulsive personality disorder.

PubMed

Ansari, Zohreh; Fadardi, Javad Salehi

2016-12-01

Visual performance is considered as commanding modality in human perception. We tested whether Obsessive-compulsive personality disorder (OCPD) people do differently in visual performance tasks than people without OCPD. One hundred ten students of Ferdowsi University of Mashhad and non-student participants were tested by Structured Clinical Interview for DSM-IV Axis II Personality Disorders (SCID-II), among whom 18 (mean age = 29.55; SD = 5.26; 84% female) met the criteria for OCPD classification; controls were 20 persons (mean age = 27.85; SD = 5.26; female = 84%), who did not met the OCPD criteria. Both groups were tested on a modified Flicker task for two dimensions of visual performance (i.e., visual acuity: detecting the location of change, complexity, and size; and visual contrast sensitivity). The OCPD group had responded more accurately on pairs related to size, complexity, and contrast, but spent more time to detect a change on pairs related to complexity and contrast. The OCPD individuals seem to have more accurate visual performance than non-OCPD controls. The findings support the relationship between personality characteristics and visual performance within the framework of top-down processing model. © 2016 Scandinavian Psychological Associations and John Wiley & Sons Ltd.

A multidisciplinary approach to overreaching detection in endurance trained athletes.

PubMed

Le Meur, Yann; Hausswirth, Christophe; Natta, Françoise; Couturier, Antoine; Bignet, Frank; Vidal, Pierre Paul

2013-02-01

In sport, high training load required to reach peak performance pushes human adaptation to their limits. In that process, athletes may experience general fatigue, impaired performance, and may be identified as overreached (OR). When this state lasts for several months, an overtraining syndrome is diagnosed (OT). Until now, no variable per se can detect OR, a requirement to prevent the transition from OR to OT. It encouraged us to further investigate OR using a multivariate approach, including physiological, biomechanical, cognitive, and perceptive monitoring. Twenty-four highly trained triathletes were separated into an overload group and a normo-trained group (NT) during 3 wk of training. Given the decrement of their running performance, 11 triathletes were diagnosed as OR after this period. A discriminant analysis showed that the changes of eight parameters measured during a maximal incremental test could explain 98.2% of the OR state (lactatemia, heart rate, biomechanical parameters and effort perception). Variations in heart rate and lactatemia were the two most discriminating factors. When the multifactorial analysis was restricted to these variables, the classification score reached 89.5%. Catecholamines and creatine kinase concentrations at rest did not change significantly in both groups. Running pattern was preserved and cognitive performance decrement was observed only at exhaustion in OR subjects. This study showed that monitoring various variables is required to prevent the transition between NT and OR. It emphasized that an OR index, which combines heart rate and blood lactate concentration changes after a strenuous training period, could be helpful to routinely detect OR.

The Applicability of Standard Error of Measurement and Minimal Detectable Change to Motor Learning Research-A Behavioral Study.

PubMed

Furlan, Leonardo; Sterr, Annette

2018-01-01

Motor learning studies face the challenge of differentiating between real changes in performance and random measurement error. While the traditional p -value-based analyses of difference (e.g., t -tests, ANOVAs) provide information on the statistical significance of a reported change in performance scores, they do not inform as to the likely cause or origin of that change, that is, the contribution of both real modifications in performance and random measurement error to the reported change. One way of differentiating between real change and random measurement error is through the utilization of the statistics of standard error of measurement (SEM) and minimal detectable change (MDC). SEM is estimated from the standard deviation of a sample of scores at baseline and a test-retest reliability index of the measurement instrument or test employed. MDC, in turn, is estimated from SEM and a degree of confidence, usually 95%. The MDC value might be regarded as the minimum amount of change that needs to be observed for it to be considered a real change, or a change to which the contribution of real modifications in performance is likely to be greater than that of random measurement error. A computer-based motor task was designed to illustrate the applicability of SEM and MDC to motor learning research. Two studies were conducted with healthy participants. Study 1 assessed the test-retest reliability of the task and Study 2 consisted in a typical motor learning study, where participants practiced the task for five consecutive days. In Study 2, the data were analyzed with a traditional p -value-based analysis of difference (ANOVA) and also with SEM and MDC. The findings showed good test-retest reliability for the task and that the p -value-based analysis alone identified statistically significant improvements in performance over time even when the observed changes could in fact have been smaller than the MDC and thereby caused mostly by random measurement error, as opposed to by learning. We suggest therefore that motor learning studies could complement their p -value-based analyses of difference with statistics such as SEM and MDC in order to inform as to the likely cause or origin of any reported changes in performance.

Bi-temporal analysis of landscape changes in the easternmost mediterranean deltas using binary and classified change information.

PubMed

Alphan, Hakan

2013-03-01

The aim of this study is (1) to quantify landscape changes in the easternmost Mediterranean deltas using bi-temporal binary change detection approach and (2) to analyze relationships between conservation/management designations and various categories of change that indicate type, degree and severity of human impact. For this purpose, image differencing and ratioing were applied to Landsat TM images of 1984 and 2006. A total of 136 candidate change images including normalized difference vegetation index (NDVI) and principal component analysis (PCA) difference images were tested to understand performance of bi-temporal pre-classification analysis procedures in the Mediterranean delta ecosystems. Results showed that visible image algebra provided high accuracies than did NDVI and PCA differencing. On the other hand, Band 5 differencing had one of the lowest change detection performances. Seven superclasses of change were identified using from/to change categories between the earlier and later dates. These classes were used to understand spatial character of anthropogenic impacts in the study area and derive qualitative and quantitative change information within and outside of the conservation/management areas. Change analysis indicated that natural site and wildlife reserve designations fell short of protecting sand dunes from agricultural expansion in the west. East of the study area, however, was exposed to least human impact owing to the fact that nature conservation status kept human interference at a minimum. Implications of these changes were discussed and solutions were proposed to deal with management problems leading to environmental change.

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.

The significance and robustness of a plasma free amino acid (PFAA) profile-based multiplex function for detecting lung cancer

PubMed Central

2013-01-01

Background We have recently reported on the changes in plasma free amino acid (PFAA) profiles in lung cancer patients and the efficacy of a PFAA-based, multivariate discrimination index for the early detection of lung cancer. In this study, we aimed to verify the usefulness and robustness of PFAA profiling for detecting lung cancer using new test samples. Methods Plasma samples were collected from 171 lung cancer patients and 3849 controls without apparent cancer. PFAA levels were measured by high-performance liquid chromatography (HPLC)–electrospray ionization (ESI)–mass spectrometry (MS). Results High reproducibility was observed for both the change in the PFAA profiles in the lung cancer patients and the discriminating performance for lung cancer patients compared to previously reported results. Furthermore, multivariate discriminating functions obtained in previous studies clearly distinguished the lung cancer patients from the controls based on the area under the receiver-operator characteristics curve (AUC of ROC = 0.731 ~ 0.806), strongly suggesting the robustness of the methodology for clinical use. Moreover, the results suggested that the combinatorial use of this classifier and tumor markers improves the clinical performance of tumor markers. Conclusions These findings suggest that PFAA profiling, which involves a relatively simple plasma assay and imposes a low physical burden on subjects, has great potential for improving early detection of lung cancer. PMID:23409863

Rapid systematic assessment of the detection and attribution of regional anthropogenic climate change

DOE PAGES

Stone, Daithi A.; Hansen, Gerrit

2015-11-21

Despite being a well-established research field, the detection and attribution of observed climate change to anthropogenic forcing is not yet provided as a climate service. One reason for this is the lack of a methodology for performing tailored detection and attribution assessments on a rapid time scale. Here we develop such an approach, based on the translation of quantitative analysis into the “confidence” language employed in recent Assessment Reports of the Intergovernmental Panel on Climate Change. While its systematic nature necessarily ignores some nuances examined in detailed expert assessments, the approach nevertheless goes beyond most detection and attribution studies inmore » considering contributors to building confidence such as errors in observational data products arising from sparse monitoring networks. When compared against recent expert assessments, the results of this approach closely match those of the existing assessments. Where there are small discrepancies, these variously reflect ambiguities in the details of what is being assessed, reveal nuances or limitations of the expert assessments, or indicate limitations of the accuracy of the sort of systematic approach employed here. Deployment of the method on 116 regional assessments of recent temperature and precipitation changes indicates that existing rules of thumb concerning the detectability of climate change ignore the full range of sources of uncertainty, most particularly the importance of adequate observational monitoring.« less

The role of audience participation and task relevance on change detection during a card trick.

PubMed

Smith, Tim J

2015-01-01

Magicians utilize many techniques for misdirecting audience attention away from the secret sleight of a trick. One technique is to ask an audience member to participate in a trick either physically by asking them to choose a card or cognitively by having them keep track of a card. While such audience participation is an established part of most magic the cognitive mechanisms by which it operates are unknown. Failure to detect changes to objects while passively viewing magic tricks has been shown to be conditional on the changing feature being irrelevant to the current task. How change blindness operates during interactive tasks is unclear but preliminary evidence suggests that relevance of the changing feature may also play a role (Triesch et al., 2003). The present study created a simple on-line card trick inspired by Triesch et al.'s (2003) that allowed playing cards to be instantaneously replaced without distraction or occlusion as participants were either actively sorting the cards (Doing condition) or watching another person perform the task (Watching conditions). Participants were given one of three sets of instructions. The relevance of the card color to the task increased across the three instructions. During half of the trials a card changed color (but retained its number) as it was moving to the stack. Participants were instructed to immediately report such changes. Analysis of the probability of reporting a change revealed that actively performing the sorting task led to more missed changes than passively watching the same task but only when the changing feature was irrelevant to the sorting task. If the feature was relevant during either the pick-up or put-down action change detection was as good as during the watching block. These results confirm the ability of audience participation to create subtle dynamics of attention and perception during a magic trick and hide otherwise striking changes at the center of attention.

The role of audience participation and task relevance on change detection during a card trick

PubMed Central

Smith, Tim J.

2015-01-01

Magicians utilize many techniques for misdirecting audience attention away from the secret sleight of a trick. One technique is to ask an audience member to participate in a trick either physically by asking them to choose a card or cognitively by having them keep track of a card. While such audience participation is an established part of most magic the cognitive mechanisms by which it operates are unknown. Failure to detect changes to objects while passively viewing magic tricks has been shown to be conditional on the changing feature being irrelevant to the current task. How change blindness operates during interactive tasks is unclear but preliminary evidence suggests that relevance of the changing feature may also play a role (Triesch et al., 2003). The present study created a simple on-line card trick inspired by Triesch et al.’s (2003) that allowed playing cards to be instantaneously replaced without distraction or occlusion as participants were either actively sorting the cards (Doing condition) or watching another person perform the task (Watching conditions). Participants were given one of three sets of instructions. The relevance of the card color to the task increased across the three instructions. During half of the trials a card changed color (but retained its number) as it was moving to the stack. Participants were instructed to immediately report such changes. Analysis of the probability of reporting a change revealed that actively performing the sorting task led to more missed changes than passively watching the same task but only when the changing feature was irrelevant to the sorting task. If the feature was relevant during either the pick-up or put-down action change detection was as good as during the watching block. These results confirm the ability of audience participation to create subtle dynamics of attention and perception during a magic trick and hide otherwise striking changes at the center of attention. PMID:25698986

Alpha-ray detection with a MgB 2 transition edge sensor

NASA Astrophysics Data System (ADS)

Okayasu, S.; Katagiri, M.; Hojou, K.; Morii, Y.; Miki, S.; Shimakage, H.; Wang, Z.; Ishida, T.

2008-09-01

We have been investigating for neutron detection with the MgB 2 transition edge sensor (TES). For the purpose, we have been developing a low noise measurement system for the detection. To confirm the performance of the detecting sensor, alpha ray detection from an americium-241 ( 241Am) alpha-ray source was achieved. A short microfabricated sample with 10 μm length and 1 μm width is used to improve the S/N ratio. The detection is achieved under a constant current condition in the range between 1 and 6 μA bias current, and the resistivity changes at the sample due to the alpha ray irradiation is detected just on the transition edge.

Enhanced biosensor performance using an avidin-biotin bridge for antibody immobilization

NASA Astrophysics Data System (ADS)

Narang, Upvan; Anderson, George P.; King, Keeley D.; Liss, Heidi S.; Ligler, Frances S.

1997-05-01

Maintaining antibody function after immobilization is critical to the performance of a biosensor. The conventional methods to immobilize antibodies onto surfaces are via covalent attachment using a crosslinker or by adsorption. Often, these methods of immobilization result in partial denaturation of the antibody and conformational changes leading to a reduced activity of the antibody. In this paper, we report on the immobilization of antibodies onto the surface of an optical fiber through an avidin-biotin bridge for the detection of ricin, ovalbumin, and Bacillus globigii (Bg). The assays are performed in a sandwich format. First, a capture antibody is immobilized, followed by the addition of the analyte. Finally, a fluorophore- labeled antibody is added for the specific detection of the analyte. The evanescent wave-induced fluorescence is coupled back through the same fiber to be detected using a photodiode. In all cases, we observe an improved performance of the biosensor, i.e., lower limit of detection and wide linear dynamic range, for the assays in which the antibody is immobilized via avidin-biotin bridges compared to covalent attachment method.

Tracing the conformational changes in BSA using FRET with environmentally-sensitive squaraine probes

NASA Astrophysics Data System (ADS)

Govor, Iryna V.; Tatarets, Anatoliy L.; Obukhova, Olena M.; Terpetschnig, Ewald A.; Gellerman, Gary; Patsenker, Leonid D.

2016-06-01

A new potential method of detecting the conformational changes in hydrophobic proteins such as bovine serum albumin (BSA) is introduced. The method is based on the change in the Förster resonance energy transfer (FRET) efficiency between protein-sensitive fluorescent probes. As compared to conventional FRET based methods, in this new approach the donor and acceptor dyes are not covalently linked to protein molecules. Performance of the new method is demonstrated using the protein-sensitive squaraine probes Square-634 (donor) and Square-685 (acceptor) to detect the urea-induced conformational changes of BSA. The FRET efficiency between these probes can be considered a more sensitive parameter to trace protein unfolding as compared to the changes in fluorescence intensity of each of these probes. Addition of urea followed by BSA unfolding causes a noticeable decrease in the emission intensities of these probes (factor of 5.6 for Square-634 and 3.0 for Square-685), and the FRET efficiency changes by a factor of up to 17. Compared to the conventional method the new approach therefore demonstrates to be a more sensitive way to detect the conformational changes in BSA.

Detection of Road Markings Recorded in In-Vehicle Camera Images by Using Position-Dependent Classifiers

NASA Astrophysics Data System (ADS)

Noda, Masafumi; Takahashi, Tomokazu; Deguchi, Daisuke; Ide, Ichiro; Murase, Hiroshi; Kojima, Yoshiko; Naito, Takashi

In this study, we propose a method for detecting road markings recorded in an image captured by an in-vehicle camera by using a position-dependent classifier. Road markings are symbols painted on the road surface that help in preventing traffic accidents and in ensuring traffic smooth. Therefore, driver support systems for detecting road markings, such as a system that provides warning in the case when traffic signs are overlooked, and supporting the stopping of a vehicle are required. It is difficult to detect road markings because their appearance changes with the actual traffic conditions, e. g. the shape and resolution change. The variation in these appearances depend on the positional relation between the vehicle and the road markings, and on the vehicle posture. Although these variations are quite large in an entire image, they are relatively small in a local area of the image. Therefore, we try to improve the detection performance by taking into account the local variations in these appearances. We propose a method in which a position-dependent classifier is used to detect road markings recorded in images captured by an in-vehicle camera. Further, to train the classifier efficiently, we propose a generative learning method that takes into consideration the positional relation between the vehicle and road markings, and also the vehicle posture. Experimental results showed that the detection performance when the proposed method was used was better than when a method involving a single classifier was used.

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.

Mass detection, localization and estimation for wind turbine blades based on statistical pattern recognition

NASA Astrophysics Data System (ADS)

Colone, L.; Hovgaard, M. K.; Glavind, L.; Brincker, R.

2018-07-01

A method for mass change detection on wind turbine blades using natural frequencies is presented. The approach is based on two statistical tests. The first test decides if there is a significant mass change and the second test is a statistical group classification based on Linear Discriminant Analysis. The frequencies are identified by means of Operational Modal Analysis using natural excitation. Based on the assumption of Gaussianity of the frequencies, a multi-class statistical model is developed by combining finite element model sensitivities in 10 classes of change location on the blade, the smallest area being 1/5 of the span. The method is experimentally validated for a full scale wind turbine blade in a test setup and loaded by natural wind. Mass change from natural causes was imitated with sand bags and the algorithm was observed to perform well with an experimental detection rate of 1, localization rate of 0.88 and mass estimation rate of 0.72.

Change Detection of Remote Sensing Images by Dt-Cwt and Mrf

NASA Astrophysics Data System (ADS)

Ouyang, S.; Fan, K.; Wang, H.; Wang, Z.

2017-05-01

Aiming at the significant loss of high frequency information during reducing noise and the pixel independence in change detection of multi-scale remote sensing image, an unsupervised algorithm is proposed based on the combination between Dual-tree Complex Wavelet Transform (DT-CWT) and Markov random Field (MRF) model. This method first performs multi-scale decomposition for the difference image by the DT-CWT and extracts the change characteristics in high-frequency regions by using a MRF-based segmentation algorithm. Then our method estimates the final maximum a posterior (MAP) according to the segmentation algorithm of iterative condition model (ICM) based on fuzzy c-means(FCM) after reconstructing the high-frequency and low-frequency sub-bands of each layer respectively. Finally, the method fuses the above segmentation results of each layer by using the fusion rule proposed to obtain the mask of the final change detection result. The results of experiment prove that the method proposed is of a higher precision and of predominant robustness properties.

Nanoplasmonic molecular ruler for nuclease activity and DNA footprinting

DOEpatents

Chen, Fanqing Frank; Liu, Gang L; Lee, Luke P

2013-10-29

This invention provides a nanoplasmonic molecular ruler, which can perform label-free and real-time monitoring of nucleic acid (e.g., DNA) length changes and perform nucleic acid footprinting. In various embodiments the ruler comprises a nucleic acid attached to a nanoparticle, such that changes in the nucleic acid length are detectable using surface plasmon resonance. The nanoplasmonic ruler provides a fast and convenient platform for mapping nucleic acid-protein interactions, for nuclease activity monitoring, and for other footprinting related methods.

Damage diagnosis algorithm using a sequential change point detection method with an unknown distribution for damage

NASA Astrophysics Data System (ADS)

Noh, Hae Young; Rajagopal, Ram; Kiremidjian, Anne S.

2012-04-01

This paper introduces a damage diagnosis algorithm for civil structures that uses a sequential change point detection method for the cases where the post-damage feature distribution is unknown a priori. This algorithm extracts features from structural vibration data using time-series analysis and then declares damage using the change point detection method. The change point detection method asymptotically minimizes detection delay for a given false alarm rate. The conventional method uses the known pre- and post-damage feature distributions to perform a sequential hypothesis test. In practice, however, the post-damage distribution is unlikely to be known a priori. Therefore, our algorithm estimates and updates this distribution as data are collected using the maximum likelihood and the Bayesian methods. We also applied an approximate method to reduce the computation load and memory requirement associated with the estimation. The algorithm is validated using multiple sets of simulated data and a set of experimental data collected from a four-story steel special moment-resisting frame. Our algorithm was able to estimate the post-damage distribution consistently and resulted in detection delays only a few seconds longer than the delays from the conventional method that assumes we know the post-damage feature distribution. We confirmed that the Bayesian method is particularly efficient in declaring damage with minimal memory requirement, but the maximum likelihood method provides an insightful heuristic approach.

Field validation of protocols developed to evaluate in-line mastitis detection systems.

PubMed

Kamphuis, C; Dela Rue, B T; Eastwood, C R

2016-02-01

This paper reports on a field validation of previously developed protocols for evaluating the performance of in-line mastitis-detection systems. The protocols outlined 2 requirements of these systems: (1) to detect cows with clinical mastitis (CM) promptly and accurately to enable timely and appropriate treatment and (2) to identify cows with high somatic cell count (SCC) to manage bulk milk SCC levels. Gold standard measures, evaluation tests, performance measures, and performance targets were proposed. The current study validated the protocols on commercial dairy farms with automated in-line mastitis-detection systems using both electrical conductivity (EC) and SCC sensor systems that both monitor at whole-udder level. The protocol for requirement 1 was applied on 3 commercial farms. For requirement 2, the protocol was applied on 6 farms; 3 of them had low bulk milk SCC (128×10(3) cells/mL) and were the same farms as used for field evaluation of requirement 1. Three farms with high bulk milk SCC (270×10(3) cells/mL) were additionally enrolled. The field evaluation methodology and results were presented at a workshop including representation from 7 international suppliers of in-line mastitis-detection systems. Feedback was sought on the acceptance of standardized performance evaluation protocols and recommended refinements to the protocols. Although the methodology for requirement 1 was relatively labor intensive and required organizational skills over an extended period, no major issues were encountered during the field validation of both protocols. The validation, thus, proved the protocols to be practical. Also, no changes to the data collection process were recommended by the technology supplier representatives. However, 4 recommendations were made to refine the protocols: inclusion of an additional analysis that ignores small (low-density) clot observations in the definition of CM, extension of the time window from 4 to 5 milkings for timely alerts for CM, setting a maximum number of 10 milkings for the time window to detect a CM episode, and presentation of sensitivity for a larger range of false alerts per 1,000 milkings replacing minimum performance targets. The recommended refinements are discussed with suggested changes to the original protocols. The information presented is intended to inform further debate toward achieving international agreement on standard protocols to evaluate performance of in-line mastitis-detection systems. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Detection of α-fetoprotein in human serum using carbon nanotube transistor

NASA Astrophysics Data System (ADS)

So, Hye-Mi; Park, Dong-Won; Lee, Seong-Kyu; Kim, Beom Soo; Chang, Hyunju; Lee, Jeong-O.

2009-03-01

We have fabricated antibody-coated carbon nanotube field effect transistor (CNT-FET) sensor for the detection of α-fetoprotein (AFP), single chain glycoprotein of 70 kDa that is normally expressed in the fetal liver, in human serum. The AFP-specific antibodies were immobilized on CNT with linker molecule such as pyrenebutyric acid N-hydroxysuccinimide ester. To prevent nonspecific adsorption of antigen, we performed blocking procedure using bovine serum albumin (BSA). Antibody-antigen binding was determined by measuring electrical conductance change of FET and took an average of thereshold voltage change before and after binding. Also we checked concentration-dependent conductance change in human serum using both p-type SWNT-FETs and n-type SWNT-FETs.

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.

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.

Joint pain undergoes a transition in accordance with signal changes of bones detected by MRI in hip osteoarthritis.

PubMed

Kamimura, Mikio; Nakamura, Yukio; Ikegami, Shota; Uchiyama, Shigeharu; Kato, Hiroyuki

2013-01-01

In this study, we aimed to investigate whether joint pain is derived from cartilage or bone alterations. We reviewed 23 hip joints of 21 patients with primary hip osteoarthritis (OA), which were classified into Kellgren-Laurence (KL) grading I to IV. Plain radiographs and magnetic resonance imaging (MRI) were obtained from all of the 23 joints. Two of the 21 patients had bilateral hip OA. Pain was assessed based on the pain scale of Denis. A Welch t test was performed for age, height, weight, body mass index, bone mineral density, and a Mann-Whitney U test was performed for KL grading. Four of 8 hip joints with pain and OA showed broad signal changes detected by MRI. Fourteen hip joints without pain, but with OA did not show broad signal changes by MRI. Collectively, MRI analyses showed that broad signal changes in OA cases without joint pain or with a slight degree of joint pain were not observed, while broad signal changes were observed in OA cases with deteriorated joint pain. Our findings suggest that hip joint pain might be associated with bone signal alterations in the hips of OA patients.

Effects of spatial cues on color-change detection in humans

PubMed Central

Herman, James P.; Bogadhi, Amarender R.; Krauzlis, Richard J.

2015-01-01

Studies of covert spatial attention have largely used motion, orientation, and contrast stimuli as these features are fundamental components of vision. The feature dimension of color is also fundamental to visual perception, particularly for catarrhine primates, and yet very little is known about the effects of spatial attention on color perception. Here we present results using novel dynamic color stimuli in both discrimination and color-change detection tasks. We find that our stimuli yield comparable discrimination thresholds to those obtained with static stimuli. Further, we find that an informative spatial cue improves performance and speeds response time in a color-change detection task compared with an uncued condition, similar to what has been demonstrated for motion, orientation, and contrast stimuli. Our results demonstrate the use of dynamic color stimuli for an established psychophysical task and show that color stimuli are well suited to the study of spatial attention. PMID:26047359

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.

Urban Change Detection of Pingtan City based on Bi-temporal Remote Sensing Images

NASA Astrophysics Data System (ADS)

Degang, JIANG; Jinyan, XU; Yikang, GAO

2017-02-01

In this paper, a pair of SPOT 5-6 images with the resolution of 0.5m is selected. An object-oriented classification method is used to the two images and five classes of ground features were identified as man-made objects, farmland, forest, waterbody and unutilized land. An auxiliary ASTER GDEM was used to improve the classification accuracy. And the change detection based on the classification results was performed. Accuracy assessment was carried out finally. Consequently, satisfactory results were obtained. The results show that great changes of the Pingtan city have been detected as the expansion of the city area and the intensity increase of man-made buildings, roads and other infrastructures with the establishment of Pingtan comprehensive experimental zone. Wide range of open sea area along the island coast zones has been reclaimed for port and CBDs construction.

The detection of higher-order acoustic transitions is reflected in the N1 ERP.

PubMed

Weise, Annekathrin; Schröger, Erich; Horváth, János

2018-01-30

The auditory system features various types of dedicated change detectors enabling the rapid parsing of auditory stimulation into distinct events. The activity of such detectors is reflected by the N1 ERP. Interestingly, certain acoustic transitions show an asymmetric N1 elicitation pattern: whereas first-order transitions (e.g., a change from a segment of constant frequency to a frequency glide [c-to-g change]) elicit N1, higher-order transitions (e.g., glide-to-constant [g-to-c] changes) do not. Consensus attributes this asymmetry to the absence of any available sensory mechanism that is able to rapidly detect higher-order changes. In contrast, our study provides compelling evidence for such a mechanism. We collected electrophysiological and behavioral data in a transient-detection paradigm. In each condition, a random (50%-50%) sequence of two types of tones occurred, which did or did not contain a transition (e.g., c-to-g and constant stimuli or g-to-c and glide tones). Additionally, the rate of pitch change of the glide varied (i.e., 10 vs. 40 semitones per second) in order to increase the number of responding neural assemblies. The rate manipulation modulated transient ERPs and behavioral detection performance for g-to-c transitions much stronger than for c-to-g transitions. The topographic and tomographic analyses suggest that the N1 response to c-to-g and also to g-to-c transitions emerged from the superior temporal gyrus. This strongly supports a sensory mechanism that allows the fast detection of higher-order changes. © 2018 Society for Psychophysiological Research.

[The advantages of early midtrimester targeted fetal systematic organ screening for the detection of fetal anomalies--will a global change start in Israel?].

PubMed

Bronshtein, Moshe; Solt, Ido; Blumenfeld, Zeev

2014-06-01

Despite more than three decades of universal popularity of fetal sonography as an integral part of pregnancy evaluation, there is still no unequivocal agreement regarding the optimal dating of fetal sonographic screening and the type of ultrasound (transvaginal vs abdominal). TransvaginaL systematic sonography at 14-17 weeks for fetal organ screening. The evaluation of over 72.000 early (14-17 weeks) and late (18-24 weeks) fetal ultrasonographic systematic organ screenings revealed that 96% of the malformations are detectable in the early screening with an incidence of 1:50 gestations. Only 4% of the fetal anomalies are diagnosed later in pregnancy. Over 99% of the fetal cardiac anomalies are detectable in the early screening and most of them appear in low risk gestations. Therefore, we suggest a new platform of fetal sonographic evaluation and follow-up: The extensive systematic fetal organ screening should be performed by an expert sonographer who has been trained in the detection of fetal malformations, at 14-17 weeks gestation. This examination should also include fetal cardiac echography Three additional ultrasound examinations are suggested during pregnancy: the first, performed by the patient's obstetrician at 6-7 weeks for the exclusion of ectopic pregnancy, confirmation of fetal viability, dating, assessment of chorionicity in multiple gestations, and visualization of maternal adnexae. The other two, at 22-26 and 32-34 weeks, require less training and should be performed by an obstetrician who has been qualified in the sonographic detection of fetal anomalies. The advantages of early midtrimester targeted fetal systematic organ screening for the detection of fetal anomalies may dictate a global change.

Modified screening and ranking algorithm for copy number variation detection.

PubMed

Xiao, Feifei; Min, Xiaoyi; Zhang, Heping

2015-05-01

Copy number variation (CNV) is a type of structural variation, usually defined as genomic segments that are 1 kb or larger, which present variable copy numbers when compared with a reference genome. The screening and ranking algorithm (SaRa) was recently proposed as an efficient approach for multiple change-points detection, which can be applied to CNV detection. However, some practical issues arise from application of SaRa to single nucleotide polymorphism data. In this study, we propose a modified SaRa on CNV detection to address these issues. First, we use the quantile normalization on the original intensities to guarantee that the normal mean model-based SaRa is a robust method. Second, a novel normal mixture model coupled with a modified Bayesian information criterion is proposed for candidate change-point selection and further clustering the potential CNV segments to copy number states. Simulations revealed that the modified SaRa became a robust method for identifying change-points and achieved better performance than the circular binary segmentation (CBS) method. By applying the modified SaRa to real data from the HapMap project, we illustrated its performance on detecting CNV segments. In conclusion, our modified SaRa method improves SaRa theoretically and numerically, for identifying CNVs with high-throughput genotyping data. The modSaRa package is implemented in R program and freely available at http://c2s2.yale.edu/software/modSaRa. Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Test-retest reliability and minimal detectable change scores for the timed "up & go" test, the six-minute walk test, and gait speed in people with Alzheimer disease.

PubMed

Ries, Julie D; Echternach, John L; Nof, Leah; Gagnon Blodgett, Michelle

2009-06-01

With the increasing incidence of Alzheimer disease (AD), determining the validity and reliability of outcome measures for people with this disease is necessary. The goals of this study were to assess test-retest reliability of data for the Timed "Up & Go" Test (TUG), the Six-Minute Walk Test (6MWT), and gait speed and to calculate minimal detectable change (MDC) scores for each outcome measure. Performance differences between groups with mild to moderate AD and moderately severe to severe AD (as determined by the Functional Assessment Staging [FAST] scale) were studied. This was a prospective, nonexperimental, descriptive methodological study. Background data collected for 51 people with AD included: use of an assistive device, Mini-Mental Status Examination scores, and FAST scale scores. Each participant engaged in 2 test sessions, separated by a 30- to 60-minute rest period, which included 2 TUG trials, 1 6MWT trial, and 2 gait speed trials using a computerized gait assessment system. A specific cuing protocol was followed to achieve optimal performance during test sessions. Test-retest reliability values for the TUG, the 6MWT, and gait speed were high for all participants together and for the mild to moderate AD and moderately severe to severe AD groups separately (intraclass correlation coefficients > or = .973); however, individual variability of performance also was high. Calculated MDC scores at the 90% confidence interval were: TUG=4.09 seconds, 6MWT=33.5 m (110 ft), and gait speed=9.4 cm/s. The 2 groups were significantly different in performance of clinical tests, with the participants who were more cognitively impaired being more physically and functionally impaired. A single researcher for data collection limited sample numbers and prohibited blinding to dementia level. The TUG, the 6MWT, and gait speed are reliable outcome measures for use with people with AD, recognizing that individual variability of performance is high. Minimal detectable change scores at the 90% confidence interval can be used to assess change in performance over time and the impact of treatment.

Detecting population recovery using gametic disequilibrium-based effective population size estimates

Treesearch

David A. Tallmon; Robin S. Waples; Dave Gregovich; Michael K. Schwartz

2012-01-01

Recovering populations often must meet specific growth rate or abundance targets before their legal status can be changed from endangered or threatened. While the efficacy, power, and performance of population metrics to infer trends in declining populations has received considerable attention, how these same metrics perform when populations are increasing is less...

The Future of Performance-Enhancing Substances in Sport.

ERIC Educational Resources Information Center

Bahrke, Michael S.; Yesalis, Charles E.

2002-01-01

Discusses the use of performance-enhancing substances in athletics, focusing on the use-detection race, burgeoning new products and off-label uses, and ways to combat the problem. The article suggests drug education programs, particularly those for adolescent athletes, have the potential to change behavior and be more cost-effective than further…

A test for a shift in the boundary of the geographical range of a species.

PubMed

Solow, Andrew; Beet, Andrew; Roll, Uri; Stone, Lewi

2014-02-01

One predicted impact of climate change is a poleward shift in the boundaries of species ranges. Existing methods for identifying such a boundary shift based on changes in the observed pattern of occupancy within a grid of cells are sensitive to changes in the overall rate of sightings and their latitudinal distribution that are unconnected to a boundary shift. A formal test for a boundary shift is described that allows for such changes. The test is applied to detect northward shifts in the northern boundary of the Essex skipper (Thymelicus lineola) butterfly and the European goldfinch (Carduelis carduelis) in Great Britain. A shift is detected in the latter case but not in the former. Results from a simulation study are presented showing that the test performs well.

Prestimulus EEG Power Predicts Conscious Awareness But Not Objective Visual Performance

PubMed Central

Veniero, Domenica

2017-01-01

Abstract Prestimulus oscillatory neural activity has been linked to perceptual outcomes during performance of psychophysical detection and discrimination tasks. Specifically, the power and phase of low frequency oscillations have been found to predict whether an upcoming weak visual target will be detected or not. However, the mechanisms by which baseline oscillatory activity influences perception remain unclear. Recent studies suggest that the frequently reported negative relationship between α power and stimulus detection may be explained by changes in detection criterion (i.e., increased target present responses regardless of whether the target was present/absent) driven by the state of neural excitability, rather than changes in visual sensitivity (i.e., more veridical percepts). Here, we recorded EEG while human participants performed a luminance discrimination task on perithreshold stimuli in combination with single-trial ratings of perceptual awareness. Our aim was to investigate whether the power and/or phase of prestimulus oscillatory activity predict discrimination accuracy and/or perceptual awareness on a trial-by-trial basis. Prestimulus power (3–28 Hz) was inversely related to perceptual awareness ratings (i.e., higher ratings in states of low prestimulus power/high excitability) but did not predict discrimination accuracy. In contrast, prestimulus oscillatory phase did not predict awareness ratings or accuracy in any frequency band. These results provide evidence that prestimulus α power influences the level of subjective awareness of threshold visual stimuli but does not influence visual sensitivity when a decision has to be made regarding stimulus features. Hence, we find a clear dissociation between the influence of ongoing neural activity on conscious awareness and objective performance. PMID:29255794

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.

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%.

Changes in cerebro-cerebellar interaction during response inhibition after performance improvement.

