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

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Nishiyama, Megumi; Kawaguchi, Jun

2014-11-01

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

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

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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.

The electrophysiological correlate of saliency: evidence from a figure-detection task.

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Straube, Sirko; Fahle, Manfred

2010-01-11

Although figure-ground segregation in a natural environment usually relies on multiple cues, we experience a coherent figure without usually noticing the individual single cues. It is still unclear how various cues interact to achieve this unified percept and whether this interaction depends on task demands. Studies investigating the effect of cue combination on the human EEG are still lacking. In the present study, we combined psychophysics, ERP and time-frequency analysis to investigate the interaction of orientation and spatial frequency as visual cues in a figure detection task. The figure was embedded in a matrix of Gabor elements, and we systematically varied figure saliency by changing the underlying cue configuration. We found a strong correlation between the posterior P2 amplitude and the perceived saliency of the figure: the P2 amplitude decreased with increasing saliency. Analogously, the power of the theta-band decreased for more salient figures. At longer latencies, the posterior P3 component was modulated in amplitude and latency, possibly reflecting increased decision confidence at higher saliencies. In conclusion, when the cue composition (e.g. one or two cues) or cue strength is changed in a figure detection task, first differences in the electrophysiological response reflect the perceived saliency and not directly the underlying cue configuration.

Changes in regional cerebral blood flow during auditory cognitive tasks

International Nuclear Information System (INIS)

Ohyama, Masashi; Kitamura, Shin; Terashi, Akiro; Senda, Michio.

1993-01-01

In order to investigate the relation between auditory cognitive function and regional brain activation, we measured the changes in the regional cerebral blood flow (CBF) using positron emission tomography (PET) during the 'odd-ball' paradigm in ten normal healthy volunteers. The subjects underwent 3 tasks, twice for each, while the evoked potential was recorded. In these tasks, the auditory stimulus was a series of pure tones delivered every 1.5 sec binaurally at 75 dB from the earphones. Task A: the stimulus was a series of tones with 1000 Hz only, and the subject was instructed to only hear. Task B: the stimulus was a series of tones with 1000 Hz only, and the subject was instructed to push the button on detecting a tone. Task C: the stimulus was a series of pure tones delivered every 1.5 sec binaurally at 75 dB with a frequency of 1000 Hz (non-target) in 80% and 2000 Hz (target) in 20% at random, and the subject was instructed to push the button on detecting a target tone. The event related potential (P300) was observed in task C (Pz: 334.3±19.6 msec). At each task, the CBF was measured using PET with i.v. injection of 1.5 GBq of O-15 water. The changes in CBF associated with auditory cognition was evaluated by the difference between the CBF images in task C and B. Localized increase was observed in the anterior cingulate cortex (in all subjects), the bilateral associate auditory cortex, the prefrontal cortex and the parietal cortex. The latter three areas had a large individual variation in the location of foci. These results suggested the role of those cortical areas in auditory cognition. The anterior cingulate was most activated (15.0±2.24% of global CBF). This region was not activated in the condition of task B minus task A. The anterior cingulate is a part of Papez's circuit that is related to memory and other higher cortical function. These results suggested that this area may play an important role in cognition as well as in attention. (author)

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

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Wenfeng Chen

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

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

Science.gov (United States)

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

2012-01-01

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

Attentional capture by irrelevant transients leads to perceptual errors in a competitive change detection task

Directory of Open Access Journals (Sweden)

Daniel eSchneider

2012-05-01

Full Text Available Theories on visual change detection imply that attention is a necessary but not sufficient prerequisite for aware perception. Misguidance of attention due to salient irrelevant distractors can therefore lead to severe deficits in change detection. The present study investigates the mechanisms behind such perceptual errors and their relation to error processing on higher cognitive levels. Participants had to detect a luminance change that occasionally occurred simultaneously with an irrelevant orientation change in the opposite hemi-field (conflict condition. By analyzing event-related potentials in the EEG separately in those error prone conflict trials for correct and erroneous change detection, we demonstrate that only correct change detection was associated with the allocation of attention to the relevant luminance change. Erroneous change detection was associated with an initial capture of attention towards the irrelevant orientation change in the N1 time window and a lack of subsequent target selection processes (N2pc. Errors were additionally accompanied by an increase of the fronto-central N2 and a kind of error negativity (Ne or ERN, which, however, peaked prior to the response. These results suggest that a strong perceptual conflict by salient distractors can disrupt the further processing of relevant information and thus affect its aware perception. Yet, it does not impair higher cognitive processes for conflict and error detection, indicating that these processes are independent from awareness.

Exploring the Cosmic Frontier, Task A - Direct Detection of Dark Matter, Task B - Experimental Particle Astrophysics

International Nuclear Information System (INIS)

Matthews, John A.J.; Gold, Michael S.

2016-01-01

This report summarizes the work of Task A and B for the period 2013-2016. For Task A the work is for direct detection of dark matter with the single-phase liquid argon experiment Mini-CLEAN. For Task B the work is for the search for new physics in the analysis of fluorescence events with the Auger experiment and for the search for the indirect detection of dark matter with the HAWC experiment.

Exploring the Cosmic Frontier, Task A - Direct Detection of Dark Matter, Task B - Experimental Particle Astrophysics

Energy Technology Data Exchange (ETDEWEB)

Matthews, John A.J. [Univ. of New Mexico, Albuquerque, NM (United States); Gold, Michael S. [Univ. of New Mexico, Albuquerque, NM (United States)

2016-08-11

This report summarizes the work of Task A and B for the period 2013-2016. For Task A the work is for direct detection of dark matter with the single-phase liquid argon experiment Mini-CLEAN. For Task B the work is for the search for new physics in the analysis of fluorescence events with the Auger experiment and for the search for the indirect detection of dark matter with the HAWC experiment.

Simulation of TanDEM-X interferograms for urban change detection

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Welte, Amelie; Hammer, Horst; Thiele, Antje; Hinz, Stefan

2017-10-01

Damage detection after natural disasters is one of the remote sensing tasks in which Synthetic Aperture Radar (SAR) sensors play an important role. Since SAR is an active sensor, it can record images at all times of day and in all weather conditions, making it ideally suited for this task. While with the newer generation of SAR satellites such as TerraSAR-X or COSMOSkyMed amplitude change detection has become possible even for urban areas, interferometric phase change detection has not been published widely. This is mainly because of the long revisit times of common SAR sensors leading to temporal decorrelation. This situation has changed dramatically with the advent of the TanDEM-X constellation, which can create single-pass interferograms from space at very high resolutions, avoiding temporal decorrelation almost completely. In this paper the basic structures that are present for any building in InSAR phases, i.e. layover, shadow, and roof areas, are examined. Approaches for their extraction from TanDEM-X interferograms are developed using simulated SAR interferograms. The extracted features of the building signature will in the future be used for urban change detection in real TanDEM-X High Resolution Spotlight interferograms.

Detecting Brain State Changes via Fiber-Centered Functional Connectivity Analysis

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Li, Xiang; Lim, Chulwoo; Li, Kaiming; Guo, Lei; Liu, Tianming

2013-01-01

Diffusion tensor imaging (DTI) and functional magnetic resonance imaging (fMRI) have been widely used to study structural and functional brain connectivity in recent years. A common assumption used in many previous functional brain connectivity studies is the temporal stationarity. However, accumulating literature evidence has suggested that functional brain connectivity is under temporal dynamic changes in different time scales. In this paper, a novel and intuitive approach is proposed to model and detect dynamic changes of functional brain states based on multimodal fMRI/DTI data. The basic idea is that functional connectivity patterns of all fiber-connected cortical voxels are concatenated into a descriptive functional feature vector to represent the brain’s state, and the temporal change points of brain states are decided by detecting the abrupt changes of the functional vector patterns via the sliding window approach. Our extensive experimental results have shown that meaningful brain state change points can be detected in task-based fMRI/DTI, resting state fMRI/DTI, and natural stimulus fMRI/DTI data sets. Particularly, the detected change points of functional brain states in task-based fMRI corresponded well to the external stimulus paradigm administered to the participating subjects, thus partially validating the proposed brain state change detection approach. The work in this paper provides novel perspective on the dynamic behaviors of functional brain connectivity and offers a starting point for future elucidation of the complex patterns of functional brain interactions and dynamics. PMID:22941508

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

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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.

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

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

2017-01-01

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

Decision criterion dynamics in animals performing an auditory detection task.

Directory of Open Access Journals (Sweden)

Robert W Mill

Full Text Available Classical signal detection theory attributes bias in perceptual decisions to a threshold criterion, against which sensory excitation is compared. The optimal criterion setting depends on the signal level, which may vary over time, and about which the subject is naïve. Consequently, the subject must optimise its threshold by responding appropriately to feedback. Here a series of experiments was conducted, and a computational model applied, to determine how the decision bias of the ferret in an auditory signal detection task tracks changes in the stimulus level. The time scales of criterion dynamics were investigated by means of a yes-no signal-in-noise detection task, in which trials were grouped into blocks that alternately contained easy- and hard-to-detect signals. The responses of the ferrets implied both long- and short-term criterion dynamics. The animals exhibited a bias in favour of responding "yes" during blocks of harder trials, and vice versa. Moreover, the outcome of each single trial had a strong influence on the decision at the next trial. We demonstrate that the single-trial and block-level changes in bias are a manifestation of the same criterion update policy by fitting a model, in which the criterion is shifted by fixed amounts according to the outcome of the previous trial and decays strongly towards a resting value. The apparent block-level stabilisation of bias arises as the probabilities of outcomes and shifts on single trials mutually interact to establish equilibrium. To gain an intuition into how stable criterion distributions arise from specific parameter sets we develop a Markov model which accounts for the dynamic effects of criterion shifts. Our approach provides a framework for investigating the dynamics of decisions at different timescales in other species (e.g., humans and in other psychological domains (e.g., vision, memory.

Is Neural Activity Detected by ERP-Based Brain-Computer Interfaces Task Specific?

Directory of Open Access Journals (Sweden)

Markus A Wenzel

Full Text Available Brain-computer interfaces (BCIs that are based on event-related potentials (ERPs can estimate to which stimulus a user pays particular attention. In typical BCIs, the user silently counts the selected stimulus (which is repeatedly presented among other stimuli in order to focus the attention. The stimulus of interest is then inferred from the electroencephalogram (EEG. Detecting attention allocation implicitly could be also beneficial for human-computer interaction (HCI, because it would allow software to adapt to the user's interest. However, a counting task would be inappropriate for the envisaged implicit application in HCI. Therefore, the question was addressed if the detectable neural activity is specific for silent counting, or if it can be evoked also by other tasks that direct the attention to certain stimuli.Thirteen people performed a silent counting, an arithmetic and a memory task. The tasks required the subjects to pay particular attention to target stimuli of a random color. The stimulus presentation was the same in all three tasks, which allowed a direct comparison of the experimental conditions.Classifiers that were trained to detect the targets in one task, according to patterns present in the EEG signal, could detect targets in all other tasks (irrespective of some task-related differences in the EEG.The neural activity detected by the classifiers is not strictly task specific but can be generalized over tasks and is presumably a result of the attention allocation or of the augmented workload. The results may hold promise for the transfer of classification algorithms from BCI research to implicit relevance detection in HCI.

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

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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.

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

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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.

A PCA-Based Change Detection Framework for Multidimensional Data Streams

KAUST Repository

Qahtan, Abdulhakim Ali Ali

2015-08-10

Detecting changes in multidimensional data streams is an important and challenging task. In unsupervised change detection, changes are usually detected by comparing the distribution in a current (test) window with a reference window. It is thus essential to design divergence metrics and density estimators for comparing the data distributions, which are mostly done for univariate data. Detecting changes in multidimensional data streams brings difficulties to the density estimation and comparisons. In this paper, we propose a framework for detecting changes in multidimensional data streams based on principal component analysis, which is used for projecting data into a lower dimensional space, thus facilitating density estimation and change-score calculations. The proposed framework also has advantages over existing approaches by reducing computational costs with an efficient density estimator, promoting the change-score calculation by introducing effective divergence metrics, and by minimizing the efforts required from users on the threshold parameter setting by using the Page-Hinkley test. The evaluation results on synthetic and real data show that our framework outperforms two baseline methods in terms of both detection accuracy and computational costs.

Towards a Framework for Change Detection in Data Sets

Science.gov (United States)

Böttcher, Mirko; Nauck, Detlef; Ruta, Dymitr; Spott, Martin

Since the world with its markets, innovations and customers is changing faster than ever before, the key to survival for businesses is the ability to detect, assess and respond to changing conditions rapidly and intelligently. Discovering changes and reacting to or acting upon them before others do has therefore become a strategical issue for many companies. However, existing data analysis techniques are insufflent for this task since they typically assume that the domain under consideration is stable over time. This paper presents a framework that detects changes within a data set at virtually any level of granularity. The underlying idea is to derive a rule-based description of the data set at different points in time and to subsequently analyse how these rules change. Nevertheless, further techniques are required to assist the data analyst in interpreting and assessing their changes. Therefore the framework also contains methods to discard rules that are non-drivers for change and to assess the interestingness of detected changes.

Change detection by rhesus monkeys (Macaca mulatta) and pigeons (Columba livia).

Science.gov (United States)

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

2012-08-01

Two monkeys (Macaca mulatta) learned a color change-detection task where two colored circles (selected from a 4-color set) were presented on a 4 × 4 invisible matrix. Following a delay, the correct response was to touch the changed colored circle. The monkeys' learning, color transfer, and delay transfer were compared to a similar experiment with pigeons. Monkeys, like pigeons (Columba livia), showed full transfer to four novel colors, and to delays as long as 6.4 s, suggesting they remembered the colors as opposed to perceptual based attentional capture process that may work at very short delays. The monkeys and pigeons were further tested to compare transfer with other dimensions. Monkeys transferred to shape and location changes, unlike the pigeons, but neither species transferred to size changes. Thus, monkeys were less restricted in their domain to detect change than pigeons, but both species learned the basic task and appear suitable for comparative studies of visual short-term memory. 2012 APA, all rights reserved

The Effect of Concurrent Music Reading and Performance on the Ability to Detect Tempo Change.

Science.gov (United States)

Ellis, Mark Carlton

1989-01-01

Measures the ability of three groups of musicians to detect tempo change while reading and performing music. Compares this ability with that of the same musicians to detect tempo change while listening only. Found that for all groups the ability to detect tempo changes was inhibited by the playing task, although to different degrees for each…

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

Science.gov (United States)

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.

Efficient Incorporation of Markov Random Fields in Change Detection

DEFF Research Database (Denmark)

Aanæs, Henrik; Nielsen, Allan Aasbjerg; Carstensen, Jens Michael

2009-01-01

of noise, implying that the pixel-wise classifier is also noisy. There is thus a need for incorporating local homogeneity constraints into such a change detection framework. For this modelling task Markov Random Fields are suitable. Markov Random Fields have, however, previously been plagued by lack...

Brain correlates of automatic visual change detection.

Science.gov (United States)

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.

Extended image differencing for change detection in UAV video mosaics

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Saur, Günter; Krüger, Wolfgang; Schumann, Arne

2014-03-01

Change detection is one of the most important tasks when using unmanned aerial vehicles (UAV) for video reconnaissance and surveillance. We address changes of short time scale, i.e. the observations are taken in time distances from several minutes up to a few hours. Each observation is a short video sequence acquired by the UAV in near-nadir view and the relevant changes are, e.g., recently parked or moved vehicles. In this paper we extend our previous approach of image differencing for single video frames to video mosaics. A precise image-to-image registration combined with a robust matching approach is needed to stitch the video frames to a mosaic. Additionally, this matching algorithm is applied to mosaic pairs in order to align them to a common geometry. The resulting registered video mosaic pairs are the input of the change detection procedure based on extended image differencing. A change mask is generated by an adaptive threshold applied to a linear combination of difference images of intensity and gradient magnitude. 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 size of shadows, and compression or transmission artifacts. The special effects of video mosaicking such as geometric distortions and artifacts at moving objects have to be considered, too. In our experiments we analyze the influence of these effects on the change detection results by considering several scenes. The results show that for video mosaics this task is more difficult than for single video frames. Therefore, we extended the image registration by estimating an elastic transformation using a thin plate spline approach. The results for mosaics are comparable to that of single video frames and are useful for interactive image exploitation due to a larger scene coverage.

Short-term change detection for UAV video

Science.gov (United States)

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

Different Neuroplasticity for Task Targets and Distractors

Science.gov (United States)

Spingath, Elsie Y.; Kang, Hyun Sug; Plummer, Thane; Blake, David T.

2011-01-01

Adult learning-induced sensory cortex plasticity results in enhanced action potential rates in neurons that have the most relevant information for the task, or those that respond strongly to one sensory stimulus but weakly to its comparison stimulus. Current theories suggest this plasticity is caused when target stimulus evoked activity is enhanced by reward signals from neuromodulatory nuclei. Prior work has found evidence suggestive of nonselective enhancement of neural responses, and suppression of responses to task distractors, but the differences in these effects between detection and discrimination have not been directly tested. Using cortical implants, we defined physiological responses in macaque somatosensory cortex during serial, matched, detection and discrimination tasks. Nonselective increases in neural responsiveness were observed during detection learning. Suppression of responses to task distractors was observed during discrimination learning, and this suppression was specific to cortical locations that sampled responses to the task distractor before learning. Changes in receptive field size were measured as the area of skin that had a significant response to a constant magnitude stimulus, and these areal changes paralleled changes in responsiveness. From before detection learning until after discrimination learning, the enduring changes were selective suppression of cortical locations responsive to task distractors, and nonselective enhancement of responsiveness at cortical locations selective for target and control skin sites. A comparison of observations in prior studies with the observed plasticity effects suggests that the non-selective response enhancement and selective suppression suffice to explain known plasticity phenomena in simple spatial tasks. This work suggests that differential responsiveness to task targets and distractors in primary sensory cortex for a simple spatial detection and discrimination task arise from nonselective

Different neuroplasticity for task targets and distractors.

Directory of Open Access Journals (Sweden)

Elsie Y Spingath

2011-01-01

Full Text Available Adult learning-induced sensory cortex plasticity results in enhanced action potential rates in neurons that have the most relevant information for the task, or those that respond strongly to one sensory stimulus but weakly to its comparison stimulus. Current theories suggest this plasticity is caused when target stimulus evoked activity is enhanced by reward signals from neuromodulatory nuclei. Prior work has found evidence suggestive of nonselective enhancement of neural responses, and suppression of responses to task distractors, but the differences in these effects between detection and discrimination have not been directly tested. Using cortical implants, we defined physiological responses in macaque somatosensory cortex during serial, matched, detection and discrimination tasks. Nonselective increases in neural responsiveness were observed during detection learning. Suppression of responses to task distractors was observed during discrimination learning, and this suppression was specific to cortical locations that sampled responses to the task distractor before learning. Changes in receptive field size were measured as the area of skin that had a significant response to a constant magnitude stimulus, and these areal changes paralleled changes in responsiveness. From before detection learning until after discrimination learning, the enduring changes were selective suppression of cortical locations responsive to task distractors, and nonselective enhancement of responsiveness at cortical locations selective for target and control skin sites. A comparison of observations in prior studies with the observed plasticity effects suggests that the non-selective response enhancement and selective suppression suffice to explain known plasticity phenomena in simple spatial tasks. This work suggests that differential responsiveness to task targets and distractors in primary sensory cortex for a simple spatial detection and discrimination task arise from

Changes in step-width during dual-task walking predicts falls.

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Nordin, E; Moe-Nilssen, R; Ramnemark, A; Lundin-Olsson, L

2010-05-01

The aim was to evaluate whether gait pattern changes between single- and dual-task conditions were associated with risk of falling in older people. Dual-task cost (DTC) of 230 community living, physically independent people, 75 years or older, was determined with an electronic walkway. Participants were followed up each month for 1 year to record falls. Mean and variability measures of gait characteristics for 5 dual-task conditions were compared to single-task walking for each participant. Almost half (48%) of the participants fell at least once during follow-up. Risk of falling increased in individuals where DTC for performing a subtraction task demonstrated change in mean step-width compared to single-task walking. Risk of falling decreased in individuals where DTC for carrying a cup and saucer demonstrated change compared to single-task walking in mean step-width, mean step-time, and step-length variability. Degree of change in gait characteristics related to a change in risk of falling differed between measures. Prognostic guidance for fall risk was found for the above DTCs in mean step-width with a negative likelihood ratio of 0.5 and a positive likelihood ratio of 2.3, respectively. Findings suggest that changes in step-width, step-time, and step-length with dual tasking may be related to future risk of falling. Depending on the nature of the second task, DTC may indicate either an increased risk of falling, or a protective strategy to avoid falling. Copyright 2010. Published by Elsevier B.V.

MULTI-TEMPORAL CLASSIFICATION AND CHANGE DETECTION USING UAV IMAGES

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S. Makuti

2018-05-01

Full Text Available 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.

Does facial processing prioritize change detection?: change blindness illustrates costs and benefits of holistic processing.

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Wilford, Miko M; Wells, Gary L

2010-11-01

There is broad consensus among researchers both that faces are processed more holistically than other objects and that this type of processing is beneficial. We predicted that holistic processing of faces also involves a cost, namely, a diminished ability to localize change. This study (N = 150) utilized a modified change-blindness paradigm in which some trials involved a change in one feature of an image (nose, chin, mouth, hair, or eyes for faces; chimney, porch, window, roof, or door for houses), whereas other trials involved no change. People were better able to detect the occurrence of a change for faces than for houses, but were better able to localize which feature had changed for houses than for faces. Half the trials used inverted images, a manipulation that disrupts holistic processing. With inverted images, the critical interaction between image type (faces vs. houses) and task (change detection vs. change localization) disappeared. The results suggest that holistic processing reduces change-localization abilities.

How Important is Conflict Detection to the Conflict Resolution Task?

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Mercer, Joey; Gabets, Cynthia; Gomez, Ashley; Edwards, Tamsyn; Bienert, Nancy; Claudatos, Lauren; Homola, Jeffrey R.

2016-01-01

To determine the capabilities and limitations of human operators and automation in separation assurance roles, the second of three Human-in-the-Loop (HITL) part-task studies investigates air traffic controllers ability to detect and resolve conflicts under varying task sets, traffic densities, and run lengths. Operations remained within a single sector, staffed by a single controller, and explored, among other things, the controllers conflict resolution performance in conditions with or without their involvement in the conflict detection task. Whereas comparisons of conflict resolution performance between these two conditions are available in a prior publication, this paper explores whether or not other subjective measures display a relationship to that data. Analyses of controller workload and situation awareness measures attempt to quantify their contribution to controllers ability to resolve traffic conflicts.

Object representations in visual working memory change according to the task context.

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Balaban, Halely; Luria, Roy

2016-08-01

This study investigated whether an item's representation in visual working memory (VWM) can be updated according to changes in the global task context. We used a modified change detection paradigm, in which the items moved before the retention interval. In all of the experiments, we presented identical color-color conjunction items that were arranged to provide a common fate Gestalt grouping cue during their movement. Task context was manipulated by adding a condition highlighting either the integrated interpretation of the conjunction items or their individuated interpretation. We monitored the contralateral delay activity (CDA) as an online marker of VWM. Experiment 1 employed only a minimal global context; the conjunction items were integrated during their movement, but then were partially individuated, at a late stage of the retention interval. The same conjunction items were perfectly integrated in an integration context (Experiment 2). An individuation context successfully produced strong individuation, already during the movement, overriding Gestalt grouping cues (Experiment 3). In Experiment 4, a short priming of the individuation context managed to individuate the conjunction items immediately after the Gestalt cue was no longer available. Thus, the representations of identical items changed according to the task context, suggesting that VWM interprets incoming input according to global factors which can override perceptual cues. Copyright © 2016 Elsevier Ltd. All rights reserved.

"Binary" and "non-binary" detection tasks: are current performance measures optimal?

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Gur, David; Rockette, Howard E; Bandos, Andriy I

2007-07-01

We have observed that a very large fraction of responses for several detection tasks during the performance of observer studies are in the extreme ranges of lower than 11% or higher than 89% regardless of the actual presence or absence of the abnormality in question or its subjectively rated "subtleness." This observation raises questions regarding the validity and appropriateness of using multicategory rating scales for such detection tasks. Monte Carlo simulation of binary and multicategory ratings for these tasks demonstrate that the use of the former (binary) often results in a less biased and more precise summary index and hence may lead to a higher statistical power for determining differences between modalities.

Detection of auditory signals in quiet and noisy backgrounds while performing a visuo-spatial task

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Vishakha W Rawool

2016-01-01

Full Text Available Context: The ability to detect important auditory signals while performing visual tasks may be further compounded by background chatter. Thus, it is important to know how task performance may interact with background chatter to hinder signal detection. Aim: To examine any interactive effects of speech spectrum noise and task performance on the ability to detect signals. Settings and Design: The setting was a sound-treated booth. A repeated measures design was used. Materials and Methods: Auditory thresholds of 20 normal adults were determined at 0.5, 1, 2 and 4 kHz in the following conditions presented in a random order: (1 quiet with attention; (2 quiet with a visuo-spatial task or puzzle (distraction; (3 noise with attention and (4 noise with task. Statistical Analysis: Multivariate analyses of variance (MANOVA with three repeated factors (quiet versus noise, visuo-spatial task versus no task, signal frequency. Results: MANOVA revealed significant main effects for noise and signal frequency and significant noise–frequency and task–frequency interactions. Distraction caused by performing the task worsened the thresholds for tones presented at the beginning of the experiment and had no effect on tones presented in the middle. At the end of the experiment, thresholds (4 kHz were better while performing the task than those obtained without performing the task. These effects were similar across the quiet and noise conditions. Conclusion: Detection of auditory signals is difficult at the beginning of a distracting visuo-spatial task but over time, task learning and auditory training effects can nullify the effect of distraction and may improve detection of high frequency sounds.

The reliability and internal consistency of one-shot and flicker change detection for measuring individual differences in visual working memory capacity.

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Pailian, Hrag; Halberda, Justin

2015-04-01

We investigated the psychometric properties of the one-shot change detection task for estimating visual working memory (VWM) storage capacity-and also introduced and tested an alternative flicker change detection task for estimating these limits. In three experiments, we found that the one-shot whole-display task returns estimates of VWM storage capacity (K) that are unreliable across set sizes-suggesting that the whole-display task is measuring different things at different set sizes. In two additional experiments, we found that the one-shot single-probe variant shows improvements in the reliability and consistency of K estimates. In another additional experiment, we found that a one-shot whole-display-with-click task (requiring target localization) also showed improvements in reliability and consistency. The latter results suggest that the one-shot task can return reliable and consistent estimates of VWM storage capacity (K), and they highlight the possibility that the requirement to localize the changed target is what engenders this enhancement. Through a final series of four experiments, we introduced and tested an alternative flicker change detection method that also requires the observer to localize the changing target and that generates, from response times, an estimate of VWM storage capacity (K). We found that estimates of K from the flicker task correlated with estimates from the traditional one-shot task and also had high reliability and consistency. We highlight the flicker method's ability to estimate executive functions as well as VWM storage capacity, and discuss the potential for measuring multiple abilities with the one-shot and flicker tasks.

A sequential sampling account of response bias and speed-accuracy tradeoffs in a conflict detection task.

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Vuckovic, Anita; Kwantes, Peter J; Humphreys, Michael; Neal, Andrew

2014-03-01

Signal Detection Theory (SDT; Green & Swets, 1966) is a popular tool for understanding decision making. However, it does not account for the time taken to make a decision, nor why response bias might change over time. Sequential sampling models provide a way of accounting for speed-accuracy trade-offs and response bias shifts. In this study, we test the validity of a sequential sampling model of conflict detection in a simulated air traffic control task by assessing whether two of its key parameters respond to experimental manipulations in a theoretically consistent way. Through experimental instructions, we manipulated participants' response bias and the relative speed or accuracy of their responses. The sequential sampling model was able to replicate the trends in the conflict responses as well as response time across all conditions. Consistent with our predictions, manipulating response bias was associated primarily with changes in the model's Criterion parameter, whereas manipulating speed-accuracy instructions was associated with changes in the Threshold parameter. The success of the model in replicating the human data suggests we can use the parameters of the model to gain an insight into the underlying response bias and speed-accuracy preferences common to dynamic decision-making tasks. © 2013 American Psychological Association

Multi-Task Vehicle Detection with Region-of-Interest Voting.

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Chu, Wenqing; Liu, Yao; Shen, Chen; Cai, Deng; Hua, Xian-Sheng

2017-10-12

Vehicle detection is a challenging problem in autonomous driving systems, due to its large structural and appearance variations. In this paper, we propose a novel vehicle detection scheme based on multi-task deep convolutional neural networks (CNN) and region-of-interest (RoI) voting. In the design of CNN architecture, we enrich the supervised information with subcategory, region overlap, bounding-box regression and category of each training RoI as a multi-task learning framework. This design allows the CNN model to share visual knowledge among different vehicle attributes simultaneously, thus detection robustness can be effectively improved. In addition, most existing methods consider each RoI independently, ignoring the clues from its neighboring RoIs. In our approach, we utilize the CNN model to predict the offset direction of each RoI boundary towards the corresponding ground truth. Then each RoI can vote those suitable adjacent bounding boxes which are consistent with this additional information. The voting results are combined with the score of each RoI itself to find a more accurate location from a large number of candidates. Experimental results on the real-world computer vision benchmarks KITTI and the PASCAL2007 vehicle dataset show that our approach achieves superior performance in vehicle detection compared with other existing published works.

Age-related Multiscale Changes in Brain Signal Variability in Pre-task versus Post-task Resting-state EEG.

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Wang, Hongye; McIntosh, Anthony R; Kovacevic, Natasa; Karachalios, Maria; Protzner, Andrea B

2016-07-01

Recent empirical work suggests that, during healthy aging, the variability of network dynamics changes during task performance. Such variability appears to reflect the spontaneous formation and dissolution of different functional networks. We sought to extend these observations into resting-state dynamics. We recorded EEG in young, middle-aged, and older adults during a "rest-task-rest" design and investigated if aging modifies the interaction between resting-state activity and external stimulus-induced activity. Using multiscale entropy as our measure of variability, we found that, with increasing age, resting-state dynamics shifts from distributed to more local neural processing, especially at posterior sources. In the young group, resting-state dynamics also changed from pre- to post-task, where fine-scale entropy increased in task-positive regions and coarse-scale entropy increased in the posterior cingulate, a key region associated with the default mode network. Lastly, pre- and post-task resting-state dynamics were linked to performance on the intervening task for all age groups, but this relationship became weaker with increasing age. Our results suggest that age-related changes in resting-state dynamics occur across different spatial and temporal scales and have consequences for information processing capacity.

Detecting Output Pressure Change of Positive-Displacement Pump by Phase Trajectory Method

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Jerzy Stojek

2010-06-01

Full Text Available The monitoring of hydraulic system condition change during its exploitation ran its complex problem. The main task is to identifyearly phase damage of hydraulic system elements (pumps, valves, ect. in order to take decision which can avoid hydraulic system breakdown. This paper presents the possibility of phase trajectories use in detecting output pressure change of hydraulic system causedby positive-displacement pump wear.

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

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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.

Electrophysiological measures of conflict detection and resolution in the Stroop task.

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Coderre, Emily; Conklin, Kathy; van Heuven, Walter J B

2011-09-21

Conflict detection and resolution is crucial in a cognitive task like the Stroop task. Previous studies have identified an early negativity component (N(inc)) as a prominent marker of Stroop conflict in event-related potentials (ERPs). However, to what extent this ERP component reflects conflict detection and/or resolution is still unclear. Here, we report a Stroop task in which the stimulus onset asynchrony (SOA) of color and word stimuli presentation was manipulated in order to disentangle the roles of conflict detection and conflict resolution in generating Stroop-related ERP components. Separating the word from the color information gives us precise control over the timing of conflict. If the N(inc) is related with conflict resolution it should be absent when the word appears during response preparation, as in a long-latency positive SOA. Our data shows that the N(inc) occurs in all SOAs, even after a response has been made, supporting its role in the detection of stimulus conflict rather than conflict resolution. The use of SOA manipulation therefore allows for the examination of a wider temporal spectrum of interference in order to specify the functions of this conflict-related component. These results provide insight into the neural signatures of conflict processes, and have implications for models of cognitive control mechanisms in the brain. Copyright © 2011 Elsevier B.V. All rights reserved.

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

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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.

Functional Task Test: 1. Sensorimotor changes Associated with Postflight Alterations in Astronaut Functional Task Performance

Science.gov (United States)

Bloomberg, J. J.; Arzeno, N. H.; Buxton, R. E.; Feiveson, A. H.; Kofman, I. S.; Lee, S. M. C.; Miller, C. A.; Mulavara, A. P.; Platts, S. H.; Peters, B. T.;

Dedicated memory structure holding data for detecting available worker thread(s) and informing available worker thread(s) of task(s) to execute

Energy Technology Data Exchange (ETDEWEB)

Chiu, George L.; Eichenberger, Alexandre E.; O' Brien, John K. P.

2016-12-13

The present disclosure relates generally to a dedicated memory structure (that is, hardware device) holding data for detecting available worker thread(s) and informing available worker thread(s) of task(s) to execute.

Technicolor/INRIA team at the MediaEval 2013 Violent Scenes Detection Task

OpenAIRE

Penet , Cédric; Demarty , Claire-Hélène; Gravier , Guillaume; Gros , Patrick

2013-01-01

International audience; This paper presents the work done at Technicolor and INRIA regarding the MediaEval 2013 Violent Scenes Detection task, which aims at detecting violent scenes in movies. We participated in both the objective and the subjective subtasks.

Change detection of medical images using dictionary learning techniques and PCA

Science.gov (United States)

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.

Improving Dual-Task Walking Paradigms to Detect Prodromal Parkinson’s and Alzheimer’s Diseases

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Maroua Belghali

2017-05-01

Full Text Available Gait control is a complex movement, relying on spinal, subcortical, and cortical structures. The presence of deficits in one or more of these structures will result in changes in gait automaticity and control, as is the case in several neurodegenerative diseases, such as Alzheimer’s disease (AD and Parkinson’s disease (PD. By reviewing recent findings in this field of research, current studies have shown that gait performance assessment under dual-task conditions could contribute to predict both of these diseases. Such suggestions are relevant mainly for people at putatively high risk of developing AD (i.e., older adults with mild cognitive impairment subtypes or PD (i.e., older adults with either Mild Parkinsonian signs or LRRK2 G2019S mutation. Despite the major importance of these results, the type of cognitive task that should be used as a concurrent secondary task has to be selected among the plurality of tasks proposed in the literature. Furthermore, the key aspects of gait control that represent sensitive and specific “gait signatures” for prodromal AD or PD need to be determined. In the present perspective article, we suggest the use of a Stroop interference task requiring inhibitory attentional control and a set-shifting task requiring reactive flexibility as being particularly relevant secondary tasks for challenging gait in prodromal AD and PD, respectively. Investigating how inhibition and cognitive flexibility interfere with gait control is a promising avenue for future research aimed at enhancing early detection of AD and PD, respectively.

Cue combination in a combined feature contrast detection and figure identification task.

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Meinhardt, Günter; Persike, Malte; Mesenholl, Björn; Hagemann, Cordula

2006-11-01

Target figures defined by feature contrast in spatial frequency, orientation or both cues had to be detected in Gabor random fields and their shape had to be identified in a dual task paradigm. Performance improved with increasing feature contrast and was strongly correlated among both tasks. Subjects performed significantly better with combined cues than with single cues. The improvement due to cue summation was stronger than predicted by the assumption of independent feature specific mechanisms, and increased with the performance level achieved with single cues until it was limited by ceiling effects. Further, cue summation was also strongly correlated among tasks: when there was benefit due to the additional cue in feature contrast detection, there was also benefit in figure identification. For the same performance level achieved with single cues, cue summation was generally larger in figure identification than in feature contrast detection, indicating more benefit when processes of shape and surface formation are involved. Our results suggest that cue combination improves spatial form completion and figure-ground segregation in noisy environments, and therefore leads to more stable object vision.

Developmental changes in using verbal self-cueing in task-switching situations: the impact of task practice and task-sequencing demands

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Kray, Jutta; Gaspard, Hanna; Karbach, Julia; Blaye, Agnès

2013-01-01

In this study we examined whether developmental changes in using verbal self-cueing for task-goal maintenance are dependent on the amount of task practice and task-sequencing demands. To measure task-goal maintenance we applied a switching paradigm in which children either performed only task A or B in single-task blocks or switched between them on every second trial in mixed-task blocks. Task-goal maintenance was determined by comparing the performance between both blocks (mixing costs). The influence of verbal self-cueing was measured by instructing children to either name the next task aloud or not to verbalize during task preparation. Task-sequencing demands were varied between groups whereas one group received spatial task cues to support keeping track of the task sequence, while the other group did not. We also varied by the amount of prior practice in task switching while one group of participants practiced task switching first, before performing the task naming in addition, and the other group did it vice versa. Results of our study investigating younger (8–10 years) and older children (11–13 years) revealed no age differences in beneficial effects of verbal self-cueing. In line with previous findings, children showed reduced mixing costs under task-naming instructions and under conditions of low task-sequence demands (with the presence of spatial task cues). Our results also indicated that these benefits were only obtained for those groups of children that first received practice in task switching alone with no additional verbalization instruction. These findings suggest that internal task-cueing strategies can be efficiently used in children but only if they received prior practice in the underlying task so that demands on keeping and coordinating various instructions are reduced. Moreover, children benefitted from spatial task cues for better task-goal maintenance only if no verbal task-cueing strategy was introduced first. PMID:24381566

Incidental orthographic learning during a color detection task.

