WorldWideScience

Sample records for contextual change detection

  1. Anterior prefrontal involvement in implicit contextual change detection

    Directory of Open Access Journals (Sweden)

    Stefan Pollmann

    2009-10-01

    Full Text Available Anterior prefrontal cortex is usually associated with high level executive functions. Here, we show that the frontal pole, specifically left lateral frontopolar cortex, is involved in signaling change in implicitly learned spatial contexts, in the absence of conscious change detection. In a variant of the contextual cueing paradigm, participants first learned implicitly contingencies between distractor contexts and target locations. After learning, repeated distractor contexts were paired with new target locations. Left lateral frontopolar (BA10 and superior frontal (BA9 cortices showed selective signal increase for this target location change in repeated displays in an event-related fMRI experiment, which was most pronounced in participants with high contextual facilitation before the change. The data support the view that left lateral frontopolar cortex is involved in signaling contextual change to posterior brain areas as a precondition for adaptive changes of attentional resource allocation. This signaling occurs in the absence of awareness of learned contingencies or contextual change.

  2. Global scene layout modulates contextual learning in change detection.

    Science.gov (United States)

    Conci, Markus; Müller, Hermann J

    2014-01-01

    Change in the visual scene often goes unnoticed - a phenomenon referred to as "change blindness." This study examined whether the hierarchical structure, i.e., the global-local layout of a scene can influence performance in a one-shot change detection paradigm. To this end, natural scenes of a laid breakfast table were presented, and observers were asked to locate the onset of a new local object. Importantly, the global structure of the scene was manipulated by varying the relations among objects in the scene layouts. The very same items were either presented as global-congruent (typical) layouts or as global-incongruent (random) arrangements. Change blindness was less severe for congruent than for incongruent displays, and this congruency benefit increased with the duration of the experiment. These findings show that global layouts are learned, supporting detection of local changes with enhanced efficiency. However, performance was not affected by scene congruency in a subsequent control experiment that required observers to localize a static discontinuity (i.e., an object that was missing from the repeated layouts). Our results thus show that learning of the global layout is particularly linked to the local objects. Taken together, our results reveal an effect of "global precedence" in natural scenes. We suggest that relational properties within the hierarchy of a natural scene are governed, in particular, by global image analysis, reducing change blindness for local objects through scene learning.

  3. Global scene layout modulates contextual learning in change detection

    Directory of Open Access Journals (Sweden)

    Markus eConci

    2014-02-01

    Full Text Available Change in the visual scene often goes unnoticed – a phenomenon referred to as ‘change blindness’. This study examined whether the hierarchical structure, i.e., the global-local layout of a scene can influence performance in a one-shot change detection paradigm. To this end, natural scenes of a laid breakfast table were presented, and observers were asked to locate the onset of a new local object. Importantly, the global structure of the scene was manipulated by varying the relations among objects in the scene layouts. The very same items were either presented as global-congruent (typical layouts or as global-incongruent (random arrangements. Change blindness was less severe for congruent than for incongruent displays, and this congruency benefit increased with the duration of the experiment. These findings show that global layouts are learned, supporting detection of local changes with enhanced efficiency. However, performance was not affected by scene congruency in a subsequent control experiment that required observers to localize a static discontinuity (i.e., an object that was missing from the repeated layouts. Our results thus show that learning of the global layout is particularly linked to the local objects. Taken together, our results reveal an effect of global precedence in natural scenes. We suggest that relational properties within the hierarchy of a natural scene are governed, in particular, by global image analysis, reducing change blindness for local objects through scene learning.

  4. Contextual remapping in visual search after predictable target-location changes.

    Science.gov (United States)

    Conci, Markus; Sun, Luning; Müller, Hermann J

    2011-07-01

    Invariant spatial context can facilitate visual search. For instance, detection of a target is faster if it is presented within a repeatedly encountered, as compared to a novel, layout of nontargets, demonstrating a role of contextual learning for attentional guidance ('contextual cueing'). Here, we investigated how context-based learning adapts to target location (and identity) changes. Three experiments were performed in which, in an initial learning phase, observers learned to associate a given context with a given target location. A subsequent test phase then introduced identity and/or location changes to the target. The results showed that contextual cueing could not compensate for target changes that were not 'predictable' (i.e. learnable). However, for predictable changes, contextual cueing remained effective even immediately after the change. These findings demonstrate that contextual cueing is adaptive to predictable target location changes. Under these conditions, learned contextual associations can be effectively 'remapped' to accommodate new task requirements.

  5. Experimental Detection of Information Deficit in a Photonic Contextuality Scenario

    Science.gov (United States)

    Zhan, Xiang; Kurzyński, Paweł; Kaszlikowski, Dagomir; Wang, Kunkun; Bian, Zhihao; Zhang, Yongsheng; Xue, Peng

    2017-12-01

    Contextuality is an essential characteristic of quantum theory, and supplies the power for many quantum information processes. Previous tests of contextuality focus mainly on the probability distribution of measurement results. However, a test of contextuality can be formulated in terms of entropic inequalities whose violations imply information deficit in the studied system. This information deficit has not been observed on a single local system. Here we report the first experimental detection of information deficit in an entropic test of quantum contextuality based on photonic setup. The corresponding inequality is violated with more than 13 standard deviations.

  6. Ecological theories of systems and contextual change in medical education.

    Science.gov (United States)

    Ellaway, Rachel H; Bates, Joanna; Teunissen, Pim W

    2017-12-01

    Contemporary medical practice is subject to many kinds of change, to which both individuals and systems have to respond and adapt. Many medical education programmes have their learners rotating through different training contexts, which means that they too must learn to adapt to contextual change. Contextual change presents many challenges to medical education scholars and practitioners, not least because of a somewhat fractured and contested theoretical basis for responding to these challenges. There is a need for robust concepts to articulate and connect the various debates on contextual change in medical education. Ecological theories of systems encompass a range of concepts of how and why systems change and how and why they respond to change. The use of these concepts has the potential to help medical education scholars explore the nature of change and understand the role it plays in affording as well as limiting teaching and learning. This paper, aimed at health professional education scholars and policy makers, explores a number of key concepts from ecological theories of systems to present a comprehensive model of contextual change in medical education to inform theory and practice in all areas of medical education. The paper considers a range of concepts drawn from ecological theories of systems, including biotic and abiotic factors, panarchy, attractors and repellers, basins of attraction, homeostasis, resilience, adaptability, transformability and hysteresis. Each concept is grounded in practical examples from medical education. Ecological theories of systems consider change and response in terms of adaptive cycles functioning at different scales and speeds. This can afford opportunities for systematic consideration of responses to contextual change in medical education, which in turn can inform the design of education programmes, activities, evaluations, assessments and research that accommodates the dynamics and consequences of contextual change.

  7. Negotiating Academic Teacher Identity Shifts during Higher Education Contextual Change

    Science.gov (United States)

    McNaughton, Susan Maree; Billot, Jennie

    2016-01-01

    Higher education teachers' roles and identities are constantly shifting in response to contextual change. Pedagogy, values, and professional and personal narratives of self are all affected, particularly by technological change. This paper explores the role and identity shifts of academics during the introduction of large-class videoconferencing.…

  8. NEW APPROACHES IN DECEPTION DETECTION II. ACTIVE INTERVIEWING STRATEGIES AND CONTEXTUAL INFORMATION

    Directory of Open Access Journals (Sweden)

    Jaume Masip

    2015-05-01

    Full Text Available Meta-analytical evidence shows that behavioural indicators of deception are scant, poorly diagnostic and inconsistent. This has yielded a shift in deception detection research. Rather than passively scrutinising the communication sender to find tell-tale behavioural indicators of deception, the deception judge needs to (a adopt an active role by using interviewing techniques specifically designed to detect deception, or (b focus on contextual (rather than behavioural deception cues. In the previous paper (Masip & Herrero, 2015a, we reviewed the antecedents of this change in focus, as well as the theoretical grounding of the new approaches. Here we describe specific interviewing strategies for detecting deception, as well as the (still scant research on contextual deception indicia. In doing this, we hope to offer the reader a detailed perspective on the recent developments in this specific area of psychology and law.

  9. 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...

  10. Age-related changes in contextual associative learning.

    Science.gov (United States)

    Luu, Trinh T; Pirogovsky, Eva; Gilbert, Paul E

    2008-01-01

    The hippocampus plays a critical role in processing contextual information. Although age-related changes in the hippocampus are well documented in humans, nonhuman primates, and rodents, few studies have examined contextual learning deficits in old rats. The present study investigated age-related differences in contextual associative learning in young (6 mo) and old (24 mo) rats using olfactory stimuli. Stimuli consisted of common odors mixed in sand and placed in clear plastic cups. Testing was conducted in two boxes that represented two different contexts (Context 1 and Context 2). The contexts varied based on environmental features of the box such as color (black vs. white), visual cues on the walls of the box, and flooring texture. Each rat was simultaneously presented with two cups, one filled with Odor A and one filled with Odor B in each context. In Context 1, the rat received a food reward for digging in the cup containing Odor A, but did not receive a food reward for digging in the cup containing Odor B. In Context 2, the rat was rewarded for digging in the cup containing Odor B, but did receive a reward for digging in the cup containing Odor A. Therefore, the rat learned to associate Context 1 with Odor A and Context 2 with Odor B. The rat was tested for eight days using the same odor problem throughout all days of testing. The results showed no significant difference between young and old rats on the first two days of testing; however, young rats significantly outperformed old rats on Day 3. Young rats continued to maintain superior performance compared to old rats on Days 4-8. The results suggest that aging results in functional impairments in brain regions that support memory for associations between specific cues and their respective context.

  11. The hippocampal CA2 ensemble is sensitive to contextual change.

    Science.gov (United States)

    Wintzer, Marie E; Boehringer, Roman; Polygalov, Denis; McHugh, Thomas J

    2014-02-19

    Contextual learning involves associating cues with an environment and relating them to past experience. Previous data indicate functional specialization within the hippocampal circuit: the dentate gyrus (DG) is crucial for discriminating similar contexts, whereas CA3 is required for associative encoding and recall. Here, we used Arc/H1a catFISH imaging to address the contribution of the largely overlooked CA2 region to contextual learning by comparing ensemble codes across CA3, CA2, and CA1 in mice exposed to familiar, altered, and novel contexts. Further, to manipulate the quality of information arriving in CA2 we used two hippocampal mutant mouse lines, CA3-NR1 KOs and DG-NR1 KOs, that result in hippocampal CA3 neuronal activity that is uncoupled from the animal's sensory environment. Our data reveal largely coherent responses across the CA axis in control mice in purely novel or familiar contexts; however, in the mutant mice subject to these protocols the CA2 response becomes uncoupled from CA1 and CA3. Moreover, we show in wild-type mice that the CA2 ensemble is more sensitive than CA1 and CA3 to small changes in overall context. Our data suggest that CA2 may be tuned to remap in response to any conflict between stored and current experience.

  12. On Improving Face Detection Performance by Modelling Contextual Information

    OpenAIRE

    Atanasoaei, Cosmin; McCool, Chris; Marcel, Sébastien

    2010-01-01

    In this paper we present a new method to enhance object detection by removing false alarms and merging multiple detections in a principled way with few parameters. The method models the output of an object classiï¬er which we consider as the context. A hierarchical model is built using the detection distribution around a target sub-window to discriminate between false alarms and true detections. Next the context is used to iteratively reï¬ne the detections. Finally the detections are clustere...

  13. Contextual Weisfeiler-Lehman Graph Kernel For Malware Detection

    OpenAIRE

    Narayanan, Annamalai; Meng, Guozhu; Yang, Liu; Liu, Jinliang; Chen, Lihui

    2016-01-01

    In this paper, we propose a novel graph kernel specifically to address a challenging problem in the field of cyber-security, namely, malware detection. Previous research has revealed the following: (1) Graph representations of programs are ideally suited for malware detection as they are robust against several attacks, (2) Besides capturing topological neighbourhoods (i.e., structural information) from these graphs it is important to capture the context under which the neighbourhoods are reac...

  14. Threat Detection in Tweets with Trigger Patterns and Contextual Cues

    NARCIS (Netherlands)

    Spitters, M.M.; Eendebak, P.T.; Worm, D.T.H.; Bouma, H.

    2014-01-01

    Many threats in the real world can be related to activities in open sources on the internet. Early detection of threats based on internet information could assist in the prevention of incidents. However, the amount of data in social media, blogs and forums rapidly increases and it is time consuming

  15. 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...

  16. Cross-cultural adjustment to the United States: The role of contextualized extraversion change

    Directory of Open Access Journals (Sweden)

    Mengqiao eLiu

    2015-10-01

    Full Text Available Personality traits can predict how well sojourners and expatriates adjust to new cultures, but the adjustment process remains largely unexamined. Based on recent findings that reveal personality traits predict as well as respond to life events and experiences, this research focuses on within-person change in contextualized extraversion and its predictive validity for cross-cultural adjustment in international students who newly arrived in U.S. colleges. We proposed that the initial level as well as the rate of change in school extraversion (i.e., contextualized extraversion that reflects behavioral tendency in school settings will predict cross-cultural adjustment, withdrawal cognitions, and school satisfaction. Latent growth modeling of three-wave longitudinal surveys of 215 new international students (54% female, Mage = 24 years revealed that the initial level of school extraversion significantly predicted cross-cultural adjustment, (lower withdrawal cognitions, and satisfaction, while the rate of change (increase in school extraversion predicted cross-cultural adjustment and (lower withdrawal cognitions. We further modeled global extraversion and cross-cultural motivation as antecedents and explored within-person change in school extraversion as a proximal factor that affects adjustment outcomes. The findings highlight the malleability of contextualized personality, and more importantly, the importance of understanding within-person change in contextualized personality in a cross-cultural adjustment context. The study points to more research that explicate the process of personality change in other contexts.

  17. Cross-cultural adjustment to the United States: the role of contextualized extraversion change.

    Science.gov (United States)

    Liu, Mengqiao; Huang, Jason L

    2015-01-01

    Personality traits can predict how well-sojourners and expatriates adjust to new cultures, but the adjustment process remains largely unexamined. Based on recent findings that reveal personality traits predict as well as respond to life events and experiences, this research focuses on within-person change in contextualized extraversion and its predictive validity for cross-cultural adjustment in international students who newly arrived in US colleges. We proposed that the initial level as well as the rate of change in school extraversion (i.e., contextualized extraversion that reflects behavioral tendency in school settings) will predict cross-cultural adjustment, withdrawal cognitions, and school satisfaction. Latent growth modeling of three-wave longitudinal surveys of 215 new international students (54% female, M age = 24 years) revealed that the initial level of school extraversion significantly predicted cross-cultural adjustment, (lower) withdrawal cognitions, and satisfaction, while the rate of change (increase) in school extraversion predicted cross-cultural adjustment and (lower) withdrawal cognitions. We further modeled global extraversion and cross-cultural motivation as antecedents and explored within-person change in school extraversion as a proximal factor that affects adjustment outcomes. The findings highlight the malleability of contextualized personality, and more importantly, the importance of understanding within-person change in contextualized personality in a cross-cultural adjustment context. The study points to more research that explicate the process of personality change in other contexts.

  18. Cross-cultural adjustment to the United States: the role of contextualized extraversion change

    Science.gov (United States)

    Liu, Mengqiao; Huang, Jason L.

    2015-01-01

    Personality traits can predict how well-sojourners and expatriates adjust to new cultures, but the adjustment process remains largely unexamined. Based on recent findings that reveal personality traits predict as well as respond to life events and experiences, this research focuses on within-person change in contextualized extraversion and its predictive validity for cross-cultural adjustment in international students who newly arrived in US colleges. We proposed that the initial level as well as the rate of change in school extraversion (i.e., contextualized extraversion that reflects behavioral tendency in school settings) will predict cross-cultural adjustment, withdrawal cognitions, and school satisfaction. Latent growth modeling of three-wave longitudinal surveys of 215 new international students (54% female, Mage = 24 years) revealed that the initial level of school extraversion significantly predicted cross-cultural adjustment, (lower) withdrawal cognitions, and satisfaction, while the rate of change (increase) in school extraversion predicted cross-cultural adjustment and (lower) withdrawal cognitions. We further modeled global extraversion and cross-cultural motivation as antecedents and explored within-person change in school extraversion as a proximal factor that affects adjustment outcomes. The findings highlight the malleability of contextualized personality, and more importantly, the importance of understanding within-person change in contextualized personality in a cross-cultural adjustment context. The study points to more research that explicate the process of personality change in other contexts. PMID:26579033

  19. A Contextual Fire Detection Algorithm for Simulated HJ-1B Imagery

    Directory of Open Access Journals (Sweden)

    Xiangsheng Kong

    2009-02-01

    Full Text Available The HJ-1B satellite, which was launched on September 6, 2008, is one of the small ones placed in the constellation for disaster prediction and monitoring. HJ-1B imagery was simulated in this paper, which contains fires of various sizes and temperatures in a wide range of terrestrial biomes and climates, including RED, NIR, MIR and TIR channels. Based on the MODIS version 4 contextual algorithm and the characteristics of HJ-1B sensor, a contextual fire detection algorithm was proposed and tested using simulated HJ-1B data. It was evaluated by the probability of fire detection and false alarm as functions of fire temperature and fire area. Results indicate that when the simulated fire area is larger than 45 m2 and the simulated fire temperature is larger than 800 K, the algorithm has a higher probability of detection. But if the simulated fire area is smaller than 10 m2, only when the simulated fire temperature is larger than 900 K, may the fire be detected. For fire areas about 100 m2, the proposed algorithm has a higher detection probability than that of the MODIS product. Finally, the omission and commission error were evaluated which are important factors to affect the performance of this algorithm. It has been demonstrated that HJ-1B satellite data are much sensitive to smaller and cooler fires than MODIS or AVHRR data and the improved capabilities of HJ-1B data will offer a fine opportunity for the fire detection.

  20. Minimum detection efficiency for the loophole-free confirmation of quantum contextuality

    International Nuclear Information System (INIS)

    Xiang Yang; Hong Fang-Yu

    2013-01-01

    Klyachko—Can—Binicioğlu—Shumovsky (KCBS) inequality is a Bell-like inequality, the violation of which can be used to confirm the existence of quantum contextuality. However, the imperfection of detection efficiency may cause the so-called loophole in actual KCBS's experiments. We derive an alternative KCBS inequality to deal with the loophole in actual KCBS's experiments. We prove that if the experimental data violate this KCBS inequality, the loophole-free violation of the original KCBS inequality will occur. We show that the minimum detection efficiency needed for a loophole-free violation of the KCBS inequality is about 0.9738

  1. 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...