PubMed

Hirose, Satoshi; Jimura, Koji; Kunimatsu, Akira; Abe, Osamu; Ohtomo, Kuni; Miyashita, Yasushi; Konishi, Seiki

2014-10-01

It has been demonstrated that motor learning is supported by the cerebellum and the cerebro-cerebellar interaction. Response inhibition involves motor responses and the higher-order inhibition that controls the motor responses. In this functional MRI study, we measured the cerebro-cerebellar interaction during response inhibition in two separate days of task performance, and detected the changes in the interaction following performance improvement. Behaviorally, performance improved in the second day, compared to the first day. The psycho-physiological interaction (PPI) analysis revealed the interaction decrease from the right inferior frontal cortex (rIFC) to the cerebellum (lobule VII or VI). It was also revealed that the interaction increased from the same cerebellar region to the primary motor area. These results suggest the involvement of the cerebellum in response inhibition, and raise the possibility that the performance improvement was supported by the changes in the cerebro-cerebellar interaction. Copyright © 2014 Elsevier Inc. All rights reserved.

Effect of structure on sensing performance of a target induced signaling probe shifting DNA-based (TISPS-DNA) sensor.

PubMed

Yu, Xiang; Yu, Zhigang; Li, Fengqin; Xu, Yanmei; He, Xunjun; Xu, Lan; Shi, Wenbing; Zhang, Guiling; Yan, Hong

2017-05-15

A type of "signal on" displacement-based sensors named target induced signaling probe shifting DNA-based (TISPS-DNA) sensor were developed for a designated DNA detection. The signaling mechanism of the signaling probe (SP) shifting different from the classical conformation/flexibility change mode endows the sensor with high sensitivity. Through using thiolated or no thiolated capturing probe (CP), two 3-probe sensing structures, sensor-1 and sensor-2, were designed and constructed. The systematical comparing research results show that both sensors exhibit some similarities or big differences in sensing performance. On the one hand, the similarity in structures determines the similarity in some aspects of signaling mechanism, background signal, signal changing form, anti-fouling ability and versatility; on the other hand, the slight difference in structures also results in two opposite hybridization modes of gradual increasing resistance and gradual decreasing resistance which can affect the hybridization efficiency between the assistant probe (AP) and the SP, further producing some big differences in sensing performance, for example, apparently different signal enhancement (SE) change, point mutation discrimination ability and response speed. Under the optimized fabrication and detection conditions, both sensors feature high sensitivity for target DNAs with the detection limits of ∼10 fM for sensor-1 and ∼7 fM for sensor-2, respectively. Among many acquired sensing virtues, the sensor-1 shows a peculiar specificity adjustability which is also a highlight in this work. Copyright © 2017 Elsevier B.V. All rights reserved.

Trend Change Detection in NDVI Time Series: Effects of Inter-Annual Variability and Methodology

NASA Technical Reports Server (NTRS)

Forkel, Matthias; Carvalhais, Nuno; Verbesselt, Jan; Mahecha, Miguel D.; Neigh, Christopher S.R.; Reichstein, Markus

2013-01-01

Changing trends in ecosystem productivity can be quantified using satellite observations of Normalized Difference Vegetation Index (NDVI). However, the estimation of trends from NDVI time series differs substantially depending on analyzed satellite dataset, the corresponding spatiotemporal resolution, and the applied statistical method. Here we compare the performance of a wide range of trend estimation methods and demonstrate that performance decreases with increasing inter-annual variability in the NDVI time series. Trend slope estimates based on annual aggregated time series or based on a seasonal-trend model show better performances than methods that remove the seasonal cycle of the time series. A breakpoint detection analysis reveals that an overestimation of breakpoints in NDVI trends can result in wrong or even opposite trend estimates. Based on our results, we give practical recommendations for the application of trend methods on long-term NDVI time series. Particularly, we apply and compare different methods on NDVI time series in Alaska, where both greening and browning trends have been previously observed. Here, the multi-method uncertainty of NDVI trends is quantified through the application of the different trend estimation methods. Our results indicate that greening NDVI trends in Alaska are more spatially and temporally prevalent than browning trends. We also show that detected breakpoints in NDVI trends tend to coincide with large fires. Overall, our analyses demonstrate that seasonal trend methods need to be improved against inter-annual variability to quantify changing trends in ecosystem productivity with higher accuracy.

Vision restoration through extrastriate stimulation in patients with visual field defects: a double-blind and randomized experimental study.

PubMed

Jobke, Sandra; Kasten, Erich; Sabel, Bernhard A

2009-01-01

. Vision restoration therapy (VRT) to treat visual field defects used single-point visual stimulation in areas of residual vision up to now. The question arises if the efficiency of restoration can be increased when the entire region of blindness is trained by a visual stimulus aimed at activating extrastriate pathways (extrastriate VRT). . In this crossover study, 18 patients with visual field defects with prior VRT experience were treated with 2 training paradigms. Group 1 (n = 8) first used extrastriate VRT followed by conventional standard VRT. Group 2 (n = 10) trained in reverse order. Visual field size was assessed with computer-based perimetry and subjective vision with the National Eye Institute Visual Function Questionnaire (NEI-VFQ). . In group 1, stimulus detection in high-resolution perimetry (HRP) improved by 5.9% (P < .01) after extrastriate VRT. After the second training period (standard VRT), detection further improved by 1.8% (P = .093). In group 2, detection performance improved after standard VRT by 2.9% (P < .05) and after extrastriate VRT by 2.9% (P < .05). Detection performance increased twice as much after extrastriate VRT (4.2%) than after standard VRT (2.4%; P < .05). All changes in fixation performance were unrelated to detection improvements. NEI-VFQ did not show any significant changes. . Greater improvement after extrastriate VRT is interpreted as an activation of extrastriate pathways by massive "spiral-like" stimulation. These pathways bypass the damaged visual cortex, stimulating extrastriate cortical regions, and are thought to be involved in blindsight.

Applications of remote sensing, volume 3

NASA Technical Reports Server (NTRS)

Landgrebe, D. A. (Principal Investigator)

1977-01-01

The author has identified the following significant results. Of the four change detection techniques (post classification comparison, delta data, spectral/temporal, and layered spectral temporal), the post classification comparison was selected for further development. This was based upon test performances of the four change detection method, straightforwardness of the procedures, and the output products desired. A standardized modified, supervised classification procedure for analyzing the Texas coastal zone data was compiled. This procedure was developed in order that all quadrangles in the study are would be classified using similar analysis techniques to allow for meaningful comparisons and evaluations of the classifications.

Incidental learning of probability information is differentially affected by the type of visual working memory representation.

PubMed

van Lamsweerde, Amanda E; Beck, Melissa R

2015-12-01

In this study, we investigated whether the ability to learn probability information is affected by the type of representation held in visual working memory. Across 4 experiments, participants detected changes to displays of coloured shapes. While participants detected changes in 1 dimension (e.g., colour), a feature from a second, nonchanging dimension (e.g., shape) predicted which object was most likely to change. In Experiments 1 and 3, items could be grouped by similarity in the changing dimension across items (e.g., colours and shapes were repeated in the display), while in Experiments 2 and 4 items could not be grouped by similarity (all features were unique). Probability information from the predictive dimension was learned and used to increase performance, but only when all of the features within a display were unique (Experiments 2 and 4). When it was possible to group by feature similarity in the changing dimension (e.g., 2 blue objects appeared within an array), participants were unable to learn probability information and use it to improve performance (Experiments 1 and 3). The results suggest that probability information can be learned in a dimension that is not explicitly task-relevant, but only when the probability information is represented with the changing dimension in visual working memory. (c) 2015 APA, all rights reserved).

Analyses of Inhomogeneities in Radiosonde Temperature and Humidity Time Series.

NASA Astrophysics Data System (ADS)

Zhai, Panmao; Eskridge, Robert E.

1996-04-01

Twice daily radiosonde data from selected stations in the United States (period 1948 to 1990) and China (period 1958 to 1990) were sorted into time series. These stations have one sounding taken in darkness and the other in sunlight. The analysis shows that the 0000 and 1200 UTC time series are highly correlated. Therefore, the Easterling and Peterson technique was tested on the 0000 and 1200 time series to detect inhomogeneities and to estimate the size of the biases. Discontinuities were detected using the difference series created from the 0000 and 1200 UTC time series. To establish that the detected bias was significant, a t test was performed to confirm that the change occurs in the daytime series but not in the nighttime series.Both U.S. and Chinese radiosonde temperature and humidity data include inhomogeneities caused by changes in radiosonde sensors and observation times. The U.S. humidity data have inhomogeneities that were caused by instrument changes and the censoring of data. The practice of reporting relative humidity as 19% when it is lower than 20% or the temperature is below 40°C is called censoring. This combination of procedural and instrument changes makes the detection of biases and adjustment of the data very difficult. In the Chinese temperatures, them are inhomogeneities related to a change in the radiation correction procedure.Test results demonstrate that a modified Easterling and Peterson method is suitable for use in detecting and adjusting time series radiosonde data.Accurate stations histories are very desirable. Stations histories can confirm that detected inhomogeneities are related to instrument or procedural changes. Adjustments can then he made to the data with some confidence.

A Meta-analytic Review of Non-specific Effects in Randomized Controlled Trials of Cognitive Remediation for Schizophrenia.

PubMed

Radhakrishnan, Rajiv; Kiluk, Brian D; Tsai, Jack

2016-03-01

Cognitive remediation (CR) has been found to improve cognitive performance among adults with schizophrenia in randomized controlled trials (RCTs). However, improvements in cognitive performance are often observed in the control groups of RCTs as well. There has been no comprehensive examination of change in control groups for CR, which may inform trial methodology and improve our understanding of measured outcomes for cognitive remediation. In this meta-analysis, we calculated pre-post change in cognitive test performance within control groups of RCTs in 32 CR trials (n = 794 participants) published between 1970 and 2011, and examined the association between pre-post change and sample size, duration of treatment, type of control group, and participants' age, intelligence, duration of illness, and psychiatric symptoms. Results showed that control groups in CR trials showed small effect size changes (Cohen's d = 0.12 ± 0.16) in cognitive test performance over the trial duration. Study characteristics associated with pre-post change included participant age and sample size. These findings suggest attention to change in control groups may help improve detection of cognitive remediation effects for schizophrenia.

Change detection in synthetic aperture radar images based on image fusion and fuzzy clustering.

PubMed

Gong, Maoguo; Zhou, Zhiqiang; Ma, Jingjing

2012-04-01

This paper presents an unsupervised distribution-free change detection approach for synthetic aperture radar (SAR) images based on an image fusion strategy and a novel fuzzy clustering algorithm. The image fusion technique is introduced to generate a difference image by using complementary information from a mean-ratio image and a log-ratio image. In order to restrain the background information and enhance the information of changed regions in the fused difference image, wavelet fusion rules based on an average operator and minimum local area energy are chosen to fuse the wavelet coefficients for a low-frequency band and a high-frequency band, respectively. A reformulated fuzzy local-information C-means clustering algorithm is proposed for classifying changed and unchanged regions in the fused difference image. It incorporates the information about spatial context in a novel fuzzy way for the purpose of enhancing the changed information and of reducing the effect of speckle noise. Experiments on real SAR images show that the image fusion strategy integrates the advantages of the log-ratio operator and the mean-ratio operator and gains a better performance. The change detection results obtained by the improved fuzzy clustering algorithm exhibited lower error than its preexistences.

IMPACTS OF VEGETATION DYNAMICS ON THE IDENTIFICATION OF LAND COVER CHANGE IN A BIOLOGICALLY COMPLEX COMMUNITY IN NORTH CAROLINA, USA

EPA Science Inventory

A land-cover (LC) change detection experiment was performed in the biologically complex landscape of the Neuse Rive Basin (NRB), NC using Landsat 5 and 7 imagery collected in May of 1993 and 2000. Methods included pixel-wise Normalized Difference Vegetation Index (NDVI) and Mult...

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

A New Statistic for Detection of Aberrant Answer Changes

ERIC Educational Resources Information Center

Sinharay, Sandip; Duong, Minh Q.; Wood, Scott W.

2017-01-01

As noted by Fremer and Olson, analysis of answer changes is often used to investigate testing irregularities because the analysis is readily performed and has proven its value in practice. Researchers such as Belov, Sinharay and Johnson, van der Linden and Jeon, van der Linden and Lewis, and Wollack, Cohen, and Eckerly have suggested several…

Power estimation of martial arts movement with different physical, mood, and behavior using motion capture camera

NASA Astrophysics Data System (ADS)

Awang Soh, Ahmad Afiq Sabqi; Mat Jafri, Mohd Zubir; Azraai, Nur Zaidi

2017-07-01

In Malay world, there is a spirit traditional ritual where they use it as healing practices or for normal life. Malay martial arts (silat) also is not exceptional where some branch of silat have spirit traditional ritual where they said can help them in combat. In this paper, we will not use any ritual, instead we will use some medicinal and environment change when they are performing. There will be 2 performers (fighter) selected, one of them have an experience in martial arts training and another performer does not have experience. Motion Capture (MOCAP) camera will help observe and analyze this move. 8 cameras have been placed in the MOCAP room 2 on each side of the wall facing toward the center of the room from every angle. This will help prevent the loss detection of a marker that been stamped on the limb of a performer. Passive marker has been used where it will reflect the infrared to the camera sensor. Infrared is generated by the source around the camera lens. A 60 kg punching bag was hung on the iron bar function as the target for the performer when throws a punch. Markers also have been stamped on the punching bag so we can detect the movement how far can it swing when hit by the performer. 2 performers will perform 2 moves each with the same position and posture. For every 2 moves, we have made the environment change without the performer notice about it. The first 2 punch with normal environment, second part we have played a positive music to change the performer's mood and third part we have put a medicine (cream/oil) on the skin of the performer. This medicine will make the skin feel a little bit hot. This process repeated to another performer with no experience. The position of this marker analyzed by the Cortex Motion Analysis software where from this data, we can estimate the kinetics and kinematics of the performer. It shows that the increase of kinetics for every part because of the change in the environment, and different result for the 2 performers.

Do Self-Assessments Work to Detect Workshop Success? An Analysis of Argument and Recommendation by D'Eon et al

ERIC Educational Resources Information Center

Lam, Tony C. M.

2009-01-01

D'Eon et al. concluded that change in performance self-assessment means from before to after a workshop can detect workshop success in their and other situations. In this commentary, their recommendation is refuted by showing that (a) self-assessments with balanced over- and underestimations are still biased and should not be used to evaluate…

Evaluation of Neutron Elastic Scatter (NES) technique for detection of graphitic corrosion in gas cast iron pipe. Final report, March 1996-April 1997

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

Charatis, G.; Hugg, E.; McEllistrem, M.

1997-04-01

PENETRON, Inc., in two phases, demonstrated the effectiveness of its Neutron elastic Scatter (NES) techniques in detecting the change in the carbon weight percentage (CWt%) as a measure of corrosion in gray cast iron pipe. In Phase I, experiments were performed with synthetic standards supplied by IIT Research Institute (IITRI) to test the applicability of the NES techniques. Irradiation experiments performed at the University of Kentucky showed that CWt% could be detected, ranging from 1.6% to 13%, within an uncertainty of around 4%. In Phase II, experiments were performed on seven (7) corroded pipe sections supplied by MichCon. Tests weremore » made on pipe sliced lengthwise into quarter sections, and in re-assembled whole pipe sections. X-ray films of the quarter sections indicated probable areas of corrosion for each quarter section.« less

Study to develop improved methods to detect leakage in fluid systems, phase 2

NASA Technical Reports Server (NTRS)

Janus, J. C.; Cimerman, I.

1971-01-01

An ultrasonic contact sensor engineering prototype leak detection system was developed and its capabilities under cryogenic operations demonstrated. The results from tests indicate that the transducer performed well on liquid hydrogen plumbing, that flow and valve actuation could be monitored, and that the phase change from gaseous to liquid hydrogen could be detected by the externally mounted transducers. Tests also demonstrate the ability of the system to detect internal leaks past valve seats and to function as a flow meter. Such a system demonstrates that it is not necessary to break into welded systems to locate internal leaks.

Better Cognitive Performance Is Associated With the Combination of High Trait Mindfulness and Low Trait Anxiety.

PubMed

Jaiswal, Satish; Tsai, Shao-Yang; Juan, Chi-Hung; Liang, Wei-Kuang; Muggleton, Neil G

2018-01-01

There are several ways in which cognitive and neurophysiological parameters have been consistently used to explain the variability in cognitive ability between people. However, little has been done to explore how such cognitive abilities are influenced by differences in personality traits. Dispositional mindfulness and anxiety are two inversely linked traits that have been independently attributed to a range of cognitive functions. The current study investigated these two traits in combination along with measures of the attentional network, cognitive inhibition, and visual working memory (VWM) capacity. A total of 392 prospective participants were screened to select two experimental groups each of 30 healthy young adults, with one having high mindfulness and low anxiety (HMLA) and the second having low mindfulness and high anxiety (LMHA). The groups performed an attentional network task, a color Stroop task, and a change detection test of VWM capacity. Results showed that the HMLA group was more accurate than the LMHA group on the Stroop and change detection tasks. Additionally, the HMLA group was more sensitive in detecting changes and had a higher WMC than the LMHA group. This research adds to the literature that has investigated mindfulness and anxiety independently with a comprehensive investigation of the effects of these two traits in conjunction on executive function.

An investigation of the trade-off between the count level and image quality in myocardial perfusion SPECT using simulated images: the effects of statistical noise and object variability on defect detectability

NASA Astrophysics Data System (ADS)

He, Xin; Links, Jonathan M.; Frey, Eric C.

2010-09-01

Quantum noise as well as anatomic and uptake variability in patient populations limits observer performance on a defect detection task in myocardial perfusion SPECT (MPS). The goal of this study was to investigate the relative importance of these two effects by varying acquisition time, which determines the count level, and assessing the change in performance on a myocardial perfusion (MP) defect detection task using both mathematical and human observers. We generated ten sets of projections of a simulated patient population with count levels ranging from 1/128 to around 15 times a typical clinical count level to simulate different levels of quantum noise. For the simulated population we modeled variations in patient, heart and defect size, heart orientation and shape, defect location, organ uptake ratio, etc. The projection data were reconstructed using the OS-EM algorithm with no compensation or with attenuation, detector response and scatter compensation (ADS). The images were then post-filtered and reoriented to generate short-axis slices. A channelized Hotelling observer (CHO) was applied to the short-axis images, and the area under the receiver operating characteristics (ROC) curve (AUC) was computed. For each noise level and reconstruction method, we optimized the number of iterations and cutoff frequencies of the Butterworth filter to maximize the AUC. Using the images obtained with the optimal iteration and cutoff frequency and ADS compensation, we performed human observer studies for four count levels to validate the CHO results. Both CHO and human observer studies demonstrated that observer performance was dependent on the relative magnitude of the quantum noise and the patient variation. When the count level was high, the patient variation dominated, and the AUC increased very slowly with changes in the count level for the same level of anatomic variability. When the count level was low, however, quantum noise dominated, and changes in the count level resulted in large changes in the AUC. This behavior agreed with a theoretical expression for the AUC as a function of quantum and anatomical noise levels. The results of this study demonstrate the importance of the tradeoff between anatomical and quantum noise in determining observer performance. For myocardial perfusion imaging, it indicates that, at current clinical count levels, there is some room to reduce acquisition time or injected activity without substantially degrading performance on myocardial perfusion defect detection.

Advanced selective non-invasive ketone body detection sensors based on new ionophores

NASA Astrophysics Data System (ADS)

Sathyapalan, A.; Sarswat, P. K.; Zhu, Y.; Free, M. L.

2014-12-01

New molecules and methods were examined that can be used to detect trace level ketone bodies. Diseases such as type 1 diabetes, childhood hypo-glycaemia-growth hormone deficiency, toxic inhalation, and body metabolism changes are linked with ketone bodies concentration. Here we introduce, selective ketone body detection sensors based on small, environmentally friendly organic molecules with Lewis acid additives. Density functional theory (DFT) simulation of the sensor molecules (Bromo-acetonaphthone tungstate (BANT) and acetonaphthophenyl ether propiono hydroxyl tungstate (APPHT)), indicated a fully relaxed geometry without symmetry attributes and specific coordination which enhances ketone bodies sensitivity. A portable sensing unit was made in which detection media containing ketone bodies at low concentration and new molecules show color change in visible light as well as unique irradiance during UV illumination. RGB analysis, electrochemical tests, SEM characterization, FTIR, absorbance and emission spectroscopy were also performed in order to validate the ketone sensitivity of these new molecules.

Thin film sensor materials for detection of Nitro-Aromatic explosives

NASA Astrophysics Data System (ADS)

Ramdasi, Dipali; Mudhalwadkar, Rohini

2018-03-01

Many countries have experienced terrorist activities and innocent people have suffered. Timely detection of explosives can avoid this situation. This paper targets the detection of Nitrobenzene and Nitrotoluene, which are nitroaromatic compounds possessing explosive properties. As direct sensors for detecting these compounds are not available, Polyaniline based thin film sensors doped with palladium are developed using the spin coating technique. The response of the developed sensors is observed for varying concentrations of explosives. It is observed that zinc oxide based sensor is more sensitive to Nitrotoluene exhibiting a relative change in resistance of 0.78. The tungsten oxide sensor is more sensitive to Nitrobenzene with a relative change in resistance of 0.48. The sensor performance is assessed by measuring the response and recovery time. The cross sensitivity of the sensors is evaluated for ethanol, acetone and methanol which was observed as very low.

A dual-responsive colorimetric and fluorescent chemosensor based on diketopyrrolopyrrole derivative for naked-eye detection of Fe3 + and its practical application

NASA Astrophysics Data System (ADS)

Zhang, Shanshan; Sun, Tao; Xiao, Dejun; Yuan, Fang; Li, Tianduo; Wang, Enhua; Liu, Haixia; Niu, Qingfen

2018-01-01

A novel dual-responsive colorimetric and fluorescent chemosensor L based on diketopyrrolopyrrole derivative for Fe3 + detection was designed and synthesized. In presence of Fe3 +, sensor L displayed strong colorimetric response as amaranth to rose pink and significant fluorescence enhancement and chromogenic change, which served as a naked-eye indicator by an obvious color change from purple to red. The binding constant for L-Fe3 + complex was found as 2.4 × 104 with the lower detection limit of 14.3 nM. The sensing mechanism was investigated in detail by fluorescence measurements, IR and 1H NMR spectra. Sensor L for Fe3 + detection also exhibited high anti-interference performance, good reversibility, wide pH response range and instantaneous response time. Furthermore, the sensor L has been used to quantify Fe3 + ions in practical water samples with good recovery.

THz Pulse Detection by Multilayered GeTe/Sb2Te3.

PubMed

Makino, Kotaro; Kuromiya, Shota; Takano, Keisuke; Kato, Kosaku; Nakajima, Makoto; Saito, Yuta; Tominaga, Junji; Iida, Hitoshi; Kinoshita, Moto; Nakano, Takashi

2016-11-30

We proposed and demonstrated terahertz (THz) pulse detection by means of multilayered GeTe/Sb 2 Te 3 phase-change memory materials that are also known as a multilayer topological insulator-normal insulator (MTN) system. THz time-domain spectroscopy measurement was performed for MTN films with different multilayer repetitions as well as a conventional as-grown Ge-Te-Sb (GST) alloy film. It was found that MTNs absorb THz waves and that the absorption coefficient depends on the number of layers, while the as-grown GST alloy film was almost transparent for THz waves. Simple MTN-based THz detection devices were fabricated, and the THz-induced change in the current signal was measured when a DC bias voltage was applied between the electrodes. We confirmed that irradiation of THz pulse causes a decrease in the resistance of the MTNs. This result indicates that our devices are capable of THz detection.

Flexible feature-space-construction architecture and its VLSI implementation for multi-scale object detection

NASA Astrophysics Data System (ADS)

Luo, Aiwen; An, Fengwei; Zhang, Xiangyu; Chen, Lei; Huang, Zunkai; Jürgen Mattausch, Hans

2018-04-01

Feature extraction techniques are a cornerstone of object detection in computer-vision-based applications. The detection performance of vison-based detection systems is often degraded by, e.g., changes in the illumination intensity of the light source, foreground-background contrast variations or automatic gain control from the camera. In order to avoid such degradation effects, we present a block-based L1-norm-circuit architecture which is configurable for different image-cell sizes, cell-based feature descriptors and image resolutions according to customization parameters from the circuit input. The incorporated flexibility in both the image resolution and the cell size for multi-scale image pyramids leads to lower computational complexity and power consumption. Additionally, an object-detection prototype for performance evaluation in 65 nm CMOS implements the proposed L1-norm circuit together with a histogram of oriented gradients (HOG) descriptor and a support vector machine (SVM) classifier. The proposed parallel architecture with high hardware efficiency enables real-time processing, high detection robustness, small chip-core area as well as low power consumption for multi-scale object detection.

mecC-Harboring Methicillin-Resistant Staphylococcus aureus: Hiding in Plain Sight.

PubMed

Ford, Bradley A

2018-01-01

Previously there was scant data on the performance of laboratory testing to detect mecC -mediated beta-lactam resistance in Staphylococcus aureus Kriegeskorte and colleagues (J Clin Microbiol 56:e00826-17, 2018, https://doi.org/10.1128/JCM.00826-17) report the performance of various clinical tests for the detection of mecC -harboring methicillin-resistant S. aureus (MRSA), which failed to identify from 0 to 41% of tested mecC -harboring MRSA isolates. Changes in practice and new test development are necessary to address the challenge of mecC -harboring MRSA. Copyright © 2017 American Society for Microbiology.

Physiologically Relevant Changes in Serotonin Resolved by Fast Microdialysis

PubMed Central

2013-01-01

Online microdialysis is a sampling and detection method that enables continuous interrogation of extracellular molecules in freely moving subjects under behaviorally relevant conditions. A majority of recent publications using brain microdialysis in rodents report sample collection times of 20–30 min. These long sampling times are due, in part, to limitations in the detection sensitivity of high performance liquid chromatography (HPLC). By optimizing separation and detection conditions, we decreased the retention time of serotonin to 2.5 min and the detection threshold to 0.8 fmol. Sampling times were consequently reduced from 20 to 3 min per sample for online detection of serotonin (and dopamine) in brain dialysates using a commercial HPLC system. We developed a strategy to collect and to analyze dialysate samples continuously from two animals in tandem using the same instrument. Improvements in temporal resolution enabled elucidation of rapid changes in extracellular serotonin levels associated with mild stress and circadian rhythms. These dynamics would be difficult or impossible to differentiate using conventional microdialysis sampling rates. PMID:23614776

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.

Massively Parallel, Molecular Analysis Platform Developed Using a CMOS Integrated Circuit With Biological Nanopores

PubMed Central

Roever, Stefan

2012-01-01

A massively parallel, low cost molecular analysis platform will dramatically change the nature of protein, molecular and genomics research, DNA sequencing, and ultimately, molecular diagnostics. An integrated circuit (IC) with 264 sensors was fabricated using standard CMOS semiconductor processing technology. Each of these sensors is individually controlled with precision analog circuitry and is capable of single molecule measurements. Under electronic and software control, the IC was used to demonstrate the feasibility of creating and detecting lipid bilayers and biological nanopores using wild type α-hemolysin. The ability to dynamically create bilayers over each of the sensors will greatly accelerate pore development and pore mutation analysis. In addition, the noise performance of the IC was measured to be 30fA(rms). With this noise performance, single base detection of DNA was demonstrated using α-hemolysin. The data shows that a single molecule, electrical detection platform using biological nanopores can be operationalized and can ultimately scale to millions of sensors. Such a massively parallel platform will revolutionize molecular analysis and will completely change the field of molecular diagnostics in the future.

I. WORKING MEMORY CAPACITY IN CONTEXT: MODELING DYNAMIC PROCESSES OF BEHAVIOR, MEMORY, AND DEVELOPMENT.

PubMed

Simmering, Vanessa R

2016-09-01

Working memory is a vital cognitive skill that underlies a broad range of behaviors. Higher cognitive functions are reliably predicted by working memory measures from two domains: children's performance on complex span tasks, and infants' performance in looking paradigms. Despite the similar predictive power across these research areas, theories of working memory development have not connected these different task types and developmental periods. The current project takes a first step toward bridging this gap by presenting a process-oriented theory, focusing on two tasks designed to assess visual working memory capacity in infants (the change-preference task) versus children and adults (the change detection task). Previous studies have shown inconsistent results, with capacity estimates increasing from one to four items during infancy, but only two to three items during early childhood. A probable source of this discrepancy is the different task structures used with each age group, but prior theories were not sufficiently specific to explain how performance relates across tasks. The current theory focuses on cognitive dynamics, that is, how memory representations are formed, maintained, and used within specific task contexts over development. This theory was formalized in a computational model to generate three predictions: 1) capacity estimates in the change-preference task should continue to increase beyond infancy; 2) capacity estimates should be higher in the change-preference versus change detection task when tested within individuals; and 3) performance should correlate across tasks because both rely on the same underlying memory system. I also tested a fourth prediction, that development across tasks could be explained through increasing real-time stability, realized computationally as strengthening connectivity within the model. Results confirmed these predictions, supporting the cognitive dynamics account of performance and developmental changes in real-time stability. The monograph concludes with implications for understanding memory, behavior, and development in a broader range of cognitive development. © 2016 The Society for Research in Child Development, Inc.

Surface plasmon resonance biosensor for enzymatic detection of small analytes

NASA Astrophysics Data System (ADS)

Massumi Miyazaki, Celina; Makoto Shimizu, Flávio; Mejía-Salazar, J. R.; Oliveira, Osvaldo N., Jr.; Ferreira, Marystela

2017-04-01

Surface plasmon resonance (SPR) biosensing is based on the detection of small changes in the refractive index on a gold surface modified with molecular recognition materials, thus being mostly limited to detecting large molecules. In this paper, we report on a SPR biosensing platform suitable to detect small molecules by making use of the mediator-type enzyme microperoxidase-11 (MP11) in layer-by-layer films. By depositing a top layer of glucose oxidase or uricase, we were able to detect glucose or uric acid with limits of detection of 3.4 and 0.27 μmol l-1, respectively. Measurable SPR signals could be achieved because of the changes in polarizability of MP11, as it is oxidized upon interaction with the analyte. Confirmation of this hypothesis was obtained with finite difference time domain simulations, which also allowed us to discard the possible effects from film roughness changes observed in atomic force microscopy images. The main advantage of this mediator-type enzyme approach is in the simplicity of the experimental method that does not require an external potential, unlike similar approaches for SPR biosensing of small molecules. The detection limits reported here were achieved without optimizing the film architecture, and therefore the performance can in principle be further enhanced, while the proposed SPR platform may be extended to any system where hydrogen peroxide is generated in enzymatic reactions.

Developing Strategies for Waste Reduction by Means of Tailored Interventions in Santiago De Cuba

ERIC Educational Resources Information Center

Tobias, Robert; Brugger, Adrian; Mosler, Hans-Joachim

2009-01-01

This article introduces an approach to tailoring behavior-change campaigns to target populations using the example of solid waste reduction in Santiago de Cuba. Tailoring is performed in the following steps: (1) Psychological constructs are selected to detect problems in performing the target behavior, and data are gathered on these constructs.…

Stress Sensitivity and Reading Performance in Spanish: A Study with Children

ERIC Educational Resources Information Center

Gutierrez-Palma, Nicolas; Reyes, Alfonso Palma

2007-01-01

This paper investigates the relationship between ability to detect changes in prosody and reading performance in Spanish. Participants were children aged 7-8 years. Their tasks consisted of reading words, reading non-words, stressing non-words and reproducing sequences of two, three or four non-words by pressing the corresponding keys on the…

Tryptophan oxidation catabolite, N-formylkynurenine, in photo degraded cell culture medium results in reduced cell culture performance.

PubMed

McElearney, Kyle; Ali, Amr; Gilbert, Alan; Kshirsagar, Rashmi; Zang, Li

2016-01-01

Chemically defined media have been widely used in the biopharmaceutical industry to enhance cell culture productivities and ensure process robustness. These media, which are quite complex, often contain a mixture of many components such as vitamins, amino acids, metals and other chemicals. Some of these components are known to be sensitive to various stress factors including photodegradation. Previous work has shown that small changes in impurity concentrations induced by these potential stresses can have a large impact on the cell culture process including growth and product quality attributes. Furthermore, it has been shown to be difficult to detect these modifications analytically due to the complexity of the cell culture media and the trace level of the degradant products. Here, we describe work performed to identify the specific chemical(s) in photodegraded medium that affect cell culture performance. First, we developed a model system capable of detecting changes in cell culture performance. Second, we used these data and applied an LC-MS analytical technique to characterize the cell culture media and identify degradant products which affect cell culture performance. Riboflavin limitation and N-formylkynurenine (NFK), a tryptophan oxidation catabolite, were identified as chemicals which results in a reduction in cell culture performance. © 2015 American Institute of Chemical Engineers.

The Decay of Motor Memories Is Independent of Context Change Detection

PubMed Central

Brennan, Andrew E.; Smith, Maurice A.

2015-01-01

When the error signals that guide human motor learning are withheld following training, recently-learned motor memories systematically regress toward untrained performance. It has previously been hypothesized that this regression results from an intrinsic volatility in these memories, resulting in an inevitable decay in the absence of ongoing error signals. However, a recently-proposed alternative posits that even recently-acquired motor memories are intrinsically stable, decaying only if a change in context is detected. This new theory, the context-dependent decay hypothesis, makes two key predictions: (1) after error signals are withheld, decay onset should be systematically delayed until the context change is detected; and (2) manipulations that impair detection by masking context changes should result in prolonged delays in decay onset and reduced decay amplitude at any given time. Here we examine the decay of motor adaptation following the learning of novel environmental dynamics in order to carefully evaluate this hypothesis. To account for potential issues in previous work that supported the context-dependent decay hypothesis, we measured decay using a balanced and baseline-referenced experimental design that allowed for direct comparisons between analogous masked and unmasked context changes. Using both an unbiased variant of the previous decay onset analysis and a novel highly-powered group-level version of this analysis, we found no evidence for systematically delayed decay onset nor for the masked context change affecting decay amplitude or its onset time. We further show how previous estimates of decay onset latency can be substantially biased in the presence of noise, and even more so with correlated noise, explaining the discrepancy between the previous results and our findings. Our results suggest that the decay of motor memories is an intrinsic feature of error-based learning that does not depend on context change detection. PMID:26111244

Automatic video shot boundary detection using k-means clustering and improved adaptive dual threshold comparison

NASA Astrophysics Data System (ADS)

Sa, Qila; Wang, Zhihui

2018-03-01

At present, content-based video retrieval (CBVR) is the most mainstream video retrieval method, using the video features of its own to perform automatic identification and retrieval. This method involves a key technology, i.e. shot segmentation. In this paper, the method of automatic video shot boundary detection with K-means clustering and improved adaptive dual threshold comparison is proposed. First, extract the visual features of every frame and divide them into two categories using K-means clustering algorithm, namely, one with significant change and one with no significant change. Then, as to the classification results, utilize the improved adaptive dual threshold comparison method to determine the abrupt as well as gradual shot boundaries.Finally, achieve automatic video shot boundary detection system.