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Protopapas, Athanassios; Mitsi, Anna; Koustoumbardis, Miltiadis; Tsitsopoulou, Sofia M; Leventi, Marianna; Seitz, Aaron R

2017-09-01

Orthographic learning refers to the acquisition of knowledge about specific spelling patterns forming words and about general biases and constraints on letter sequences. It is thought to occur by strengthening simultaneously activated visual and phonological representations during reading. Here we demonstrate that a visual perceptual learning procedure that leaves no time for articulation can result in orthographic learning evidenced in improved reading and spelling performance. We employed task-irrelevant perceptual learning (TIPL), in which the stimuli to be learned are paired with an easy task target. Assorted line drawings and difficult-to-spell words were presented in red color among sequences of other black-colored words and images presented in rapid succession, constituting a fast-TIPL procedure with color detection being the explicit task. In five experiments, Greek children in Grades 4-5 showed increased recognition of words and images that had appeared in red, both during and after the training procedure, regardless of within-training testing, and also when targets appeared in blue instead of red. Significant transfer to reading and spelling emerged only after increased training intensity. In a sixth experiment, children in Grades 2-3 showed generalization to words not presented during training that carried the same derivational affixes as in the training set. We suggest that reinforcement signals related to detection of the target stimuli contribute to the strengthening of orthography-phonology connections beyond earlier levels of visually-based orthographic representation learning. These results highlight the potential of perceptual learning procedures for the reinforcement of higher-level orthographic representations. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Visual performance on detection tasks with double-targets of the same and different difficulty.

Science.gov (United States)

Chan, Alan H S; Courtney, Alan J; Ma, C W

2002-10-20

This paper reports a study of measurement of horizontal visual sensitivity limits for 16 subjects in single-target and double-targets detection tasks. Two phases of tests were conducted in the double-targets task; targets of the same difficulty were tested in phase one while targets of different difficulty were tested in phase two. The range of sensitivity for the double-targets test was found to be smaller than that for single-target in both the same and different target difficulty cases. The presence of another target was found to affect performance to a marked degree. Interference effect of the difficult target on detection of the easy one was greater than that of the easy one on the detection of the difficult one. Performance decrement was noted when correct percentage detection was plotted against eccentricity of target in both the single-target and double-targets tests. Nevertheless, the non-significant correlation found between the performance for the two tasks demonstrated that it was impossible to predict quantitatively ability for detection of double targets from the data for single targets. This indicated probable problems in generalizing data for single target visual lobes to those for multiple targets. Also lobe area values obtained from measurements using a single-target task cannot be applied in a mathematical model for situations with multiple occurrences of targets.

Comparing kinematic changes between a finger-tapping task and unconstrained finger flexion-extension task in patients with Parkinson's disease.

Science.gov (United States)

Teo, W P; Rodrigues, J P; Mastaglia, F L; Thickbroom, G W

2013-06-01

Repetitive finger tapping is a well-established clinical test for the evaluation of parkinsonian bradykinesia, but few studies have investigated other finger movement modalities. We compared the kinematic changes (movement rate and amplitude) and response to levodopa during a conventional index finger-thumb-tapping task and an unconstrained index finger flexion-extension task performed at maximal voluntary rate (MVR) for 20 s in 11 individuals with levodopa-responsive Parkinson's disease (OFF and ON) and 10 healthy age-matched controls. Between-task comparisons showed that for all conditions, the initial movement rate was greater for the unconstrained flexion-extension task than the tapping task. Movement rate in the OFF state was slower than in controls for both tasks and normalized in the ON state. The movement amplitude was also reduced for both tasks in OFF and increased in the ON state but did not reach control levels. The rate and amplitude of movement declined significantly for both tasks under all conditions (OFF/ON and controls). The time course of rate decline was comparable for both tasks and was similar in OFF/ON and controls, whereas the tapping task was associated with a greater decline in MA, both in controls and ON, but not OFF. The findings indicate that both finger movement tasks show similar kinematic changes during a 20-s sustained MVR, but that movement amplitude is less well sustained during the tapping task than the unconstrained finger movement task. Both movement rate and amplitude improved with levodopa; however, movement rate was more levodopa responsive than amplitude.

Climate change and precipitation: Detecting changes Climate change and precipitation: Detecting changes

International Nuclear Information System (INIS)

Van Boxel, John H

2001-01-01

Precipitation is one of the most, if not the most important climate parameter In most studies on climate change the emphasis is on temperature and sea level rise. Often too little attention is given to precipitation. For a large part this is due to the large spatial en temporal variability of precipitation, which makes the detection of changes difficult. This paper describes methods to detect changes in precipitation. In order to arrive at statistically significant changes one must use long time series and spatial averages containing the information from several stations. In the Netherlands the average yearly precipitation increased by 11% during the 20th century .In the temperate latitudes on the Northern Hemisphere (40-60QN) the average increase was about 7% over the 20th century and the globally averaged precipitation increased by about 3%. During the 20th century 38% of the land surface of the earth became wetter, 42% experienced little change (less than 5% change) and 20% became dryer. More important than the average precipitation is the occurrence of extremes. In the Netherlands there is a tendency to more extreme precipitations, whereas the occurrence of relatively dry months has not changed. Also in many other countries increases in heavy precipitation events are observed. All climate models predict a further increase of mean global precipitation if the carbon dioxide concentration doubles. Nevertheless some areas get dryer, others have little change and consequently there are also areas where the increase is much more than the global average. On a regional scale however there are large differences between the models. Climate models do not yet provide adequate information on changes in extreme precipitations

Changing change detection

DEFF Research Database (Denmark)

Kyllingsbæk, Søren; Bundesen, Claus

2009-01-01

The change detection paradigm is a popular way of measuring visual short-term memory capacity. Using the paradigm, researchers have found evidence for a capacity of about four independent visual objects, confirming classic estimates that were based on the number of items that could be reported...

Implicit Behavioral Change in Response to Cognitive Tasks in Alzheimer Disease.

Science.gov (United States)

Bomilcar, Iris; Morris, Robin G; Brown, Richard G; Mograbi, Daniel C

2018-03-01

Lack of awareness about impairments is commonly found in Alzheimer disease (AD), but recent evidence suggests that patients may respond to the experience of illness despite limited awareness. In this study, we explored whether implicit emotional responses to experiences of failure in cognitive tasks would result in longer-term change in behavior. Twenty-two patients with AD were seen 1 week after a previous session in which they performed computer tasks that had been manipulated to be either too difficult (failure condition) or very easy (success condition) for them. At the second session, both types of tasks were set to have medium difficulty and were administered so that the participants decided how long to persist on each task. Task persistence was determined by relative time spent doing the tasks, considering that participants would be more likely to stop performing tasks in which they had experienced failure during the first session. Task persistence in the second session was not affected by performance in the first session. However, when participants' awareness of performance in the first session was taken into account, differences were found in persistence between tasks in the second session. During the second session, participants stopped performing tasks after a sequence of errors. There were no self-reported changes in motivation or enjoyment in response to task failure. These findings suggest that implicit learning of task valence may be compromised in AD, but that initial moments of awareness of performance may influence long-term adaptation in unaware patients.

Simple real-time computerized tasks for detection of malingering among murderers with schizophrenia.

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Kertzman, Semion; Grinspan, Haim; Birger, Moshe; Shliapnikov, Nina; Alish, Yakov; Ben Nahum, Zeev; Mester, Roberto; Kotler, Moshe

2006-01-01

It is our contention that computer-based two-alternative forced choice techniques can be useful tools for the detection of patients with schizophrenia who feign acute psychotic symptoms and cognitive impairment as opposed to patients with schizophrenia with a true active psychosis. In our experiment, Visual Simple and Choice Reaction Time tasks were used. Reaction time in milliseconds was recorded and accuracy rate was obtained for all subjects' responses. Both types of task were administered to 27 patients with schizophrenia suspected of having committed murder. Patients with schizophrenia who were clinically assessed as malingerers achieved significantly fewer correct results, were significantly slower and less consistent in their reaction time. Congruence of performance between the Simple and Choice tasks was an additional parameter for the accurate diagnosis of malingering. The four parameters of both tests (accuracy of response, reaction time, standard deviation of reaction time and task congruency) are simple and constitute a user-friendly means for the detection of malingering in forensic practice. Another advantage of this procedure is that the software automatically measures and evaluates all the parameters.

Task-dependent changes of corticospinal excitability during observation and motor imagery of balance tasks.

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Mouthon, A; Ruffieux, J; Wälchli, M; Keller, M; Taube, W

2015-09-10

Non-physical balance training has demonstrated to be efficient to improve postural control in young people. However, little is known about the potential to increase corticospinal excitability by mental simulation in lower leg muscles. Mental simulation of isolated, voluntary contractions of limb muscles increase corticospinal excitability but more automated tasks like walking seem to have no or only minor effects on motor-evoked potentials (MEPs) evoked by transcranial magnetic stimulation (TMS). This may be related to the way of performing the mental simulation or the task itself. Therefore, the present study aimed to clarify how corticospinal excitability is modulated during AO+MI, MI and action observation (AO) of balance tasks. For this purpose, MEPs and H-reflexes were elicited during three different mental simulations (a) AO+MI, (b) MI and (c) passive AO. For each condition, two balance tasks were evaluated: (1) quiet upright stance (static) and (2) compensating a medio-lateral perturbation while standing on a free-swinging platform (dynamic). AO+MI resulted in the largest facilitation of MEPs followed by MI and passive AO. MEP facilitation was significantly larger in the dynamic perturbation than in the static standing task. Interestingly, passive observation resulted in hardly any facilitation independent of the task. H-reflex amplitudes were not modulated. The current results demonstrate that corticospinal excitability during mental simulation of balance tasks is influenced by both the type of mental simulation and the task difficulty. As H-reflexes and background EMG were not modulated, it may be argued that changes in excitability of the primary motor cortex were responsible for the MEP modulation. From a functional point of view, our findings suggest best training/rehabilitation effects when combining MI with AO during challenging postural tasks. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Support Vector Machines for Multitemporal and Multisensor Change Detection in a Mining Area

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Hecheltjen, Antje; Waske, Bjorn; Thonfeld, Frank; Braun, Matthias; Menz, Gunter

2010-12-01

Long-term change detection often implies the challenge of incorporating multitemporal data from different sensors. Most of the conventional change detection algorithms are designed for bi-temporal datasets from the same sensors detecting only the existence of changes. The labeling of change areas remains a difficult task. To overcome such drawbacks, much attention has been given lately to algorithms arising from machine learning, such as Support Vector Machines (SVMs). While SVMs have been applied successfully for land cover classifications, the exploitation of this approach for change detection is still in its infancy. Few studies have already proven the applicability of SVMs for bi- and multitemporal change detection using data from one sensor only. In this paper we demonstrate the application of SVM for multitemporal and -sensor change detection. Our study site covers lignite open pit mining areas in the German state North Rhine-Westphalia. The dataset consists of bi-temporal Landsat data and multi-temporal ERS SAR data covering two time slots (2001 and 2009). The SVM is conducted using the IDL program imageSVM. Change is deduced from one time slot to the next resulting in two change maps. In contrast to change detection, which is based on post-classification comparison, change detection is seen here as a specific classification problem. Thus, changes are directly classified from a layer-stack of the two years. To reduce the number of change classes, we created a change mask using the magnitude of Change Vector Analysis (CVA). Training data were selected for different change classes (e.g. forest to mining or mining to agriculture) as well as for the no-change classes (e.g. agriculture). Subsequently, they were divided in two independent sets for training the SVMs and accuracy assessment, respectively. Our study shows the applicability of SVMs to classify changes via SVMs. The proposed method yielded a change map of reclaimed and active mines. The use of ERS SAR

Detecting gait abnormalities after concussion or mild traumatic brain injury: A systematic review of single-task, dual-task, and complex gait.

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Fino, Peter C; Parrington, Lucy; Pitt, Will; Martini, Douglas N; Chesnutt, James C; Chou, Li-Shan; King, Laurie A

2018-05-01

While a growing number of studies have investigated the effects of concussion or mild traumatic brain injury (mTBI) on gait, many studies use different experimental paradigms and outcome measures. The path for translating experimental studies for objective clinical assessments of gait is unclear. This review asked 2 questions: 1) is gait abnormal after concussion/mTBI, and 2) what gait paradigms (single-task, dual-task, complex gait) detect abnormalities after concussion. Data sources included MEDLINE/PubMed, Scopus, Web of Science, and Cumulative Index to Nursing and Allied Health Literature (CINAHL) accessed on March 14, 2017. Original research articles reporting gait outcomes in people with concussion or mTBI were included. Studies of moderate, severe, or unspecified TBI, and studies without a comparator were excluded. After screening 233 articles, 38 studies were included and assigned to one or more sections based on the protocol and reported outcomes. Twenty-six articles reported single-task simple gait outcomes, 24 reported dual-task simple gait outcomes, 21 reported single-task complex gait outcomes, and 10 reported dual-task complex gait outcomes. Overall, this review provides evidence for two conclusions: 1) gait is abnormal acutely after concussion/mTBI but generally resolves over time; and 2) the inconsistency of findings, small sample sizes, and small number of studies examining homogenous measures at the same time-period post-concussion highlight the need for replication across independent populations and investigators. Future research should concentrate on dual-task and complex gait tasks, as they showed promise for detecting abnormal locomotor function outside of the acute timeframe. Additionally, studies should provide detailed demographic and clinical characteristics to enable more refined comparisons across studies. Copyright © 2018 Elsevier B.V. All rights reserved.

Changes in Self-Efficacy and Task Value in Online Learning

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Lee, Cheng-Yuan

2015-01-01

This study was designed to investigate whether course content self-efficacy, online technologies self-efficacy, and task value change over the course of a semester. Sixty-nine participating students from four classes provided data through two instruments: (1) the self-efficacy instrument and (2) the task value instrument. Students' self-efficacy…

Validation of auditory detection response task method for assessing the attentional effects of cognitive load.

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Stojmenova, Kristina; Sodnik, Jaka

2018-07-04

There are 3 standardized versions of the Detection Response Task (DRT), 2 using visual stimuli (remote DRT and head-mounted DRT) and one using tactile stimuli. In this article, we present a study that proposes and validates a type of auditory signal to be used as DRT stimulus and evaluate the proposed auditory version of this method by comparing it with the standardized visual and tactile version. This was a within-subject design study performed in a driving simulator with 24 participants. Each participant performed 8 2-min-long driving sessions in which they had to perform 3 different tasks: driving, answering to DRT stimuli, and performing a cognitive task (n-back task). Presence of additional cognitive load and type of DRT stimuli were defined as independent variables. DRT response times and hit rates, n-back task performance, and pupil size were observed as dependent variables. Significant changes in pupil size for trials with a cognitive task compared to trials without showed that cognitive load was induced properly. Each DRT version showed a significant increase in response times and a decrease in hit rates for trials with a secondary cognitive task compared to trials without. Similar and significantly better results in differences in response times and hit rates were obtained for the auditory and tactile version compared to the visual version. There were no significant differences in performance rate between the trials without DRT stimuli compared to trials with and among the trials with different DRT stimuli modalities. The results from this study show that the auditory DRT version, using the signal implementation suggested in this article, is sensitive to the effects of cognitive load on driver's attention and is significantly better than the remote visual and tactile version for auditory-vocal cognitive (n-back) secondary tasks.

Quantifying Human Performance of a Dynamic Military Target Detection Task: An Application of the Theory of Signal Detection.

Science.gov (United States)

1995-06-01

applied to analyze numerous experimental tasks (Macmillan and Creelman , 1991). One of these tasks, target detection, is the subject research. In...between each associated pair of false alarm rate and hit rate z-scores is d’ for the bias level associated with the pairing (Macmillan and Creelman , 1991...unequal variance in normal distributions (Macmillan and Creelman , 1991). 61 1966). It is described in detail for the interested reader by Green and

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

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Kuo, Chiao-Ling; Hong, Jung-Hong

2016-01-01

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

TMTI Task 1.6 Genetic Engineering Methods and Detection

Energy Technology Data Exchange (ETDEWEB)

Slezak, T; Lenhoff, R; Allen, J; Borucki, M; Vitalis, E; Gardner, S

2009-12-04

A large number of GE techniques can be adapted from other microorganisms to biothreat bacteria and viruses. Detection of GE in a microorganism increases in difficulty as the size of the genetic change decreases. In addition to the size of the engineered change, the consensus genomic sequence of the microorganism can impact the difficulty of detecting an engineered change in genomes that are highly variable from strain to strain. This problem will require comprehensive databases of whole genome sequences for more genetically variable biothreat bacteria and viruses. Preliminary work with microarrays for detecting synthetic elements or virulence genes and analytic bioinformatic approaches for whole genome sequence comparison to detect genetic engineering show promise for attacking this difficult problem but a large amount of future work remains.

Reconciling change blindness with long-term memory for objects.

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Wood, Katherine; Simons, Daniel J

2017-02-01

How can we reconcile remarkably precise long-term memory for thousands of images with failures to detect changes to similar images? We explored whether people can use detailed, long-term memory to improve change detection performance. Subjects studied a set of images of objects and then performed recognition and change detection tasks with those images. Recognition memory performance exceeded change detection performance, even when a single familiar object in the postchange display consistently indicated the change location. In fact, participants were no better when a familiar object predicted the change location than when the displays consisted of unfamiliar objects. When given an explicit strategy to search for a familiar object as a way to improve performance on the change detection task, they performed no better than in a 6-alternative recognition memory task. Subjects only benefited from the presence of familiar objects in the change detection task when they had more time to view the prechange array before it switched. Once the cost to using the change detection information decreased, subjects made use of it in conjunction with memory to boost performance on the familiar-item change detection task. This suggests that even useful information will go unused if it is sufficiently difficult to extract.

Use of Task-Value Instructional Inductions for Facilitating Engagement and Conceptual Change

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Johnson, Marcus Lee; Sinatra, Gale M.

2013-01-01

This study explored the relationship between task values, engagement, and conceptual change. One hundred and sixty-six under graduate students were randomly assigned to one of three task value instructional inductions (utility, attainment, and control) to determine whether induced task values would result in different degrees of engagement and…

Imaging, object detection, and change detection with a polarized multistatic GPR array

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Beer, N. Reginald; Paglieroni, David W.

2015-07-21

A polarized detection system performs imaging, object detection, and change detection factoring in the orientation of an object relative to the orientation of transceivers. The polarized detection system may operate on one of several modes of operation based on whether the imaging, object detection, or change detection is performed separately for each transceiver orientation. In combined change mode, the polarized detection system performs imaging, object detection, and change detection separately for each transceiver orientation, and then combines changes across polarizations. In combined object mode, the polarized detection system performs imaging and object detection separately for each transceiver orientation, and then combines objects across polarizations and performs change detection on the result. In combined image mode, the polarized detection system performs imaging separately for each transceiver orientation, and then combines images across polarizations and performs object detection followed by change detection on the result.

Developmental changes in children's abilities to share and allocate attention in a dual task.

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Irwin-Chase, H; Burns, B

2000-09-01

Characterizing developmental changes in children's dual-task performance has been problematic because differences in divided attention abilities are easily confounded with differences in overall capacity. Two experiments showed that after individual differences in children's capacity for single-task performance were controlled for, age differences between second- (M = 8.1 years) and fifth-grade (M = 11.1 years) children did not exist in dual-task performance when tasks were of equal priority. However, when tasks had different priorities, only fifth-grade children could differentially allocate attention in the dual task. Results are discussed within the coordination hypothesis framework (see A. F. Kramer & J. L. Larish, 1996), which suggests that changes in dual-task performance with aging are due to changes in the ability to coordinate and control the allocation of attention. It is argued that linking the investigations of children's attention with research on attention and aging provides both methodological and theoretical benefits. Copyright 2000 Academic Press.

Expectations impact short-term memory through changes in connectivity between attention- and task-related brain regions.

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Sinke, Christopher; Forkmann, Katarina; Schmidt, Katharina; Wiech, Katja; Bingel, Ulrike

2016-05-01

Over the recent years, neuroimaging studies have investigated the neural mechanisms underlying the influence of expectations on perception. However, it seems equally reasonable to assume that expectations impact cognitive functions. Here we used fMRI to explore the role of expectations on task performance and its underlying neural mechanisms. 43 healthy participants were randomly assigned to two groups. Using verbal instructions, group 1 was led to believe that pain enhances task performance while group 2 was instructed that pain hampers their performance. All participants performed a Rapid-Serial-Visual-Presentation (RSVP) Task (target detection and short-term memory component) with or without concomitant painful heat stimulation during 3T fMRI scanning. As hypothesized, short-term memory performance showed an interaction between painful stimulation and expectation. Positive expectations induced stronger neural activation in the right inferior parietal cortex (IPC) during painful stimulation than negative expectation. Moreover, IPC displayed differential functional coupling with the left inferior occipital cortex under pain as a function of expectancy. Our data show that an individual's expectation can influence cognitive performance in a visual short-term memory task which is associated with activity and connectivity changes in brain areas implicated in attentional processing and task performance. Copyright © 2016. Published by Elsevier Ltd.

SuBSENSE: a universal change detection method with local adaptive sensitivity.

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St-Charles, Pierre-Luc; Bilodeau, Guillaume-Alexandre; Bergevin, Robert

2015-01-01

Foreground/background segmentation via change detection in video sequences is often used as a stepping stone in high-level analytics and applications. Despite the wide variety of methods that have been proposed for this problem, none has been able to fully address the complex nature of dynamic scenes in real surveillance tasks. In this paper, we present a universal pixel-level segmentation method that relies on spatiotemporal binary features as well as color information to detect changes. This allows camouflaged foreground objects to be detected more easily while most illumination variations are ignored. Besides, instead of using manually set, frame-wide constants to dictate model sensitivity and adaptation speed, we use pixel-level feedback loops to dynamically adjust our method's internal parameters without user intervention. These adjustments are based on the continuous monitoring of model fidelity and local segmentation noise levels. This new approach enables us to outperform all 32 previously tested state-of-the-art methods on the 2012 and 2014 versions of the ChangeDetection.net dataset in terms of overall F-Measure. The use of local binary image descriptors for pixel-level modeling also facilitates high-speed parallel implementations: our own version, which used no low-level or architecture-specific instruction, reached real-time processing speed on a midlevel desktop CPU. A complete C++ implementation based on OpenCV is available online.

CHANGE@CERN:Task Force 4: Matching personnel to activities

CERN Multimedia

2002-01-01

Our series on the work of the Task Forces moves on to Human Ressources at CERN. Staff mobility and topics related to contract policy were the main personnel issues to be considered by Task Force 4, led by John Ferguson, head of AS Division. The aim, as with the other Task Forces, was to find ways to focus resources on the LHC, and once again the recommendations recognise the opportunity to make constructive changes, in this case in Human Resources policy at CERN. Movement of staff between divisions at CERN has generally not been easy, with 'staff complements' (total numbers) set for each sector (research, accelerator, technical and administration). However, the restructuring of the accelerator sector (proposed by Task Force 5 and already agreed in principle) should allow some staff to move to LHC activities. More generally, Task Force 4 recommends that the Laboratory carries out a review of all activities, at a relatively detailed level, so as to identify the resources required to achieve specific goals (t...

Brain Activations for Vestibular Stimulation and Dual Tasking Change with Spaceflight

Science.gov (United States)

Yuan, Peng; Koppelmans, Vincent; Reuter-Lorenz, Patricia; De Dios, Yiri; Gadd, Nichole; Wood, Scott; Riascos, Roy; Kofman, Igor; Bloomberg, Jacob; Mulavara, Ajitkumar;

Adaptive filtering and change detection

CERN Document Server

Gustafsson, Fredrik

2003-01-01

Adaptive filtering is a classical branch of digital signal processing (DSP). Industrial interest in adaptive filtering grows continuously with the increase in computer performance that allows ever more conplex algorithms to be run in real-time. Change detection is a type of adaptive filtering for non-stationary signals and is also the basic tool in fault detection and diagnosis. Often considered as separate subjects Adaptive Filtering and Change Detection bridges a gap in the literature with a unified treatment of these areas, emphasizing that change detection is a natural extensi

Automatic Change Detection to Facial Expressions in Adolescents: Evidence from Visual Mismatch Negativity Responses

Directory of Open Access Journals (Sweden)

Tongran eLiu

2016-03-01

Full Text Available Adolescence is a critical period for the neurodevelopment of social-emotional processing, wherein the automatic detection of changes in facial expressions is crucial for the development of interpersonal communication. Two groups of participants (an adolescent group and an adult group were recruited to complete an emotional oddball task featuring on happy and one fearful condition. The measurement of event-related potential (ERP was carried out via electroencephalography (EEG and electrooculography (EOG recording, to detect visual mismatch negativity (vMMN with regard to the automatic detection of changes in facial expressions between the two age groups. The current findings demonstrated that the adolescent group featured more negative vMMN amplitudes than the adult group in the fronto-central region during the 120-200 ms interval. During the time window of 370-450 ms, only the adult group showed better automatic processing on fearful faces than happy faces. The present study indicated that adolescents posses stronger automatic detection of changes in emotional expression relative to adults, and sheds light on the neurodevelopment of automatic processes concerning social-emotional information.

Neural Bases of Unconscious Error Detection in a Chinese Anagram Solution Task: Evidence from ERP Study.

Directory of Open Access Journals (Sweden)

Hua-Zhan Yin

Full Text Available In everyday life, error monitoring and processing are important for improving ongoing performance in response to a changing environment. However, detecting an error is not always a conscious process. The temporal activation patterns of brain areas related to cognitive control in the absence of conscious awareness of an error remain unknown. In the present study, event-related potentials (ERPs in the brain were used to explore the neural bases of unconscious error detection when subjects solved a Chinese anagram task. Our ERP data showed that the unconscious error detection (UED response elicited a more negative ERP component (N2 than did no error (NE and detect error (DE responses in the 300-400-ms time window, and the DE elicited a greater late positive component (LPC than did the UED and NE in the 900-1200-ms time window after the onset of the anagram stimuli. Taken together with the results of dipole source analysis, the N2 (anterior cingulate cortex might reflect unconscious/automatic conflict monitoring, and the LPC (superior/medial frontal gyrus might reflect conscious error recognition.

Automatic detection of adverse events to predict drug label changes using text and data mining techniques.

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Gurulingappa, Harsha; Toldo, Luca; Rajput, Abdul Mateen; Kors, Jan A; Taweel, Adel; Tayrouz, Yorki

2013-11-01

The aim of this study was to assess the impact of automatically detected adverse event signals from text and open-source data on the prediction of drug label changes. Open-source adverse effect data were collected from FAERS, Yellow Cards and SIDER databases. A shallow linguistic relation extraction system (JSRE) was applied for extraction of adverse effects from MEDLINE case reports. Statistical approach was applied on the extracted datasets for signal detection and subsequent prediction of label changes issued for 29 drugs by the UK Regulatory Authority in 2009. 76% of drug label changes were automatically predicted. Out of these, 6% of drug label changes were detected only by text mining. JSRE enabled precise identification of four adverse drug events from MEDLINE that were undetectable otherwise. Changes in drug labels can be predicted automatically using data and text mining techniques. Text mining technology is mature and well-placed to support the pharmacovigilance tasks. Copyright © 2013 John Wiley & Sons, Ltd.

Social Network Change Detection

National Research Council Canada - National Science Library

McCulloh, Ian A; Carley, Kathleen M

2008-01-01

... between group members. The ability to systematically, statistically, effectively and efficiently detect these changes has the potential to enable the anticipation of change, provide early warning of change, and enable...

Perseveration effects in detection tasks with correlated decision intervals. [applied to pilot collision avoidance

Science.gov (United States)

Gai, E. G.; Curry, R. E.

1978-01-01

An investigation of the behavior of the human decisionmaker is described for a task related to the problem of a pilot using a traffic situation display to avoid collisions. This sequential signal detection task is characterized by highly correlated signals with time varying strength. Experimental results are presented and the behavior of the observers is analyzed using the theory of Markov processes and classical signal detection theory. Mathematical models are developed which describe the main result of the experiment: that correlation in sequential signals induced perseveration in the observer response and a strong tendency to repeat their previous decision, even when they were wrong.

Changes in Standing and Walking Performance Under Dual-Task Conditions Across the Lifespan.

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Ruffieux, Jan; Keller, Martin; Lauber, Benedikt; Taube, Wolfgang

2015-12-01

Simultaneous performance of a postural and a concurrent task is rather unproblematic as long as the postural task is executed in an automatic way. However, in situations where postural control requires more central processing, cognitive resources may be exceeded by the addition of an attentionally demanding task. This may lead to interference between the two tasks, manifested in a decreased performance in one or both tasks (dual-task costs). Owing to changes in attentional demands of postural tasks as well as processing capacities across the lifespan, it might be assumed that dual-task costs are particularly pronounced in children and older adults probably leading to a U-shaped pattern for dual-task costs as a function of age. However, these changes in the ability of dual-tasking posture from childhood to old age have not yet been systematically reviewed. Therefore, Web of Science and PubMed databases were searched for studies comparing dual-task performance with one task being standing or walking in healthy groups of young adults and either children or older adults. Seventy-nine studies met inclusion criteria. For older adults, the expected increase in dual-task costs could be confirmed. In contrast, in children there was only feeble evidence for a trend towards enlarged dual-task costs. More good-quality studies comparing dual-task ability in children, young, and, ideally, also older adults within the same paradigm are needed to draw unambiguous conclusions about lifespan development of dual-task performance in postural tasks. There is evidence that, in older adults, dual-task performance can be improved by training. For the other age groups, these effects have yet to be investigated.

Dependency of human target detection performance on clutter and quality of supporting image analysis algorithms in a video surveillance task

Science.gov (United States)

Huber, Samuel; Dunau, Patrick; Wellig, Peter; Stein, Karin

2017-10-01

Background: In target detection, the success rates depend strongly on human observer performances. Two prior studies tested the contributions of target detection algorithms and prior training sessions. The aim of this Swiss-German cooperation study was to evaluate the dependency of human observer performance on the quality of supporting image analysis algorithms. Methods: The participants were presented 15 different video sequences. Their task was to detect all targets in the shortest possible time. Each video sequence showed a heavily cluttered simulated public area from a different viewing angle. In each video sequence, the number of avatars in the area was altered to 100, 150 and 200 subjects. The number of targets appearing was kept at 10%. The number of marked targets varied from 0, 5, 10, 20 up to 40 marked subjects while keeping the positive predictive value of the detection algorithm at 20%. During the task, workload level was assessed by applying an acoustic secondary task. Detection rates and detection times for the targets were analyzed using inferential statistics. Results: The study found Target Detection Time to increase and Target Detection Rates to decrease with increasing numbers of avatars. The same is true for the Secondary Task Reaction Time while there was no effect on Secondary Task Hit Rate. Furthermore, we found a trend for a u-shaped correlation between the numbers of markings and RTST indicating increased workload. Conclusion: The trial results may indicate useful criteria for the design of training and support of observers in observational tasks.

Functional neuroimaging of visuospatial working memory tasks enables accurate detection of attention deficit and hyperactivity disorder

Directory of Open Access Journals (Sweden)

Rubi Hammer

2015-01-01

Full Text Available Finding neurobiological markers for neurodevelopmental disorders, such as attention deficit and hyperactivity disorder (ADHD, is a major objective of clinicians and neuroscientists. We examined if functional Magnetic Resonance Imaging (fMRI data from a few distinct visuospatial working memory (VSWM tasks enables accurately detecting cases with ADHD. We tested 20 boys with ADHD combined type and 20 typically developed (TD boys in four VSWM tasks that differed in feedback availability (feedback, no-feedback and reward size (large, small. We used a multimodal analysis based on brain activity in 16 regions of interest, significantly activated or deactivated in the four VSWM tasks (based on the entire participants' sample. Dimensionality of the data was reduced into 10 principal components that were used as the input variables to a logistic regression classifier. fMRI data from the four VSWM tasks enabled a classification accuracy of 92.5%, with high predicted ADHD probability values for most clinical cases, and low predicted ADHD probabilities for most TDs. This accuracy level was higher than those achieved by using the fMRI data of any single task, or the respective behavioral data. This indicates that task-based fMRI data acquired while participants perform a few distinct VSWM tasks enables improved detection of clinical cases.

Collimator optimization in myocardial perfusion SPECT using the ideal observer and realistic background variability for lesion detection and joint detection and localization tasks

Science.gov (United States)

Ghaly, Michael; Du, Yong; Links, Jonathan M.; Frey, Eric C.

2016-03-01

In SPECT imaging, collimators are a major factor limiting image quality and largely determine the noise and resolution of SPECT images. In this paper, we seek the collimator with the optimal tradeoff between image noise and resolution with respect to performance on two tasks related to myocardial perfusion SPECT: perfusion defect detection and joint detection and localization. We used the Ideal Observer (IO) operating on realistic background-known-statistically (BKS) and signal-known-exactly (SKE) data. The areas under the receiver operating characteristic (ROC) and localization ROC (LROC) curves (AUCd, AUCd+l), respectively, were used as the figures of merit for both tasks. We used a previously developed population of 54 phantoms based on the eXtended Cardiac Torso Phantom (XCAT) that included variations in gender, body size, heart size and subcutaneous adipose tissue level. For each phantom, organ uptakes were varied randomly based on distributions observed in patient data. We simulated perfusion defects at six different locations with extents and severities of 10% and 25%, respectively, which represented challenging but clinically relevant defects. The extent and severity are, respectively, the perfusion defect’s fraction of the myocardial volume and reduction of uptake relative to the normal myocardium. Projection data were generated using an analytical projector that modeled attenuation, scatter, and collimator-detector response effects, a 9% energy resolution at 140 keV, and a 4 mm full-width at half maximum (FWHM) intrinsic spatial resolution. We investigated a family of eight parallel-hole collimators that spanned a large range of sensitivity-resolution tradeoffs. For each collimator and defect location, the IO test statistics were computed using a Markov Chain Monte Carlo (MCMC) method for an ensemble of 540 pairs of defect-present and -absent images that included the aforementioned anatomical and uptake variability. Sets of test statistics were

Identification of Swallowing Tasks from a Modified Barium Swallow Study That Optimize the Detection of Physiological Impairment

Science.gov (United States)

Hazelwood, R. Jordan; Armeson, Kent E.; Hill, Elizabeth G.; Bonilha, Heather Shaw; Martin-Harris, Bonnie

2017-01-01

Purpose: The purpose of this study was to identify which swallowing task(s) yielded the worst performance during a standardized modified barium swallow study (MBSS) in order to optimize the detection of swallowing impairment. Method: This secondary data analysis of adult MBSSs estimated the probability of each swallowing task yielding the derived…

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

Science.gov (United States)

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.

Task-based detectability in CT image reconstruction by filtered backprojection and penalized likelihood estimation

Energy Technology Data Exchange (ETDEWEB)

Gang, Grace J. [Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, Ontario M5G 2M9, Canada and Department of Biomedical Engineering, Johns Hopkins University, Baltimore Maryland 21205 (Canada); Stayman, J. Webster; Zbijewski, Wojciech [Department of Biomedical Engineering, Johns Hopkins University, Baltimore Maryland 21205 (United States); Siewerdsen, Jeffrey H., E-mail: jeff.siewerdsen@jhu.edu [Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, Ontario M5G 2M9, Canada and Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland 21205 (United States)

2014-08-15

Purpose: Nonstationarity is an important aspect of imaging performance in CT and cone-beam CT (CBCT), especially for systems employing iterative reconstruction. This work presents a theoretical framework for both filtered-backprojection (FBP) and penalized-likelihood (PL) reconstruction that includes explicit descriptions of nonstationary noise, spatial resolution, and task-based detectability index. Potential utility of the model was demonstrated in the optimal selection of regularization parameters in PL reconstruction. Methods: Analytical models for local modulation transfer function (MTF) and noise-power spectrum (NPS) were investigated for both FBP and PL reconstruction, including explicit dependence on the object and spatial location. For FBP, a cascaded systems analysis framework was adapted to account for nonstationarity by separately calculating fluence and system gains for each ray passing through any given voxel. For PL, the point-spread function and covariance were derived using the implicit function theorem and first-order Taylor expansion according toFessler [“Mean and variance of implicitly defined biased estimators (such as penalized maximum likelihood): Applications to tomography,” IEEE Trans. Image Process. 5(3), 493–506 (1996)]. Detectability index was calculated for a variety of simple tasks. The model for PL was used in selecting the regularization strength parameter to optimize task-based performance, with both a constant and a spatially varying regularization map. Results: Theoretical models of FBP and PL were validated in 2D simulated fan-beam data and found to yield accurate predictions of local MTF and NPS as a function of the object and the spatial location. The NPS for both FBP and PL exhibit similar anisotropic nature depending on the pathlength (and therefore, the object and spatial location within the object) traversed by each ray, with the PL NPS experiencing greater smoothing along directions with higher noise. The MTF of FBP

Explicit behavioral detection of visual changes develops without their implicit neurophysiological detectability

Directory of Open Access Journals (Sweden)

Pessi eLyyra

2012-03-01

Full Text Available Change blindness is a failure of explicitly detecting changes between consecutively presented images when separated, e.g., by a brief blank screen. There is a growing body of evidence of implicit detection of even explicitly undetectable changes, pointing to the possibility of the implicit change detection as a prerequisite for its explicit counterpart. We recorded event-related potentials (ERPs of the electroencephalography in adults during an oddball-variant of change blindness flicker paradigm. In this variant, rare pictures with a change were interspersed with frequent pictures with no change. In separate stimulus blocks, the blank screen between the change and no-change picture was either of 100 ms or 500 ms in duration. In both stimulus conditions the participants eventually explicitly detect the changed pictures, the blank screen of the longer duration only requiring in average 10 % longer exposure to the picture series until the ability emerged. However, during the change blindness, ERPs were displaced towards negative polarity at 200–260 ms after the stimulus onset (visual mismatch negativity only with the blank screens of the shorter ISI. Our finding of ‘implicit change blindness’ for pictorial material that, nevertheless, successfully prepares the visual system for explicit change detection suggests that implicit change detection may not be a necessary condition for explicit change detection and that they may recruit at least partially distinct memory mechanisms.