  2. Human Behavioral Contributions to Climate Change: Psychological and Contextual Drivers

    Science.gov (United States)

    Swim, Janet K.; Clayton, Susan; Howard, George S.

    2011-01-01

    We are facing rapid changes in the global climate, and these changes are attributable to human behavior. Humans produce this global impact through our use of natural resources, multiplied by the vast increase in population seen in the past 50 to 100 years. Our goal in this article is to examine the underlying psychosocial causes of human impact,…

  3. Multilevel Contextual 3-D CNNs for False Positive Reduction in Pulmonary Nodule Detection.

    Science.gov (United States)

    Dou, Qi; Chen, Hao; Yu, Lequan; Qin, Jing; Heng, Pheng-Ann

    2017-07-01

    False positive reduction is one of the most crucial components in an automated pulmonary nodule detection system, which plays an important role in lung cancer diagnosis and early treatment. The objective of this paper is to effectively address the challenges in this task and therefore to accurately discriminate the true nodules from a large number of candidates. We propose a novel method employing three-dimensional (3-D) convolutional neural networks (CNNs) for false positive reduction in automated pulmonary nodule detection from volumetric computed tomography (CT) scans. Compared with its 2-D counterparts, the 3-D CNNs can encode richer spatial information and extract more representative features via their hierarchical architecture trained with 3-D samples. More importantly, we further propose a simple yet effective strategy to encode multilevel contextual information to meet the challenges coming with the large variations and hard mimics of pulmonary nodules. The proposed framework has been extensively validated in the LUNA16 challenge held in conjunction with ISBI 2016, where we achieved the highest competition performance metric (CPM) score in the false positive reduction track. Experimental results demonstrated the importance and effectiveness of integrating multilevel contextual information into 3-D CNN framework for automated pulmonary nodule detection in volumetric CT data. While our method is tailored for pulmonary nodule detection, the proposed framework is general and can be easily extended to many other 3-D object detection tasks from volumetric medical images, where the targeting objects have large variations and are accompanied by a number of hard mimics.

  4. Contextual Multi-Scale Region Convolutional 3D Network for Activity Detection

    KAUST Repository

    Bai, Yancheng

    2018-01-28

    Activity detection is a fundamental problem in computer vision. Detecting activities of different temporal scales is particularly challenging. In this paper, we propose the contextual multi-scale region convolutional 3D network (CMS-RC3D) for activity detection. To deal with the inherent temporal scale variability of activity instances, the temporal feature pyramid is used to represent activities of different temporal scales. On each level of the temporal feature pyramid, an activity proposal detector and an activity classifier are learned to detect activities of specific temporal scales. Temporal contextual information is fused into activity classifiers for better recognition. More importantly, the entire model at all levels can be trained end-to-end. Our CMS-RC3D detector can deal with activities at all temporal scale ranges with only a single pass through the backbone network. We test our detector on two public activity detection benchmarks, THUMOS14 and ActivityNet. Extensive experiments show that the proposed CMS-RC3D detector outperforms state-of-the-art methods on THUMOS14 by a substantial margin and achieves comparable results on ActivityNet despite using a shallow feature extractor.

  5. Contextual Multi-Scale Region Convolutional 3D Network for Activity Detection

    KAUST Repository

    Bai, Yancheng; Xu, Huijuan; Saenko, Kate; Ghanem, Bernard

    2018-01-01

    Activity detection is a fundamental problem in computer vision. Detecting activities of different temporal scales is particularly challenging. In this paper, we propose the contextual multi-scale region convolutional 3D network (CMS-RC3D) for activity detection. To deal with the inherent temporal scale variability of activity instances, the temporal feature pyramid is used to represent activities of different temporal scales. On each level of the temporal feature pyramid, an activity proposal detector and an activity classifier are learned to detect activities of specific temporal scales. Temporal contextual information is fused into activity classifiers for better recognition. More importantly, the entire model at all levels can be trained end-to-end. Our CMS-RC3D detector can deal with activities at all temporal scale ranges with only a single pass through the backbone network. We test our detector on two public activity detection benchmarks, THUMOS14 and ActivityNet. Extensive experiments show that the proposed CMS-RC3D detector outperforms state-of-the-art methods on THUMOS14 by a substantial margin and achieves comparable results on ActivityNet despite using a shallow feature extractor.

  6. Changing Avatars, Changing Selves? The Influence of Social and Contextual Expectations on Digital Rendition of Identity.

    Science.gov (United States)

    Triberti, Stefano; Durosini, Ilaria; Aschieri, Filippo; Villani, Daniela; Riva, Giuseppe

    2017-08-01

    Avatar creation is an interesting topic for both video game and social network studies. Research has shown that the creation of avatars is influenced by individual, contextual, and cultural features. Avatars are used to represent aspects of users' personality, but multiple avatars are used in different virtual contexts, as self-presentation strategies may vary according to the different "audiences" to be met online (say: friends, or strangers). Moreover, avatar creation is also influenced by cultural variables, such as gender, as avatars embody stereotypical aspects of being a woman or a man. This research tested whether avatars, as digital self-representations, may change depending on the above-mentioned variables. Ninety-four participants created two avatars to be used in different contexts (video game and job-themed social network). Moreover, two groups of participants were told that they would have met friends or total strangers within the two virtual contexts. Results showed that avatars changed from the game to the job context. Changes involved avatars' transient features (Clothes) more than physical (Body) and symbolic (Accessories) ones, and females changed accessories more than males. Moreover, females who expected to meet friends changed their avatars' bodies significantly more than males in both virtual contexts. The findings are discussed based on literature about computer-mediated communication and online self-disclosure. In conclusion, possible implications of the results for avatar-based interventions and the field of video games and social network design are reviewed.

  7. Human behavioral contributions to climate change: psychological and contextual drivers.

    Science.gov (United States)

    Swim, Janet K; Clayton, Susan; Howard, George S

    2011-01-01

    We are facing rapid changes in the global climate, and these changes are attributable to human behavior. Humans produce this global impact through our use of natural resources, multiplied by the vast increase in population seen in the past 50 to 100 years. Our goal in this article is to examine the underlying psychosocial causes of human impact, primarily through patterns of reproduction and consumption. We identify and distinguish individual, societal, and behavioral predictors of environmental impact. Relevant research in these areas (as well as areas that would be aided by greater attention by psychologists) are reviewed. We conclude by highlighting ethical issues that emerge when considering how to address human behavioral contributions to climate change.

  8. Contextualizing the global relevance of local land change observations

    International Nuclear Information System (INIS)

    Magliocca, N R; Ellis, E C; Oates, T; Schmill, M

    2014-01-01

    To understand global changes in the Earth system, scientists must generalize globally from observations made locally and regionally. In land change science (LCS), local field-based observations are costly and time consuming, and generally obtained by researchers working at disparate local and regional case-study sites chosen for different reasons. As a result, global synthesis efforts in LCS tend to be based on non-statistical inferences subject to geographic biases stemming from data limitations and fragmentation. Thus, a fundamental challenge is the production of generalized knowledge that links evidence of the causes and consequences of local land change to global patterns and vice versa. The GLOBE system was designed to meet this challenge. GLOBE aims to transform global change science by enabling new scientific workflows based on statistically robust, globally relevant integration of local and regional observations using an online social-computational and geovisualization system. Consistent with the goals of Digital Earth, GLOBE has the capability to assess the global relevance of local case-study findings within the context of over 50 global biophysical, land-use, climate, and socio-economic datasets. We demonstrate the implementation of one such assessment – a representativeness analysis – with a recently published meta-study of changes in swidden agriculture in tropical forests. The analysis provides a standardized indicator to judge the global representativeness of the trends reported in the meta-study, and a geovisualization is presented that highlights areas for which sampling efforts can be reduced and those in need of further study. GLOBE will enable researchers and institutions to rapidly share, compare, and synthesize local and regional studies within the global context, as well as contributing to the larger goal of creating a Digital Earth

  9. Applying a Comprehensive Contextual Climate Change Vulnerability Framework to New Zealand's Tourism Industry.

    Science.gov (United States)

    Hopkins, Debbie

    2015-03-01

    Conceptualisations of 'vulnerability' vary amongst scholarly communities, contributing to a wide variety of applications. Research investigating vulnerability to climate change has often excluded non-climatic changes which may contribute to degrees of vulnerability perceived or experienced. This paper introduces a comprehensive contextual vulnerability framework which incorporates physical, social, economic and political factors which could amplify or reduce vulnerability. The framework is applied to New Zealand's tourism industry to explore its value in interpreting a complex, human-natural environment system with multiple competing vulnerabilities. The comprehensive contextual framework can inform government policy and industry decision making, integrating understandings of climate change within the broader context of internal and external social, physical, economic, and institutional stressors.

  10. Penteoostalism & schisms in the Reformed church in Zambia 1996-2001: contextual and identity changes

    OpenAIRE

    Hendriks, H.J.; Soko, L.

    2011-01-01

    This article analyzes the historical, contextual and identity changes that took place in the RCZ between 1996 and 2001 in order to find an answer to the question why it happened. The hypothesis is as follows; The leadership style of church leaders was influenced by the one-party state with its autocratic presidential powers that continued the missionary legacy of autocratic rule. The autocratic leadership style met head on with a new globalizing culture and with the Pentecostal tendencies in ...

  11. Analysis of the moderate resolution imaging spectroradiometer contextual algorithm for small fire detection, Journal of Applied Remote Sensing Vol.3

    Science.gov (United States)

    W. Wang; J.J. Qu; X. Hao; Y. Liu

    2009-01-01

    In the southeastern United States, most wildland fires are of low intensity. A substantial number of these fires cannot be detected by the MODIS contextual algorithm. To improve the accuracy of fire detection for this region, the remote-sensed characteristics of these fires have to be...

  12. No apparent influence of psychometrically-defined schizotypy on orientation-dependent contextual modulation of visual contrast detection

    Directory of Open Access Journals (Sweden)

    Damien J. Mannion

    2017-01-01

    Full Text Available We investigated the relationship between psychometrically-defined schizotypy and the ability to detect a visual target pattern. Target detection is typically impaired by a surrounding pattern (context with an orientation that is parallel to the target, relative to a surrounding pattern with an orientation that is orthogonal to the target (orientation-dependent contextual modulation. Based on reports that this effect is reduced in those with schizophrenia, we hypothesised that there would be a negative relationship between the relative score on psychometrically-defined schizotypy and the relative effect of orientation-dependent contextual modulation. We measured visual contrast detection thresholds and scores on the Oxford-Liverpool Inventory of Feelings and Experiences (O-LIFE from a non-clinical sample (N = 100. Contrary to our hypothesis, we find an absence of a monotonic relationship between the relative magnitude of orientation-dependent contextual modulation of visual contrast detection and the relative score on any of the subscales of the O-LIFE. The apparent difference of this result with previous reports on those with schizophrenia suggests that orientation-dependent contextual modulation may be an informative condition in which schizophrenia and psychometrically-defined schizotypy are dissociated. However, further research is also required to clarify the strength of orientation-dependent contextual modulation in those with schizophrenia.

  13. A contextual model of self-regulation change mechanisms among individuals with addictive disorders.

    Science.gov (United States)

    Roos, Corey R; Witkiewitz, Katie

    2017-11-01

    Numerous behavioral treatments for addictive disorders include components explicitly aimed at targeting self-regulation (e.g., coping and emotion regulation). We first provide a summary of key findings to date among studies that have examined self-regulation as a mechanism of behavior change (MOBC) in behavioral treatments for addictive disorders. Based on our review, we conclude that the role of self-regulation as a MOBC across behavioral treatments for addictive disorders is not well-characterized and findings are inconsistent across studies. For example, our review indicates that there is still inconsistent evidence that coping is a unique MOBC in cognitive-behavioral approaches for addictive behaviors. We propose that there has been slow progress in understanding self-regulation as a MOBC in addiction treatment because of a lack of attention to contextual factors. Accordingly, in the second half of this paper, we propose a contextual model of self-regulation change mechanisms, which emphasizes that the role of various facets of self-regulation as MOBC may depend on contextual factors in the immediate situational context (e.g., fluctuating internal and external cues) and in the broader context in which an individual is embedded (e.g., major life stressors, environmental conditions, dispositions). Additionally, we provide specific recommendations to guide future research for understanding both between-person and within-person self-regulation MOBC in addiction treatment. In particular, we provide key recommendations for how to capitalize on intensive longitudinal measurement methods (e.g., ecological momentary assessment) when bringing a contextual perspective to the study of self-regulation as MOBC in various addiction treatments. Copyright © 2017 Elsevier Ltd. All rights reserved.

  14. Contextual Change After Fear Acquisition Affects Conditioned Responding and the Time Course of Extinction Learning-Implications for Renewal Research.

    Science.gov (United States)

    Sjouwerman, Rachel; Niehaus, Johanna; Lonsdorf, Tina B

    2015-01-01

    Context plays a central role in retrieving (fear) memories. Accordingly, context manipulations are inherent to most return of fear (ROF) paradigms (in particular renewal), involving contextual changes after fear extinction. Context changes are, however, also often embedded during earlier stages of ROF experiments such as context changes between fear acquisition and extinction (e.g., in ABC and ABA renewal). Previous studies using these paradigms have however focused exclusively on the context switch after extinction (i.e., renewal). Thus, the possibility of a general effect of context switch on conditioned responding that may not be conditional to preceding extinction learning remains unstudied. Hence, the current study investigated the impact of a context switch between fear acquisition and extinction on immediate conditioned responding and on the time-course of extinction learning by using a multimodal approach. A group that underwent contextual change after fear conditioning (AB; n = 36) was compared with a group without a contextual change from acquisition to extinction (AA; n = 149), while measuring physiological (skin conductance and fear potentiated startle) measures and subjective fear ratings. Contextual change between fear acquisition and extinction had a pronounced effect on both immediate conditioned responding and on the time course of extinction learning in skin conductance responses and subjective fear ratings. This may have important implications for the mechanisms underlying and the interpretation of the renewal effect (i.e., contextual switch after extinction). Consequently, future studies should incorporate designs and statistical tests that disentangle general effects of contextual change from genuine ROF effects.

  15. The changing food outlet distributions and local contextual factors in the United States.

    Science.gov (United States)

    Chen, Hsin-Jen; Wang, Youfa

    2014-01-16

    Little is known about the dynamics of the food outlet distributions associated with local contextual factors in the U.S. This study examines the changes in food stores/services at the 5-digit Zip Code Tabulated Area (ZCTA5) level in the U.S., and assesses contextual factors associated with the changes. Data from 27,878 ZCTA5s in the contiguous United States without an extreme change in the number of 6 types of food stores/services (supermarkets, small-size grocery stores, convenience stores, fresh/specialty food markets, carry-out restaurants, and full-service restaurants) were used. ZCTA5s' contextual factors were from the 2000 Census. Numbers of food stores/services were derived from the Census Business Pattern databases. Linear regression models assessed contextual factors' influences (racial/ethnic compositions, poverty rate, urbanization level, and foreign-born population%) on 1-year changes in food stores/services during 2000-2001, adjusted for population size, total business change, and census regions. Small-size grocery stores and fresh/specialty food markets increased more and convenience stores decreased more in Hispanic-predominant than other areas. Among supermarket-free places, new supermarkets were less likely to be introduced into black-predominant than white-predominant areas (odds ratio (OR) = 0.52, 95% CI = 0.30-0.92). However, among areas without the following type of store at baseline, supermarket (OR = 0.48 (0.33-0.70)), small-size grocery stores (OR = 1.32 (1.08-1.62)), and fresh/specialty food markets (OR = 0.70 (0.53-0.92)) were less likely to be introduced into areas of low foreign-born population than into areas of high foreign-born population. Higher poverty rate was associated with a greater decrease in supermarket, a less decrease in small-size grocery stores, and a less increase in carry-out restaurants (all p for trends restaurants than suburban areas. Local area characteristics affect 1-year changes in food

  16. Uncertain Reasoning for Detection of Selling Stolen Goods in Online Auctions Using Contextual Information

    Directory of Open Access Journals (Sweden)

    Ladislav Beranek

    2014-01-01

    Full Text Available This work describes the design of a decision support system for detection of fraudulent behavior of selling stolen goods in online auctions. In this system, each seller is associated with a type of certification, namely “proper seller,” “suspect seller,” and “selling stolen goods.” The certification level is determined on the basis of a seller’s behaviors and especially on the basis of contextual information whose origin is outside online auctions portals. In this paper, we focus on representing knowledge about sellers in online auctions, the influence of additional information available from other Internet source, and reasoning on bidders’ trustworthiness under uncertainties using Dempster-Shafer theory of evidence. To demonstrate the practicability of our approach, we performed a case study using real auction data from Czech auction portal Aukro. The analysis results show that our approach can be used to detect selling stolen goods. By applying Dempster-Shafer theory to combine multiple sources of evidence for the detection of this fraudulent behavior, the proposed approach can reduce the number of false positive results in comparison to approaches using a single source of evidence.

  17. How does an invasive social wasp deal with changing contextual cues while foraging?

    Science.gov (United States)

    Lozada, M; D'Adamo, P

    2009-06-01

    In this study, we explore how an invasive social wasp, Vespula germanica (F.), deals with contextual changes while searching for a food source that is no longer available. Four experiments were conducted to evaluate the effect of different degrees of context modification on wasp behavior. Learning sessions consisted of a variable number of feeding trials during which an individual wasp fed from a landmark array made up of a feeder surrounded by four cylinders of the same color. The food and cylinders were subsequently removed from the training site, and this learned landmark array was modified in such a way that information relating to color and/or location of the resulting feeding arrays varied from that previously learned. The results indicate that the color most recently associated with food is prioritized over a formerly learned color, and this pattern is also maintained when wasps have learned the alternative color during a higher number of feeding experiences. This highlights the high plasticity with which V. germanica responds to unpredictable contextual changes while foraging.