Poly(ionic liquid) based chemosensors for detection of basic amino acids in aqueous medium

NASA Astrophysics Data System (ADS)

Li, Xinjuan; Wang, Kai; Ma, Nana; Jia, Xianbin

2017-09-01

Naked-eye detection of amino acids in water is of great significance in the field of bio-analytical applications. Herein, polymerized ionic liquids (PILs) with controlled chain length structures were synthesized via reversible addition-fragmentation chain-transfer (RAFT) polymerization and post-quaternization approach. The amino acids recognition performance of PILs with different alkyl chain lengths and molecular weights was evaluated by naked-eye color change and ultraviolet-visible (UV-vis) spectral studies. These PILs were successfully used for highly sensitive and selective detection of Arg, Lys and His in water. The recognition performance was improved effectively with increased molecular weight of PILs. The biosensitivity of the PILs in water was strongly dependent on their aggregation effect and polarization effect. Highly sensitive and selective detection of amino acids was successfully accomplished by introducing positively charged pyridinium moieties and controlled RAFT radical polymerization.

Application of artificial neural network to fMRI regression analysis.

PubMed

Misaki, Masaya; Miyauchi, Satoru

2006-01-15

We used an artificial neural network (ANN) to detect correlations between event sequences and fMRI (functional magnetic resonance imaging) signals. The layered feed-forward neural network, given a series of events as inputs and the fMRI signal as a supervised signal, performed a non-linear regression analysis. This type of ANN is capable of approximating any continuous function, and thus this analysis method can detect any fMRI signals that correlated with corresponding events. Because of the flexible nature of ANNs, fitting to autocorrelation noise is a problem in fMRI analyses. We avoided this problem by using cross-validation and an early stopping procedure. The results showed that the ANN could detect various responses with different time courses. The simulation analysis also indicated an additional advantage of ANN over non-parametric methods in detecting parametrically modulated responses, i.e., it can detect various types of parametric modulations without a priori assumptions. The ANN regression analysis is therefore beneficial for exploratory fMRI analyses in detecting continuous changes in responses modulated by changes in input values.

Automated Landslides Detection for Mountain Cities Using Multi-Temporal Remote Sensing Imagery.

PubMed

Chen, Zhong; Zhang, Yifei; Ouyang, Chao; Zhang, Feng; Ma, Jie

2018-03-09

Landslides that take place in mountain cities tend to cause huge casualties and economic losses, and a precise survey of landslide areas is a critical task for disaster emergency. However, because of the complicated appearance of the nature, it is difficult to find a spatial regularity that only relates to landslides, thus landslides detection based on only spatial information or artificial features usually performs poorly. In this paper, an automated landslides detection approach that is aiming at mountain cities has been proposed based on pre- and post-event remote sensing images, it mainly utilizes the knowledge of landslide-related surface covering changes, and makes full use of the temporal and spatial information. A change detection method using Deep Convolution Neural Network (DCNN) was introduced to extract the areas where drastic alterations have taken place; then, focusing on the changed areas, the Spatial Temporal Context Learning (STCL) was conducted to identify the landslides areas; finally, we use slope degree which is derived from digital elevation model (DEM) to make the result more reliable, and the change of DEM is used for making the detected areas more complete. The approach was applied to detecting the landslides in Shenzhen, Zhouqu County and Beichuan County in China, and a quantitative accuracy assessment has been taken. The assessment indicates that this approach can guarantee less commission error of landslide areal extent which is below 17.6% and achieves a quality percentage above 61.1%, and for landslide areas, the detection percentage is also competitive, the experimental results proves the feasibility and accuracy of the proposed approach for the detection landslides in mountain cities.

Automated Landslides Detection for Mountain Cities Using Multi-Temporal Remote Sensing Imagery

PubMed Central

Chen, Zhong; Zhang, Yifei; Ouyang, Chao; Zhang, Feng; Ma, Jie

2018-01-01

Landslides that take place in mountain cities tend to cause huge casualties and economic losses, and a precise survey of landslide areas is a critical task for disaster emergency. However, because of the complicated appearance of the nature, it is difficult to find a spatial regularity that only relates to landslides, thus landslides detection based on only spatial information or artificial features usually performs poorly. In this paper, an automated landslides detection approach that is aiming at mountain cities has been proposed based on pre- and post-event remote sensing images, it mainly utilizes the knowledge of landslide-related surface covering changes, and makes full use of the temporal and spatial information. A change detection method using Deep Convolution Neural Network (DCNN) was introduced to extract the areas where drastic alterations have taken place; then, focusing on the changed areas, the Spatial Temporal Context Learning (STCL) was conducted to identify the landslides areas; finally, we use slope degree which is derived from digital elevation model (DEM) to make the result more reliable, and the change of DEM is used for making the detected areas more complete. The approach was applied to detecting the landslides in Shenzhen, Zhouqu County and Beichuan County in China, and a quantitative accuracy assessment has been taken. The assessment indicates that this approach can guarantee less commission error of landslide areal extent which is below 17.6% and achieves a quality percentage above 61.1%, and for landslide areas, the detection percentage is also competitive, the experimental results proves the feasibility and accuracy of the proposed approach for the detection landslides in mountain cities. PMID:29522424

Quantification of susceptibility change at high-concentrated SPIO-labeled target by characteristic phase gradient recognition.

PubMed

Zhu, Haitao; Nie, Binbin; Liu, Hua; Guo, Hua; Demachi, Kazuyuki; Sekino, Masaki; Shan, Baoci

2016-05-01

Phase map cross-correlation detection and quantification may produce highlighted signal at superparamagnetic iron oxide nanoparticles, and distinguish them from other hypointensities. The method may quantify susceptibility change by performing least squares analysis between a theoretically generated magnetic field template and an experimentally scanned phase image. Because characteristic phase recognition requires the removal of phase wrap and phase background, additional steps of phase unwrapping and filtering may increase the chance of computing error and enlarge the inconsistence among algorithms. To solve problem, phase gradient cross-correlation and quantification method is developed by recognizing characteristic phase gradient pattern instead of phase image because phase gradient operation inherently includes unwrapping and filtering functions. However, few studies have mentioned the detectable limit of currently used phase gradient calculation algorithms. The limit may lead to an underestimation of large magnetic susceptibility change caused by high-concentrated iron accumulation. In this study, mathematical derivation points out the value of maximum detectable phase gradient calculated by differential chain algorithm in both spatial and Fourier domain. To break through the limit, a modified quantification method is proposed by using unwrapped forward differentiation for phase gradient generation. The method enlarges the detectable range of phase gradient measurement and avoids the underestimation of magnetic susceptibility. Simulation and phantom experiments were used to quantitatively compare different methods. In vivo application performs MRI scanning on nude mice implanted by iron-labeled human cancer cells. Results validate the limit of detectable phase gradient and the consequent susceptibility underestimation. Results also demonstrate the advantage of unwrapped forward differentiation compared with differential chain algorithms for susceptibility quantification at high-concentrated iron accumulation. Copyright © 2015 Elsevier Inc. All rights reserved.

Obstacle Detection and Avoidance System Based on Monocular Camera and Size Expansion Algorithm for UAVs

PubMed Central

Al-Kaff, Abdulla; García, Fernando; Martín, David; De La Escalera, Arturo; Armingol, José María

2017-01-01

One of the most challenging problems in the domain of autonomous aerial vehicles is the designing of a robust real-time obstacle detection and avoidance system. This problem is complex, especially for the micro and small aerial vehicles, that is due to the Size, Weight and Power (SWaP) constraints. Therefore, using lightweight sensors (i.e., Digital camera) can be the best choice comparing with other sensors; such as laser or radar.For real-time applications, different works are based on stereo cameras in order to obtain a 3D model of the obstacles, or to estimate their depth. Instead, in this paper, a method that mimics the human behavior of detecting the collision state of the approaching obstacles using monocular camera is proposed. The key of the proposed algorithm is to analyze the size changes of the detected feature points, combined with the expansion ratios of the convex hull constructed around the detected feature points from consecutive frames. During the Aerial Vehicle (UAV) motion, the detection algorithm estimates the changes in the size of the area of the approaching obstacles. First, the method detects the feature points of the obstacles, then extracts the obstacles that have the probability of getting close toward the UAV. Secondly, by comparing the area ratio of the obstacle and the position of the UAV, the method decides if the detected obstacle may cause a collision. Finally, by estimating the obstacle 2D position in the image and combining with the tracked waypoints, the UAV performs the avoidance maneuver. The proposed algorithm was evaluated by performing real indoor and outdoor flights, and the obtained results show the accuracy of the proposed algorithm compared with other related works. PMID:28481277

Selective Maintenance in Visual Working Memory Does Not Require Sustained Visual Attention

PubMed Central

Hollingworth, Andrew; Maxcey-Richard, Ashleigh M.

2012-01-01

In four experiments, we tested whether sustained visual attention is required for the selective maintenance of objects in VWM. Participants performed a color change-detection task. During the retention interval, a valid cue indicated the item that would be tested. Change detection performance was higher in the valid-cue condition than in a neutral-cue control condition. To probe the role of visual attention in the cuing effect, on half of the trials, a difficult search task was inserted after the cue, precluding sustained attention on the cued item. The addition of the search task produced no observable decrement in the magnitude of the cuing effect. In a complementary test, search efficiency was not impaired by simultaneously prioritizing an object for retention in VWM. The results demonstrate that selective maintenance in VWM can be dissociated from the locus of visual attention. PMID:23067118

Selective maintenance in visual working memory does not require sustained visual attention.

PubMed

Hollingworth, Andrew; Maxcey-Richard, Ashleigh M

2013-08-01

In four experiments, we tested whether sustained visual attention is required for the selective maintenance of objects in visual working memory (VWM). Participants performed a color change-detection task. During the retention interval, a valid cue indicated the item that would be tested. Change-detection performance was higher in the valid-cue condition than in a neutral-cue control condition. To probe the role of visual attention in the cuing effect, on half of the trials, a difficult search task was inserted after the cue, precluding sustained attention on the cued item. The addition of the search task produced no observable decrement in the magnitude of the cuing effect. In a complementary test, search efficiency was not impaired by simultaneously prioritizing an object for retention in VWM. The results demonstrate that selective maintenance in VWM can be dissociated from the locus of visual attention. 2013 APA, all rights reserved

Syndromic surveillance using veterinary laboratory data: data pre-processing and algorithm performance evaluation

PubMed Central

Dórea, Fernanda C.; McEwen, Beverly J.; McNab, W. Bruce; Revie, Crawford W.; Sanchez, Javier

2013-01-01

Diagnostic test orders to an animal laboratory were explored as a data source for monitoring trends in the incidence of clinical syndromes in cattle. Four years of real data and over 200 simulated outbreak signals were used to compare pre-processing methods that could remove temporal effects in the data, as well as temporal aberration detection algorithms that provided high sensitivity and specificity. Weekly differencing demonstrated solid performance in removing day-of-week effects, even in series with low daily counts. For aberration detection, the results indicated that no single algorithm showed performance superior to all others across the range of outbreak scenarios simulated. Exponentially weighted moving average charts and Holt–Winters exponential smoothing demonstrated complementary performance, with the latter offering an automated method to adjust to changes in the time series that will likely occur in the future. Shewhart charts provided lower sensitivity but earlier detection in some scenarios. Cumulative sum charts did not appear to add value to the system; however, the poor performance of this algorithm was attributed to characteristics of the data monitored. These findings indicate that automated monitoring aimed at early detection of temporal aberrations will likely be most effective when a range of algorithms are implemented in parallel. PMID:23576782

Syndromic surveillance using veterinary laboratory data: data pre-processing and algorithm performance evaluation.

PubMed

Dórea, Fernanda C; McEwen, Beverly J; McNab, W Bruce; Revie, Crawford W; Sanchez, Javier

2013-06-06

Diagnostic test orders to an animal laboratory were explored as a data source for monitoring trends in the incidence of clinical syndromes in cattle. Four years of real data and over 200 simulated outbreak signals were used to compare pre-processing methods that could remove temporal effects in the data, as well as temporal aberration detection algorithms that provided high sensitivity and specificity. Weekly differencing demonstrated solid performance in removing day-of-week effects, even in series with low daily counts. For aberration detection, the results indicated that no single algorithm showed performance superior to all others across the range of outbreak scenarios simulated. Exponentially weighted moving average charts and Holt-Winters exponential smoothing demonstrated complementary performance, with the latter offering an automated method to adjust to changes in the time series that will likely occur in the future. Shewhart charts provided lower sensitivity but earlier detection in some scenarios. Cumulative sum charts did not appear to add value to the system; however, the poor performance of this algorithm was attributed to characteristics of the data monitored. These findings indicate that automated monitoring aimed at early detection of temporal aberrations will likely be most effective when a range of algorithms are implemented in parallel.

Adaptive Sensor Tuning for Seismic Event Detection in Environment with Electromagnetic Noise

NASA Astrophysics Data System (ADS)

Ziegler, Abra E.

The goal of this research is to detect possible microseismic events at a carbon sequestration site. Data recorded on a continuous downhole microseismic array in the Farnsworth Field, an oil field in Northern Texas that hosts an ongoing carbon capture, utilization, and storage project, were evaluated using machine learning and reinforcement learning techniques to determine their effectiveness at seismic event detection on a dataset with electromagnetic noise. The data were recorded from a passive vertical monitoring array consisting of 16 levels of 3-component 15 Hz geophones installed in the field and continuously recording since January 2014. Electromagnetic and other noise recorded on the array has significantly impacted the utility of the data and it was necessary to characterize and filter the noise in order to attempt event detection. Traditional detection methods using short-term average/long-term average (STA/LTA) algorithms were evaluated and determined to be ineffective because of changing noise levels. To improve the performance of event detection and automatically and dynamically detect seismic events using effective data processing parameters, an adaptive sensor tuning (AST) algorithm developed by Sandia National Laboratories was utilized. AST exploits neuro-dynamic programming (reinforcement learning) trained with historic event data to automatically self-tune and determine optimal detection parameter settings. The key metric that guides the AST algorithm is consistency of each sensor with its nearest neighbors: parameters are automatically adjusted on a per station basis to be more or less sensitive to produce consistent agreement of detections in its neighborhood. The effects that changes in neighborhood configuration have on signal detection were explored, as it was determined that neighborhood-based detections significantly reduce the number of both missed and false detections in ground-truthed data. The performance of the AST algorithm was quantitatively evaluated during a variety of noise conditions and seismic detections were identified using AST and compared to ancillary injection data. During a period of CO2 injection in a nearby well to the monitoring array, 82% of seismic events were accurately detected, 13% of events were missed, and 5% of detections were determined to be false. Additionally, seismic risk was evaluated from the stress field and faulting regime at FWU to determine the likelihood of pressure perturbations to trigger slip on previously mapped faults. Faults oriented NW-SE were identified as requiring the smallest pore pressure changes to trigger slip and faults oriented N-S will also potentially be reactivated although this is less likely.

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.

Dynamic mesolimbic dopamine signaling during action sequence learning and expectation violation

PubMed Central

Collins, Anne L.; Greenfield, Venuz Y.; Bye, Jeffrey K.; Linker, Kay E.; Wang, Alice S.; Wassum, Kate M.

2016-01-01

Prolonged mesolimbic dopamine concentration changes have been detected during spatial navigation, but little is known about the conditions that engender this signaling profile or how it develops with learning. To address this, we monitored dopamine concentration changes in the nucleus accumbens core of rats throughout acquisition and performance of an instrumental action sequence task. Prolonged dopamine concentration changes were detected that ramped up as rats executed each action sequence and declined after earned reward collection. With learning, dopamine concentration began to rise increasingly earlier in the execution of the sequence and ultimately backpropagated away from stereotyped sequence actions, becoming only transiently elevated by the most distal and unexpected reward predictor. Action sequence-related dopamine signaling was reactivated in well-trained rats if they became disengaged in the task and in response to an unexpected change in the value, but not identity of the earned reward. Throughout training and test, dopamine signaling correlated with sequence performance. These results suggest that action sequences can engender a prolonged mode of dopamine signaling in the nucleus accumbens core and that such signaling relates to elements of the motivation underlying sequence execution and is dynamic with learning, overtraining and violations in reward expectation. PMID:26869075

The internal model: A study of the relative contribution of proprioception and visual information to failure detection in dynamic systems. [sensitivity of operators versus monitors to failures

NASA Technical Reports Server (NTRS)

Kessel, C.; Wickens, C. D.

1978-01-01

The development of the internal model as it pertains to the detection of step changes in the order of control dynamics is investigated for two modes of participation: whether the subjects are actively controlling those dynamics or are monitoring an autopilot controlling them. A transfer of training design was used to evaluate the relative contribution of proprioception and visual information to the overall accuracy of the internal model. Sixteen subjects either tracked or monitored the system dynamics as a 2-dimensional pursuit display under single task conditions and concurrently with a sub-critical tracking task at two difficulty levels. Detection performance was faster and more accurate in the manual as opposed to the autopilot mode. The concurrent tracking task produced a decrement in detection performance for all conditions though this was more marked for the manual mode. The development of an internal model in the manual mode transferred positively to the automatic mode producing enhanced detection performance. There was no transfer from the internal model developed in the automatic mode to the manual mode.

Detection of tuberculosis patterns in digital photographs of chest X-ray images using Deep Learning: feasibility study.

PubMed

Becker, A S; Blüthgen, C; Phi van, V D; Sekaggya-Wiltshire, C; Castelnuovo, B; Kambugu, A; Fehr, J; Frauenfelder, T

2018-03-01

To evaluate the feasibility of Deep Learning-based detection and classification of pathological patterns in a set of digital photographs of chest X-ray (CXR) images of tuberculosis (TB) patients. In this prospective, observational study, patients with previously diagnosed TB were enrolled. Photographs of their CXRs were taken using a consumer-grade digital still camera. The images were stratified by pathological patterns into classes: cavity, consolidation, effusion, interstitial changes, miliary pattern or normal examination. Image analysis was performed with commercially available Deep Learning software in two steps. Pathological areas were first localised; detected areas were then classified. Detection was assessed using receiver operating characteristics (ROC) analysis, and classification using a confusion matrix. The study cohort was 138 patients with human immunodeficiency virus (HIV) and TB co-infection (median age 34 years, IQR 28-40); 54 patients were female. Localisation of pathological areas was excellent (area under the ROC curve 0.82). The software could perfectly distinguish pleural effusions from intraparenchymal changes. The most frequent misclassifications were consolidations as cavitations, and miliary patterns as interstitial patterns (and vice versa). Deep Learning analysis of CXR photographs is a promising tool. Further efforts are needed to build larger, high-quality data sets to achieve better diagnostic performance.

Implementation of a channelized Hotelling observer model to assess image quality of x-ray angiography systems.

PubMed

Favazza, Christopher P; Fetterly, Kenneth A; Hangiandreou, Nicholas J; Leng, Shuai; Schueler, Beth A

2015-01-01

Evaluation of flat-panel angiography equipment through conventional image quality metrics is limited by the scope of standard spatial-domain image quality metric(s), such as contrast-to-noise ratio and spatial resolution, or by restricted access to appropriate data to calculate Fourier domain measurements, such as modulation transfer function, noise power spectrum, and detective quantum efficiency. Observer models have been shown capable of overcoming these limitations and are able to comprehensively evaluate medical-imaging systems. We present a spatial domain-based channelized Hotelling observer model to calculate the detectability index (DI) of our different sized disks and compare the performance of different imaging conditions and angiography systems. When appropriate, changes in DIs were compared to expectations based on the classical Rose model of signal detection to assess linearity of the model with quantum signal-to-noise ratio (SNR) theory. For these experiments, the estimated uncertainty of the DIs was less than 3%, allowing for precise comparison of imaging systems or conditions. For most experimental variables, DI changes were linear with expectations based on quantum SNR theory. DIs calculated for the smallest objects demonstrated nonlinearity with quantum SNR theory due to system blur. Two angiography systems with different detector element sizes were shown to perform similarly across the majority of the detection tasks.

Optimizing a neural network for detection of moving vehicles in video

NASA Astrophysics Data System (ADS)

Fischer, Noëlle M.; Kruithof, Maarten C.; Bouma, Henri

2017-10-01

In the field of security and defense, it is extremely important to reliably detect moving objects, such as cars, ships, drones and missiles. Detection and analysis of moving objects in cameras near borders could be helpful to reduce illicit trading, drug trafficking, irregular border crossing, trafficking in human beings and smuggling. Many recent benchmarks have shown that convolutional neural networks are performing well in the detection of objects in images. Most deep-learning research effort focuses on classification or detection on single images. However, the detection of dynamic changes (e.g., moving objects, actions and events) in streaming video is extremely relevant for surveillance and forensic applications. In this paper, we combine an end-to-end feedforward neural network for static detection with a recurrent Long Short-Term Memory (LSTM) network for multi-frame analysis. We present a practical guide with special attention to the selection of the optimizer and batch size. The end-to-end network is able to localize and recognize the vehicles in video from traffic cameras. We show an efficient way to collect relevant in-domain data for training with minimal manual labor. Our results show that the combination with LSTM improves performance for the detection of moving vehicles.

Sensor data fusion for spectroscopy-based detection of explosives

NASA Astrophysics Data System (ADS)

Shah, Pratik V.; Singh, Abhijeet; Agarwal, Sanjeev; Sedigh, Sahra; Ford, Alan; Waterbury, Robert

2009-05-01

In-situ trace detection of explosive compounds such as RDX, TNT, and ammonium nitrate, is an important problem for the detection of IEDs and IED precursors. Spectroscopic techniques such as LIBS and Raman have shown promise for the detection of residues of explosive compounds on surfaces from standoff distances. Individually, both LIBS and Raman techniques suffer from various limitations, e.g., their robustness and reliability suffers due to variations in peak strengths and locations. However, the orthogonal nature of the spectral and compositional information provided by these techniques makes them suitable candidates for the use of sensor fusion to improve the overall detection performance. In this paper, we utilize peak energies in a region by fitting Lorentzian or Gaussian peaks around the location of interest. The ratios of peak energies are used for discrimination, in order to normalize the effect of changes in overall signal strength. Two data fusion techniques are discussed in this paper. Multi-spot fusion is performed on a set of independent samples from the same region based on the maximum likelihood formulation. Furthermore, the results from LIBS and Raman sensors are fused using linear discriminators. Improved detection performance with significantly reduced false alarm rates is reported using fusion techniques on data collected for sponsor demonstration at Fort Leonard Wood.

[Asymmetric confusability effects in recognition memory of line drawings].

PubMed

Uchino, Y; Hakoda, Y; Yamada, N

2000-06-01

Experiment 1 and 2 examined the effect of addition or deletion changes in a picture recognition test. Addition and deletion applied to original pictures were referred to deviation change, and addition to deleted pictures or deletion from added pictures was referred to restoration change. In Experiment 1 (n = 40), elaborative detailed information contained in line drawings of scenes was changed whereas one of major features in a single object was changed in Experiment 2 (n = 36). In the test phase, participants indicated whether each test picture was changed or not from the picture they had seen in the study phase. Deviation change had a greater effect on detection performance than restoration only in Experiment 2. Additions were easily detected than deletions only in deviation change in Experiment 2. In Experiment 3, 51 participants rated impression of added or deleted pictures used in Experiment 2. Impression of added pictures was significantly different from that of deleted in 3 factors. These results suggest that superiority of additions over deletions might be due to their different impression change.

A Burst-Mode Photon-Counting Receiver with Automatic Channel Estimation and Bit Rate Detection

DTIC Science & Technology

2016-02-24

communication at data rates up to 10.416 Mb/s over a 30-foot water channel. To the best of our knowledge, this is the first demonstration of burst-mode...obstructions. The receiver is capable of on-the-fly data rate detection and adapts to changing levels of signal and background light. The receiver...receiver. We demonstrate on-the-fly rate detection, channel BER within 0.2 dB of theory across all data rates, and error-free performance within 1.82 dB

A dual-mode generalized likelihood ratio approach to self-reorganizing digital flight control system design

NASA Technical Reports Server (NTRS)

1976-01-01

Analytic techniques have been developed for detecting and identifying abrupt changes in dynamic systems. The GLR technique monitors the output of the Kalman filter and searches for the time that the failure occured, thus allowing it to be sensitive to new data and consequently increasing the chances for fast system recovery following detection of a failure. All failure detections are based on functional redundancy. Performance tests of the F-8 aircraft flight control system and computerized modelling of the technique are presented.

High-Performance Sensors Based on Resistance Fluctuations of Single-Layer-Graphene Transistors.

PubMed

Amin, Kazi Rafsanjani; Bid, Aveek

2015-09-09

One of the most interesting predicted applications of graphene-monolayer-based devices is as high-quality sensors. In this article, we show, through systematic experiments, a chemical vapor sensor based on the measurement of low-frequency resistance fluctuations of single-layer-graphene field-effect-transistor devices. The sensor has extremely high sensitivity, very high specificity, high fidelity, and fast response times. The performance of the device using this scheme of measurement (which uses resistance fluctuations as the detection parameter) is more than 2 orders of magnitude better than a detection scheme in which changes in the average value of the resistance is monitored. We propose a number-density-fluctuation-based model to explain the superior characteristics of a noise-measurement-based detection scheme presented in this article.

Buildings Change Detection Based on Shape Matching for Multi-Resolution Remote Sensing Imagery

NASA Astrophysics Data System (ADS)

Abdessetar, M.; Zhong, Y.

2017-09-01

Buildings change detection has the ability to quantify the temporal effect, on urban area, for urban evolution study or damage assessment in disaster cases. In this context, changes analysis might involve the utilization of the available satellite images with different resolutions for quick responses. In this paper, to avoid using traditional method with image resampling outcomes and salt-pepper effect, building change detection based on shape matching is proposed for multi-resolution remote sensing images. Since the object's shape can be extracted from remote sensing imagery and the shapes of corresponding objects in multi-scale images are similar, it is practical for detecting buildings changes in multi-scale imagery using shape analysis. Therefore, the proposed methodology can deal with different pixel size for identifying new and demolished buildings in urban area using geometric properties of objects of interest. After rectifying the desired multi-dates and multi-resolutions images, by image to image registration with optimal RMS value, objects based image classification is performed to extract buildings shape from the images. Next, Centroid-Coincident Matching is conducted, on the extracted building shapes, based on the Euclidean distance measurement between shapes centroid (from shape T0 to shape T1 and vice versa), in order to define corresponding building objects. Then, New and Demolished buildings are identified based on the obtained distances those are greater than RMS value (No match in the same location).

Abnormal global and local event detection in compressive sensing domain

NASA Astrophysics Data System (ADS)

Wang, Tian; Qiao, Meina; Chen, Jie; Wang, Chuanyun; Zhang, Wenjia; Snoussi, Hichem

2018-05-01

Abnormal event detection, also known as anomaly detection, is one challenging task in security video surveillance. It is important to develop effective and robust movement representation models for global and local abnormal event detection to fight against factors such as occlusion and illumination change. In this paper, a new algorithm is proposed. It can locate the abnormal events on one frame, and detect the global abnormal frame. The proposed algorithm employs a sparse measurement matrix designed to represent the movement feature based on optical flow efficiently. Then, the abnormal detection mission is constructed as a one-class classification task via merely learning from the training normal samples. Experiments demonstrate that our algorithm performs well on the benchmark abnormal detection datasets against state-of-the-art methods.

Class imbalance in unsupervised change detection - A diagnostic analysis from urban remote sensing

NASA Astrophysics Data System (ADS)

Leichtle, Tobias; Geiß, Christian; Lakes, Tobia; Taubenböck, Hannes

2017-08-01

Automatic monitoring of changes on the Earth's surface is an intrinsic capability and simultaneously a persistent methodological challenge in remote sensing, especially regarding imagery with very-high spatial resolution (VHR) and complex urban environments. In order to enable a high level of automatization, the change detection problem is solved in an unsupervised way to alleviate efforts associated with collection of properly encoded prior knowledge. In this context, this paper systematically investigates the nature and effects of class distribution and class imbalance in an unsupervised binary change detection application based on VHR imagery over urban areas. For this purpose, a diagnostic framework for sensitivity analysis of a large range of possible degrees of class imbalance is presented, which is of particular importance with respect to unsupervised approaches where the content of images and thus the occurrence and the distribution of classes are generally unknown a priori. Furthermore, this framework can serve as a general technique to evaluate model transferability in any two-class classification problem. The applied change detection approach is based on object-based difference features calculated from VHR imagery and subsequent unsupervised two-class clustering using k-means, genetic k-means and self-organizing map (SOM) clustering. The results from two test sites with different structural characteristics of the built environment demonstrated that classification performance is generally worse in imbalanced class distribution settings while best results were reached in balanced or close to balanced situations. Regarding suitable accuracy measures for evaluating model performance in imbalanced settings, this study revealed that the Kappa statistics show significant response to class distribution while the true skill statistic was widely insensitive to imbalanced classes. In general, the genetic k-means clustering algorithm achieved the most robust results with respect to class imbalance while the SOM clustering exhibited a distinct optimization towards a balanced distribution of classes.

Sensitivity to changes during antidepressant treatment: a comparison of unidimensional subscales of the Inventory of Depressive Symptomatology (IDS-C) and the Hamilton Depression Rating Scale (HAMD) in patients with mild major, minor or subsyndromal depression.

PubMed

Helmreich, Isabella; Wagner, Stefanie; Mergl, Roland; Allgaier, Antje-Kathrin; Hautzinger, Martin; Henkel, Verena; Hegerl, Ulrich; Tadić, André

2012-06-01

In the efficacy evaluation of antidepressant treatments, the total score of the Hamilton Depression Rating Scale (HAMD) is still regarded as the 'gold standard'. We previously had shown that the Inventory of Depressive Symptomatology (IDS) was more sensitive to detect depressive symptom changes than the HAMD17 (Helmreich et al. 2011). Furthermore, studies suggest that the unidimensional subscales of the HAMD, which capture the core depressive symptoms, outperform the full HAMD regarding the detection of antidepressant treatment effects. The aim of the present study was to compare several unidimensional subscales of the HAMD and the IDS regarding their sensitivity to changes in depression symptoms in a sample of patients with mild major, minor or subsyndromal depression (MIND). Biweekly IDS-C28 and HAMD17 data from 287 patients of a 10-week randomised, placebo-controlled trial comparing the effectiveness of sertraline and cognitive-behavioural group therapy in patients with MIND were converted to subscale scores and analysed during the antidepressant treatment course. We investigated sensitivity to depressive change for all scales from assessment-to-assessment, in relation to depression severity level and placebo-verum differences. The subscales performed similarly during the treatment course, with slight advantages for some subscales in detecting treatment effects depending on the treatment modality and on the items included. Most changes in depressive symptomatology were detected by the IDS short scale, but regarding the effect sizes, it performed worse than most subscales. Unidimensional subscales are a time- and cost-saving option in judging drug therapy outcomes, especially in antidepressant treatment efficacy studies. However, subscales do not cover all facets of depression (e.g. atypical symptoms, sleep disturbances), which might be important for comprehensively understanding the nature of the disease depression. Therefore, the cost-to-benefit ratio must be carefully assessed in the decision for using unidimensional subscales.

Change Detection in Uav Video Mosaics Combining a Feature Based Approach and Extended Image Differencing

NASA Astrophysics Data System (ADS)

Saur, Günter; Krüger, Wolfgang

2016-06-01

Change detection is an important task when using unmanned aerial vehicles (UAV) for video surveillance. We address changes of short time scale using observations in time distances of a few hours. Each observation (previous and current) is a short video sequence acquired by UAV in near-Nadir view. Relevant changes are, e.g., recently parked or moved vehicles. Examples for non-relevant changes are parallaxes caused by 3D structures of the scene, shadow and illumination changes, and compression or transmission artifacts. In this paper we present (1) a new feature based approach to change detection, (2) a combination with extended image differencing (Saur et al., 2014), and (3) the application to video sequences using temporal filtering. In the feature based approach, information about local image features, e.g., corners, is extracted in both images. The label "new object" is generated at image points, where features occur in the current image and no or weaker features are present in the previous image. The label "vanished object" corresponds to missing or weaker features in the current image and present features in the previous image. This leads to two "directed" change masks and differs from image differencing where only one "undirected" change mask is extracted which combines both label types to the single label "changed object". The combination of both algorithms is performed by merging the change masks of both approaches. A color mask showing the different contributions is used for visual inspection by a human image interpreter.

Impact of the climate change on the performance of the steam and gas turbines in Russia

NASA Astrophysics Data System (ADS)

Fedotova (Kasilova, E. V.; Klimenko, V. V.; Klimenko, A. V.; Tereshin, A. G.

2017-11-01

The power generating industry is known to be vulnerable to the climate change due to the deteriorating efficiency of the power equipment. Effects for Russia are not completely understood yet. But they are already detected and will be more pronounced during the entire current century, as the Russian territory is one of the areas around the world where the climate change is developing most rapidly. An original climate model was applied to simulate the change of the air temperature across Russia for the twenty-first century. The results of the climate simulations were used to conduct impact analysis for the steam and gas turbine performance taking into account seasonal and spatial heterogeneity of the climate change across the Russian territory. Sensitivity of the turbines to the climatic conditions was simulated using both results of fundamental heat transfer research and empirical performance curves for the units being in operation nowadays. The integral effect of the climate change on the power generating industry was estimated. Some possible challenges and opportunities resulted from the climate change were identified.

Pharmacologic Modulation of Hand Pain in Osteoarthritis: A Double-Blind Placebo-Controlled Functional Magnetic Resonance Imaging Study Using Naproxen

PubMed Central

Sanders, Duncan; Krause, Kristina; O'Muircheartaigh, Jonathan; Thacker, Michael A; Huggins, John P; Vennart, William; Massat, Nathalie J; Choy, Ernest; Williams, Steven C R; Howard, Matthew A

2015-01-01

Objective In an attempt to shed light on management of chronic pain conditions, there has long been a desire to complement behavioral measures of pain perception with measures of underlying brain mechanisms. Using functional magnetic resonance imaging (fMRI), we undertook this study to investigate changes in brain activity following the administration of naproxen or placebo in patients with pain related to osteoarthritis (OA) of the carpometacarpal (CMC) joint. Methods A placebo-controlled, double-blind, 2-period crossover study was performed in 19 individuals with painful OA of the CMC joint of the right hand. Following placebo or naproxen treatment periods, a functionally relevant task was performed, and behavioral measures of the pain experience were collected in identical fMRI examinations. Voxelwise and a priori region of interest analyses were performed to detect between-period differences in brain activity. Results Significant reductions in brain activity following treatment with naproxen, compared to placebo, were observed in brain regions commonly associated with pain perception, including the bilateral primary somatosensory cortex, thalamus, and amygdala. Significant relationships between changes in perceived pain intensity and changes in brain activity were also observed in brain regions previously associated with pain intensity. Conclusion This study demonstrates the sensitivity of fMRI to detect the mechanisms underlying treatments of known efficacy. The data illustrate the enticing potential of fMRI as an adjunct to self-report for detecting early signals of efficacy of novel therapies, both pharmacologic and nonpharmacologic, in small numbers of individuals with persistent pain. PMID:25533872

Use of head-worn sensors to detect lapses in vigilance through the measurement of PERCLOS and cerebral blood flow velocity

NASA Astrophysics Data System (ADS)

McIntire, Lindsey K.; McKinley, R. Andy; Goodyear, Chuck; McIntire, John P.