Quench detection system of the EURATOM coil for the Large Coil Task

International Nuclear Information System (INIS)

Noether, G.; Gauss, S.; Maurer, W.; Siewerdt, L.; Ulbricht, A.; Wuechner, F.

1989-01-01

A special quench detection system has been developed for the EURATOM Large Coil Task (LCT) coil. The system is based on a bridge circuit which uses a special 'two in hand' winding technique for the pancakes of the EURATOM LCT coil. The electronic circuit was designed in a fail safe way to prevent failure of the quench detector due to failure of one of its components. A method for quick balancing of the quench detection system in a large toroidal magnet system was applied. The quench detection system worked very reliably during the experimental phase of the LCT and was within the quench detection level setting of 50 mV, i.e. the system was not sensitive to poloidal field transients at or below this level. Non-electrical methods for quench detection were also investigated. (author)

Complementary roles of systems representing sensory evidence and systems detecting task difficulty during perceptual decision making

Directory of Open Access Journals (Sweden)

Douglas A Ruff

2010-11-01

Full Text Available Perceptual decision making is a multi-stage process where incoming sensory information is used to select one option from several alternatives. Researchers typically have adopted one of two conceptual frameworks to define the criteria for determining whether a brain region is involved in decision computations. One framework, building on single unite recordings in monkeys, posits that activity in a region involved in decision making reflects the accumulation of evidence toward a decision threshold, thus showing the lowest level of BOLD signal during the hardest decisions. The other framework instead posits that activity in a decision-making region reflects the difficulty of a decision, thus showing the highest level of BOLD signal during the hardest decisions. We had subjects perform a face detection task on degraded face images while we simultaneously recorded BOLD activity. We searched for brain regions where changes in BOLD activity during this task supported either of these frameworks by calculating the correlation of BOLD activity with reaction time - a measure of task difficulty. We found that the right supplementary eye field, right frontal eye field and right inferior frontal gyrus had increased activity relative to baseline that positively correlated with reaction time, while the left superior frontal sulcus and left middle temporal gyrus had decreased activity relative to baseline that negatively correlated with reaction time. We propose that a simple mechanism that scales a region’s activity based on task demands can explain our results.

Supervised / unsupervised change detection

OpenAIRE

de Alwis Pitts, Dilkushi; De Vecchi, Daniele; Harb, Mostapha; So, Emily; Dell'Acqua, Fabio

2014-01-01

The aim of this deliverable is to provide an overview of the state of the art in change detection techniques and a critique of what could be programmed to derive SENSUM products. It is the product of the collaboration between UCAM and EUCENTRE. The document includes as a necessary requirement a discussion about a proposed technique for co-registration. Since change detection techniques require an assessment of a series of images and the basic process involves comparing and contrasting the sim...

Detecting change-points in extremes

KAUST Repository

Dupuis, D. J.

2015-01-01

Even though most work on change-point estimation focuses on changes in the mean, changes in the variance or in the tail distribution can lead to more extreme events. In this paper, we develop a new method of detecting and estimating the change-points in the tail of multiple time series data. In addition, we adapt existing tail change-point detection methods to our specific problem and conduct a thorough comparison of different methods in terms of performance on the estimation of change-points and computational time. We also examine three locations on the U.S. northeast coast and demonstrate that the methods are useful for identifying changes in seasonally extreme warm temperatures.

Uncovering beat deafness: detecting rhythm disorders with synchronized finger tapping and perceptual timing tasks.

Science.gov (United States)

Dalla Bella, Simone; Sowiński, Jakub

2015-03-16

A set of behavioral tasks for assessing perceptual and sensorimotor timing abilities in the general population (i.e., non-musicians) is presented here with the goal of uncovering rhythm disorders, such as beat deafness. Beat deafness is characterized by poor performance in perceiving durations in auditory rhythmic patterns or poor synchronization of movement with auditory rhythms (e.g., with musical beats). These tasks include the synchronization of finger tapping to the beat of simple and complex auditory stimuli and the detection of rhythmic irregularities (anisochrony detection task) embedded in the same stimuli. These tests, which are easy to administer, include an assessment of both perceptual and sensorimotor timing abilities under different conditions (e.g., beat rates and types of auditory material) and are based on the same auditory stimuli, ranging from a simple metronome to a complex musical excerpt. The analysis of synchronized tapping data is performed with circular statistics, which provide reliable measures of synchronization accuracy (e.g., the difference between the timing of the taps and the timing of the pacing stimuli) and consistency. Circular statistics on tapping data are particularly well-suited for detecting individual differences in the general population. Synchronized tapping and anisochrony detection are sensitive measures for identifying profiles of rhythm disorders and have been used with success to uncover cases of poor synchronization with spared perceptual timing. This systematic assessment of perceptual and sensorimotor timing can be extended to populations of patients with brain damage, neurodegenerative diseases (e.g., Parkinson's disease), and developmental disorders (e.g., Attention Deficit Hyperactivity Disorder).

Improving Sensitivity to Detect Mild Cognitive Impairment: Cognitive Load Dual-Task Gait Speed Assessment.

Science.gov (United States)

MacAulay, Rebecca K; Wagner, Mark T; Szeles, Dana; Milano, Nicholas J

2017-07-01

Longitudinal research indicates that cognitive load dual-task gait assessment is predictive of cognitive decline and thus might provide a sensitive measure to screen for mild cognitive impairment (MCI). However, research among older adults being clinically evaluated for cognitive concerns, a defining feature of MCI, is lacking. The present study investigated the effect of performing a cognitive task on normal walking speed in patients presenting to a memory clinic with cognitive complaints. Sixty-one patients with a mean age of 68 years underwent comprehensive neuropsychological testing, clinical interview, and gait speed (simple- and dual-task conditions) assessments. Thirty-four of the 61 patients met criteria for MCI. Repeated measure analyses of covariance revealed that greater age and MCI both significantly associated with slower gait speed, pscognitive dual task within a clinically representative population. Cognitive load dual-task gait assessment may provide a cost efficient and sensitive measure to detect older adults at high risk of a dementia disorder. (JINS, 2017, 23, 493-501).

On Radar Resolution in Coherent Change Detection.

Energy Technology Data Exchange (ETDEWEB)

Bickel, Douglas L. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2015-11-01

It is commonly observed that resolution plays a role in coherent change detection. Although this is the case, the relationship of the resolution in coherent change detection is not yet defined . In this document, we present an analytical method of evaluating this relationship using detection theory. Specifically we examine the effect of resolution on receiver operating characteristic curves for coherent change detection.

A Hybrid Change Detection Approach for Damage Detection and Recovery Monitoring

Science.gov (United States)

de Alwis Pitts, Dilkushi; Wieland, Marc; Wang, Shifeng; So, Emily; Pittore, Massimiliano

2014-05-01

Following a disaster, change detection via pre- and post-event very high resolution remote sensing images is an essential technique for damage assessment and recovery monitoring over large areas in complex urban environments. Most assessments to date focus on detection, destruction and recovery of man-made objects that facilitate shelter and accessibility, such as buildings, roads, bridges, etc., as indicators for assessment and better decision making. Moreover, many current change-detection mechanisms do not use all the data and knowledge which are often available for the pre-disaster state. Recognizing the continuous rather than dichotomous character of the data-rich/data-poor distinction permits the incorporation of ancillary data and existing knowledge into the processing flow. Such incorporation could improve the reliability of the results and thereby enhance the usability of robust methods for disaster management. This study proposes an application-specific and robust change detection method from multi-temporal very high resolution multi-spectral satellite images. This hybrid indicator-specific method uses readily available pre-disaster GIS data and integrates existing knowledge into the processing flow to optimize the change detection while offering the possibility to target specific types of changes to man-made objects. The indicator-specific information of the GIS objects is used as a series of masks to treat the GIS objects with similar characteristics similarly for better accuracy. The proposed approach is based on a fusion of a multi-index change detection method based on gradient, texture and edge similarity filters. The change detection index is flexible for disaster cases in which the pre-disaster and post-disaster images are not of the same resolution. The proposed automated method is evaluated with QuickBird and Ikonos datasets for abrupt changes soon after disaster. The method could also be extended in a semi-automated way for monitoring

CHANGE@CERN:Task Force 3: adjusting services to future needs

CERN Document Server

2002-01-01

We continue our articles on the Task Force reports The number of craftsmen and technicians could be increased with a change in the staff composition. The mandate for Task Force 3 was to make proposals for savings and new cost control procedures in the area of Industrial Support and Contracts for the period until 2009. The aim, explains the convenor, Karl-Heinz Kissler, was to keep spending under control under difficult conditions when staff numbers are decreasing and the work for the LHC becomes more demanding. The measures proposed, if implemented, could lead to savings of around 170 MCHF. The proposals involve both Industrial Services contracts, which were discussed in the Bulletin of the 22nd of April (n°17/2002) and readjustments for staff at CERN, on which we concentrate here. As with other Task Forces the principle aim was to be able to refocus resources onto the LHC project. In this respect, Task Force 3 could work within the framework of the revised programme for the LHC and the reduced non-LHC pro...

Detecting change-points in extremes

KAUST Repository

Dupuis, D. J.; Sun, Ying; Wang, Huixia Judy

2015-01-01

Even though most work on change-point estimation focuses on changes in the mean, changes in the variance or in the tail distribution can lead to more extreme events. In this paper, we develop a new method of detecting and estimating the change

A dual-process account of auditory change detection.

Science.gov (United States)

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

2010-08-01

Listeners can be "deaf" to a substantial change in a scene comprising multiple auditory objects unless their attention has been directed to the changed object. It is unclear whether auditory change detection relies on identification of the objects in pre- and post-change scenes. We compared the rates at which listeners correctly identify changed objects with those predicted by change-detection models based on signal detection theory (SDT) and high-threshold theory (HTT). Detected changes were not identified as accurately as predicted by models based on either theory, suggesting that some changes are detected by a process that does not support change identification. Undetected changes were identified as accurately as predicted by the HTT model but much less accurately than predicted by the SDT models. The process underlying change detection was investigated further by determining receiver-operating characteristics (ROCs). ROCs did not conform to those predicted by either a SDT or a HTT model but were well modeled by a dual-process that incorporated HTT and SDT components. The dual-process model also accurately predicted the rates at which detected and undetected changes were correctly identified.

Attribute and topology based change detection in a constellation of previously detected objects

Science.gov (United States)

Paglieroni, David W.; Beer, Reginald N.

2016-01-19

A system that applies attribute and topology based change detection to networks of objects that were detected on previous scans of a structure, roadway, or area of interest. The attributes capture properties or characteristics of the previously detected objects, such as location, time of detection, size, elongation, orientation, etc. The topology of the network of previously detected objects is maintained in a constellation database that stores attributes of previously detected objects and implicitly captures the geometrical structure of the network. A change detection system detects change by comparing the attributes and topology of new objects detected on the latest scan to the constellation database of previously detected objects.

Channelized relevance vector machine as a numerical observer for cardiac perfusion defect detection task

Science.gov (United States)

Kalayeh, Mahdi M.; Marin, Thibault; Pretorius, P. Hendrik; Wernick, Miles N.; Yang, Yongyi; Brankov, Jovan G.

2011-03-01

In this paper, we present a numerical observer for image quality assessment, aiming to predict human observer accuracy in a cardiac perfusion defect detection task for single-photon emission computed tomography (SPECT). In medical imaging, image quality should be assessed by evaluating the human observer accuracy for a specific diagnostic task. This approach is known as task-based assessment. Such evaluations are important for optimizing and testing imaging devices and algorithms. Unfortunately, human observer studies with expert readers are costly and time-demanding. To address this problem, numerical observers have been developed as a surrogate for human readers to predict human diagnostic performance. The channelized Hotelling observer (CHO) with internal noise model has been found to predict human performance well in some situations, but does not always generalize well to unseen data. We have argued in the past that finding a model to predict human observers could be viewed as a machine learning problem. Following this approach, in this paper we propose a channelized relevance vector machine (CRVM) to predict human diagnostic scores in a detection task. We have previously used channelized support vector machines (CSVM) to predict human scores and have shown that this approach offers better and more robust predictions than the classical CHO method. The comparison of the proposed CRVM with our previously introduced CSVM method suggests that CRVM can achieve similar generalization accuracy, while dramatically reducing model complexity and computation time.

Measuring attention in rodents: comparison of a modified signal detection task and the 5-choice serial reaction time task

Directory of Open Access Journals (Sweden)

Karly Maree Turner

2016-01-01

Full Text Available Neuropsychiatric research has utilised cognitive testing in rodents to improve our understanding of cognitive deficits and for preclinical drug development. However, more sophisticated cognitive tasks have not been as widely exploited due to low throughput and the extensive training time required. We developed a modified signal detection task (SDT based on the growing body of literature aimed at improving cognitive testing in rodents. This study directly compares performance on the modified SDT with the traditional test for measuring attention, the 5-choice serial reaction time task (5CSRTT. Adult male Sprague-Dawley rats were trained on either the 5CSRTT or the SDT. Briefly, the 5CSRTT required rodents to pay attention to a spatial array of 5 apertures and respond with a nose poke when an aperture was illuminated. The SDT required the rat to attend to a light panel and respond either left or right to indicate the presence of a signal. In addition, modifications were made to the reward delivery, timing, control of body positioning and the self-initiation of trials. It was found that less training time was required for the SDT, with both sessions to criteria and daily session duration significantly reduced. Rats performed with a high level of accuracy (>87% on both tasks, however omissions were far more frequent on the 5CSRTT. The signal duration was reduced on both tasks as a manipulation of task difficulty relevant to attention and a similar pattern of decreasing accuracy was observed on both tasks. These results demonstrate some of the advantages of the SDT over the traditional 5CSRTT as being higher throughput with reduced training time, fewer omission responses and their body position at stimulus onset was controlled. In addition, rats performing the SDT had comparable high levels of accuracy. These results highlight the differences and similarities between the 5CSRTT and a modified SDT as tools for assessing attention in preclinical animal

Adaptively detecting changes in Autonomic Grid Computing

KAUST Repository

Zhang, Xiangliang

2010-10-01

Detecting the changes is the common issue in many application fields due to the non-stationary distribution of the applicative data, e.g., sensor network signals, web logs and gridrunning logs. Toward Autonomic Grid Computing, adaptively detecting the changes in a grid system can help to alarm the anomalies, clean the noises, and report the new patterns. In this paper, we proposed an approach of self-adaptive change detection based on the Page-Hinkley statistic test. It handles the non-stationary distribution without the assumption of data distribution and the empirical setting of parameters. We validate the approach on the EGEE streaming jobs, and report its better performance on achieving higher accuracy comparing to the other change detection methods. Meanwhile this change detection process could help to discover the device fault which was not claimed in the system logs. © 2010 IEEE.

Simulation of a Real-Time Brain Computer Interface for Detecting a Self-Paced Hitting Task.

Science.gov (United States)

Hammad, Sofyan H; Kamavuako, Ernest N; Farina, Dario; Jensen, Winnie

2016-12-01

An invasive brain-computer interface (BCI) is a promising neurorehabilitation device for severely disabled patients. Although some systems have been shown to work well in restricted laboratory settings, their utility must be tested in less controlled, real-time environments. Our objective was to investigate whether a specific motor task could be reliably detected from multiunit intracortical signals from freely moving animals in a simulated, real-time setting. Intracortical signals were first obtained from electrodes placed in the primary motor cortex of four rats that were trained to hit a retractable paddle (defined as a "Hit"). In the simulated real-time setting, the signal-to-noise-ratio was first increased by wavelet denoising. Action potentials were detected, and features were extracted (spike count, mean absolute values, entropy, and combination of these features) within pre-defined time windows (200 ms, 300 ms, and 400 ms) to classify the occurrence of a "Hit." We found higher detection accuracy of a "Hit" (73.1%, 73.4%, and 67.9% for the three window sizes, respectively) when the decision was made based on a combination of features rather than on a single feature. However, the duration of the window length was not statistically significant (p = 0.5). Our results showed the feasibility of detecting a motor task in real time in a less restricted environment compared to environments commonly applied within invasive BCI research, and they showed the feasibility of using information extracted from multiunit recordings, thereby avoiding the time-consuming and complex task of extracting and sorting single units. © 2016 International Neuromodulation Society.

Indigenous people's detection of rapid ecological change.

Science.gov (United States)

Aswani, Shankar; Lauer, Matthew

2014-06-01

When sudden catastrophic events occur, it becomes critical for coastal communities to detect and respond to environmental transformations because failure to do so may undermine overall ecosystem resilience and threaten people's livelihoods. We therefore asked how capable of detecting rapid ecological change following massive environmental disruptions local, indigenous people are. We assessed the direction and periodicity of experimental learning of people in the Western Solomon Islands after a tsunami in 2007. We compared the results of marine science surveys with local ecological knowledge of the benthos across 3 affected villages and 3 periods before and after the tsunami. We sought to determine how people recognize biophysical changes in the environment before and after catastrophic events such as earthquakes and tsunamis and whether people have the ability to detect ecological changes over short time scales or need longer time scales to recognize changes. Indigenous people were able to detect changes in the benthos over time. Detection levels differed between marine science surveys and local ecological knowledge sources over time, but overall patterns of statistically significant detection of change were evident for various habitats. Our findings have implications for marine conservation, coastal management policies, and disaster-relief efforts because when people are able to detect ecological changes, this, in turn, affects how they exploit and manage their marine resources. © 2014 Society for Conservation Biology.

UNEP-IOC-ASPEI global task team on the implications of climate change on coral reefs

Energy Technology Data Exchange (ETDEWEB)

1992-01-01

The first meeting of the Global Task Team on the Implications of Climate Change on Coral Reefs was held to develop an authoritative scientific and technical review of the implications of climate change for coral reefs and their ecologically sustainable use. The Task Team is expected to provide expert advice and guidance in the implementation of the pilot activity on coral reef monitoring as part of the UNEP-IOC-WMO Long-Term Global Monitoring System of coastal and near-shore phenomena related to climate change. This would ensure coordination of various activities aimed at assessing the scale of impacts on natural environments and socio-economic systems particularly in the case of low-lying islands and other areas vulnerable to climate change and sea level rise. The work of the Task Team should ultimately assist the Governments concerned in mitigating the impacts of such changes.

Geospatial Image Stream Processing: Models, techniques, and applications in remote sensing change detection

Science.gov (United States)

Rueda-Velasquez, Carlos Alberto

Detection of changes in environmental phenomena using remotely sensed data is a major requirement in the Earth sciences, especially in natural disaster related scenarios where real-time detection plays a crucial role in the saving of human lives and the preservation of natural resources. Although various approaches formulated to model multidimensional data can in principle be applied to the inherent complexity of remotely sensed geospatial data, there are still challenging peculiarities that demand a precise characterization in the context of change detection, particularly in scenarios of fast changes. In the same vein, geospatial image streams do not fit appropriately in the standard Data Stream Management System (DSMS) approach because these systems mainly deal with tuple-based streams. Recognizing the necessity for a systematic effort to address the above issues, the work presented in this thesis is a concrete step toward the foundation and construction of an integrated Geospatial Image Stream Processing framework, GISP. First, we present a data and metadata model for remotely sensed image streams. We introduce a precise characterization of images and image streams in the context of remotely sensed geospatial data. On this foundation, we define spatially-aware temporal operators with a consistent semantics for change analysis tasks. We address the change detection problem in settings where multiple image stream sources are available, and thus we introduce an architectural design for the processing of geospatial image streams from multiple sources. With the aim of targeting collaborative scientific environments, we construct a realization of our architecture based on Kepler, a robust and widely used scientific workflow management system, as the underlying computational support; and open data and Web interface standards, as a means to facilitate the interoperability of GISP instances with other processing infrastructures and client applications. We demonstrate our

Changes are detected - cameras and video systems are monitoring the plant site, only rarely giving false alarm

International Nuclear Information System (INIS)

Zeissler, H.

1988-01-01

The main purpose of automatic data acquisition and processing for monitoring goals is to relieve the security personnel from monotonous observation tasks. The novel video systems can be programmed to detect moving target alarm signals, or accept alarm-suppressing image changes. This allows an intelligent alarm evaluation for physical protection in industry, differentiating between real and false alarm signals. (orig.) [de

Analysis and detection of climate change

International Nuclear Information System (INIS)

Thejll, P.; Stendel, M.

2001-01-01

The authors first discuss the concepts 'climate' and 'climate change detection', outlining the difficulties of the latter in terms of the properties of the former. In more detail they then discuss the analysis and detection, carried out at the Danish Climate Centre, of anthropogenic climate change and the nonanthropogenic changes regarding anthropogenic climate change the emphasis is on the improvement of global and regional climate models, and the reconstruction of past climates regarding non-anthropogenic changes the authors describe two case studies of potential solar influence on climate. (LN)

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

Science.gov (United States)

Kennedy, R R; Merry, A F

2011-09-01

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

[Developmental changes in reading ability of Japanese elementary school children--analysis of 4 kana reading tasks].

Science.gov (United States)

Kobayashi, Tomoka; Inagaki, Masumi; Gunji, Atsuko; Yatabe, Kiyomi; Kaga, Makiko; Goto, Takaaki; Koike, Toshihide; Wakamiya, Eiji; Koeda, Tatsuya

2010-01-01

Five hundred and twenty-eight Japanese elementary school children aged from 6 (Grade 1) to 12 (Grade 6) were tested for their abilities to read Hiragana characters, words, and short sentences. They were typically developing children whom the classroom teachers judged to have no problems with reading and writing in Japanese. Each child was asked to read four tasks which were written in Hiragana script: single mora reading task, four syllable non-word reading task, four syllable word reading task, and short sentence reading task. The total articulation time for reading and performance in terms of accuracy were measured for each task. Developmental changes in these variables were evaluated. The articulation time was significantly longer for the first graders, and it gradually shortened as they moved through to the upper grades in all tasks. The articulation time reached a plateau in the 4th grade for the four syllable word and short sentence reading tasks, while it did so for the single mora and four syllable non-word reading tasks in the 5th grade. The articulation times for the four syllable word and short sentence reading tasks correlated strongly. There were very few clear errors for all tasks, and the number of such errors significantly changed between the school grades only for the single mora and four syllable word reading tasks. It was noted that more than half of the children read the beginning portion of the word or phrase twice or more, in order to read it accurately, and developmental changes were also seen in this pattern of reading. This study revealed that the combination of these reading tasks may function as a screening test for reading disorders such as developmental dyslexia in children below the age of ten or eleven years old.

Event-related near-infrared spectroscopy detects conflict in the motor cortex in a Stroop task.

Science.gov (United States)

Szűcs, Dénes; Killikelly, Clare; Cutini, Simone

2012-10-05

The Stroop effect is one of the most popular models of conflict processing in neuroscience and psychology. The response conflict theory of the Stroop effect explains decreased performance in the incongruent condition of Stroop tasks by assuming that the task-relevant and the task-irrelevant stimulus features elicit conflicting response tendencies. However, to date, there is not much explicit neural evidence supporting this theory. Here we used functional near-infrared imaging (fNIRS) to examine whether conflict at the level of the motor cortex can be detected in the incongruent relative to the congruent condition of a Stroop task. Response conflict was determined by comparing the activity of the hemisphere ipsilateral to the response hand in the congruent and incongruent conditions. First, results provided explicit hemodynamic evidence supporting the response conflict theory of the Stroop effect: there was greater motor cortex activation in the hemisphere ipsilateral to the response hand in the incongruent than in the congruent condition during the initial stage of the hemodynamic response. Second, as fNIRS is still a relatively novel technology, it is methodologically significant that our data shows that fNIRS is able to detect a brief and transient increase in hemodynamic activity localized to the motor cortex, which in this study is related to subthreshold motor response activation. Copyright © 2012 Elsevier B.V. All rights reserved.

Probabilistic BPRRC: Robust Change Detection against Illumination Changes and Background Movements

Science.gov (United States)

Yokoi, Kentaro

This paper presents Probabilistic Bi-polar Radial Reach Correlation (PrBPRRC), a change detection method that is robust against illumination changes and background movements. Most of the traditional change detection methods are robust against either illumination changes or background movements; BPRRC is one of the illumination-robust change detection methods. We introduce a probabilistic background texture model into BPRRC and add the robustness against background movements including foreground invasions such as moving cars, walking people, swaying trees, and falling snow. We show the superiority of PrBPRRC in the environment with illumination changes and background movements by using three public datasets and one private dataset: ATON Highway data, Karlsruhe traffic sequence data, PETS 2007 data, and Walking-in-a-room data.

Adaptive strategy changes as a function of task demands : a study of car drivers

NARCIS (Netherlands)

Cnossen, Fokie; Meijman, Theo; Rothengatter, Talib

2004-01-01

When drivers perform additional tasks while driving, research shows conflicting results: primary driving performance may deteriorate but adaptive changes such as reducing driving speed have also been noted. We hypothesized that the nature of the secondary task may be important: drivers may give more

Unsupervised Condition Change Detection In Large Diesel Engines

DEFF Research Database (Denmark)

Pontoppidan, Niels Henrik; Larsen, Jan

2003-01-01

This paper presents a new method for unsupervised change detection which combines independent component modeling and probabilistic outlier etection. The method further provides a compact data representation, which is amenable to interpretation, i.e., the detected condition changes can be investig...... be investigated further. The method is successfully applied to unsupervised condition change detection in large diesel engines from acoustical emission sensor signal and compared to more classical techniques based on principal component analysis and Gaussian mixture models.......This paper presents a new method for unsupervised change detection which combines independent component modeling and probabilistic outlier etection. The method further provides a compact data representation, which is amenable to interpretation, i.e., the detected condition changes can...

Comparison of model and human observer performance for detection and discrimination tasks using dual-energy x-ray images

International Nuclear Information System (INIS)

Richard, Samuel; Siewerdsen, Jeffrey H.

2008-01-01

Model observer performance, computed theoretically using cascaded systems analysis (CSA), was compared to the performance of human observers in detection and discrimination tasks. Dual-energy (DE) imaging provided a wide range of acquisition and decomposition parameters for which observer performance could be predicted and measured. This work combined previously derived observer models (e.g., Fisher-Hotelling and non-prewhitening) with CSA modeling of the DE image noise-equivalent quanta (NEQ) and imaging task (e.g., sphere detection, shape discrimination, and texture discrimination) to yield theoretical predictions of detectability index (d ' ) and area under the receiver operating characteristic (A Z ). Theoretical predictions were compared to human observer performance assessed using 9-alternative forced-choice tests to yield measurement of A Z as a function of DE image acquisition parameters (viz., allocation of dose between the low- and high-energy images) and decomposition technique [viz., three DE image decomposition algorithms: standard log subtraction (SLS), simple-smoothing of the high-energy image (SSH), and anti-correlated noise reduction (ACNR)]. Results showed good agreement between theory and measurements over a broad range of imaging conditions. The incorporation of an eye filter and internal noise in the observer models demonstrated improved correspondence with human observer performance. Optimal acquisition and decomposition parameters were shown to depend on the imaging task; for example, ACNR and SSH yielded the greatest performance in the detection of soft-tissue and bony lesions, respectively. This study provides encouraging evidence that Fourier-based modeling of NEQ computed via CSA and imaging task provides a good approximation to human observer performance for simple imaging tasks, helping to bridge the gap between Fourier metrics of detector performance (e.g., NEQ) and human observer performance.

Video change detection for fixed wing UAVs

Science.gov (United States)

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

Functional brain and age-related changes associated with congruency in task switching

Science.gov (United States)

Eich, Teal S.; Parker, David; Liu, Dan; Oh, Hwamee; Razlighi, Qolamreza; Gazes, Yunglin; Habeck, Christian; Stern, Yaakov

2016-01-01

Alternating between completing two simple tasks, as opposed to completing only one task, has been shown to produce costs to performance and changes to neural patterns of activity, effects which are augmented in old age. Cognitive conflict may arise from factors other than switching tasks, however. Sensorimotor congruency (whether stimulus-response mappings are the same or different for the two tasks) has been shown to behaviorally moderate switch costs in older, but not younger adults. In the current study, we used fMRI to investigate the neurobiological mechanisms of response-conflict congruency effects within a task switching paradigm in older (N=75) and younger (N=62) adults. Behaviorally, incongruency moderated age-related differences in switch costs. Neurally, switch costs were associated with greater activation in the dorsal attention network for older relative to younger adults. We also found that older adults recruited an additional set of brain areas in the ventral attention network to a greater extent than did younger adults to resolve congruency-related response-conflict. These results suggest both a network and an age-based dissociation between congruency and switch costs in task switching. PMID:27520472

Feature-Based Change Detection Reveals Inconsistent Individual Differences in Visual Working Memory Capacity.

Science.gov (United States)

Ambrose, Joseph P; Wijeakumar, Sobanawartiny; Buss, Aaron T; Spencer, John P

2016-01-01

Visual working memory (VWM) is a key cognitive system that enables people to hold visual information in mind after a stimulus has been removed and compare past and present to detect changes that have occurred. VWM is severely capacity limited to around 3-4 items, although there are robust individual differences in this limit. Importantly, these individual differences are evident in neural measures of VWM capacity. Here, we capitalized on recent work showing that capacity is lower for more complex stimulus dimension. In particular, we asked whether individual differences in capacity remain consistent if capacity is shifted by a more demanding task, and, further, whether the correspondence between behavioral and neural measures holds across a shift in VWM capacity. Participants completed a change detection (CD) task with simple colors and complex shapes in an fMRI experiment. As expected, capacity was significantly lower for the shape dimension. Moreover, there were robust individual differences in behavioral estimates of VWM capacity across dimensions. Similarly, participants with a stronger BOLD response for color also showed a strong neural response for shape within the lateral occipital cortex, intraparietal sulcus (IPS), and superior IPS. Although there were robust individual differences in the behavioral and neural measures, we found little evidence of systematic brain-behavior correlations across feature dimensions. This suggests that behavioral and neural measures of capacity provide different views onto the processes that underlie VWM and CD. Recent theoretical approaches that attempt to bridge between behavioral and neural measures are well positioned to address these findings in future work.

Task effects on BOLD signal correlates of implicit syntactic processing

Science.gov (United States)

Caplan, David

2010-01-01

BOLD signal was measured in sixteen participants who made timed font change detection judgments in visually presented sentences that varied in syntactic structure and the order of animate and inanimate nouns. Behavioral data indicated that sentences were processed to the level of syntactic structure. BOLD signal increased in visual association areas bilaterally and left supramarginal gyrus in the contrast of sentences with object- and subject-extracted relative clauses without font changes in which the animacy order of the nouns biased against the syntactically determined meaning of the sentence. This result differs from the findings in a non-word detection task (Caplan et al, 2008a), in which the same contrast led to increased BOLD signal in the left inferior frontal gyrus. The difference in areas of activation indicates that the sentences were processed differently in the two tasks. These differences were further explored in an eye tracking study using the materials in the two tasks. Issues pertaining to how parsing and interpretive operations are affected by a task that is being performed, and how this might affect BOLD signal correlates of syntactic contrasts, are discussed. PMID:20671983

Changes in Predictive Task Switching with Age and with Cognitive Load.

Science.gov (United States)

Levy-Tzedek, Shelly

2017-01-01

Predictive control of movement is more efficient than feedback-based control, and is an important skill in everyday life. We tested whether the ability to predictively control movements of the upper arm is affected by age and by cognitive load. A total of 63 participants were tested in two experiments. In both experiments participants were seated, and controlled a cursor on a computer screen by flexing and extending their dominant arm. In Experiment 1, 20 young adults and 20 older adults were asked to continuously change the frequency of their horizontal arm movements, with the goal of inducing an abrupt switch between discrete movements (at low frequencies) and rhythmic movements (at high frequencies). We tested whether that change was performed based on a feed-forward (predictive) or on a feedback (reactive) control. In Experiment 2, 23 young adults performed the same task, while being exposed to a cognitive load half of the time via a serial subtraction task. We found that both aging and cognitive load diminished, on average, the ability of participants to predictively control their movements. Five older adults and one young adult under a cognitive load were not able to perform the switch between rhythmic and discrete movement (or vice versa). In Experiment 1, 40% of the older participants were able to predictively control their movements, compared with 70% in the young group. In Experiment 2, 48% of the participants were able to predictively control their movements with a cognitively loading task, compared with 70% in the no-load condition. The ability to predictively change a motor plan in anticipation of upcoming changes may be an important component in performing everyday functions, such as safe driving and avoiding falls.

Leading change: a three-dimensional model of nurse leaders' main tasks and roles during a change process.

Science.gov (United States)

Salmela, Susanne; Eriksson, Katie; Fagerström, Lisbeth

2012-02-01

This paper is a report of a qualitative study which explored how nurse leaders described and understood their main tasks and roles during a change process. During a database search for literature, no actual research that highlighted the main tasks and roles of nurse leaders during a change process was found. Earlier research has indicated the need for different leadership styles and the importance of strategies and values. In-depth interviews with 17 nurse leaders took place in 2004. A phenomenological-hermeneutical approach was used for data analysis. The findings resulted in a model of leading change in health care that focuses on good patient care and consists of three dimensions: leading relationships, leading processes and leading a culture. In addition to leading relationships and processes, nurse leaders, as role models, greatly impact caring culture and its inherent ethical behaviour, especially about the responsibility for achieving good patient care. Nurse leaders are also instrumental in leading ward culture. Nurse leaders need guidance and knowledge of what is expected of them during a structural change process. They play different roles by directing, guiding, motivating, supporting and communicating without losing their cultural ethos of caring and use various leadership styles to bring about actual change, which, in turn, requires learning so that the thought patterns, values and attitudes of personnel can be changed. © 2011 Blackwell Publishing Ltd.

Detecting and Attributing Health Burdens to Climate Change.

Science.gov (United States)

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

2017-08-07

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

From sounds to words: a neurocomputational model of adaptation, inhibition and memory processes in auditory change detection.

Science.gov (United States)

Garagnani, Max; Pulvermüller, Friedemann

2011-01-01

Most animals detect sudden changes in trains of repeated stimuli but only some can learn a wide range of sensory patterns and recognise them later, a skill crucial for the evolutionary success of higher mammals. Here we use a neural model mimicking the cortical anatomy of sensory and motor areas and their connections to explain brain activity indexing auditory change and memory access. Our simulations indicate that while neuronal adaptation and local inhibition of cortical activity can explain aspects of change detection as observed when a repeated unfamiliar sound changes in frequency, the brain dynamics elicited by auditory stimulation with well-known patterns (such as meaningful words) cannot be accounted for on the basis of adaptation and inhibition alone. Specifically, we show that the stronger brain responses observed to familiar stimuli in passive oddball tasks are best explained in terms of activation of memory circuits that emerged in the cortex during the learning of these stimuli. Such memory circuits, and the activation enhancement they entail, are absent for unfamiliar stimuli. The model illustrates how basic neurobiological mechanisms, including neuronal adaptation, lateral inhibition, and Hebbian learning, underlie neuronal assembly formation and dynamics, and differentially contribute to the brain's major change detection response, the mismatch negativity. Copyright © 2010 Elsevier Inc. All rights reserved.

Detecting abrupt dynamic change based on changes in the fractal properties of spatial images

Science.gov (United States)

Liu, Qunqun; He, Wenping; Gu, Bin; Jiang, Yundi

2017-10-01

Many abrupt climate change events often cannot be detected timely by conventional abrupt detection methods until a few years after these events have occurred. The reason for this lag in detection is that abundant and long-term observational data are required for accurate abrupt change detection by these methods, especially for the detection of a regime shift. So, these methods cannot help us understand and forecast the evolution of the climate system in a timely manner. Obviously, spatial images, generated by a coupled spatiotemporal dynamical model, contain more information about a dynamic system than a single time series, and we find that spatial images show the fractal properties. The fractal properties of spatial images can be quantitatively characterized by the Hurst exponent, which can be estimated by two-dimensional detrended fluctuation analysis (TD-DFA). Based on this, TD-DFA is used to detect an abrupt dynamic change of a coupled spatiotemporal model. The results show that the TD-DFA method can effectively detect abrupt parameter changes in the coupled model by monitoring the changing in the fractal properties of spatial images. The present method provides a new way for abrupt dynamic change detection, which can achieve timely and efficient abrupt change detection results.

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

Science.gov (United States)

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.

Illumination Invariant Change Detection (iicd): from Earth to Mars

Science.gov (United States)

Wan, X.; Liu, J.; Qin, M.; Li, S. Y.

2018-04-01

Multi-temporal Earth Observation and Mars orbital imagery data with frequent repeat coverage provide great capability for planetary surface change detection. When comparing two images taken at different times of day or in different seasons for change detection, the variation of topographic shades and shadows caused by the change of sunlight angle can be so significant that it overwhelms the real object and environmental changes, making automatic detection unreliable. An effective change detection algorithm therefore has to be robust to the illumination variation. This paper presents our research on developing and testing an Illumination Invariant Change Detection (IICD) method based on the robustness of phase correlation (PC) to the variation of solar illumination for image matching. The IICD is based on two key functions: i) initial change detection based on a saliency map derived from pixel-wise dense PC matching and ii) change quantization which combines change type identification, motion estimation and precise appearance change identification. Experiment using multi-temporal Landsat 7 ETM+ satellite images, Rapid eye satellite images and Mars HiRiSE images demonstrate that our frequency based image matching method can reach sub-pixel accuracy and thus the proposed IICD method can effectively detect and precisely segment large scale change such as landslide as well as small object change such as Mars rover, under daily and seasonal sunlight changes.