  18. The changing food outlet distributions and local contextual factors in the United States

    Science.gov (United States)

    2014-01-01

    Background Little is known about the dynamics of the food outlet distributions associated with local contextual factors in the U.S. This study examines the changes in food stores/services at the 5-digit Zip Code Tabulated Area (ZCTA5) level in the U.S., and assesses contextual factors associated with the changes. Methods Data from 27,878 ZCTA5s in the contiguous United States without an extreme change in the number of 6 types of food stores/services (supermarkets, small-size grocery stores, convenience stores, fresh/specialty food markets, carry-out restaurants, and full-service restaurants) were used. ZCTA5s’ contextual factors were from the 2000 Census. Numbers of food stores/services were derived from the Census Business Pattern databases. Linear regression models assessed contextual factors’ influences (racial/ethnic compositions, poverty rate, urbanization level, and foreign-born population%) on 1-year changes in food stores/services during 2000–2001, adjusted for population size, total business change, and census regions. Results Small-size grocery stores and fresh/specialty food markets increased more and convenience stores decreased more in Hispanic-predominant than other areas. Among supermarket-free places, new supermarkets were less likely to be introduced into black-predominant than white-predominant areas (odds ratio (OR) = 0.52, 95% CI = 0.30-0.92). However, among areas without the following type of store at baseline, supermarket (OR = 0.48 (0.33-0.70)), small-size grocery stores (OR = 1.32 (1.08-1.62)), and fresh/specialty food markets (OR = 0.70 (0.53-0.92)) were less likely to be introduced into areas of low foreign-born population than into areas of high foreign-born population. Higher poverty rate was associated with a greater decrease in supermarket, a less decrease in small-size grocery stores, and a less increase in carry-out restaurants (all p for trends <0.001). Urban areas experienced more increases in full

  19. Contextual change after fear acquisition affects conditioned responding and the time course of extinction learning – Implications for renewal research

    Directory of Open Access Journals (Sweden)

    Rachel eSjouwerman

    2015-12-01

    Full Text Available Context plays a central role in retrieving (fear memories. Accordingly, context manipulations are inherent to most return of fear (ROF paradigms (in particular renewal, involving contextual changes after fear extinction. Context changes are, however, also often embedded during earlier stages of ROF experiments such as context changes between fear acquisition and extinction (e.g. in ABC and ABA renewal. Previous studies using these paradigms have however focused exclusively on the context switch after extinction (i.e. renewal. Thus, the possibility of a general effect of a context switch on conditioned responding that may not be conditional to preceding extinction learning remains unstudied.Hence, the current study investigated the impact of a context switch between fear acquisition and extinction on immediate conditioned responding and on the time-course of extinction learning by using a multimodal approach. A group that underwent contextual change after fear conditioning (AB; n = 36 was compared with a group without a contextual change from acquisition to extinction (AA; n = 149, while measuring autonomic (skin conductance and fear potentiated startle measures and subjective fear ratings. Contextual change between fear acquisition and extinction had a pronounced effect on both immediate conditioned responding and on the time course of extinction learning in skin conductance responses and subjective fear ratings. This may have important implications for the mechanisms underlying and the interpretation of the renewal effect (i.e. contextual switch after extinction. Consequently, future studies should incorporate designs and statistical tests that disentangle general effects of contextual change from genuine ROF effects.

  20. 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...

  1. 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.

  2. 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

  3. Deception Detection: Accuracy Levels Among International Military Officers Using Content and Contextual Questioning Methods

    Science.gov (United States)

    2016-12-01

    deception than any one method on its own. This research project focuses on students at the Naval Postgraduate School (NPS) in Monterey, CA, to...international military officers were also limited on the type of contextual questioning methods and scenarios. These scenarios were not a very good ...research received participation from 52 students . Although the sample size was small, proportionally, 24% is a good response rate for lab research

  4. Sociodemographic and social contextual predictors of multiple health behavior change: data from the Healthy Directions-Small Business study.

    Science.gov (United States)

    Harley, Amy E; Sapp, Amy L; Li, Yi; Marino, Miguel; Quintiliani, Lisa M; Sorensen, Glorian

    2013-03-01

    Multiple modifiable health behaviors contribute to the chronic diseases that are the leading causes of death in the USA. Disparities for meeting recommended health behavior guidelines exist across occupational classes and socioeconomic levels. The purpose of this paper was to investigate sociodemographic and social contextual predictors of multiple health behavior change in a worksite intervention. We analyzed data on four diet and exercise variables from an intervention trial with worksite-level randomization. Eight hundred forty-one employees had complete data from baseline (response rate = 84 %) and follow-up surveys (response rate = 77 %). Multilevel logistic regression estimated associations between least absolute shrinkage and selection operator-selected sociodemographic and social contextual predictor variables and the multiple health behavior change outcome (changing 2+ versus 0 behaviors). Gender, being married/partnered, and perceived discrimination were significantly associated with multiple health behavior change. Sociodemographic and social contextual factors predict multiple health behavior change and could inform the design and delivery of worksite interventions targeting multiple health behaviors.

  5. 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.

  6. Attentional and Contextual Priors in Sound Perception.

    Science.gov (United States)

    Wolmetz, Michael; Elhilali, Mounya

    2016-01-01

    Behavioral and neural studies of selective attention have consistently demonstrated that explicit attentional cues to particular perceptual features profoundly alter perception and performance. The statistics of the sensory environment can also provide cues about what perceptual features to expect, but the extent to which these more implicit contextual cues impact perception and performance, as well as their relationship to explicit attentional cues, is not well understood. In this study, the explicit cues, or attentional prior probabilities, and the implicit cues, or contextual prior probabilities, associated with different acoustic frequencies in a detection task were simultaneously manipulated. Both attentional and contextual priors had similarly large but independent impacts on sound detectability, with evidence that listeners tracked and used contextual priors for a variety of sound classes (pure tones, harmonic complexes, and vowels). Further analyses showed that listeners updated their contextual priors rapidly and optimally, given the changing acoustic frequency statistics inherent in the paradigm. A Bayesian Observer model accounted for both attentional and contextual adaptations found with listeners. These results bolster the interpretation of perception as Bayesian inference, and suggest that some effects attributed to selective attention may be a special case of contextual prior integration along a feature axis.

  7. 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.

  8. Contextual and interdependent causes of climate change adaptation barriers: Insights from water management institutions in Himachal Pradesh, India.

    Science.gov (United States)

    Azhoni, Adani; Holman, Ian; Jude, Simon

    2017-01-15

    Research on adaptation barriers is increasing as the need for climate change adaptation becomes evident. However, empirical studies regarding the emergence, causes and sustenance of adaptation barriers remain limited. This research identifies key contextual causes of adaptation barriers in water institutions in the mountainous Himalayan state of Himachal Pradesh in northern India. Semi-structured interviews were carried out with representatives from twenty-six key governmental, non-governmental, academic and research institutions in the State with responsibilities spanning domestic water supply, irrigation and hydropower generation, environmental monitoring and research. It identified low knowledge capacity and resources, policy implementation gaps, normative attitudes, and unavailability and inaccessibility of data and information compounded with weak interinstitutional networks as key adaptation barriers. Although these barriers are similar to those reported elsewhere, they have important locally-contextual root causes. For instance, inadequate resources result from fragmented resources allocation due to competing developmental priorities and the desire of the political leadership to please diverse electors, rather than climate scepticism. The identified individual barriers are found to be highly inter-dependent and closely intertwined which enables the identification of leverage points for interventions to maximise barrier removal. For instance, breaking down key barriers hindering accessibility to data and information, which are shaped by systemic bureaucracies and cultural attitudes, will involve attitudinal change through sensitisation to the importance of accurate and accessible data and information and the building trust between different actors, in addition to institutional structural changes through legislation and inter-institutional agreements. Approaching barriers as a system of contextually interconnected cultural, systemic, geographical and political

  9. Changing ‘Multi-Problem Families’ – Developing a Multi-Contextual Systemic Approach

    Directory of Open Access Journals (Sweden)

    2007-05-01

    Full Text Available Over the past 30 years the Marlborough Family Service in London has pioneered multi-family work with marginalized families presenting simultaneously with abuse and neglect, family violence, substance misuse, educational failure and mental illness. The approach is based on a systemic multi-contextual mode and this chapter describes the evolving work, including the establishment of the first permanent multiple family day setting, specifically designed for and solely dedicated to the work with seemingly ‘hopeless’ families. The ingredients of ‘therapeutic assessments’ of parents and families are outlined and the importance of initial network meetings with professionals and family members is emphasized.

  10. 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.

  11. 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.

  12. 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

  13. Evidential analysis of difference images for change detection of multitemporal remote sensing images

    Science.gov (United States)

    Chen, Yin; Peng, Lijuan; Cremers, Armin B.

    2018-03-01

    In this article, we develop two methods for unsupervised change detection in multitemporal remote sensing images based on Dempster-Shafer's theory of evidence (DST). In most unsupervised change detection methods, the probability of difference image is assumed to be characterized by mixture models, whose parameters are estimated by the expectation maximization (EM) method. However, the main drawback of the EM method is that it does not consider spatial contextual information, which may entail rather noisy detection results with numerous spurious alarms. To remedy this, we firstly develop an evidence theory based EM method (EEM) which incorporates spatial contextual information in EM by iteratively fusing the belief assignments of neighboring pixels to the central pixel. Secondly, an evidential labeling method in the sense of maximizing a posteriori probability (MAP) is proposed in order to further enhance the detection result. It first uses the parameters estimated by EEM to initialize the class labels of a difference image. Then it iteratively fuses class conditional information and spatial contextual information, and updates labels and class parameters. Finally it converges to a fixed state which gives the detection result. A simulated image set and two real remote sensing data sets are used to evaluate the two evidential change detection methods. Experimental results show that the new evidential methods are comparable to other prevalent methods in terms of total error rate.

  14. Contextualizing Neuro-Collaborations: Reflections on a Transdisciplinary fMRI Lie Detection Experiment

    Directory of Open Access Journals (Sweden)

    Melissa M. Littlefield

    2014-03-01

    Full Text Available Recent neuroscience initiatives (including the E.U.’s Human Brain Project and the U.S.’s BRAIN Initiative have reinvigorated discussions about the possibilities for transdisciplinary collaboration between the neurosciences, the social sciences, and the humanities. As STS scholars have argued for decades, however, such inter- and transdisciplinary collaborations are potentially fraught with tensions between researchers. This essay build on such claims by arguing that the tensions of transdisciplinary research also exist within researchers’ own experiences of working between disciplines – a phenomenon that we call ‘Disciplinary Double Consciousness’ (DDC. Building on previous work that has characterized similar spaces (and especially on the Critical Neuroscience literature, we argue that ‘neuro-collaborations’ inevitably engage researchers in DDC – a phenomenon that allows us to explore the useful dissonance that researchers can experience when working between a home discipline and a secondary discipline. Our case study is a five-year case study in fMRI lie detection involving a transdisciplinary research team made up of social scientists, a neuroscientist, and a humanist. In addition to theorizing neuro-collaborations from the inside-out, this essay presents practical suggestions for developing transdisciplinary infrastructures that could support future neuro-collaborations.

  15. Changes in heart rate variability are associated with expression of short-term and long-term contextual and cued fear memories.

    Directory of Open Access Journals (Sweden)

    Jun Liu

    Full Text Available Heart physiology is a highly useful indicator for measuring not only physical states, but also emotional changes in animals. Yet changes of heart rate variability during fear conditioning have not been systematically studied in mice. Here, we investigated changes in heart rate and heart rate variability in both short-term and long-term contextual and cued fear conditioning. We found that while fear conditioning could increase heart rate, the most significant change was the reduction in heart rate variability which could be further divided into two distinct stages: a highly rhythmic phase (stage-I and a more variable phase (stage-II. We showed that the time duration of the stage-I rhythmic phase were sensitive enough to reflect the transition from short-term to long-term fear memories. Moreover, it could also detect fear extinction effect during the repeated tone recall. These results suggest that heart rate variability is a valuable physiological indicator for sensitively measuring the consolidation and expression of fear memories in mice.

  16. 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

  17. On Contextuality.

    Science.gov (United States)

    Thayer-Bacon, Barbara J.

    This exploration of what feminism has to contribute to pragmatism, and vice versa, considers the idea of contextuality through an examination of the role of current pragmatists, such as Cornel West and Richard Rorty, and current feminists, including Charlene Haddock Siegfried, Maxine Greene, and Seyla Benhabib. To set the stage historically for…

  18. Contextual Autism

    DEFF Research Database (Denmark)

    Raahauge, Kirsten Marie

    2009-01-01

    This project deals with the notion of ghost anthropologically and artistic. The contextual autism of ghosting reveals itself as a sensation of in-betweeness in art as well as in everyday life. The ghost is not easily defined; as Jacques Derrida states in Spectres of Marx (1993/1994) about...

  19. Put a Frame on It: Contextualizing Climate Change for Museum Visitors

    Science.gov (United States)

    Canning, Katharine

    Public opinion polls continue to show that Americans are divided---particularly along political and ideological lines---on whether climate change is real and warrants immediate action. Those in the natural and social sciences have recognized that effective communication is key to closing the gap that exists between scientific and public understanding on this issue. A body of social science research on climate change communication has emerged within the last decade. This field has identified strategies for climate change communicators and educators, emphasizing the importance of framing climate change issues in ways that help it resonate with a wider range of public concerns and values in order to develop a shared belief regarding the necessity of action. Museum exhibits and programs on climate change that were developed within the last five years are likely to have benefitted from this body of work. This qualitative research seeks to examine and analyze the various ways museums in the United States are communicating about climate change related issues to the public. Three case studies of museum exhibits on climate change issues were examined. The scope and purpose of climate change communication in museums, the specific messages that museums are choosing to communicate, and how those messages are being framed for public audiences were explored through these case studies. The findings suggest that museums are considering their audience when framing messages about climate change and have used work from the climate change communication field to inform message development. In particular, museums are making climate change issues more relevant by emphasizing social, economic, and human health concerns, and are considering strategies to counteract fear-fatigue and empower visitors to take action.

  20. Within-Year Changes in Children's Intrinsic and Extrinsic Motivational Orientations: Contextual Predictors and Academic Outcomes

    Science.gov (United States)

    Corpus, Jennifer Henderlong; McClintic-Gilbert, Megan S.; Hayenga, Amynta O.

    2009-01-01

    The present study was designed to investigate the nature, timing, and correlates of motivational change among a large sample (N = 1051) of third- through eighth-grade students. Analyses of within-year changes in students' motivational orientations revealed that both intrinsic and extrinsic motivations decreased from fall to spring, with declines…

  1. A bridge over troubled water: A contextual analysis of social vulnerability to climate change in a riverine landscape in south-east Norway

    Science.gov (United States)

    Vegard Gundersen; Bjorn Petter Kaltenborn; Daniel R. Williams

    2016-01-01

    Local communities in the Gudbrandsdalen region in Norway are increasingly exposed to climateinduced hazards such as floods and landslides. A core question is how community members respond to climate change and what factors contribute to more resilient communities. The authors used a contextual approach to analyze data from semi-structured interviews along five...

  2. Changes in Mothers' Experiences of Receiving an Autism Diagnosis: A Contextualized Case Study

    Science.gov (United States)

    Hornstein, Shana

    2011-01-01

    Autism has a unique history. The definition has broadened and changed over time, from an emotional disturbance with psychogenic origins to a neurodevelopmental disability with suspected environmental and genetic origins. Diagnosis occurs later than children born with obvious disabilities such as cerebral palsy or Down syndrome, but earlier than…

  3. 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

  4. 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.

  5. 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.

  6. Context matters: the experience of 14 research teams in systematically reporting contextual factors important for practice change.

    Science.gov (United States)

    Tomoaia-Cotisel, Andrada; Scammon, Debra L; Waitzman, Norman J; Cronholm, Peter F; Halladay, Jacqueline R; Driscoll, David L; Solberg, Leif I; Hsu, Clarissa; Tai-Seale, Ming; Hiratsuka, Vanessa; Shih, Sarah C; Fetters, Michael D; Wise, Christopher G; Alexander, Jeffrey A; Hauser, Diane; McMullen, Carmit K; Scholle, Sarah Hudson; Tirodkar, Manasi A; Schmidt, Laura; Donahue, Katrina E; Parchman, Michael L; Stange, Kurt C

    2013-01-01

    We aimed to advance the internal and external validity of research by sharing our empirical experience and recommendations for systematically reporting contextual factors. Fourteen teams conducting research on primary care practice transformation retrospectively considered contextual factors important to interpreting their findings (internal validity) and transporting or reinventing their findings in other settings/situations (external validity). Each team provided a table or list of important contextual factors and interpretive text included as appendices to the articles in this supplement. Team members identified the most important contextual factors for their studies. We grouped the findings thematically and developed recommendations for reporting context. The most important contextual factors sorted into 5 domains: (1) the practice setting, (2) the larger organization, (3) the external environment, (4) implementation pathway, and (5) the motivation for implementation. To understand context, investigators recommend (1) engaging diverse perspectives and data sources, (2) considering multiple levels, (3) evaluating history and evolution over time, (4) looking at formal and informal systems and culture, and (5) assessing the (often nonlinear) interactions between contextual factors and both the process and outcome of studies. We include a template with tabular and interpretive elements to help study teams engage research participants in reporting relevant context. These findings demonstrate the feasibility and potential utility of identifying and reporting contextual factors. Involving diverse stakeholders in assessing context at multiple stages of the research process, examining their association with outcomes, and consistently reporting critical contextual factors are important challenges for a field interested in improving the internal and external validity and impact of health care research.

  7. Contextual modulation of social and endocrine correlates of fitness: insights from the life history of a sex changing fish

    Directory of Open Access Journals (Sweden)

    Devaleena S Pradhan

    2015-02-01

    Full Text Available Steroid hormones are critical regulators of reproductive life history, and the steroid sensitive traits (morphology, behavior, physiology associated with particular life history stages can have substantial fitness consequences for an organism. Hormones, behavior and fitness are reciprocally associated and can be used in an integrative fashion to understand how the environment impacts organismal function. To address the fitness component, we highlight the importance of using reliable proxies of reproductive success, when studying proximate regulation of reproductive phenotypes. To understand the mechanisms by which the endocrine system regulates phenotype, we discuss the use of particular endocrine proxies and the need for appropriate functional interpretation of each. Lastly, in any experimental paradigm, the responses of animals vary based on the subtle differences in environmental and social context and this must also be considered. We explore these different levels of analyses by focusing on the fascinating life history transitions exhibited by the bi-directionally hermaphroditic fish, Lythrypnus dalli. Sex changing fish are excellent models for providing a deeper understanding of the fitness consequences associated with the behavioral and endocrine variation. We close by proposing that local regulation of steroids is one potential mechanism that allows for the expression of novel phenotypes that can be characteristic of specific life history stages. A comparative species approach will facilitate progress in understanding the diversity of mechanisms underlying the contextual regulation of phenotypes and their associated fitness correlates.

  8. Contextual modulation of social and endocrine correlates of fitness: insights from the life history of a sex changing fish.