2017-05-01

The purpose of this study is to determine the ability of an eye-tracker to detect changes in vigilance performance compared to the common method of using cerebral blood flow velocities (CBFV). Sixteen subjects completed this study. Each participant performed a 40-minute vigilance task while wearing an eye-tracker and a transcranial doppler (TCD) on each of four separate days. The results indicate that percentage of eye closure (PERCLOS) measured by the eye-tracker increased as vigilance performance declined and right CBFV as measured by the TCD decreased as performance declined. The results indicate that PERCLOS (left eye r=-.72 right eye r=-.67) more strongly correlated with changes in performance when compared to CBFV (r=.54). We conclude that PERCLOS, as measured by a head-worn eye tracking system, may serve as a compelling alternative (or supplemental) indicator of impending or concurrent performance declines in operational settings where sustained attention or vigilance is required. Such head-worn or perhaps even offbody oculometric sensor systems could potentially overcome some of the practical disadvantages inherent with TCD data collection for operational purposes. If portability and discomfort challenges with TCD can be overcome, both TCD and eye tracking might be advantageously combined for even greater performance monitoring than can be offered by any single device.

Pharmaceutical Composition for Improving Physical Working Capacity.

PubMed

Baulin, S I; Rogacheva, S M; Afanaseva, S V; Zabanova, E V; Karagaycheva, Yu V

2015-11-01

For development of a pharmaceutical composition improving physical performance, effects of various drugs and their combinations on forced swimming test performance were studied on laboratory rats. Maximum increase in animal performance was produced by a 3-component composition asparcam+mildronate+metaprote in proportion of 5.0, 10.7, and 14.3 mg/kg, respectively. No changes in blood serum biochemistry and morphological composition of the peripheral blood were detected after single intragastric administration of the composition.

Musicians Are Better than Non-musicians in Frequency Change Detection: Behavioral and Electrophysiological Evidence

PubMed Central

Liang, Chun; Earl, Brian; Thompson, Ivy; Whitaker, Kayla; Cahn, Steven; Xiang, Jing; Fu, Qian-Jie; Zhang, Fawen

2016-01-01

Objective: The objectives of this study were: (1) to determine if musicians have a better ability to detect frequency changes under quiet and noisy conditions; (2) to use the acoustic change complex (ACC), a type of electroencephalographic (EEG) response, to understand the neural substrates of musician vs. non-musician difference in frequency change detection abilities. Methods: Twenty-four young normal hearing listeners (12 musicians and 12 non-musicians) participated. All participants underwent psychoacoustic frequency detection tests with three types of stimuli: tones (base frequency at 160 Hz) containing frequency changes (Stim 1), tones containing frequency changes masked by low-level noise (Stim 2), and tones containing frequency changes masked by high-level noise (Stim 3). The EEG data were recorded using tones (base frequency at 160 and 1200 Hz, respectively) containing different magnitudes of frequency changes (0, 5, and 50% changes, respectively). The late-latency evoked potential evoked by the onset of the tones (onset LAEP or N1-P2 complex) and that evoked by the frequency change contained in the tone (the acoustic change complex or ACC or N1′-P2′ complex) were analyzed. Results: Musicians significantly outperformed non-musicians in all stimulus conditions. The ACC and onset LAEP showed similarities and differences. Increasing the magnitude of frequency change resulted in increased ACC amplitudes. ACC measures were found to be significantly different between musicians (larger P2′ amplitude) and non-musicians for the base frequency of 160 Hz but not 1200 Hz. Although the peak amplitude in the onset LAEP appeared to be larger and latency shorter in musicians than in non-musicians, the difference did not reach statistical significance. The amplitude of the onset LAEP is significantly correlated with that of the ACC for the base frequency of 160 Hz. Conclusion: The present study demonstrated that musicians do perform better than non-musicians in detecting frequency changes in quiet and noisy conditions. The ACC and onset LAEP may involve different but overlapping neural mechanisms. Significance: This is the first study using the ACC to examine music-training effects. The ACC measures provide an objective tool for documenting musical training effects on frequency detection. PMID:27826221

Region-Based Building Rooftop Extraction and Change Detection

NASA Astrophysics Data System (ADS)

Tian, J.; Metzlaff, L.; d'Angelo, P.; Reinartz, P.

2017-09-01

Automatic extraction of building changes is important for many applications like disaster monitoring and city planning. Although a lot of research work is available based on 2D as well as 3D data, an improvement in accuracy and efficiency is still needed. The introducing of digital surface models (DSMs) to building change detection has strongly improved the resulting accuracy. In this paper, a post-classification approach is proposed for building change detection using satellite stereo imagery. Firstly, DSMs are generated from satellite stereo imagery and further refined by using a segmentation result obtained from the Sobel gradients of the panchromatic image. Besides the refined DSMs, the panchromatic image and the pansharpened multispectral image are used as input features for mean-shift segmentation. The DSM is used to calculate the nDSM, out of which the initial building candidate regions are extracted. The candidate mask is further refined by morphological filtering and by excluding shadow regions. Following this, all segments that overlap with a building candidate region are determined. A building oriented segments merging procedure is introduced to generate a final building rooftop mask. As the last step, object based change detection is performed by directly comparing the building rooftops extracted from the pre- and after-event imagery and by fusing the change indicators with the roof-top region map. A quantitative and qualitative assessment of the proposed approach is provided by using WorldView-2 satellite data from Istanbul, Turkey.

TBS (Trabecular Bone Score) Expands Understanding of Spaceflight Effects on the Lumbar Spine of Long-Duration Astronauts

NASA Technical Reports Server (NTRS)

Smith, Scott A.; Watts, Nelson; Hans, Didier; LeBlanc, Adrian; Spector, Elisabeth; King, Lisa; Sibonga, Jean

2014-01-01

Bone loss due to long-duration spaceflight has been characterized by both DXA and QCT serial scans. It is unclear if these spaceflight-induced changes in bone mineral density (BMD) and structure result in increased fracture incidence. NASA astronauts currently fly 5 to 6-month missions on the International Space Station (ISS) and at least one 12-month mission is planned. While NASA has measured areal BMD (by DXA) and volumetric BMD (by QCT) and has estimated hip strength (by finite element models of QCT data, no method has yet been used to examine bone micro-architecture from lumbar spine (LS). DXA scans are routinely performed pre- and postflight on all ISS astronauts to follow BMD changes associated with spaceflight. Trabecular Bone Score (TBS) is a relatively new method that measures grey-scale-level texture information extracted from LS DXA images and correlates with 3D parameters of bone micro-architecture. We evaluated the ability of LS TBS to discriminate changes in astronauts who have flown on ISS missions and to determine if TBS can provide additional information compared to DXA. Methods: Lumbar Spine (L1-4) DXA scans from 51 astronauts (mean age, 47 +/- 4 yrs) were divided into 3 groups based on the exercise regimens performed onboard the ISS. "Pre-ARED" (exercise using a load-limited resistive exercise device, <300 lb), "ARED" (exercise with a high-load resistive exercise device, up to 600 lb) and "Bisphos+ARED" group (ARED exercise and a 70-mg alendronate tablet once a week before and during flight, starting 17 days before launch). DXA scans were performed and analyzed on a Hologic Discovery W using the same technician for the pre- and post-flight scans. LSC for the LS in our laboratory is 0.025 g/sq. cm. TBS was performed at the Mercy Hospital, Cincinnati, Ohio on a similar Hologic computer. Data were analyzed using a paired, 2-tailed Student's t-test for the difference between pre- and postflight means. Percent change and % change per month are noted. Interpretation: Our data suggest that: TBS and DXA both detected significant decrements in the LS in these pre- ARED astronauts, not unexpected given the insufficient loads provided by this early exercise device. TBS did not detect significant changes in the ARED or Bisphos+ARED groups while DXA did detect significant changes in the ARED astronauts. These findings suggest that DXA and TBS are detecting independent effects of bone loss interventions tested in ISS astronauts in space, which may be due to distinct effects of interventions on mineral content of separate cortical vs. trabecular bone. Conclusion: TBS, in conjunction with DXA BMD, may provide additional insight into the nature of changes (or lack thereof) in the microstructure of trabecular bone and the areal BMD of vertebral bodies.

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

Stone, Daithi A.; Hansen, Gerrit

Despite being a well-established research field, the detection and attribution of observed climate change to anthropogenic forcing is not yet provided as a climate service. One reason for this is the lack of a methodology for performing tailored detection and attribution assessments on a rapid time scale. Here we develop such an approach, based on the translation of quantitative analysis into the “confidence” language employed in recent Assessment Reports of the Intergovernmental Panel on Climate Change. While its systematic nature necessarily ignores some nuances examined in detailed expert assessments, the approach nevertheless goes beyond most detection and attribution studies inmore » considering contributors to building confidence such as errors in observational data products arising from sparse monitoring networks. When compared against recent expert assessments, the results of this approach closely match those of the existing assessments. Where there are small discrepancies, these variously reflect ambiguities in the details of what is being assessed, reveal nuances or limitations of the expert assessments, or indicate limitations of the accuracy of the sort of systematic approach employed here. Deployment of the method on 116 regional assessments of recent temperature and precipitation changes indicates that existing rules of thumb concerning the detectability of climate change ignore the full range of sources of uncertainty, most particularly the importance of adequate observational monitoring.« less

Change detection of polarimetric SAR images based on the KummerU Distribution

NASA Astrophysics Data System (ADS)

Chen, Quan; Zou, Pengfei; Li, Zhen; Zhang, Ping

2014-11-01

In the society of PolSAR image segmentation, change detection and classification, the classical Wishart distribution has been used for a long time, but it especially suit to low-resolution SAR image, because in traditional sensors, only a small number of scatterers are present in each resolution cell. With the improving of SAR systems these years, the classical statistical models can therefore be reconsidered for high resolution and polarimetric information contained in the images acquired by these advanced systems. In this study, SAR image segmentation algorithm based on level-set method, added with distance regularized level-set evolution (DRLSE) is performed using Envisat/ASAR single-polarization data and Radarsat-2 polarimetric images, respectively. KummerU heterogeneous clutter model is used in the later to overcome the homogeneous hypothesis at high resolution cell. An enhanced distance regularized level-set evolution (DRLSE-E) is also applied in the later, to ensure accurate computation and stable level-set evolution. Finally, change detection based on four polarimetric Radarsat-2 time series images is carried out at Genhe area of Inner Mongolia Autonomous Region, NorthEastern of China, where a heavy flood disaster occurred during the summer of 2013, result shows the recommend segmentation method can detect the change of watershed effectively.

Water Vapour Mixing Ratio Measurements in Potenza in the Frame of the International Network for the Detection of Atmospheric Composition Change - NDACC

NASA Astrophysics Data System (ADS)

De Rosa, Benedetto; Di Girolamo, Paolo; Summa, Donato; Stelitano, Dario; Mancini, Ignazio

2016-06-01

In November 2012 the University of BASILicata Raman Lidar system (BASIL) was approved to enter the International Network for the Detection of Atmospheric Composition Change (NDACC). This network includes more than 70 high-quality, remote-sensing research stations for observing and understanding the physical and chemical state of the upper troposphere and stratosphere and for assessing the impact of stratosphere changes on the underlying troposphere and on global climate. As part of this network, more than thirty groundbased Lidars deployed worldwide are routinely operated to monitor atmospheric ozone, temperature, aerosols, water vapour, and polar stratospheric clouds. In the frame of NDACC, BASIL performs measurements on a routine basis each Thursday, typically from local noon to midnight, covering a large portion of the daily cycle. Measurements from BASIL are included in the NDACC database both in terms of water vapour mixing ratio and temperature. This paper illustrates some measurement examples from BASIL, with a specific focus on water vapour measurements, with the goal to try and characterize the system performances.

Increased cerebellar gray matter volume in head chefs.

PubMed

Cerasa, Antonio; Sarica, Alessia; Martino, Iolanda; Fabbricatore, Carmelo; Tomaiuolo, Francesco; Rocca, Federico; Caracciolo, Manuela; Quattrone, Aldo

2017-01-01

Chefs exert expert motor and cognitive performances on a daily basis. Neuroimaging has clearly shown that that long-term skill learning (i.e., athletes, musicians, chess player or sommeliers) induces plastic changes in the brain thus enabling tasks to be performed faster and more accurately. How a chef's expertise is embodied in a specific neural network has never been investigated. Eleven Italian head chefs with long-term brigade management expertise and 11 demographically-/ psychologically- matched non-experts underwent morphological evaluations. Voxel-based analysis performed with SUIT, as well as, automated volumetric measurement assessed with Freesurfer, revealed increased gray matter volume in the cerebellum in chefs compared to non-experts. The most significant changes were detected in the anterior vermis and the posterior cerebellar lobule. The magnitude of the brigade staff and the higher performance in the Tower of London test correlated with these specific gray matter increases, respectively. We found that chefs are characterized by an anatomical variability involving the cerebellum. This confirms the role of this region in the development of similar expert brains characterized by learning dexterous skills, such as pianists, rock climbers and basketball players. However, the nature of the cellular events underlying the detected morphological differences remains an open question.

Probabilistic change mapping from airborne LiDAR for post-disaster damage assessment

NASA Astrophysics Data System (ADS)

Jalobeanu, A.; Runyon, S. C.; Kruse, F. A.

2013-12-01

When both pre- and post-event LiDAR point clouds are available, change detection can be performed to identify areas that were most affected by a disaster event, and to obtain a map of quantitative changes in terms of height differences. In the case of earthquakes in built-up areas for instance, first responders can use a LiDAR change map to help prioritize search and recovery efforts. The main challenge consists of producing reliable change maps, robust to collection conditions, free of processing artifacts (due for instance to triangulation or gridding), and taking into account the various sources of uncertainty. Indeed, datasets acquired within a few years interval are often of different point density (sometimes an order of magnitude higher for recent data), different acquisition geometries, and very likely suffer from georeferencing errors and geometric discrepancies. All these differences might not be important for producing maps from each dataset separately, but they are crucial when performing change detection. We have developed a novel technique for the estimation of uncertainty maps from the LiDAR point clouds, using Bayesian inference, treating all variables as random. The main principle is to grid all points on a common grid before attempting any comparison, as working directly with point clouds is cumbersome and time consuming. A non-parametric approach based on local linear regression was implemented, assuming a locally linear model for the surface. This enabled us to derive error bars on gridded elevations, and then elevation differences. In this way, a map of statistically significant changes could be computed - whereas a deterministic approach would not allow testing of the significance of differences between the two datasets. This approach allowed us to take into account not only the observation noise (due to ranging, position and attitude errors) but also the intrinsic roughness of the observed surfaces occurring when scanning vegetation. As only elevation differences above a predefined noise level are accounted for (according to a specified confidence interval related to the allowable false alarm rate) the change detection is robust to all these sources of noise. To first validate the approach, we built small-scale models and scanned them using a terrestrial laser scanner to establish 'ground truth'. Changes were manually applied to the models then new scans were performed and analyzed. Additionally, two airborne datasets of the Monterey Peninsula, California, were processed and analyzed. The first one was acquired during 2010 (with relatively low point density, 1-3 pts/m2), and the second one was acquired during 2012 (with up to 30 pts/m2). To perform the comparison, a new point cloud registration technique was developed and the data were registered to a common 1 m grid. The goal was to correct systematic shifts due to GPS and INS errors, and focus on the actual height differences regardless of the absolute planimetric accuracy of the datasets. Though no major disaster event occurred between the two acquisition dates, sparse changes were detected and interpreted mostly as construction and natural landscape evolution.

Moving target detection method based on improved Gaussian mixture model

NASA Astrophysics Data System (ADS)

Ma, J. Y.; Jie, F. R.; Hu, Y. J.

2017-07-01

Gaussian Mixture Model is often employed to build background model in background difference methods for moving target detection. This paper puts forward an adaptive moving target detection algorithm based on improved Gaussian Mixture Model. According to the graylevel convergence for each pixel, adaptively choose the number of Gaussian distribution to learn and update background model. Morphological reconstruction method is adopted to eliminate the shadow.. Experiment proved that the proposed method not only has good robustness and detection effect, but also has good adaptability. Even for the special cases when the grayscale changes greatly and so on, the proposed method can also make outstanding performance.

[Changes of epidermal growth factor level in blood serum, saliva and gastric juice in children with duodenal ulcer].

PubMed

Zhukova, E A; Vidmanova, T A; Viskova, I N; Kolesov, S A; Korkotashvili, L V; Shirokova, N Iu; Kan'kova, N Iu

2013-01-01

The aim of our study is to investigate EGF content in biological mediums in children with duodenum ulcer depending on phase of the disease and different variants of its course. The present study was performed in Federal State Establishment "Nizhniy Novgorod Research Institute of Children Gastroenterology", Nizhniy Novgorod, Russia. 92 children, between the ages of 8 to 17, with duodenum ulcer were under observation. Endoscopy was performed by Pentax endoscope (FG-24V). EGF detection was performed in blood serum, gastric juice and saliva by ELISA method with Human EGF Kit, "Invitrogen", USA. The peculiarities of EGF level changes in human biological mediums, depending on phase of the disease. The highest EGF level was detected with acute peptic ulcer in the presence of ulcerous defects. EGF level increasing was marked out in the remission phaseas ulcerous defects healing, and it didn't reach normal values in gastric juice. EGF content changes in biological mediums were revealed with different variants of duodenum ulcer clinical course in children. The lowest EGF level was marked out in blood, saliva and gastric juice with unfavorable course of the disease (frequent relapses, cicatricial-ulcerous strains formation), which can serve as a prognostic factor.

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.

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).

Visual Costs of the Inhomogeneity of Luminance and Contrast by Viewing LCD-TFT Screens Off-Axis.

PubMed

Ziefle, Martina; Groeger, Thomas; Sommer, Dietmar

2003-01-01

In this study the anisotropic characteristics of TFT-LCD (Thin-Film-Transistor-Liquid Crystal Display) screens were examined. Anisotropy occurs as the distribution of luminance and contrast changes over the screen surface due to different viewing angles. On the basis of detailed photometric measurements the detection performance in a visual reaction task was measured in different viewing conditions. Viewing angle (0 degrees, frontal view; 30 degrees, off-axis; 50 degrees, off-axis) as well as ambient lighting (a dark or illuminated room) were varied. Reaction times and accuracy of detection performance were recorded. Results showed TFT's anisotropy to be a crucial factor deteriorating performance. With an increasing viewing angle performance decreased. It is concluded that TFT's anisotropy is a limiting factor for overall suitability and usefulness of this new display technology.

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.

Musical experts recruit action-related neural structures in harmonic anomaly detection: Evidence for embodied cognition in expertise

PubMed Central

Sherwin, Jason; Sajda, Paul

2013-01-01

Humans are extremely good at detecting anomalies in sensory input. For example, while listening to a piece of Western-style music, an anomalous key change or an out-of-key pitch is readily apparent, even to the non-musician. In this paper we investigate differences between musical experts and non-experts during musical anomaly detection. Specifically, we analyzed the electroencephalograms (EEG) of five expert cello players and five non-musicians while they listened to excerpts of J.S. Bach’s Prelude from Cello Suite No.1. All subjects were familiar with the piece, though experts also had extensive experience playing the piece. Subjects were told that anomalous musical events (AMEs) could occur at random within the excerpts of the piece and were told to report the number of AMEs after each excerpt. Furthermore, subjects were instructed to remain still while listening to the excerpts and their lack of movement was verified via visual and EEG monitoring. Experts had significantly better behavioral performance (i.e. correctly reporting AME counts) than non-experts, though both groups had mean accuracies greater than 80%. These group differences were also reflected in the EEG correlates of key-change detection post-stimulus, with experts showing more significant, greater magnitude, longer periods of and earlier peaks in condition-discriminating EEG activity than novices. Using the timing of the maximum discriminating neural correlates, we performed source reconstruction and compared significant differences between cellists and non-musicians. We found significant differences that included a slightly right lateralized motor and frontal source distribution. The right lateralized motor activation is consistent with the cortical representation of the left hand – i.e. the hand a cellist would use, while playing, to generate the anomalous key-changes. In general, these results suggest that sensory anomalies detected by experts may in fact be partially a result of an embodied cognition, with a model of the action for generating the anomaly playing a role in its detection. PMID:24056235

Visual search and emotion: how children with autism spectrum disorders scan emotional scenes.

PubMed

Maccari, Lisa; Pasini, Augusto; Caroli, Emanuela; Rosa, Caterina; Marotta, Andrea; Martella, Diana; Fuentes, Luis J; Casagrande, Maria

2014-11-01

This study assessed visual search abilities, tested through the flicker task, in children diagnosed with autism spectrum disorders (ASDs). Twenty-two children diagnosed with ASD and 22 matched typically developing (TD) children were told to detect changes in objects of central interest or objects of marginal interest (MI) embedded in either emotion-laden (positive or negative) or neutral real-world pictures. The results showed that emotion-laden pictures equally interfered with performance of both ASD and TD children, slowing down reaction times compared with neutral pictures. Children with ASD were faster than TD children, particularly in detecting changes in MI objects, the most difficult condition. However, their performance was less accurate than performance of TD children just when the pictures were negative. These findings suggest that children with ASD have better visual search abilities than TD children only when the search is particularly difficult and requires strong serial search strategies. The emotional-social impairment that is usually considered as a typical feature of ASD seems to be limited to processing of negative emotional information.

Contingent capture of involuntary visual spatial attention does not differ between normally hearing children and proficient cochlear implant users.

PubMed

Kamke, Marc R; Van Luyn, Jeanette; Constantinescu, Gabriella; Harris, Jill

2014-01-01

Evidence suggests that deafness-induced changes in visual perception, cognition and attention may compensate for a hearing loss. Such alterations, however, may also negatively influence adaptation to a cochlear implant. This study investigated whether involuntary attentional capture by salient visual stimuli is altered in children who use a cochlear implant. Thirteen experienced implant users (aged 8-16 years) and age-matched normally hearing children were presented with a rapid sequence of simultaneous visual and auditory events. Participants were tasked with detecting numbers presented in a specified color and identifying a change in the tonal frequency whilst ignoring irrelevant visual distractors. Compared to visual distractors that did not possess the target-defining characteristic, target-colored distractors were associated with a decrement in visual performance (response time and accuracy), demonstrating a contingent capture of involuntary attention. Visual distractors did not, however, impair auditory task performance. Importantly, detection performance for the visual and auditory targets did not differ between the groups. These results suggest that proficient cochlear implant users demonstrate normal capture of visuospatial attention by stimuli that match top-down control settings.

Effects of VDT workstation lighting conditions on operator visual workload.

PubMed

Lin, Chiuhsiang Joe; Feng, Wen-Yang; Chao, Chin-Jung; Tseng, Feng-Yi

2008-04-01

Industrial lighting covers a wide range of different characteristics of working interiors and work tasks. This study investigated the effects of illumination on visual workload in visual display terminal (VDT) workstation. Ten college students (5 males and 5 females) were recruited as participants to perform VDT signal detection tasks. A randomized block design was utilized with four light colors (red, blue, green and white), two ambient illumination levels (20 lux and 340 lux), with the subject as the block. The dependent variables were the change of critical fusion frequency (CFF), visual acuity, reaction time of targets detection, error rates, and rating scores in a subjective questionnaire. The study results showed that both visual acuity and the subjective visual fatigue were significantly affected by the color of light. The illumination had significant effect on CFF threshold change and reaction time. Subjects prefer to perform VDT task under blue and white lights than green and red. Based on these findings, the study discusses and suggests ways of color lighting and ambient illumination to promote operators' visual performance and prevent visual fatigue effectively.

Incidence of human papillomavirus contamination of transvaginal probes in Japan and possible contamination prevention strategy.

PubMed

Kuwata, Tomoyuki; Takahashi, Hironori; Koibuchi, Harumi; Ichizuka, Kiyotake; Natori, Michiya; Matsubara, Shigeki

2016-10-01

To clarify the present status of human papillomavirus (HPV) contamination of transvaginal probes in Japan and propose a preventive method. This study was performed at three institutes: a tertiary center, secondary hospital, and primary facility. To identify contamination rates, probes were disinfected and covered with probe covers and condoms; the cover was changed for each patient. The probes were tested for HPV, and those with HPV detected were analyzed to identify the type of HPV. Next, nurses put on new gloves before covering the probe for each patient, and the probes were similarly tested for HPV. A total of 120 probes were tested, and HPV was detected from a total of five probes, a contamination rate of 4.2 % (5/120). HPV was detected in all three institutes. Importantly, high-risk HPV, i.e., HPV-52, 56, and 59, was detected. After the "glove change strategy" was implemented, HPV was not detected on any of 150 probes tested at any of the three institutions. In Japan, the HPV contamination rate of vaginal probes in routine practice was 4.2 %. There was no HPV contamination of probes after changing the gloves for cover exchange for each patient. This strategy may prevent HPV probe contamination.

[Early detection of cervical cancer in Chile: time for change].

PubMed

Léniz Martelli, Javiera; Van De Wyngard, Vanessa; Lagos, Marcela; Barriga, María Isabel; Puschel Illanes, Klaus; Ferreccio Readi, Catterina

2014-08-01

Mortality rates for cervical cancer (CC) in Chile are higher than those of developed countries and it has an unequal socioeconomic distribution. The recognition of human papilloma virus (HPV) as the causal agent of cervical cancer in the early 80's changed the prevention paradigms. Current goals are to prevent HPV infection by vaccination before the onset of sexual activity and to detect HPV infection in women older than 30 years. This article reviews CC prevention and early detection methods, discusses relevant evidence to support a change in Chile and presents an innovation proposal. A strategy of primary screening based on HPV detection followed by triage of HPV-positive women by colposcopy in primary care or by cytological or molecular reflex testing is proposed. Due to the existence in Chile of a well-organized nationwide CC prevention program, the replacement of a low-sensitivity screening test such as the Papanicolau test with a highly sensitive one such as HPV detection, could quickly improve the effectiveness of the program. The program also has a network of personnel qualified to conduct naked-eye inspections of the cervix, who could easily be trained to perform triage colposcopy. The incorporation of new prevention strategies could reduce the deaths of Chilean women and correct inequities.

Iohexol clearance is superior to creatinine-based renal function estimating equations in detecting short-term renal function decline in chronic heart failure.

PubMed

Cvan Trobec, Katja; Kerec Kos, Mojca; von Haehling, Stephan; Anker, Stefan D; Macdougall, Iain C; Ponikowski, Piotr; Lainscak, Mitja

2015-12-01

To compare the performance of iohexol plasma clearance and creatinine-based renal function estimating equations in monitoring longitudinal renal function changes in chronic heart failure (CHF) patients, and to assess the effects of body composition on the equation performance. Iohexol plasma clearance was measured in 43 CHF patients at baseline and after at least 6 months. Simultaneously, renal function was estimated with five creatinine-based equations (four- and six-variable Modification of Diet in Renal Disease, Cockcroft-Gault, Cockcroft-Gault adjusted for lean body mass, Chronic Kidney Disease Epidemiology Collaboration equation) and body composition was assessed using bioimpedance and dual-energy x-ray absorptiometry. Over a median follow-up of 7.5 months (range 6-17 months), iohexol clearance significantly declined (52.8 vs 44.4 mL/[min ×1.73 m2], P=0.001). This decline was significantly higher in patients receiving mineralocorticoid receptor antagonists at baseline (mean decline -22% of baseline value vs -3%, P=0.037). Mean serum creatinine concentration did not change significantly during follow-up and no creatinine-based renal function estimating equation was able to detect the significant longitudinal decline of renal function determined by iohexol clearance. After accounting for body composition, the accuracy of the equations improved, but not their ability to detect renal function decline. Renal function measured with iohexol plasma clearance showed relevant decline in CHF patients, particularly in those treated with mineralocorticoid receptor antagonists. None of the equations for renal function estimation was able to detect these changes. ClinicalTrials.gov registration number: NCT01829880.

Retrieval from long-term memory reduces working memory representations for visual features and their bindings.

PubMed

van Lamsweerde, Amanda E; Beck, Melissa R; Elliott, Emily M

2015-02-01

The ability to remember feature bindings is an important measure of the ability to maintain objects in working memory (WM). In this study, we investigated whether both object- and feature-based representations are maintained in WM. Specifically, we tested the hypotheses that retaining a greater number of feature representations (i.e., both as individual features and bound representations) results in a more robust representation of individual features than of feature bindings, and that retrieving information from long-term memory (LTM) into WM would cause a greater disruption to feature bindings. In four experiments, we examined the effects of retrieving a word from LTM on shape and color-shape binding change detection performance. We found that binding changes were more difficult to detect than individual-feature changes overall, but that the cost of retrieving a word from LTM was the same for both individual-feature and binding changes.

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.

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.

Quantifying the performance of in vivo portal dosimetry in detecting four types of treatment parameter variations

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

Bojechko, C.; Ford, E. C., E-mail: eford@uw.edu

Purpose: To quantify the ability of electronic portal imaging device (EPID) dosimetry used during treatment (in vivo) in detecting variations that can occur in the course of patient treatment. Methods: Images of transmitted radiation from in vivo EPID measurements were converted to a 2D planar dose at isocenter and compared to the treatment planning dose using a prototype software system. Using the treatment planning system (TPS), four different types of variability were modeled: overall dose scaling, shifting the positions of the multileaf collimator (MLC) leaves, shifting of the patient position, and changes in the patient body contour. The gamma passmore » rate was calculated for the modified and unmodified plans and used to construct a receiver operator characteristic (ROC) curve to assess the detectability of the different parameter variations. The detectability is given by the area under the ROC curve (AUC). The TPS was also used to calculate the impact of the variations on the target dose–volume histogram. Results: Nine intensity modulation radiation therapy plans were measured for four different anatomical sites consisting of 70 separate fields. Results show that in vivo EPID dosimetry was most sensitive to variations in the machine output, AUC = 0.70 − 0.94, changes in patient body habitus, AUC = 0.67 − 0.88, and systematic shifts in the MLC bank positions, AUC = 0.59 − 0.82. These deviations are expected to have a relatively small clinical impact [planning target volume (PTV) D{sub 99} change <7%]. Larger variations have even higher detectability. Displacements in the patient’s position and random variations in MLC leaf positions were not readily detectable, AUC < 0.64. The D{sub 99} of the PTV changed by up to 57% for the patient position shifts considered here. Conclusions: In vivo EPID dosimetry is able to detect relatively small variations in overall dose, systematic shifts of the MLC’s, and changes in the patient habitus. Shifts in the patient’s position which can introduce large changes in the target dose coverage were not readily detected.« less

Material damage modeling and detection in a thin metallic sheet and sandwich panel using passive acoustic transmission

NASA Astrophysics Data System (ADS)

Jiang, Hao

A method is developed for modeling, detecting, and locating material damage in homogeneous thin metallic sheets and sandwich panels. Analytical and numerical models are used along with non-contact, passive acoustic transmission measurements. It is shown that global and local damage mechanisms characterized by both material and geometrical changes in structural components can be detected using passive acoustic transmission measurements. Theoretical models of a flat sheet and sandwich panel are developed to describe the effects of global material damage due to density, modulus, or thickness changes on backplane radiated sound pressure level distributions. To describe the effects of local material damage, a three-segment stepped beam model and finite element beam, plate, and sandwich panel models are developed and analyzed using the acoustic transmission approach. It is shown that increases or decreases in transmitted sound energy occur behind a damaged material component that exhibits changes in thickness or other geometric or material properties. The damage due to thickness and density changes can be detected from the acoustic transmission, but modulus changes cannot. If the damage is located at an anti-node of a certain forced vibration pattern, the damage can be more readily observed in the data. Higher excitation frequencies within the operating spectrum are preferred to lower frequencies for damage detection. With the finite element beam, plate, and sandwich panel models, local damage detection has been performed in simulations. Experiments on a baffled homogeneous sheet and sandwich panel subjected to broadband acoustic energy show that transmitted intensity measurements with non-contact probes can be used to identify and locate material defects in the sheet and sandwich panel. Material damage is most readily identified where the changes in transmitted sound intensity are largest in the resonant frequency range of the panel. The three main contributions of this research are: (1) the use of non-contact sensing to detect global and localized damage in structural components; (2) the analytical and numerical modeling of material and geometrical damage mechanisms in structural components; and, (3) the experimental verification of acoustic transmission measurements for detecting both material and geometric damage mechanisms.

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.

A new metric for detecting change in slowly evolving brain tumors: validation in meningioma patients.

PubMed

Pohl, Kilian M; Konukoglu, Ender; Novellas, Sebastian; Ayache, Nicholas; Fedorov, Andriy; Talos, Ion-Florin; Golby, Alexandra; Wells, William M; Kikinis, Ron; Black, Peter M

2011-03-01

Change detection is a critical component in the diagnosis and monitoring of many slowly evolving pathologies. This article describes a semiautomatic monitoring approach using longitudinal medical images. We test the method on brain scans of patients with meningioma, which experts have found difficult to monitor because the tumor evolution is very slow and may be obscured by artifacts related to image acquisition. We describe a semiautomatic procedure targeted toward identifying difficult-to-detect changes in brain tumor imaging. The tool combines input from a medical expert with state-of-the-art technology. The software is easy to calibrate and, in less than 5 minutes, returns the total volume of tumor change in mm. We test the method on postgadolinium, T1-weighted magnetic resonance images of 10 patients with meningioma and compare our results with experts' findings. We also perform benchmark testing with synthetic data. Our experiments indicated that experts' visual inspections are not sensitive enough to detect subtle growth. Measurements based on experts' manual segmentations were highly accurate but also labor intensive. The accuracy of our approach was comparable to the experts' results. However, our approach required far less user input and generated more consistent measurements. The sensitivity of experts' visual inspection is often too low to detect subtle growth of meningiomas from longitudinal scans. Measurements based on experts' segmentation are highly accurate but generally too labor intensive for standard clinical settings. We described an alternative metric that provides accurate and robust measurements of subtle tumor changes while requiring a minimal amount of user input.

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.

TU-G-BRD-08: In-Vivo EPID Dosimetry: Quantifying the Detectability of Four Classes of Errors

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

Ford, E; Phillips, M; Bojechko, C

Purpose: EPID dosimetry is an emerging method for treatment verification and QA. Given that the in-vivo EPID technique is in clinical use at some centers, we investigate the sensitivity and specificity for detecting different classes of errors. We assess the impact of these errors using dose volume histogram endpoints. Though data exist for EPID dosimetry performed pre-treatment, this is the first study quantifying its effectiveness when used during patient treatment (in-vivo). Methods: We analyzed 17 patients; EPID images of the exit dose were acquired and used to reconstruct the planar dose at isocenter. This dose was compared to the TPSmore » dose using a 3%/3mm gamma criteria. To simulate errors, modifications were made to treatment plans using four possible classes of error: 1) patient misalignment, 2) changes in patient body habitus, 3) machine output changes and 4) MLC misalignments. Each error was applied with varying magnitudes. To assess the detectability of the error, the area under a ROC curve (AUC) was analyzed. The AUC was compared to changes in D99 of the PTV introduced by the simulated error. Results: For systematic changes in the MLC leaves, changes in the machine output and patient habitus, the AUC varied from 0.78–0.97 scaling with the magnitude of the error. The optimal gamma threshold as determined by the ROC curve varied between 84–92%. There was little diagnostic power in detecting random MLC leaf errors and patient shifts (AUC 0.52–0.74). Some errors with weak detectability had large changes in D99. Conclusion: These data demonstrate the ability of EPID-based in-vivo dosimetry in detecting variations in patient habitus and errors related to machine parameters such as systematic MLC misalignments and machine output changes. There was no correlation found between the detectability of the error using the gamma pass rate, ROC analysis and the impact on the dose volume histogram. Funded by grant R18HS022244 from AHRQ.« less

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

Changes in the Capacity of Visual Working Memory in 5- to 10-Year-Olds

ERIC Educational Resources Information Center

Riggs, Kevin J.; McTaggart, James; Simpson, Andrew; Freeman, Richard P. J.