Detection and Tracking Strategies for Autonomous Aerial Refuelling Tasks Based on Monocular Vision

Directory of Open Access Journals (Sweden)

Yingjie Yin

2014-07-01

Full Text Available Detection and tracking strategies based on monocular vision are proposed for autonomous aerial refuelling tasks. The drogue attached to the fuel tanker aircraft has two important features. The grey values of the drogue's inner part are different from the external umbrella ribs, as shown in the image. The shape of the drogue's inner dark part is nearly circular. According to crucial prior knowledge, the rough and fine positioning algorithms are designed to detect the drogue. Particle filter based on the drogue's shape is proposed to track the drogue. A strategy to switch between detection and tracking is proposed to improve the robustness of the algorithms. The inner dark part of the drogue is segmented precisely in the detecting and tracking process and the segmented circular part can be used to measure its spatial position. The experimental results show that the proposed method has good performance in real-time and satisfied robustness and positioning accuracy.

Automated baseline change detection phase I. Final report

Energy Technology Data Exchange (ETDEWEB)

NONE

1995-12-01

The Automated Baseline Change Detection (ABCD) project is supported by the DOE Morgantown Energy Technology Center (METC) as part of its ER&WM cross-cutting technology program in robotics. Phase 1 of the Automated Baseline Change Detection project is summarized in this topical report. The primary objective of this project is to apply robotic and optical sensor technology to the operational inspection of mixed toxic and radioactive waste stored in barrels, using Automated Baseline Change Detection (ABCD), based on image subtraction. Absolute change detection is based on detecting any visible physical changes, regardless of cause, between a current inspection image of a barrel and an archived baseline image of the same barrel. Thus, in addition to rust, the ABCD system can also detect corrosion, leaks, dents, and bulges. The ABCD approach and method rely on precise camera positioning and repositioning relative to the barrel and on feature recognition in images. In support of this primary objective, there are secondary objectives to determine DOE operational inspection requirements and DOE system fielding requirements.

Automated baseline change detection phase I. Final report

International Nuclear Information System (INIS)

1995-12-01

The Automated Baseline Change Detection (ABCD) project is supported by the DOE Morgantown Energy Technology Center (METC) as part of its ER ampersand WM cross-cutting technology program in robotics. Phase 1 of the Automated Baseline Change Detection project is summarized in this topical report. The primary objective of this project is to apply robotic and optical sensor technology to the operational inspection of mixed toxic and radioactive waste stored in barrels, using Automated Baseline Change Detection (ABCD), based on image subtraction. Absolute change detection is based on detecting any visible physical changes, regardless of cause, between a current inspection image of a barrel and an archived baseline image of the same barrel. Thus, in addition to rust, the ABCD system can also detect corrosion, leaks, dents, and bulges. The ABCD approach and method rely on precise camera positioning and repositioning relative to the barrel and on feature recognition in images. In support of this primary objective, there are secondary objectives to determine DOE operational inspection requirements and DOE system fielding requirements

A new type of change blindness: smooth, isoluminant color changes are monitored on a coarse spatial scale.

Science.gov (United States)

Goddard, Erin; Clifford, Colin W G

2013-04-22

Attending selectively to changes in our visual environment may help filter less important, unchanging information within a scene. Here, we demonstrate that color changes can go unnoticed even when they occur throughout an otherwise static image. The novelty of this demonstration is that it does not rely upon masking by a visual disruption or stimulus motion, nor does it require the change to be very gradual and restricted to a small section of the image. Using a two-interval, forced-choice change-detection task and an odd-one-out localization task, we showed that subjects were slowest to respond and least accurate (implying that change was hardest to detect) when the color changes were isoluminant, smoothly varying, and asynchronous with one another. This profound change blindness offers new constraints for theories of visual change detection, implying that, in the absence of transient signals, changes in color are typically monitored at a coarse spatial scale.

Saliency predicts change detection in pictures of natural scenes.

Science.gov (United States)

Wright, Michael J

2005-01-01

It has been proposed that the visual system encodes the salience of objects in the visual field in an explicit two-dimensional map that guides visual selective attention. Experiments were conducted to determine whether salience measurements applied to regions of pictures of outdoor scenes could predict the detection of changes in those regions. To obtain a quantitative measure of change detection, observers located changes in pairs of colour pictures presented across an interstimulus interval (ISI). Salience measurements were then obtained from different observers for image change regions using three independent methods, and all were positively correlated with change detection. Factor analysis extracted a single saliency factor that accounted for 62% of the variance contained in the four measures. Finally, estimates of the magnitude of the image change in each picture pair were obtained, using nine separate visual filters representing low-level vision features (luminance, colour, spatial frequency, orientation, edge density). None of the feature outputs was significantly associated with change detection or saliency. On the other hand it was shown that high-level (structural) properties of the changed region were related to saliency and to change detection: objects were more salient than shadows and more detectable when changed.

Minimal changes in health status questionnaires: distinction between minimally detectable change and minimally important change

Directory of Open Access Journals (Sweden)

Knol Dirk L

2006-08-01

Full Text Available Abstract Changes in scores on health status questionnaires are difficult to interpret. Several methods to determine minimally important changes (MICs have been proposed which can broadly be divided in distribution-based and anchor-based methods. Comparisons of these methods have led to insight into essential differences between these approaches. Some authors have tried to come to a uniform measure for the MIC, such as 0.5 standard deviation and the value of one standard error of measurement (SEM. Others have emphasized the diversity of MIC values, depending on the type of anchor, the definition of minimal importance on the anchor, and characteristics of the disease under study. A closer look makes clear that some distribution-based methods have been merely focused on minimally detectable changes. For assessing minimally important changes, anchor-based methods are preferred, as they include a definition of what is minimally important. Acknowledging the distinction between minimally detectable and minimally important changes is useful, not only to avoid confusion among MIC methods, but also to gain information on two important benchmarks on the scale of a health status measurement instrument. Appreciating the distinction, it becomes possible to judge whether the minimally detectable change of a measurement instrument is sufficiently small to detect minimally important changes.

Learning a Transferable Change Rule from a Recurrent Neural Network for Land Cover Change Detection

Directory of Open Access Journals (Sweden)

Haobo Lyu

2016-06-01

Full Text Available When exploited in remote sensing analysis, a reliable change rule with transfer ability can detect changes accurately and be applied widely. However, in practice, the complexity of land cover changes makes it difficult to use only one change rule or change feature learned from a given multi-temporal dataset to detect any other new target images without applying other learning processes. In this study, we consider the design of an efficient change rule having transferability to detect both binary and multi-class changes. The proposed method relies on an improved Long Short-Term Memory (LSTM model to acquire and record the change information of long-term sequence remote sensing data. In particular, a core memory cell is utilized to learn the change rule from the information concerning binary changes or multi-class changes. Three gates are utilized to control the input, output and update of the LSTM model for optimization. In addition, the learned rule can be applied to detect changes and transfer the change rule from one learned image to another new target multi-temporal image. In this study, binary experiments, transfer experiments and multi-class change experiments are exploited to demonstrate the superiority of our method. Three contributions of this work can be summarized as follows: (1 the proposed method can learn an effective change rule to provide reliable change information for multi-temporal images; (2 the learned change rule has good transferability for detecting changes in new target images without any extra learning process, and the new target images should have a multi-spectral distribution similar to that of the training images; and (3 to the authors’ best knowledge, this is the first time that deep learning in recurrent neural networks is exploited for change detection. In addition, under the framework of the proposed method, changes can be detected under both binary detection and multi-class change detection.

Bayesian change-point analysis reveals developmental change in a classic theory of mind task.

Science.gov (United States)

Baker, Sara T; Leslie, Alan M; Gallistel, C R; Hood, Bruce M

2016-12-01

Although learning and development reflect changes situated in an individual brain, most discussions of behavioral change are based on the evidence of group averages. Our reliance on group-averaged data creates a dilemma. On the one hand, we need to use traditional inferential statistics. On the other hand, group averages are highly ambiguous when we need to understand change in the individual; the average pattern of change may characterize all, some, or none of the individuals in the group. Here we present a new method for statistically characterizing developmental change in each individual child we study. Using false-belief tasks, fifty-two children in two cohorts were repeatedly tested for varying lengths of time between 3 and 5 years of age. Using a novel Bayesian change point analysis, we determined both the presence and-just as importantly-the absence of change in individual longitudinal cumulative records. Whenever the analysis supports a change conclusion, it identifies in that child's record the most likely point at which change occurred. Results show striking variability in patterns of change and stability across individual children. We then group the individuals by their various patterns of change or no change. The resulting patterns provide scarce support for sudden changes in competence and shed new light on the concepts of "passing" and "failing" in developmental studies. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Land-cover change detection

Science.gov (United States)

Chen, Xuexia; Giri, Chandra; Vogelmann, James

2012-01-01

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

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

Science.gov (United States)

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

Interpreting the change detection error matrix

NARCIS (Netherlands)

Oort, van P.A.J.

2007-01-01

Two different matrices are commonly reported in assessment of change detection accuracy: (1) single date error matrices and (2) binary change/no change error matrices. The third, less common form of reporting, is the transition error matrix. This paper discuses the relation between these matrices.

FAST AND ROBUST SEGMENTATION AND CLASSIFICATION FOR CHANGE DETECTION IN URBAN POINT CLOUDS

Directory of Open Access Journals (Sweden)

X. Roynard

2016-06-01

Full Text Available 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.

Real-time changes in corticospinal excitability related to motor imagery of a force control task

DEFF Research Database (Denmark)

Tatemoto, Tsuyoshi; Tsuchiya, Junko; Numata, Atsuki

2017-01-01

Objective To investigate real-time excitability changes in corticospinal pathways related to motor imagery in a changing force control task, using transcranial magnetic stimulation (TMS). Methods Ten healthy volunteers learnt to control the contractile force of isometric right wrist dorsiflexion...... in order to track an on-screen sine wave form. Participants performed the trained task 40 times with actual muscle contraction in order to construct the motor image. They were then instructed to execute the task without actual muscle contraction, but by imagining contraction of the right wrist...... in dorsiflexion. Motor evoked potentials (MEPs), induced by TMS in the right extensor carpi radialis muscle (ECR) and flexor carpi radialis muscle (FCR), were measured during motor imagery. MEPs were induced at five time points: prior to imagery, during the gradual generation of the imaged wrist dorsiflexion...

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

Science.gov (United States)

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…

Adaptive 4d Psi-Based Change Detection

Science.gov (United States)

Yang, Chia-Hsiang; Soergel, Uwe

2018-04-01

In a previous work, we proposed a PSI-based 4D change detection to detect disappearing and emerging PS points (3D) along with their occurrence dates (1D). Such change points are usually caused by anthropic events, e.g., building constructions in cities. This method first divides an entire SAR image stack into several subsets by a set of break dates. The PS points, which are selected based on their temporal coherences before or after a break date, are regarded as change candidates. Change points are then extracted from these candidates according to their change indices, which are modelled from their temporal coherences of divided image subsets. Finally, we check the evolution of the change indices for each change point to detect the break date that this change occurred. The experiment validated both feasibility and applicability of our method. However, two questions still remain. First, selection of temporal coherence threshold associates with a trade-off between quality and quantity of PS points. This selection is also crucial for the amount of change points in a more complex way. Second, heuristic selection of change index thresholds brings vulnerability and causes loss of change points. In this study, we adapt our approach to identify change points based on statistical characteristics of change indices rather than thresholding. The experiment validates this adaptive approach and shows increase of change points compared with the old version. In addition, we also explore and discuss optimal selection of temporal coherence threshold.

Sensor for detecting changes in magnetic fields

Science.gov (United States)

Praeg, Walter F.

1981-01-01

A sensor for detecting changes in the magnetic field of the equilibrium-field coil of a Tokamak plasma device comprises a pair of bifilar wires disposed circumferentially, one inside and one outside the equilibrium-field coil. Each is shorted at one end. The difference between the voltages detected at the other ends of the bifilar wires provides a measure of changing flux in the equilibrium-field coil. This difference can be used to detect faults in the coil in time to take action to protect the coil.

Change Detection in Social Networks

National Research Council Canada - National Science Library

McCulloh, Ian; Webb, Matthew; Graham, John; Carley, Kathleen; Horn, Daniel B

2008-01-01

.... This project proposes a new method for detecting change in social networks over time, by applying a cumulative sum statistical process control statistic to normally distributed network measures...

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

Science.gov (United States)

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

Wide area change detection with satellite imagery for locating underground nuclear testing

International Nuclear Information System (INIS)

Canty, M.J.; Jasani, B.; Schlittenhardt, J.

2001-01-01

With the advent of high resolution optical imagery from commercial earth observation satellites, the use of remote sensing data for verification of nuclear non-proliferation agreements is becoming increasingly attractive. Non-governmental organizations are routinely publishing high-quality imagery of sensitive nuclear installations round the world, and international verification authorities, such as the International Atomic Energy Agency (IAEA) or the Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO), will also want to make use, directly or indirectly, of this additional open source of information. Exact location of the sites of underground nuclear explosions is a task eminently suited to satellite imagery. Here both moderate resolutions for detecting signals in very large testing ranges as well as high resolution images for exact interpretation play important roles. We describe in our paper a particularly sensitive change detection procedure for bitemporal, multispectral satellite imagery which can be used to locate the spall zone of underground nuclear explosions with commercial satellite imagery. The method is based on the multivariate alteration detection (MAD) technique of Nielsen et al. Linear combinations of the spectral channels in two images of the same scene are chosen so as to minimize their positive correlation. This leads to a series of difference images - the so-called MAD components - which are mutually orthogonal (uncorrelated) and ordered according to decreasing variance in their pixel intensities. Since interesting changes in man-made structures may contribute minimally to the overall variance (as the latter may be dominated for instance by seasonal vegetation differences) it is often the case that such changes turn up in a higher order MAD component. This is because they will be uncorrelated with seasonal vegetation changes, stochastic image noise or other major contributions to the overall change signal. This in fact is one of the

Trace Contraband Detection Field-Test by the South Texas Specialized Crimes and Narcotics Task Force

Energy Technology Data Exchange (ETDEWEB)

Hannum, David W. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Contraband Detection Dept.; Shannon, Gary W. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Contraband Detection Dept.

2006-04-01

This report describes the collaboration between the South Texas Specialized Crimes and Narcotics Task Force (STSCNTF) and Sandia National Laboratories (SNL) in a field test that provided prototype hand-held trace detection technology for use in counter-drug operations. The National Institute of Justice (NIJ)/National Law Enforcement and Corrections Technology Center (NLECTC)/Border Research and Technology Center (BRTC) was contacted by STSCNTF for assistance in obtaining cutting-edge technology. The BRTC created a pilot project for Sandia National Laboratories (SNL) and the STSCNTF for the use of SNL’s Hound, a hand-held sample collection and preconcentration system that, when combined with a commercial chemical detector, can be used for the trace detection of illicit drugs and explosives. The STSCNTF operates in an area of high narcotics trafficking where methods of concealment make the detection of narcotics challenging. Sandia National Laboratories’ (SNL) Contraband Detection Department personnel provided the Hound system hardware and operational training. The Hound system combines the GE VaporTracer2, a hand-held commercial chemical detector, with an SNL-developed sample collection and preconcentration system. The South Texas Task force reported a variety of successes, including identification of a major shipment of methamphetamines, the discovery of hidden compartments in vehicles that contained illegal drugs and currency used in drug deals, and the identification of a suspect in a nightclub shooting. The main advantage of the hand-held trace detection unit is its ability to quickly identify the type of chemical (drugs or explosives) without a long lag time for laboratory analysis, which is the most common analysis method for current law enforcement procedures.

CHANGE@CERN:Task Force 2: reshaping for the future

CERN Multimedia

2002-01-01

Second in our series reviewing the Task Forces reports. How to lay the foundations for a more efficient organisational structure. Our present organization is based on sixteen Divisions and units under the Directorate. CERN's organization is based on a Directorate and sixteen Divisions and units, while its activities are broadly divided into four Sectors: Research, Accelerators, Technical and Administration. The mandate of Task Force 2, led by Horst Wenninger, was to identify if a structural change and a reduction of duplicated efforts could result in an increased efficiency at CERN, especially as the Laboratory continues to focus its resources on the LHC. 'This is the most difficult project ever undertaken at CERN', acknowledges Wenninger, 'a double accelerator at a temperature of 1.9 K'. For the next five years the success of the LHC must be the main priority, and CERN will have to adapt the procedures of how it works. Wenninger sees the process as an opportunity for the Laboratory to move into the 21st c...

Sustained change blindness to incremental scene rotation: a dissociation between explicit change detection and visual memory.

Science.gov (United States)

Hollingworth, Andrew; Henderson, John M

2004-07-01

In a change detection paradigm, the global orientation of a natural scene was incrementally changed in 1 degree intervals. In Experiments 1 and 2, participants demonstrated sustained change blindness to incremental rotation, often coming to consider a significantly different scene viewpoint as an unchanged continuation of the original view. Experiment 3 showed that participants who failed to detect the incremental rotation nevertheless reliably detected a single-step rotation back to the initial view. Together, these results demonstrate an important dissociation between explicit change detection and visual memory. Following a change, visual memory is updated to reflect the changed state of the environment, even if the change was not detected.

Real-time changes in corticospinal excitability related to motor imagery of a force control task.

Science.gov (United States)

Tatemoto, Tsuyoshi; Tsuchiya, Junko; Numata, Atsuki; Osawa, Ryuji; Yamaguchi, Tomofumi; Tanabe, Shigeo; Kondo, Kunitsugu; Otaka, Yohei; Sugawara, Kenichi

2017-09-29

To investigate real-time excitability changes in corticospinal pathways related to motor imagery in a changing force control task, using transcranial magnetic stimulation (TMS). Ten healthy volunteers learnt to control the contractile force of isometric right wrist dorsiflexion in order to track an on-screen sine wave form. Participants performed the trained task 40 times with actual muscle contraction in order to construct the motor image. They were then instructed to execute the task without actual muscle contraction, but by imagining contraction of the right wrist in dorsiflexion. Motor evoked potentials (MEPs), induced by TMS in the right extensor carpi radialis muscle (ECR) and flexor carpi radialis muscle (FCR), were measured during motor imagery. MEPs were induced at five time points: prior to imagery, during the gradual generation of the imaged wrist dorsiflexion (Increasing phase), the peak value of the sine wave, during the gradual reduction (Decreasing phase), and after completion of the task. The MEP ratio, as the ratio of imaged MEPs to resting-state, was compared between pre- and post-training at each time point. In the ECR muscle, the MEP ratio significantly increased during the Increasing phase and at the peak force of dorsiflexion imagery after training. Moreover, the MEP ratio was significantly greater in the Increasing phase than in the Decreasing phase. In the FCR, there were no significant consistent changes. Corticospinal excitability during motor imagery in an isometric contraction task was modulated in relation to the phase of force control after image construction. Copyright © 2017 Elsevier B.V. All rights reserved.

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

Science.gov (United States)

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.

Acoustic change detection algorithm using an FM radio

Science.gov (United States)

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.

Incrementally Detecting Change Types of Spatial Area Object: A Hierarchical Matching Method Considering Change Process

Directory of Open Access Journals (Sweden)

Yanhui Wang

2018-01-01

Full Text Available Detecting and extracting the change types of spatial area objects can track area objects’ spatiotemporal change pattern and provide the change backtracking mechanism for incrementally updating spatial datasets. To respond to the problems of high complexity of detection methods, high redundancy rate of detection factors, and the low automation degree during incrementally update process, we take into account the change process of area objects in an integrated way and propose a hierarchical matching method to detect the nine types of changes of area objects, while minimizing the complexity of the algorithm and the redundancy rate of detection factors. We illustrate in details the identification, extraction, and database entry of change types, and how we achieve a close connection and organic coupling of incremental information extraction and object type-of-change detection so as to characterize the whole change process. The experimental results show that this method can successfully detect incremental information about area objects in practical applications, with the overall accuracy reaching above 90%, which is much higher than the existing weighted matching method, making it quite feasible and applicable. It helps establish the corresponding relation between new-version and old-version objects, and facilitate the linked update processing and quality control of spatial data.

A Longitudinal Perspective on Inductive Reasoning Tasks. Illuminating the Probability of Change

Science.gov (United States)

Ifenthaler, Dirk; Seel, Norbert M.

2011-01-01

Cognitive scientists have studied internal cognitive structures, processes, and systems for decades in order to understand how they function in human learning. Nevertheless, questions concerning the diagnosis of changes in these cognitive structures while solving inductive reasoning tasks are still being scrutinized. This paper reports findings…

Cortical Thickness Changes and Their Relationship to Dual-Task Performance following Mild Traumatic Brain Injury in Youth.

Science.gov (United States)

Urban, Karolina J; Riggs, Lily; Wells, Greg D; Keightley, Michelle; Chen, Jen-Kai; Ptito, Alain; Fait, Philippe; Taha, Tim; Sinopoli, Katia J

2017-02-15

Mild traumatic brain injury (mTBI) is common in youth, especially in those who participate in sport. Recent investigations from our group have shown that asymptomatic children and adolescents with mTBI continue to exhibit alterations in neural activity and cognitive performance compared with those without a history of mTBI. This is an intriguing finding, given that current return-to-learn and return-to-play protocols rely predominately on subjective symptom reports, which may not be sensitive enough to detect subtle injury-related changes. As a result, youth may be at greater risk for re-injury and long-term consequences if they are cleared for activity while their brains continue to be compromised. It is currently unknown whether mTBI also affects brain microstructure in the developing brain, particularly cortical thickness, and whether such changes are also related to cognitive performance. The present study examined cortical thickness in 13 asymptomatic youth (10-14 years old) who had sustained an mTBI 3-8 months prior to testing compared with 14 age-matched typically developing controls. Cortical thickness was also examined in relation to working memory performance during single and dual task paradigms. The results show that youth who had sustained an mTBI had thinner cortices in the left dorsolateral prefrontal region and right anterior and posterior inferior parietal lobes. Additionally, cortical thinning was associated with slower reaction time during the dual-task condition in the injured youth only. The results also point to a possible relationship between functional and structural alterations as a result of mTBI in youth, and lend evidence for neural changes beyond symptom resolution.

What you fear will appear: detection of schematic spiders in spider fear.

Science.gov (United States)

Peira, Nathalie; Golkar, Armita; Larsson, Maria; Wiens, Stefan

2010-01-01

Various experimental tasks suggest that fear guides attention. However, because these tasks often lack ecological validity, it is unclear to what extent results from these tasks can be generalized to real-life situations. In change detection tasks, a brief interruption of the visual input (i.e., a blank interval or a scene cut) often results in undetected changes in the scene. This setup resembles real-life viewing behavior and is used here to increase ecological validity of the attentional task without compromising control over the stimuli presented. Spider-fearful and nonfearful women detected schematic spiders and flowers that were added to one of two identical background pictures that alternated with a brief blank in between them (i.e., flicker paradigm). Results showed that spider-fearful women detected spiders (but not flowers) faster than did nonfearful women. Because spiders and flowers had similar low-level features, these findings suggest that fear guides attention on the basis of object features rather than simple low-level features.

Detection of Acute and Long-Term Effects of Concussion: Dual-Task Gait Balance Control Versus Computerized Neurocognitive Test.

Science.gov (United States)

Howell, David R; Osternig, Louis R; Chou, Li-Shan

2018-02-16

To examine the acute (within 72h of injury) and long-term (2mo postinjury) independent associations between objective dual-task gait balance and neurocognitive measurements among adolescents and young adults with a concussion and matched controls. Longitudinal case-control. Motion analysis laboratory. A total of 95 participants completed the study: 51 who sustained a concussion (mean age, 17.5±3.3y; 71% men) and 44 controls (mean age, 17.7±2.9y; 72% men). Participants who sustained a concussion underwent a dual-task gait analysis and computerized neurocognitive testing within 72 hours of injury and again 2 months later. Uninjured controls also completed the same test protocol in similar time increments. Not applicable. We compared dual-task gait balance control and computerized neurocognitive test performance between groups using independent samples t tests. Multivariable binary logistic regression models were then constructed for each testing time to determine the association between group membership (concussion vs control), dual-task gait balance control, and neurocognitive function. Medial-lateral center-of-mass displacement during dual-task gait was independently associated with group membership at the initial test (adjusted odds ratio [aOR], 2.432; 95% confidence interval [CI], 1.269-4.661) and 2-month follow-up test (aOR, 1.817; 95% CI, 1.014-3.256) tests. Visual memory composite scores were significantly associated with group membership at the initial hour postinjury time point (aOR, .953; 95% CI, .833-.998). However, the combination of computerized neurocognitive test variables did not predict dual-task gait balance control for participants with concussion, and no single neurocognitive variable was associated with dual-task gait balance control at either testing time. Dual-task assessments concurrently evaluating gait and cognitive performance may allow for the detection of persistent deficits beyond those detected by computerized neurocognitive deficits

Age-related changes in learning across early childhood: a new imitation task.

Science.gov (United States)

Dickerson, Kelly; Gerhardstein, Peter; Zack, Elizabeth; Barr, Rachel

2013-11-01

Imitation plays a critical role in social and cognitive development, but the social learning mechanisms contributing to the development of imitation are not well understood. We developed a new imitation task designed to examine social learning mechanisms across the early childhood period. The new task involves assembly of abstract-shaped puzzle pieces in an arbitrary sequence on a magnet board. Additionally, we introduce a new scoring system that extends traditional goal-directed imitation scoring to include measures of both children's success at copying gestures (sliding the puzzle pieces) and goals (connecting the puzzle pieces). In Experiment 1, we demonstrated an age-invariant baseline from 1.5 to 3.5 years of age, accompanied by age-related changes in success at copying goals and gestures from a live demonstrator. In Experiment 2, we applied our new task to learning following a video demonstration. Imitation performance in the video demonstration group lagged behind that of the live demonstration group, showing a protracted video deficit effect. Across both experiments, children were more likely to copy gestures at earlier ages, suggesting mimicry, and only later copy both goals and gestures, suggesting imitation. Taken together, the findings suggest that different social learning strategies may predominate in imitation learning dependent upon the degree of object affordance, task novelty, and task complexity. © 2012 Wiley Periodicals, Inc.

Fast Change Point Detection for Electricity Market Analysis

Energy Technology Data Exchange (ETDEWEB)

Berkeley, UC; Gu, William; Choi, Jaesik; Gu, Ming; Simon, Horst; Wu, Kesheng

2013-08-25

Electricity is a vital part of our daily life; therefore it is important to avoid irregularities such as the California Electricity Crisis of 2000 and 2001. In this work, we seek to predict anomalies using advanced machine learning algorithms. These algorithms are effective, but computationally expensive, especially if we plan to apply them on hourly electricity market data covering a number of years. To address this challenge, we significantly accelerate the computation of the Gaussian Process (GP) for time series data. In the context of a Change Point Detection (CPD) algorithm, we reduce its computational complexity from O($n^{5}$) to O($n^{2}$). Our efficient algorithm makes it possible to compute the Change Points using the hourly price data from the California Electricity Crisis. By comparing the detected Change Points with known events, we show that the Change Point Detection algorithm is indeed effective in detecting signals preceding major events.

Unsupervised Speaker Change Detection for Broadcast News Segmentation

DEFF Research Database (Denmark)

Jørgensen, Kasper Winther; Mølgaard, Lasse Lohilahti; Hansen, Lars Kai

2006-01-01

This paper presents a speaker change detection system for news broadcast segmentation based on a vector quantization (VQ) approach. The system does not make any assumption about the number of speakers or speaker identity. The system uses mel frequency cepstral coefficients and change detection...

OBJECT-ORIENTED CHANGE DETECTION BASED ON MULTI-SCALE APPROACH

Directory of Open Access Journals (Sweden)

Y. Jia

2016-06-01

Full Text Available The change detection of remote sensing images means analysing the change information quantitatively and recognizing the change types of the surface coverage data in different time phases. With the appearance of high resolution remote sensing image, object-oriented change detection method arises at this historic moment. In this paper, we research multi-scale approach for high resolution images, which includes multi-scale segmentation, multi-scale feature selection and multi-scale classification. Experimental results show that this method has a stronger advantage than the traditional single-scale method of high resolution remote sensing image change detection.

Ventrolateral prefrontal activation during a N-back task assessed with multichannel functional near-infrared spectroscopy

Science.gov (United States)

Zhou, Yuan; Zhu, Ye; Jiang, Tianzi

2007-05-01

Functional near-infrared spectroscopy (fNIRS) has been used to investigate the changes in the concentration of oxygenated (O2Hb) and deoxygenated (HHb) hemoglobin in brain issue during several cognitive tasks. In the present study, by means of multichannel dual wavelength light-emitting diode continuous-wave (CW) NIRS, we investigated the blood oxygenation changes of prefrontal cortex in 18 healthy subjects while performing a verbal n-back task (0-back and 2-back), which has been rarely investigated by fNIRS. Compared to the 0-back task (control task), we found a significant increase of O2Hb and total amount of hemoglobin (THb) in left and right ventrolateral prefrontal cortex (VLPFC) during the execution of the 2-back task compared to the 0-back task (pdominance. In addition, the effects of gender and its interaction with task performance on O2Hb concentration change were suggested in the present study. Our findings not only confirm that multichannel fNIRS is suitable to detect spatially specific activation during the performance of cognitive tasks; but also suggest that it should be cautious of gender-dependent difference in cerebral activation when interpreting the fNIRS data during cognitive tasks.

Changes in regional cerebral blood flow in nondominant hemisphere during speech task in aphasics. A PET activation study

Energy Technology Data Exchange (ETDEWEB)

Ohyama, Masashi; Kitamura, Shin; Mishina, Masahiro; Terashi, Akiro [Nippon Medical School, Tokyo (Japan); Senda, Michio; Ishii, Kenji

1995-08-01

To investigate the patients with language disorder and to detect the activated areas in language processing, we measured the changes in the regional cerebral blood flow (CBF) during speech task (`counting` task) using O-15 water PET activation technique in six normal subjects (age 58.3 {+-}8.1, mean{+-}SD), ten fluent aphasics (age 60.3{+-}12.5) and six nonfluent aphasics (age 50.5{+-}8.3). In `counting` task, the subjects were instructed to count the number aloud from 1 to 10 and repeat the sequence over and over in the native language (Japanese) at the rate of one number per 2.5 sec. The data were analyzed with stereotactic intersubject averaging analysis for the normal subjects. Apart from it, the regions of interest (ROI) analysis (a circular ROI of 12 mm diameter) was performed in the language-related area for each subject. In the normal subjects, the language-related areas: posteroinferofrontal areas (PIF), posterosuperotemporal area (PST), and Rolandic areas (related to the mouth and lips) were significantly activated bilaterally in the `counting` task. PIF were activated with a dominance in the left side. In the resting state, rCBF in the left PIF and left PST was reduced in both fluent and nonfluent aphasics. In nonfluent aphasics, the magnitude of activation in the right PIF by `counting` task was significantly greater than normal subjects and patients with fluent aphasia (ANOVA). It suggests the importance of the right PIF in the simple language processing in the nonfluent aphasia. In the sixteen aphasic patients, the increase in rCBF in the right PST during the `counting` task was negatively correlated with the score of comprehension (WAB) in the Spearman ranked correlation (p<0.05). It suggests that, while the activity of the right PST is minimal for the `counting` in normal subjects, it plays an important and compensatory role in aphasic patients. (author).

Changes in regional cerebral blood flow in nondominant hemisphere during speech task in aphasics. A PET activation study

International Nuclear Information System (INIS)

Ohyama, Masashi; Kitamura, Shin; Mishina, Masahiro; Terashi, Akiro; Senda, Michio; Ishii, Kenji.

1995-01-01

To investigate the patients with language disorder and to detect the activated areas in language processing, we measured the changes in the regional cerebral blood flow (CBF) during speech task ('counting' task) using O-15 water PET activation technique in six normal subjects (age 58.3 ±8.1, mean±SD), ten fluent aphasics (age 60.3±12.5) and six nonfluent aphasics (age 50.5±8.3). In 'counting' task, the subjects were instructed to count the number aloud from 1 to 10 and repeat the sequence over and over in the native language (Japanese) at the rate of one number per 2.5 sec. The data were analyzed with stereotactic intersubject averaging analysis for the normal subjects. Apart from it, the regions of interest (ROI) analysis (a circular ROI of 12 mm diameter) was performed in the language-related area for each subject. In the normal subjects, the language-related areas: posteroinferofrontal areas (PIF), posterosuperotemporal area (PST), and Rolandic areas (related to the mouth and lips) were significantly activated bilaterally in the 'counting' task. PIF were activated with a dominance in the left side. In the resting state, rCBF in the left PIF and left PST was reduced in both fluent and nonfluent aphasics. In nonfluent aphasics, the magnitude of activation in the right PIF by 'counting' task was significantly greater than normal subjects and patients with fluent aphasia (ANOVA). It suggests the importance of the right PIF in the simple language processing in the nonfluent aphasia. In the sixteen aphasic patients, the increase in rCBF in the right PST during the 'counting' task was negatively correlated with the score of comprehension (WAB) in the Spearman ranked correlation (p<0.05). It suggests that, while the activity of the right PST is minimal for the 'counting' in normal subjects, it plays an important and compensatory role in aphasic patients. (author)

Task-dependent changes in cross-level coupling between single neurons and oscillatory activity in multiscale networks.

Directory of Open Access Journals (Sweden)

Ryan T Canolty

Full Text Available Understanding the principles governing the dynamic coordination of functional brain networks remains an important unmet goal within neuroscience. How do distributed ensembles of neurons transiently coordinate their activity across a variety of spatial and temporal scales? While a complete mechanistic account of this process remains elusive, evidence suggests that neuronal oscillations may play a key role in this process, with different rhythms influencing both local computation and long-range communication. To investigate this question, we recorded multiple single unit and local field potential (LFP activity from microelectrode arrays implanted bilaterally in macaque motor areas. Monkeys performed a delayed center-out reach task either manually using their natural arm (Manual Control, MC or under direct neural control through a brain-machine interface (Brain Control, BC. In accord with prior work, we found that the spiking activity of individual neurons is coupled to multiple aspects of the ongoing motor beta rhythm (10-45 Hz during both MC and BC, with neurons exhibiting a diversity of coupling preferences. However, here we show that for identified single neurons, this beta-to-rate mapping can change in a reversible and task-dependent way. For example, as beta power increases, a given neuron may increase spiking during MC but decrease spiking during BC, or exhibit a reversible shift in the preferred phase of firing. The within-task stability of coupling, combined with the reversible cross-task changes in coupling, suggest that task-dependent changes in the beta-to-rate mapping play a role in the transient functional reorganization of neural ensembles. We characterize the range of task-dependent changes in the mapping from beta amplitude, phase, and inter-hemispheric phase differences to the spike rates of an ensemble of simultaneously-recorded neurons, and discuss the potential implications that dynamic remapping from oscillatory activity to

Real-time change detection for countering improvised explosive devices

NARCIS (Netherlands)

Wouw, van de D.W.J.M.; Rens, van K.; Lint, van R.H.; Jaspers, Egbert; With, de P.H.N.; Loce, R.P.; Saber, E.

2014-01-01

We explore an automatic real-time change detection system to assist military personnel during transport and surveillance, by detection changes in the environment with respect to a previous operation. Such changes may indicate the presence of Improvised Explosive Devices (IEDs), which can then be

Rapid Change Detection Algorithm for Disaster Management

Science.gov (United States)

Michel, U.; Thunig, H.; Ehlers, M.; Reinartz, P.

2012-07-01

This paper focuses on change detection applications in areas where catastrophic events took place which resulted in rapid destruction especially of manmade objects. Standard methods for automated change detection prove not to be sufficient; therefore a new method was developed and tested. The presented method allows a fast detection and visualization of change in areas of crisis or catastrophes. While often new methods of remote sensing are developed without user oriented aspects, organizations and authorities are not able to use these methods because of absence of remote sensing know how. Therefore a semi-automated procedure was developed. Within a transferable framework, the developed algorithm can be implemented for a set of remote sensing data among different investigation areas. Several case studies are the base for the retrieved results. Within a coarse dividing into statistical parts and the segmentation in meaningful objects, the framework is able to deal with different types of change. By means of an elaborated Temporal Change Index (TCI) only panchromatic datasets are used to extract areas which are destroyed, areas which were not affected and in addition areas where rebuilding has already started.

The Persistence of Experience: Prior Attentional and Emotional State Affects Network Functioning in a Target Detection Task.

Science.gov (United States)

Stern, Emily R; Muratore, Alexandra F; Taylor, Stephan F; Abelson, James L; Hof, Patrick R; Goodman, Wayne K

2015-09-01

Efficient, adaptive behavior relies on the ability to flexibly move between internally focused (IF) and externally focused (EF) attentional states. Despite evidence that IF cognitive processes such as event imagination comprise a significant amount of awake cognition, the consequences of internal absorption on the subsequent recruitment of brain networks during EF tasks are unknown. The present functional magnetic resonance imaging (fMRI) study employed a novel attentional state switching task. Subjects imagined positive and negative events (IF task) or performed a working memory task (EF task) before switching to a target detection (TD) task also requiring attention to external information, allowing for the investigation of neural functioning during external attention based on prior attentional state. There was a robust increase of activity in frontal, parietal, and temporal regions during TD when subjects were previously performing the EF compared with IF task, an effect that was most pronounced following negative IF. Additionally, dorsolateral prefrontal cortex was less negatively coupled with ventromedial prefrontal and posterior cingulate cortices during TD following IF compared with EF. These findings reveal the striking consequences for brain activity following immersion in an IF attentional state, which have strong implications for psychiatric disorders characterized by excessive internal focus. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Detecting changes in real-time data: a user's guide to optimal detection.