    Science.gov (United States)

    Pradhan, Devaleena S; Solomon-Lane, Tessa K; Grober, Matthew S

    2015-01-01

    Steroid hormones are critical regulators of reproductive life history, and the steroid sensitive traits (morphology, behavior, physiology) associated with particular life history stages can have substantial fitness consequences for an organism. Hormones, behavior and fitness are reciprocally associated and can be used in an integrative fashion to understand how the environment impacts organismal function. To address the fitness component, we highlight the importance of using reliable proxies of reproductive success when studying proximate regulation of reproductive phenotypes. To understand the mechanisms by which the endocrine system regulates phenotype, we discuss the use of particular endocrine proxies and the need for appropriate functional interpretation of each. Lastly, in any experimental paradigm, the responses of animals vary based on the subtle differences in environmental and social context and this must also be considered. We explore these different levels of analyses by focusing on the fascinating life history transitions exhibited by the bi-directionally hermaphroditic fish, Lythrypnus dalli. Sex changing fish are excellent models for providing a deeper understanding of the fitness consequences associated with behavioral and endocrine variation. We close by proposing that local regulation of steroids is one potential mechanism that allows for the expression of novel phenotypes that can be characteristic of specific life history stages. A comparative species approach will facilitate progress in understanding the diversity of mechanisms underlying the contextual regulation of phenotypes and their associated fitness correlates.

  9. 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.

  10. 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)

  11. Benefit sharing: an exploration on the contextual discourse of a changing concept.

    Science.gov (United States)

    Dauda, Bege; Dierickx, Kris

    2013-09-12

    The concept of benefit sharing has been a topical issue on the international stage for more than two decades, gaining prominence in international law, research ethics and political philosophy. In spite of this prominence, the concept of benefit sharing is not devoid of controversies related to its definition and justification. This article examines the discourses and justifications of benefit sharing concept. We examine the discourse on benefit sharing within three main spheres; namely: common heritage of humankind, access and use of genetic resources according to the Convention on Biological Diversity (CBD), and international clinical research. Benefit sharing has changed from a concept that is enshrined in a legally binding regulation in the contexts of common heritage of humankind and CBD to a non-binding regulation in international clinical research. Nonetheless, there are more ethical justifications that accentuate benefit sharing in international clinical research than in the contexts of common heritage of humankind and the CBD. There is a need to develop a legal framework in order to strengthen the advocacy and decisiveness of benefit sharing practice in international health research. Based on this legal framework, research sponsors would be required to provide a minimum set of possible benefits to participants and communities in research. Such legal framework on benefit sharing will encourage research collaboration with local communities; and dispel mistrust between research sponsors and host communities. However, more research is needed, drawing from other international legal frameworks, to understand how such a legal framework on benefit sharing can be successfully formulated in international health research.

  12. 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.

  13. 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.

  14. 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.

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

    Science.gov (United States)

    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.

  16. 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

  17. Contextual Education

    Directory of Open Access Journals (Sweden)

    Janani Harish

    2015-10-01

    Full Text Available When the knowledge gained over centuries has to be presented to students through a 12-15 year study, it has to be abridged and organized elaborately. This process of encapsulating all knowledge into an educational course often results in fragmentation of knowledge and a mental divorce from life. Life knowledge that is reduced to objective principles may be intelligible to the intellect, but is incomprehensible to the imagination, creativity and emotional intelligence, all of which are important to the full development of personality. A study of Economics without the human and social dimensions, industrialization detached from ecology, or science devoid of moral accountability results in problems. Education of each part must be in the context of the whole. Knowing the whole context helps one get the right perspective to address the issue effectively. In the education of the future, the gap between abstract concept and social relevance must be bridged. The following article explores the need for contextual education and the ways in which it can be implemented.

  18. 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

  19. 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.

  20. 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.

  1. 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

  2. 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.

  3. Contextual Fraction as a Measure of Contextuality

    Science.gov (United States)

    Abramsky, Samson; Barbosa, Rui Soares; Mansfield, Shane

    2017-08-01

    We consider the contextual fraction as a quantitative measure of contextuality of empirical models, i.e., tables of probabilities of measurement outcomes in an experimental scenario. It provides a general way to compare the degree of contextuality across measurement scenarios; it bears a precise relationship to violations of Bell inequalities; its value, and a witnessing inequality, can be computed using linear programing; it is monotonic with respect to the "free" operations of a resource theory for contextuality; and it measures quantifiable advantages in informatic tasks, such as games and a form of measurement-based quantum computing.

  4. 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.

  5. 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

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

    Science.gov (United States)

    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.

  7. 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.

  8. 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.

  9. Contextual anomaly detection for cyber-physical security in Smart Grids based on an artificial neural network model

    DEFF Research Database (Denmark)

    Kosek, Anna Magdalena

    2016-01-01

    control. An intrusion detection system observes distributed energy resource’s behaviour, control actions and the power system impact, and is tested together with an ongoing voltage control attack in a co-simulation set-up. The simulation results obtained with a real photovoltaic rooftop power plant data...

  10. Detecting significant changes in protein abundance

    Directory of Open Access Journals (Sweden)

    Kai Kammers

    2015-06-01

    Full Text Available We review and demonstrate how an empirical Bayes method, shrinking a protein's sample variance towards a pooled estimate, leads to far more powerful and stable inference to detect significant changes in protein abundance compared to ordinary t-tests. Using examples from isobaric mass labelled proteomic experiments we show how to analyze data from multiple experiments simultaneously, and discuss the effects of missing data on the inference. We also present easy to use open source software for normalization of mass spectrometry data and inference based on moderated test statistics.

  11. Detectable perfusion changes in MAG3 studies

    International Nuclear Information System (INIS)

    Shuter, B.; Bernar, A.; Roach, P.

    1998-01-01

    Full text: The use of 120 MBq 99m Tc-MAG 3 instead of 600 MBq 99m Tc-DTPA in renal imaging has degraded the images obtained during the perfusion phase. An increase of the minimum detectable change (MDC) in blood flow (BF) would also be expected. In transplant patients, renal BF is an important factor in patient management and the MDC should be small to allow early detection of reduced perfusion. We determined the mean and coefficient of variation (CoV: standard deviation/mean) of three renal perfusion indices as a function of counts in the time-activity curves (TACs). Transplant patients were given a dose of about 300 MBq of 99m Tc-MAG3 and images acquired at 8 fps for 60s. TACs made up from 8, 4, 2 or I images per second allowed calculation of renal perfusion indices as if doses of 300, 150, 75 and 38 MBq had been administered. Perfusion indices based on area under the TACs up to the arterial peak (API), the maximum slopes of the TACs (SPI) and the maximum slope of renal TAC and height of arterial TAC (BPI) were calculated by our routine renal software package. As the administered dose decreased, the CoV rose for all indices, least for BPI and most for API. BPI CoV increased from ∼10% at 300 MBq to 20% at 75 MBq, but API CoV rose from 6% to 46%. Mean BPI was stable over the dose range, but mean API showed a systematic increase of about 50% over the 300 MBq result. We conclude that at 120 MBq the MDC (expressed as 2*CoV) in BF is 30-60%, whereas at 600 MBq it may be as low as 10%, allowing earlier confident detection of a change in BF. The BPI was the preferred perfusion index as its mean value changed little and it had the least CoV at lower activities. The data also imply that relative kidney perfusion in the one individual will be much less accurate with 120 MBq of MAG 3

  12. Detecting and Understanding Changing Arctic Carbon Emissions

    Science.gov (United States)

    Bruhwiler, L.

    2017-12-01

    Warming in the Arctic has proceeded faster than anyplace on Earth. Our current understanding of biogeochemistry suggests that we can expect feedbacks between climate and carbon in the Arctic. Changes in terrestrial fluxes of carbon can be expected as the Arctic warms, and the vast stores of organic carbon frozen in Arctic soils could be mobilized to the atmosphere, with possible significant impacts on global climate. Quantifying trends in Arctic carbon exchanges is important for policymaking because greater reductions in anthropogenic emissions may be required to meet climate goals. Observations of greenhouse gases in the Arctic and globally have been collected for several decades. Analysis of this data does not currently support significantly changed Arctic emissions of CH4, however it is difficult to detect changes in Arctic emissions because of transport from lower latitudes and large inter-annual variability. Unfortunately, current space-based remote sensing systems have limitations at Arctic latitudes. Modeling systems can help untangle the Arctic budget of greenhouse gases, but they are dependent on underlying prior fluxes, wetland distributions and global anthropogenic emissions. Also, atmospheric transport models may have significant biases and errors. For example, unrealistic near-surface stability can lead to underestimation of emissions in atmospheric inversions. We discuss our current understanding of the Arctic carbon budget from both top-down and bottom-up approaches. We show that current atmospheric inversions agree well on the CH4 budget. On the other hand, bottom-up models vary widely in their predictions of natural emissions, with some models predicting emissions too large to be accommodated by the budget implied by global observations. Large emissions from the shallow Arctic ocean are also inconsistent with atmospheric observations. We also discuss the sensitivity of the current atmospheric network to what is likely small, gradual increases in

  13. 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.

  14. What Butterfly Effect? The Contextual Differences in Public Perceptions of the Health Risk Posed by Climate Change

    OpenAIRE

    Stoutenborough, James; Kirkpatrick, Kellee; Field, M.; Vedlitz, Arnold

    2015-01-01

    One of the most difficult aspects of persuading the public to support climate change policy is the lack of recognition that climate change will likely have a direct impact on an individual’s life. Anecdotal evidence and arguments within the media suggest that those who are skeptical of climate change are more likely to believe that the negative externalities associated with climate change will be experienced by others, and, therefore, are not a concern to that individual. This project examine...

  15. Contextual Development: Situating the Social Change Model of Leadership Development within a Broader Reality of Comprehensive Support

    Science.gov (United States)

    Whitten-Andrews, Jeanie

    2016-01-01

    The social change model has proven an effective and widely utilized model assisting college students in leadership development toward positive social change. However, while this particular model gives much needed attention to the process of development leading to social change, it fails to acknowledge the external factors which significantly…

  16. Contextual and interdependent causes of climate change adaptation barriers for water management: responses from regional and local institutions in Himachal Pradesh, India

    Science.gov (United States)

    Azhoni, Adani; Holman, Ian; Jude, Simon

    2016-04-01

    Research on adaptation barriers is gaining increasing prominence as the need for climate change adaptation becomes evident. This research seeks to identify and understand the reasons for key barriers preventing water institutions in the mountainous Himalayan state of Himachal Pradesh in northern India from adapting to climate change. Semi-structured interviews were carried out in January & February 2015 with representatives from twenty-seven key governmental, academic, NGO and commercial institutions in the State, with responsibilities spanning from municipal water supply to irrigation and hydropower generation in addition to environmental conservation. Empirical analysis of the transcripts found that inadequate knowledge capacity, poor implementation of policies, inadequate resources, normative work culture, weak governance, unavailability and inaccessibility of data & information and limited inter-institutional networks are key barriers for adaptation. Although these generic barriers are similar to those reported elsewhere in literature, they are identified as having locally-contextual root causes. For example, the inadequate resources are identified to be occurring as a consequence of the fragmentation of resources allocation among others. This is due to competing developmental priorities and the desire of the political leadership to please the maximum number of electors rather than the more-usual inadequate budgetary allocation and climate scepticism. The identified individual barriers are found to be highly inter-dependent and closely intertwined which enables the identification of leverage points of interventions that can maximise removal of barriers. For example, breaking down key barriers for data and information accessibility will have to involve normative attitudinal change, through sensitisation of the larger picture of the role of accurate and accessible data; changes in working style involving moving from paper-based data management to digital; and

  17. A qualitative study of contextual factors' impact on measures to reduce surgery cancellations.

    Science.gov (United States)

    Hovlid, Einar; Bukve, Oddbjørn

    2014-05-13

    Contextual factors influence quality improvement outcomes. Understanding this influence is important when adapting and implementing interventions and translating improvements into new settings. To date, there is limited knowledge about how contextual factors influence quality improvement processes. In this study, we explore how contextual factors affected measures to reduce surgery cancellations, which are a persistent problem in healthcare. We discuss the usefulness of the theoretical framework provided by the model for understanding success in quality (MUSIQ) for this kind of research. We performed a qualitative case study at Førde Hospital, Norway, where we had previously demonstrated a reduction in surgery cancellations. We interviewed 20 clinicians and performed content analysis to explore how contextual factors affected measures to reduce cancellations of planned surgeries. We identified three common themes concerning how contextual factors influenced the change process: 1) identifying a need to change, 2) facilitating system-wide improvement, and 3) leader involvement and support. Input from patients helped identify a need to change and contributed to the consensus that change was necessary. Reducing cancellations required improving the clinical system. This improvement process was based on a strategy that emphasized the involvement of frontline clinicians in detecting and improving system problems. Clinicians shared information about their work by participating in improvement teams to develop a more complete understanding of the clinical system and its interdependencies. This new understanding allowed clinicians to detect system problems and design adequate interventions. Middle managers' participation in the improvement teams and in regular work processes was important for successfully implementing and adapting interventions. Contextual factors interacted with one another and with the interventions to facilitate changes in the clinical system, reducing

  18. Potential fire detection based on Kalman-driven change detection

    CSIR Research Space (South Africa)

    Van Den Bergh, F

    2009-07-01

    Full Text Available A new active fire event detection algorithm for data collected with the Spinning Enhanced Visible and Infrared Imager (SEVIRI) sensor, based on the extended Kalman filter, is introduced. Instead of using the observed temperatures of the spatial...

  19. What Butterfly Effect? The Contextual Differences in Public Perceptions of the Health Risk Posed by Climate Change

    Directory of Open Access Journals (Sweden)

    James W. Stoutenborough

    2015-08-01

    Full Text Available One of the most difficult aspects of persuading the public to support climate change policy is the lack of recognition that climate change will likely have a direct impact on an individual’s life. Anecdotal evidence and arguments within the media suggest that those who are skeptical of climate change are more likely to believe that the negative externalities associated with climate change will be experienced by others, and, therefore, are not a concern to that individual. This project examines public perceptions of the health risk posed by climate change. Using a large national public opinion survey of adults in the United States, respondents were asked to evaluate the health risk for themselves, their community, the United States, and the world. The results suggest that individuals evaluate the risk for each of these contexts differently. Statistical analyses are estimated to identify the determinants of each risk perception to identify their respective differences. The implications of these findings on support for climate change policy are discussed.

  20. Orthogonal transformations for change detection, Matlab code

    DEFF Research Database (Denmark)

    2005-01-01

    Matlab code to do multivariate alteration detection (MAD) analysis, maximum autocorrelation factor (MAF) analysis, canonical correlation analysis (CCA) and principal component analysis (PCA) on image data.......Matlab code to do multivariate alteration detection (MAD) analysis, maximum autocorrelation factor (MAF) analysis, canonical correlation analysis (CCA) and principal component analysis (PCA) on image data....

  1. A Saliency Guided Semi-Supervised Building Change Detection Method for High Resolution Remote Sensing Images

    Directory of Open Access Journals (Sweden)

    Bin Hou

    2016-08-01

    Full Text Available Characterizations of up to date information of the Earth’s surface are an important application providing insights to urban planning, resources monitoring and environmental studies. A large number of change detection (CD methods have been developed to solve them by utilizing remote sensing (RS images. The advent of high resolution (HR remote sensing images further provides challenges to traditional CD methods and opportunities to object-based CD methods. While several kinds of geospatial objects are recognized, this manuscript mainly focuses on buildings. Specifically, we propose a novel automatic approach combining pixel-based strategies with object-based ones for detecting building changes with HR remote sensing images. A multiresolution contextual morphological transformation called extended morphological attribute profiles (EMAPs allows the extraction of geometrical features related to the structures within the scene at different scales. Pixel-based post-classification is executed on EMAPs using hierarchical fuzzy clustering. Subsequently, the hierarchical fuzzy frequency vector histograms are formed based on the image-objects acquired by simple linear iterative clustering (SLIC segmentation. Then, saliency and morphological building index (MBI extracted on difference images are used to generate a pseudo training set. Ultimately, object-based semi-supervised classification is implemented on this training set by applying random forest (RF. Most of the important changes are detected by the proposed method in our experiments. This study was checked for effectiveness using visual evaluation and numerical evaluation.

  2. Multiculturalism and contextualism

    DEFF Research Database (Denmark)

    Lægaard, Sune

    2015-01-01

    Many political theorists of multiculturalism (e.g. Joseph Carens, Bhikhu Parekh, James Tully) describe their theories as “contextualist.” But it is unclear what “contextualism” means and what difference it makes for political theory. I use a specific prominent example of a multiculturalist...... discussion, namely Tariq Modood’s argument about “moderate secularism,” as a test case and distinguish between different senses of contextualism. I discuss whether the claim that political theory is contextual in each sense is novel and interesting, and whether contextualism is a distinct feature...... of political theory of multiculturalism. I argue that the forms of contextualism which concern the scope and methodology of political theory are sensible, but not novel or distinctive of multiculturalism. I then discuss the more controversial forms of contextualism, which I call political and theoretical...

  3. 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.

  4. Epigenetic changes detected in micropropagated hop plants.

    Science.gov (United States)

    Peredo, Elena L; Arroyo-García, Rosa; Revilla, M Angeles

    2009-07-01

    Micropropagation is a widely used technique in hops (Humulus lupulus L.). However, to the best of our knowledge, the genetic and epigenetic stability of the microplants has never been tested before. In the present study, two hop accessions were established in vitro and micropropagated for 2 years. The genetic and epigenetic stability of the in vitro plants was analyzed with several molecular techniques: random amplified DNA polymorphism (RAPD), retrotransposon microsatellite amplified polymorphism (REMAP), and methylation-sensitive amplification polymorphism (MSAP). No genetic variation among control and treated plants was found, even after 12 cycles of micropropagation. Epigenetic variation was detected, first, when field and in vitro samples were compared. Nearly a 30% of the detected fragments presented the same pattern of alterations in all the vitroplants. Second, lower levels of epigenetic variation were detected among plants from the different subcultures. Part of this detected variation seemed to be accumulated along the 12 sequential subcultures tested.

  5. Activity Level Change Detection for Persistent Surveillance

    National Research Council Canada - National Science Library

    Liu, F; Bush, L. A

    2004-01-01

    .... Instead of traditional target tracking, this approach utilizes GMTI data as moving spots on the ground to estimate the level of activities and detect unusual activities such as military deployments...

  6. Detecting Holocene changes in thermohaline circulation

    OpenAIRE

    Keigwin, L. D.; Boyle, E. A.