2006-01-01

Using the Luck and Vogel change detection paradigm, we sought to investigate the capacity of visual working memory in 5-, 7-, and 10-year-olds. We found that performance on the task improved significantly with age and also obtained evidence that the capacity of visual working memory approximately doubles between 5 and 10 years of age, where it…

No Change of Body Mass, Fat Mass, and Skeletal Muscle Mass in Ultraendurance Swimmers after 12 Hours of Swimming

ERIC Educational Resources Information Center

Knechtle, Beat; Knechtle, Patrizia; Kaul, Rene; Kohler, Gotz

2009-01-01

We evaluated whether ultraendurance swimmers suffer a change of body mass, fat mass, skeletal muscle mass, total body water, and specific gravity of urine during a 12-hr swim in 12 male Caucasian ultraswimmers. Proton nuclear magnetic resonance of urine samples before and after the race was performed to detect alanine, lactate, and…

Rasch Modeling of Revised Token Test Performance: Validity and Sensitivity to Change

ERIC Educational Resources Information Center

Hula, William; Doyle, Patrick J.; McNeil, Malcolm R.; Mikolic, Joseph M.

2006-01-01

The purpose of this research was to examine the validity of the 55-item Revised Token Test (RTT) and to compare traditional and Rasch-based scores in their ability to detect group differences and change over time. The 55-item RTT was administered to 108 left- and right-hemisphere stroke survivors, and the data were submitted to Rasch analysis.…

[Effects of psychological stress on performances in open-field test of rats and tyrosine's modulation].

PubMed

Chen, Wei-Qiang; Cheng, Yi-Yong; Li, Shu-Tian; Hong, Yan; Wang, Dong-Lan; Hou, Yue

2009-02-01

To explore the effects of different doses of tyrosine modulation on behavioral performances in open field test of psychological stress rats. The animal model of psychological stress was developed by restraint stress for 21 days. Wistar rats were randomly assigned to five groups (n = 10) as follows: control group (CT), stress control group (SCT), low, medium and high-doses of tyrosine modulation stress groups (SLT, SMT and SIT). The changes of behavioral performances were examined by open-field test. Serum levels of cortisol, norepinephrine and dopamine were also detected. The levels of serum cortisol were all increased obviously in the four stress groups, and their bodyweight gainings were diminished. The behavioral performances of SCT rats in open-field test were changed significantly in contrast to that of CT rats. However, The behavioral performances of SMT and SHT rats were not different from that of CT rats. In addition, the serum levels of norepinephrine and dopamine were downregulated obviously in SCT and SLT groups, and no differences were observed in other groups. Psychological stress can impair body behavioral performances, and moderate tyrosine modulation may improve these abnormal changes. The related mechanisms may be involved with the changes of norepinephrine and dopamine.

Redundancy analysis allows improved detection of methylation changes in large genomic regions.

PubMed

Ruiz-Arenas, Carlos; González, Juan R

2017-12-14

DNA methylation is an epigenetic process that regulates gene expression. Methylation can be modified by environmental exposures and changes in the methylation patterns have been associated with diseases. Methylation microarrays measure methylation levels at more than 450,000 CpGs in a single experiment, and the most common analysis strategy is to perform a single probe analysis to find methylation probes associated with the outcome of interest. However, methylation changes usually occur at the regional level: for example, genomic structural variants can affect methylation patterns in regions up to several megabases in length. Existing DMR methods provide lists of Differentially Methylated Regions (DMRs) of up to only few kilobases in length, and cannot check if a target region is differentially methylated. Therefore, these methods are not suitable to evaluate methylation changes in large regions. To address these limitations, we developed a new DMR approach based on redundancy analysis (RDA) that assesses whether a target region is differentially methylated. Using simulated and real datasets, we compared our approach to three common DMR detection methods (Bumphunter, blockFinder, and DMRcate). We found that Bumphunter underestimated methylation changes and blockFinder showed poor performance. DMRcate showed poor power in the simulated datasets and low specificity in the real data analysis. Our method showed very high performance in all simulation settings, even with small sample sizes and subtle methylation changes, while controlling type I error. Other advantages of our method are: 1) it estimates the degree of association between the DMR and the outcome; 2) it can analyze a targeted or region of interest; and 3) it can evaluate the simultaneous effects of different variables. The proposed methodology is implemented in MEAL, a Bioconductor package designed to facilitate the analysis of methylation data. We propose a multivariate approach to decipher whether an outcome of interest alters the methylation pattern of a region of interest. The method is designed to analyze large target genomic regions and outperforms the three most popular methods for detecting DMRs. Our method can evaluate factors with more than two levels or the simultaneous effect of more than one continuous variable, which is not possible with the state-of-the-art methods.

Emotion detection deficits and changes in personality traits linked to loss of white matter integrity in primary progressive aphasia.

PubMed

Multani, Namita; Galantucci, Sebastiano; Wilson, Stephen M; Shany-Ur, Tal; Poorzand, Pardis; Growdon, Matthew E; Jang, Jung Yun; Kramer, Joel H; Miller, Bruce L; Rankin, Katherine P; Gorno-Tempini, Maria Luisa; Tartaglia, Maria Carmela

2017-01-01

Non-cognitive features including personality changes are increasingly recognized in the three PPA variants (semantic-svPPA, non fluent-nfvPPA, and logopenic-lvPPA). However, differences in emotion processing among the PPA variants and its association with white matter tracts are unknown. We compared emotion detection across the three PPA variants and healthy controls (HC), and related them to white matter tract integrity and cortical degeneration. Personality traits in the PPA group were also examined in relation to white matter tracts. Thirty-three patients with svPPA, nfvPPA, lvPPA, and 32 HC underwent neuropsychological assessment, emotion evaluation task (EET), and MRI scan. Patients' study partners were interviewed on the Clinical Dementia Rating Scale (CDR) and completed an interpersonal traits assessment, the Interpersonal Adjective Scale (IAS). Diffusion tensor imaging of uncinate fasciculus (UF), superior longitudinal fasciculus (SLF) and inferior longitudinal fasciculus (ILF), and voxel-based morphometry to derive gray matter volumes for orbitofrontal cortex (OFC), anterior temporal lobe (ATL) regions were performed. In addition, gray matter volumes of white matter tract-associated regions were also calculated: inferior frontal gyrus (IFG), posterior temporal lobe (PTL), inferior parietal lobe (IPL) and occipital lobe (OL). ANCOVA was used to compare EET performance. Partial correlation and multivariate linear regression were conducted to examine association between EET and neuroanatomical regions affected in PPA. All three variants of PPA performed significantly worse than HC on EET, and the svPPA group was least accurate at recognizing emotions. Performance on EET was related to the right UF, SLF, and ILF integrity. Regression analysis revealed EET performance primarily relates to the right UF integrity. The IAS subdomain, cold-hearted, was also associated with right UF integrity. Disease-specific emotion recognition and personality changes occur in the three PPA variants and are likely associated with disease-specific neuroanatomical changes. Loss of white matter integrity contributes as significantly as focal atrophy in behavioral changes in PPA.

Molecular Profiles for Lung Cancer Pathogenesis and Detection in US Veterans

DTIC Science & Technology

2012-10-01

will be further strengthened via Multiple Reaction Monitoring ( MRM ) performed on the remaining samples by the Vanderbilt group. MRM using mass...proteomics detects all protein changes in the sample in an unfocused fashion, MRM is targeted and highly selective, allowing us to specifically look for...proteins of interest. To this end, we have generated a list of candidate proteins for MRM utilizing shotgun proteomic, mRNA array, and miRNA array

Robust Face Detection from Still Images

DTIC Science & Technology

2014-01-01

significant change in false acceptance rates. Keywords— face detection; illumination; skin color variation; Haar-like features; OpenCV I. INTRODUCTION... OpenCV and an algorithm which used histogram equalization. The test is performed against 17 subjects under 576 viewing conditions from the extended Yale...original OpenCV algorithm proved the least accurate, having a hit rate of only 75.6%. It also had the lowest FAR but only by a slight margin at 25.2

Test and Evaluation Plan for the Explosive Device Detection Baseline (EDDB) Study

DTIC Science & Technology

1995-08-01

of civil aviation security has changed from hijackings to methods of countering bombings. This shift has markedly increased the need for improvements...to detect an environmental event or signal. SDT is a mathematical representation of human performance in deciding whether or not a signal is present...1970; Macmillan & Creelman , 1990; Snodgrass & Corwin, 1988). The chief difference between the measure c and its parametric alternative P3 lies in the

Automated Segmentation Methods of Drusen to Diagnose Age-Related Macular Degeneration Screening in Retinal Images.

PubMed

Kim, Young Jae; Kim, Kwang Gi

2018-01-01

Existing drusen measurement is difficult to use in clinic because it requires a lot of time and effort for visual inspection. In order to resolve this problem, we propose an automatic drusen detection method to help clinical diagnosis of age-related macular degeneration. First, we changed the fundus image to a green channel and extracted the ROI of the macular area based on the optic disk. Next, we detected the candidate group using the difference image of the median filter within the ROI. We also segmented vessels and removed them from the image. Finally, we detected the drusen through Renyi's entropy threshold algorithm. We performed comparisons and statistical analysis between the manual detection results and automatic detection results for 30 cases in order to verify validity. As a result, the average sensitivity was 93.37% (80.95%~100%) and the average DSC was 0.73 (0.3~0.98). In addition, the value of the ICC was 0.984 (CI: 0.967~0.993, p < 0.01), showing the high reliability of the proposed automatic method. We expect that the automatic drusen detection helps clinicians to improve the diagnostic performance in the detection of drusen on fundus image.

Improvement of automatic hemorrhage detection methods using brightness correction on fundus images

NASA Astrophysics Data System (ADS)

Hatanaka, Yuji; Nakagawa, Toshiaki; Hayashi, Yoshinori; Kakogawa, Masakatsu; Sawada, Akira; Kawase, Kazuhide; Hara, Takeshi; Fujita, Hiroshi

2008-03-01

We have been developing several automated methods for detecting abnormalities in fundus images. The purpose of this study is to improve our automated hemorrhage detection method to help diagnose diabetic retinopathy. We propose a new method for preprocessing and false positive elimination in the present study. The brightness of the fundus image was changed by the nonlinear curve with brightness values of the hue saturation value (HSV) space. In order to emphasize brown regions, gamma correction was performed on each red, green, and blue-bit image. Subsequently, the histograms of each red, blue, and blue-bit image were extended. After that, the hemorrhage candidates were detected. The brown regions indicated hemorrhages and blood vessels and their candidates were detected using density analysis. We removed the large candidates such as blood vessels. Finally, false positives were removed by using a 45-feature analysis. To evaluate the new method for the detection of hemorrhages, we examined 125 fundus images, including 35 images with hemorrhages and 90 normal images. The sensitivity and specificity for the detection of abnormal cases was were 80% and 88%, respectively. These results indicate that the new method may effectively improve the performance of our computer-aided diagnosis system for hemorrhages.

Detection of Early Ischemic Changes in Noncontrast CT Head Improved with "Stroke Windows".

PubMed

Mainali, Shraddha; Wahba, Mervat; Elijovich, Lucas

2014-01-01

Introduction. Noncontrast head CT (NCCT) is the standard radiologic test for patients presenting with acute stroke. Early ischemic changes (EIC) are often overlooked on initial NCCT. We determine the sensitivity and specificity of improved EIC detection by a standardized method of image evaluation (Stroke Windows). Methods. We performed a retrospective chart review to identify patients with acute ischemic stroke who had NCCT at presentation. EIC was defined by the presence of hyperdense MCA/basilar artery sign; sulcal effacement; basal ganglia/subcortical hypodensity; and loss of cortical gray-white differentiation. NCCT was reviewed with standard window settings and with specialized Stroke Windows. Results. Fifty patients (42% females, 58% males) with a mean NIHSS of 13.4 were identified. EIC was detected in 9 patients with standard windows, while EIC was detected using Stroke Windows in 35 patients (18% versus 70%; P < 0.0001). Hyperdense MCA sign was the most commonly reported EIC; it was better detected with Stroke Windows (14% and 36%; P < 0.0198). Detection of the remaining EIC also improved with Stroke Windows (6% and 46%; P < 0.0001). Conclusions. Detection of EIC has important implications in diagnosis and treatment of acute ischemic stroke. Utilization of Stroke Windows significantly improved detection of EIC.

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.

Information Foraging and Change Detection for Automated Science Exploration

NASA Technical Reports Server (NTRS)

Furlong, P. Michael; Dille, Michael

2016-01-01

This paper presents a new algorithm for autonomous on-line exploration in unknown environments. The objective is to free remote scientists from possibly-infeasible extensive preliminary site investigation prior to sending robotic agents. We simulate a common exploration task for an autonomous robot sampling the environment at various locations and compare performance against simpler control strategies. An extension is proposed and evaluated that further permits operation in the presence of environmental variability in which the robot encounters a change in the distribution underlying sampling targets. Experimental results indicate a strong improvement in performance across varied parameter choices for the scenario.

The role of behavioral, normative and control beliefs in breast self-examination.

PubMed

Mason, Tania E; White, Katherine M

2008-01-01

A limited number of studies have been conducted examining the role of beliefs in the prediction of breast self-examination (BSE) behavior in Australian women, particularly women under 50 years of age for which it is the primary method of early detection of breast cancer. The present research investigated the differences in behavioral, normative and control beliefs between BSE performers and non-performers, within a theory of planned behavior framework, to assist in the development of specific education programs aimed at increasing BSE amongst this demographic group. Two hundred and fifty-three women enrolled in an undergraduate psychology course completed a questionnaire assessing beliefs regarding BSE. One month later, these women reported their BSE behavior during the previous month. Multivariate analyses were performed to identify belief-based differences between BSE performers and non-performers. Underlying behavioral and control, but not normative, beliefs about BSE distinguished between BSE performers and non-performers. Performers were more likely than non-performers to believe that engaging in BSE would be associated with identifying a lump or breast change sooner and detecting a breast cancer earlier in its course. Non-performers were more likely to perceive factors such as forgetting to perform the behavior, lack of time, lack of knowledge about how to perform the behavior, laziness, and a lack of confidence in their ability to identify lumps and breast changes as factors preventing their control over the performance of BSE. The belief-based differences between BSE performers and non-performers found in this study can be used to inform health promotion strategies aimed at increasing BSE behavior in women less than 50 years of age.

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.

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

Four-year bacterial monitoring in the International Space Station-Japanese Experiment Module "Kibo" with culture-independent approach.

PubMed

Ichijo, Tomoaki; Yamaguchi, Nobuyasu; Tanigaki, Fumiaki; Shirakawa, Masaki; Nasu, Masao

2016-01-01

Studies on the relationships between humans and microbes in space habitation environments are critical for success in long-duration space missions, to reduce potential hazards to the crew and the spacecraft infrastructure. We performed microbial monitoring in the Japanese Experiment Module "Kibo", a part of the International Space Station, for 4 years after its completion, and analyzed samples with modern molecular microbiological techniques. Sampling was performed in September 2009, February 2011, and October 2012. The surface of the incubator, inside the door of the incubator, an air intake, air diffuser, and handrail were selected as sampling sites. Sampling was performed using the optimized swabbing method. Abundance and phylogenetic affiliation of bacteria on the interior surfaces of Kibo were determined by quantitative PCR and pyrosequencing, respectively. Bacteria in the phyla Proteobacteria (γ-subclass) and Firmicutes were frequently detected on the interior surfaces in Kibo. Families Staphylococcaceae and Enterobacteriaceae were dominant. Most bacteria detected belonged to the human microbiota; thus, we suggest that bacterial cells are transferred to the surfaces in Kibo from the astronauts. Environmental bacteria such as Legionella spp. were also detected. From the data on bacterial abundance and phylogenetic affiliation, Kibo has been microbiologically well maintained; however, the microbial community structure in Kibo may change with prolonged stay of astronauts. Continuous monitoring is required to obtain information on changes in the microbial community structure in Kibo.

Detecting aroma changes of local flavored green tea (Camellia sinensis) using electronic nose

NASA Astrophysics Data System (ADS)

Ralisnawati, D.; Sukartiko, A. C.; Suryandono, A.; Triyana, K.

2018-03-01

Indonesia is currently the sixth largest tea producer in the world. However, consumption of the product in the country was considered low. Besides tea, the country also has various local flavor ingredients that are potential to be developed. The addition of local flavored ingredients such as ginger, lemon grass, and lime leaves on green tea products is gaining acceptance from consumers and producers. The aroma of local flavored green tea was suspected to changes during storage, while its sensory testing has some limitations. Therefore, the study aimed to detect aroma changes of local flavors added in green tea using electronic nose (e-nose), an instrument developed to mimic the function of the human nose. The test was performed on a four-gram sample. The data was collected with 120 seconds of sensing time and 60 seconds of blowing time. Principal Component Analysis (PCA) was used to find out the aroma changes of local flavored green tea during storage. We observed that electronic nose could detect aroma changes of ginger flavored green tea from day 0 to day 6 with variance percentage 99.6%. Variance proportion of aroma changes of lemon grass flavored green tea from day 0 to day 6 was 99.3%. Variance proportion of aroma changes of lime leaves flavored green tea from day 0 to day 6 was 99.4%.

Longitudinal design considerations to optimize power to detect variances and covariances among rates of change: Simulation results based on actual longitudinal studies

PubMed Central

Rast, Philippe; Hofer, Scott M.

2014-01-01

We investigated the power to detect variances and covariances in rates of change in the context of existing longitudinal studies using linear bivariate growth curve models. Power was estimated by means of Monte Carlo simulations. Our findings show that typical longitudinal study designs have substantial power to detect both variances and covariances among rates of change in a variety of cognitive, physical functioning, and mental health outcomes. We performed simulations to investigate the interplay among number and spacing of occasions, total duration of the study, effect size, and error variance on power and required sample size. The relation between growth rate reliability (GRR) and effect size to the sample size required to detect power ≥ .80 was non-linear, with rapidly decreasing sample sizes needed as GRR increases. The results presented here stand in contrast to previous simulation results and recommendations (Hertzog, Lindenberger, Ghisletta, & von Oertzen, 2006; Hertzog, von Oertzen, Ghisletta, & Lindenberger, 2008; von Oertzen, Ghisletta, & Lindenberger, 2010), which are limited due to confounds between study length and number of waves, error variance with GCR, and parameter values which are largely out of bounds of actual study values. Power to detect change is generally low in the early phases (i.e. first years) of longitudinal studies but can substantially increase if the design is optimized. We recommend additional assessments, including embedded intensive measurement designs, to improve power in the early phases of long-term longitudinal studies. PMID:24219544

Effect of respiratory muscle training on exercise performance in healthy individuals: a systematic review and meta-analysis.

PubMed

Illi, Sabine K; Held, Ulrike; Frank, Irène; Spengler, Christina M

2012-08-01

Two distinct types of specific respiratory muscle training (RMT), i.e. respiratory muscle strength (resistive/threshold) and endurance (hyperpnoea) training, have been established to improve the endurance performance of healthy individuals. We performed a systematic review and meta-analysis in order to determine the factors that affect the change in endurance performance after RMT in healthy subjects. A computerized search was performed without language restriction in MEDLINE, EMBASE and CINAHL and references of original studies and reviews were searched for further relevant studies. RMT studies with healthy individuals assessing changes in endurance exercise performance by maximal tests (constant load, time trial, intermittent incremental, conventional [non-intermittent] incremental) were screened and abstracted by two independent investigators. A multiple linear regression model was used to identify effects of subjects' fitness, type of RMT (inspiratory or combined inspiratory/expiratory muscle strength training, respiratory muscle endurance training), type of exercise test, test duration and type of sport (rowing, running, swimming, cycling) on changes in performance after RMT. In addition, a meta-analysis was performed to determine the effect of RMT on endurance performance in those studies providing the necessary data. The multiple linear regression analysis including 46 original studies revealed that less fit subjects benefit more from RMT than highly trained athletes (6.0% per 10 mL · kg⁻¹ · min⁻¹ decrease in maximal oxygen uptake, 95% confidence interval [CI] 1.8, 10.2%; p = 0.005) and that improvements do not differ significantly between inspiratory muscle strength and respiratory muscle endurance training (p = 0.208), while combined inspiratory and expiratory muscle strength training seems to be superior in improving performance, although based on only 6 studies (+12.8% compared with inspiratory muscle strength training, 95% CI 3.6, 22.0%; p = 0.006). Furthermore, constant load tests (+16%, 95% CI 10.2, 22.9%) and intermittent incremental tests (+18.5%, 95% CI 10.8, 26.3%) detect changes in endurance performance better than conventional incremental tests (both p < 0.001) with no difference between time trials and conventional incremental tests (p = 0.286). With increasing test duration, improvements in performance are greater (+0.4% per minute test duration, 95% CI 0.1, 0.6%; p = 0.011) and the type of sport does not influence the magnitude of improvements (all p > 0.05). The meta-analysis, performed on eight controlled trials revealed a significant improvement in performance after RMT, which was detected by constant load tests, time trials and intermittent incremental tests, but not by conventional incremental tests. RMT improves endurance exercise performance in healthy individuals with greater improvements in less fit individuals and in sports of longer durations. The two most common types of RMT (inspiratory muscle strength and respiratory muscle endurance training) do not differ significantly in their effect, while combined inspiratory/expiratory strength training might be superior. Improvements are similar between different types of sports. Changes in performance can be detected by constant load tests, time trials and intermittent incremental tests only. Thus, all types of RMT can be used to improve exercise performance in healthy subjects but care must be taken regarding the test used to investigate the improvements.

Detecting and isolating abrupt changes in linear switching systems

NASA Astrophysics Data System (ADS)

Nazari, Sohail; Zhao, Qing; Huang, Biao

2015-04-01

In this paper, a novel fault detection and isolation (FDI) method for switching linear systems is developed. All input and output signals are assumed to be corrupted with measurement noises. In the proposed method, a 'lifted' linear model named as stochastic hybrid decoupling polynomial (SHDP) is introduced. The SHDP model governs the dynamics of the switching linear system with all different modes, and is independent of the switching sequence. The error-in-variable (EIV) representation of SHDP is derived, and is used for the fault residual generation and isolation following the well-adopted local approach. The proposed FDI method can detect and isolate the fault-induced abrupt changes in switching models' parameters without estimating the switching modes. Furthermore, in this paper, the analytical expressions of the gradient vector and Hessian matrix are obtained based on the EIV SHDP formulation, so that they can be used to implement the online fault detection scheme. The performance of the proposed method is then illustrated by simulation examples.

A dual-responsive colorimetric and fluorescent chemosensor based on diketopyrrolopyrrole derivative for naked-eye detection of Fe3+ and its practical application.

PubMed

Zhang, Shanshan; Sun, Tao; Xiao, Dejun; Yuan, Fang; Li, Tianduo; Wang, Enhua; Liu, Haixia; Niu, Qingfen

2018-01-15

A novel dual-responsive colorimetric and fluorescent chemosensor L based on diketopyrrolopyrrole derivative for Fe 3+ detection was designed and synthesized. In presence of Fe 3+ , sensor L displayed strong colorimetric response as amaranth to rose pink and significant fluorescence enhancement and chromogenic change, which served as a naked-eye indicator by an obvious color change from purple to red. The binding constant for L-Fe 3+ complex was found as 2.4×10 4 with the lower detection limit of 14.3nM. The sensing mechanism was investigated in detail by fluorescence measurements, IR and 1 H NMR spectra. Sensor L for Fe 3+ detection also exhibited high anti-interference performance, good reversibility, wide pH response range and instantaneous response time. Furthermore, the sensor L has been used to quantify Fe 3+ ions in practical water samples with good recovery. Copyright © 2017 Elsevier B.V. All rights reserved.

Influence of humidity on spectral performance for near-infrared detection of fruit

NASA Astrophysics Data System (ADS)

Zhou, Ying; Fu, Xiaping; Ying, Yibin

2006-10-01

Spectral performance would be affected by many factors such as temperature, equipment parameters and so on. Humidity fluctuations may occur in practice because of varying weather conditions. The objective of this research was to find out whether the change of humidity would influence the near infrared spectrum of samples. In this trial, an airproof, humidity-controllable test-bed was established to change the humidity of the mini environment. At 40%, 50%, 60%, 70% and 80% degrees of humidity, each sample's final spectrum was attained by removing the background's spectrum from the sample's. For whether the influence of the sample's and the background's spectrum are equal was not known, This trial was divided into two groups: detecting background and sample at each degree of humidity (group 1) and background's detecting just happened at 40% degree of humidity (group 2). This research was based on the hardware of NEXUS intelligent FT-IR spectrometer, made by Nicolet instrument company U.S.A, with using fiber optic diffuse reflectance accessory. The final spectrum was analysed using single variance analysis and Mahalanobis Distance methods. The result shows that neither in group 1 nor 2, humidity had little influence on NIR.

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

Seismic detection of increased degassing before Kīlauea's 2008 summit explosion.

PubMed

Johnson, Jessica H; Poland, Michael P

2013-01-01

The 2008 explosion that started a new eruption at the summit of Kīlauea Volcano, Hawai'i, was not preceded by a dramatic increase in earthquakes nor inflation, but was associated with increases in SO2 emissions and seismic tremor. Here we perform shear wave splitting analysis on local earthquakes spanning the onset of the eruption. Shear wave splitting measures seismic anisotropy and is traditionally used to infer changes in crustal stress over time. We show that shear wave splitting may also vary due to changes in volcanic degassing. The orientation of fast shear waves at Kīlauea is usually controlled by structure, but in 2008 showed changes with increased SO2 emissions preceding the start of the summit eruption. This interpretation for changing anisotropy is supported by corresponding decreases in Vp/Vs ratio. Our result demonstrates a novel method for detecting changes in gas flux using seismic observations and provides a new tool for monitoring under-instrumented volcanoes.

Seismic detection of increased degassing before Kīlauea's 2008 summit explosion

USGS Publications Warehouse

Johnson, Jessica H.; Poland, Michael P.

2013-01-01

The 2008 explosion that started a new eruption at the summit of Kīlauea Volcano, Hawai‘i, was not preceded by a dramatic increase in earthquakes nor inflation, but was associated with increases in SO2 emissions and seismic tremor. Here we perform shear wave splitting analysis on local earthquakes spanning the onset of the eruption. Shear wave splitting measures seismic anisotropy and is traditionally used to infer changes in crustal stress over time. We show that shear wave splitting may also vary due to changes in volcanic degassing. The orientation of fast shear waves at Kīlauea is usually controlled by structure, but in 2008 showed changes with increased SO2 emissions preceding the start of the summit eruption. This interpretation for changing anisotropy is supported by corresponding decreases in Vp/Vs ratio. Our result demonstrates a novel method for detecting changes in gas flux using seismic observations and provides a new tool for monitoring under-instrumented volcanoes.

Familiarization, validity and smallest detectable difference of the isometric squat test in evaluating maximal strength.

PubMed

Drake, David; Kennedy, Rodney; Wallace, Eric

2018-02-06

Isometric multi-joint tests are considered reliable and have strong relationships with 1RM performance. However, limited evidence is available for the isometric squat in terms of effects of familiarization and reliability. This study aimed to assess, the effect of familiarization, stability reliability, determine the smallest detectible difference, and the correlation of the isometric squat test with 1RM squat performance. Thirty-six strength-trained participants volunteered to take part in this study. Following three familiarization sessions, test-retest reliability was evaluated with a 48-hour window between each time point. Isometric squat peak, net and relative force were assessed. Results showed three familiarizations were required, isometric squat had a high level of stability reliability and smallest detectible difference of 11% for peak and relative force. Isometric strength at a knee angle of ninety degrees had a strong significant relationship with 1RM squat performance. In conclusion, the isometric squat is a valid test to assess multi-joint strength and can discriminate between strong and weak 1RM squat performance. Changes greater than 11% in peak and relative isometric squat performance should be considered as meaningful in participants who are familiar with the test.

Multi-Tasking and Choice of Training Data Influencing Parietal ERP Expression and Single-Trial Detection-Relevance for Neuroscience and Clinical Applications.

PubMed

Kirchner, Elsa A; Kim, Su Kyoung

2018-01-01

Event-related potentials (ERPs) are often used in brain-computer interfaces (BCIs) for communication or system control for enhancing or regaining control for motor-disabled persons. Especially results from single-trial EEG classification approaches for BCIs support correlations between single-trial ERP detection performance and ERP expression. Hence, BCIs can be considered as a paradigm shift contributing to new methods with strong influence on both neuroscience and clinical applications. Here, we investigate the relevance of the choice of training data and classifier transfer for the interpretability of results from single-trial ERP detection. In our experiments, subjects performed a visual-motor oddball task with motor-task relevant infrequent ( targets ), motor-task irrelevant infrequent ( deviants ), and motor-task irrelevant frequent ( standards ) stimuli. Under dual-task condition, a secondary senso-motor task was performed, compared to the simple-task condition. For evaluation, average ERP analysis and single-trial detection analysis with different numbers of electrodes were performed. Further, classifier transfer was investigated between simple and dual task. Parietal positive ERPs evoked by target stimuli (but not by deviants) were expressed stronger under dual-task condition, which is discussed as an increase of task emphasis and brain processes involved in task coordination and change of task set. Highest classification performance was found for targets irrespective whether all 62, 6 or 2 parietal electrodes were used. Further, higher detection performance of targets compared to standards was achieved under dual-task compared to simple-task condition in case of training on data from 2 parietal electrodes corresponding to results of ERP average analysis. Classifier transfer between tasks improves classification performance in case that training took place on more varying examples (from dual task). In summary, we showed that P300 and overlaying parietal positive ERPs can successfully be detected while subjects are performing additional ongoing motor activity. This supports single-trial detection of ERPs evoked by target events to, e.g., infer a patient's attentional state during therapeutic intervention.

Technical Review of the Domestic Nuclear Detection Office Transformational and Applied Research Directorate’s Research and Development Program

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

Lavietes, Anthony; Trebes, James; Borchers, Robert

2013-01-01

At the request of the Domestic Nuclear Detection Office (DNDO), a Review Committee comprised of representatives from the American Physical Society (APS) Panel on Public Affairs (POPA) and the Institute of Electrical and Electronics Engineers (IEEE) Nuclear and Plasma Sciences Society (NPSS) performed a technical review of the DNDO Transformational and Applied Research Directorate (TARD) research and development program. TARD’s principal objective is to address gaps in the Global Nuclear Detection Architecture (GNDA) through improvements in the performance, cost, and operational burden of detectors and systems. The charge to the Review Committee was to investigate the existing TARD research andmore » development plan and portfolio, recommend changes to the existing plan, and recommend possible new R&D areas and opportunities. The Review Committee has several recommendations.« less

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.

Antenna Allocation in MIMO Radar with Widely Separated Antennas for Multi-Target Detection

PubMed Central

Gao, Hao; Wang, Jian; Jiang, Chunxiao; Zhang, Xudong

2014-01-01

In this paper, we explore a new resource called multi-target diversity to optimize the performance of multiple input multiple output (MIMO) radar with widely separated antennas for detecting multiple targets. In particular, we allocate antennas of the MIMO radar to probe different targets simultaneously in a flexible manner based on the performance metric of relative entropy. Two antenna allocation schemes are proposed. In the first scheme, each antenna is allocated to illuminate a proper target over the entire illumination time, so that the detection performance of each target is guaranteed. The problem is formulated as a minimum makespan scheduling problem in the combinatorial optimization framework. Antenna allocation is implemented through a branch-and-bound algorithm and an enhanced factor 2 algorithm. In the second scheme, called antenna-time allocation, each antenna is allocated to illuminate different targets with different illumination time. Both antenna allocation and time allocation are optimized based on illumination probabilities. Over a large range of transmitted power, target fluctuations and target numbers, both of the proposed antenna allocation schemes outperform the scheme without antenna allocation. Moreover, the antenna-time allocation scheme achieves a more robust detection performance than branch-and-bound algorithm and the enhanced factor 2 algorithm when the target number changes. PMID:25350505

Antenna allocation in MIMO radar with widely separated antennas for multi-target detection.

PubMed

Gao, Hao; Wang, Jian; Jiang, Chunxiao; Zhang, Xudong

2014-10-27

In this paper, we explore a new resource called multi-target diversity to optimize the performance of multiple input multiple output (MIMO) radar with widely separated antennas for detecting multiple targets. In particular, we allocate antennas of the MIMO radar to probe different targets simultaneously in a flexible manner based on the performance metric of relative entropy. Two antenna allocation schemes are proposed. In the first scheme, each antenna is allocated to illuminate a proper target over the entire illumination time, so that the detection performance of each target is guaranteed. The problem is formulated as a minimum makespan scheduling problem in the combinatorial optimization framework. Antenna allocation is implemented through a branch-and-bound algorithm and an enhanced factor 2 algorithm. In the second scheme, called antenna-time allocation, each antenna is allocated to illuminate different targets with different illumination time. Both antenna allocation and time allocation are optimized based on illumination probabilities. Over a large range of transmitted power, target fluctuations and target numbers, both of the proposed antenna allocation schemes outperform the scheme without antenna allocation. Moreover, the antenna-time allocation scheme achieves a more robust detection performance than branch-and-bound algorithm and the enhanced factor 2 algorithm when the target number changes.

Optimized spatio-temporal descriptors for real-time fall detection: comparison of support vector machine and Adaboost-based classification

NASA Astrophysics Data System (ADS)

Charfi, Imen; Miteran, Johel; Dubois, Julien; Atri, Mohamed; Tourki, Rached

2013-10-01

We propose a supervised approach to detect falls in a home environment using an optimized descriptor adapted to real-time tasks. We introduce a realistic dataset of 222 videos, a new metric allowing evaluation of fall detection performance in a video stream, and an automatically optimized set of spatio-temporal descriptors which fed a supervised classifier. We build the initial spatio-temporal descriptor named STHF using several combinations of transformations of geometrical features (height and width of human body bounding box, the user's trajectory with her/his orientation, projection histograms, and moments of orders 0, 1, and 2). We study the combinations of usual transformations of the features (Fourier transform, wavelet transform, first and second derivatives), and we show experimentally that it is possible to achieve high performance using support vector machine and Adaboost classifiers. Automatic feature selection allows to show that the best tradeoff between classification performance and processing time is obtained by combining the original low-level features with their first derivative. Hence, we evaluate the robustness of the fall detection regarding location changes. We propose a realistic and pragmatic protocol that enables performance to be improved by updating the training in the current location with normal activities records.

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.