Science.gov (United States)

Johnson, P; Moriarty, J; Peskir, G

2017-08-13

The real-time detection of changes in a noisily observed signal is an important problem in applied science and engineering. The study of parametric optimal detection theory began in the 1930s, motivated by applications in production and defence. Today this theory, which aims to minimize a given measure of detection delay under accuracy constraints, finds applications in domains including radar, sonar, seismic activity, global positioning, psychological testing, quality control, communications and power systems engineering. This paper reviews developments in optimal detection theory and sequential analysis, including sequential hypothesis testing and change-point detection, in both Bayesian and classical (non-Bayesian) settings. For clarity of exposition, we work in discrete time and provide a brief discussion of the continuous time setting, including recent developments using stochastic calculus. Different measures of detection delay are presented, together with the corresponding optimal solutions. We emphasize the important role of the signal-to-noise ratio and discuss both the underlying assumptions and some typical applications for each formulation.This article is part of the themed issue 'Energy management: flexibility, risk and optimization'. © 2017 The Author(s).

Adaptively detecting changes in Autonomic Grid Computing

KAUST Repository

Zhang, Xiangliang; Germain, Cé cile; Sebag, Michè le

2010-01-01

Detecting the changes is the common issue in many application fields due to the non-stationary distribution of the applicative data, e.g., sensor network signals, web logs and gridrunning logs. Toward Autonomic Grid Computing, adaptively detecting

Effects of night work, sleep loss and time on task on simulated threat detection performance.

Science.gov (United States)

Basner, Mathias; Rubinstein, Joshua; Fomberstein, Kenneth M; Coble, Matthew C; Ecker, Adrian; Avinash, Deepa; Dinges, David F

2008-09-01

To investigate the effects of night work and sleep loss on a simulated luggage screening task (SLST) that mimicked the x-ray system used by airport luggage screeners. We developed more than 5,800 unique simulated x-ray images of luggage organized into 31 stimulus sets of 200 bags each. 25% of each set contained either a gun or a knife with low or high target difficulty. The 200-bag stimuli sets were then run on software that simulates an x-ray screening system (SLST). Signal detection analysis was used to obtain measures of hit rate (HR), false alarm rate (FAR), threat detection accuracy (A'), and response bias (B"(D)). Experimental laboratory study 24 healthy nonprofessional volunteers (13 women, mean age +/- SD = 29.9 +/- 6.5 years). Subjects performed the SLST every 2 h during a 5-day period that included a 35 h period of wakefulness that extended to night work and then another day work period after the night without sleep. Threat detection accuracy A' decreased significantly (P work, while both A' (P = 0.001) and HR decreased (P = 0.008) during day work following sleep loss. There were prominent time-on-task effects on response bias B"(D) (P= 0.002) and response latency (P = 0.004), but accuracy A' was unaffected. Both HR and FAR increased significantly with increasing study duration (both P work and sleep loss adversely affect the accuracy of detecting complex real world objects among high levels of background clutter. If the results can be replicated in professional screeners and real work environments, fatigue in luggage screening personnel may pose a threat for air traffic safety unless countermeasures for fatigue are deployed.

No evidence for an item limit in change detection.

Directory of Open Access Journals (Sweden)

Shaiyan Keshvari

Full Text Available Change detection is a classic paradigm that has been used for decades to argue that working memory can hold no more than a fixed number of items ("item-limit models". Recent findings force us to consider the alternative view that working memory is limited by the precision in stimulus encoding, with mean precision decreasing with increasing set size ("continuous-resource models". Most previous studies that used the change detection paradigm have ignored effects of limited encoding precision by using highly discriminable stimuli and only large changes. We conducted two change detection experiments (orientation and color in which change magnitudes were drawn from a wide range, including small changes. In a rigorous comparison of five models, we found no evidence of an item limit. Instead, human change detection performance was best explained by a continuous-resource model in which encoding precision is variable across items and trials even at a given set size. This model accounts for comparison errors in a principled, probabilistic manner. Our findings sharply challenge the theoretical basis for most neural studies of working memory capacity.

WHAT DOES A WORD ALTER? THE EFFECT OF CONCEPTUAL NETWORKS ON THE DIMENSIONAL CHANGE SORTING TASK

Directory of Open Access Journals (Sweden)

Tolga Yildiz

2013-06-01

Full Text Available The purpose of the research was to examine the cognitive flexibility of three-year-olds, who usually persevere in the Dimensional Change Card Sort task, when a constant representation was referred in the classic instruction. In accordance with this purpose, the Dimensional Change Pencil Sort task was developed and used in the current study that 13 three-year-olds participated in. Findings seemed to support partially the hypothesis predicted that the kids could achieve the task in terms of rule use and mental representational flexibilities between length and color at the post switch phase in which situation classification dimensions were referred over a real and constant object (pencil instead of a card. This result drew attention to the conceptual and perceptual mediation roles of language and objects respectively in terms of the cognitive flexibility literature.

CHARACTERIZATION OF THE EFFECTS OF INHALED PERCHLOROETHYLENE ON SUSTAINED ATTENTION IN RATS PERFORMING A VISUAL SIGNAL DETECTION TASK

Science.gov (United States)

The aliphatic hydrocarbon perchloroethyelene (PCE) has been associated with neurobehavioral dysfunction including reduced attention in humans. The current study sought to assess the effects of inhaled PCE on sustained attention in rats performing a visual signal detection task (S...

Multichannel linear descriptors analysis for event-related EEG of vascular dementia patients during visual detection task.

Science.gov (United States)

Lou, Wutao; Xu, Jin; Sheng, Hengsong; Zhao, Songzhen

2011-11-01

Multichannel EEG recorded in a task condition could contain more information about cognition. However, that has not been widely investigated in the vascular-dementia (VaD)- related studies. The purpose of this study was to explore the differences of brain functional states between VaD patients and normal controls while performing a detection task. Three multichannel linear descriptors, i.e. spatial complexity (Ω), field strength (Σ) and frequency of field changes (Φ), were applied to analyse four frequency bands (delta, theta, alpha and beta) of multichannel event-related EEG signals for 12 VaD patients (mean age ± SD: 69.25 ± 10.56 years ; MMSE score ± SD: 22.58 ± 4.42) and 12 age-matched healthy subjects (mean age ± SD: 67.17 ± 5.97 years ; MMSE score ± SD: 29.08 ± 0.9). The correlations between the three measures and MMSE scores were also analysed. VaD patients showed a significant higher Ω value in the delta (p = 0.013) and theta (p = 0.021) frequency bands, a lower Σ value (p = 0.011) and a higher Φ (p = 0.008) value in the delta frequency band compared with normal controls. The MMSE scores were negatively correlated with the Ω (r = -0.52, p = 0.01) and Φ (r = -0.47, p = 0.02) values in the delta frequency band. The results indicated the VaD patients presented a reduction of synchronization in the slow frequency band during target detection, and suggested more neurons might be activated in VaD patients compared with normal controls. The Ω and Φ measures in the delta frequency band might be used to evaluate the degree of cognitive dysfunction. The multichannel linear descriptors are promising measures to reveal the differences in brain functions between VaD patients and normal subjects, and could potentially be used to evaluate the degree of cognitive dysfunction in VaD patients. Copyright © 2011 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Multivariate information-theoretic measures reveal directed information structure and task relevant changes in fMRI connectivity.

Science.gov (United States)

Lizier, Joseph T; Heinzle, Jakob; Horstmann, Annette; Haynes, John-Dylan; Prokopenko, Mikhail

2011-02-01

The human brain undertakes highly sophisticated information processing facilitated by the interaction between its sub-regions. We present a novel method for interregional connectivity analysis, using multivariate extensions to the mutual information and transfer entropy. The method allows us to identify the underlying directed information structure between brain regions, and how that structure changes according to behavioral conditions. This method is distinguished in using asymmetric, multivariate, information-theoretical analysis, which captures not only directional and non-linear relationships, but also collective interactions. Importantly, the method is able to estimate multivariate information measures with only relatively little data. We demonstrate the method to analyze functional magnetic resonance imaging time series to establish the directed information structure between brain regions involved in a visuo-motor tracking task. Importantly, this results in a tiered structure, with known movement planning regions driving visual and motor control regions. Also, we examine the changes in this structure as the difficulty of the tracking task is increased. We find that task difficulty modulates the coupling strength between regions of a cortical network involved in movement planning and between motor cortex and the cerebellum which is involved in the fine-tuning of motor control. It is likely these methods will find utility in identifying interregional structure (and experimentally induced changes in this structure) in other cognitive tasks and data modalities.

Differences in Multitask Resource Reallocation After Change in Task Values.

Science.gov (United States)

Matton, Nadine; Paubel, Pierre; Cegarra, Julien; Raufaste, Eric

2016-12-01

The objective was to characterize multitask resource reallocation strategies when managing subtasks with various assigned values. When solving a resource conflict in multitasking, Salvucci and Taatgen predict a globally rational strategy will be followed that favors the most urgent subtask and optimizes global performance. However, Katidioti and Taatgen identified a locally rational strategy that optimizes only a subcomponent of the whole task, leading to detrimental consequences on global performance. Moreover, the question remains open whether expertise would have an impact on the choice of the strategy. We adopted a multitask environment used for pilot selection with a change in emphasis on two out of four subtasks while all subtasks had to be maintained over a minimum performance. A laboratory eye-tracking study contrasted 20 recently selected pilot students considered as experienced with this task and 15 university students considered as novices. When two subtasks were emphasized, novices focused their resources particularly on one high-value subtask and failed to prevent both low-value subtasks falling below minimum performance. On the contrary, experienced people delayed the processing of one low-value subtask but managed to optimize global performance. In a multitasking environment where some subtasks are emphasized, novices follow a locally rational strategy whereas experienced participants follow a globally rational strategy. During complex training, trainees are only able to adjust their resource allocation strategy to subtask emphasis changes once they are familiar with the multitasking environment. © 2016, Human Factors and Ergonomics Society.

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

Science.gov (United States)

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

2017-08-15

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

Detection of greenhouse-gas-induced climatic change

International Nuclear Information System (INIS)

Wigley, T.M.L.; Jones, P.D.

1992-01-01

The aims of the US Department of Energy's Carbon Dioxide Research Program are to improve assessments of greenhouse-gas-induced climatic change and to define and reduce uncertainties through selected research. This project will address: The regional and seasonal details of the expected climatic changes; how rapidly will these changes occur; how and when will the climatic effects of CO 2 and other greenhouse gases be first detected; and the relationships between greenhouse-gas-induced climatic change and changes caused by other external and internal factors. The present project addresses all of these questions. Many of the diverse facets of greenhouse-gas-related climate research can be grouped under three interlinked subject areas: modeling, first detection and supporting data. This project will include the analysis of climate forcing factors, the development and refinement of transient response climate models, and the use of instrumental data in validating General Circulation Models (GCMs)

Detection and Attribution of Anthropogenic Climate Change Impacts

Science.gov (United States)

Rosenzweig, Cynthia; Neofotis, Peter

2013-01-01

Human-influenced climate change is an observed phenomenon affecting physical and biological systems across the globe. The majority of observed impacts are related to temperature changes and are located in the northern high- and midlatitudes. However, new evidence is emerging that demonstrates that impacts are related to precipitation changes as well as temperature, and that climate change is impacting systems and sectors beyond the Northern Hemisphere. In this paper, we highlight some of this new evidence-focusing on regions and sectors that the Intergovernmental Panel on Climate Change Fourth Assessment Report (IPCC AR4) noted as under-represented-in the context of observed climate change impacts, direct and indirect drivers of change (including carbon dioxide itself), and methods of detection. We also present methods and studies attributing observed impacts to anthropogenic forcing. We argue that the expansion of methods of detection (in terms of a broader array of climate variables and data sources, inclusion of the major modes of climate variability, and incorporation of other drivers of change) is key to discerning the climate sensitivities of sectors and systems in regions where the impacts of climate change currently remain elusive. Attributing such changes to human forcing of the climate system, where possible, is important for development of effective mitigation and adaptation. Current challenges in documenting adaptation and the role of indigenous knowledge in detection and attribution are described.

A Test of Canine Olfactory Capacity: Comparing Various Dog Breeds and Wolves in a Natural Detection Task.

Science.gov (United States)

Polgár, Zita; Kinnunen, Mari; Újváry, Dóra; Miklósi, Ádám; Gácsi, Márta

2016-01-01

Many dog breeds are bred specifically for increased performance in scent-based tasks. Whether dogs bred for this purpose have higher olfactory capacities than other dogs, or even wolves with whom they share a common ancestor, has not yet been studied. Indeed, there is no standard test for assessing canine olfactory ability. This study aimed to create a simple procedure that requires no pre-training and to use it to measure differences in olfactory capacity across four groups of canines: (1) dog breeds that have been selected for their scenting ability; (2) dog breeds that have been bred for other purposes; (3) dog breeds with exaggerated short-nosed features; and (4) hand-reared grey wolves. The procedure involved baiting a container with raw turkey meat and placing it under one of four identical ceramic pots. Subjects were led along the row of pots and were tasked with determining by olfaction alone which of them contained the bait. There were five levels of increasing difficulty determined by the number of holes on the container's lid. A subsample of both dogs and wolves was retested to assess reliability. The results showed that breeds selected for scent work were better than both short-nosed and non-scent breeds. In the most difficult level, wolves and scenting breeds performed better than chance, while non-scenting and short-nosed breeds did not. In the retested samples wolves improved their success; however, dogs showed no change in their performances indicating that a single test may be reliable enough to assess their capacity. Overall, we revealed measurable differences between dog breeds in their olfactory abilities and suggest that the Natural Detection Task is a good foundation for developing an efficient way of quantifying them.

A Test of Canine Olfactory Capacity: Comparing Various Dog Breeds and Wolves in a Natural Detection Task.

Directory of Open Access Journals (Sweden)

Zita Polgár

Full Text Available Many dog breeds are bred specifically for increased performance in scent-based tasks. Whether dogs bred for this purpose have higher olfactory capacities than other dogs, or even wolves with whom they share a common ancestor, has not yet been studied. Indeed, there is no standard test for assessing canine olfactory ability. This study aimed to create a simple procedure that requires no pre-training and to use it to measure differences in olfactory capacity across four groups of canines: (1 dog breeds that have been selected for their scenting ability; (2 dog breeds that have been bred for other purposes; (3 dog breeds with exaggerated short-nosed features; and (4 hand-reared grey wolves. The procedure involved baiting a container with raw turkey meat and placing it under one of four identical ceramic pots. Subjects were led along the row of pots and were tasked with determining by olfaction alone which of them contained the bait. There were five levels of increasing difficulty determined by the number of holes on the container's lid. A subsample of both dogs and wolves was retested to assess reliability. The results showed that breeds selected for scent work were better than both short-nosed and non-scent breeds. In the most difficult level, wolves and scenting breeds performed better than chance, while non-scenting and short-nosed breeds did not. In the retested samples wolves improved their success; however, dogs showed no change in their performances indicating that a single test may be reliable enough to assess their capacity. Overall, we revealed measurable differences between dog breeds in their olfactory abilities and suggest that the Natural Detection Task is a good foundation for developing an efficient way of quantifying them.

Coherent Change Detection with COSMO SkyMed Data-experimental Results

OpenAIRE

A. Mishra; D. Chaudhuri; C. Bhattacharya; Y.S. Rao

2013-01-01

Change detection is a technique in which we try to find changes between two acquisitions. These acquisitions can be from different platforms and sensors. Acquisition from satellite using synthetic aperture radar (SAR) is of immense interest to military applications. Satellite has the ability to peep into the enemy territory while SAR has the capability of day and night operations, being an active sensor. Coherent change detection (CCD) can be used to detect minute changes between two images. ...

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

Directory of Open Access Journals (Sweden)

Stefan eBerti

2013-07-01

Full Text Available 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.

Change Detection Based on Persistent Scatterer Interferometry - a New Method of Monitoring Building Changes

Science.gov (United States)

Yang, C. H.; Kenduiywo, B. K.; Soergel, U.

2016-06-01

Persistent Scatterer Interferometry (PSI) is a technique to detect a network of extracted persistent scatterer (PS) points which feature temporal phase stability and strong radar signal throughout time-series of SAR images. The small surface deformations on such PS points are estimated. PSI particularly works well in monitoring human settlements because regular substructures of man-made objects give rise to large number of PS points. If such structures and/or substructures substantially alter or even vanish due to big change like construction, their PS points are discarded without additional explorations during standard PSI procedure. Such rejected points are called big change (BC) points. On the other hand, incoherent change detection (ICD) relies on local comparison of multi-temporal images (e.g. image difference, image ratio) to highlight scene modifications of larger size rather than detail level. However, image noise inevitably degrades ICD accuracy. We propose a change detection approach based on PSI to synergize benefits of PSI and ICD. PS points are extracted by PSI procedure. A local change index is introduced to quantify probability of a big change for each point. We propose an automatic thresholding method adopting change index to extract BC points along with a clue of the period they emerge. In the end, PS ad BC points are integrated into a change detection image. Our method is tested at a site located around north of Berlin main station where steady, demolished, and erected building substructures are successfully detected. The results are consistent with ground truth derived from time-series of aerial images provided by Google Earth. In addition, we apply our technique for traffic infrastructure, business district, and sports playground monitoring.

Changes to the way support programme tasks are managed in the IAEA's Department of Safeguards

International Nuclear Information System (INIS)

Khlebnikov, N.; Hamilton, A.

2001-01-01

Full text: The Department of Safeguards and the 16 Member State Support Programmes jointly manage about 250 tasks. Recently, in response to a number of events, the Department has reorganized the manner in which these tasks are proposed and managed. The presentation and paper will document the following: The need to change - Although there have been a number of significant successes it has been recognised that both the way in which tasks are proposed and the management of tasks could be better performed. In particular the Report of the External Auditor 1999 stated the following: With respect to the R and D Programme the Agency 'has had difficulty in defining and prioritising tasks'; 'Ideas for tasks have come from operational units but not always in a coordinated manner'; 'I support the Agency's consideration of a move towards more centralised planning of task priorities' and the application of the 'general principles of good programme or project management. The tone of these comments was generally repeated by Member State Support Programme Co-ordinators at their meeting in November 1999 and by the Programme Performance Assessment System Report on Equipment Development. Of course the Department already knew that improvements could be made. The 'old' system - Prior to the changes three structures dominated the organisation. Firstly, a task approval process that did not allow for the application of the Department's priorities in a coordinated manner. Each task proposal was judged on its individual merits. Secondly, the distribution of task management responsibilities throughout the Department again did not allow easy coordination. Finally the focus on Member State task review meetings which did not allow the coordination of tasks in a particular subject area. The consequences of this were almost certainly the duplication of tasks, the performance of the wrong tasks and poor prioritisation of work. All at a time when the Department was generally short of resources. The

Land cover change detection in West Jilin using ETM+ images

Institute of Scientific and Technical Information of China (English)

Edward M.Osei,Jr.; ZHOU Yun-xuan

2004-01-01

In order to assess the information content and accuracy ofLandsat ETM+ digital images in land cover change detection,change-detection techniques of image differencing,normalized difference vegetation index,principal components analysis and tasseled-cap transformation were applied to yield 13 images. These images were thresholded into change and no change areas. The thresholded images were then checked in terms of various accuracies. The experiment results show that kappa coefficients of the 13 images range from 48.05 ～78.09. Different images do detect different types of changes. Images associated with changes in the near-infrared-reflectance or greenness detects crop-type changes and changes between vegetative and non-vegetative features. A unique means of using only Landsat imagery without reference data for the assessment of change in arid land are presented. Images of 12th June, 2000 and 2nd June, 2002 are used to validate the means. Analyses of standard accuracy and spatial agreement are performed to compare the new images (hereafter called "change images" ) representing the change between the two dates. Spatial agreement evaluates the conformity in the classified "change pixels" and "no-change pixels" at the same location on different change images and comprehensively examines the different techniques. This method would enable authorities to monitor land degradation efficiently and accurately.

Heuristics and representational change in two-move matchstick arithmetic tasks

Directory of Open Access Journals (Sweden)

Michael Öllinger

2006-01-01

Full Text Available Insight problems are problems where the problem solver struggles to find a solution until * aha! * the solution suddenly appears. Two contemporary theories suggest that insight problems are difficult either because problem solvers begin with an incorrect representation of the problem, or that problem solvers apply inappropriate heuristics to the problem. The relative contributions of representational change and inappropriate heuristics on the process of insight problem solving was studied with a task that required the problem solver to move two matchsticks in order to transform an incorrect arithmetic statement into a correct one. Problem solvers (N = 120 worked on two different types of two-move matchstick arithmetic problems that both varied with respect to the effectiveness of heuristics and to the degree of a necessary representational change of the problem representation. A strong influence of representational change on solution rates was found whereas the influence of heuristics hadminimal effects on solution rates. That is, the difficulty of insight problems within the two-move matchstick arithmetic domain is governed by the degree of representational change required. A model is presented that details representational change as the necessary condition for ensuring that appropriate heuristics can be applied on the proper problem representation.

When global rule reversal meets local task switching: The neural mechanisms of coordinated behavioral adaptation to instructed multi-level demand changes.

Science.gov (United States)

Shi, Yiquan; Wolfensteller, Uta; Schubert, Torsten; Ruge, Hannes

2018-02-01

Cognitive flexibility is essential to cope with changing task demands and often it is necessary to adapt to combined changes in a coordinated manner. The present fMRI study examined how the brain implements such multi-level adaptation processes. Specifically, on a "local," hierarchically lower level, switching between two tasks was required across trials while the rules of each task remained unchanged for blocks of trials. On a "global" level regarding blocks of twelve trials, the task rules could reverse or remain the same. The current task was cued at the start of each trial while the current task rules were instructed before the start of a new block. We found that partly overlapping and partly segregated neural networks play different roles when coping with the combination of global rule reversal and local task switching. The fronto-parietal control network (FPN) supported the encoding of reversed rules at the time of explicit rule instruction. The same regions subsequently supported local task switching processes during actual implementation trials, irrespective of rule reversal condition. By contrast, a cortico-striatal network (CSN) including supplementary motor area and putamen was increasingly engaged across implementation trials and more so for rule reversal than for nonreversal blocks, irrespective of task switching condition. Together, these findings suggest that the brain accomplishes the coordinated adaptation to multi-level demand changes by distributing processing resources either across time (FPN for reversed rule encoding and later for task switching) or across regions (CSN for reversed rule implementation and FPN for concurrent task switching). © 2017 Wiley Periodicals, Inc.

Non-linear laws of echoic memory and auditory change detection in humans

OpenAIRE

Inui, Koji; Urakawa, Tomokazu; Yamashiro, Koya; Otsuru, Naofumi; Nishihara, Makoto; Takeshima, Yasuyuki; Keceli, Sumru; Kakigi, Ryusuke

2010-01-01

Abstract Background The detection of any abrupt change in the environment is important to survival. Since memory of preceding sensory conditions is necessary for detecting changes, such a change-detection system relates closely to the memory system. Here we used an auditory change-related N1 subcomponent (change-N1) of event-related brain potentials to investigate cortical mechanisms underlying change detection and echoic memory. Results Change-N1 was elicited by a simple paradigm with two to...

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

Science.gov (United States)

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.

Detection of prospective memory deficits in mild cognitive impairment of suspected Alzheimer's disease etiology using a novel event-based prospective memory task.

LENUS (Irish Health Repository)

Blanco-Campal, Alberto

2009-01-01

We investigated the relative discriminatory efficacy of an event-based prospective memory (PM) task, in which specificity of the instructions and perceptual salience of the PM cue were manipulated, compared with two widely used retrospective memory (RM) tests (Rivermead Paragraph Recall Test and CERAD-Word List Test), when detecting mild cognitive impairment of suspected Alzheimer\\'s disease etiology (MCI-AD) (N = 19) from normal controls (NC) (N = 21). Statistical analyses showed high discriminatory capacity of the PM task for detecting MCI-AD. The Non-Specific-Non-Salient condition proved particularly useful in detecting MCI-AD, possibly reflecting the difficulty of the task, requiring more strategic attentional resources to monitor for the PM cue. With a cutoff score of <4\\/10, the Non-Specific-Non-Salient condition achieved a sensitivity = 84%, and a specificity = 95%, superior to the most discriminative RM test used (CERAD-Total Learning: sensitivity = 83%; specificity = 76%). Results suggest that PM is an early sign of memory failure in MCI-AD and may be a more pronounced deficit than retrospective failure, probably reflecting the greater self-initiated retrieval demands involved in the PM task used. Limitations include the relatively small sample size, and the use of a convenience sample (i.e. memory clinic attenders and healthy active volunteers), reducing the generalizability of the results, which should be regarded as preliminary. (JINS, 2009, 15, 154-159.).

Dual-task related gait changes in individuals with trans-tibial lower extremity amputation.

Science.gov (United States)

Hunter, Susan W; Frengopoulos, Courtney; Holmes, Jeffrey; Viana, Ricardo; Payne, Michael W C

2018-03-01

The improvement of gait and mobility are major rehabilitation goals following lower extremity amputations. However, when living in the community many daily activities require the multitasking of motor and cognitive tasks. The dual-task paradigm can be used to evaluate the concurrent performance of mobility and cognitive tasks. The purpose of this study was to evaluate the effects of dual-task gait testing in older adults with trans-tibial amputations. Twenty-four people (15 men, mean age ± SD, 62.72 ± 8.59) with trans-tibial amputation walked on an electronic walkway at i) self-selected comfortable pace and ii) self-selected comfortable pace while counting backwards by threes from a number randomly selected between 100 and 150. Cognitive performance, in the form of corrected response rate, was also evaluated as a single-task. The dual-task testing produced poorer performance in velocity (single-task = 58.15 ± 23.16 cm/s, dual-task = 50.92 ± 21.16 cm/s, p = 0.008), cadence (single-task = 76.65 ± 15.84 steps/min, dual-task = 67.85 ± 15.76 steps/min, p = 0.002) and stride time (single-task = 1094 ± 458.28 ms, dual-task = 1241.44 ± 513.73 ms, p = 0.005). Step length, stance time and single limb support time symmetry were also affected, such that less time was spent on the amputated limb during the dual-task testing. Dual-task testing demonstrated interference resulting in a poor performance in both gait and cognitive performance in trans-tibial amputees. Further research is suggested to evaluate the change in cognition-mobility effects over time and the relationship of this value to future adverse events such as falls and successful outcomes such as community ambulation and reintegration. Copyright © 2018 Elsevier B.V. All rights reserved.

Real-time change detection in data streams with FPGAs

International Nuclear Information System (INIS)

Vega, J.; Dormido-Canto, S.; Cruz, T.; Ruiz, M.; Barrera, E.; Castro, R.; Murari, A.; Ochando, M.

2014-01-01

Highlights: • Automatic recognition of changes in data streams of multidimensional signals. • Detection algorithm based on testing exchangeability on-line. • Real-time and off-line applicability. • Real-time implementation in FPGAs. - Abstract: The automatic recognition of changes in data streams is useful in both real-time and off-line data analyses. This article shows several effective change-detecting algorithms (based on martingales) and describes their real-time applicability in the data acquisition systems through the use of Field Programmable Gate Arrays (FPGA). The automatic event recognition system is absolutely general and it does not depend on either the particular event to detect or the specific data representation (waveforms, images or multidimensional signals). The developed approach provides good results for change detection in both the temporal evolution of profiles and the two-dimensional spatial distribution of volume emission intensity. The average computation time in the FPGA is 210 μs per profile

Task performance in astronomical adaptive optics

Science.gov (United States)

Barrett, Harrison H.; Myers, Kyle J.; Devaney, Nicholas; Dainty, J. C.; Caucci, Luca

2006-06-01

In objective or task-based assessment of image quality, figures of merit are defined by the performance of some specific observer on some task of scientific interest. This methodology is well established in medical imaging but is just beginning to be applied in astronomy. In this paper we survey the theory needed to understand the performance of ideal or ideal-linear (Hotelling) observers on detection tasks with adaptive-optical data. The theory is illustrated by discussing its application to detection of exoplanets from a sequence of short-exposure images.

Regularisation in multi- and hyperspectral remote sensing change detection

DEFF Research Database (Denmark)

Nielsen, Allan Aasbjerg

2005-01-01

Change detection methods for multi- and hypervariate data look for differences in data acquired over the same area at different points in time. These differences may be due to noise or differences in (atmospheric etc.) conditions at the two acquisition time points. To prevent a change detection m...

Single-task and dual-task tandem gait test performance after concussion.

Science.gov (United States)

Howell, David R; Osternig, Louis R; Chou, Li-Shan

2017-07-01

To compare single-task and dual-task tandem gait test performance between athletes after concussion with controls on observer-timed, spatio-temporal, and center-of-mass (COM) balance control measurements. Ten participants (19.0±5.5years) were prospectively identified and completed a tandem gait test protocol within 72h of concussion and again 1 week, 2 weeks, 1 month, and 2 months post-injury. Seven uninjured controls (20.0±4.5years) completed the same protocol in similar time increments. Tandem gait test trials were performed with (dual-task) and without (single-task) concurrently performing a cognitive test as whole-body motion analysis was performed. Outcome variables included test completion time, average tandem gait velocity, cadence, and whole-body COM frontal plane displacement. Concussion participants took significantly longer to complete the dual-task tandem gait test than controls throughout the first 2 weeks post-injury (mean time=16.4 [95% CI: 13.4-19.4] vs. 10.1 [95% CI: 6.4-13.7] seconds; p=0.03). Single-task tandem gait times were significantly lower 72h post-injury (p=0.04). Dual-task cadence was significantly lower for concussion participants than controls (89.5 [95% CI: 68.6-110.4] vs. 127.0 [95% CI: 97.4-156.6] steps/minute; p=0.04). Moderately-high to high correlations between tandem gait test time and whole-body COM medial-lateral displacement were detected at each time point during dual-task gait (r s =0.70-0.93; p=0.03-0.001). Adding a cognitive task during the tandem gait test resulted in longer detectable deficits post-concussion compared to the traditional single-task tandem gait test. As a clinical tool to assess dynamic motor function, tandem gait may assist with return to sport decisions after concussion. Copyright © 2017 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.

The Functional Task Test (FTT): An Interdisciplinary Testing Protocol to Investigate the Factors Underlying Changes in Astronaut Functional Performance

Science.gov (United States)

Bloomberg, J. J.; Lawrence, E. L.; Arzeno, N. M.; Buxton, R. E.; Feiveson, A. H.; Kofman, I. S.; Lee, S. M. C.; Mulavara, A. P.; Peters, B. T.; Platts. S. H.;

CHANGE DETECTION VIA SELECTIVE GUIDED CONTRASTING FILTERS

Directory of Open Access Journals (Sweden)

Y. V. Vizilter

2017-05-01

Full Text Available 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

Real-time changes in hippocampal energy demands during a spatial working memory task.

Science.gov (United States)

Kealy, John; Bennett, Rachel; Woods, Barbara; Lowry, John P

2017-05-30

Activity-dependent changes in hippocampal energy consumption have largely been determined using microdialysis. However, real-time recordings of brain energy consumption can be more accurately achieved using amperometric sensors, allowing for sensitive real-time monitoring of concentration changes. Here, we test the theory that systemic pre-treatment with glucose in rats prevents activity-dependent decreases in hippocampal glucose levels and thus enhances their performance in a spontaneous alternation task. Male Sprague Dawley rats were implanted into the hippocampus with either: 1) microdialysis probe; or 2) an oxygen sensor and glucose biosensor co-implanted together. Animals were pre-treated with either saline or glucose (250mg/kg) 30min prior to performing a single 20-min spontaneous alternation task in a +-maze. There were no significant differences found between either treatment group in terms of spontaneous alternation performance. Additionally, there was a significant difference found between treatment groups on hippocampal glucose levels measured using microdialysis (a decrease associated with glucose pre-treatment in control animals) but not amperometry. There were significant increases in hippocampal oxygen during +-maze exploration. Combining the findings from both methods, it appears that hippocampal activity in the spontaneous alternation task does not cause an increase in glucose consumption, despite an increase in regional cerebral blood flow (using oxygen supply as an index of blood flow) and, as such, pre-treatment with glucose does not enhance spontaneous alternation performance. Copyright © 2017 Elsevier B.V. All rights reserved.

Videogame training strategy-induced change in brain function during a complex visuomotor task.

Science.gov (United States)

Lee, Hyunkyu; Voss, Michelle W; Prakash, Ruchika Shaurya; Boot, Walter R; Vo, Loan T K; Basak, Chandramallika; Vanpatter, Matt; Gratton, Gabriele; Fabiani, Monica; Kramer, Arthur F

2012-07-01

Although changes in brain function induced by cognitive training have been examined, functional plasticity associated with specific training strategies is still relatively unexplored. In this study, we examined changes in brain function during a complex visuomotor task following training using the Space Fortress video game. To assess brain function, participants completed functional magnetic resonance imaging (fMRI) before and after 30 h of training with one of two training regimens: Hybrid Variable-Priority Training (HVT), with a focus on improving specific skills and managing task priority, or Full Emphasis Training (FET), in which participants simply practiced the game to obtain the highest overall score. Control participants received only 6 h of FET. Compared to FET, HVT learners reached higher performance on the game and showed less brain activation in areas related to visuo-spatial attention and goal-directed movement after training. Compared to the control group, HVT exhibited less brain activation in right dorsolateral prefrontal cortex (DLPFC), coupled with greater performance improvement. Region-of-interest analysis revealed that the reduction in brain activation was correlated with improved performance on the task. This study sheds light on the neurobiological mechanisms of improved learning from directed training (HVT) over non-directed training (FET), which is related to visuo-spatial attention and goal-directed motor planning, while separating the practice-based benefit, which is related to executive control and rule management. Copyright © 2012 Elsevier B.V. All rights reserved.

Sensitive change detection for remote sensing monitoring of nuclear treaties

DEFF Research Database (Denmark)

Canty, Morton J.; Nielsen, Allan Aasbjerg; Schlittenhardt, Jörg

2005-01-01

change is a commonplace application in remote sensing, the detection of anthropogenic changes associated with nuclear activities, whether declared or clandestine, presents a difficult challenge. It is necessary to discriminate subtle, often weak signals of interest on a background of irrelevant...... in multispectral, bitemporal image data: New approaches to change detection studies, Remote Sens. Environ. 64(1), 1998, pp. 1--19. Nielsen, A. A., Iteratively re-weighted multivariate alteration detection in multi- and hyperspectral data, to be published....

Changing scenes: memory for naturalistic events following change blindness.

Science.gov (United States)

Mäntylä, Timo; Sundström, Anna

2004-11-01

Research on scene perception indicates that viewers often fail to detect large changes to scene regions when these changes occur during a visual disruption such as a saccade or a movie cut. In two experiments, we examined whether this relative inability to detect changes would produce systematic biases in event memory. In Experiment 1, participants decided whether two successively presented images were the same or different, followed by a memory task, in which they recalled the content of the viewed scene. In Experiment 2, participants viewed a short video, in which an actor carried out a series of daily activities, and central scenes' attributes were changed during a movie cut. A high degree of change blindness was observed in both experiments, and these effects were related to scene complexity (Experiment 1) and level of retrieval support (Experiment 2). Most important, participants reported the changed, rather than the initial, event attributes following a failure in change detection. These findings suggest that attentional limitations during encoding contribute to biases in episodic memory.

Hardware accelerator design for change detection in smart camera

Science.gov (United States)

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

2011-10-01

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

Change-Point Detection Method for Clinical Decision Support System Rule Monitoring.

Science.gov (United States)

Liu, Siqi; Wright, Adam; Hauskrecht, Milos

2017-06-01

A clinical decision support system (CDSS) and its components can malfunction due to various reasons. Monitoring the system and detecting its malfunctions can help one to avoid any potential mistakes and associated costs. In this paper, we investigate the problem of detecting changes in the CDSS operation, in particular its monitoring and alerting subsystem, by monitoring its rule firing counts. The detection should be performed online, that is whenever a new datum arrives, we want to have a score indicating how likely there is a change in the system. We develop a new method based on Seasonal-Trend decomposition and likelihood ratio statistics to detect the changes. Experiments on real and simulated data show that our method has a lower delay in detection compared with existing change-point detection methods.

Visual mismatch negativity indicates automatic, task-independent detection of artistic image composition in abstract artworks.

Science.gov (United States)

Menzel, Claudia; Kovács, Gyula; Amado, Catarina; Hayn-Leichsenring, Gregor U; Redies, Christoph

2018-05-06

In complex abstract art, image composition (i.e., the artist's deliberate arrangement of pictorial elements) is an important aesthetic feature. We investigated whether the human brain detects image composition in abstract artworks automatically (i.e., independently of the experimental task). To this aim, we studied whether a group of 20 original artworks elicited a visual mismatch negativity when contrasted with a group of 20 images that were composed of the same pictorial elements as the originals, but in shuffled arrangements, which destroy artistic composition. We used a passive oddball paradigm with parallel electroencephalogram recordings to investigate the detection of image type-specific properties. We observed significant deviant-standard differences for the shuffled and original images, respectively. Furthermore, for both types of images, differences in amplitudes correlated with the behavioral ratings of the images. In conclusion, we show that the human brain can detect composition-related image properties in visual artworks in an automatic fashion. Copyright © 2018 Elsevier B.V. All rights reserved.