    2000-01-01

    Throughout the last glacial cycle, reorganizations of deep ocean water masses were coincident with rapid millennial-scale changes in climate. Climate changes have been less severe during the present interglacial, but evidence for concurrent deep ocean circulation change is ambiguous.

  7. Change Detection in Naturalistic Pictures among Children with Autism

    Science.gov (United States)

    Burack, Jacob A.; Joseph, Shari; Russo, Natalie; Shore, David I.; Porporino, Mafalda; Enns, James T.

    2009-01-01

    Persons with autism often show strong reactions to changes in the environment, suggesting that they may detect changes more efficiently than typically developing (TD) persons. However, Fletcher-Watson et al. (Br J Psychol 97:537-554, 2006) reported no differences between adults with autism and TD adults with a change-detection task. In this study,…

  8. 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

  9. The role of iconic memory in change-detection tasks.

    Science.gov (United States)

    Becker, M W; Pashler, H; Anstis, S M

    2000-01-01

    In three experiments, subjects attempted to detect the change of a single item in a visually presented array of items. Subjects' ability to detect a change was greatly reduced if a blank interstimulus interval (ISI) was inserted between the original array and an array in which one item had changed ('change blindness'). However, change detection improved when the location of the change was cued during the blank ISI. This suggests that people represent more information of a scene than change blindness might suggest. We test two possible hypotheses why, in the absence of a cue, this representation fails to produce good change detection. The first claims that the intervening events employed to create change blindness result in multiple neural transients which co-occur with the to-be-detected change. Poor detection rates occur because a serial search of all the transient locations is required to detect the change, during which time the representation of the original scene fades. The second claims that the occurrence of the second frame overwrites the representation of the first frame, unless that information is insulated against overwriting by attention. The results support the second hypothesis. We conclude that people may have a fairly rich visual representation of a scene while the scene is present, but fail to detect changes because they lack the ability to simultaneously represent two complete visual representations.

  10. Contextual Factors Predict Patterns of Change in Functioning over 10 Years Among Adolescents and Adults with Autism Spectrum Disorders

    OpenAIRE

    Woodman, Ashley C.; Smith, Leann E.; Greenberg, Jan S.; Mailick, Marsha R.

    2016-01-01

    In the present study, we jointly employ and integrate variable- and person-centered approaches to identify groups of individuals with autism spectrum disorders (ASD) who have similar profiles of change over a period of 10 years across three critical domains of functioning: maladaptive behaviors, autism symptoms, and daily living skills. Two distinct developmental profiles were identified. Above and beyond demographic and individual characteristics, aspects of both the educational context (lev...

  11. 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.

  12. 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.

  13. 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....

  14. Kernel principal component analysis for change detection

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg; Morton, J.C.

    2008-01-01

    region acquired at two different time points. If change over time does not dominate the scene, the projection of the original two bands onto the second eigenvector will show change over time. In this paper a kernel version of PCA is used to carry out the analysis. Unlike ordinary PCA, kernel PCA...... with a Gaussian kernel successfully finds the change observations in a case where nonlinearities are introduced artificially....

  15. 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.

  16. A Contextual Analysis of Land-Use and Vegetation Changes in Two Wooded Pastures in the Swiss Jura Mountains

    Directory of Open Access Journals (Sweden)

    Joël Chételat

    2013-03-01

    The most important changes in tree density occurred during World War II and resulted in a more open landscape. The intensive use of wooded pastures during the war was the consequence of a high demand for wood and food resources. Postwar protectionist regulations, agricultural subsidies, and technical improvements maintained considerable pressure on wooded pastures. Storms and drought episodes further exacerbated this process in some areas. The trend then reversed from the 1970s onwards because of the limitations put on milk production and the falling price of wood. This resulted in a more extensive use of pastures, leading to tree encroachment. However, remote sites were more impacted than pastures closer to inhabited areas, which exhibited a trend towards more segregation between grassland and densely wooded pastures. With both extensification and segregation of land use, the complex vegetation mosaic and the landscape diversity that characterize wooded pastures are threatened but still offer good economic opportunities that call for differentiated management strategies.

  17. Time to learn: evidence for two types of attentional guidance in contextual cueing.

    Science.gov (United States)

    Ogawa, Hirokazu; Watanabe, Katsumi

    2010-01-01

    Repetition of the same spatial configurations of a search display implicitly facilitates performance of a visual-search task when the target location in the display is fixed. The improvement of performance is referred to as contextual cueing. We examined whether the association process between target location and surrounding configuration of distractors occurs during active search or at the instant the target is found. To dissociate these two processes, we changed the surrounding configuration of the distractors at the instant of target detection so that the layout where the participants had searched for the target and the layout presented at the instant of target detection differed. The results demonstrated that both processes are responsible for the contextual-cueing effect, but they differ in the accuracies of attentional guidance and their time courses, suggesting that two different types of attentional-guidance processes may be involved in contextual cueing.

  18. Detecting Change-Point via Saddlepoint Approximations

    Institute of Scientific and Technical Information of China (English)

    Zhaoyuan LI; Maozai TIAN

    2017-01-01

    It's well-known that change-point problem is an important part of model statistical analysis.Most of the existing methods are not robust to criteria of the evaluation of change-point problem.In this article,we consider "mean-shift" problem in change-point studies.A quantile test of single quantile is proposed based on saddlepoint approximation method.In order to utilize the information at different quantile of the sequence,we further construct a "composite quantile test" to calculate the probability of every location of the sequence to be a change-point.The location of change-point can be pinpointed rather than estimated within a interval.The proposed tests make no assumptions about the functional forms of the sequence distribution and work sensitively on both large and small size samples,the case of change-point in the tails,and multiple change-points situation.The good performances of the tests are confirmed by simulations and real data analysis.The saddlepoint approximation based distribution of the test statistic that is developed in the paper is of independent interest and appealing.This finding may be of independent interest to the readers in this research area.

  19. 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.

  20. 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...

  1. 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...

  2. 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...

  3. 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...

  4. Detecting evolutionary forces in language change.

    Science.gov (United States)

    Newberry, Mitchell G; Ahern, Christopher A; Clark, Robin; Plotkin, Joshua B

    2017-11-09

    Both language and genes evolve by transmission over generations with opportunity for differential replication of forms. The understanding that gene frequencies change at random by genetic drift, even in the absence of natural selection, was a seminal advance in evolutionary biology. Stochastic drift must also occur in language as a result of randomness in how linguistic forms are copied between speakers. Here we quantify the strength of selection relative to stochastic drift in language evolution. We use time series derived from large corpora of annotated texts dating from the 12th to 21st centuries to analyse three well-known grammatical changes in English: the regularization of past-tense verbs, the introduction of the periphrastic 'do', and variation in verbal negation. We reject stochastic drift in favour of selection in some cases but not in others. In particular, we infer selection towards the irregular forms of some past-tense verbs, which is likely driven by changing frequencies of rhyming patterns over time. We show that stochastic drift is stronger for rare words, which may explain why rare forms are more prone to replacement than common ones. This work provides a method for testing selective theories of language change against a null model and reveals an underappreciated role for stochasticity in language evolution.

  5. 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.

  6. Detection of Hydrological changes of Wujiang River

    Science.gov (United States)

    Dong, L.; Chen, Y.

    2016-12-01

    In the century our earth experienced a rapid environment changes due to strong human activities, which impactedthe earth'shydrology and water resources systems negatively, and causedsevere problems to the society, such as increased flood and drought risk, water pollution and ecosystem degradation. Understanding the variations of hydrological characteristics has important meaning to solve the problem of hydrology and water resources and maintain sustainable development of river basin water resources.This paper takesWujiangriveras an example,which is a typical medium watershedaffected by human activities seriously in southern China.Using the methods of Mann-Kendall test and serial cluster analysis, this paper studies the characteristics and laws of historical hydrological process inWujiang river, detectsthe impact of changing environment to watershed hydrological processes, based on the observed hydrological data of 36 years from 1980 to 2015 in three representative hydrological stationsnamedFenshi,Chixi and Pingshi. The results show that the annual runoffandannual precipitation has some kind of changes.

  7. 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.

  8. Age-dependent changes in autophosphorylation of alpha calcium/calmodulin dependent kinase II in hippocampus and amygdala after contextual fear conditioning.

    Science.gov (United States)

    Fang, Ton; Kasbi, Kamillia; Rothe, Stephanie; Aziz, Wajeeha; Giese, K Peter

    2017-09-01

    The hippocampus and amygdala are essential brain regions responsible for contextual fear conditioning (CFC). The autophosphorylation of alpha calcium-calmodulin kinase II (αCaMKII) at threonine-286 (T286) is a critical step implicated in long-term potentiation (LTP), learning and memory. However, the changes in αCaMKII levels with aging and training in associated brain regions are not fully understood. Here, we studied how aging and training affect the levels of phosphorylated (T286) and proportion of phosphorylated:total αCaMKII in the hippocampus and amygdala. Young and aged mice, naïve (untrained) and trained in CFC, were analysed by immunohistochemistry for the levels of total and phosphorylated αCaMKII in the hippocampus and amygdala. We found that two hours after CFC training, young mice exhibited a higher level of phosphorylated and increased ratio of phosphorylated:total αCaMKII in hippocampal CA3 stratum radiatum. Furthermore, aged untrained mice showed a higher ratio of phosphorylated:total αCaMKII in the CA3 region of the hippocampus when compared to the young untrained group. No effect of training or aging were seen in the central, lateral and basolateral amygdala regions, for both phosphorylated and ratio of phosphorylated:total αCaMKII. These results show that aging impairs the training-induced upregulation of autophosphorylated (T286) αCaMKII in the CA3 stratum radiatum of the hippocampus. This indicates that distinct age-related mechanisms underlie CFC that may rely more heavily on NMDA receptor-dependent plasticity in young age. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

  9. 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.

  10. 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.

  11. 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…

  12. Detection and Attribution of Regional Climate Change

    Energy Technology Data Exchange (ETDEWEB)

    Bala, G; Mirin, A

    2007-01-19

    We developed a high resolution global coupled modeling capability to perform breakthrough studies of the regional climate change. The atmospheric component in our simulation uses a 1{sup o} latitude x 1.25{sup o} longitude grid which is the finest resolution ever used for the NCAR coupled climate model CCSM3. Substantial testing and slight retuning was required to get an acceptable control simulation. The major accomplishment is the validation of this new high resolution configuration of CCSM3. There are major improvements in our simulation of the surface wind stress and sea ice thickness distribution in the Arctic. Surface wind stress and ocean circulation in the Antarctic Circumpolar Current are also improved. Our results demonstrate that the FV version of the CCSM coupled model is a state of the art climate model whose simulation capabilities are in the class of those used for IPCC assessments. We have also provided 1000 years of model data to Scripps Institution of Oceanography to estimate the natural variability of stream flow in California. In the future, our global model simulations will provide boundary data to high-resolution mesoscale model that will be used at LLNL. The mesoscale model would dynamically downscale the GCM climate to regional scale on climate time scales.

  13. 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.

  14. 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.

  15. 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.

  16. Unsupervised land cover change detection: meaningful sequential time series analysis

    CSIR Research Space (South Africa)

    Salmon, BP

    2011-06-01

    Full Text Available An automated land cover change detection method is proposed that uses coarse spatial resolution hyper-temporal earth observation satellite time series data. The study compared three different unsupervised clustering approaches that operate on short...

  17. 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.

  18. 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.

  19. 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.

  20. 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....

  1. Brogaard's Moral Contextualism

    DEFF Research Database (Denmark)

    Binderup, Lars Grassme

    2008-01-01

    Brogaard's non-indexical version of moral contextualism has two related problems. It is unable to account for the function of truth-governed assertoric moral discourse, since it leaves two (semantically clearheaded) disputants without any incentive to resolve seemingly contradictory moral claims....... The moral contextualist could explain why people do feel such an incentive by ascribing false beliefs about the semantic workings of their own language. But, secondly, this leaves Brogaard's moral contextualism looking weaker than a Mackie-style invariantist error theory about morals. The latter is equally...

  2. Tools of Contextualization

    DEFF Research Database (Denmark)

    Bouvin, Niels Olof; Brodersen, Ann Christina; Hansen, Frank Allan

    2005-01-01

    Project based education is growing in importance in elementary schools though it is still quite poorly technologically supported, particularly with respect to actively taking advantage of contextual information. Based on an empirical study of teaching and in particular project based education...... in Danish elementary schools, we present the HyConExplorer, a geospatial hypermedia system supporting project based education and learning outside of the classroom through contextualization of information. More specifically, the HyCon-Explorer provides means for: browsing with your feet, annotating...

  3. 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.

  4. 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

  5. Contextual Text Mining

    Science.gov (United States)

    Mei, Qiaozhu

    2009-01-01

    With the dramatic growth of text information, there is an increasing need for powerful text mining systems that can automatically discover useful knowledge from text. Text is generally associated with all kinds of contextual information. Those contexts can be explicit, such as the time and the location where a blog article is written, and the…

  6. 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.

  7. MULTI-TEMPORAL CLASSIFICATION AND CHANGE DETECTION USING UAV IMAGES

    Directory of Open Access Journals (Sweden)

    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.

  8. 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...

  9. Structuring mobile and contextual learning

    NARCIS (Netherlands)

    Glahn, Christian; Specht, Marcus

    2011-01-01

    Glahn, C., & Specht, M. (2011). Structuring mobile and contextual learning. In Proceedings of the 10th World Conference on Mobile and Contextual Learning (pp. 188-195). October, 18-21, 2011, Beijing, China.

  10. 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.

  11. 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.

  12. 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

  13. 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.

  14. Contextual Variability in Free Recall

    Science.gov (United States)

    Lohnas, Lynn J.; Polyn, Sean M.; Kahana, Michael J.

    2011-01-01

    According to contextual-variability theory, experiences encoded at different times tend to be associated with different contextual states. The gradual evolution of context implies that spaced items will be associated with more distinct contextual states, and thus have more unique retrieval cues, than items presented in proximity. Ross and Landauer…

  15. 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.

  16. 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)

  17. 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.

  18. AN INVESTIGATION OF AUTOMATIC CHANGE DETECTION FOR TOPOGRAPHIC MAP UPDATING

    Directory of Open Access Journals (Sweden)

    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.

  19. 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

  20. Extended image differencing for change detection in UAV video mosaics

    Science.gov (United States)

    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.

  1. 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.

  2. 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.

  3. 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.

  4. 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

  5. Contextuality under weak assumptions

    International Nuclear Information System (INIS)

    Simmons, Andrew W; Rudolph, Terry; Wallman, Joel J; Pashayan, Hakop; Bartlett, Stephen D

    2017-01-01

    The presence of contextuality in quantum theory was first highlighted by Bell, Kochen and Specker, who discovered that for quantum systems of three or more dimensions, measurements could not be viewed as deterministically revealing pre-existing properties of the system. More precisely, no model can assign deterministic outcomes to the projectors of a quantum measurement in a way that depends only on the projector and not the context (the full set of projectors) in which it appeared, despite the fact that the Born rule probabilities associated with projectors are independent of the context. A more general, operational definition of contextuality introduced by Spekkens, which we will term ‘probabilistic contextuality’, drops the assumption of determinism and allows for operations other than measurements to be considered contextual. Even two-dimensional quantum mechanics can be shown to be contextual under this generalised notion. Probabilistic noncontextuality represents the postulate that elements of an operational theory that cannot be distinguished from each other based on the statistics of arbitrarily many repeated experiments (they give rise to the same operational probabilities) are ontologically identical. In this paper, we introduce a framework that enables us to distinguish between different noncontextuality assumptions in terms of the relationships between the ontological representations of objects in the theory given a certain relation between their operational representations. This framework can be used to motivate and define a ‘possibilistic’ analogue, encapsulating the idea that elements of an operational theory that cannot be unambiguously distinguished operationally can also not be unambiguously distinguished ontologically. We then prove that possibilistic noncontextuality is equivalent to an alternative notion of noncontextuality proposed by Hardy. Finally, we demonstrate that these weaker noncontextuality assumptions are sufficient to prove

  6. 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.

  7. 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.

  8. Contextualism in Normative Political Theory

    DEFF Research Database (Denmark)

    Lægaard, Sune

    2016-01-01

    Contextualism denotes a set of ideas about the importance of attention to context. The topic of the article is contextualism in normative political theory/philosophy, in relation to the part of political theory concerned with systematic political argument for normative claims—evaluative claims...... that can be invoked to contextualize a specific object of political discussion such as a law, an institution, or the like. Contextualism denotes any view that political theory should take context into account, but there are many different views about what this means. Contextualism can be characterized...... by way of different contrasts, which imply that the resulting conceptions of contextualism are views about different things, such as justification, the nature of political theory, or methodology. Here the focus is on characterizations of contextualism in terms of methodology and justification...

  9. Contextualizing symbol, symbolizing context

    Science.gov (United States)

    Maudy, Septiani Yugni; Suryadi, Didi; Mulyana, Endang

    2017-08-01

    When students learn algebra for the first time, inevitably they are experiencing transition from arithmetic to algebraic thinking. Once students could apprehend this essential mathematical knowledge, they are cultivating their ability in solving daily life problems by applying algebra. However, as we dig into this transitional stage, we identified possible students' learning obstacles to be dealt with seriously in order to forestall subsequent hindrance in studying more advance algebra. We come to realize this recurring problem as we undertook the processes of re-personalization and re-contextualization in which we scrutinize the very basic questions: 1) what is variable, linear equation with one variable and their relationship with the arithmetic-algebraic thinking? 2) Why student should learn such concepts? 3) How to teach those concepts to students? By positioning ourselves as a seventh grade student, we address the possibility of children to think arithmetically when confronted with the problems of linear equation with one variable. To help them thinking algebraically, Bruner's modes of representation developed contextually from concrete to abstract were delivered to enhance their interpretation toward the idea of variables. Hence, from the outset we designed the context for student to think symbolically initiated by exploring various symbols that could be contextualized in order to bridge student traversing the arithmetic-algebraic fruitfully.