Applying a 2D based CAD scheme for detecting micro-calcification clusters using digital breast tomosynthesis images: an assessment

NASA Astrophysics Data System (ADS)

Park, Sang Cheol; Zheng, Bin; Wang, Xiao-Hui; Gur, David

2008-03-01

Digital breast tomosynthesis (DBT) has emerged as a promising imaging modality for screening mammography. However, visually detecting micro-calcification clusters depicted on DBT images is a difficult task. Computer-aided detection (CAD) schemes for detecting micro-calcification clusters depicted on mammograms can achieve high performance and the use of CAD results can assist radiologists in detecting subtle micro-calcification clusters. In this study, we compared the performance of an available 2D based CAD scheme with one that includes a new grouping and scoring method when applied to both projection and reconstructed DBT images. We selected a dataset involving 96 DBT examinations acquired on 45 women. Each DBT image set included 11 low dose projection images and a varying number of reconstructed image slices ranging from 18 to 87. In this dataset 20 true-positive micro-calcification clusters were visually detected on the projection images and 40 were visually detected on the reconstructed images, respectively. We first applied the CAD scheme that was previously developed in our laboratory to the DBT dataset. We then tested a new grouping method that defines an independent cluster by grouping the same cluster detected on different projection or reconstructed images. We then compared four scoring methods to assess the CAD performance. The maximum sensitivity level observed for the different grouping and scoring methods were 70% and 88% for the projection and reconstructed images with a maximum false-positive rate of 4.0 and 15.9 per examination, respectively. This preliminary study demonstrates that (1) among the maximum, the minimum or the average CAD generated scores, using the maximum score of the grouped cluster regions achieved the highest performance level, (2) the histogram based scoring method is reasonably effective in reducing false-positive detections on the projection images but the overall CAD sensitivity is lower due to lower signal-to-noise ratio, and (3) CAD achieved higher sensitivity and higher false-positive rate (per examination) on the reconstructed images. We concluded that without changing the detection threshold or performing pre-filtering to possibly increase detection sensitivity, current CAD schemes developed and optimized for 2D mammograms perform relatively poorly and need to be re-optimized using DBT datasets and new grouping and scoring methods need to be incorporated into the schemes if these are to be used on the DBT examinations.

Video Shot Boundary Detection Using QR-Decomposition and Gaussian Transition Detection

NASA Astrophysics Data System (ADS)

Amiri, Ali; Fathy, Mahmood

2010-12-01

This article explores the problem of video shot boundary detection and examines a novel shot boundary detection algorithm by using QR-decomposition and modeling of gradual transitions by Gaussian functions. Specifically, the authors attend to the challenges of detecting gradual shots and extracting appropriate spatiotemporal features that affect the ability of algorithms to efficiently detect shot boundaries. The algorithm utilizes the properties of QR-decomposition and extracts a block-wise probability function that illustrates the probability of video frames to be in shot transitions. The probability function has abrupt changes in hard cut transitions, and semi-Gaussian behavior in gradual transitions. The algorithm detects these transitions by analyzing the probability function. Finally, we will report the results of the experiments using large-scale test sets provided by the TRECVID 2006, which has assessments for hard cut and gradual shot boundary detection. These results confirm the high performance of the proposed algorithm.

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.

Screening unlabeled DNA targets with randomly ordered fiber-optic gene arrays.

PubMed

Steemers, F J; Ferguson, J A; Walt, D R

2000-01-01

We have developed a randomly ordered fiber-optic gene array for rapid, parallel detection of unlabeled DNA targets with surface immobilized molecular beacons (MB) that undergo a conformational change accompanied by a fluorescence change in the presence of a complementary DNA target. Microarrays are prepared by randomly distributing MB-functionalized 3-microm diameter microspheres in an array of wells etched in a 500-microm diameter optical imaging fiber. Using several MBs, each designed to recognize a different target, we demonstrate the selective detection of genomic cystic fibrosis related targets. Positional registration and fluorescence response monitoring of the microspheres was performed using an optical encoding scheme and an imaging fluorescence microscope system.

Ratiometric analysis of in vivo retinal layer thicknesses in multiple sclerosis

NASA Astrophysics Data System (ADS)

Bhaduri, Basanta; Nolan, Ryan M.; Shelton, Ryan L.; Pilutti, Lara A.; Motl, Robert W.; Boppart, Stephen A.

2016-09-01

We performed ratiometric analysis of retinal optical coherence tomography images for the first time in multiple sclerosis (MS) patients. The ratiometric analysis identified differences in several retinal layer thickness ratios in the cohort of MS subjects without a history of optic neuritis (ON) compared to healthy control (HC) subjects, and there was no difference in standard retinal nerve fiber layer thickness (RNFLT). The difference in such ratios between HC subjects and those with mild MS-disability, without a difference in RNFLT, further suggests the possibility of using layer ratiometric analysis for detecting early retinal changes in MS. Ratiometric analysis may be useful and potentially more sensitive for detecting disease changes in MS.

Diagnostic Imaging of Reproductive Tract Disorders in Reptiles.

PubMed

Gumpenberger, Michaela

2017-05-01

Diagnostic imaging of the reproductive tract in reptiles is used for gender determination, evaluation of breeding status, detection of pathologic changes, and supervising treatment. Whole-body radiographs provide an overview and support detection of mineralized egg shells. Sonography is used to evaluate follicles, nonmineralized eggs, and the salpinx in all reptiles. Computed tomography is able to overcome imaging limitations in chelonian species. This article provides detailed information about the performance of different imaging techniques. Multiple images demonstrate the physiologic appearance of the male and female reproductive tract in various reptile species and pathologic changes. Advantages and disadvantages of radiography, sonography, and computed tomography are described. Copyright © 2016 Elsevier Inc. All rights reserved.

Spectral Induced Polarization Signatures of Ethanol in Sand-Clay Medium

EPA Science Inventory

The spectral Induced Polarization (SIP) method has previously been investigated as a tool for detecting physicochemical changes occurring as result of clay-organic interactions in porous media. We performed SIP measurements with a dynamic signal analyzer (NI-4551) on laboratory ...

Development of the MASW method for pavement evaluation.

DOT National Transportation Integrated Search

2016-07-31

The purpose of this research is to establish a recommended procedure for performing multichannel analysis of surface waves (MASW) on pavements as well as evaluating the ability of MASW to detect a change in shear wave velocity as damage in concrete i...

Algorithms for Autonomous Plume Detection on Outer Planet Satellites

NASA Astrophysics Data System (ADS)

Lin, Y.; Bunte, M. K.; Saripalli, S.; Greeley, R.

2011-12-01

We investigate techniques for automated detection of geophysical events (i.e., volcanic plumes) from spacecraft images. The algorithms presented here have not been previously applied to detection of transient events on outer planet satellites. We apply Scale Invariant Feature Transform (SIFT) to raw images of Io and Enceladus from the Voyager, Galileo, Cassini, and New Horizons missions. SIFT produces distinct interest points in every image; feature descriptors are reasonably invariant to changes in illumination, image noise, rotation, scaling, and small changes in viewpoint. We classified these descriptors as plumes using the k-nearest neighbor (KNN) algorithm. In KNN, an object is classified by its similarity to examples in a training set of images based on user defined thresholds. Using the complete database of Io images and a selection of Enceladus images where 1-3 plumes were manually detected in each image, we successfully detected 74% of plumes in Galileo and New Horizons images, 95% in Voyager images, and 93% in Cassini images. Preliminary tests yielded some false positive detections; further iterations will improve performance. In images where detections fail, plumes are less than 9 pixels in size or are lost in image glare. We compared the appearance of plumes and illuminated mountain slopes to determine the potential for feature classification. We successfully differentiated features. An advantage over other methods is the ability to detect plumes in non-limb views where they appear in the shadowed part of the surface; improvements will enable detection against the illuminated background surface where gradient changes would otherwise preclude detection. This detection method has potential applications to future outer planet missions for sustained plume monitoring campaigns and onboard automated prioritization of all spacecraft data. The complementary nature of this method is such that it could be used in conjunction with edge detection algorithms to increase effectiveness. We have demonstrated an ability to detect transient events above the planetary limb and on the surface and to distinguish feature classes in spacecraft images.

Non-invasive detection of the freezing of gait in Parkinson's disease using spectral and wavelet features.

PubMed

Nazarzadeh, Kimia; Arjunan, Sridhar P; Kumar, Dinesh K; Das, Debi Prasad

2016-08-01

In this study, we have analyzed the accelerometer data recorded during gait analysis of Parkinson disease patients for detecting freezing of gait (FOG) episodes. The proposed method filters the recordings for noise reduction of the leg movement changes and computes the wavelet coefficients to detect FOG events. Publicly available FOG database was used and the technique was evaluated using receiver operating characteristic (ROC) analysis. Results show a higher performance of the wavelet feature in discrimination of the FOG events from the background activity when compared with the existing technique.

Cluster signal-to-noise analysis for evaluation of the information content in an image.

PubMed

Weerawanich, Warangkana; Shimizu, Mayumi; Takeshita, Yohei; Okamura, Kazutoshi; Yoshida, Shoko; Yoshiura, Kazunori

2018-01-01

(1) To develop an observer-free method of analysing image quality related to the observer performance in the detection task and (2) to analyse observer behaviour patterns in the detection of small mass changes in cone-beam CT images. 13 observers detected holes in a Teflon phantom in cone-beam CT images. Using the same images, we developed a new method, cluster signal-to-noise analysis, to detect the holes by applying various cut-off values using ImageJ and reconstructing cluster signal-to-noise curves. We then evaluated the correlation between cluster signal-to-noise analysis and the observer performance test. We measured the background noise in each image to evaluate the relationship with false positive rates (FPRs) of the observers. Correlations between mean FPRs and intra- and interobserver variations were also evaluated. Moreover, we calculated true positive rates (TPRs) and accuracies from background noise and evaluated their correlations with TPRs from observers. Cluster signal-to-noise curves were derived in cluster signal-to-noise analysis. They yield the detection of signals (true holes) related to noise (false holes). This method correlated highly with the observer performance test (R 2 = 0.9296). In noisy images, increasing background noise resulted in higher FPRs and larger intra- and interobserver variations. TPRs and accuracies calculated from background noise had high correlation with actual TPRs from observers; R 2 was 0.9244 and 0.9338, respectively. Cluster signal-to-noise analysis can simulate the detection performance of observers and thus replace the observer performance test in the evaluation of image quality. Erroneous decision-making increased with increasing background noise.

Optical biosensor system for the quick and reliable detection of virus infections: VIROSENS

NASA Astrophysics Data System (ADS)

Proll, Günther; Hartjes, Anja; Sinclair, Alexander; Markovic, Goran; Pröll, Florian; Patel, Pranav; Niedrig, Matthias

2014-10-01

Viral infections are of special threat because they can induce severe courses of disease but only few medical treatments are available. Because of socio-economic and climate changes, increased worldwide mobility and population growth, the risk of newly occurring and quickly spreading viral pathogens has increased. A diagnosis of these diseases at an early stage is essential for a quick risk assessment and a proper health management as well as patient's treatment in an optimal way. Currently, the diagnosis of such diseases is based on time consuming and costly detection methods that can only be performed by specially trained personnel in laboratories at specific security levels. Aim of the project VIROSENS is the development of a biosensor platform that can specifically detect virus particles as well as virus-specific antibodies out of biological matrices like blood, serum, plasma and other body fluids. For this purpose, a disposable cartridge for such antibody- and virus-arrays is designed and developed within the project. The optical detection of viruses is performed with a portable device that will be benchmarked and evaluated concerning currently used standard detection methods in terms of its analytical performance. Within this project, a novel combination of serological tests and direct detection of virus particles will be developed, which will provide faster and more reliable results than presently available and used test systems.

Event-related potentials reveal rapid registration of features of infrequent changes during change blindness

PubMed Central

2010-01-01

Background Change blindness refers to a failure to detect changes between consecutively presented images separated by, for example, a brief blank screen. As an explanation of change blindness, it has been suggested that our representations of the environment are sparse outside focal attention and even that changed features may not be represented at all. In order to find electrophysiological evidence of neural representations of changed features during change blindness, we recorded event-related potentials (ERPs) in adults in an oddball variant of the change blindness flicker paradigm. Methods ERPs were recorded when subjects performed a change detection task in which the modified images were infrequently interspersed (p = .2) among the frequently (p = .8) presented unmodified images. Responses to modified and unmodified images were compared in the time window of 60-100 ms after stimulus onset. Results ERPs to infrequent modified images were found to differ in amplitude from those to frequent unmodified images at the midline electrodes (Fz, Pz, Cz and Oz) at the latency of 60-100 ms even when subjects were unaware of changes (change blindness). Conclusions The results suggest that the brain registers changes very rapidly, and that changed features in images are neurally represented even without participants' ability to report them. PMID:20181126

Evaluating detection and estimation capabilities of magnetometer-based vehicle sensors

NASA Astrophysics Data System (ADS)

Slater, David M.; Jacyna, Garry M.

2013-05-01

In an effort to secure the northern and southern United States borders, MITRE has been tasked with developing Modeling and Simulation (M&S) tools that accurately capture the mapping between algorithm-level Measures of Performance (MOP) and system-level Measures of Effectiveness (MOE) for current/future surveillance systems deployed by the the Customs and Border Protection Office of Technology Innovations and Acquisitions (OTIA). This analysis is part of a larger M&S undertaking. The focus is on two MOPs for magnetometer-based Unattended Ground Sensors (UGS). UGS are placed near roads to detect passing vehicles and estimate properties of the vehicle's trajectory such as bearing and speed. The first MOP considered is the probability of detection. We derive probabilities of detection for a network of sensors over an arbitrary number of observation periods and explore how the probability of detection changes when multiple sensors are employed. The performance of UGS is also evaluated based on the level of variance in the estimation of trajectory parameters. We derive the Cramer-Rao bounds for the variances of the estimated parameters in two cases: when no a priori information is known and when the parameters are assumed to be Gaussian with known variances. Sample results show that UGS perform significantly better in the latter case.

Defect detection performance of the UCSD non-contact air-coupled ultrasonic guided wave inspection of rails prototype

NASA Astrophysics Data System (ADS)

Mariani, Stefano; Nguyen, Thompson V.; Sternini, Simone; Lanza di Scalea, Francesco; Fateh, Mahmood; Wilson, Robert

2016-04-01

The University of California at San Diego (UCSD), under a Federal Railroad Administration (FRA) Office of Research and Development (R&D) grant, is developing a system for high-speed and non-contact rail defect detection. A prototype using an ultrasonic air-coupled guided wave signal generation and air-coupled signal detection, paired with a real-time statistical analysis algorithm, has been realized. This system requires a specialized filtering approach based on electrical impedance matching due to the inherently poor signal-to-noise ratio of air-coupled ultrasonic measurements in rail steel. Various aspects of the prototype have been designed with the aid of numerical analyses. In particular, simulations of ultrasonic guided wave propagation in rails have been performed using a Local Interaction Simulation Approach (LISA) algorithm. The system's operating parameters were selected based on Receiver Operating Characteristic (ROC) curves, which provide a quantitative manner to evaluate different detection performances based on the trade-off between detection rate and false positive rate. The prototype based on this technology was tested in October 2014 at the Transportation Technology Center (TTC) in Pueblo, Colorado, and again in November 2015 after incorporating changes based on lessons learned. Results from the 2015 field test are discussed in this paper.

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 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.

Transmission electron microscopy of the preclinical phase of experimental phytophotodermatitis.

PubMed

Almeida, Hiram Larangeira de; Sotto, Miriam Nakagami; Castro, Luis Antonio Suita de; Rocha, Nara Moreira

2008-06-01

To examine the epidermis in induced phytophotodermatitis using transmission electron microscopy in order to detect histologic changes even before lesions are visible by light microscopy. In the first six hours after the experimental induction of phytophotodermatitis, no changes are detectable by light microscopy. Only after 24 hours can keratinocyte necrosis and epidermal vacuolization be detected histologically, and blisters form by 48 hours. The dorsum of four adult rats (Rattus norvegicus) was manually epilated. After painting the right half of the rat with the peel juice of Tahiti lemon, they were exposed to sunlight for eight minutes under general anesthesia. The left side was used as the control and exposed to sunlight only. Biopsies were performed immediately after photoinduction and one and two hours later, and the tissue was analyzed by transmission electron microscopy. No histological changes were seen on the control side. Immediately after induction, vacuolization in keratinocytes was observed. After one hour, desmosomal changes were also observed in addition to vacuolization. Keratin filaments were not attached to the desmosomal plaque. Free desmosomes and membrane ruptures were also seen. At two hours after induction, similar changes were found, and granular degeneration of keratin was also observed. The interaction of sunlight and psoralens generates a photoproduct that damages keratinocyte proteins, leading to keratinocyte necrosis and blister formation. Transmission electron microscopy can detect vacuolization, lesions of the membrane, and desmosomes in the first two hours after experimental induction of phytophotodermatitis.

Implementation of a channelized Hotelling observer model to assess image quality of x-ray angiography systems

PubMed Central

Favazza, Christopher P.; Fetterly, Kenneth A.; Hangiandreou, Nicholas J.; Leng, Shuai; Schueler, Beth A.

2015-01-01

Abstract. Evaluation of flat-panel angiography equipment through conventional image quality metrics is limited by the scope of standard spatial-domain image quality metric(s), such as contrast-to-noise ratio and spatial resolution, or by restricted access to appropriate data to calculate Fourier domain measurements, such as modulation transfer function, noise power spectrum, and detective quantum efficiency. Observer models have been shown capable of overcoming these limitations and are able to comprehensively evaluate medical-imaging systems. We present a spatial domain-based channelized Hotelling observer model to calculate the detectability index (DI) of our different sized disks and compare the performance of different imaging conditions and angiography systems. When appropriate, changes in DIs were compared to expectations based on the classical Rose model of signal detection to assess linearity of the model with quantum signal-to-noise ratio (SNR) theory. For these experiments, the estimated uncertainty of the DIs was less than 3%, allowing for precise comparison of imaging systems or conditions. For most experimental variables, DI changes were linear with expectations based on quantum SNR theory. DIs calculated for the smallest objects demonstrated nonlinearity with quantum SNR theory due to system blur. Two angiography systems with different detector element sizes were shown to perform similarly across the majority of the detection tasks. PMID:26158086

Balancing the Needs of Personalization and Reasoning in a User-Centric Scheduling Assistant

DTIC Science & Technology

2007-02-01

perform the diarying, either due to excessive busyness (despite the low overhead of the exercise), or because their schedules are managed by their...and existing meetings; (4) locations of meetings; (5) participants in meetings; (6) time or duration changes for existing meetings; and (7...after each change to detect conflicts and display them with suggestions for removing them. The calendaring domains allows specialized partial

The Network for the Detection of Atmospheric Composition Change (NDACC): history, status and perspectives

NASA Astrophysics Data System (ADS)

De Mazière, Martine; Thompson, Anne M.; Kurylo, Michael J.; Wild, Jeannette D.; Bernhard, Germar; Blumenstock, Thomas; Braathen, Geir O.; Hannigan, James W.; Lambert, Jean-Christopher; Leblanc, Thierry; McGee, Thomas J.; Nedoluha, Gerald; Petropavlovskikh, Irina; Seckmeyer, Gunther; Simon, Paul C.; Steinbrecht, Wolfgang; Strahan, Susan E.

2018-04-01

The Network for the Detection of Atmospheric Composition Change (NDACC) is an international global network of more than 90 stations making high-quality measurements of atmospheric composition that began official operations in 1991 after 5 years of planning. Apart from sonde measurements, all measurements in the network are performed by ground-based remote-sensing techniques. Originally named the Network for the Detection of Stratospheric Change (NDSC), the name of the network was changed to NDACC in 2005 to better reflect the expanded scope of its measurements. The primary goal of NDACC is to establish long-term databases for detecting changes and trends in the chemical and physical state of the atmosphere (mesosphere, stratosphere, and troposphere) and to assess the coupling of such changes with climate and air quality. NDACC's origins, station locations, organizational structure, and data archiving are described. NDACC is structured around categories of ground-based observational techniques (sonde, lidar, microwave radiometers, Fourier-transform infrared, UV-visible DOAS (differential optical absorption spectroscopy)-type, and Dobson-Brewer spectrometers, as well as spectral UV radiometers), timely cross-cutting themes (ozone, water vapour, measurement strategies, cross-network data integration), satellite measurement systems, and theory and analyses. Participation in NDACC requires compliance with strict measurement and data protocols to ensure that the network data are of high and consistent quality. To widen its scope, NDACC has established formal collaborative agreements with eight other cooperating networks and Global Atmosphere Watch (GAW). A brief history is provided, major accomplishments of NDACC during its first 25 years of operation are reviewed, and a forward-looking perspective is presented.

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 Network for the Detection of Atmospheric Composition Change (NDACC): History, Status and Perspectives

NASA Technical Reports Server (NTRS)

Simon, Paul C.; De Maziere, Martine; Bernhard, Germar; Blumenstock, Thomas; McGee, Thomas J.; Petropavlovskikh, Irina; Steinbrecht, Wolfgang; Wild, Jeannette D.; Lambert, Jean-Christopher; Seckmeyer, Gunther;

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.

Reliability and minimal detectable change of physical performance measures in individuals with pre-manifest and manifest Huntington disease.

PubMed

Quinn, Lori; Khalil, Hanan; Dawes, Helen; Fritz, Nora E; Kegelmeyer, Deb; Kloos, Anne D; Gillard, Jonathan W; Busse, Monica

2013-07-01

Clinical intervention trials in people with Huntington disease (HD) have been limited by a lack of reliable and appropriate outcome measures. The purpose of this study was to determine the reliability and minimal detectable change (MDC) of various outcome measures that are potentially suitable for evaluating physical functioning in individuals with HD. This was a multicenter, prospective, observational study. Participants with pre-manifest and manifest HD (early, middle, and late stages) were recruited from 8 international sites to complete a battery of physical performance and functional measures at 2 assessments, separated by 1 week. Test-retest reliability (using intraclass correlation coefficients) and MDC values were calculated for all measures. Seventy-five individuals with HD (mean age=52.12 years, SD=11.82) participated in the study. Test-retest reliability was very high (>.90) for participants with manifest HD for the Six-Minute Walk Test (6MWT), 10-Meter Walk Test, Timed "Up & Go" Test (TUG), Berg Balance Scale (BBS), Physical Performance Test (PPT), Barthel Index, Rivermead Mobility Index, and Tinetti Mobility Test (TMT). Many MDC values suggested a relatively high degree of inherent variability, particularly in the middle stage of HD. Minimum detectable change values for participants with manifest HD that were relatively low across disease stages were found for the BBS (5), PPT (5), and TUG (2.98). For individuals with pre-manifest HD (n=11), the 6MWT and Four Square Step Test had high reliability and low MDC values. The sample size for the pre-manifest HD group was small. The BBS, PPT, and TUG appear most appropriate for clinical trials aimed at improving physical functioning in people with manifest HD. Further research in people with pre-manifest HD is necessary.

The Changes of Gene Expression on Human Hair during Long-Spaceflight

NASA Astrophysics Data System (ADS)

Terada, Masahiro; Mukai, Chiaki; Ishioka, Noriaki; Majima, Hideyuki J.; Yamada, Shin; Seki, Masaya; Takahashi, Rika; Higashibata, Akira; Ohshima, Hiroshi; Sudoh, Masamichi; Minamisawa, Susumu

Hair has many advantages as the experimental sample. In a hair follicle, hair matrix cells actively divide and these active changes sensitively reflect physical condition on human body. The hair shaft records the metabolic conditions of mineral elements in our body. From human hairs, we can detect physiological informations about the human health. Therefore, we focused on using hair root analysis to understand the effects of spaceflight on astronauts. In 2009, we started a research program focusing on the analysis of astronauts’ hairs to examine the effects of long-term spaceflight on the gene expression in the human body. We want to get basic information to invent the effectivly diagnostic methods to detect the health situations of astronauts during space flight by analyzing human hair. We extracted RNA form the collected samples. Then, these extracted RNA was amplified. Amplified RNA was processed and hybridized to the Whole Human Genome (4×44K) Oligo Microarray (Agilent Technologies) according to the manufacturer’s protocol. Slide scanning was performed using the Agilent DNA Microarray Scanner. Scanning data were normalized with Agilent’s Feature Extraction software. Data preprocessing and analysis were performed using GeneSpring software 11.0.1. Next, Synthesis of cDNA (1 mg) was carried out using the PrimeScript RT reagent Kit (TaKaRa Bio) following the manufacturer’s instructions. The qRT-PCR experiment was performed with SYBR Premix Ex Taq (TaKaRa Bio) using the 7500 Real-Time PCR system (Applied Biosystems). We detected the changes of some gene expressions during spaceflight from both microarray and qRT-PCR data. These genes seems to be related with the hair proliferation. We believe that these results will lead to the discovery of the important factor effected during space flight on the hair.

Necrosulfonamide Attenuates Spinal Cord Injury via Necroptosis Inhibition.

PubMed

Wang, Yongxiang; Wang, Jingcheng; Wang, Hua; Feng, Xinmin; Tao, Yuping; Yang, Jiandong; Cai, Jun

2018-06-01

Spinal cord injury (SCI) is a serious trauma without efficient treatment currently. Necroptosis can be blocked post injury by special inhibitors. This study is to investigate the effects, mechanism, and potential benefit of necrosulfonamide (NSA) for SCI therapy. Pathologic condition was detected using hematoxylin-eosin staining on injured spinal cord and other major organs. Necroptosis-related factors-RIP1, RIP3, and MLKL-were detected using Western blot. Detections on mitochondrial functions such as adenosine triphosphate generation and activities of superoxide dismutase and caspase-3 were also performed. Finally, ethologic performance was detected using a 21-point open-field locomotion test. Reduced lesions and protected neurons were found in the injured spinal cord after treatment with NSA using hematoxylin-eosin staining for pathologic detection. No obvious toxicity on rat liver, kidney, heart, and spleen was detected. Rather than RIP1 and RIP3, MLKL was significantly inhibited by the NSA using Western blot detection. Adenosine triphosphate generation was obviously decreased post injury but slightly increased after the NSA treatment, especially 24 hours post injury. No significant changes were found on activities of superoxide dismutase and caspase-3 after the treatment of NSA. Ethologic performance was significantly improved using a 21-point, open-field locomotion test. Our research indicates NSA attenuates the spinal cord injury via necroptosis inhibition. It might be a potential and safe chemical benefit for SCI therapy. To our knowledge, this is the first study on the effects of NSA as treatment of traumatic SCI. Copyright © 2018 Elsevier Inc. All rights reserved.

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.

Can SNOMED CT Changes Be Used as a Surrogate Standard for Evaluating the Performance of Its Auditing Methods?

PubMed Central

Guo-Qiang, Zhang; Yan, Huang; Licong, Cui

2017-01-01

We introduce RGT, Retrospective Ground-Truthing, as a surrogate reference standard for evaluating the performance of automated Ontology Quality Assurance (OQA) methods. The key idea of RGT is to use cumulative SNOMED CT changes derived from its regular longitudinal distributions by the official SNOMED CT editorial board as a partial, surrogate reference standard. The contributions of this paper are twofold: (1) to construct an RGT reference set for SNOMED CT relational changes; and (2) to perform a comparative evaluation of the performances of lattice, non-lattice, and randomized relational error detection methods using the standard precision, recall, and geometric measures. An RGT relational-change reference set of 32,241 IS-A changes were constructed from 5 U.S. editions of SNOMED CT from September 2014 to September 2016, with reversals and changes due to deletion or addition of new concepts excluded. 68,849 independent non-lattice fragments, 118,587 independent lattice fragments, and 446,603 relations were extracted from the SNOMED CT March 2014 distribution. Comparative performance analysis of smaller (less than 15) lattice vs. non-lattice fragments was also given to approach the more realistic setting in which such methods may be applied. Among the 32,241 IS-A changes, independent non-lattice fragments covered 52.8% changes with 26.4% precision with a G-score of 0.373. Even though this G-score is significantly lower in comparison to those in information retrieval, it breaks new ground in that such evaluations have never performed before in the highly discovery-oriented setting of OQA. PMID:29854262

Can SNOMED CT Changes Be Used as a Surrogate Standard for Evaluating the Performance of Its Auditing Methods?

PubMed

Guo-Qiang, Zhang; Yan, Huang; Licong, Cui

2017-01-01

We introduce RGT, Retrospective Ground-Truthing, as a surrogate reference standard for evaluating the performance of automated Ontology Quality Assurance (OQA) methods. The key idea of RGT is to use cumulative SNOMED CT changes derived from its regular longitudinal distributions by the official SNOMED CT editorial board as a partial, surrogate reference standard. The contributions of this paper are twofold: (1) to construct an RGT reference set for SNOMED CT relational changes; and (2) to perform a comparative evaluation of the performances of lattice, non-lattice, and randomized relational error detection methods using the standard precision, recall, and geometric measures. An RGT relational-change reference set of 32,241 IS-A changes were constructed from 5 U.S. editions of SNOMED CT from September 2014 to September 2016, with reversals and changes due to deletion or addition of new concepts excluded. 68,849 independent non-lattice fragments, 118,587 independent lattice fragments, and 446,603 relations were extracted from the SNOMED CT March 2014 distribution. Comparative performance analysis of smaller (less than 15) lattice vs. non-lattice fragments was also given to approach the more realistic setting in which such methods may be applied. Among the 32,241 IS-A changes, independent non-lattice fragments covered 52.8% changes with 26.4% precision with a G-score of 0.373. Even though this G-score is significantly lower in comparison to those in information retrieval, it breaks new ground in that such evaluations have never performed before in the highly discovery-oriented setting of OQA.

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.

Effects of human fatigue on speech signals

NASA Astrophysics Data System (ADS)

Stamoulis, Catherine

2004-05-01

Cognitive performance may be significantly affected by fatigue. In the case of critical personnel, such as pilots, monitoring human fatigue is essential to ensure safety and success of a given operation. One of the modalities that may be used for this purpose is speech, which is sensitive to respiratory changes and increased muscle tension of vocal cords, induced by fatigue. Age, gender, vocal tract length, physical and emotional state may significantly alter speech intensity, duration, rhythm, and spectral characteristics. In addition to changes in speech rhythm, fatigue may also affect the quality of speech, such as articulation. In a noisy environment, detecting fatigue-related changes in speech signals, particularly subtle changes at the onset of fatigue, may be difficult. Therefore, in a performance-monitoring system, speech parameters which are significantly affected by fatigue need to be identified and extracted from input signals. For this purpose, a series of experiments was performed under slowly varying cognitive load conditions and at different times of the day. The results of the data analysis are presented here.

Gpm Level 1 Science Requirements: Science and Performance Viewed from the Ground

NASA Technical Reports Server (NTRS)

Petersen, W.; Kirstetter, P.; Wolff, D.; Kidd, C.; Tokay, A.; Chandrasekar, V.; Grecu, M.; Huffman, G.; Jackson, G. S.

2016-01-01

GPM meets Level 1 science requirements for rain estimation based on the strong performance of its radar algorithms. Changes in the V5 GPROF algorithm should correct errors in V4 and will likely resolve GPROF performance issues relative to L1 requirements. L1 FOV Snow detection largely verified but at unknown SWE rate threshold (likely < 0.5 –1 mm/hr/liquid equivalent). Ongoing work to improve SWE rate estimation for both satellite and GV remote sensing.

Make Caffeine Visible: a Fluorescent Caffeine “Traffic Light” Detector

NASA Astrophysics Data System (ADS)

Xu, Wang; Kim, Tae-Hyeong; Zhai, Duanting; Er, Jun Cheng; Zhang, Liyun; Kale, Anup Atul; Agrawalla, Bikram Keshari; Cho, Yoon-Kyoung; Chang, Young-Tae

2013-07-01

Caffeine has attracted abundant attention due to its extensive existence in beverages and medicines. However, to detect it sensitively and conveniently remains a challenge, especially in resource-limited regions. Here we report a novel aqueous phase fluorescent caffeine sensor named Caffeine Orange which exhibits 250-fold fluorescence enhancement upon caffeine activation and high selectivity. Nuclear magnetic resonance spectroscopy and Fourier transform infrared spectroscopy indicate that π-stacking and hydrogen-bonding contribute to their interactions while dynamic light scattering and transmission electron microscopy experiments demonstrate the change of Caffeine Orange ambient environment induces its fluorescence emission. To utilize this probe in real life, we developed a non-toxic caffeine detection kit and tested it for caffeine quantification in various beverages. Naked-eye sensing of various caffeine concentrations was possible based on color changes upon irradiation with a laser pointer. Lastly, we performed the whole system on a microfluidic device to make caffeine detection quick, sensitive and automated.

A non-contact time-domain scanning brain imaging system: first in-vivo results

NASA Astrophysics Data System (ADS)

Mazurenka, M.; Di Sieno, L.; Boso, G.; Contini, D.; Pifferi, A.; Dalla Mora, A.; Tosi, A.; Wabnitz, H.; Macdonald, R.

2013-06-01

We present results of first in-vivo tests of an optical non-contact scanning imaging system, intended to study oxidative metabolism related processes in biological tissue by means of time-resolved near-infrared spectroscopy. Our method is a novel realization of the short source-detector separation approach and based on a fast-gated single-photon avalanche diode to detect late photons only. The scanning system is built in quasi-confocal configuration and utilizes polarizationsensitive detection. It scans an area of 4×4 cm2, recording images with 32×32 pixels, thus creating a high density of source-detector pairs. To test the system we performed a range of in vivo measurements of hemodynamic changes in several types of biological tissues, i.e. skin (Valsalva maneuver), muscle (venous and arterial occlusions) and brain (motor and cognitive tasks). Task-related changes in hemoglobin concentrations were clearly detected in skin and muscle. The brain activation shows weaker, but yet detectable changes. These changes were localized in pixels near the motor cortex area (C3). However, it was found that even very short hair substantially impairs the measurement. Thus the applicability of the scanner is limited to hairless parts of body. The results of our first in-vivo tests prove the feasibility of non-contact scanning imaging as a first step towards development of a prototype for biological tissue imaging for various medical applications.

Change Detection via Selective Guided Contrasting Filters

NASA Astrophysics Data System (ADS)

Vizilter, Y. V.; Rubis, A. Y.; Zheltov, S. Y.

2017-05-01

Change detection scheme based on guided contrasting was previously proposed. Guided contrasting filter takes two images (test and sample) as input and forms the output as filtered version of test image. Such filter preserves the similar details and smooths the non-similar details of test image with respect to sample image. Due to this the difference between test image and its filtered version (difference map) could be a basis for robust change detection. Guided contrasting is performed in two steps: at the first step some smoothing operator (SO) is applied for elimination of test image details; at the second step all matched details are restored with local contrast proportional to the value of some local similarity coefficient (LSC). The guided contrasting filter was proposed based on local average smoothing as SO and local linear correlation as LSC. In this paper we propose and implement new set of selective guided contrasting filters based on different combinations of various SO and thresholded LSC. Linear average and Gaussian smoothing, nonlinear median filtering, morphological opening and closing are considered as SO. Local linear correlation coefficient, morphological correlation coefficient (MCC), mutual information, mean square MCC and geometrical correlation coefficients are applied as LSC. Thresholding of LSC allows operating with non-normalized LSC and enhancing the selective properties of guided contrasting filters: details are either totally recovered or not recovered at all after the smoothing. These different guided contrasting filters are tested as a part of previously proposed change detection pipeline, which contains following stages: guided contrasting filtering on image pyramid, calculation of difference map, binarization, extraction of change proposals and testing change proposals using local MCC. Experiments on real and simulated image bases demonstrate the applicability of all proposed selective guided contrasting filters. All implemented filters provide the robustness relative to weak geometrical discrepancy of compared images. Selective guided contrasting based on morphological opening/closing and thresholded morphological correlation demonstrates the best change detection result.