DOCUMENTATION AND DETECTION OF COLOUR CHANGES OF BAS RELIEVES USING CLOSE RANGE PHOTOGRAMMETRY

Directory of Open Access Journals (Sweden)

E. S. Malinverni

2017-05-01

Full Text Available The digitization of complex buildings, findings or bas relieves can strongly facilitate the work of archaeologists, mainly for in depth analysis tasks. Notwithstanding, whether new visualization techniques ease the study phase, a classical naked-eye approach for determining changes or surface alteration could bring towards several drawbacks. The research work described in these pages is aimed at providing experts with a workflow for the evaluation of alterations (e.g. color decay or surface alterations, allowing a more rapid and objective monitoring of monuments. More in deep, a pipeline of work has been tested in order to evaluate the color variation between surfaces acquired at different époques. The introduction of reliable tools of change detection in the archaeological domain is needful; in fact, the most widespread practice, among archaeologists and practitioners, is to perform a traditional monitoring of surfaces that is made of three main steps: production of a hand-made map based on a subjective analysis, selection of a sub-set of regions of interest, removal of small portion of surface for in depth analysis conducted in laboratory. To overcome this risky and time consuming process, digital automatic change detection procedure represents a turning point. To do so, automatic classification has been carried out according to two approaches: a pixel-based and an object-based method. Pixel-based classification aims to identify the classes by means of the spectral information provided by each pixel belonging to the original bands. The object-based approach operates on sets of pixels (objects/regions grouped together by means of an image segmentation technique. The methodology was tested by studying the bas-relieves of a temple located in Peru, named Huaca de la Luna. Despite the data sources were collected with unplanned surveys, the workflow proved to be a valuable solution useful to understand which are the main changes over time.

Documentation and Detection of Colour Changes of Bas Relieves Using Close Range Photogrammetry

Science.gov (United States)

Malinverni, E. S.; Pierdicca, R.; Sturari, M.; Colosi, F.; Orazi, R.

2017-05-01

The digitization of complex buildings, findings or bas relieves can strongly facilitate the work of archaeologists, mainly for in depth analysis tasks. Notwithstanding, whether new visualization techniques ease the study phase, a classical naked-eye approach for determining changes or surface alteration could bring towards several drawbacks. The research work described in these pages is aimed at providing experts with a workflow for the evaluation of alterations (e.g. color decay or surface alterations), allowing a more rapid and objective monitoring of monuments. More in deep, a pipeline of work has been tested in order to evaluate the color variation between surfaces acquired at different époques. The introduction of reliable tools of change detection in the archaeological domain is needful; in fact, the most widespread practice, among archaeologists and practitioners, is to perform a traditional monitoring of surfaces that is made of three main steps: production of a hand-made map based on a subjective analysis, selection of a sub-set of regions of interest, removal of small portion of surface for in depth analysis conducted in laboratory. To overcome this risky and time consuming process, digital automatic change detection procedure represents a turning point. To do so, automatic classification has been carried out according to two approaches: a pixel-based and an object-based method. Pixel-based classification aims to identify the classes by means of the spectral information provided by each pixel belonging to the original bands. The object-based approach operates on sets of pixels (objects/regions) grouped together by means of an image segmentation technique. The methodology was tested by studying the bas-relieves of a temple located in Peru, named Huaca de la Luna. Despite the data sources were collected with unplanned surveys, the workflow proved to be a valuable solution useful to understand which are the main changes over time.

Behavioral sensitivity of Japanese children with and without ADHD to changing reinforcer availability: an experimental study using signal detection methodology.

Science.gov (United States)

Furukawa, Emi; Shimabukuro, Shizuka; Alsop, Brent; Tripp, Gail

2017-09-25

Most research on motivational processes in attention deficit hyperactivity disorder (ADHD) has been undertaken in Western Europe and North America. The extent to which these findings apply to other cultural groups is unclear. The current study evaluated the behavioral sensitivity of Japanese children with and without ADHD to changing reward availability. Forty-one school-aged children, 19 diagnosed with DSM-IV ADHD, completed a signal-detection task in which correct discriminations between two stimuli were associated with different reinforcement frequencies. The response alternative associated with the higher rate of reinforcement switched twice during the task without warning. Both groups of children developed an initial bias toward the more frequently reinforced response alternative. When the reward contingencies switched the response allocation (bias) of the control group children followed suit. The response bias scores of the children with ADHD did not, suggesting impaired tracking of reward availability over time. Japanese children with ADHD adjust their behavioral responses to changing reinforcer availability less than their typically developing peers. This is not explained by poor attention to task or a lack of sensitivity to reward. The current results are consistent with altered sensitivity to changing reward contingencies identified in non-Japanese samples of children with ADHD. Irrespective of their country of origin, children with ADHD will likely benefit from behavioral expectations and reinforcement contingencies being made explicit together with high rates of reinforcement for appropriate behaviors.

One new method for road data shape change detection

Science.gov (United States)

Tang, Luliang; Li, Qingquan; Xu, Feng; Chang, Xiaomeng

2009-10-01

Similarity is a psychological cognition; this paper defines the Difference Distance and puts forward the Similarity Measuring Model for linear spatial data (SMM-L) based on the integration of the Distance View and the Feature Set View which are the views for similarity cognition. Based on the study of the relationship between the spatial data change and the similarity, a change detection algorithm for linear spatial data is developed, and a test on road data change detection is realized.

Total least squares for anomalous change detection

Science.gov (United States)

Theiler, James; Matsekh, Anna M.

2010-04-01

A family of subtraction-based anomalous change detection algorithms is derived from a total least squares (TLSQ) framework. This provides an alternative to the well-known chronochrome algorithm, which is derived from ordinary least squares. In both cases, the most anomalous changes are identified with the pixels that exhibit the largest residuals with respect to the regression of the two images against each other. The family of TLSQbased anomalous change detectors is shown to be equivalent to the subspace RX formulation for straight anomaly detection, but applied to the stacked space. However, this family is not invariant to linear coordinate transforms. On the other hand, whitened TLSQ is coordinate invariant, and special cases of it are equivalent to canonical correlation analysis and optimized covariance equalization. What whitened TLSQ offers is a generalization of these algorithms with the potential for better performance.

Detecting land cover change using a sliding window temporal autocorrelation approach

CSIR Research Space (South Africa)

Kleynhans, W

2012-07-01

Full Text Available There has been recent developments in the use of hypertemporal satellite time series data for land cover change detection and classification. Recently, an Autocorrelation function (ACF) change detection method was proposed to detect the development...

Abnormal global and local event detection in compressive sensing domain

Science.gov (United States)

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.

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

Science.gov (United States)

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

Multiscale Region-Level VHR Image Change Detection via Sparse Change Descriptor and Robust Discriminative Dictionary Learning

Directory of Open Access Journals (Sweden)

Yuan Xu

2015-01-01

Full Text Available Very high resolution (VHR image change detection is challenging due to the low discriminative ability of change feature and the difficulty of change decision in utilizing the multilevel contextual information. Most change feature extraction techniques put emphasis on the change degree description (i.e., in what degree the changes have happened, while they ignore the change pattern description (i.e., how the changes changed, which is of equal importance in characterizing the change signatures. Moreover, the simultaneous consideration of the classification robust to the registration noise and the multiscale region-consistent fusion is often neglected in change decision. To overcome such drawbacks, in this paper, a novel VHR image change detection method is proposed based on sparse change descriptor and robust discriminative dictionary learning. Sparse change descriptor combines the change degree component and the change pattern component, which are encoded by the sparse representation error and the morphological profile feature, respectively. Robust change decision is conducted by multiscale region-consistent fusion, which is implemented by the superpixel-level cosparse representation with robust discriminative dictionary and the conditional random field model. Experimental results confirm the effectiveness of the proposed change detection technique.

The neural basis of task switching changes with skill acquisition

Directory of Open Access Journals (Sweden)

Koji eJimura

2014-05-01

Full Text Available Learning novel skills involves reorganization and optimization of cognitive processing involving a broad network of brain regions. Previous work has shown asymmetric costs of switching to a well-trained task versus a poorly-trained task, but the neural basis of these differential switch costs is unclear. The current study examined the neural signature of task switching in the context of acquisition of new skill. Human participants alternated randomly between a novel visual task (mirror-reversed word reading and a highly practiced one (plain word reading, allowing the isolation of task switching and skill set maintenance. Two scan sessions were separated by two weeks, with behavioral training on the mirror reading task in between the two sessions. Broad cortical regions, including bilateral prefrontal, parietal, and extrastriate cortices, showed decreased activity associated with learning of the mirror reading skill. In contrast, learning to switch to the novel skill was associated with decreased activity in a focal subcortical region in the dorsal striatum. Switching to the highly practiced task was associated with a non-overlapping set of regions, suggesting substantial differences in the neural substrates of switching as a function of task skill. Searchlight multivariate pattern analysis also revealed that learning was associated with decreased pattern information for mirror versus plain reading tasks in fronto-parietal regions. Inferior frontal junction and posterior parietal cortex showed a joint effect of univariate activation and pattern information. These results suggest distinct learning mechanisms task performance and executive control as a function of learning.

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

Science.gov (United States)

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.

CHANGE DETECTION BASED ON PERSISTENT SCATTERER INTERFEROMETRY – A NEW METHOD OF MONITORING BUILDING CHANGES

Directory of Open Access Journals (Sweden)

C. H. Yang

2016-06-01

Full Text Available Persistent Scatterer Interferometry (PSI is a technique to detect a network of extracted persistent scatterer (PS points which feature temporal phase stability and strong radar signal throughout time-series of SAR images. The small surface deformations on such PS points are estimated. PSI particularly works well in monitoring human settlements because regular substructures of man-made objects give rise to large number of PS points. If such structures and/or substructures substantially alter or even vanish due to big change like construction, their PS points are discarded without additional explorations during standard PSI procedure. Such rejected points are called big change (BC points. On the other hand, incoherent change detection (ICD relies on local comparison of multi-temporal images (e.g. image difference, image ratio to highlight scene modifications of larger size rather than detail level. However, image noise inevitably degrades ICD accuracy. We propose a change detection approach based on PSI to synergize benefits of PSI and ICD. PS points are extracted by PSI procedure. A local change index is introduced to quantify probability of a big change for each point. We propose an automatic thresholding method adopting change index to extract BC points along with a clue of the period they emerge. In the end, PS ad BC points are integrated into a change detection image. Our method is tested at a site located around north of Berlin main station where steady, demolished, and erected building substructures are successfully detected. The results are consistent with ground truth derived from time-series of aerial images provided by Google Earth. In addition, we apply our technique for traffic infrastructure, business district, and sports playground monitoring.

Detection of cardiac activity changes from human speech

Science.gov (United States)

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

2015-05-01

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

Cortical dynamics of visual change detection based on sensory memory.

Science.gov (United States)

Urakawa, Tomokazu; Inui, Koji; Yamashiro, Koya; Tanaka, Emi; Kakigi, Ryusuke

2010-08-01

Detecting a visual change was suggested to relate closely to the visual sensory memory formed by visual stimuli before the occurrence of the change, because change detection involves identifying a difference between ongoing and preceding sensory conditions. Previous neuroimaging studies showed that an abrupt visual change activates the middle occipital gyrus (MOG). However, it still remains to be elucidated whether the MOG is related to visual change detection based on sensory memory. Here we tried to settle this issue using a new method of stimulation with blue and red LEDs to emphasize a memory-based change detection process. There were two stimuli, a standard trial stimulus and a deviant trial stimulus. The former was a red light lasting 500 ms, and the latter was a red light lasting 250 ms immediately followed by a blue light lasting 250 ms. Effects of the trial-trial interval, 250 approximately 2000 ms, were investigated to know how cortical responses to the abrupt change (from red to blue) were affected by preceding conditions. The brain response to the deviant trial stimulus was recorded by magnetoencephalography. Results of a multi-dipole analysis showed that the activity in the MOG, peaking at around 150 ms after the change onset, decreased in amplitude as the interval increased, but the earlier activity in BA 17/18 was not affected by the interval. These results suggested that the MOG is an important cortical area relating to the sensory memory-based visual change-detecting system. Copyright 2010 Elsevier Inc. All rights reserved.

Strategic Adaptation to Task Characteristics, Incentives, and Individual Differences in Dual-Tasking.

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Christian P Janssen

Full Text Available We investigate how good people are at multitasking by comparing behavior to a prediction of the optimal strategy for dividing attention between two concurrent tasks. In our experiment, 24 participants had to interleave entering digits on a keyboard with controlling a randomly moving cursor with a joystick. The difficulty of the tracking task was systematically varied as a within-subjects factor. Participants were also exposed to different explicit reward functions that varied the relative importance of the tracking task relative to the typing task (between-subjects. Results demonstrate that these changes in task characteristics and monetary incentives, together with individual differences in typing ability, influenced how participants choose to interleave tasks. This change in strategy then affected their performance on each task. A computational cognitive model was used to predict performance for a wide set of alternative strategies for how participants might have possibly interleaved tasks. This allowed for predictions of optimal performance to be derived, given the constraints placed on performance by the task and cognition. A comparison of human behavior with the predicted optimal strategy shows that participants behaved near optimally. Our findings have implications for the design and evaluation of technology for multitasking situations, as consideration should be given to the characteristics of the task, but also to how different users might use technology depending on their individual characteristics and their priorities.

TOWARDS CHANGE DETECTION IN URBAN AREA BY SAR INTERFEROMETRY AND RADARGRAMMETRY

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C. Dubois

2013-04-01

Full Text Available Change detection in urban area is an active topic in remote sensing. However, well-dealt subject in optical remote sensing, this research topic is still at an early stage and needs deeper investigations and improvement in what concerns SAR and InSAR remote sensing. Due to their weather and daylight-independency, SAR sensors allow an all-time observation of the earth. This is determining in cases where rapid change detection is required after a natural – or technological – disaster. Due to the high resolution that can be achieved, the new generation of space-borne radar sensors opens up new perspectives for analysing buildings in urban areas. Moreover, due to their short revisiting cycle, they give rise to monitoring and change detection applications. In this paper, we present a concept for change detection in urban area at building level, relying only on SAR- and InSAR data. In this approach, interferometric and radargrammetric SAR data are merged in order to detect changes. Here, we present the overall workflow, the test area, the required data as well as first findings on the best-suited stereo-configurations for change detection.

Detecting changes during pregnancy with Raman spectroscopy

Science.gov (United States)

Vargis, Elizabeth; Robertson, Kesha; Al-Hendy, Ayman; Reese, Jeff; Mahadevan-Jansen, Anita

2010-02-01

Preterm labor is the second leading cause of neonatal mortality and leads to a myriad of complications like delayed development and cerebral palsy. Currently, there is no way to accurately predict preterm labor, making its prevention and treatment virtually impossible. While there are some at-risk patients, over half of all preterm births do not fall into any high-risk category. This study seeks to predict and prevent preterm labor by using Raman spectroscopy to detect changes in the cervix during pregnancy. Since Raman spectroscopy has been used to detect cancers in vivo in organs like the cervix and skin, it follows that spectra will change over the course of pregnancy. Previous studies have shown that fluorescence decreased during pregnancy and increased during post-partum exams to pre-pregnancy levels. We believe significant changes will occur in the Raman spectra obtained during the course of pregnancy. In this study, Raman spectra from the cervix of pregnant mice and women will be acquired. Specific changes that occur due to cervical softening or changes in hormonal levels will be observed to understand the likelihood that a female mouse or a woman will enter labor.

In-vitro studies of change in edge detection with changes in bone density

International Nuclear Information System (INIS)

Pocock, N.; Noakes, K.; Griffiths, M.

1999-01-01

Full text: Dual energy X-ray absorptiometry (DXA) requires edge detection software to identify the skeletal regions for quantitation of bone mineral density (BMD) and bone mineral content (BMC). As bone mass decreases, the detection of bone edges becomes more difficult and this potentially could cause errors in DXA estimations of areal BMD or BMC. To address this issue, we have used an in-vitro model to study the effects of 'bone loss' on calculated bone area, BMD and BMC. Multiple vertebral phantoms, of equal cross-sectional area but incrementally decreased areal BMD, were constructed using calcium sulphate hemihydrate. The weight of each phantom vertebra, measured accurately using an electronic balance, was used as an index of its true 'bone mass equivalent' (BME). The phantoms were scanned and analysed in the lumbar spine mode using a Lunar DPX-L (L) and Hologic QDR-1000 (H). The changes in BME were compared to changes in measured area, BMC and areal BMD. The results demonstrate that, in an in-vitro model, as bone mass decreases, measured bone area and consequently BMC will decrease as the edge detection algorithms have greater difficulty in detecting the true edges. In conclusion, in an in-vitro model, the DXA edge detection algorithms will underestimate bone area as bone mass decreases. This has potential implications for monitoring changes in bone mass in vivo

CHANGE@CERN:Task Force 1: finding the least painful cuts

CERN Multimedia

2002-01-01

This week sees the first in our series of reports on the work of the Task Forces By 2004, COMPASS will be the main experiment at the SPS, but the LHC experiments will also be calibrating detectors. 'It was a painful task, with which we had to proceed in the least damaging way', says Dieter Schlatter, Head of the EP Division, when describing his experience as Convenor of Task Force 1. This Task Force was charged with responsibility for advising on how money could be saved within CERN's research programme, in order to help deal with the increased cost to completion of the LHC project. Their role, as with the other Task Forces, was to suggest where savings could be made, and in most cases their suggestions have been incorporated in the Management's draft Long Term Plan. The pain of the task was to some extent alleviated by developments within the LHC project itself. Delays in the delivery of superconducting cable meant that the start up of the LHC would be delayed by a year, to 2007, and this gave Task Force ...

a Landsat Time-Series Stacks Model for Detection of Cropland Change

Science.gov (United States)

Chen, J.; Chen, J.; Zhang, J.

2017-09-01

Global, timely, accurate and cost-effective cropland monitoring with a fine spatial resolution will dramatically improve our understanding of the effects of agriculture on greenhouse gases emissions, food safety, and human health. Time-series remote sensing imagery have been shown particularly potential to describe land cover dynamics. The traditional change detection techniques are often not capable of detecting land cover changes within time series that are severely influenced by seasonal difference, which are more likely to generate pseuso changes. Here,we introduced and tested LTSM ( Landsat time-series stacks model), an improved Continuous Change Detection and Classification (CCDC) proposed previously approach to extract spectral trajectories of land surface change using a dense Landsat time-series stacks (LTS). The method is expected to eliminate pseudo changes caused by phenology driven by seasonal patterns. The main idea of the method is that using all available Landsat 8 images within a year, LTSM consisting of two term harmonic function are estimated iteratively for each pixel in each spectral band .LTSM can defines change area by differencing the predicted and observed Landsat images. The LTSM approach was compared with change vector analysis (CVA) method. The results indicated that the LTSM method correctly detected the "true change" without overestimating the "false" one, while CVA pointed out "true change" pixels with a large number of "false changes". The detection of change areas achieved an overall accuracy of 92.37 %, with a kappa coefficient of 0.676.

Observer efficiency in free-localization tasks with correlated noise

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Craig eAbbey

2014-05-01

Full Text Available The efficiency of visual tasks involving localization has traditionally been evaluated using forced choice experiments that capitalize on independence across locations to simplify the performance of the ideal observer. However, developments in ideal observer analysis have shown how an ideal observer can be defined for free-localization tasks, where a target can appear anywhere in a defined search region and subjects respond by localizing the target. Since these tasks are representative of many real-world search tasks, it is of interest to evaluate the efficiency of observer performance in them. The central question of this work is whether humans are able to effectively use the information in a free-localization task relative to a similar task where target location is fixed. We use a yes-no detection task at a cued location as the reference for this comparison. Each of the tasks is evaluated using a Gaussian target profile embedded in four different Gaussian noise backgrounds having power-law noise power spectra with exponents ranging from 0 to 3. The free localization task had a square 6.7° search region. We report on two follow-up studies investigating efficiency in a detect-and-localize task, and the effect of processing the white-noise backgrounds. In the fixed-location detection task, we find average observer efficiency ranges from 35% to 59% for the different noise backgrounds. Observer efficiency improves dramatically in the tasks involving localization, ranging from 63% to 82% in the forced localization tasks and from 78% to 92% in the detect-and- localize tasks. Performance in white noise, the lowest efficiency condition, was improved by filtering to give them a power-law exponent of 2. Classification images, used to examine spatial frequency weights for the tasks, show better tuning to ideal weights in the free-localization tasks. The high absolute levels of efficiency suggest that observers are well-adapted to free-localization tasks.

Changing societies and four tasks of schooling: Challenges for strongly differentiated educational systems

Science.gov (United States)

van de Werfhorst, Herman G.

2014-05-01

Changing labour markets, increased calls for selection and excellence, and increased diversity and individualisation have repercussions on how educational systems can prepare youth for work, optimise knowledge production, achieve equality of opportunity, and socialise students into active civic engagement. This paper discusses four central tasks of schooling and examines to what extent societal developments challenge education policy to deliver on the tasks at hand. Particular attention is given to the challenges Europe's strongly diversified educational systems are currently facing. Both the Netherlands and Germany, for example, have been offering vocationally-oriented pathways alongside traditional academic higher education for some time. But today's ongoing changes in job descriptions, mainly due to ever-accelerating technological developments, are causing a risk of skills obsolescence which can only be avoided by continuous upskilling and/or reskilling of a sufficiently flexible workforce. Overcoming differences of intelligence as well as differences of diverse socioeconomic, ethnic and linguistic backgrounds by way of education is another challenge, as is fostering "soft" skills and political awareness. This paper investigates the effectiveness of current education systems in preparing citizens for a functioning modern society.

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

Science.gov (United States)

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

2016-12-01

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

Change Best.Task 2.1. National Report on the Energy Efficiency Service Business in Italy

International Nuclear Information System (INIS)

Sabbatucci, N.; Labanca, N.

2009-05-01

The aim of the Change Best project is to promote the development of an energy efficiency service (EES) market and to give good practice examples of changes in energy service business, strategies, and supportive policies and measures in the course of the implementation of Directive 2006/32/EC on Energy End-Use Efficiency and Energy Services. This report addresses Task 2.1: National Report on the Energy Efficiency Service Business in Italy. More information can be found on the website of Change Best at www.changebest.eu.

Self-adaptive change detection in streaming data with non-stationary distribution

KAUST Repository

Zhang, Xiangliang

2010-01-01

Non-stationary distribution, in which the data distribution evolves over time, is a common issue in many application fields, e.g., intrusion detection and grid computing. Detecting the changes in massive streaming data with a non-stationary distribution helps to alarm the anomalies, to clean the noises, and to report the new patterns. In this paper, we employ a novel approach for detecting changes in streaming data with the purpose of improving the quality of modeling the data streams. Through observing the outliers, this approach of change detection uses a weighted standard deviation to monitor the evolution of the distribution of data streams. A cumulative statistical test, Page-Hinkley, is employed to collect the evidence of changes in distribution. The parameter used for reporting the changes is self-adaptively adjusted according to the distribution of data streams, rather than set by a fixed empirical value. The self-adaptability of the novel approach enhances the effectiveness of modeling data streams by timely catching the changes of distributions. We validated the approach on an online clustering framework with a benchmark KDDcup 1999 intrusion detection data set as well as with a real-world grid data set. The validation results demonstrate its better performance on achieving higher accuracy and lower percentage of outliers comparing to the other change detection approaches. © 2010 Springer-Verlag.

Using adversary text to detect adversary phase changes.

Energy Technology Data Exchange (ETDEWEB)

Speed, Ann Elizabeth; Doser, Adele Beatrice; Warrender, Christina E.

2009-05-01

The purpose of this work was to help develop a research roadmap and small proof ofconcept for addressing key problems and gaps from the perspective of using text analysis methods as a primary tool for detecting when a group is undergoing a phase change. Self- rganizing map (SOM) techniques were used to analyze text data obtained from the tworld-wide web. Statistical studies indicate that it may be possible to predict phase changes, as well as detect whether or not an example of writing can be attributed to a group of interest.

Changes in intervertebral disk dimensions after a loading task and the relationship with stature change measurements.

Science.gov (United States)

Lewis, Sandra E; Fowler, Neil E

2009-10-01

Lewis SE, Fowler NE. Changes in intervertebral disk dimensions after a loading task and the relationship with stature change measurements. To test the hypothesis that there would be a linear relationship between overall stature change determined by stadiometry and markers of lumbar disk height loss determined from magnetic resonance imaging (MRI). The short-term loading response of the lumbar spine was evaluated with both stadiometry and MRI, using a within-subject repeated-measures design. Measures were obtained both before and after 15 minutes of walking wearing a weighted vest (20% of body mass). Stature loss measured on the stadiometer was compared with change in lumbar spine length assessed from the MRI images. A university laboratory. Participants (N=13; mean age +/- SD, 28.5+/-5.2y; mean height +/- SD, 1.76+/-0.10m; mean body mass +/- SD, 76.6+/-14.9kg) were invited to take part in the investigation. The group was mixed (9 men, 4 women) and comprised people with no history of low back pain. Not applicable. Lumbar spine length assessed via MRI and stature change measured via stadiometry. A significant height loss was observed over the complete lumbar spine (Pstature loss (r=.61). The results were supportive of the use of stadiometry as an indirect measure of changes in intervertebral disk height.

Removing Parallax-Induced False Changes in Change Detection

Science.gov (United States)

2014-03-27

Teller , “Equation of state calculations by fast computing machines ,” The Journal of Chemical Physics, vol. 21, no. 6, pp. 1087–1092, 1953. [89] J. D’Errico...especially in the case of HS data, due to its hundreds of spectral channels. Therefore, there is a strong need for methodologies that enable automated ...researchers for many years due in large part to the number of applications across diverse disciplines. Automated image change detection (CD) is the

Automated Change Detection for Validation and Update of Geodata

DEFF Research Database (Denmark)

Olsen, Brian Pilemann; Knudsen, Thomas

)is presented. Height information is used to determine the location of object which stands above terrain, and the CIR-Imagery is used to exclude vegetation, leading to a potential buildings mask. Comparing the existing objects in the map database with these extracted objects leads to a validation of the map...... to newer (raster based) remote sensing images in order to detect changes in objects. In this paper an automatic change detection method considering changes in the building theme and based on colourinfrared (CIR) aerial photographs in combination with height information (LIDAR, digital photogrammetry...

Individual tree crown modeling and change detection from airborne lidar data

NARCIS (Netherlands)

Xiao, W.; Xu, Sudan; Oude Elberink, S.J.; Vosselman, G.

2016-01-01

Light detection and ranging (lidar) provides a promising way of detecting changes of trees in three-dimensional (3-D) because laser beams can penetrate through the foliage and therefore provide full coverage of trees. The aim is to detect changes in trees in urban areas using multitemporal airborne

Correlation between model observers in uniform background and human observers in patient liver background for a low-contrast detection task in CT

Science.gov (United States)

Gong, Hao; Yu, Lifeng; Leng, Shuai; Dilger, Samantha; Zhou, Wei; Ren, Liqiang; McCollough, Cynthia H.

2018-03-01

Channelized Hotelling observer (CHO) has demonstrated strong correlation with human observer (HO) in both single-slice viewing mode and multi-slice viewing mode in low-contrast detection tasks with uniform background. However, it remains unknown if the simplest single-slice CHO in uniform background can be used to predict human observer performance in more realistic tasks that involve patient anatomical background and multi-slice viewing mode. In this study, we aim to investigate the correlation between CHO in a uniform water background and human observer performance at a multi-slice viewing mode on patient liver background for a low-contrast lesion detection task. The human observer study was performed on CT images from 7 abdominal CT exams. A noise insertion tool was employed to synthesize CT scans at two additional dose levels. A validated lesion insertion tool was used to numerically insert metastatic liver lesions of various sizes and contrasts into both phantom and patient images. We selected 12 conditions out of 72 possible experimental conditions to evaluate the correlation at various radiation doses, lesion sizes, lesion contrasts and reconstruction algorithms. CHO with both single and multi-slice viewing modes were strongly correlated with HO. The corresponding Pearson's correlation coefficient was 0.982 (with 95% confidence interval (CI) [0.936, 0.995]) and 0.989 (with 95% CI of [0.960, 0.997]) in multi-slice and single-slice viewing modes, respectively. Therefore, this study demonstrated the potential to use the simplest single-slice CHO to assess image quality for more realistic clinically relevant CT detection tasks.

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

Science.gov (United States)

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.

Training-induced improvement of response selection and error detection in aging assessed by task switching: effects of cognitive, physical, and relaxation training.

Science.gov (United States)

Gajewski, Patrick D; Falkenstein, Michael

2012-01-01

Cognitive control functions decline with increasing age. The present study examines if different types of group-based and trainer-guided training effectively enhance performance of older adults in a task switching task, and how this expected enhancement is reflected in changes of cognitive functions, as measured in electrophysiological brain activity (event-related potentials). One hundred forty-one healthy participants aged 65 years and older were randomly assigned to one of four groups: physical training (combined aerobic and strength training), cognitive training (paper-pencil and computer-aided), relaxation and wellness (social control group), and a control group that did not receive any intervention. Training sessions took place twice a week for 90 min for a period of 4 months. The results showed a greater improvement of performance for attendants of the cognitive training group compared to the other groups. This improvement was evident in a reduction of mixing costs in accuracy and intraindividual variability of speed, indexing improved maintenance of multiple task sets in working memory, and an enhanced coherence of neuronal processing. These findings were supported by event-related brain potentials which showed higher amplitudes in a number of potentials associated with response selection (N2), allocation of cognitive resources (P3b), and error detection (Ne). Taken together, our findings suggest neurocognitive plasticity of aging brains which can be stimulated by broad and multilayered cognitive training and assessed in detail by electrophysiological methods.

Abnormal global and local event detection in compressive sensing domain

Directory of Open Access Journals (Sweden)

Tian Wang

2018-05-01

Full Text Available 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.

Mild Depression Detection of College Students: an EEG-Based Solution with Free Viewing Tasks.

Science.gov (United States)

Li, Xiaowei; Hu, Bin; Shen, Ji; Xu, Tingting; Retcliffe, Martyn

2015-12-01

Depression is a common mental disorder with growing prevalence; however current diagnoses of depression face the problem of patient denial, clinical experience and subjective biases from self-report. By using a combination of linear and nonlinear EEG features in our research, we aim to develop a more accurate and objective approach to depression detection that supports the process of diagnosis and assists the monitoring of risk factors. By classifying EEG features during free viewing task, an accuracy of 99.1%, which is the highest to our knowledge by far, was achieved using kNN classifier to discriminate depressed and non-depressed subjects. Furthermore, through correlation analysis, comparisons of performance on each electrode were discussed on the availability of single channel EEG recording depression detection system. Combined with wearable EEG collecting devices, our method offers the possibility of cost effective wearable ubiquitous system for doctors to monitor their patients with depression, and for normal people to understand their mental states in time.

Expertise with unfamiliar objects is flexible to changes in task but not changes in class.

Directory of Open Access Journals (Sweden)

Rachel A Searston

Full Text Available Perceptual expertise is notoriously specific and bound by familiarity; generalizing to novel or unfamiliar images, objects, identities, and categories often comes at some cost to performance. In forensic and security settings, however, examiners are faced with the task of discriminating unfamiliar images of unfamiliar objects within their general domain of expertise (e.g., fingerprints, faces, or firearms. The job of a fingerprint expert, for instance, is to decide whether two unfamiliar fingerprint images were left by the same unfamiliar finger (e.g., Smith's left thumb, or two different unfamiliar fingers (e.g., Smith and Jones's left thumb. Little is known about the limits of this kind of perceptual expertise. Here, we examine fingerprint experts' and novices' ability to distinguish fingerprints compared to inverted faces in two different tasks. Inverted face images serve as an ideal comparison because they vary naturally between and within identities, as do fingerprints, and people tend to be less accurate or more novice-like at distinguishing faces when they are presented in an inverted or unfamiliar orientation. In Experiment 1, fingerprint experts outperformed novices in locating categorical fingerprint outliers (i.e., a loop pattern in an array of whorls, but not inverted face outliers (i.e., an inverted male face in an array of inverted female faces. In Experiment 2, fingerprint experts were more accurate than novices at discriminating matching and mismatching fingerprints that were presented very briefly, but not so for inverted faces. Our data show that perceptual expertise with fingerprints can be flexible to changing task demands, but there can also be abrupt limits: fingerprint expertise did not generalize to an unfamiliar class of stimuli. We interpret these findings as evidence that perceptual expertise with unfamiliar objects is highly constrained by one's experience.

LANDSAT-8 OPERATIONAL LAND IMAGER CHANGE DETECTION ANALYSIS

Directory of Open Access Journals (Sweden)

W. Pervez

2017-05-01

Full Text Available This paper investigated the potential utility of Landsat-8 Operational Land Imager (OLI for change detection analysis and mapping application because of its superior technical design to previous Landsat series. The OLI SVM classified data was successfully classified with regard to all six test classes (i.e., bare land, built-up land, mixed trees, bushes, dam water and channel water. OLI support vector machine (SVM classified data for the four seasons (i.e., spring, autumn, winter, and summer was used to change detection results of six cases: (1 winter to spring which resulted reduction in dam water mapping and increases of bushes; (2 winter to summer which resulted reduction in dam water mapping and increase of vegetation; (3 winter to autumn which resulted increase in dam water mapping; (4 spring to summer which resulted reduction of vegetation and shallow water; (5 spring to autumn which resulted decrease of vegetation; and (6 summer to autumn which resulted increase of bushes and vegetation . OLI SVM classified data resulted higher overall accuracy and kappa coefficient and thus found suitable for change detection analysis.

A change detection strategy for monitoring vegetative and land-use cover types using remotely-sensed, satellite-based data

International Nuclear Information System (INIS)

Hallum, C.

1993-01-01

Changes to the environment are of critical concern in the world today; consequently, monitoring such changes and assessing their impacts are tasks demanding considerably higher priority. The ecological impacts of the natural global cycles of gases and particulates in the earth's atmosphere are highly influenced by the extent of changes to vegetative canopy characteristics which dictates the need for capability to detect and assess the magnitude of such changes. The primary emphasis of this paper is on the determination of the size and configuration of the sampling unit that maximizes the probability of its intersection with a 'change' area. Assessment of the significance of the 'change' in a given locality is also addressed and relies on a statistical approach that compares the number of elemental units exceeding a reflectance threshold when compared to a previous point in time. Consideration is also given to a technical framework that supports quantifying the magnitude of the 'change' over large areas (i.e., the estimated area changing from forest to agricultural land-use). The latter entails a multistage approach which utilizes satellite-based and other related data sources

Change Detection with Polarimetric SAR Imagery for Nuclear Verification

International Nuclear Information System (INIS)

Canty, M.

2015-01-01

This paper investigates the application of multivariate statistical change detection with high-resolution polarimetric SAR imagery acquired from commercial satellite platforms for observation and verification of nuclear activities. A prototype software tool comprising a processing chain starting from single look complex (SLC) multitemporal data through to change detection maps is presented. Multivariate change detection algorithms applied to polarimetric SAR data are not common. This is because, up until recently, not many researchers or practitioners have had access to polarimetric data. However with the advent of several spaceborne polarimetric SAR instruments such as the Japanese ALOS, the Canadian Radarsat-2, the German TerraSAR-X, the Italian COSMO-SkyMed missions and the European Sentinal SAR platform, the situation has greatly improved. There is now a rich source of weather-independent satellite radar data which can be exploited for Nuclear Safeguards purposes. The method will also work for univariate data, that is, it is also applicable to scalar or single polarimetric SAR data. The change detection procedure investigated here exploits the complex Wishart distribution of dual and quad polarimetric imagery in look-averaged covariance matrix format in order to define a per-pixel change/no-change hypothesis test. It includes approximations for the probability distribution of the test statistic, and so permits quantitative significance levels to be quoted for change pixels. The method has been demonstrated previously with polarimetric images from the airborne EMISAR sensor, but is applied here for the first time to satellite platforms. In addition, an improved multivariate method is used to estimate the so-called equivalent number of looks (ENL), which is a critical parameter of the hypothesis test. (author)

Change Best: Task 2.3. Analysis of policy mix and development of Energy Efficiency Services

International Nuclear Information System (INIS)

Boonekamp, P.; Vethman, P.

2010-04-01

The aim of the Change Best project is to promote the development of an energy efficiency service (EES) market and to give good practice examples of changes in energy service business, strategies, and supportive policies and measures in the course of the implementation of Directive 2006/32/EC on Energy End-Use Efficiency and Energy Services. This report addresses task 2.3: Analysis of policy mix and development of Energy Efficiency Services.

Influence of dual-tasking with different levels of attention diversion on characteristics of the movement-related cortical potential.

Science.gov (United States)

Aliakbaryhosseinabadi, Susan; Kamavuako, Ernest Nlandu; Jiang, Ning; Farina, Dario; Mrachacz-Kersting, Natalie

2017-11-01

Dual tasking is defined as performing two tasks concurrently and has been shown to have a significant effect on attention directed to the performance of the main task. In this study, an attention diversion task with two different levels was administered while participants had to complete a cue-based motor task consisting of foot dorsiflexion. An auditory oddball task with two levels of complexity was implemented to divert the user's attention. Electroencephalographic (EEG) recordings were made from nine single channels. Event-related potentials (ERPs) confirmed that the oddball task of counting a sequence of two tones decreased the auditory P300 amplitude more than the oddball task of counting one target tone among three different tones. Pre-movement features quantified from the movement-related cortical potential (MRCP) were changed significantly between single and dual-task conditions in motor and fronto-central channels. There was a significant delay in movement detection for the case of single tone counting in two motor channels only (237.1-247.4ms). For the task of sequence counting, motor cortex and frontal channels showed a significant delay in MRCP detection (232.1-250.5ms). This study investigated the effect of attention diversion in dual-task conditions by analysing both ERPs and MRCPs in single channels. The higher attention diversion lead to a significant reduction in specific MRCP features of the motor task. These results suggest that attention division in dual-tasking situations plays an important role in movement execution and detection. This has important implications in designing real-time brain-computer interface systems. Copyright © 2017 Elsevier B.V. All rights reserved.

Multivariate Alteration Detection (MAD) and MAF Postprocessing in Multispectral, Bitemporal Image Data: New Approaches to Change Detection Studies

DEFF Research Database (Denmark)

Nielsen, Allan Aasbjerg; Conradsen, Knut; Simpson, James J.