  10. Significant Statistics: Viewed with a Contextual Lens

    Science.gov (United States)

    Tait-McCutcheon, Sandi

    2010-01-01

    This paper examines the pedagogical and organisational changes three lead teachers made to their statistics teaching and learning programs. The lead teachers posed the research question: What would the effect of contextually integrating statistical investigations and literacies into other curriculum areas be on student achievement? By finding the…

  11. Pigeons (Columba livia) show change blindness in a color-change detection task.

    Science.gov (United States)

    Herbranson, Walter T; Jeffers, Jacob S

    2017-07-01

    Change blindness is a phenomenon whereby changes to a stimulus are more likely go unnoticed under certain circumstances. Pigeons learned a change detection task, in which they observed sequential stimulus displays consisting of individual colors back-projected onto three response keys. The color of one response key changed during each sequence and pecks to the key that displayed the change were reinforced. Pigeons showed a change blindness effect, in that change detection accuracy was worse when there was an inter-stimulus interval interrupting the transition between consecutive stimulus displays. Birds successfully transferred to stimulus displays involving novel colors, indicating that pigeons learned a general change detection rule. Furthermore, analysis of responses to specific color combinations showed that pigeons could detect changes involving both spectral and non-spectral colors and that accuracy was better for changes involving greater differences in wavelength. These results build upon previous investigations of change blindness in both humans and pigeons and suggest that change blindness may be a general consequence of selective visual attention relevant to multiple species and stimulus dimensions.

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

    Science.gov (United States)

    Pessoa, Luiz; Ungerleider, Leslie G

    2004-05-01

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

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

    Science.gov (United States)

    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.

  14. Blind spot detection & passive lane change assist systems

    NARCIS (Netherlands)

    Surovtcev, I.

    2015-01-01

    The project goal was design and implementation of proof-of-concept for two systems that aim to tackle the blind spot problem of for the commercial vehicles: Blind Spot Detection and Passive Lane Change Assist functions. The system implementation was done using Rapid Control Prototype (RCP) hardware.

  15. 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...

  16. 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

  17. Fundamental differences in change detection between vision and audition.

    Science.gov (United States)

    Demany, Laurent; Semal, Catherine; Cazalets, Jean-René; Pressnitzer, Daniel

    2010-06-01

    We compared auditory change detection to visual change detection using closely matched stimuli and tasks in the two modalities. On each trial, participants were presented with a test stimulus consisting of ten elements: pure tones with various frequencies for audition, or dots with various spatial positions for vision. The test stimulus was preceded or followed by a probe stimulus consisting of a single element, and two change-detection tasks were performed. In the "present/absent" task, the probe either matched one randomly selected element of the test stimulus or none of them; participants reported present or absent. In the "direction-judgment" task, the probe was always slightly shifted relative to one randomly selected element of the test stimulus; participants reported the direction of the shift. Whereas visual performance was systematically better in the present/absent task than in the direction-judgment task, the opposite was true for auditory performance. Moreover, whereas visual performance was strongly dependent on selective attention and on the time interval separating the probe from the test stimulus, this was not the case for auditory performance. Our results show that small auditory changes can be detected automatically across relatively long temporal gaps, using an implicit memory system that seems to have no similar counterpart in the visual domain.

  18. Reference chart for relative weight change to detect hypernatraemic dehydration

    NARCIS (Netherlands)

    Dommelen, P. van; Wouwe, J.P. van; Breuning-Boers, J.M.; Buuren, S. van; Verkerk, P.H.

    2007-01-01

    Objective: The validity of the rule of thumb that infants may have a weight loss of 10% in the first days after birth is unknown. We assessed the validity of this and other rules to detect breast-fed infants with hypernatraemic dehydration. Design: A reference chart for relative weight change was

  19. Consumer behaviour in district heating systems. Detecting changes

    Energy Technology Data Exchange (ETDEWEB)

    Jonsson, G.R. [University of Iceland (Iceland). Dept. of Mechanical and Industrial Engineering

    2002-10-01

    This paper focuses on methods or measures that can be used to detect changes in the consumer behavior regarding hot water use. This is done by estimating models that describe the average daily flow using several climate variables as input variables. (orig.)

  20. 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.

  1. 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.

  2. 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)

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

    Science.gov (United States)

    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.

  4. Drillstring Washout Diagnosis Using Friction Estimation and Statistical Change Detection

    DEFF Research Database (Denmark)

    Willersrud, Anders; Blanke, Mogens; Imsland, Lars

    2015-01-01

    In oil and gas drilling, corrosion or tensile stress can give small holes in the drillstring, which can cause leakage and prevent sufficient flow of drilling fluid. If such washout remains undetected and develops, the consequence can be a complete twist-off of the drillstring. Aiming at early...... washout diagnosis, this paper employs an adaptive observer to estimate friction parameters in the nonlinear pro- cess. Non-Gaussian noise is a nuisance in the parameter estimates, and dedicated generalized likelihood tests are developed to make efficient washout detection with the multivariate t...... -distribution encountered in data. Change detection methods are developed using logged sensor data from a horizontal 1400 m managed pressure drilling test rig. Detection scheme design is conducted using probabilities for false alarm and detection to determine thresholds in hypothesis tests. A multivariate...

  5. Probability of detection of clinical seizures using heart rate changes.

    Science.gov (United States)

    Osorio, Ivan; Manly, B F J

    2015-08-01

    Heart rate-based seizure detection is a viable complement or alternative to ECoG/EEG. This study investigates the role of various biological factors on the probability of clinical seizure detection using heart rate. Regression models were applied to 266 clinical seizures recorded from 72 subjects to investigate if factors such as age, gender, years with epilepsy, etiology, seizure site origin, seizure class, and data collection centers, among others, shape the probability of EKG-based seizure detection. Clinical seizure detection probability based on heart rate changes, is significantly (pprobability of detecting clinical seizures (>0.8 in the majority of subjects) using heart rate is highest for complex partial seizures, increases with a patient's years with epilepsy, is lower for females than for males and is unrelated to the side of hemisphere origin. Clinical seizure detection probability using heart rate is multi-factorially dependent and sufficiently high (>0.8) in most cases to be clinically useful. Knowledge of the role that these factors play in shaping said probability will enhance its applicability and usefulness. Heart rate is a reliable and practical signal for extra-cerebral detection of clinical seizures originating from or spreading to central autonomic network structures. Copyright © 2015 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

  6. Water Feature Extraction and Change Detection Using Multitemporal Landsat Imagery

    Directory of Open Access Journals (Sweden)

    Komeil Rokni

    2014-05-01

    Full Text Available Lake Urmia is the 20th largest lake and the second largest hyper saline lake (before September 2010 in the world. It is also the largest inland body of salt water in the Middle East. Nevertheless, the lake has been in a critical situation in recent years due to decreasing surface water and increasing salinity. This study modeled the spatiotemporal changes of Lake Urmia in the period 2000–2013 using the multi-temporal Landsat 5-TM, 7-ETM+ and 8-OLI images. In doing so, the applicability of different satellite-derived indexes including Normalized Difference Water Index (NDWI, Modified NDWI (MNDWI, Normalized Difference Moisture Index (NDMI, Water Ratio Index (WRI, Normalized Difference Vegetation Index (NDVI, and Automated Water Extraction Index (AWEI were investigated for the extraction of surface water from Landsat data. Overall, the NDWI was found superior to other indexes and hence it was used to model the spatiotemporal changes of the lake. In addition, a new approach based on Principal Components of multi-temporal NDWI (NDWI-PCs was proposed and evaluated for surface water change detection. The results indicate an intense decreasing trend in Lake Urmia surface area in the period 2000–2013, especially between 2010 and 2013 when the lake lost about one third of its surface area compared to the year 2000. The results illustrate the effectiveness of the NDWI-PCs approach for surface water change detection, especially in detecting the changes between two and three different times, simultaneously.

  7. 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)

  8. Region-Based Building Rooftop Extraction and Change Detection

    Science.gov (United States)

    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.

  9. REGION-BASED BUILDING ROOFTOP EXTRACTION AND CHANGE DETECTION

    Directory of Open Access Journals (Sweden)

    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.

  10. 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).

  11. Contextualizing aquired brain damage

    DEFF Research Database (Denmark)

    Nielsen, Charlotte Marie Bisgaard

    2014-01-01

    Contextualizing aquired brain damage Traditional approaches study ’communicational problems’ often in a discourse of disabledness or deficitness. With an ontology of communcation as something unique and a presupposed uniqueness of each one of us, how could an integrational approach (Integrational...... for people with aquired brain injuries will be presented and comparatively discussed in a traditional versus an integrational perspective. Preliminary results and considerations on ”methods” and ”participation” from this study will be presented along with an overview of the project's empirical data....

  12. Action Centered Contextual Bandits.

    Science.gov (United States)

    Greenewald, Kristjan; Tewari, Ambuj; Klasnja, Predrag; Murphy, Susan

    2017-12-01

    Contextual bandits have become popular as they offer a middle ground between very simple approaches based on multi-armed bandits and very complex approaches using the full power of reinforcement learning. They have demonstrated success in web applications and have a rich body of associated theoretical guarantees. Linear models are well understood theoretically and preferred by practitioners because they are not only easily interpretable but also simple to implement and debug. Furthermore, if the linear model is true, we get very strong performance guarantees. Unfortunately, in emerging applications in mobile health, the time-invariant linear model assumption is untenable. We provide an extension of the linear model for contextual bandits that has two parts: baseline reward and treatment effect. We allow the former to be complex but keep the latter simple. We argue that this model is plausible for mobile health applications. At the same time, it leads to algorithms with strong performance guarantees as in the linear model setting, while still allowing for complex nonlinear baseline modeling. Our theory is supported by experiments on data gathered in a recently concluded mobile health study.

  13. 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....

  14. Segment-based change detection for polarimetric SAR data

    DEFF Research Database (Denmark)

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

    2006-01-01

    that is needed compared to single polarisation SAR to provide reliable and robust detection of changes. Polarimetric SAR data will be available from satellites in the near future, e.g. the Japanese ALOS, the Canadian Radarsat-2 and the German TerraSAR-X. An appropriate way of representing multi-look fully...... be split into a number of smaller fields, a building may be removed from or added to some area, hedgerows may be removed/added or other type of vegetated areas may be partly removed or added. In this case, ambiguities may arise when segments have changed shape and extent from one image to another...

  15. A structural framework for anomalous change detection and characterization

    Energy Technology Data Exchange (ETDEWEB)

    Prasad, Lakshman [Los Alamos National Laboratory; Theiler, James P [Los Alamos National Laboratory

    2009-01-01

    We present a spatially adaptive scheme for automatically searching a pair of images of a scene for unusual and interesting changes. Our motivation is to bring into play structural aspects of image features alongside the spectral attributes used for anomalous change detection (ACD). We leverage a small but informative subset of pixels, namely edge pixels of the images, as anchor points of a Delaunay triangulation to jointly decompose the images into a set of triangular regions, called trixels, which are spectrally uniform. Such decomposition helps in image regularization by simple-function approximation on a feature-adaptive grid. Applying ACD to this trixel grid instead of pixels offers several advantages. It allows: (1) edge-preserving smoothing of images, (2) speed-up of spatial computations by significantly reducing the representation of the images, and (3) the easy recovery of structure of the detected anomalous changes by associating anomalous trixels with polygonal image features. The latter facility further enables the application of shape-theoretic criteria and algorithms to characterize the changes and recognize them as interesting or not. This incorporation of spatial information has the potential to filter out some spurious changes, such as due to parallax, shadows, and misregistration, by identifying and filtering out those that are structurally similar and spatially pervasive. Our framework supports the joint spatial and spectral analysis of images, potentially enabling the design of more robust ACD algorithms.

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

    Science.gov (United States)

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

    2014-08-01

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

  17. Happy Face Superiority Effect in Change Detection Paradigm

    Directory of Open Access Journals (Sweden)

    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.

  18. 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).

  19. Applications of Graph-Theoretic Tests to Online Change Detection

    Science.gov (United States)

    2014-05-09

    stock broker decides to sell a majority of his positions due to a change in the markets; a child grabs a snack because he has become hungry; an alarm...detected and the time when a negative result will occur (i.e. machine death through mechanical failure) or a positive chance squandered (not buying ...and moving low pressure systems in the atmosphere, and these systems cause persistence to daily rainfall. The daily weather in this area is a

  20. Rainfall distribution and change detection across climatic zones in Nigeria

    OpenAIRE

    Stephen Bunmi Ogungbenro; Tobi Eniolu Morakinyo

    2014-01-01

    Nigerian agriculture is mainly rain-fed and basically dependent on the vagaries of weather especially rainfall. Nigeria today has about forty-four (44) weather observation stations which provide measurement of rainfall amount for different locations across the country. Hence, this study investigates change detection in rainfall pattern over each climatic zone of Nigeria. Data were collected for 90 years (1910–1999) period for all the weather observation stations in Nigeria, while a subdivisio...

  1. 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.

  2. Ice Sheet Change Detection by Satellite Image Differencing

    Science.gov (United States)

    Bindschadler, Robert A.; Scambos, Ted A.; Choi, Hyeungu; Haran, Terry M.

    2010-01-01

    Differencing of digital satellite image pairs highlights subtle changes in near-identical scenes of Earth surfaces. Using the mathematical relationships relevant to photoclinometry, we examine the effectiveness of this method for the study of localized ice sheet surface topography changes using numerical experiments. We then test these results by differencing images of several regions in West Antarctica, including some where changes have previously been identified in altimeter profiles. The technique works well with coregistered images having low noise, high radiometric sensitivity, and near-identical solar illumination geometry. Clouds and frosts detract from resolving surface features. The ETM(plus) sensor on Landsat-7, ALI sensor on EO-1, and MODIS sensor on the Aqua and Terra satellite platforms all have potential for detecting localized topographic changes such as shifting dunes, surface inflation and deflation features associated with sub-glacial lake fill-drain events, or grounding line changes. Availability and frequency of MODIS images favor this sensor for wide application, and using it, we demonstrate both qualitative identification of changes in topography and quantitative mapping of slope and elevation changes.

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

    Science.gov (United States)

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

    2017-12-01

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

  4. 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.

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

    International Nuclear Information System (INIS)

    Byler, E.

    1997-01-01

    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. The ABCD image processing software was installed on a robotic vehicle developed under a related DOE/FETC contract DE-AC21-92MC29112 Intelligent Mobile Sensor System (IMSS) and integrated with the electronics and software. This vehicle was designed especially to navigate in DOE Waste Storage Facilities. Initial system testing was performed at Fernald in June 1996. After some further development and more extensive integration the prototype integrated system was installed and tested at the Radioactive Waste Management Facility (RWMC) at INEEL beginning in April 1997 through the present (November 1997). The integrated system, composed of ABCD imaging software and IMSS mobility base, is called MISS EVE (Mobile Intelligent Sensor System--Environmental Validation Expert). Evaluation of the integrated system in RWMC Building 628, containing approximately 10,000 drums, demonstrated an easy to use system with the ability to properly navigate through the facility, image all the defined drums, and process the results into a report delivered to the operator on a GUI interface and on hard copy. Further work is needed to make the brassboard system more operationally robust

  6. Change detection in a time series of polarimetric SAR images

    DEFF Research Database (Denmark)

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

    A test statistic for the equality of two or several variance-covariance matrices following the real (as opposed to the complex) Wishart distribution with an associated probability of finding a smaller value of the test statistic is described in the literature [1]. In 2003 we introduced a test...... statistic for the equality of two variance-covariance matrices following the complex Wishart distribution with an associated probability measure [2]. In that paper we also demonstrated the use of the test statistic to change detection over time in both fully polarimetric and azimuthal symmetric SAR data...... positives (postulating a change when there actually is none) and/or false negatives (missing an actual change). Therefore we need to test for equality for all time points simultaneously. In this paper we demonstrate a new test statistic for the equality of several variance-covariance matrices from the real...

  7. 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...

  8. 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.

  9. 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.

  10. VEHICLE LOCALIZATION BY LIDAR POINT CORRELATION IMPROVED BY CHANGE DETECTION

    Directory of Open Access Journals (Sweden)

    A. Schlichting

    2016-06-01

    Full Text Available LiDAR sensors are proven sensors for accurate vehicle localization. Instead of detecting and matching features in the LiDAR data, we want to use the entire information provided by the scanners. As dynamic objects, like cars, pedestrians or even construction sites could lead to wrong localization results, we use a change detection algorithm to detect these objects in the reference data. If an object occurs in a certain number of measurements at the same position, we mark it and every containing point as static. In the next step, we merge the data of the single measurement epochs to one reference dataset, whereby we only use static points. Further, we also use a classification algorithm to detect trees. For the online localization of the vehicle, we use simulated data of a vertical aligned automotive LiDAR sensor. As we only want to use static objects in this case as well, we use a random forest classifier to detect dynamic scan points online. Since the automotive data is derived from the LiDAR Mobile Mapping System, we are able to use the labelled objects from the reference data generation step to create the training data and further to detect dynamic objects online. The localization then can be done by a point to image correlation method using only static objects. We achieved a localization standard deviation of about 5 cm (position and 0.06° (heading, and were able to successfully localize the vehicle in about 93 % of the cases along a trajectory of 13 km in Hannover, Germany.

  11. Vehicle Localization by LIDAR Point Correlation Improved by Change Detection

    Science.gov (United States)

    Schlichting, A.; Brenner, C.

    2016-06-01

    LiDAR sensors are proven sensors for accurate vehicle localization. Instead of detecting and matching features in the LiDAR data, we want to use the entire information provided by the scanners. As dynamic objects, like cars, pedestrians or even construction sites could lead to wrong localization results, we use a change detection algorithm to detect these objects in the reference data. If an object occurs in a certain number of measurements at the same position, we mark it and every containing point as static. In the next step, we merge the data of the single measurement epochs to one reference dataset, whereby we only use static points. Further, we also use a classification algorithm to detect trees. For the online localization of the vehicle, we use simulated data of a vertical aligned automotive LiDAR sensor. As we only want to use static objects in this case as well, we use a random forest classifier to detect dynamic scan points online. Since the automotive data is derived from the LiDAR Mobile Mapping System, we are able to use the labelled objects from the reference data generation step to create the training data and further to detect dynamic objects online. The localization then can be done by a point to image correlation method using only static objects. We achieved a localization standard deviation of about 5 cm (position) and 0.06° (heading), and were able to successfully localize the vehicle in about 93 % of the cases along a trajectory of 13 km in Hannover, Germany.

  12. 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...