Scale Changes Provide an Alternative Cue For the Discrimination of Heading, But Not Object Motion

PubMed Central

Calabro, Finnegan J.; Vaina, Lucia Maria

2016-01-01

Background Understanding the dynamics of our surrounding environments is a task usually attributed to the detection of motion based on changes in luminance across space. Yet a number of other cues, both dynamic and static, have been shown to provide useful information about how we are moving and how objects around us move. One such cue, based on changes in spatial frequency, or scale, over time has been shown to be useful in conveying motion in depth even in the absence of a coherent, motion-defined flow field (optic flow). Material/Methods 16 right handed healthy observers (ages 18–28) participated in the behavioral experiments described in this study. Using analytical behavioral methods we investigate the functional specificity of this cue by measuring the ability of observers to perform tasks of heading (direction of self-motion) and 3D trajectory discrimination on the basis of scale changes and optic flow. Results Statistical analyses of performance on the test-experiments in comparison to the control experiments suggests that while scale changes may be involved in the detection of heading, they are not correctly integrated with translational motion and, thus, do not provide a correct discrimination of 3D object trajectories. Conclusions These results have the important implication for the type of visual guided navigation that can be done by an observer blind to optic flow. Scale change is an important alternative cue for self-motion. PMID:27231114

Scale Changes Provide an Alternative Cue For the Discrimination of Heading, But Not Object Motion.

PubMed

Calabro, Finnegan J; Vaina, Lucia Maria

2016-05-27

BACKGROUND Understanding the dynamics of our surrounding environments is a task usually attributed to the detection of motion based on changes in luminance across space. Yet a number of other cues, both dynamic and static, have been shown to provide useful information about how we are moving and how objects around us move. One such cue, based on changes in spatial frequency, or scale, over time has been shown to be useful in conveying motion in depth even in the absence of a coherent, motion-defined flow field (optic flow). MATERIAL AND METHODS 16 right handed healthy observers (ages 18-28) participated in the behavioral experiments described in this study. Using analytical behavioral methods we investigate the functional specificity of this cue by measuring the ability of observers to perform tasks of heading (direction of self-motion) and 3D trajectory discrimination on the basis of scale changes and optic flow. RESULTS Statistical analyses of performance on the test-experiments in comparison to the control experiments suggests that while scale changes may be involved in the detection of heading, they are not correctly integrated with translational motion and, thus, do not provide a correct discrimination of 3D object trajectories. CONCLUSIONS These results have the important implication for the type of visual guided navigation that can be done by an observer blind to optic flow. Scale change is an important alternative cue for self-motion.

An ultrasensitive bio-surrogate for nanoporous filter membrane performance metrology directed towards contamination control in microlithography applications

NASA Astrophysics Data System (ADS)

Ahmad, Farhan; Mish, Barbara; Qiu, Jian; Singh, Amarnauth; Varanasi, Rao; Bedford, Eilidh; Smith, Martin

2016-03-01

Contamination tolerances in semiconductor manufacturing processes have changed dramatically in the past two decades, reaching below 20 nm according to the guidelines of the International Technology Roadmap for Semiconductors. The move to narrower line widths drives the need for innovative filtration technologies that can achieve higher particle/contaminant removal performance resulting in cleaner process fluids. Nanoporous filter membrane metrology tools that have been the workhorse over the past decade are also now reaching limits. For example, nanoparticle (NP) challenge testing is commonly applied for assessing particle retention performance of filter membranes. Factors such as high NP size dispersity, low NP detection sensitivity, and high NP particle-filter affinity impose challenges in characterizing the next generation of nanoporous filter membranes. We report a novel bio-surrogate, 5 nm DNA-dendrimer conjugate for evaluating particle retention performance of nanoporous filter membranes. A technique capable of single molecule detection is employed to detect sparse concentration of conjugate in filter permeate, providing >1000- fold higher detection sensitivity than any existing 5 nm-sized particle enumeration technique. This bio-surrogate also offers narrow size distribution, high stability and chemical tunability. This bio-surrogate can discriminate various sub-15 nm pore-rated nanoporous filter membranes based on their particle retention performance. Due to high bio-surrogate detection sensitivity, a lower challenge concentration of bio-surrogate (as compared to other NPs of this size) can be used for filter testing, providing a better representation of customer applications. This new method should provide better understanding of the next generation filter membranes for removing defect-causing contaminants from lithography processes.

Psychometric Properties of Performance-based Measurements of Functional Capacity: Test-Retest Reliability, Practice Effects, and Potential Sensitivity to Change

PubMed Central

Leifker, Feea R.; Patterson, Thomas L.; Bowie, Christopher R.; Mausbach, Brent T.; Harvey, Philip D.

2010-01-01

Performance-based measures of the ability to perform social and everyday living skills are being more widely used to assess functional capacity in people with serious mental illnesses such as schizophrenia and bipolar disorder. Since they are also being used as outcome measures in pharmacological and cognitive remediation studies aimed at cognitive impairments in schizophrenia, understanding their measurement properties and potential sensitivity to change is important. In this study, the test-retest reliability, practice effects, and reliable change indices of two different performance-based functional capacity measures, the UCSD Performance-based skills assessment (UPSA) and Social skills performance assessment (SSPA) were examined over several different retest intervals in two different samples of people with schizophrenia (n’s=238 and 116) and a healthy comparison sample (n=109). These psychometric properties were compared to those of a neuropsychological assessment battery. Test-retest reliabilities of the long form of the UPSA ranged from r=.63 to r=.80 over follow-up periods up to 36 months in people with schizophrenia, while brief UPSA reliabilities ranged from r=.66 to r=.81. Test-retest reliability of the NP performance scores ranged from r=.77 to r=.79. Test-retest reliabilities of the UPSA were lower in healthy controls, while NP performance was slightly more reliable. SSPA test-retest reliability was lower. Practice effect sizes ranged from .05 to .16 for the UPSA and .07 to .19 for the NP assessment in patients, with HC having more practice effects. Reliable change intervals were consistent across NP and both FC measures, indicating equal potential for detection of change. These performance-based measures of functional capacity appear to have similar potential to be sensitive to change compared to NP performance in people with schizophrenia. PMID:20399613

Bioavailability and biochemical effects of diclofenac sodium 0.1% ophthalmic solution in the domestic chicken (Gallus gallus domesticus).

PubMed

Griggs, Angela N; Yaw, Taylor J; Haynes, Joseph S; Ben-Shlomo, Gil; Tofflemire, Kyle L; Allbaugh, Rachel A

2017-03-01

To determine if topical ophthalmic diclofenac sodium 0.1% solution alters renal parameters in the domestic chicken, and to determine if the drug is detectable in plasma after topical ophthalmic administration. Thirty healthy domestic chickens. Over 7 days, six birds were treated unilaterally with one drop of artificial tear solution (group 1), 12 birds were treated unilaterally (group 2) and 12 bilaterally (group 3) with diclofenac sodium 0.1% ophthalmic solution. Treatments were provided every 12 h in all groups. Pre- and post-treatment plasma samples from all birds were evaluated for changes in albumin, total protein, and uric acid. Post-treatment samples of all birds, collected 15 min post-administration, were analyzed by high-performance liquid chromatography with mass spectrometry for diclofenac sodium detection. A randomly selected renal sample from each group was submitted for histopathologic review. Changes in pre- and post-treatment plasma albumin were significant (P < 0.05) in groups 2 and 3, but not for group 1. Pre- and post-treatment changes in total protein and uric acid were not significant for any group. Diclofenac sodium was not detectable (limit of detection = 0.10 ng/mL) in plasma samples from birds in group 1. Post-treatment concentration of diclofenac in group 3 was statistically greater than group 2 (P = 0.0008). Histopathologic changes did not identify diclofenac-induced acute renal tubular necrosis. Ophthalmic diclofenac sodium 0.1% administered topically every 12 h in one or both eyes for 7 days is detectable in systemic circulation in the domestic chicken, but does not cause overt significant changes in plasma uric acid or total protein. © 2016 American College of Veterinary Ophthalmologists.

Studies of recognition with multitemporal remote sensor data

NASA Technical Reports Server (NTRS)

Malila, W. A.; Hieber, R. H.; Cicone, R. C.

1975-01-01

Characteristics of multitemporal data and their use in recognition processing were investigated. Principal emphasis was on satellite data collected by the LANDSAT multispectral scanner and on temporal changes throughout a growing season. The effects of spatial misregistration on recognition performance with multitemporal data were examined. A capability to compute probabilities of detection and false alarm was developed and used with simulated distributions for misregistered pixels. Wheat detection was found to be degraded and false alarms increased by misregistration effects. Multitemporal signature characteristics and multitemporal recognition processing were studied to gain insights into problems associated with this approach and possible improvements. Recognition performance with one multitemporal data set displayed marked improvements over results from single-time data.

Evaluation of the performance of accelerometer-based gait event detection algorithms in different real-world scenarios using the MAREA gait database.

PubMed

Khandelwal, Siddhartha; Wickström, Nicholas

2017-01-01

Numerous gait event detection (GED) algorithms have been developed using accelerometers as they allow the possibility of long-term gait analysis in everyday life. However, almost all such existing algorithms have been developed and assessed using data collected in controlled indoor experiments with pre-defined paths and walking speeds. On the contrary, human gait is quite dynamic in the real-world, often involving varying gait speeds, changing surfaces and varying surface inclinations. Though portable wearable systems can be used to conduct experiments directly in the real-world, there is a lack of publicly available gait datasets or studies evaluating the performance of existing GED algorithms in various real-world settings. This paper presents a new gait database called MAREA (n=20 healthy subjects) that consists of walking and running in indoor and outdoor environments with accelerometers positioned on waist, wrist and both ankles. The study also evaluates the performance of six state-of-the-art accelerometer-based GED algorithms in different real-world scenarios, using the MAREA gait database. The results reveal that the performance of these algorithms is inconsistent and varies with changing environments and gait speeds. All algorithms demonstrated good performance for the scenario of steady walking in a controlled indoor environment with a combined median F1score of 0.98 for Heel-Strikes and 0.94 for Toe-Offs. However, they exhibited significantly decreased performance when evaluated in other lesser controlled scenarios such as walking and running in an outdoor street, with a combined median F1score of 0.82 for Heel-Strikes and 0.53 for Toe-Offs. Moreover, all GED algorithms displayed better performance for detecting Heel-Strikes as compared to Toe-Offs, when evaluated in different scenarios. Copyright © 2016 Elsevier B.V. All rights reserved.

The Tölz Temporal Topography Study: mapping the visual field across the life span. Part I: the topography of light detection and temporal-information processing.

PubMed

Poggel, Dorothe A; Treutwein, Bernhard; Calmanti, Claudia; Strasburger, Hans

2012-08-01

Temporal performance parameters vary across the visual field. Their topographical distributions relative to each other and relative to basic visual performance measures and their relative change over the life span are unknown. Our goal was to characterize the topography and age-related change of temporal performance. We acquired visual field maps in 95 healthy participants (age: 10-90 years): perimetric thresholds, double-pulse resolution (DPR), reaction times (RTs), and letter contrast thresholds. DPR and perimetric thresholds increased with eccentricity and age; the periphery showed a more pronounced age-related increase than the center. RT increased only slightly and uniformly with eccentricity. It remained almost constant up to the age of 60, a marked change occurring only above 80. Overall, age was a poor predictor of functionality. Performance decline could be explained only in part by the aging of the retina and optic media. In Part II, we therefore examine higher visual and cognitive functions.

Making great leaps forward: Accounting for detectability in herpetological field studies

USGS Publications Warehouse

Mazerolle, Marc J.; Bailey, Larissa L.; Kendall, William L.; Royle, J. Andrew; Converse, Sarah J.; Nichols, James D.

2007-01-01

Detecting individuals of amphibian and reptile species can be a daunting task. Detection can be hindered by various factors such as cryptic behavior, color patterns, or observer experience. These factors complicate the estimation of state variables of interest (e.g., abundance, occupancy, species richness) as well as the vital rates that induce changes in these state variables (e.g., survival probabilities for abundance; extinction probabilities for occupancy). Although ad hoc methods (e.g., counts uncorrected for detection, return rates) typically perform poorly in the face of no detection, they continue to be used extensively in various fields, including herpetology. However, formal approaches that estimate and account for the probability of detection, such as capture-mark-recapture (CMR) methods and distance sampling, are available. In this paper, we present classical approaches and recent advances in methods accounting for detectability that are particularly pertinent for herpetological data sets. Through examples, we illustrate the use of several methods, discuss their performance compared to that of ad hoc methods, and we suggest available software to perform these analyses. The methods we discuss control for imperfect detection and reduce bias in estimates of demographic parameters such as population size, survival, or, at other levels of biological organization, species occurrence. Among these methods, recently developed approaches that no longer require marked or resighted individuals should be particularly of interest to field herpetologists. We hope that our effort will encourage practitioners to implement some of the estimation methods presented herein instead of relying on ad hoc methods that make more limiting assumptions.

Retrofit device to improve vapor compression cooling system performance by dynamic blower speed modulation

DOEpatents

Roth, Robert Paul; Hahn, David C.; Scaringe, Robert P.

2015-12-08

A device and method are provided to improve performance of a vapor compression system using a retrofittable control board to start up the vapor compression system with the evaporator blower initially set to a high speed. A baseline evaporator operating temperature with the evaporator blower operating at the high speed is recorded, and then the device detects if a predetermined acceptable change in evaporator temperature has occurred. The evaporator blower speed is reduced from the initially set high speed as long as there is only a negligible change in the measured evaporator temperature and therefore a negligible difference in the compressor's power consumption so as to obtain a net increase in the Coefficient of Performance.

The effect of increased monitoring load on vigilance performance using a simulated radar display.

DOT National Transportation Integrated Search

1977-07-01

The present study examined the extent to which level of target density influences the ability to sustain attention to a complex monitoring task requiring only a detection response to simple stimulus change. The visual display was designed to approxim...

Reliability of Speech Diadochokinetic Test Measurement

ERIC Educational Resources Information Center

Gadesmann, Miriam; Miller, Nick

2008-01-01

Background: Measures of articulatory diadochokinesis (DDK) are widely used in the assessment of motor speech disorders and they play a role in detecting abnormality, monitoring speech performance changes and classifying syndromes. Although in clinical practice DDK is generally measured perceptually, without support from instrumental methods that…

Magnetic resonance imaging in central nervous system sarcoidosis.

PubMed

Miller, D H; Kendall, B E; Barter, S; Johnson, G; MacManus, D G; Logsdail, S J; Ormerod, I E; McDonald, W I

1988-03-01

We performed brain MRIs on 21 patients with CNS sarcoidosis. Brain CTs were performed in 18 of these. Parenchymal lesions were seen in 17 of 21 with MRI, compared with 9 of 18 with CT. MRI detected a greater number of parenchymal lesions in cases where both CT and MRI were positive, and some lesions appeared more extensive with MRI than with CT. The most common MRI pattern was one of periventricular and multifocal white matter lesions (14 cases). Such a pattern is not specific, and other recognized causes for it were identified in four cases. It is likely, however, that sarcoid tissue causes this pattern in some cases, and confirmation was obtained from cerebral biopsy in one. In six patients, the white matter changes were indistinguishable from those seen in multiple sclerosis. Contrast-enhanced CT in two patients showed diffuse meningeal involvement not seen with MRI. MRI is the investigation of choice in detecting parenchymal changes in the brain of patients with CNS sarcoidosis and may prove useful in monitoring treatment in such cases.

Object memory and change detection: dissociation as a function of visual and conceptual similarity.

PubMed

Yeh, Yei-Yu; Yang, Cheng-Ta

2008-01-01

People often fail to detect a change between two visual scenes, a phenomenon referred to as change blindness. This study investigates how a post-change object's similarity to the pre-change object influences memory of the pre-change object and affects change detection. The results of Experiment 1 showed that similarity lowered detection sensitivity but did not affect the speed of identifying the pre-change object, suggesting that similarity between the pre- and post-change objects does not degrade the pre-change representation. Identification speed for the pre-change object was faster than naming the new object regardless of detection accuracy. Similarity also decreased detection sensitivity in Experiment 2 but improved the recognition of the pre-change object under both correct detection and detection failure. The similarity effect on recognition was greatly reduced when 20% of each pre-change stimulus was masked by random dots in Experiment 3. Together the results suggest that the level of pre-change representation under detection failure is equivalent to the level under correct detection and that the pre-change representation is almost complete. Similarity lowers detection sensitivity but improves explicit access in recognition. Dissociation arises between recognition and change detection as the two judgments rely on the match-to-mismatch signal and mismatch-to-match signal, respectively.

Colorimetric-Based Detection of TNT Explosives Using Functionalized Silica Nanoparticles

PubMed Central

Idros, Noorhayati; Ho, Man Yi; Pivnenko, Mike; Qasim, Malik M.; Xu, Hua; Gu, Zhongze; Chu, Daping

2015-01-01

This proof-of-concept study proposes a novel sensing mechanism for selective and label-free detection of 2,4,6-trinitrotoluene (TNT). It is realized by surface chemistry functionalization of silica nanoparticles (NPs) with 3-aminopropyl-triethoxysilane (APTES). The primary amine anchored to the surface of the silica nanoparticles (SiO2-NH2) acts as a capturing probe for TNT target binding to form Meisenheimer amine–TNT complexes. A colorimetric change of the self-assembled (SAM) NP samples from the initial green of a SiO2-NH2 nanoparticle film towards red was observed after successful attachment of TNT, which was confirmed as a result of the increased separation between the nanoparticles. The shift in the peak wavelength of the reflected light normal to the film surface (λpeak) and the associated change of the peak width were measured, and a merit function taking into account their combined effect was proposed for the detection of TNT concentrations from 10−12 to 10−4 molar. The selectivity of our sensing approach is confirmed by using TNT-bound nanoparticles incubated in AptamerX, with 2,4-dinitrotoluene (DNT) and toluene used as control and baseline, respectively. Our results show the repeatable systematic color change with the TNT concentration and the possibility to develop a robust, easy-to-use, and low-cost TNT detection method for performing a sensitive, reliable, and semi-quantitative detection in a wide detection range. PMID:26046595

The relative proportions of different lipid classes and their fatty acid compositions change with culture age in the cariogenic dental pathogen Streptococcus mutans UA159.

PubMed

Custer, Jenny E; Goddard, Bryan D; Matter, Stephen F; Kaneshiro, Edna S

2014-06-01

The oral cariogenic bacterial pathogen Streptococcus mutans strain UA159 has become an important research organism strain since its genome was sequenced. However, there is a paucity of information on its lipidome using direct analytical biochemical approaches. We here report on comprehensive analyses of the major lipid classes and their fatty acids in cells grown in batch standing cultures. Using 2-D high-performance thin-layer chromatography lipid class composition changes were detected with culture age. More lipid components were detected in the stationary-phase compared to log-phase cells. The major lipids identified included 1,3-bis(sn-3'-phosphatidyl)-sn-glycerol (phosphatidylglycerol), 1,3-diphosphatidylglycerol (cardiolipin), aminoacyl-phosphatidylglycerol, monoglucosyldiacylglycerol, diglucosyldiacylglycerol, diglucosylmonoacylglycerol and, glycerophosphoryldiglucosyldiacylglycerol. Culture age also affected the fatty acid composition of the total polar lipid fraction. Thus, the major lipid classes detected in log-phase and stationary-phase cells were isolated and their fatty acids were analyzed by gas-liquid chromatography to determine the basis for the fatty acid compositional changes in the total polar lipid fraction. The analyses showed that the relative proportions of these acids changed with culture age within individual lipid classes. Hence fatty acid changes in the total polar lipid fraction reflected changes in both lipid class composition and fatty acid compositions within individual lipid classes.

Ventricular fractional shortening in 108 dogs with malignant lymphoma undergoing chemotherapy with a cyclic combination protocol including doxorubicin.

PubMed

Tater, G; Eberle, N; Hungerbuehler, S; Joetzke, A; Nolte, I; Wess, G; Betz, D

2012-01-01

The aim of this study was to evaluate whether changes in the left ventricular fractional shortening (LVFS) can be detected in dogs with malignant lymphoma undergoing a cyclic combination chemotherapy protocol including doxorubicin. Left ventricular fractional shortening as a stand-alone measurement will not show a significant change during the cyclic combination protocol. In this retrospective study, the records of dogs with malignant lymphoma treated between April 2001 and October 2010 were reviewed. Inclusion criteria comprised: a diagnosis of malignant lymphoma, a cyclic combination chemotherapy (including L-asparaginase, vincristine, cyclophosphamide, doxorubicin and prednisolone), and an echocardiographic examination by an experienced examiner before treatment and after each doxorubicin administration. One hundred and eight dogs were included and a total of 446 LVFS measurements had been performed. Patients were divided into four groups according to the number of doxorubicin administrations. Median LVFS did not change significantly during the cyclic combination protocol in all groups. All median LVFS values remained above the lower reference value of 25%. The measurement of LVFS did not show a significant change during the cyclic combination protocol treatment including doxorubicin in this population of dogs. Therefore either this cyclic combination protocol does not cause a systolic dysfunction or LVFS is not sensitive enough to detect early changes. Newer methods that are more sensitive then LVFS might be necessary to detect such changes.

A Behaviour Monitoring System (BMS) for Ambient Assisted Living

PubMed Central

Eisa, Samih

2017-01-01

Unusual changes in the regular daily mobility routine of an elderly person at home can be an indicator or early symptom of developing health problems. Sensor technology can be utilised to complement the traditional healthcare systems to gain a more detailed view of the daily mobility of a person at home when performing everyday tasks. We hypothesise that data collected from low-cost sensors such as presence and occupancy sensors can be analysed to provide insights on the daily mobility habits of the elderly living alone at home and to detect routine changes. We validate this hypothesis by designing a system that automatically learns the daily room-to-room transitions and permanence habits in each room at each time of the day and generates alarm notifications when deviations are detected. We present an algorithm to process the sensors’ data streams and compute sensor-driven features that describe the daily mobility routine of the elderly as part of the developed Behaviour Monitoring System (BMS). We are able to achieve low detection delay with confirmation time that is high enough to convey the detection of a set of common abnormal situations. We illustrate and evaluate BMS with synthetic data, generated by a developed data generator that was designed to mimic different user’s mobility profiles at home, and also with a real-life dataset collected from prior research work. Results indicate BMS detects several mobility changes that can be symptoms of common health problems. The proposed system is a useful approach for learning the mobility habits at the home environment, with the potential to detect behaviour changes that occur due to health problems, and therefore, motivating progress toward behaviour monitoring and elder’s care. PMID:28837105

Slantingly cross loading sample system enables simultaneous performance of separation and mixture to detect molecular interactions on thin-layer chromatography.

PubMed

Shimizu-Yumoto, Hiroko; Hayashi, Nobuyuki; Ichimura, Kazuo; Nakayama, Masayoshi

2012-07-06

Anthocyanins are major flower pigments that can be affected by copigments, colorless compounds that can modify anthocyanin coloration to more intense and bluer. Thin-layer chromatography (TLC) is an available technique to separate and analyze anthocyanins and copigments. To easily and comprehensively detect copigments, we added function of mixture of compounds to TLC; by slantingly cross loading samples on TLC, compounds are symmetrically developed at various angle lines from the upper origin to individual R(f) values and cross each other in an orderly fashion, where mixture is simultaneously performed with separation. Occurrence of copigments can be detected as a coloration change on the developed line of anthocyanin. Pink sweet pea (Lathyrus odoratus L.) petals were analyzed by the cross-TLC and a more intense spot and a paler spot on the anthocyanin line were detected. As each spot overlapped with an ultraviolet absorbance line, each of these ultraviolet absorption compounds was purified and identified as kaempferol 3-rhamnoside and 2-cyanoethyl-isoxazolin-5-one, respectively. Whereas kaempferol 3-rhamnoside is a flavonoid and had a general copigment effect of more intense and bluer coloration change, 2-cyanoethyl-isoxazolin-5-one is a compound whose structure is outside of conventional categories of copigments and had a novel effect to change anthocyanin coloration paler while maintaining color tone. We determined that the search for copigments should be carried out without pre-existing prediction of structures and effects. We have shown that slantingly cross loading samples system on plate-type chromatography is an effective technique for such comprehensive analysis of molecular interaction. Crown Copyright © 2012. Published by Elsevier B.V. All rights reserved.

Iohexol clearance is superior to creatinine-based renal function estimating equations in detecting short-term renal function decline in chronic heart failure

PubMed Central

Cvan Trobec, Katja; Kerec Kos, Mojca; von Haehling, Stephan; Anker, Stefan D.; Macdougall, Iain C.; Ponikowski, Piotr; Lainscak, Mitja

2015-01-01

Aim To compare the performance of iohexol plasma clearance and creatinine-based renal function estimating equations in monitoring longitudinal renal function changes in chronic heart failure (CHF) patients, and to assess the effects of body composition on the equation performance. Methods Iohexol plasma clearance was measured in 43 CHF patients at baseline and after at least 6 months. Simultaneously, renal function was estimated with five creatinine-based equations (four- and six-variable Modification of Diet in Renal Disease, Cockcroft-Gault, Cockcroft-Gault adjusted for lean body mass, Chronic Kidney Disease Epidemiology Collaboration equation) and body composition was assessed using bioimpedance and dual-energy x-ray absorptiometry. Results Over a median follow-up of 7.5 months (range 6-17 months), iohexol clearance significantly declined (52.8 vs 44.4 mL/[min ×1.73 m2], P = 0.001). This decline was significantly higher in patients receiving mineralocorticoid receptor antagonists at baseline (mean decline -22% of baseline value vs -3%, P = 0.037). Mean serum creatinine concentration did not change significantly during follow-up and no creatinine-based renal function estimating equation was able to detect the significant longitudinal decline of renal function determined by iohexol clearance. After accounting for body composition, the accuracy of the equations improved, but not their ability to detect renal function decline. Conclusions Renal function measured with iohexol plasma clearance showed relevant decline in CHF patients, particularly in those treated with mineralocorticoid receptor antagonists. None of the equations for renal function estimation was able to detect these changes. ClinicalTrials.gov registration number NCT01829880 PMID:26718759

Serial 3-dimensional computed tomography and a novel method of volumetric analysis for the evaluation of the osteo-odonto-keratoprosthesis.

PubMed

Sipkova, Zuzana; Lam, Fook Chang; Francis, Ian; Herold, Jim; Liu, Christopher

2013-04-01

To assess the use of serial computed tomography (CT) in the detection of osteo-odonto-lamina resorption in osteo-odonto-keratoprosthesis (OOKP) and to investigate the use of new volumetric software, Advanced Lung Analysis software (3D-ALA; GE Healthcare), for detecting changes in OOKP laminar volume. A retrospective assessment of the radiological databases and hospital records was performed for 22 OOKP patients treated at the National OOKP referral center in Brighton, United Kingdom. Three-dimensional surface reconstructions of the OOKP laminae were performed using stored CT data. For the 2-dimensional linear analysis, the linear dimensions of the reconstructed laminae were measured, compared with original measurements taken at the time of surgery, and then assigned a CT grade based on a predetermined resorption grading scale. The volumetric analysis involved calculating the laminar volumes using 3D-ALA. The effectiveness of 2-dimensional linear analysis, volumetric analysis, and clinical examination in detecting laminar resorption was compared. The mean change in laminar volume between the first and second scans was -6.67% (range, +10.13% to -24.86%). CT grades assigned to patients based on laminar dimension measurements remained the same, despite significant changes in laminar volumes. Clinical examination failed to identify 60% of patients who were found to have resorption on volumetric analysis. Currently, the detection of laminar resorption relies on clinical examination and the measurement of laminar dimensions on the 2- and 3-dimensional radiological images. Laminar volume measurement is a useful new addition to the armamentarium. It provides an objective tool that allows for a precise and reproducible assessment of laminar resorption.

Monitoring radiation use in cardiac fluoroscopy imaging procedures

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

Stevens, Nathaniel T.; Steiner, Stefan H.; Smith, Ian R.

2011-01-15

Purpose: Timely identification of systematic changes in radiation delivery of an imaging system can lead to a reduction in risk for the patients involved. However, existing quality assurance programs involving the routine testing of equipment performance using phantoms are limited in their ability to effectively carry out this task. To address this issue, the authors propose the implementation of an ongoing monitoring process that utilizes procedural data to identify unexpected large or small radiation exposures for individual patients, as well as to detect persistent changes in the radiation output of imaging platforms. Methods: Data used in this study were obtainedmore » from records routinely collected during procedures performed in the cardiac catheterization imaging facility at St. Andrew's War Memorial Hospital, Brisbane, Australia, over the period January 2008-March 2010. A two stage monitoring process employing individual and exponentially weighted moving average (EWMA) control charts was developed and used to identify unexpectedly high or low radiation exposure levels for individual patients, as well as detect persistent changes in the radiation output delivered by the imaging systems. To increase sensitivity of the charts, we account for variation in dose area product (DAP) values due to other measured factors (patient weight, fluoroscopy time, and digital acquisition frame count) using multiple linear regression. Control charts are then constructed using the residual values from this linear regression. The proposed monitoring process was evaluated using simulation to model the performance of the process under known conditions. Results: Retrospective application of this technique to actual clinical data identified a number of cases in which the DAP result could be considered unexpected. Most of these, upon review, were attributed to data entry errors. The charts monitoring the overall system radiation output trends demonstrated changes in equipment performance associated with relocation of the equipment to a new department. When tested under simulated conditions, the EWMA chart was capable of detecting a sustained 15% increase in average radiation output within 60 cases (<1 month of operation), while a 33% increase would be signaled within 20 cases. Conclusions: This technique offers a valuable enhancement to existing quality assurance programs in radiology that rely upon the testing of equipment radiation output at discrete time frames to ensure performance security.« less

SU-E-T-144: Effective Analysis of VMAT QA Generated Trajectory Log Files for Medical Accelerator Predictive Maintenance

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

Able, CM; Baydush, AH; Nguyen, C

Purpose: To determine the effectiveness of SPC analysis for a model predictive maintenance process that uses accelerator generated parameter and performance data contained in trajectory log files. Methods: Each trajectory file is decoded and a total of 131 axes positions are recorded (collimator jaw position, gantry angle, each MLC, etc.). This raw data is processed and either axis positions are extracted at critical points during the delivery or positional change over time is used to determine axis velocity. The focus of our analysis is the accuracy, reproducibility and fidelity of each axis. A reference positional trace of the gantry andmore » each MLC is used as a motion baseline for cross correlation (CC) analysis. A total of 494 parameters (482 MLC related) were analyzed using Individual and Moving Range (I/MR) charts. The chart limits were calculated using a hybrid technique that included the use of the standard 3σ limits and parameter/system specifications. Synthetic errors/changes were introduced to determine the initial effectiveness of I/MR charts in detecting relevant changes in operating parameters. The magnitude of the synthetic errors/changes was based on: TG-142 and published analysis of VMAT delivery accuracy. Results: All errors introduced were detected. Synthetic positional errors of 2mm for collimator jaw and MLC carriage exceeded the chart limits. Gantry speed and each MLC speed are analyzed at two different points in the delivery. Simulated Gantry speed error (0.2 deg/sec) and MLC speed error (0.1 cm/sec) exceeded the speed chart limits. Gantry position error of 0.2 deg was detected by the CC maximum value charts. The MLC position error of 0.1 cm was detected by the CC maximum value location charts for every MLC. Conclusion: SPC I/MR evaluation of trajectory log file parameters may be effective in providing an early warning of performance degradation or component failure for medical accelerator systems.« less

Computerized Adaptive Tests Detect Change Following Orthopaedic Surgery in Youth with Cerebral Palsy.

PubMed

Mulcahey, M J; Slavin, Mary D; Ni, Pengsheng; Vogel, Lawrence C; Kozin, Scott H; Haley, Stephen M; Jette, Alan M

2015-09-16

The Cerebral Palsy Computerized Adaptive Test (CP-CAT) is a parent-reported outcomes instrument for measuring lower and upper-extremity function, activity, and global health across impairment levels and a broad age range of children with cerebral palsy (CP). This study was performed to examine whether the Lower Extremity/Mobility (LE) CP-CAT detects change in mobility following orthopaedic surgery in children with CP. This multicenter, longitudinal study involved administration of the LE CP-CAT, the Pediatric Outcomes Data Collection Instrument (PODCI) Transfer/Mobility and Sports/Physical Functioning domains, and the Timed "Up & Go" test (TUG) before and after elective orthopaedic surgery in a convenience sample of 255 children, four to twenty years of age, who had CP and a Gross Motor Function Classification System (GMFCS) level of I, II, or III. Standardized response means (SRMs) and 95% confidence intervals (CIs) were calculated for all measures at six, twelve, and twenty-four months following surgery. SRM estimates for the LE CP-CAT were significantly greater than the SRM estimates for the PODCI Transfer/Mobility domain at twelve months, the PODCI Sports/Physical Functioning domain at twelve months, and the TUG at twelve and twenty-four months. When the results for the children at GMFCS levels I, II, and III were grouped together, the improvements in function detected by the LE CP-CAT at twelve and twenty-four months were found to be greater than the changes detected by the PODCI Transfer/Mobility and Sports/Physical Functioning scales. The LE CP-CAT outperformed the PODCI scales for GMFCS levels I and III at both of these follow-up intervals; none of the scales performed well for patients with GMFCS level II. The results of this study showed that the LE CP-CAT displayed superior sensitivity to change than the PODCI and TUG scales after musculoskeletal surgery in children with CP. Copyright © 2015 by The Journal of Bone and Joint Surgery, Incorporated.

Bacteriological incidence in pneumonia patients with pulmonary emphysema: a bacterial floral analysis using the 16S ribosomal RNA gene in bronchoalveolar lavage fluid.

PubMed

Naito, Keisuke; Yamasaki, Kei; Yatera, Kazuhiro; Akata, Kentaro; Noguchi, Shingo; Kawanami, Toshinori; Fukuda, Kazumasa; Kido, Takashi; Ishimoto, Hiroshi; Mukae, Hiroshi

2017-01-01

Pulmonary emphysema is an important radiological finding in chronic obstructive pulmonary disease patients, but bacteriological differences in pneumonia patients according to the severity of emphysematous changes have not been reported. Therefore, we evaluated the bacteriological incidence in the bronchoalveolar lavage fluid (BALF) of pneumonia patients using cultivation and a culture-independent molecular method. Japanese patients with community-acquired pneumonia (83) and healthcare-associated pneumonia (94) between April 2010 and February 2014 were evaluated. The BALF obtained from pneumonia lesions was evaluated by both cultivation and a molecular method. In the molecular method, ~600 base pairs of bacterial 16S ribosomal RNA genes in the BALF were amplified by polymerase chain reaction, and clone libraries were constructed. The nucleotide sequences of 96 randomly selected colonies were determined, and a homology search was performed to identify the bacterial species. A qualitative radiological evaluation of pulmonary emphysema based on chest computed tomography (CT) images was performed using the Goddard classification. The severity of pulmonary emphysema based on the Goddard classification was none in 47.4% (84/177), mild in 36.2% (64/177), moderate in 10.2% (18/177), and severe in 6.2% (11/177). Using the culture-independent molecular method, Moraxella catarrhalis was significantly more frequently detected in moderate or severe emphysema patients than in patients with no or mild emphysematous changes. The detection rates of Haemophilus influenzae and Pseudomonas aeruginosa were unrelated to the severity of pulmonary emphysematous changes, and Streptococcus species - except for the S. anginosus group and S. pneumoniae - were detected more frequently using the molecular method we used for the BALF of patients with pneumonia than using culture methods. Our findings suggest that M. catarrhalis is more frequently detected in pneumonia patients with moderate or severe emphysema than in those with no or mild emphysematous changes on chest CT. M. catarrhalis may play a major role in patients with pneumonia complicating severe pulmonary emphysema.