1998-01-01

type analyses of simple difference images. Case studies with AHVRR and Landsat MSS data using simple linear stretching and masking of the change images show the usefulness of the new MAD and MAF/MAD change detection schemes. Ground truth observations confirm the detected changes. A simple simulation...

Feature learning and change feature classification based on deep learning for ternary change detection in SAR images

Science.gov (United States)

Gong, Maoguo; Yang, Hailun; Zhang, Puzhao

2017-07-01

Ternary change detection aims to detect changes and group the changes into positive change and negative change. It is of great significance in the joint interpretation of spatial-temporal synthetic aperture radar images. In this study, sparse autoencoder, convolutional neural networks (CNN) and unsupervised clustering are combined to solve ternary change detection problem without any supervison. Firstly, sparse autoencoder is used to transform log-ratio difference image into a suitable feature space for extracting key changes and suppressing outliers and noise. And then the learned features are clustered into three classes, which are taken as the pseudo labels for training a CNN model as change feature classifier. The reliable training samples for CNN are selected from the feature maps learned by sparse autoencoder with certain selection rules. Having training samples and the corresponding pseudo labels, the CNN model can be trained by using back propagation with stochastic gradient descent. During its training procedure, CNN is driven to learn the concept of change, and more powerful model is established to distinguish different types of changes. Unlike the traditional methods, the proposed framework integrates the merits of sparse autoencoder and CNN to learn more robust difference representations and the concept of change for ternary change detection. Experimental results on real datasets validate the effectiveness and superiority of the proposed framework.

Stochastic Change Detection based on an Active Fault Diagnosis Approach

DEFF Research Database (Denmark)

Poulsen, Niels Kjølstad; Niemann, Hans Henrik

2007-01-01

The focus in this paper is on stochastic change detection applied in connection with active fault diagnosis (AFD). An auxiliary input signal is applied in AFD. This signal injection in the system will in general allow to obtain a fast change detection/isolation by considering the output or an err...

Impact of number of repeated scans on model observer performance for a low-contrast detection task in computed tomography.

Science.gov (United States)

Ma, Chi; Yu, Lifeng; Chen, Baiyu; Favazza, Christopher; Leng, Shuai; McCollough, Cynthia

2016-04-01

Channelized Hotelling observer (CHO) models have been shown to correlate well with human observers for several phantom-based detection/classification tasks in clinical computed tomography (CT). A large number of repeated scans were used to achieve an accurate estimate of the model's template. The purpose of this study is to investigate how the experimental and CHO model parameters affect the minimum required number of repeated scans. A phantom containing 21 low-contrast objects was scanned on a 128-slice CT scanner at three dose levels. Each scan was repeated 100 times. For each experimental configuration, the low-contrast detectability, quantified as the area under receiver operating characteristic curve, [Formula: see text], was calculated using a previously validated CHO with randomly selected subsets of scans, ranging from 10 to 100. Using [Formula: see text] from the 100 scans as the reference, the accuracy from a smaller number of scans was determined. Our results demonstrated that the minimum number of repeated scans increased when the radiation dose level decreased, object size and contrast level decreased, and the number of channels increased. As a general trend, it increased as the low-contrast detectability decreased. This study provides a basis for the experimental design of task-based image quality assessment in clinical CT using CHO.

A pdf-Free Change Detection Test Based on Density Difference Estimation.

Science.gov (United States)

Bu, Li; Alippi, Cesare; Zhao, Dongbin

2018-02-01

The ability to detect online changes in stationarity or time variance in a data stream is a hot research topic with striking implications. In this paper, we propose a novel probability density function-free change detection test, which is based on the least squares density-difference estimation method and operates online on multidimensional inputs. The test does not require any assumption about the underlying data distribution, and is able to operate immediately after having been configured by adopting a reservoir sampling mechanism. Thresholds requested to detect a change are automatically derived once a false positive rate is set by the application designer. Comprehensive experiments validate the effectiveness in detection of the proposed method both in terms of detection promptness and accuracy.

The effects of foreknowledge and task-set shifting as mirrored in cue- and target-locked event-related potentials.

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Mareike Finke

Full Text Available The present study examined the use of foreknowledge in a task-cueing protocol while manipulating sensory updating and executive control in both, informatively and non-informatively pre-cued trials. Foreknowledge, sensory updating (cue switch effects and task-switching were orthogonally manipulated in order to address the question of whether, and to which extent, the sensory processing of cue changes can partly or totally explain the final task switch costs. Participants responded faster when they could prepare for the upcoming task and if no task-set updating was necessary. Sensory cue switches influenced cue-locked ERPs only when they contained conceptual information about the upcoming task: frontal P2 amplitudes were modulated by task-relevant cue changes, mid-parietal P3 amplitudes by the anticipatory updating of stimulus-response mappings, and P3 peak latencies were modulated by task switching. Task preparation was advantageous for efficient stimulus-response re-mapping at target-onset as mirrored in target N2 amplitudes. However, N2 peak latencies indicate that this process is faster for all repeat trials. The results provide evidence to support a very fast detection of task-relevance in sensory (cue changes and argue against the view of task repetition benefits as secondary to purely perceptual repetition priming. Advanced preparation may have a stronger influence on behavioral performance and target-locked brain activity than the local effect of repeating or switching the task-set in the current trial.

Region-Based Building Rooftop Extraction and Change Detection

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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.

REGION-BASED BUILDING ROOFTOP EXTRACTION AND CHANGE DETECTION

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J. Tian

2017-09-01

Full Text Available 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.

Sustained posterior contralateral activity indicates re-entrant target processing in visual change detection: An EEG study

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Daniel eSchneider

2014-05-01

Full Text Available The present study investigated the neural mechanisms that contribute to the detection of visual feature changes between stimulus displays by means of event-related lateralizations of the electroencephalogram (EEG. Participants were instructed to respond to a luminance change in either of two lateralized stimuli that could randomly occur alone or together with an irrelevant orientation change of the same or contralateral stimulus. Task performance based on response times and accuracy was decreased compared to the remaining stimulus conditions when relevant and irrelevant feature changes were presented contralateral to each other (lateral distractor condition. The sensory response to the feature changes was reflected in a posterior contralateral positivity at around 100ms after change presentation and a posterior contralateral negativity in the N1 time window (N1pc. N2pc reflected a subsequent attentional bias in favor of the relevant luminance change. The continuation of the sustained posterior contralateral negativity (SPCN following N2pc covaried with response times within feature change conditions and revealed a posterior topography comparable to the earlier components associated with sensory and attentional mechanisms. Therefore, this component might reflect the re-processing of information based on sustained short-term memory representations in the visual system until a stable target percept is created that can serve as the perceptual basis for response selection and the initiation of goal-directed behavior.

Vigilance task-related change in brain functional connectivity as revealed by wavelet phase coherence analysis of near-infrared spectroscopy signals

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Wang Wei

2016-08-01

Full Text Available This study aims to assess the vigilance task-related change in connectivity in healthy adults using wavelet phase coherence (WPCO analysis of near-infrared spectroscopy signals (NIRS. NIRS is a non-invasive neuroimaging technique for assessing brain activity. Continuous recordings of the NIRS signals were obtained from the prefrontal cortex (PFC and sensorimotor cortical areas of 20 young healthy adults (24.9±3.3 years during a 10-min resting state and a 20-min vigilance task state. The vigilance task was used to simulate driving mental load by judging three random numbers (i.e., whether odd numbers. The task was divided into two sessions: the first 10 minutes (Task t1 and the second 10 minutes (Task t2. The WPCO of six channel pairs were calculated in five frequency intervals: 0.6–2 Hz (I, 0.145–0.6 Hz (II, 0.052–0.145 Hz (III, 0.021–0.052 Hz (IV, and 0.0095–0.021 Hz (V. The significant WPCO formed global connectivity (GC maps in intervals I and II and functional connectivity (FC maps in intervals III to V. Results show that the GC levels in interval I and FC levels in interval III were significantly lower in the Task t2 than in the resting state (p < 0.05, particularly between the left PFC and bilateral sensorimotor regions. Also, the reaction time shows an increase in Task t2 compared with that in Task t1. However, no significant difference in WPCO was found between Task t1 and resting state. The results showed that the change in FC at the range of 0.6-2 Hz was not attributed to the vigilance task pe se, but the interaction effect of vigilance task and time factors. The findings suggest that the decreased attention level might be partly attributed to the reduced GC levels between the left prefrontal region and sensorimotor area. The present results provide a new insight into the vigilance task-related brain activity.

Developmental change in cognitive organization underlying stroop tasks of Japanese orthographies.

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Toma, C; Toshima, T

1989-01-01

Cognitive processes underlying Stroop interference tasks of two Japanese orthographies, hiragana (a phonetic orthography) and kanji (a logographic orthography) were studied from the developmental point of view. Four age groups (first, second, third graders, and university students) were employed as subjects. Significant interference was yielded both in the hiragana and in the kanji version. Performance time on interference task decreased with age. For elementary school children, the error frequency on the interference task was higher than that on the task of naming patch colors or on the task of reading words printed in black ink, but the error frequencies did not differ among tasks for university students. In the interference task more word reading errors were yielded in the kanji version than in the hiragana version during and after third grade. The findings suggested that (1) the recognition system of hiragana and of kanji becomes qualitatively different during and after third grade, (2) the integrative system, which organizes cognitive processes underlying Stroop task, develops with age, and (3) efficiency of the organization increases with age.

Temporal Forest Change Detection and Forest Health Assessment using Remote Sensing

International Nuclear Information System (INIS)

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

2014-01-01

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

Selective attention to task-irrelevant emotional distractors is unaffected by the perceptual load associated with a foreground task.

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Hindi Attar, Catherine; Müller, Matthias M

2012-01-01

A number of studies have shown that emotionally arousing stimuli are preferentially processed in the human brain. Whether or not this preference persists under increased perceptual load associated with a task at hand remains an open question. Here we manipulated two possible determinants of the attentional selection process, perceptual load associated with a foreground task and the emotional valence of concurrently presented task-irrelevant distractors. As a direct measure of sustained attentional resource allocation in early visual cortex we used steady-state visual evoked potentials (SSVEPs) elicited by distinct flicker frequencies of task and distractor stimuli. Subjects either performed a detection (low load) or discrimination (high load) task at a centrally presented symbol stream that flickered at 8.6 Hz while task-irrelevant neutral or unpleasant pictures from the International Affective Picture System (IAPS) flickered at a frequency of 12 Hz in the background of the stream. As reflected in target detection rates and SSVEP amplitudes to both task and distractor stimuli, unpleasant relative to neutral background pictures more strongly withdrew processing resources from the foreground task. Importantly, this finding was unaffected by the factor 'load' which turned out to be a weak modulator of attentional processing in human visual cortex.

Selective attention to task-irrelevant emotional distractors is unaffected by the perceptual load associated with a foreground task.

Directory of Open Access Journals (Sweden)

Catherine Hindi Attar

Full Text Available A number of studies have shown that emotionally arousing stimuli are preferentially processed in the human brain. Whether or not this preference persists under increased perceptual load associated with a task at hand remains an open question. Here we manipulated two possible determinants of the attentional selection process, perceptual load associated with a foreground task and the emotional valence of concurrently presented task-irrelevant distractors. As a direct measure of sustained attentional resource allocation in early visual cortex we used steady-state visual evoked potentials (SSVEPs elicited by distinct flicker frequencies of task and distractor stimuli. Subjects either performed a detection (low load or discrimination (high load task at a centrally presented symbol stream that flickered at 8.6 Hz while task-irrelevant neutral or unpleasant pictures from the International Affective Picture System (IAPS flickered at a frequency of 12 Hz in the background of the stream. As reflected in target detection rates and SSVEP amplitudes to both task and distractor stimuli, unpleasant relative to neutral background pictures more strongly withdrew processing resources from the foreground task. Importantly, this finding was unaffected by the factor 'load' which turned out to be a weak modulator of attentional processing in human visual cortex.

75 FR 43944 - Defense Science Board; Task Force on Trends and Implications of Climate Change for National and...

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2010-07-27

... DEPARTMENT OF DEFENSE Office of the Secretary Defense Science Board; Task Force on Trends and Implications of Climate Change for National and International Security AGENCY: Department of Defense (DoD... and Implications of Climate Change for National and International Security will meet in closed session...

75 FR 34438 - Defense Science Board Task Force on Trends and Implications of Climate Change for National and...

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2010-06-17

... DEPARTMENT OF DEFENSE Office of the Secretary Defense Science Board Task Force on Trends and Implications of Climate Change for National and International Security AGENCY: Department of Defense (DoD... and Implications of Climate Change for National and International Security will meet in closed session...

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

Science.gov (United States)

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

Science.gov (United States)

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.

Detection of Changes in Ground-Level Ozone Concentrations via Entropy

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Yuehua Wu

2015-04-01

Full Text Available Ground-level ozone concentration is a key indicator of air quality. Theremay exist sudden changes in ozone concentration data over a long time horizon, which may be caused by the implementation of government regulations and policies, such as establishing exhaust emission limits for on-road vehicles. To monitor and assess the efficacy of these policies, we propose a methodology for detecting changes in ground-level ozone concentrations, which consists of three major steps: data transformation, simultaneous autoregressive modelling and change-point detection on the estimated entropy. To show the effectiveness of the proposed methodology, the methodology is applied to detect changes in ground-level ozone concentration data collected in the Toronto region of Canada between June and September for the years from 1988 to 2009. The proposed methodology is also applicable to other climate data.

Spatio-temporal change detection from multidimensional arrays: Detecting deforestation from MODIS time series

Science.gov (United States)

Lu, Meng; Pebesma, Edzer; Sanchez, Alber; Verbesselt, Jan

2016-07-01

Growing availability of long-term satellite imagery enables change modeling with advanced spatio-temporal statistical methods. Multidimensional arrays naturally match the structure of spatio-temporal satellite data and can provide a clean modeling process for complex spatio-temporal analysis over large datasets. Our study case illustrates the detection of breakpoints in MODIS imagery time series for land cover change in the Brazilian Amazon using the BFAST (Breaks For Additive Season and Trend) change detection framework. BFAST includes an Empirical Fluctuation Process (EFP) to alarm the change and a change point time locating process. We extend the EFP to account for the spatial autocorrelation between spatial neighbors and assess the effects of spatial correlation when applying BFAST on satellite image time series. In addition, we evaluate how sensitive EFP is to the assumption that its time series residuals are temporally uncorrelated, by modeling it as an autoregressive process. We use arrays as a unified data structure for the modeling process, R to execute the analysis, and an array database management system to scale computation. Our results point to BFAST as a robust approach against mild temporal and spatial correlation, to the use of arrays to ease the modeling process of spatio-temporal change, and towards communicable and scalable analysis.

Lake Chapala change detection using time series

Science.gov (United States)

López-Caloca, Alejandra; Tapia-Silva, Felipe-Omar; Escalante-Ramírez, Boris

2008-10-01

The Lake Chapala is the largest natural lake in Mexico. It presents a hydrological imbalance problem caused by diminishing intakes from the Lerma River, pollution from said volumes, native vegetation and solid waste. This article presents a study that allows us to determine with high precision the extent of the affectation in both extension and volume reduction of the Lake Chapala in the period going from 1990 to 2007. Through satellite images this above-mentioned period was monitored. Image segmentation was achieved through a Markov Random Field model, extending the application towards edge detection. This allows adequately defining the lake's limits as well as determining new zones within the lake, both changes pertaining the Lake Chapala. Detected changes are related to a hydrological balance study based on measuring variables such as storage volumes, evapotranspiration and water balance. Results show that the changes in the Lake Chapala establish frail conditions which pose a future risk situation. Rehabilitation of the lake requires a hydrologic balance in its banks and aquifers.

AN INVESTIGATION OF AUTOMATIC CHANGE DETECTION FOR TOPOGRAPHIC MAP UPDATING

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P. Duncan

2012-08-01

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

The development of children's knowledge of attention and resource allocation in single and dual tasks.

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Dossett, D; Burns, B

2000-06-01

Developmental changes in kindergarten, 1st-, and 4th-grade children's knowledge about the variables that affect attention sharing and resource allocation were examined. Findings from the 2 experiments showed that kindergartners understood that person and strategy variables affect performance in attention-sharing tasks. However, knowledge of how task variables affect performance was not evident to them and was inconsistent for 1st and 4th graders. Children's knowledge about resource allocation revealed a different pattern and varied according to the dissimilarity of task demands in the attention-sharing task. In Experiment 1, in which the dual attention tasks were similar (i.e., visual detection), kindergarten and 1st-grade children did not differentiate performance in single and dual tasks. Fourth graders demonstrated knowledge that performance on a single task would be better than performance on the dual tasks for only 2 of the variables examined. In Experiment 2, in which the dual attention tasks were dissimilar (i.e., visual and auditory detection), kindergarten and 1st-grade children demonstrated knowledge that performance in the single task would be better than in the dual tasks for 1 of the task variables examined. However, 4th-grade children consistently gave higher ratings for performance on the single than on the dual attention tasks for all variables examined. These findings (a) underscore that children's meta-attention is not unitary and (b) demonstrate that children's knowledge about variables affecting attention sharing and resource allocation have different developmental pathways. Results show that knowledge about attention sharing and about the factors that influence the control of attention develops slowly and undergoes reorganization in middle childhood.

Street-side vehicle detection, classification and change detection using mobile laser scanning data

Science.gov (United States)

Xiao, Wen; Vallet, Bruno; Schindler, Konrad; Paparoditis, Nicolas

2016-04-01

Statistics on street-side car parks, e.g. occupancy rates, parked vehicle types, parking durations, are of great importance for urban planning and policy making. Related studies, e.g. vehicle detection and classification, mostly focus on static images or video. Whereas mobile laser scanning (MLS) systems are increasingly utilized for urban street environment perception due to their direct 3D information acquisition, high accuracy and movability. In this paper, we design a complete system for car park monitoring, including vehicle recognition, localization, classification and change detection, from laser scanning point clouds. The experimental data are acquired by an MLS system using high frequency laser scanner which scans the streets vertically along the system's moving trajectory. The point clouds are firstly classified as ground, building façade, and street objects which are then segmented using state-of-the-art methods. Each segment is treated as an object hypothesis, and its geometric features are extracted. Moreover, a deformable vehicle model is fitted to each object. By fitting an explicit model to the vehicle points, detailed information, such as precise position and orientation, can be obtained. The model parameters are also treated as vehicle features. Together with the geometric features, they are applied to a supervised learning procedure for vehicle or non-vehicle recognition. The classes of detected vehicles are also investigated. Whether vehicles have changed across two datasets acquired at different times is detected to estimate the durations. Here, vehicles are trained pair-wisely. Two same or different vehicles are paired up as training samples. As a result, the vehicle recognition, classification and change detection accuracies are 95.9%, 86.0% and 98.7%, respectively. Vehicle modelling improves not only the recognition rate, but also the localization precision compared to bounding boxes.

Convolutional neural network features based change detection in satellite images

Science.gov (United States)

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.

Change detection using landsat time series: A review of frequencies, preprocessing, algorithms, and applications

Science.gov (United States)

Zhu, Zhe

2017-08-01

The free and open access to all archived Landsat images in 2008 has completely changed the way of using Landsat data. Many novel change detection algorithms based on Landsat time series have been developed We present a comprehensive review of four important aspects of change detection studies based on Landsat time series, including frequencies, preprocessing, algorithms, and applications. We observed the trend that the more recent the study, the higher the frequency of Landsat time series used. We reviewed a series of image preprocessing steps, including atmospheric correction, cloud and cloud shadow detection, and composite/fusion/metrics techniques. We divided all change detection algorithms into six categories, including thresholding, differencing, segmentation, trajectory classification, statistical boundary, and regression. Within each category, six major characteristics of different algorithms, such as frequency, change index, univariate/multivariate, online/offline, abrupt/gradual change, and sub-pixel/pixel/spatial were analyzed. Moreover, some of the widely-used change detection algorithms were also discussed. Finally, we reviewed different change detection applications by dividing these applications into two categories, change target and change agent detection.

Detection of Greenhouse-Gas-Induced Climatic Change

Energy Technology Data Exchange (ETDEWEB)

Jones, P.D.; Wigley, T.M.L.

1998-05-26

The objective of this report is to assemble and analyze instrumental climate data and to develop and apply climate models as a basis for (1) detecting greenhouse-gas-induced climatic change, and (2) validation of General Circulation Models.

Task-relevant cognitive and motor functions are prioritized during prolonged speed-accuracy motor task performance.

Science.gov (United States)

Solianik, Rima; Satas, Andrius; Mickeviciene, Dalia; Cekanauskaite, Agne; Valanciene, Dovile; Majauskiene, Daiva; Skurvydas, Albertas

2018-06-01

This study aimed to explore the effect of prolonged speed-accuracy motor task on the indicators of psychological, cognitive, psychomotor and motor function. Ten young men aged 21.1 ± 1.0 years performed a fast- and accurate-reaching movement task and a control task. Both tasks were performed for 2 h. Despite decreased motivation, and increased perception of effort as well as subjective feeling of fatigue, speed-accuracy motor task performance improved during the whole period of task execution. After the motor task, the increased working memory function and prefrontal cortex oxygenation at rest and during conflict detection, and the decreased efficiency of incorrect response inhibition and visuomotor tracking were observed. The speed-accuracy motor task increased the amplitude of motor-evoked potentials, while grip strength was not affected. These findings demonstrate that to sustain the performance of 2-h speed-accuracy task under conditions of self-reported fatigue, task-relevant functions are maintained or even improved, whereas less critical functions are impaired.

Functional Task Test (FTT)

Science.gov (United States)

Bloomberg, Jacob J.; Mulavara, Ajitkumar; Peters, Brian T.; Rescheke, Millard F.; Wood, Scott; Lawrence, Emily; Koffman, Igor; Ploutz-Snyder, Lori; Spiering, Barry A.; Feeback, Daniel L.;

CEST ANALYSIS: AUTOMATED CHANGE DETECTION FROM VERY-HIGH-RESOLUTION REMOTE SENSING IMAGES

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M. Ehlers

2012-08-01

Full Text Available A fast detection, visualization and assessment of change in areas of crisis or catastrophes are important requirements for coordination and planning of help. Through the availability of new satellites and/or airborne sensors with very high spatial resolutions (e.g., WorldView, GeoEye new remote sensing data are available for a better detection, delineation and visualization of change. For automated change detection, a large number of algorithms has been proposed and developed. From previous studies, however, it is evident that to-date no single algorithm has the potential for being a reliable change detector for all possible scenarios. This paper introduces the Combined Edge Segment Texture (CEST analysis, a decision-tree based cooperative suite of algorithms for automated change detection that is especially designed for the generation of new satellites with very high spatial resolution. The method incorporates frequency based filtering, texture analysis, and image segmentation techniques. For the frequency analysis, different band pass filters can be applied to identify the relevant frequency information for change detection. After transforming the multitemporal images via a fast Fourier transform (FFT and applying the most suitable band pass filter, different methods are available to extract changed structures: differencing and correlation in the frequency domain and correlation and edge detection in the spatial domain. Best results are obtained using edge extraction. For the texture analysis, different 'Haralick' parameters can be calculated (e.g., energy, correlation, contrast, inverse distance moment with 'energy' so far providing the most accurate results. These algorithms are combined with a prior segmentation of the image data as well as with morphological operations for a final binary change result. A rule-based combination (CEST of the change algorithms is applied to calculate the probability of change for a particular location. CEST

Landsat change detection can aid in water quality monitoring

Science.gov (United States)

Macdonald, H. C.; Steele, K. F.; Waite, W. P.; Shinn, M. R.

1977-01-01

Comparison between Landsat-1 and -2 imagery of Arkansas provided evidence of significant land use changes during the 1972-75 time period. Analysis of Arkansas historical water quality information has shown conclusively that whereas point source pollution generally can be detected by use of water quality data collected by state and federal agencies, sampling methodologies for nonpoint source contamination attributable to surface runoff are totally inadequate. The expensive undertaking of monitoring all nonpoint sources for numerous watersheds can be lessened by implementing Landsat change detection analyses.

Stochastic change detection in uncertain nonlinear systems using reduced-order models: classification

International Nuclear Information System (INIS)

Yun, Hae-Bum; Masri, Sami F

2009-01-01

A reliable structural health monitoring methodology (SHM) is proposed to detect relatively small changes in uncertain nonlinear systems. A total of 4000 physical tests were performed using a complex nonlinear magneto-rheological (MR) damper. With the effective (or 'genuine') changes and uncertainties in the system characteristics of the semi-active MR damper, which were precisely controlled with known means and standard deviation of the input current, the tested MR damper was identified with the restoring force method (RFM), a non-parametric system identification method involving two-dimensional orthogonal polynomials. Using the identified RFM coefficients, both supervised and unsupervised pattern recognition techniques (including support vector classification and k-means clustering) were employed to detect system changes in the MR damper. The classification results showed that the identified coefficients with orthogonal basis function can be used as reliable indicators for detecting (small) changes, interpreting the physical meaning of the detected changes without a priori knowledge of the monitored system and quantifying the uncertainty bounds of the detected changes. The classification errors were analyzed using the standard detection theory to evaluate the performance of the developed SHM methodology. An optimal classifier design procedure was also proposed and evaluated to minimize type II (or 'missed') errors

Adaptive Change Detection for Long-Term Machinery Monitoring Using Incremental Sliding-Window

Science.gov (United States)

Wang, Teng; Lu, Guo-Liang; Liu, Jie; Yan, Peng

2017-11-01

Detection of structural changes from an operational process is a major goal in machine condition monitoring. Existing methods for this purpose are mainly based on retrospective analysis, resulting in a large detection delay that limits their usages in real applications. This paper presents a new adaptive real-time change detection algorithm, an extension of the recent research by combining with an incremental sliding-window strategy, to handle the multi-change detection in long-term monitoring of machine operations. In particular, in the framework, Hilbert space embedding of distribution is used to map the original data into the Re-producing Kernel Hilbert Space (RKHS) for change detection; then, a new adaptive threshold strategy can be developed when making change decision, in which a global factor (used to control the coarse-to-fine level of detection) is introduced to replace the fixed value of threshold. Through experiments on a range of real testing data which was collected from an experimental rotating machinery system, the excellent detection performances of the algorithm for engineering applications were demonstrated. Compared with state-of-the-art methods, the proposed algorithm can be more suitable for long-term machinery condition monitoring without any manual re-calibration, thus is promising in modern industries.

Does image quality matter? Impact of resolution and noise on mammographic task performance

International Nuclear Information System (INIS)

Saunders, Robert S. Jr.; Baker, Jay A.; Delong, David M.; Johnson, Jeff P.; Samei, Ehsan

2007-01-01

The purpose of this study was to examine the effects of different resolution and noise levels on task performance in digital mammography. This study created an image set with images at three different resolution levels, corresponding to three digital display devices, and three different noise levels, with noise magnitudes similar to full clinical dose, half clinical dose, and quarter clinical dose. The images were read by five experienced breast imaging radiologists. The data were then analyzed to compute two accuracy statistics (overall classification accuracy and lesion detection accuracy) and performance at four diagnostic tasks (detection of microcalcifications, benign masses, malignant masses, and discrimination of benign and malignant masses). Human observer results showed decreasing display resolution had little effect on overall classification accuracy and individual diagnostic task performance, but increasing noise caused overall classification accuracy to decrease by a statistically significant 21% as the breast dose went to one quarter of its normal clinical value. The noise effects were most prominent for the tasks of microcalcification detection and mass discrimination. When the noise changed from full clinical dose to quarter clinical dose, the microcalcification detection performance fell from 89% to 67% and the mass discrimination performance decreased from 93% to 79%, while malignant mass detection performance remained relatively constant with values of 88% and 84%, respectively. As a secondary aim, the image set was also analyzed by two observer models to examine whether their performance was similar to humans. Observer models differed from human observers and each other in their sensitivity to resolution degradation and noise. The primary conclusions of this study suggest that quantum noise appears to be the dominant image quality factor in digital mammography, affecting radiologist performance much more profoundly than display resolution

Graph-based structural change detection for rotating machinery monitoring

Science.gov (United States)

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).

Walking while performing working memory tasks changes the prefrontal cortex hemodynamic activations and gait kinematics

Directory of Open Access Journals (Sweden)

Ming-I Brandon Lin

2016-05-01

Full Text Available BackgroundIncreasing evidence suggests that walking while performing a concurrent task negatively influences gait performance. However, it remains unclear how higher-level cognitive processes and coordination of limb movements are altered in challenging walking environments. This study investigated the influence of cognitive task complexity and walking road condition on the neutral correlates of executive function and postural control in dual-task walking. MethodsTwenty-four healthy young adults completed a series of overground walks with three walking road conditions (wide, narrow, with obstacles with and without the concurrent n-back working memory tasks of two complexity levels (1-back and 3-back. Prefrontal brain activation was assessed by functional near-infrared spectroscopy. A three-dimensional motion analysis system was used simultaneously to measure gait performance and lower-extremity kinematics. Repeated measures analysis of variance were performed to examine the differences between the conditions. ResultsIn comparison with standing still, participants showed lower n-back task accuracy while walking, with the worst performance from the road with obstacles. Spatiotemporal gait parameters, lower-extremity joint movements, and the relative changes in oxygenated hemoglobin (HbO concentration levels were all significantly different across the task complexity and walking path conditions. While dual-tasking participants were found to flex their hips and knees less, leading to a slower gait speed, longer stride time, shorter step length, and greater gait variability than during normal walking. For narrow-road walking, smaller ankle dorsiflexion and larger hip flexion were observed, along with a reduced gait speed. Obstacle negotiation was mainly characterized by increased gait variability than other conditions. HbO levels appeared to be lower during dual-task walking than normal walking. Compared to wide and obstacle conditions, walking on

Change Best.Task 2.1. National Report on the Energy Efficiency Service Business in the Netherlands

International Nuclear Information System (INIS)

Boonekamp, P.; Vethman, P.

2009-11-01

The aim of the Change Best project is to promote the development of an energy efficiency service (EES) market and to give good practice examples of changes in energy service business, strategies, and supportive policies and measures in the course of the implementation of Directive 2006/32/EC on Energy End-Use Efficiency and Energy Services. This report addresses Task 2.1: National Report on the Energy Efficiency Service Business in the Netherlands. More information can be found on the website of Change Best at www.changebest.eu.

Contribution of the Cerebellum in Cue-Dependent Force Changes During an Isometric Precision Grip Task.

Science.gov (United States)

Kutz, Dieter F; Schmid, Barbara C; Meindl, Tobias; Timmann, Dagmar; Kolb, Florian P

2016-08-01

The "raspberry task" represents a precision grip task that requires continuous adjustment of grip forces and pull forces. During this task, subjects use a specialised grip rod and have to increase the pull force linearly while the rod is locked. The positions of the fingers are unrestrained and freely selectable. From the finger positions and the geometry of the grip rod, a physical lever was derived which is a comprehensive measurement of the subject's grip behaviour. In this study, the involvement of the cerebellum in establishing cued force changes (CFC) was examined. The auditory stimulus was associated with a motor behaviour that has to be readjusted during an ongoing movement that already started. Moreover, cerebellar involvement on grip behaviour was examined. The results show that patients presenting with degenerating cerebellar disease (CBL) were able to elicit CFC and were additionally able to optimise grip behaviour by minimising the lever. Comparison of the results of CBL with a control group of healthy subjects showed, however, that the CFC incidence was significantly lower and the reduction of the lever was less in CBL. Hence, the cerebellum is involved not only in the classical conditioning of reflexes but also in the association of sensory stimuli with complex changes in motor behaviour. Furthermore, the cerebellum is involved in the optimisation of grip behaviour during ongoing movements. Recent studies lead to the assumption that the cerebello-reticulo-spinal pathway might be important for the reduced optimisation of grip behaviour in CBL.

Perspective Effects during Reading: Evidence from Text Change-Detection

Science.gov (United States)

Bohan, Jason; Filik, Ruth

2018-01-01

We report two text change-detection studies in which we investigate the influence of reading perspective on text memory. In Experiment 1 participants read from the perspective of one of two characters in a series of short stories, and word changes were either semantically close or distant. Participants correctly reported more changes to…

Distinct changes in CREB phosphorylation in frontal cortex and striatum during contingent and non-contingent performance of a visual attention task

Directory of Open Access Journals (Sweden)

Mirjana eCarli

2011-10-01

Full Text Available The cyclic-AMP response element binding protein (CREB family of transcription factors has been implicated in numerous forms of behavioural plasticity. We investigated CREB phosphorylation along some nodes of corticostriatal circuitry such as frontal cortex (FC and dorsal (caudate putamen, CPu and ventral (nucleus accumbens, NAC striatum in response to the contingent or non-contingent performance of the five-choice serial reaction time task (5-CSRTT used to assess visuospatial attention. Three experimental manipulations were used; an attentional performance group (contingent, master, a group trained previously on the task but for whom the instrumental contingency coupling responding with stimulus detection and reward was abolished (non-contingent, yoked and a control group matched for food deprivation and exposure to the test apparatus (untrained. Rats trained on the 5-CSRTT (both master and yoked had higher levels of CREB protein in the FC, CPu and NAC compared to untrained controls. Despite the divergent behaviour of master and yoked rats CREB activity in the FC was not substantially different. In rats performing the 5-CSRTT (master, CREB activity was completely abolished in the CPu whereas in the NAC it remained unchanged. In contrast, CREB phosphorylation in CPu and NAC increased only when the contingency changed from goal-dependent to goal-independent reinforcement (yoked. The present results indicate that up-regulation of CREB protein expression across cortical and striatal regions possibly reflects the extensive instrumental learning and performance whereas increased CREB activity in striatal regions may signal the unexpected change in the relationship between instrumental action and reinforcement.

Green offal inspection of cattle, small ruminants and pigs in the United Kingdom: Impact assessment of changes in the inspection protocol on likelihood of detection of selected hazards.

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Blagojevic, Bojan; Dadios, Nikolaos; Reinmann, Karin; Guitian, Javier; Stärk, Katharina D C

2015-06-01

The changes in detection of selected public and animal health as well as welfare hazards due to the change in current inspection of green offal in cattle, small ruminants and pigs were assessed. With respect to public health and animal health, the conditional likelihood of detection with the current green offal inspection was found to be low for eleven out of the twenty-four selected hazard-species pairings and very low for the remaining thirteen pairings. This strongly suggests that the contribution of current green offal inspection to risk mitigation is very limited for public and animal health hazards. The removal of green offal inspection would reduce the detection of some selected animal welfare conditions. For all selected public and animal health as well as welfare hazards, the reduced detection could be compensated with other pre-harvest, harvest and/or post-harvest control measures including existing meat inspection tasks. Copyright © 2015 Elsevier Ltd. All rights reserved.

A robust anomaly based change detection method for time-series remote sensing images

Science.gov (United States)

Shoujing, Yin; Qiao, Wang; Chuanqing, Wu; Xiaoling, Chen; Wandong, Ma; Huiqin, Mao

2014-03-01

Time-series remote sensing images record changes happening on the earth surface, which include not only abnormal changes like human activities and emergencies (e.g. fire, drought, insect pest etc.), but also changes caused by vegetation phenology and climate changes. Yet, challenges occur in analyzing global environment changes and even the internal forces. This paper proposes a robust Anomaly Based Change Detection method (ABCD) for time-series images analysis by detecting abnormal points in data sets, which do not need to follow a normal distribution. With ABCD we can detect when and where changes occur, which is the prerequisite condition of global change studies. ABCD was tested initially with 10-day SPOT VGT NDVI (Normalized Difference Vegetation Index) times series tracking land cover type changes, seasonality and noise, then validated to real data in a large area in Jiangxi, south of China. Initial results show that ABCD can precisely detect spatial and temporal changes from long time series images rapidly.

Detecting anthropogenic climate change with an optimal fingerprint method

International Nuclear Information System (INIS)

Hegerl, G.C.; Storch, H. von; Hasselmann, K.; Santer, B.D.; Jones, P.D.

1994-01-01

We propose a general fingerprint strategy to detect anthropogenic climate change and present application to near surface temperature trends. An expected time-space-variable pattern of anthropogenic climate change (the 'signal') is identified through application of an appropriate optimally matched space-time filter (the 'fingerprint') to the observations. The signal and the fingerprint are represented in a space with sufficient observed and simulated data. The signal pattern is derived from a model-generated prediction of anthropogenic climate change. Application of the fingerprint filter to the data yields a scalar detection variable. The statistically optimal fingerprint is obtained by weighting the model-predicted pattern towards low-noise directions. A combination of model output and observations is used to estimate the noise characteristics of the detection variable, arising from the natural variability of climate in the absence of external forcing. We test then the null hypothesis that the observed climate change is part of natural climate variability. We conclude that a statistically significant externally induced warming has been observed, with the caveat of a possibly inadequate estimate of the internal climate variability. In order to attribute this warming uniquely to anthropogenic greenhouse gas forcing, more information on the climate's response to other forcing mechanisms (e.g. changes in solar radiation, volcanic or anthropogenic aerosols) and their interaction is needed. (orig./KW)

Comparison of changes in oxygenated hemoglobin during the tree-drawing task between patients with schizophrenia and healthy controls.