  13. Growth Curve Analysis and Change-Points Detection in Extremes

    KAUST Repository

    Meng, Rui

    2016-05-15

    The thesis consists of two coherent projects. The first project presents the results of evaluating salinity tolerance in barley using growth curve analysis where different growth trajectories are observed within barley families. The study of salinity tolerance in plants is crucial to understanding plant growth and productivity. Because fully-automated smarthouses with conveyor systems allow non-destructive and high-throughput phenotyping of large number of plants, it is now possible to apply advanced statistical tools to analyze daily measurements and to study salinity tolerance. To compare different growth patterns of barley variates, we use functional data analysis techniques to analyze the daily projected shoot areas. In particular, we apply the curve registration method to align all the curves from the same barley family in order to summarize the family-wise features. We also illustrate how to use statistical modeling to account for spatial variation in microclimate in smarthouses and for temporal variation across runs, which is crucial for identifying traits of the barley variates. In our analysis, we show that the concentrations of sodium and potassium in leaves are negatively correlated, and their interactions are associated with the degree of salinity tolerance. The second project studies change-points detection methods in extremes when multiple time series data are available. Motived by the scientific question of whether the chances to experience extreme weather are different in different seasons of a year, we develop a change-points detection model to study changes in extremes or in the tail of a distribution. Most of existing models identify seasons from multiple yearly time series assuming a season or a change-point location remains exactly the same across years. In this work, we propose a random effect model that allows the change-point to vary from year to year, following a given distribution. Both parametric and nonparametric methods are developed

  14. 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.

  15. 基于MRF的多时相SAR影像非监督变化检测%Unsupervised Change Detection in Multitemporal SAR Images Using MRF Models

    Institute of Scientific and Technical Information of China (English)

    江利明; 廖明生; 张路; 林珲

    2007-01-01

    An unsupervised change-detection method that considers the spatial contextual information in a log-ratio difference image generated from multitemporal SAR images is proposed. A Markov random filed (MRF) model is particularly employed to exploit statistical spatial correlation of intensity levels among neighboring pixels. Under the assumption of the independency of pixels and mixed Gaussian distribution in the log-ratio difference image, a stochastic and iterative EM-MPM change-detection algorithm based on an MRF model is developed. The EM-MPM algorithm is based on a maximiser of posterior marginals (MPM) algorithm for image segmentation and an expectation-maximum (EM) algorithm for parameter estimation in a completely automatic way. The experiment results obtained on multitemporal ERS-2 SAR images show the effectiveness of the proposed method.

  16. Using the Contextual Hub Analysis Tool (CHAT) in Cytoscape to Identify Contextually Relevant Network Hubs.

    Science.gov (United States)

    Muetze, Tanja; Lynn, David J

    2017-09-13

    Highly connected nodes in biological networks are called network hubs. Hubs are topologically important to the structure of the network and have been shown to be preferentially associated with a range of phenotypes of interest. The relative importance of a hub node, however, can change depending on the biological context. Here, we provide a step-by-step protocol for using the Contextual Hub Analysis Tool (CHAT), an application within Cytoscape 3, which enables users to easily construct and visualize a network of interactions from a gene or protein list of interest, integrate contextual information, such as gene or protein expression data, and identify hub nodes that are more highly connected to contextual nodes than expected by chance. © 2017 by John Wiley & Sons, Inc. Copyright © 2017 John Wiley & Sons, Inc.

  17. Sequential Change-Point Detection via Online Convex Optimization

    Directory of Open Access Journals (Sweden)

    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.

  18. 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.

  19. Early detection of structual changes in random signal

    International Nuclear Information System (INIS)

    Kuroda, Yoshiteru; Yokota, Katsuhiro

    1981-01-01

    Early detection of structual changes in observed random signal is very important from the point of system diagnosis. In this paper, the following procedures are applied to this problem and the results are compared. (1) auto-regressive model to random signal to calculate the prediction error, i.e., the defference between observed and predicted values. (2) auto-regressive method to caluculate the sum of the prediction error. (3) a method is based on AIC (Akaike Information Criterion). Simulation is made of these procedures, indicating their merits and demerits as a diagostic tools. (author)

  20. Image change detection systems, methods, and articles of manufacture

    Science.gov (United States)

    Jones, James L.; Lassahn, Gordon D.; Lancaster, Gregory D.

    2010-01-05

    Aspects of the invention relate to image change detection systems, methods, and articles of manufacture. According to one aspect, a method of identifying differences between a plurality of images is described. The method includes loading a source image and a target image into memory of a computer, constructing source and target edge images from the source and target images to enable processing of multiband images, displaying the source and target images on a display device of the computer, aligning the source and target edge images, switching displaying of the source image and the target image on the display device, to enable identification of differences between the source image and the target image.

  1. 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.

  2. 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

  3. Tool successfully detects changes in cathodic protection system

    Energy Technology Data Exchange (ETDEWEB)

    Anon.

    2011-05-15

    A new oil and gas industry tool has been developed to check if an operator's cathodic protection (CP) is effective. This inline inspection tool developed, by Baker Hughes, is called cathodic protection current measurement (CPCM). It measures how much CP current the pipeline is receiving and shows the direction of the current flowing back to the CP source. This system was used to successfully perform a full CP current inspection on a 43 mile-long pipeline in the Eastern United States. Tests identified that one rectifier was flowing current in the reverse direction from that expected and that a few areas had high current densities. The operator then changed the CP system to test the tool and results showed that the tool correctly detected the changes.

  4. Radiation detection using the color changes of lilac spodumene

    International Nuclear Information System (INIS)

    Oliveira, Raquel A.P.; Mello, Ana Carolina S.; Lima, Hestia R.B.R.; Campos, Simara Santos; Souza, Suzana O.

    2009-01-01

    The use of radiation in industrial processes currently offers several advantages in the field of sterilization of medical and pharmaceuticals products, the preservation of food, and a variety of other products widely used in modern society. A dosimetry of confidence is a key parameter for the quality assurance of radiation processing and the irradiated products. This work investigates dosimetric properties in natural spodumene, LiAlSi 2 O 6 , called kunzite, from Minas Gerais State, Brazil. After X irradiation on the samples in powder form was detected a change in color of the crystal where the dose received. This makes a possible viability of this material is applied in research on development of radiation detectors using the change in color of purple spodumene. (author)

  5. Global Repetition Influences Contextual Cueing

    Science.gov (United States)

    Zang, Xuelian; Zinchenko, Artyom; Jia, Lina; Li, Hong

    2018-01-01

    Our visual system has a striking ability to improve visual search based on the learning of repeated ambient regularities, an effect named contextual cueing. Whereas most of the previous studies investigated contextual cueing effect with the same number of repeated and non-repeated search displays per block, the current study focused on whether a global repetition frequency formed by different presentation ratios between the repeated and non-repeated configurations influence contextual cueing effect. Specifically, the number of repeated and non-repeated displays presented in each block was manipulated: 12:12, 20:4, 4:20, and 4:4 in Experiments 1–4, respectively. The results revealed a significant contextual cueing effect when the global repetition frequency is high (≥1:1 ratio) in Experiments 1, 2, and 4, given that processing of repeated displays was expedited relative to non-repeated displays. Nevertheless, the contextual cueing effect reduced to a non-significant level when the repetition frequency reduced to 4:20 in Experiment 3. These results suggested that the presentation frequency of repeated relative to the non-repeated displays could influence the strength of contextual cueing. In other words, global repetition statistics could be a crucial factor to mediate contextual cueing effect. PMID:29636716

  6. Contextual sensitivity in scientific reproducibility.

    Science.gov (United States)

    Van Bavel, Jay J; Mende-Siedlecki, Peter; Brady, William J; Reinero, Diego A

    2016-06-07

    In recent years, scientists have paid increasing attention to reproducibility. For example, the Reproducibility Project, a large-scale replication attempt of 100 studies published in top psychology journals found that only 39% could be unambiguously reproduced. There is a growing consensus among scientists that the lack of reproducibility in psychology and other fields stems from various methodological factors, including low statistical power, researcher's degrees of freedom, and an emphasis on publishing surprising positive results. However, there is a contentious debate about the extent to which failures to reproduce certain results might also reflect contextual differences (often termed "hidden moderators") between the original research and the replication attempt. Although psychologists have found extensive evidence that contextual factors alter behavior, some have argued that context is unlikely to influence the results of direct replications precisely because these studies use the same methods as those used in the original research. To help resolve this debate, we recoded the 100 original studies from the Reproducibility Project on the extent to which the research topic of each study was contextually sensitive. Results suggested that the contextual sensitivity of the research topic was associated with replication success, even after statistically adjusting for several methodological characteristics (e.g., statistical power, effect size). The association between contextual sensitivity and replication success did not differ across psychological subdisciplines. These results suggest that researchers, replicators, and consumers should be mindful of contextual factors that might influence a psychological process. We offer several guidelines for dealing with contextual sensitivity in reproducibility.

  7. Viewpoint-independent contextual cueing effect

    Directory of Open Access Journals (Sweden)

    taiga etsuchiai

    2012-06-01

    Full Text Available We usually perceive things in our surroundings as unchanged despite viewpoint changes caused by self-motion. The visual system therefore must have a function to process objects independently of viewpoint. In this study, we examined whether viewpoint-independent spatial layout can be obtained implicitly. For this purpose, we used a contextual cueing effect, a learning effect of spatial layout in visual search displays known to be an implicit effect. We compared the transfer of the contextual cueing effect between cases with and without self-motion by using visual search displays for 3D objects, which changed according to the participant’s assumed location for viewing the stimuli. The contextual cueing effect was obtained with self-motion but disappeared when the display changed without self-motion. This indicates that there is an implicit learning effect in spatial coordinates and suggests that the spatial representation of object layouts or scenes can be obtained and updated implicitly. We also showed that binocular disparity play an important role in the layout representations.

  8. Contextuality is about identity of random variables

    International Nuclear Information System (INIS)

    Dzhafarov, Ehtibar N; Kujala, Janne V

    2014-01-01

    Contextual situations are those in which seemingly ‘the same’ random variable changes its identity depending on the conditions under which it is recorded. Such a change of identity is observed whenever the assumption that the variable is one and the same under different conditions leads to contradictions when one considers its joint distribution with other random variables (this is the essence of all Bell-type theorems). In our Contextuality-by-Default approach, instead of asking why or how the conditions force ‘one and the same’ random variable to change ‘its’ identity, any two random variables recorded under different conditions are considered different ‘automatically.’ They are never the same, nor are they jointly distributed, but one can always impose on them a joint distribution (probabilistic coupling). The special situations when there is a coupling in which these random variables are equal with probability 1 are considered noncontextual. Contextuality means that such couplings do not exist. We argue that the determination of the identity of random variables by conditions under which they are recorded is not a causal relationship and cannot violate laws of physics. (paper)

  9. Task demands determine comparison strategy in whole probe change detection.

    Science.gov (United States)

    Udale, Rob; Farrell, Simon; Kent, Chris

    2018-05-01

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

  10. A New Maximum-Likelihood Change Estimator for Two-Pass SAR Coherent Change Detection.

    Energy Technology Data Exchange (ETDEWEB)

    Wahl, Daniel E.; Yocky, David A.; Jakowatz, Charles V,

    2014-09-01

    In this paper, we derive a new optimal change metric to be used in synthetic aperture RADAR (SAR) coherent change detection (CCD). Previous CCD methods tend to produce false alarm states (showing change when there is none) in areas of the image that have a low clutter-to-noise power ratio (CNR). The new estimator does not suffer from this shortcoming. It is a surprisingly simple expression, easy to implement, and is optimal in the maximum-likelihood (ML) sense. The estimator produces very impressive results on the CCD collects that we have tested.

  11. Pharmacological Fingerprints of Contextual Uncertainty.

    Directory of Open Access Journals (Sweden)

    Louise Marshall

    2016-11-01

    Full Text Available Successful interaction with the environment requires flexible updating of our beliefs about the world. By estimating the likelihood of future events, it is possible to prepare appropriate actions in advance and execute fast, accurate motor responses. According to theoretical proposals, agents track the variability arising from changing environments by computing various forms of uncertainty. Several neuromodulators have been linked to uncertainty signalling, but comprehensive empirical characterisation of their relative contributions to perceptual belief updating, and to the selection of motor responses, is lacking. Here we assess the roles of noradrenaline, acetylcholine, and dopamine within a single, unified computational framework of uncertainty. Using pharmacological interventions in a sample of 128 healthy human volunteers and a hierarchical Bayesian learning model, we characterise the influences of noradrenergic, cholinergic, and dopaminergic receptor antagonism on individual computations of uncertainty during a probabilistic serial reaction time task. We propose that noradrenaline influences learning of uncertain events arising from unexpected changes in the environment. In contrast, acetylcholine balances attribution of uncertainty to chance fluctuations within an environmental context, defined by a stable set of probabilistic associations, or to gross environmental violations following a contextual switch. Dopamine supports the use of uncertainty representations to engender fast, adaptive responses.

  12. Change Detection Algorithm for the Production of Land Cover Change Maps over the European Union Countries

    Directory of Open Access Journals (Sweden)

    Sebastian Aleksandrowicz

    2014-06-01

    Full Text Available Contemporary satellite Earth Observation systems provide growing amounts of very high spatial resolution data that can be used in various applications. An increasing number of sensors make it possible to monitor selected areas in great detail. However, in order to handle the volume of data, a high level of automation is required. The semi-automatic change detection methodology described in this paper was developed to annually update land cover maps prepared in the context of the Geoland2. The proposed algorithm was tailored to work with different very high spatial resolution images acquired over different European landscapes. The methodology is a fusion of various change detection methods ranging from: (1 layer arithmetic; (2 vegetation indices (NDVI differentiating; (3 texture calculation; and methods based on (4 canonical correlation analysis (multivariate alteration detection (MAD. User intervention during the production of the change map is limited to the selection of the input data, the size of initial segments and the threshold for texture classification (optionally. To achieve a high level of automation, statistical thresholds were applied in most of the processing steps. Tests showed an overall change recognition accuracy of 89%, and the change type classification methodology can accurately classify transitions between classes.

  13. Volumetric Forest Change Detection Through Vhr Satellite Imagery

    Science.gov (United States)

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

    2016-06-01

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

  14. 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...

  15. Contextual Hub Analysis Tool (CHAT): A Cytoscape app for identifying contextually relevant hubs in biological networks.

    Science.gov (United States)

    Muetze, Tanja; Goenawan, Ivan H; Wiencko, Heather L; Bernal-Llinares, Manuel; Bryan, Kenneth; Lynn, David J

    2016-01-01

    Highly connected nodes (hubs) in biological networks are topologically important to the structure of the network and have also been shown to be preferentially associated with a range of phenotypes of interest. The relative importance of a hub node, however, can change depending on the biological context. Here, we report a Cytoscape app, the Contextual Hub Analysis Tool (CHAT), which enables users to easily construct and visualize a network of interactions from a gene or protein list of interest, integrate contextual information, such as gene expression or mass spectrometry data, and identify hub nodes that are more highly connected to contextual nodes (e.g. genes or proteins that are differentially expressed) than expected by chance. In a case study, we use CHAT to construct a network of genes that are differentially expressed in Dengue fever, a viral infection. CHAT was used to identify and compare contextual and degree-based hubs in this network. The top 20 degree-based hubs were enriched in pathways related to the cell cycle and cancer, which is likely due to the fact that proteins involved in these processes tend to be highly connected in general. In comparison, the top 20 contextual hubs were enriched in pathways commonly observed in a viral infection including pathways related to the immune response to viral infection. This analysis shows that such contextual hubs are considerably more biologically relevant than degree-based hubs and that analyses which rely on the identification of hubs solely based on their connectivity may be biased towards nodes that are highly connected in general rather than in the specific context of interest. CHAT is available for Cytoscape 3.0+ and can be installed via the Cytoscape App Store ( http://apps.cytoscape.org/apps/chat).

  16. Examining change detection approaches for tropical mangrove monitoring

    Science.gov (United States)

    Myint, Soe W.; Franklin, Janet; Buenemann, Michaela; Kim, Won; Giri, Chandra

    2014-01-01

    This study evaluated the effectiveness of different band combinations and classifiers (unsupervised, supervised, object-oriented nearest neighbor, and object-oriented decision rule) for quantifying mangrove forest change using multitemporal Landsat data. A discriminant analysis using spectra of different vegetation types determined that bands 2 (0.52 to 0.6 μm), 5 (1.55 to 1.75 μm), and 7 (2.08 to 2.35 μm) were the most effective bands for differentiating mangrove forests from surrounding land cover types. A ranking of thirty-six change maps, produced by comparing the classification accuracy of twelve change detection approaches, was used. The object-based Nearest Neighbor classifier produced the highest mean overall accuracy (84 percent) regardless of band combinations. The automated decision rule-based approach (mean overall accuracy of 88 percent) as well as a composite of bands 2, 5, and 7 used with the unsupervised classifier and the same composite or all band difference with the object-oriented Nearest Neighbor classifier were the most effective approaches.

  17. Robust real-time change detection in high jitter.

    Energy Technology Data Exchange (ETDEWEB)

    Simonson, Katherine Mary; Ma, Tian J.

    2009-08-01

    A new method is introduced for real-time detection of transient change in scenes observed by staring sensors that are subject to platform jitter, pixel defects, variable focus, and other real-world challenges. The approach uses flexible statistical models for the scene background and its variability, which are continually updated to track gradual drift in the sensor's performance and the scene under observation. Two separate models represent temporal and spatial variations in pixel intensity. For the temporal model, each new frame is projected into a low-dimensional subspace designed to capture the behavior of the frame data over a recent observation window. Per-pixel temporal standard deviation estimates are based on projection residuals. The second approach employs a simple representation of jitter to generate pixelwise moment estimates from a single frame. These estimates rely on spatial characteristics of the scene, and are used gauge each pixel's susceptibility to jitter. The temporal model handles pixels that are naturally variable due to sensor noise or moving scene elements, along with jitter displacements comparable to those observed in the recent past. The spatial model captures jitter-induced changes that may not have been seen previously. Change is declared in pixels whose current values are inconsistent with both models.

  18. Early auditory change detection implicitly facilitated by ignored concurrent visual change during a Braille reading task.