Increased cerebellar gray matter volume in head chefs

PubMed Central

Sarica, Alessia; Martino, Iolanda; Fabbricatore, Carmelo; Tomaiuolo, Francesco; Rocca, Federico; Caracciolo, Manuela; Quattrone, Aldo

2017-01-01

Objective Chefs exert expert motor and cognitive performances on a daily basis. Neuroimaging has clearly shown that that long-term skill learning (i.e., athletes, musicians, chess player or sommeliers) induces plastic changes in the brain thus enabling tasks to be performed faster and more accurately. How a chef's expertise is embodied in a specific neural network has never been investigated. Methods Eleven Italian head chefs with long-term brigade management expertise and 11 demographically-/ psychologically- matched non-experts underwent morphological evaluations. Results Voxel-based analysis performed with SUIT, as well as, automated volumetric measurement assessed with Freesurfer, revealed increased gray matter volume in the cerebellum in chefs compared to non-experts. The most significant changes were detected in the anterior vermis and the posterior cerebellar lobule. The magnitude of the brigade staff and the higher performance in the Tower of London test correlated with these specific gray matter increases, respectively. Conclusions We found that chefs are characterized by an anatomical variability involving the cerebellum. This confirms the role of this region in the development of similar expert brains characterized by learning dexterous skills, such as pianists, rock climbers and basketball players. However, the nature of the cellular events underlying the detected morphological differences remains an open question. PMID:28182712

Detection of Historical and Future Precipitation Variations and Extremes Over the Continental United States

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

Anderson, Bruce T.

2015-12-11

Problem: The overall goal of this proposal is to detect observed seasonal-mean precipitation variations and extreme event occurrences over the United States. Detection, e.g. the process of demonstrating that an observed change in climate is unusual, first requires some means of estimating the range of internal variability absent any external drivers. Ideally, the internal variability would be derived from the observations themselves, however generally the observed variability is a confluence of both internal variability and variability in response to external drivers. Further, numerical climate models—the standard tool for detection studies—have their own estimates of intrinsic variability, which may differ substantiallymore » from that found in the observed system as well as other model systems. These problems are further compounded for weather and climate extremes, which as singular events are particularly ill-suited for detection studies because of their infrequent occurrence, limited spatial range, and underestimation within global and even regional numerical models. Rationale: As a basis for this research we will show how stochastic daily-precipitation models—models in which the simulated interannual-to-multidecadal precipitation variance is purely the result of the random evolution of daily precipitation events within a given time period—can be used to address many of these issues simultaneously. Through the novel application of these well-established models, we can first estimate the changes/trends in various means and extremes that can occur even with fixed daily-precipitation characteristics, e.g. that can occur simply as a result of the stochastic evolution of daily weather events within a given climate. Detection of a change in the observed climate—either naturally or anthropogenically forced—can then be defined as any change relative to this stochastic variability, e.g. as changes/trends in the means and extremes that could only have occurred through a change in the underlying climate. As such, this method is capable of detecting “hot spot” regions—as well as “flare ups” within the hot spot regions—that have experienced interannual to multi-decadal scale variations and trends in seasonal-mean precipitation and extreme events. Further by applying the same methods to numerical climate models we can discern the fidelity of the current-generation climate models in representing detectability within the observed climate system. In this way, we can objectively determine the utility of these model systems for performing detection studies of historical and future climate change.« less

Integrated microfluidic technology for sub-lethal and behavioral marine ecotoxicity biotests

NASA Astrophysics Data System (ADS)

Huang, Yushi; Reyes Aldasoro, Constantino Carlos; Persoone, Guido; Wlodkowic, Donald

2015-06-01

Changes in behavioral traits exhibited by small aquatic invertebrates are increasingly postulated as ethically acceptable and more sensitive endpoints for detection of water-born ecotoxicity than conventional mortality assays. Despite importance of such behavioral biotests, their implementation is profoundly limited by the lack of appropriate biocompatible automation, integrated optoelectronic sensors, and the associated electronics and analysis algorithms. This work outlines development of a proof-of-concept miniaturized Lab-on-a-Chip (LOC) platform for rapid water toxicity tests based on changes in swimming patterns exhibited by Artemia franciscana (Artoxkit M™) nauplii. In contrast to conventionally performed end-point analysis based on counting numbers of dead/immobile specimens we performed a time-resolved video data analysis to dynamically assess impact of a reference toxicant on swimming pattern of A. franciscana. Our system design combined: (i) innovative microfluidic device keeping free swimming Artemia sp. nauplii under continuous microperfusion as a mean of toxin delivery; (ii) mechatronic interface for user-friendly fluidic actuation of the chip; and (iii) miniaturized video acquisition for movement analysis of test specimens. The system was capable of performing fully programmable time-lapse and video-microscopy of multiple samples for rapid ecotoxicity analysis. It enabled development of a user-friendly and inexpensive test protocol to dynamically detect sub-lethal behavioral end-points such as changes in speed of movement or distance traveled by each animal.

Robust failure detection filters. M.S. Thesis

NASA Technical Reports Server (NTRS)

Sanmartin, A. M.

1985-01-01

The robustness of detection filters applied to the detection of actuator failures on a free-free beam is analyzed. This analysis is based on computer simulation tests of the detection filters in the presence of different types of model mismatch, and on frequency response functions of the transfers corresponding to the model mismatch. The robustness of detection filters based on a model of the beam containing a large number of structural modes varied dramatically with the placement of some of the filter poles. The dynamics of these filters were very hard to analyze. The design of detection filters with a number of modes equal to the number of sensors was trivial. They can be configured to detect any number of actuator failure events. The dynamics of these filters were very easy to analyze and their robustness properties were much improved. A change of the output transformation allowed the filter to perform satisfactorily with realistic levels of model mismatch.

Incremental Principal Component Analysis Based Outlier Detection Methods for Spatiotemporal Data Streams

NASA Astrophysics Data System (ADS)

Bhushan, A.; Sharker, M. H.; Karimi, H. A.

2015-07-01

In this paper, we address outliers in spatiotemporal data streams obtained from sensors placed across geographically distributed locations. Outliers may appear in such sensor data due to various reasons such as instrumental error and environmental change. Real-time detection of these outliers is essential to prevent propagation of errors in subsequent analyses and results. Incremental Principal Component Analysis (IPCA) is one possible approach for detecting outliers in such type of spatiotemporal data streams. IPCA has been widely used in many real-time applications such as credit card fraud detection, pattern recognition, and image analysis. However, the suitability of applying IPCA for outlier detection in spatiotemporal data streams is unknown and needs to be investigated. To fill this research gap, this paper contributes by presenting two new IPCA-based outlier detection methods and performing a comparative analysis with the existing IPCA-based outlier detection methods to assess their suitability for spatiotemporal sensor data streams.

Immobilization of gold nanoclusters inside porous electrospun fibers for selective detection of Cu(II): A strategic approach to shielding pristine performance

NASA Astrophysics Data System (ADS)

Senthamizhan, Anitha; Celebioglu, Asli; Balusamy, Brabu; Uyar, Tamer

2015-10-01

Here, a distinct demonstration of highly sensitive and selective detection of copper (Cu2+) in a vastly porous cellulose acetate fibers (pCAF) has been carried out using dithiothreitol capped gold nanocluster (DTT.AuNC) as fluorescent probe. A careful optimization of all potential factors affecting the performance of the probe for effective detection of Cu2+ were studied and the resultant sensor strip exhibiting unique features including high stability, retained parent fluorescence nature and reproducibility. The visual colorimetric detection of Cu2+ in water, presenting the selective sensing performance towards Cu2+ ions over Zn2+, Cd2+ and Hg2+ under UV light in naked eye, contrast to other metal ions that didn’t significantly produce such a change. The comparative sensing performance of DTT.AuNC@pCAF, keeping the nonporous CA fiber (DTT.AuNC@nCAF) as a support matrix has been demonstrated. The resulting weak response of DTT.AuNC@nCAF denotes the lack of ligand protection leading to the poor coordination ability with Cu2+. The determined detection limit (50 ppb) is far lower than the maximum level of Cu2+ in drinking water (1.3 ppm) set by U.S. Environmental Protection Agency (EPA). An interesting find from this study has been the specific oxidation nature between Cu2+ and DTT.AuNC, offering solid evidence for selective sensors.

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

Point pattern match-based change detection in a constellation of previously detected objects

DOEpatents

Paglieroni, David W.

2016-06-07

A method and system is provided that applies attribute- and topology-based change detection to objects that were detected on previous scans of a medium. The attributes capture properties or characteristics of the previously detected objects, such as location, time of detection, detection strength, size, elongation, orientation, etc. The locations define a three-dimensional network topology forming a constellation of previously detected objects. The change detection system stores attributes of the previously detected objects in a constellation database. The change detection system detects changes by comparing the attributes and topological consistency of newly detected objects encountered during a new scan of the medium to previously detected objects in the constellation database. The change detection system may receive the attributes of the newly detected objects as the objects are detected by an object detection system in real time.

Properties of a color-changeable chewing gum used to evaluate masticatory performance.

PubMed

Hama, Yohei; Kanazawa, Manabu; Minakuchi, Shunsuke; Uchida, Tatsuro; Sasaki, Yoshiyuki

2014-04-01

To clarify the basic properties of a color-changeable chewing gum to determine its applicability to evaluations of masticatory performance under different types of dental status. Ten participants with natural dentition aged 26-30 years chewed gum that changes color during several chewing strokes over five repetitions. Changes in color were assessed using a colorimeter, and then L*, a*, and b* values in the CIELAB color system were quantified. Relationships between chewing progression and color changes were assessed using regression analysis and the reliability of color changes was assessed using intraclass correlation coefficients. We then measured 42 dentate participants (age, 22-31 years) and 47 complete denture wearers (age, 44-90 years) to determine the detectability of masticatory performance under two types of dental status. Regression between the number of chewing strokes and the difference between two colors was non-linear. The intraclass correlation coefficients were highest between 60 and 160 chewing strokes. Dentate and edentulous groups significantly differed (Wilcoxon rank sum test) and values were widely distributed within each group. The color of the chewing gum changed over a wide range, which was sufficient to evaluate the masticatory performance of individuals with natural dentition and those with complete dentures. Changes in the color values of the gum reliably reflected masticatory performance. These findings indicate that the color-changeable chewing gum will be useful for evaluating masticatory performance under any dental status. Copyright © 2014 Japan Prosthodontic Society. Published by Elsevier Ltd. All rights reserved.

Minimal detectable change of the Personal and Social Performance scale in individuals with schizophrenia.

PubMed

Lee, Shu-Chun; Tang, Shih-Fen; Lu, Wen-Shian; Huang, Sheau-Ling; Deng, Nai-Yu; Lue, Wen-Chyn; Hsieh, Ching-Lin

2016-12-30

The minimal detectable change (MDC) of the Personal and Social Performance scale (PSP) has not yet been investigated, limiting its utility in data interpretation. The purpose of this study was to determine the MDCs of the PSP administered by the same rater or different raters in individuals with schizophrenia. Participants with schizophrenia were recruited from two psychiatric community rehabilitation centers to complete the PSP assessments twice, 2 weeks apart, by the same rater or 2 different raters. MDC values were calculated from the coefficients of intra- and inter-rater reliability (i.e., intraclass correlation coefficients). Forty patients (mean age 36.9 years, SD 9.7) from one center participated in the intra-rater reliability study. Another 40 patients (mean age 44.3 years, SD 11.1) from the other center participated in the inter-rater study. The MDCs (MDC%) of the PSP were 10.7 (17.1%) for the same rater and 16.2 (24.1%) for different raters. The MDCs of the PSP appeared appropriate for clinical trials aiming to determine whether a real change in social functioning has occurred in people with schizophrenia. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Detection of Matrix Crack Density of CFRP using an Electrical Potential Change Method with Multiple Probes

NASA Astrophysics Data System (ADS)

Todoroki, Akira; Omagari, Kazuomi

Carbon Fiber Reinforced Plastic (CFRP) laminates are adopted for fuel tank structures of next generation space rockets or automobiles. Matrix cracks may cause fuel leak or trigger fatigue damage. A monitoring system of the matrix crack density is required. The authors have developed an electrical resistance change method for the monitoring of delamination cracks in CFRP laminates. Reinforcement fibers are used as a self-sensing system. In the present study, the electric potential method is adopted for matrix crack density monitoring. Finite element analysis (FEA) was performed to investigate the possibility of monitoring matrix crack density using multiple electrodes mounted on a single surface of a specimen. The FEA reveals the matrix crack density increases electrical resistance for a target segment between electrodes. Experimental confirmation was also performed using cross-ply laminates. Eight electrodes were mounted on a single surface of a specimen using silver paste after polishing of the specimen surface with sandpaper. The two outermost electrodes applied electrical current, and the inner electrodes measured electric voltage changes. The slope of electrical resistance during reloading is revealed to be an appropriate index for the detection of matrix crack density.

Modic Type 1 Changes: Detection Performance of Fat-Suppressed Fluid-Sensitive MRI Sequences.

PubMed

Finkenstaedt, Tim; Del Grande, Filippo; Bolog, Nicolae; Ulrich, Nils; Tok, Sina; Kolokythas, Orpheus; Steurer, Johann; Andreisek, Gustav; Winklhofer, Sebastian

2018-02-01

 To assess the performance of fat-suppressed fluid-sensitive MRI sequences compared to T1-weighted (T1w) / T2w sequences for the detection of Modic 1 end-plate changes on lumbar spine MRI.  Sagittal T1w, T2w, and fat-suppressed fluid-sensitive MRI images of 100 consecutive patients (consequently 500 vertebral segments; 52 female, mean age 74 ± 7.4 years; 48 male, mean age 71 ± 6.3 years) were retrospectively evaluated. We recorded the presence (yes/no) and extension (i. e., Likert-scale of height, volume, and end-plate extension) of Modic I changes in T1w/T2w sequences and compared the results to fat-suppressed fluid-sensitive sequences (McNemar/Wilcoxon-signed-rank test).  Fat-suppressed fluid-sensitive sequences revealed significantly more Modic I changes compared to T1w/T2w sequences (156 vs. 93 segments, respectively; p < 0.001). The extension of Modic I changes in fat-suppressed fluid-sensitive sequences was significantly larger compared to T1w/T2w sequences (height: 2.53 ± 0.82 vs. 2.27 ± 0.79, volume: 2.35 ± 0.76 vs. 2.1 ± 0.65, end-plate: 2.46 ± 0.76 vs. 2.19 ± 0.81), (p < 0.05). Modic I changes that were only visible in fat-suppressed fluid-sensitive sequences but not in T1w/T2w sequences were significantly smaller compared to Modic I changes that were also visible in T1w/T2w sequences (p < 0.05).  In conclusion, fat-suppressed fluid-sensitive MRI sequences revealed significantly more Modic I end-plate changes and demonstrated a greater extent compared to standard T1w/T2w imaging.   · When the Modic classification was defined in 1988, T2w sequences were heavily T2-weighted and thus virtually fat-suppressed.. · Nowadays, the bright fat signal in T2w images masks edema-like changes.. · The conventional definition of Modic I changes is not fully applicable anymore.. · Fat-suppressed fluid-sensitive MRI sequences revealed more/greater extent of Modic I changes.. · Finkenstaedt T, Del Grande F, Bolog N et al. Modic Type 1 Changes: Detection Performance of Fat-Suppressed Fluid-Sensitive MRI Sequences. Fortschr Röntgenstr 2018; 190: 152 - 160. © Georg Thieme Verlag KG Stuttgart · New York.

Preoperative evaluation of patients with squamous cell carcinoma of the oral cavity: fluorine-18 fluorodeoxyglucose positron emission tomography/computed tomography and ultrasonography versus histopathology.

PubMed

Sugawara, Chieko; Takahashi, Akira; Kubo, Michiko; Otsuka, Hideki; Ishimaru, Naozumi; Miyamoto, Youji; Honda, Eiichi

2012-10-01

The purpose of this retrospective study was to compare fluorine-18 fluorodeoxyglucose positron emission tomography/computed tomography (PET/CT) and ultrasonography (US) in the staging of patients with squamous cell carcinoma of the oral cavity. We compared preoperative evaluations regarding lymph nodes using PET/CT, US, and both methods. The cutoff for the maximum standardized uptake value (SUV(max)) in PET/CT was set at 2.7 by a receiver operating characteristic analysis that was based on the histopathological diagnosis. US was used to examine internal structural changes on B-mode and hilar vascularity on power Doppler. The performance of PET/CT and US in combination was better than that of each modality separately. However, there were histopathological changes that could not be detected on PET/CT or US. PET/CT could not detect nodes with necrotic or cystic changes. US could not detect lymph nodes that did not have abnormal structures. PET/CT and US are complementary tools to evaluate preoperative patients. Copyright © 2012 Elsevier Inc. All rights reserved.

Gray matter volume is associated with rate of subsequent skill learning after a long term training intervention

PubMed Central

Sampaio-Baptista, Cassandra; Scholz, Jan; Jenkinson, Mark; Thomas, Adam G.; Filippini, Nicola; Smit, Gabrielle; Douaud, Gwenaëlle; Johansen-Berg, Heidi

2014-01-01

The ability to predict learning performance from brain imaging data has implications for selecting individuals for training or rehabilitation interventions. Here, we used structural MRI to test whether baseline variations in gray matter (GM) volume correlated with subsequent performance after a long-term training of a complex whole-body task. 44 naïve participants were scanned before undertaking daily juggling practice for 6 weeks, following either a high intensity or a low intensity training regime. To assess performance across the training period participants' practice sessions were filmed. Greater GM volume in medial occipito-parietal areas at baseline correlated with steeper learning slopes. We also tested whether practice time or performance outcomes modulated the degree of structural brain change detected between the baseline scan and additional scans performed immediately after training and following a further 4 weeks without training. Participants with better performance had higher increases in GM volume during the period following training (i.e., between scans 2 and 3) in dorsal parietal cortex and M1. When contrasting brain changes between the practice intensity groups, we did not find any straightforward effects of practice time though practice modulated the relationship between performance and GM volume change in dorsolateral prefrontal cortex. These results suggest that practice time and performance modulate the degree of structural brain change evoked by long-term training regimes. PMID:24680712

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 the detection of abrupt changes (such as failures) in stochastic dynamical systems were surveyed. The class of linear systems were emphasized, 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.

Curcumin based chemosensor for selective detection of fluoride and cyanide anions in aqueous media.

PubMed

Ponnuvel, Kandasamy; Santhiya, Kuppusamy; Padmini, Vediappen

2016-11-30

The conjugate N,N-dimethyl curcumin analogue fluorophore dye 1 has been synthesized and its performance as a sensor was demonstrated. As a fluoride and cyanide sensor it enabled visual detection, and showed changes in UV-vis and fluorescence spectra in the presence of fluoride and cyanide ions in aqueous medium. The Job's plot indicated that the formation of a complex between dye-1 fluoride ions has a 1 : 1 stoichiometric ratio.

Damage detection methodology under variable load conditions based on strain field pattern recognition using FBGs, nonlinear principal component analysis, and clustering techniques

NASA Astrophysics Data System (ADS)

Sierra-Pérez, Julián; Torres-Arredondo, M.-A.; Alvarez-Montoya, Joham

2018-01-01

Structural health monitoring consists of using sensors integrated within structures together with algorithms to perform load monitoring, damage detection, damage location, damage size and severity, and prognosis. One possibility is to use strain sensors to infer structural integrity by comparing patterns in the strain field between the pristine and damaged conditions. In previous works, the authors have demonstrated that it is possible to detect small defects based on strain field pattern recognition by using robust machine learning techniques. They have focused on methodologies based on principal component analysis (PCA) and on the development of several unfolding and standardization techniques, which allow dealing with multiple load conditions. However, before a real implementation of this approach in engineering structures, changes in the strain field due to conditions different from damage occurrence need to be isolated. Since load conditions may vary in most engineering structures and promote significant changes in the strain field, it is necessary to implement novel techniques for uncoupling such changes from those produced by damage occurrence. A damage detection methodology based on optimal baseline selection (OBS) by means of clustering techniques is presented. The methodology includes the use of hierarchical nonlinear PCA as a nonlinear modeling technique in conjunction with Q and nonlinear-T 2 damage indices. The methodology is experimentally validated using strain measurements obtained by 32 fiber Bragg grating sensors bonded to an aluminum beam under dynamic bending loads and simultaneously submitted to variations in its pitch angle. The results demonstrated the capability of the methodology for clustering data according to 13 different load conditions (pitch angles), performing the OBS and detecting six different damages induced in a cumulative way. The proposed methodology showed a true positive rate of 100% and a false positive rate of 1.28% for a 99% of confidence.

The effects of slice thickness and radiation dose level variations on computer-aided diagnosis (CAD) nodule detection performance in pediatric chest CT scans

NASA Astrophysics Data System (ADS)

Emaminejad, Nastaran; Lo, Pechin; Ghahremani, Shahnaz; Kim, Grace H.; Brown, Matthew S.; McNitt-Gray, Michael F.

2017-03-01

For pediatric oncology patients, CT scans are performed to assess treatment response and disease progression. CAD may be used to detect lung nodules which would reflect metastatic disease. The purpose of this study was to investigate the effects of reducing radiation dose and varying slice thickness on CAD performance in the detection of solid lung nodules in pediatric patients. The dataset consisted of CT scans of 58 pediatric chest cases, from which 7 cases had lung nodules detected by radiologist, and a total of 28 nodules were marked. For each case, the original raw data (sinogram data) was collected and a noise addition model was used to simulate reduced-dose scans of 50%, 25% and 10% of the original dose. In addition, the original and reduced-dose raw data were reconstructed at slice thicknesses of 1.5 and 3 mm using a medium sharp (B45) kernel; the result was eight datasets (4 dose levels x 2 thicknesses) for each case An in-house CAD tool was applied on all reconstructed scans, and results were compared with the radiologist's markings. Patient level mean sensitivities at 3mm thickness were 24%, 26%, 25%, 27%, and at 1.5 mm thickness were 23%, 29%, 35%, 36% for 10%, 25%, 50%, and 100% dose level, respectively. Mean FP numbers were 1.5, 0.9, 0.8, 0.7 at 3 mm and 11.4, 3.5, 2.8, 2.8 at 1.5 mm thickness for 10%, 25%, 50%, and 100% dose level respectively. CAD sensitivity did not change with dose level for 3mm thickness, but did change with dose for 1.5 mm. False Positives increased at low dose levels where noise values were high.

Neural correlates of individual performance differences in resolving perceptual conflict.

PubMed

Labrenz, Franziska; Themann, Maria; Wascher, Edmund; Beste, Christian; Pfleiderer, Bettina

2012-01-01

Attentional mechanisms are a crucial prerequisite to organize behavior. Most situations may be characterized by a 'competition' between salient, but irrelevant stimuli and less salient, relevant stimuli. In such situations top-down and bottom-up mechanisms interact with each other. In the present fMRI study, we examined how interindividual differences in resolving situations of perceptual conflict are reflected in brain networks mediating attentional selection. Doing so, we employed a change detection task in which subjects had to detect luminance changes in the presence and absence of competing distractors. The results show that good performers presented increased activation in the orbitofrontal cortex (BA 11), anterior cingulate (BA 25), inferior parietal lobule (BA 40) and visual areas V2 and V3 but decreased activation in BA 39. This suggests that areas mediating top-down attentional control are stronger activated in this group. Increased activity in visual areas reflects distinct neuronal enhancement relating to selective attentional mechanisms in order to solve the perceptual conflict. Opposed to good performers, brain areas activated by poor performers comprised the left inferior parietal lobule (BA 39) and fronto-parietal and visual regions were continuously deactivated, suggesting that poor performers perceive stronger conflict than good performers. Moreover, the suppression of neural activation in visual areas might indicate a strategy of poor performers to inhibit the processing of the irrelevant non-target feature. These results indicate that high sensitivity in perceptual areas and increased attentional control led to less conflict in stimulus processing and consequently to higher performance in competitive attentional selection.

Airborne and Ground-Based Measurements Using a High-Performance Raman Lidar. Part 2; Ground Based

NASA Technical Reports Server (NTRS)

Whiteman, David N.; Cadirola, Martin; Venable, Demetrius; Connell, Rasheen; Rush, Kurt; Leblanc, Thierry; McDermid, Stuart

2009-01-01

The same RASL hardware as described in part I was installed in a ground-based mobile trailer and used in a water vapor lidar intercomparison campaign, hosted at Table Mountain, CA, under the auspices of the Network for the Detection of Atmospheric Composition Change (NDACC). The converted RASL hardware demonstrated high sensitivity to lower stratospheric water vapor indicating that profiling water vapor at those altitudes with sufficient accuracy to monitor climate change is possible. The measurements from Table Mountain also were used to explain the reason, and correct , for sub-optimal airborne aerosol extinction performance during the flight campaign.

Dynamic voltage and frequency scaling for on-demand performance and availability of biomedical embedded systems.

PubMed

Raskovic, Dejan; Giessel, David

2009-11-01

The goal of the study presented in this paper is to develop an embedded biomedical system capable of delivering maximum performance on demand, while maintaining the optimal energy efficiency whenever possible. Several hardware and software solutions are presented allowing the system to intelligently change the power supply voltage and frequency in runtime. The resulting system allows use of more energy-efficient components, operates most of the time in its most battery-efficient mode, and provides means to quickly change the operation mode while maintaining reliable performance. While all of these techniques extend battery life, the main benefit is on-demand availability of computational performance using a system that is not excessive. Biomedical applications, perhaps more than any other application, require battery operation, favor infrequent battery replacements, and can benefit from increased performance under certain conditions (e.g., when anomaly is detected) that makes them ideal candidates for this approach. In addition, if the system is a part of a body area network, it needs to be light, inexpensive, and adaptable enough to satisfy changing requirements of the other nodes in the network.

Modified Whittaker plots as an assessment and monitoring tool for vegetation in a lowland tropical rainforest.

PubMed

Campbell, Patrick; Comiskey, James; Alonso, Alfonso; Dallmeier, Francisco; Nuñez, Percy; Beltran, Hamilton; Baldeon, Severo; Nauray, William; de la Colina, Rafael; Acurio, Lucero; Udvardy, Shana

2002-05-01

Resource exploitation in lowland tropical forests is increasing and causing loss of biodiversity. Effective evaluation and management of the impacts of development on tropical forests requires appropriate assessment and monitoring tools. We propose the use of 0.1-ha multi-scale, modified Whittaker plots (MWPs) to assess and monitor vegetation in lowland tropical rainforests. We established MWPs at 4 sites to: (1) describe and compare composition and structure of the sites using MWPs, (2) compare these results to those of 1-ha permanent vegetation plots (BDPs), and (3) evaluate the ability of MWPs to detect changes in populations (statistical power). We recorded more than 400 species at each site. Species composition among the sites was distinctive, while mean abundance and basal area was similar. Comparisons between MWPs and BDPs show that they record similar species composition and abundance and that both perform equally well at detecting rare species. However, MWPs tend to record more species, and power analysis studies show that MWPs were more effective at detecting changes in the mean number of species of trees > or = 10 cm in diameter at breast height (dbh) and in herbaceous plants. Ten MWPs were sufficient to detect a change of 11% in the mean number of herb species, and they were able to detect a 14% change in the mean number of species of trees > or =10 cm dbh. The value of MWPs for assessment and monitoring is discussed, along with recommendations for improving the sampling design to increase power.

Interrupted Visual Searches Reveal Volatile Search Memory

ERIC Educational Resources Information Center

Shen, Y. Jeremy; Jiang, Yuhong V.

2006-01-01

This study investigated memory from interrupted visual searches. Participants conducted a change detection search task on polygons overlaid on scenes. Search was interrupted by various disruptions, including unfilled delay, passive viewing of other scenes, and additional search on new displays. Results showed that performance was unaffected by…

Icon Duration and Development.

ERIC Educational Resources Information Center

Gummerman, Kent; And Others

In this study, developmental changes in duration of the icon (visual sensory store) were investigated with three converging tachistoscopic tasks. (1) Stimulus interuption detection (SID), a variation of the two-flash threshold method, was performed by 29 first- and 32 fifth-graders, and 32 undergraduates. Icon duration was estimated by stimulus…

A comparison of the vigilance performance of men and women using a simulated radar task.

DOT National Transportation Integrated Search

1978-03-01

The present study examined the question of possible sex differences in the ability to sustain attention to a complex monitoring task requiring only a detection response to critical stimulus changes. The visual display was designed to approximate a fu...

Dynamic modulation of the perceptual load on microsaccades during a selective spatial attention task.

PubMed

Xue, Linyan; Huang, Dan; Wang, Tong; Hu, Qiyi; Chai, Xinyu; Li, Liming; Chen, Yao

2017-11-28

Selective spatial attention enhances task performance at restricted regions within the visual field. The magnitude of this effect depends on the level of attentional load, which determines the efficiency of distractor rejection. Mechanisms of attentional load include perceptual selection and/or cognitive control involving working memory. Recent studies have provided evidence that microsaccades are influenced by spatial attention. Therefore, microsaccade activities may be exploited to help understand the dynamic control of selective attention under different load levels. However, previous reports in humans on the effect of attentional load on microsaccades are inconsistent, and it is not clear to what extent these results and the dynamic changes of microsaccade activities are similar in monkeys. We trained monkeys to perform a color detection task in which the perceptual load was manipulated by task difficulty with limited involvement of working memory. Our results indicate that during the task with high perceptual load, the rate and amplitude of microsaccades immediately before the target color change were significantly suppressed. We also found that the occurrence of microsaccades before the monkeys' detection response deteriorated their performance, especially in the hard task. We propose that the activity of microsaccades might be an efficacious indicator of the perceptual load.

Aberrant functional connectivity in Papez circuit correlates with memory performance in cognitively intact middle-aged APOE4 carriers.

PubMed

Li, Wenjun; Antuono, Piero G; Xie, Chunming; Chen, Gang; Jones, Jennifer L; Ward, B Douglas; Singh, Suraj P; Franczak, Malgorzata B; Goveas, Joseph S; Li, Shi-Jiang

2014-08-01

The main objective of this study is to detect the early changes in resting-state Papez circuit functional connectivity using the hippocampus as the seed, and to determine the associations between altered functional connectivity (FC) and the episodic memory performance in cognitively intact middle-aged apolipoprotein E4 (APOE4) carriers who are at risk of Alzheimer's disease (AD). Forty-six cognitively intact, middle-aged participants, including 20 APOE4 carriers and 26 age-, sex-, and education-matched noncarriers were studied. The resting-state FC of the hippocampus (HFC) was compared between APOE4 carriers and noncarriers. APOE4 carriers showed significantly decreased FC in brain areas that involve learning and memory functions, including the frontal, cingulate, thalamus and basal ganglia regions. Multiple linear regression analysis showed significant correlations between HFC and the episodic memory performance. Conjunction analysis between neural correlates of memory and altered HFC showed the overlapping regions, especially the subcortical regions such as thalamus, caudate nucleus, and cingulate cortices involved in the Papez circuit. Thus, changes in connectivity in the Papez circuit may be used as an early risk detection for AD. Copyright © 2014. Published by Elsevier Ltd.

Evaluation of a PCR assay on overgrown environmental samples cultured for Mycobacterium avium subsp. paratuberculosis.

PubMed

Arango-Sabogal, Juan C; Labrecque, Olivia; Paré, Julie; Fairbrother, Julie-Hélène; Roy, Jean-Philippe; Wellemans, Vincent; Fecteau, Gilles

2016-11-01

Culture of Mycobacterium avium subsp. paratuberculosis (MAP) is the definitive antemortem test method for paratuberculosis. Microbial overgrowth is a challenge for MAP culture, as it complicates, delays, and increases the cost of the process. Additionally, herd status determination is impeded when noninterpretable (NI) results are obtained. The performance of PCR is comparable to fecal culture, thus it may be a complementary detection tool to classify NI samples. Our study aimed to determine if MAP DNA can be identified by PCR performed on NI environmental samples and to evaluate the performance of PCR before and after the culture of these samples in liquid media. A total of 154 environmental samples (62 NI, 62 negative, and 30 positive) were analyzed by PCR before being incubated in an automated system. Growth was confirmed by acid-fast bacilli stain and then the same PCR method was again applied on incubated samples, regardless of culture and stain results. Change in MAP DNA after incubation was assessed by converting the PCR quantification cycle (Cq) values into fold change using the 2 -ΔCq method (ΔCq = Cq after culture - Cq before culture). A total of 1.6% (standard error [SE] = 1.6) of the NI environmental samples had detectable MAP DNA. The PCR had a significantly better performance when applied after culture than before culture (p = 0.004). After culture, a 66-fold change (SE = 17.1) in MAP DNA was observed on average. Performing a PCR on NI samples improves MAP culturing. The PCR method used in our study is a reliable and consistent method to classify NI environmental samples. © 2016 The Author(s).

Detecting and Quantifying Mind Wandering during Simulated Driving.

PubMed

Baldwin, Carryl L; Roberts, Daniel M; Barragan, Daniela; Lee, John D; Lerner, Neil; Higgins, James S

2017-01-01

Mind wandering is a pervasive threat to transportation safety, potentially accounting for a substantial number of crashes and fatalities. In the current study, mind wandering was induced through completion of the same task for 5 days, consisting of a 20-min monotonous freeway-driving scenario, a cognitive depletion task, and a repetition of the 20-min driving scenario driven in the reverse direction. Participants were periodically probed with auditory tones to self-report whether they were mind wandering or focused on the driving task. Self-reported mind wandering frequency was high, and did not statistically change over days of participation. For measures of driving performance, participant labeled periods of mind wandering were associated with reduced speed and reduced lane variability, in comparison to periods of on task performance. For measures of electrophysiology, periods of mind wandering were associated with increased power in the alpha band of the electroencephalogram (EEG), as well as a reduction in the magnitude of the P3a component of the event related potential (ERP) in response to the auditory probe. Results support that mind wandering has an impact on driving performance and the associated change in driver's attentional state is detectable in underlying brain physiology. Further, results suggest that detecting the internal cognitive state of humans is possible in a continuous task such as automobile driving. Identifying periods of likely mind wandering could serve as a useful research tool for assessment of driver attention, and could potentially lead to future in-vehicle safety countermeasures.