Science.gov (United States)

Nakano, Shinya; Shoji, Yoshihisa; Morita, Kiichiro; Igimi, Hiroyasu; Sato, Mamoru; Ishii, Youhei; Kondo, Akihiko; Uchimura, Naohisa

2018-01-01

Tree-drawing test is used as a projective psychological test that expresses the abnormal internal experience in patients with schizophrenia (SZ). Despite the widely accepted view that the cognitive function is involved in characteristic tree-drawing in patients with SZ, no study has psychophysiologically examined it. The present study aimed to investigate the involvement of cognitive function during tree-drawing in patients with SZ. For that purpose, we evaluated the brain function in patients with SZ during a tree-drawing task by using near-infrared spectroscopy (NIRS) and compared them with those in healthy controls. The subjects were 28 healthy controls and 28 patients with SZ. Changes in the oxygenated hemoglobin ([oxy-Hb]) concentration in both the groups during the task of drawing a tree imagined freely (free-drawing task) and the task of copying an illustration of a tree (copying task) were measured by using NIRS. Because of the difference between the task conditions, [oxy-Hb] levels in controls during the free-drawing task were higher than that during the copying task at the bilateral frontal pole regions and left inferior frontal region. Because of the difference between the groups, [oxy-Hb] levels at the left middle frontal region, bilateral inferior frontal regions, bilateral inferior parietal regions, and left superior temporal region during the free-drawing task in patients were lower than that in controls. [oxy-Hb] during the tree-drawing task in patients with SZ was lower than that in healthy controls. Our results suggest that brain dysfunction in patients with SZ might be associated with their tree-drawing.

Brain functional network changes following Prelimbic area inactivation in a spatial memory extinction task.

Science.gov (United States)

Méndez-Couz, Marta; Conejo, Nélida M; Vallejo, Guillermo; Arias, Jorge L

2015-01-01

Several studies suggest a prefrontal cortex involvement during the acquisition and consolidation of spatial memory, suggesting an active modulating role at late stages of acquisition processes. Recently, we have reported that the prelimbic and infralimbic areas of the prefrontal cortex, among other structures, are also specifically involved in the late phases of spatial memory extinction. This study aimed to evaluate whether the inactivation of the prelimbic area of the prefrontal cortex impaired spatial memory extinction. For this purpose, male Wistar rats were implanted bilaterally with cannulae into the prelimbic region of the prefrontal cortex. Animals were trained during 5 consecutive days in a hidden platform task and tested for reference spatial memory immediately after the last training session. One day after completing the training task, bilateral infusion of the GABAA receptor agonist Muscimol was performed before the extinction protocol was carried out. Additionally, cytochrome c oxidase histochemistry was applied to map the metabolic brain activity related to the spatial memory extinction under prelimbic cortex inactivation. Results show that animals acquired the reference memory task in the water maze, and the extinction task was successfully completed without significant impairment. However, analysis of the functional brain networks involved by cytochrome oxidase activity interregional correlations showed changes in brain networks between the group treated with Muscimol as compared to the saline-treated group, supporting the involvement of the mammillary bodies at a the late stage in the memory extinction process. Copyright © 2015 Elsevier B.V. All rights reserved.

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

Science.gov (United States)

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

2018-04-01

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

You can’t kid a kidder: Association between production and detection of deception in an interactive deception task

Directory of Open Access Journals (Sweden)

Gordon R.T. Wright

2012-04-01

Full Text Available Both the ability to deceive others, and the ability to detect deception, have long been proposed to confer an evolutionary advantage. Deception detection has been studied extensively, and the finding that typical individuals fare little better than chance in detecting deception is one of the more robust in the behavioral sciences. Surprisingly, little research has examined individual differences in lie-production ability. As a consequence, as far as we are aware, no previous study has investigated whether there exists an association between the ability to lie successfully and the ability to detect lies. Furthermore, only a minority of studies have examined deception as it naturally occurs; in a social, interactive setting. The present study therefore explored the relationship between these two facets of deceptive behavior by employing a novel competitive interactive deception task. For the first time, signal-detection theory was used to measure performance in both the detection and production of deception. A significant relationship was found between the deception-related abilities; those who could accurately detect a lie were able to produce statements that others found difficult to classify as deceptive or truthful. Furthermore, neither ability was related to measures of intelligence or emotional ability. We therefore suggest the existence of an underlying deception-general ability that varies across individuals.

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

Science.gov (United States)

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.

Correlates of academic procrastination: discomfort, task aversiveness, and task capability.

Science.gov (United States)

Milgram, N; Marshevsky, S; Sadeh, C

1995-03-01

The relationships among five aspects of academic procrastination--behavioral delay, personal upset about the delay, task aversiveness, task capability, and the desire to reduce behavioral delay--were investigated in 10th-grade Israeli students (N = 195). Upset about delay was weakly related to delay itself, and--unlike delay--was strongly related to perceived capability to perform academic tasks and to the desire to change delaying behavior. Students delayed more on academic tasks labeled unpleasant than pleasant, were neutral in between, and were correspondingly more upset about the former than the latter. They more frequently acknowledged reasons for academic procrastination that were less threatening to their self-image (e.g., problems in time management) than reasons that were more threatening (e.g., lack of ability). Interest in reducing delay is related more to self-perceived ability to handle tasks than to time spent procrastinating or reasons given for procrastinating.

Nationwide Hybrid Change Detection of Buildings

Science.gov (United States)

Hron, V.; Halounova, L.

2016-06-01

The Fundamental Base of Geographic Data of the Czech Republic (hereinafter FBGD) is a national 2D geodatabase at a 1:10,000 scale with more than 100 geographic objects. This paper describes the design of the permanent updating mechanism of buildings in FBGD. The proposed procedure belongs to the category of hybrid change detection (HCD) techniques which combine pixel-based and object-based evaluation. The main sources of information for HCD are cadastral information and bi-temporal vertical digital aerial photographs. These photographs have great information potential because they contain multispectral, position and also elevation information. Elevation information represents a digital surface model (DSM) which can be obtained using the image matching technique. Pixel-based evaluation of bi-temporal DSMs enables fast localization of places with potential building changes. These coarse results are subsequently classified through the object-based image analysis (OBIA) using spectral, textural and contextual features and GIS tools. The advantage of the two-stage evaluation is the pre-selection of locations where image segmentation (a computationally demanding part of OBIA) is performed. It is not necessary to apply image segmentation to the entire scene, but only to the surroundings of detected changes, which contributes to significantly faster processing and lower hardware requirements. The created technology is based on open-source software solutions that allow easy portability on multiple computers and parallelization of processing. This leads to significant savings of financial resources which can be expended on the further development of FBGD.

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

Science.gov (United States)

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

Task dynamics in self-organising task groups : expertise, motivational, and performance differences of specialists and generalists

NARCIS (Netherlands)

Zoethout, Kees; Jager, Wander; Molleman, Eric

Multi-agent simulation is applied to explore how different types of task variety cause workgroups to change their task allocation accordingly. We studied two groups, generalists and specialists. We hypothesised that the performance of the specialists would decrease when task variety increases. The

Walking modality, but not task difficulty, influences the control of dual-task walking.

Science.gov (United States)

Wrightson, J G; Smeeton, N J

2017-10-01

During dual-task gait, changes in the stride-to-stride variability of stride time (STV) are suggested to represent the allocation of cognitive control to walking [1]. However, contrasting effects have been reported for overground and treadmill walking, which may be due to differences in the relative difficulty of the dual task. Here we compared the effect of overground and treadmill dual-task walking on STV in 18 healthy adults. Participants walked overground and on a treadmill for 120s during single-task (walking only) and dual-task (walking whilst performing serial subtractions in sevens) conditions. Dual-task effects on STV, cognitive task (serial subtraction) performance and perceived task difficulty were compared between walking modalities. STV was increased during overground dual-task walking, but was unchanged during treadmill dual-task walking. There were no differences in cognitive task performance or perceived task difficulty. These results show that gait is controlled differently during overground and treadmill dual-task walking. However, these differences are not solely due to differences in task difficulty, and may instead represent modality dependent control strategies. Copyright © 2017 Elsevier B.V. All rights reserved.

Stimulus-dependent modulation of visual neglect in a touch-screen cancellation task.

Science.gov (United States)

Keller, Ingo; Volkening, Katharina; Garbacenkaite, Ruta

2015-05-01

Patients with left-sided neglect frequently show omissions and repetitive behavior on cancellation tests. Using a touch-screen-based cancellation task, we tested how visual feedback and distracters influence the number of omissions and perseverations. Eighteen patients with left-sided visual neglect and 18 healthy controls performed four different cancellation tasks on an iPad touch screen: no feedback (the display did not change during the task), visual feedback (touched targets changed their color from black to green), visual feedback with distracters (20 distracters were evenly embedded in the display; detected targets changed their color from black to green), vanishing targets (touched targets disappeared from the screen). Except for the condition with vanishing targets, neglect patients had significantly more omissions and perseverations than healthy controls in the remaining three subtests. Both conditions providing feedback by changing the target color showed the highest number of omissions. Erasure of targets nearly diminished omissions completely. The highest rate of perseverations was observed in the no-feedback condition. The implementation of distracters led to a moderate number of perseverations. Visual feedback without distracters and vanishing targets abolished perseverations nearly completely. Visual feedback and the presence of distracters aggravated hemispatial neglect. This finding is compatible with impaired disengagement from the ipsilesional side as an important factor of visual neglect. Improvement of cancellation behavior with vanishing targets could have therapeutic implications. (c) 2015 APA, all rights reserved).

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

Science.gov (United States)

Moody, Daniela Irina

2018-04-17

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 detect geologic, vegetative, hydrologic, and man-made features, as well as changes in these features over time.

Short-Term Change Detection in Wetlands Using Sentinel-1 Time Series

DEFF Research Database (Denmark)

Muro, Javier; Canty, Morton; Conradsen, Knut

2016-01-01

Automated monitoring systems that can capture wetlands’ high spatial and temporal variability are essential for their management. SAR-based change detection approaches offer a great opportunity to enhance our understanding of complex and dynamic ecosystems. We test a recently-developed time serie...... certain landscape changes are detected only by either the Landsat-based or the S1-omnibus method. The S1-omnibus method shows a great potential for an automated monitoring of short time changes and accurate delineation of areas of high variability and of slow and gradual changes....

Neurometaplasticity: Glucoallostasis control of plasticity of the neural networks of error commission, detection, and correction modulates neuroplasticity to influence task precision

Science.gov (United States)

Welcome, Menizibeya O.; Dane, Şenol; Mastorakis, Nikos E.; Pereverzev, Vladimir A.

2017-12-01

The term "metaplasticity" is a recent one, which means plasticity of synaptic plasticity. Correspondingly, neurometaplasticity simply means plasticity of neuroplasticity, indicating that a previous plastic event determines the current plasticity of neurons. Emerging studies suggest that neurometaplasticity underlie many neural activities and neurobehavioral disorders. In our previous work, we indicated that glucoallostasis is essential for the control of plasticity of the neural network that control error commission, detection and correction. Here we review recent works, which suggest that task precision depends on the modulatory effects of neuroplasticity on the neural networks of error commission, detection, and correction. Furthermore, we discuss neurometaplasticity and its role in error commission, detection, and correction.

Task-driven image acquisition and reconstruction in cone-beam CT

International Nuclear Information System (INIS)

Gang, Grace J; Stayman, J Webster; Siewerdsen, Jeffrey H; Ehtiati, Tina

2015-01-01

This work introduces a task-driven imaging framework that incorporates a mathematical definition of the imaging task, a model of the imaging system, and a patient-specific anatomical model to prospectively design image acquisition and reconstruction techniques to optimize task performance. The framework is applied to joint optimization of tube current modulation, view-dependent reconstruction kernel, and orbital tilt in cone-beam CT. The system model considers a cone-beam CT system incorporating a flat-panel detector and 3D filtered backprojection and accurately describes the spatially varying noise and resolution over a wide range of imaging parameters in the presence of a realistic anatomical model. Task-based detectability index (d′) is incorporated as the objective function in a task-driven optimization of image acquisition and reconstruction techniques. The orbital tilt was optimized through an exhaustive search across tilt angles ranging ±30°. For each tilt angle, the view-dependent tube current and reconstruction kernel (i.e. the modulation profiles) that maximized detectability were identified via an alternating optimization. The task-driven approach was compared with conventional unmodulated and automatic exposure control (AEC) strategies for a variety of imaging tasks and anthropomorphic phantoms. The task-driven strategy outperformed the unmodulated and AEC cases for all tasks. For example, d′ for a sphere detection task in a head phantom was improved by 30% compared to the unmodulated case by using smoother kernels for noisy views and distributing mAs across less noisy views (at fixed total mAs) in a manner that was beneficial to task performance. Similarly for detection of a line-pair pattern, the task-driven approach increased d′ by 80% compared to no modulation by means of view-dependent mA and kernel selection that yields modulation transfer function and noise-power spectrum optimal to the task. Optimization of orbital tilt identified the

A Doubly Stochastic Change Point Detection Algorithm for Noisy Biological Signals

Directory of Open Access Journals (Sweden)

Nathan Gold

2018-01-01

Full Text Available 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.

Automated Change Detection for Synthetic Aperture Sonar

Science.gov (United States)

2014-01-01

alerting to the presence of an acoustically chameleonic object. While the utility of exploiting changes in signal phase degrades over time, with time...pp. 643–656, October 2003. [7] D. Brie, M. Tomczak, H. Oehlmann, and A. Richard, “Gear crack detection by adaptive amplitude and phase demodulation

Multisensor Fusion for Change Detection

Science.gov (United States)

Schenk, T.; Csatho, B.

2005-12-01

with detecting surface elevation changes on the Byrd Glacier, Antarctica, with aerial imagery from 1980s and ICESat laser altimetry data from 2003-05. Change detection from such disparate data sets is an intricate fusion problem, beginning with sensor alignment, and on to reasoning with spatial information as to where changes occurred and to what extent.

Investigating the visual span in comparative search: the effects of task difficulty and divided attention.

Science.gov (United States)

Pomplun, M; Reingold, E M; Shen, J

2001-09-01

In three experiments, participants' visual span was measured in a comparative visual search task in which they had to detect a local match or mismatch between two displays presented side by side. Experiment 1 manipulated the difficulty of the comparative visual search task by contrasting a mismatch detection task with a substantially more difficult match detection task. In Experiment 2, participants were tested in a single-task condition involving only the visual task and a dual-task condition in which they concurrently performed an auditory task. Finally, in Experiment 3, participants performed two dual-task conditions, which differed in the difficulty of the concurrent auditory task. Both the comparative search task difficulty (Experiment 1) and the divided attention manipulation (Experiments 2 and 3) produced strong effects on visual span size.

Scientific Uncertainties in Climate Change Detection and Attribution Studies

Science.gov (United States)

Santer, B. D.

2017-12-01

It has been claimed that the treatment and discussion of key uncertainties in climate science is "confined to hushed sidebar conversations at scientific conferences". This claim is demonstrably incorrect. Climate change detection and attribution studies routinely consider key uncertainties in observational climate data, as well as uncertainties in model-based estimates of natural variability and the "fingerprints" in response to different external forcings. The goal is to determine whether such uncertainties preclude robust identification of a human-caused climate change fingerprint. It is also routine to investigate the impact of applying different fingerprint identification strategies, and to assess how detection and attribution results are impacted by differences in the ability of current models to capture important aspects of present-day climate. The exploration of the uncertainties mentioned above will be illustrated using examples from detection and attribution studies with atmospheric temperature and moisture.

A New Study of Two Divergence Metrics for Change Detection in Data Streams

KAUST Repository

Qahtan, Abdulhakim Ali Ali; Wang, Suojin; Carroll, Raymond; Zhang, Xiangliang

2014-01-01

Streaming data are dynamic in nature with frequent changes. To detect such changes, most methods measure the difference between the data distributions in a current time window and a reference window. Divergence metrics and density estimation are required to measure the difference between the data distributions. Our study shows that the Kullback-Leibler (KL) divergence, the most popular metric for comparing distributions, fails to detect certain changes due to its asymmetric property and its dependence on the variance of the data. We thus consider two metrics for detecting changes in univariate data streams: a symmetric KL-divergence and a divergence metric measuring the intersection area of two distributions. The experimental results show that these two metrics lead to more accurate results in change detection than baseline methods such as Change Finder and using conventional KL-divergence.

A New Study of Two Divergence Metrics for Change Detection in Data Streams

KAUST Repository

Qahtan, Abdulhakim Ali Ali

2014-08-01

Streaming data are dynamic in nature with frequent changes. To detect such changes, most methods measure the difference between the data distributions in a current time window and a reference window. Divergence metrics and density estimation are required to measure the difference between the data distributions. Our study shows that the Kullback-Leibler (KL) divergence, the most popular metric for comparing distributions, fails to detect certain changes due to its asymmetric property and its dependence on the variance of the data. We thus consider two metrics for detecting changes in univariate data streams: a symmetric KL-divergence and a divergence metric measuring the intersection area of two distributions. The experimental results show that these two metrics lead to more accurate results in change detection than baseline methods such as Change Finder and using conventional KL-divergence.

Non-linear laws of echoic memory and auditory change detection in humans.

Science.gov (United States)

Inui, Koji; Urakawa, Tomokazu; Yamashiro, Koya; Otsuru, Naofumi; Nishihara, Makoto; Takeshima, Yasuyuki; Keceli, Sumru; Kakigi, Ryusuke

2010-07-03

The detection of any abrupt change in the environment is important to survival. Since memory of preceding sensory conditions is necessary for detecting changes, such a change-detection system relates closely to the memory system. Here we used an auditory change-related N1 subcomponent (change-N1) of event-related brain potentials to investigate cortical mechanisms underlying change detection and echoic memory. Change-N1 was elicited by a simple paradigm with two tones, a standard followed by a deviant, while subjects watched a silent movie. The amplitude of change-N1 elicited by a fixed sound pressure deviance (70 dB vs. 75 dB) was negatively correlated with the logarithm of the interval between the standard sound and deviant sound (1, 10, 100, or 1000 ms), while positively correlated with the logarithm of the duration of the standard sound (25, 100, 500, or 1000 ms). The amplitude of change-N1 elicited by a deviance in sound pressure, sound frequency, and sound location was correlated with the logarithm of the magnitude of physical differences between the standard and deviant sounds. The present findings suggest that temporal representation of echoic memory is non-linear and Weber-Fechner law holds for the automatic cortical response to sound changes within a suprathreshold range. Since the present results show that the behavior of echoic memory can be understood through change-N1, change-N1 would be a useful tool to investigate memory systems.

Change detection in polarimetric SAR data over several time points

DEFF Research Database (Denmark)

Conradsen, Knut; Nielsen, Allan Aasbjerg; Skriver, Henning

2014-01-01

A test statistic for the equality of several variance-covariance matrices following the complex Wishart distribution is introduced. The test statistic is applied successfully to detect change in C-band EMISAR polarimetric SAR data over four time points.......A test statistic for the equality of several variance-covariance matrices following the complex Wishart distribution is introduced. The test statistic is applied successfully to detect change in C-band EMISAR polarimetric SAR data over four time points....

Functional Task Test: 3. Skeletal Muscle Performance Adaptations to Space Flight

Science.gov (United States)

Ryder, Jeffrey W.; Wickwire, P. J.; Buxton, R. E.; Bloomberg, J. J.; Ploutz-Snyder, L.

2011-01-01

The functional task test is a multi-disciplinary study investigating how space-flight induced changes to physiological systems impacts functional task performance. Impairment of neuromuscular function would be expected to negatively affect functional performance of crewmembers following exposure to microgravity. This presentation reports the results for muscle performance testing in crewmembers. Functional task performance will be presented in the abstract "Functional Task Test 1: sensory motor adaptations associated with postflight alternations in astronaut functional task performance." METHODS: Muscle performance measures were obtained in crewmembers before and after short-duration space flight aboard the Space Shuttle and long-duration International Space Station (ISS) missions. The battery of muscle performance tests included leg press and bench press measures of isometric force, isotonic power and total work. Knee extension was used for the measurement of central activation and maximal isometric force. Upper and lower body force steadiness control were measured on the bench press and knee extension machine, respectively. Tests were implemented 60 and 30 days before launch, on landing day (Shuttle crew only), and 6, 10 and 30 days after landing. Seven Space Shuttle crew and four ISS crew have completed the muscle performance testing to date. RESULTS: Preliminary results for Space Shuttle crew reveal significant reductions in the leg press performance metrics of maximal isometric force, power and total work on R+0 (pperformance metrics were observed in returning Shuttle crew and these adaptations are likely contributors to impaired functional tasks that are ambulatory in nature (See abstract Functional Task Test: 1). Interestingly, no significant changes in central activation capacity were detected. Therefore, impairments in muscle function in response to short-duration space flight are likely myocellular rather than neuromotor in nature.

Symmetrized local co-registration optimization for anomalous change detection

Energy Technology Data Exchange (ETDEWEB)

Wohlberg, Brendt E [Los Alamos National Laboratory; Theiler, James P [Los Alamos National Laboratory

2009-01-01

The goal of anomalous change detection (ACD) is to identify what unusual changes have occurred in a scene, based on two images of the scene taken at different times and under different conditions. The actual anomalous changes need to be distinguished from the incidental differences that occur throughout the imagery, and one of the most common and confounding of these incidental differences is due to the misregistration of the images, due to limitations of the registration pre-processing applied to the image pair. We propose a general method to compensate for residual misregistration in any ACD algorithm which constructs an estimate of the degree of 'anomalousness' for every pixel in the image pair. The method computes a modified misregistration-insensitive anomalousness by making local re-registration adjustments to minimize the local anomalousness. In this paper we describe a symmetrized version of our initial algorithm, and find significant performance improvements in the anomalous change detection ROC curves for a number of real and synthetic data sets.

The change in perceived motor competence and motor task values during elementary school : A longitudinal cohort study

NARCIS (Netherlands)

Noordstar, Johannes J; van der Net, Janjaap; Jak, Suzanne; Helders, Paul J M; Jongmans, Marian J

Participation in motor activities is essential for social interaction and life satisfaction in children. Self-perceptions and task values have a central position in why children do or do not participate in (motor) activities. Investigating developmental changes in motor self-perceptions and motor

The Dark Side of Micro-Task Marketplaces: Characterizing Fiverr and Automatically Detecting Crowdturfing

OpenAIRE

Lee, Kyumin; Webb, Steve; Ge, Hancheng

2014-01-01

As human computation on crowdsourcing systems has become popular and powerful for performing tasks, malicious users have started misusing these systems by posting malicious tasks, propagating manipulated contents, and targeting popular web services such as online social networks and search engines. Recently, these malicious users moved to Fiverr, a fast-growing micro-task marketplace, where workers can post crowdturfing tasks (i.e., astroturfing campaigns run by crowd workers) and malicious c...

Detecting change in stochastic sound sequences.

Directory of Open Access Journals (Sweden)

Benjamin Skerritt-Davis

2018-05-01

Full Text Available Our ability to parse our acoustic environment relies on the brain's capacity to extract statistical regularities from surrounding sounds. Previous work in regularity extraction has predominantly focused on the brain's sensitivity to predictable patterns in sound sequences. However, natural sound environments are rarely completely predictable, often containing some level of randomness, yet the brain is able to effectively interpret its surroundings by extracting useful information from stochastic sounds. It has been previously shown that the brain is sensitive to the marginal lower-order statistics of sound sequences (i.e., mean and variance. In this work, we investigate the brain's sensitivity to higher-order statistics describing temporal dependencies between sound events through a series of change detection experiments, where listeners are asked to detect changes in randomness in the pitch of tone sequences. Behavioral data indicate listeners collect statistical estimates to process incoming sounds, and a perceptual model based on Bayesian inference shows a capacity in the brain to track higher-order statistics. Further analysis of individual subjects' behavior indicates an important role of perceptual constraints in listeners' ability to track these sensory statistics with high fidelity. In addition, the inference model facilitates analysis of neural electroencephalography (EEG responses, anchoring the analysis relative to the statistics of each stochastic stimulus. This reveals both a deviance response and a change-related disruption in phase of the stimulus-locked response that follow the higher-order statistics. These results shed light on the brain's ability to process stochastic sound sequences.

NATIONWIDE HYBRID CHANGE DETECTION OF BUILDINGS

Directory of Open Access Journals (Sweden)

V. Hron

2016-06-01

Full Text Available The Fundamental Base of Geographic Data of the Czech Republic (hereinafter FBGD is a national 2D geodatabase at a 1:10,000 scale with more than 100 geographic objects. This paper describes the design of the permanent updating mechanism of buildings in FBGD. The proposed procedure belongs to the category of hybrid change detection (HCD techniques which combine pixel-based and object-based evaluation. The main sources of information for HCD are cadastral information and bi-temporal vertical digital aerial photographs. These photographs have great information potential because they contain multispectral, position and also elevation information. Elevation information represents a digital surface model (DSM which can be obtained using the image matching technique. Pixel-based evaluation of bi-temporal DSMs enables fast localization of places with potential building changes. These coarse results are subsequently classified through the object-based image analysis (OBIA using spectral, textural and contextual features and GIS tools. The advantage of the two-stage evaluation is the pre-selection of locations where image segmentation (a computationally demanding part of OBIA is performed. It is not necessary to apply image segmentation to the entire scene, but only to the surroundings of detected changes, which contributes to significantly faster processing and lower hardware requirements. The created technology is based on open-source software solutions that allow easy portability on multiple computers and parallelization of processing. This leads to significant savings of financial resources which can be expended on the further development of FBGD.

Automatic change detection to facial expressions in adolescents

DEFF Research Database (Denmark)

Liu, Tongran; Xiao, Tong; Jiannong, Shi

2016-01-01

Adolescence is a critical period for the neurodevelopment of social-emotional processing, wherein the automatic detection of changes in facial expressions is crucial for the development of interpersonal communication. Two groups of participants (an adolescent group and an adult group) were...... in facial expressions between the two age groups. The current findings demonstrated that the adolescent group featured more negative vMMN amplitudes than the adult group in the fronto-central region during the 120–200 ms interval. During the time window of 370–450 ms, only the adult group showed better...... automatic processing on fearful faces than happy faces. The present study indicated that adolescent’s posses stronger automatic detection of changes in emotional expression relative to adults, and sheds light on the neurodevelopment of automatic processes concerning social-emotional information....

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

Science.gov (United States)

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

2003-12-01

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

Detecting and Quantifying Mind Wandering during Simulated Driving

Directory of Open Access Journals (Sweden)

Carryl L. Baldwin

2017-08-01

Full Text Available 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.

The Effect of Creative Tasks on Electrocardiogram: Using Linear and Nonlinear Features in Combination with Classification Approaches

Directory of Open Access Journals (Sweden)

Sahar Zakeri

2017-02-01

Full Text Available Objective: Interest in the subject of creativity and its impacts on human life is growing extensively. However, only a few surveys pay attention to the relation between creativity and physiological changes. This paper presents a novel approach to distinguish between creativity states from electrocardiogram signals. Nineteen linear and nonlinear features of the cardiac signal were extracted to detect creativity states. Method: ECG signals of 52 participants were recorded while doing three tasks of Torrance Tests of Creative Thinking (TTCT/ figural B. To remove artifacts, notch filter 50 Hz and Chebyshev II were applied. According to TTCT scores, participants were categorized into the high and low creativity groups: Participants with scores higher than 70 were assigned into the high creativity group and those with scores less than 30 were considered as low creativity group. Some linear and nonlinear features were extracted from the ECGs. Then, Support Vector Machine (SVM and Adaptive Neuro-Fuzzy Inference System (ANFIS were used to classify the groups.Results: Applying the Wilcoxon test, significant differences were observed between rest and each three tasks of creativity. However, better discrimination was performed between rest and the first task. In addition, there were no statistical differences between the second and third task of the test. The results indicated that the SVM effectively detects all the three tasks from the rest, particularly the task 1 and reached the maximum accuracy of 99.63% in the linear analysis. In addition, the high creative group was separated from the low creative group with the accuracy of 98.41%.Conclusion: the combination of SVM classifier with linear features can be useful to show the relation between creativity and physiological changes.

Mind Wandering in Text Comprehension under Dual-Task Conditions

Directory of Open Access Journals (Sweden)

Peter eDixon

2013-10-01

Full Text Available In two experiments, subjects responded to on-task probes while reading under dual-task conditions. The secondary task was to monitor the text for occurrences of the letter e. In Experiment 1, reading comprehension was assessed with a multiple-choice recognition test; in Experiment 2, subjects recalled the text. In both experiments, the secondary task replicated the well-known missing-letter effect in which detection of e’s was less effective for the word the. Letter detection was also more effective when subjects were on task, but this effect did not interact with the missing-letter effect. Comprehension was assessed in both the dual-task conditions and in a control single-task conditions. In the single-task conditions, both recognition (Experiment 1 and recall (Experiment 2 was better when subjects were on task, replicating previous research on mind wandering. Surprisingly, though, comprehension under dual-task conditions only showed an effect of being on task when measured with recall; there was no effect on recognition performance. Our interpretation of this pattern of results is that subjects generate their response to on-task probes on the basis of a retrospective assessment of the contents of working memory. Further, we argue that under dual-task conditions, the contents of working memory is not related to the reading processes required for accurate recognition performance. These conclusions have implications for models of text comprehension and for the interpretation of on-task probe responses.

Landslide Change Detection Based on Multi-Temporal Airborne LiDAR-Derived DEMs

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Omar E. Mora

2018-01-01

Full Text Available Remote sensing technologies have seen extraordinary improvements in both spatial resolution and accuracy recently. In particular, airborne laser scanning systems can now provide data for surface modeling with unprecedented resolution and accuracy, which can effectively support the detection of sub-meter surface features, vital for landslide mapping. Also, the easy repeatability of data acquisition offers the opportunity to monitor temporal surface changes, which are essential to identifying developing or active slides. Specific methods are needed to detect and map surface changes due to landslide activities. In this paper, we present a methodology that is based on fusing probabilistic change detection and landslide surface feature extraction utilizing multi-temporal Light Detection and Ranging (LiDAR derived Digital Elevation Models (DEMs to map surface changes demonstrating landslide activity. The proposed method was tested in an area with numerous slides ranging from 200 m2 to 27,000 m2 in area under low vegetation and tree cover, Zanesville, Ohio, USA. The surface changes observed are probabilistically evaluated to determine the likelihood of the changes being landslide activity related. Next, based on surface features, a Support Vector Machine (SVM quantifies and maps the topographic signatures of landslides in the entire area. Finally, these two processes are fused to detect landslide prone changes. The results demonstrate that 53 out of 80 inventory mapped landslides were identified using this method. Additionally, some areas that were not mapped in the inventory map displayed changes that are likely to be developing landslides.

Learning Change from Synthetic Aperture Radar Images: Performance Evaluation of a Support Vector Machine to Detect Earthquake and Tsunami-Induced Changes

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Marc Wieland

2016-09-01

Full Text Available This study evaluates the performance of a Support Vector Machine (SVM classifier to learn and detect changes in single- and multi-temporal X- and L-band Synthetic Aperture Radar (SAR images under varying conditions. The purpose is to provide guidance on how to train a powerful learning machine for change detection in SAR images and to contribute to a better understanding of potentials and limitations of supervised change detection approaches. This becomes particularly important on the background of a rapidly growing demand for SAR change detection to support rapid situation awareness in case of natural disasters. The application environment of this study thus focuses on detecting changes caused by the 2011 Tohoku earthquake and tsunami disaster, where single polarized TerraSAR-X and ALOS PALSAR intensity images are used as input. An unprecedented reference dataset of more than 18,000 buildings that have been visually inspected by local authorities for damages after the disaster forms a solid statistical population for the performance experiments. Several critical choices commonly made during the training stage of a learning machine are being assessed for their influence on the change detection performance, including sampling approach, location and number of training samples, classification scheme, change feature space and the acquisition dates of the satellite images. Furthermore, the proposed machine learning approach is compared with the widely used change image thresholding. The study concludes that a well-trained and tuned SVM can provide highly accurate change detections that outperform change image thresholding. While good performance is achieved in the binary change detection case, a distinction between multiple change classes in terms of damage grades leads to poor performance in the tested experimental setting. The major drawback of a machine learning approach is related to the high costs of training. The outcomes of this study, however

Happy Face Superiority Effect in Change Detection Paradigm

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Domagoj Švegar

2013-09-01

Full Text Available The aim of the present study was to investigate which affective component guides cognitive processing of emotional facial expressions. According to the threat hypothesis, processing of angry faces is prioritized by the human cognitive system, because rapid detection of threat has a large adaptive value. The negativity hypothesis presumes that distressing emotional experiences of other people attract attention, regardless of whether they represent danger or not. The emotionality hypothesis proposes that positive emotional facial expressions can capture attention as effective as negative ones, while the happy face superiority hypothesis predicts that happy faces are prioritized. In the present study, which was conducted on 24 participants, change detection paradigm was used, because that procedure enables insight into the later stage of information processing. The results obtained show that happy facial expressions are heavily prioritized by the human cognitive system. In explanation of these results, that clearly support the happy face superiority hypothesis, we propose that angry expressions are initially prioritized by our cognitive system, because we benefit from early detection of potential threat in the environment, but in later cognitive processing, happy expressions are given the priority, because smiling is a valuable mechanism for forming and maintaining cooperative relationships. Besides the theoretical relevance, the present study is also valuable methodologically, because we demonstrated that change detection paradigm can be efficiently used for the research of emotional facial expressions processing.

Sequential Change-Point Detection via Online Convex Optimization

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Yang Cao

2018-02-01

Full Text Available Sequential change-point detection when the distribution parameters are unknown is a fundamental problem in statistics and machine learning. When the post-change parameters are unknown, we consider a set of detection procedures based on sequential likelihood ratios with non-anticipating estimators constructed using online convex optimization algorithms such as online mirror descent, which provides a more versatile approach to tackling complex situations where recursive maximum likelihood estimators cannot be found. When the underlying distributions belong to a exponential family and the estimators satisfy the logarithm regret property, we show that this approach is nearly second-order asymptotically optimal. This means that the upper bound for the false alarm rate of the algorithm (measured by the average-run-length meets the lower bound asymptotically up to a log-log factor when the threshold tends to infinity. Our proof is achieved by making a connection between sequential change-point and online convex optimization and leveraging the logarithmic regret bound property of online mirror descent algorithm. Numerical and real data examples validate our theory.

Detection of reduced interhemispheric cortical communication during task execution in multiple sclerosis patients using functional near-infrared spectroscopy

Science.gov (United States)

Jimenez, Jon J.; Yang, Runze; Nathoo, Nabeela; Varshney, Vishal P.; Golestani, Ali-Mohammad; Goodyear, Bradley G.; Metz, Luanne M.; Dunn, Jeff F.

2014-07-01

Multiple sclerosis (MS) impairs brain activity through demyelination and loss of axons. Increased brain activity is accompanied by increases in microvascular hemoglobin oxygen saturation (oxygenation) and total hemoglobin, which can be measured using functional near-infrared spectroscopy (fNIRS). Due to the potentially reduced size and integrity of the white matter tracts within the corpus callosum, it may be expected that MS patients have reduced functional communication between the left and right sides of the brain; this could potentially be an indicator of disease progression. To assess interhemispheric communication in MS, we used fNIRS during a unilateral motor task and the resting state. The magnitude of the change in hemoglobin parameters in the motor cortex was significantly reduced in MS patients during the motor task relative to healthy control subjects. There was also a significant decrease in interhemispheric communication between the motor cortices (expressed as coherence) in MS patients compared to controls during the motor task, but not during the resting state. fNIRS assessment of interhemispheric coherence during task execution may be a useful marker in disorders with white matter damage or axonal loss, including MS.

Default network connectivity during a working memory task.

Science.gov (United States)

Bluhm, Robyn L; Clark, C Richard; McFarlane, Alexander C; Moores, Kathryn A; Shaw, Marnie E; Lanius, Ruth A

2011-07-01

The default network exhibits correlated activity at rest and has shown decreased activation during performance of cognitive tasks. There has been little investigation of changes in connectivity of this network during task performance. In this study, we examined task-related modulation of connectivity between two seed regions from the default network posterior cingulated cortex (PCC) and medial prefrontal cortex (mPFC) and the rest of the brain in 12 healthy adults. The purpose was to determine (1) whether connectivity within the default network differs between a resting state and performance of a cognitive (working memory) task and (2) whether connectivity differs between these nodes of the default network and other brain regions, particularly those implicated in cognitive tasks. There was little change in connectivity with the other main areas of the default network for either seed region, but moderate task-related changes in connectivity occurred between seed regions and regions outside the default network. For example, connectivity of the mPFC with the right insula and the right superior frontal gyrus decreased during task performance. Increased connectivity during the working memory task occurred between the PCC and bilateral inferior frontal gyri, and between the mPFC and the left inferior frontal gyrus, cuneus, superior parietal lobule, middle temporal gyrus and cerebellum. Overall, the areas showing greater correlation with the default network seed regions during task than at rest have been previously implicated in working memory tasks. These changes may reflect a decrease in the negative correlations occurring between the default and task-positive networks at rest. Copyright © 2010 Wiley-Liss, Inc.

Non-linear laws of echoic memory and auditory change detection in humans

Directory of Open Access Journals (Sweden)

Takeshima Yasuyuki

2010-07-01

Full Text Available Abstract Background The detection of any abrupt change in the environment is important to survival. Since memory of preceding sensory conditions is necessary for detecting changes, such a change-detection system relates closely to the memory system. Here we used an auditory change-related N1 subcomponent (change-N1 of event-related brain potentials to investigate cortical mechanisms underlying change detection and echoic memory. Results Change-N1 was elicited by a simple paradigm with two tones, a standard followed by a deviant, while subjects watched a silent movie. The amplitude of change-N1 elicited by a fixed sound pressure deviance (70 dB vs. 75 dB was negatively correlated with the logarithm of the interval between the standard sound and deviant sound (1, 10, 100, or 1000 ms, while positively correlated with the logarithm of the duration of the standard sound (25, 100, 500, or 1000 ms. The amplitude of change-N1 elicited by a deviance in sound pressure, sound frequency, and sound location was correlated with the logarithm of the magnitude of physical differences between the standard and deviant sounds. Conclusions The present findings suggest that temporal representation of echoic memory is non-linear and Weber-Fechner law holds for the automatic cortical response to sound changes within a suprathreshold range. Since the present results show that the behavior of echoic memory can be understood through change-N1, change-N1 would be a useful tool to investigate memory systems.