    Science.gov (United States)

    Aoyama, Atsushi; Haruyama, Tomohiro; Kuriki, Shinya

    2013-09-01

    Unconscious monitoring of multimodal stimulus changes enables humans to effectively sense the external environment. Such automatic change detection is thought to be reflected in auditory and visual mismatch negativity (MMN) and mismatch negativity fields (MMFs). These are event-related potentials and magnetic fields, respectively, evoked by deviant stimuli within a sequence of standard stimuli, and both are typically studied during irrelevant visual tasks that cause the stimuli to be ignored. Due to the sensitivity of MMN/MMF to potential effects of explicit attention to vision, however, it is unclear whether multisensory co-occurring changes can purely facilitate early sensory change detection reciprocally across modalities. We adopted a tactile task involving the reading of Braille patterns as a neutral ignore condition, while measuring magnetoencephalographic responses to concurrent audiovisual stimuli that were infrequently deviated either in auditory, visual, or audiovisual dimensions; 1000-Hz standard tones were switched to 1050-Hz deviant tones and/or two-by-two standard check patterns displayed on both sides of visual fields were switched to deviant reversed patterns. The check patterns were set to be faint enough so that the reversals could be easily ignored even during Braille reading. While visual MMFs were virtually undetectable even for visual and audiovisual deviants, significant auditory MMFs were observed for auditory and audiovisual deviants, originating from bilateral supratemporal auditory areas. Notably, auditory MMFs were significantly enhanced for audiovisual deviants from about 100 ms post-stimulus, as compared with the summation responses for auditory and visual deviants or for each of the unisensory deviants recorded in separate sessions. Evidenced by high tactile task performance with unawareness of visual changes, we conclude that Braille reading can successfully suppress explicit attention and that simultaneous multisensory changes can

  19. Detection and attribution of streamflow timing changes to climate change in the Western United States

    Science.gov (United States)

    Hidalgo, H.G.; Das, T.; Dettinger, M.D.; Cayan, D.R.; Pierce, D.W.; Barnett, T.P.; Bala, G.; Mirin, A.; Wood, A.W.; Bonfils, Celine; Santer, B.D.; Nozawa, T.

    2009-01-01

    This article applies formal detection and attribution techniques to investigate the nature of observed shifts in the timing of streamflow in the western United States. Previous studies have shown that the snow hydrology of the western United States has changed in the second half of the twentieth century. Such changes manifest themselves in the form of more rain and less snow, in reductions in the snow water contents, and in earlier snowmelt and associated advances in streamflow "center" timing (the day in the "water-year" on average when half the water-year flow at a point has passed). However, with one exception over a more limited domain, no other study has attempted to formally attribute these changes to anthropogenic increases of greenhouse gases in the atmosphere. Using the observations together with a set of global climate model simulations and a hydrologic model (applied to three major hydrological regions of the western United States_the California region, the upper Colorado River basin, and the Columbia River basin), it is found that the observed trends toward earlier "center" timing of snowmelt-driven streamflows in the western United States since 1950 are detectably different from natural variability (significant at the p analysis, and it is the only basin that showed a detectable signal when the analysis was performed on individual basins. It should be noted that although climate change is an important signal, other climatic processes have also contributed to the hydrologic variability of large basins in the western United States. ?? 2009 American Meteorological Society.

  20. Updating National Topographic Data Base Using Change Detection Methods

    Science.gov (United States)

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

    2016-06-01

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

  1. Automatic detection of surface changes on Mars - a status report

    Science.gov (United States)

    Sidiropoulos, Panagiotis; Muller, Jan-Peter

    2016-10-01

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

  2. Detecting Change in Landscape Greenness over Large Areas: An Example for New Mexico, USA

    Science.gov (United States)

    Monitoring and quantifying changes in vegetation cover over large areas using remote sensing can potentially detect large-scale, slow changes (e.g., climate change), as well as more local and rapid changes (e.g., fire, land development). A useful indicator for detecting change i...

  3. Against Contextualism: Belief, Evidence, & the Bank Cases

    Directory of Open Access Journals (Sweden)

    Logan Paul Gage

    2013-04-01

    Full Text Available http://dx.doi.org/10.5007/1808-1711.2013v17n1p57 Contextualism (the view that ‘knowledge’ and its variants are context-sensitive has been supported in large part through appeal to intuitions about Keith DeRose’s Bank Cases. Recently, however, the contextualist construal of these cases has come under fire from Kent Bach and Jennifer Nagel who question whether the Bank Case subject’s confidence can remain constant in both low- and high-stakes cases. Having explained the Bank Cases and this challenge to them, I argue that DeRose has given a reasonable reply to this initial challenge. However, I proceed to argue that the current stalemate can be broken. Seeking to extend the Bach–Nagel critique, I offer a novel interpretation of the Bank Cases according to which the subject’s evidence changes between low- and high-stakes cases. If I am correct, then, given the amount of support the Bank Cases have been thought to lend contextualism, the case for contextualism is seriously weakened.

  4. Perpendicularity misjudgments caused by contextual stimulus elements.

    Science.gov (United States)

    Bulatov, Aleksandr; Bulatova, Natalija; Surkys, Tadas

    2012-10-15

    It has been demonstrated in previous studies that the illusions of extent of the Brentano type can be explained by the perceptual positional shifts of the stimulus terminators in direction of the centers-of-masses (centroids) of adjacent contextual flanks [Bulatov, A. et al. (2011). Contextual flanks' tilting and magnitude of illusion of extent. Vision Research, 51(1), 58-64]. In the present study, the applicability of the centroid approach to explain the right-angle misjudgments was tested psychophysically using stimuli composed of three small disks (dots) forming an imaginary rectangular triangle. Stimuli comprised the Müller-Lyer wings or line segments (bars) as the contextual distracters rotated around the vertices of the triangle, and changes in the magnitude of the illusion of perpendicularity were measured in a set of experiments. A good resemblance between the experimental data and theoretical predictions obtained strongly supports the suggestion regarding the common "centroid" origin of the illusions of extent of the Brentano type and misperception of the perpendicularity investigated. 2012 Elsevier Ltd. All rights reserved

  5. Contextual sensitivity in scientific reproducibility

    Science.gov (United States)

    Van Bavel, Jay J.; Mende-Siedlecki, Peter; Brady, William J.; Reinero, Diego A.

    2016-01-01

    In recent years, scientists have paid increasing attention to reproducibility. For example, the Reproducibility Project, a large-scale replication attempt of 100 studies published in top psychology journals found that only 39% could be unambiguously reproduced. There is a growing consensus among scientists that the lack of reproducibility in psychology and other fields stems from various methodological factors, including low statistical power, researcher’s degrees of freedom, and an emphasis on publishing surprising positive results. However, there is a contentious debate about the extent to which failures to reproduce certain results might also reflect contextual differences (often termed “hidden moderators”) between the original research and the replication attempt. Although psychologists have found extensive evidence that contextual factors alter behavior, some have argued that context is unlikely to influence the results of direct replications precisely because these studies use the same methods as those used in the original research. To help resolve this debate, we recoded the 100 original studies from the Reproducibility Project on the extent to which the research topic of each study was contextually sensitive. Results suggested that the contextual sensitivity of the research topic was associated with replication success, even after statistically adjusting for several methodological characteristics (e.g., statistical power, effect size). The association between contextual sensitivity and replication success did not differ across psychological subdisciplines. These results suggest that researchers, replicators, and consumers should be mindful of contextual factors that might influence a psychological process. We offer several guidelines for dealing with contextual sensitivity in reproducibility. PMID:27217556

  6. Influence of individual and social contextual factors on changes in leisure-time physical activity in working-class populations: results of the Healthy Directions–Small Businesses Study

    Science.gov (United States)

    Stoddard, Anne; Bennett, Gary G.; Wolin, Kathleen Y.; Sorensen, Glorian G.

    2012-01-01

    Background As part of the Harvard Cancer Prevention Program Project, we sought to address disparities reflected in social class and race/ethnicity by developing and testing a behavioral intervention model that targeted fruit and vegetable consumption, red meat consumption, multivitamin intake, and physical activity in working-class, multiethnic populations. Methods This paper examined the associations between change in leisure-time physical activity and individual and social contextual factors in participants employed in small businesses (n = 850) at both baseline and at 18-month final. Results In bivariate analyses, age, language acculturation, social ties, and workplace social capital were significantly associated with physical activity at final. In multivariable analyses, being younger and having high language acculturation were significantly associated with greater leisuretime physical activity at final; high workplace social capital was significantly associated with a decline in physical activity at final. Conclusion These findings have implications for understanding factors that are integral to promoting change in physical activity among working-class, multiethnic populations. PMID:22806257

  7. 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…

  8. Empathy and contextual social cognition.

    Science.gov (United States)

    Melloni, Margherita; Lopez, Vladimir; Ibanez, Agustin

    2014-03-01

    Empathy is a highly flexible and adaptive process that allows for the interplay of prosocial behavior in many different social contexts. Empathy appears to be a very situated cognitive process, embedded with specific contextual cues that trigger different automatic and controlled responses. In this review, we summarize relevant evidence regarding social context modulation of empathy for pain. Several contextual factors, such as stimulus reality and personal experience, affectively link with other factors, emotional cues, threat information, group membership, and attitudes toward others to influence the affective, sensorimotor, and cognitive processing of empathy. Thus, we propose that the frontoinsular-temporal network, the so-called social context network model (SCNM), is recruited during the contextual processing of empathy. This network would (1) update the contextual cues and use them to construct fast predictions (frontal regions), (2) coordinate the internal (body) and external milieus (insula), and (3) consolidate the context-target associative learning of empathic processes (temporal sites). Furthermore, we propose these context-dependent effects of empathy in the framework of the frontoinsular-temporal network and examine the behavioral and neural evidence of three neuropsychiatric conditions (Asperger syndrome, schizophrenia, and the behavioral variant of frontotemporal dementia), which simultaneously present with empathy and contextual integration impairments. We suggest potential advantages of a situated approach to empathy in the assessment of these neuropsychiatric disorders, as well as their relationship with the SCNM.

  9. Object-based implicit learning in visual search: perceptual segmentation constrains contextual cueing.

    Science.gov (United States)

    Conci, Markus; Müller, Hermann J; von Mühlenen, Adrian

    2013-07-09

    In visual search, detection of a target is faster when it is presented within a spatial layout of repeatedly encountered nontarget items, indicating that contextual invariances can guide selective attention (contextual cueing; Chun & Jiang, 1998). However, perceptual regularities may interfere with contextual learning; for instance, no contextual facilitation occurs when four nontargets form a square-shaped grouping, even though the square location predicts the target location (Conci & von Mühlenen, 2009). Here, we further investigated potential causes for this interference-effect: We show that contextual cueing can reliably occur for targets located within the region of a segmented object, but not for targets presented outside of the object's boundaries. Four experiments demonstrate an object-based facilitation in contextual cueing, with a modulation of context-based learning by relatively subtle grouping cues including closure, symmetry, and spatial regularity. Moreover, the lack of contextual cueing for targets located outside the segmented region was due to an absence of (latent) learning of contextual layouts, rather than due to an attentional bias towards the grouped region. Taken together, these results indicate that perceptual segmentation provides a basic structure within which contextual scene regularities are acquired. This in turn argues that contextual learning is constrained by object-based selection.

  10. UPDATING NATIONAL TOPOGRAPHIC DATA BASE USING CHANGE DETECTION METHODS

    Directory of Open Access Journals (Sweden)

    E. Keinan

    2016-06-01

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

  11. Europe. An analysis of changes in the consumption of alcoholic beverages: the interaction among consumption, related harms, contextual factors and alcoholic beverage control policies.

    Science.gov (United States)

    Allamani, Allaman; Pepe, Pasquale; Baccini, Michela; Massini, Giulia; Voller, Fabio

    2014-10-01

    This AMPHORA study's aim was to investigate selected factors potentially affecting changes in consumption of alcoholic beverages in 12 European countries during the 1960s-2008 (an average increase in beer, decreases in wine and spirits, total alcohol drinking decrease). Both time series and artificial neural networks-based analyses were used. Results indicated that selected socio-demographic and economic factors showed an overall major impact on consumption changes; particularly urbanization, increased income, and older mothers' age at their childbirths were significantly associated with consumption increase or decrease, depending on the country. Alcoholic beverage control policies showed an overall minor impact on consumption changes: among them, permissive availability measures were significantly associated with consumption increases, while drinking and driving limits and availability restrictions were correlated with consumption decreases, and alcohol taxation and prices of the alcoholic beverages were not significantly correlated with consumption. Population ageing, older mother's age at childbirths, increased income and increases in female employment, as well as drink driving limitations were associated with the decrease of transport mortality. Study's limitations are noted.

  12. De/Contextualizing Information

    DEFF Research Database (Denmark)

    Marton, Attila; Mariategui, Jose-Carlos

    2015-01-01

    The pervasive diffusion of digital media has introduced profound changes to social practices, challenging established notions of embeddedness and context. Based on our case study on the BBC's Digital Media Initiative, we further explore these changes in the domain of video craft editing for telev...

  13. Communication Games Reveal Preparation Contextuality

    Science.gov (United States)

    Hameedi, Alley; Tavakoli, Armin; Marques, Breno; Bourennane, Mohamed

    2017-12-01

    A communication game consists of distributed parties attempting to jointly complete a task with restricted communication. Such games are useful tools for studying limitations of physical theories. A theory exhibits preparation contextuality whenever its predictions cannot be explained by a preparation noncontextual model. Here, we show that communication games performed in operational theories reveal the preparation contextuality of that theory. For statistics obtained in a particular family of communication games, we show a direct correspondence with correlations in spacelike separated events obeying the no-signaling principle. Using this, we prove that all mixed quantum states of any finite dimension are preparation contextual. We report on an experimental realization of a communication game involving three-level quantum systems from which we observe a strong violation of the constraints of preparation noncontextuality.

  14. Contextual Validity in Hybrid Logic

    DEFF Research Database (Denmark)

    Blackburn, Patrick Rowan; Jørgensen, Klaus Frovin

    2013-01-01

    interpretations. Moreover, such indexicals give rise to a special kind of validity—contextual validity—that interacts with ordinary logi- cal validity in interesting and often unexpected ways. In this paper we model these interactions by combining standard techniques from hybrid logic with insights from the work...... of Hans Kamp and David Kaplan. We introduce a simple proof rule, which we call the Kamp Rule, and first we show that it is all we need to take us from logical validities involving now to contextual validities involving now too. We then go on to show that this deductive bridge is strong enough to carry us...... to contextual validities involving yesterday, today and tomorrow as well....

  15. 3D Bayesian contextual classifiers

    DEFF Research Database (Denmark)

    Larsen, Rasmus

    2000-01-01

    We extend a series of multivariate Bayesian 2-D contextual classifiers to 3-D by specifying a simultaneous Gaussian distribution for the feature vectors as well as a prior distribution of the class variables of a pixel and its 6 nearest 3-D neighbours.......We extend a series of multivariate Bayesian 2-D contextual classifiers to 3-D by specifying a simultaneous Gaussian distribution for the feature vectors as well as a prior distribution of the class variables of a pixel and its 6 nearest 3-D neighbours....

  16. Linear contextual modal type theory

    DEFF Research Database (Denmark)

    Schack-Nielsen, Anders; Schürmann, Carsten

    Abstract. When one implements a logical framework based on linear type theory, for example the Celf system [?], one is immediately con- fronted with questions about their equational theory and how to deal with logic variables. In this paper, we propose linear contextual modal type theory that gives...... a mathematical account of the nature of logic variables. Our type theory is conservative over intuitionistic contextual modal type theory proposed by Nanevski, Pfenning, and Pientka. Our main contributions include a mechanically checked proof of soundness and a working implementation....

  17. 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. ...

  18. 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

  19. Contextual Bandits for Information Retrieval

    NARCIS (Netherlands)

    Hofmann, K.; Whiteson, S.; de Rijke, M.

    2011-01-01

    In this paper we give an overview of and outlook on research at the intersection of information retrieval (IR) and contextual bandit problems. A critical problem in information retrieval is online learning to rank, where a search engine strives to improve the quality of the ranked result lists it

  20. DISCOURSE STYLISTICS AS CONTEXTUALIZED STYLISTICS

    OpenAIRE

    Marina Katnić-Bakaršić

    2003-01-01

    The focus of the paper is on discourse stylistics, viewed as contextualized discipline. Context includes various factors (sociohistorical, cognitive, cultural and intertextual). The paper investigates the most important approaches to discourse stylistics: pragmatic stylistics, discourse and/ or conversational analysis, cognitive stylistics, critical stylistics, feminists stylistics. In discourse stylistics analysis is always combined with interpretation, and description is followed by explana...

  1. Contextualizing Data Warehouses with Documents

    DEFF Research Database (Denmark)

    Perez, Juan Manuel; Berlanga, Rafael; Aramburu, Maria Jose

    2008-01-01

    warehouse with a document warehouse, resulting in a contextualized warehouse. Thus, the user first selects an analysis context by supplying some keywords. Then, the analysis is performed on a novel type of OLAP cube, called an R-cube, which is materialized by retrieving and ranking the documents...

  2. 3-D contextual Bayesian classifiers

    DEFF Research Database (Denmark)

    Larsen, Rasmus

    In this paper we will consider extensions of a series of Bayesian 2-D contextual classification pocedures proposed by Owen (1984) Hjort & Mohn (1984) and Welch & Salter (1971) and Haslett (1985) to 3 spatial dimensions. It is evident that compared to classical pixelwise classification further...

  3. A 3-D Contextual Classifier

    DEFF Research Database (Denmark)

    Larsen, Rasmus

    1997-01-01

    In this paper we will consider an extension of the Bayesian 2-D contextual class ification routine developed by Owen, Hjort \\$\\backslash\\$& Mohn to 3 spatial dimensions. It is evident that compared to classical pixelwise classification further information can be obtained by tak ing into account...

  4. Contextual knowledge reduces demands on working memory during reading.

    Science.gov (United States)

    Miller, Lisa M Soederberg; Cohen, Jason A; Wingfield, Arthur

    2006-09-01

    An experiment is reported in which young, middle-aged, and older adults read and recalled ambiguous texts either with or without the topic title that supplied contextual knowledge. Within each of the age groups, the participants were divided into those with high or low working memory (WM) spans, with available WM capacity further manipulated by the presence or absence of an auditory target detection task concurrent with the reading task. Differences in reading efficiency (reading time per proposition recalled) between low WM span and high WM span groups were greater among readers who had access to contextual knowledge relative to those who did not, suggesting that contextual knowledge reduces demands on WM capacity. This position was further supported by the finding that increased age and attentional demands, two factors associated with reduced WM capacity, exaggerated the benefits of contextual knowledge on reading efficiency. The relative strengths of additional potential predictors of reading efficiency (e.g., interest, effort, and memory beliefs), along with knowledge, WM span, and age, are reported. Findings showed that contextual knowledge was the strongest predictor of reading efficiency even after controlling for the effects of all of the other predictors.

  5. 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.

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

    KAUST Repository

    Zhang, Xiangliang; Wang, Wei

    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

  7. Change Detection Algorithms for Information Assurance of Computer Networks

    National Research Council Canada - National Science Library

    Cardenas, Alvaro A

    2002-01-01

    .... In this thesis, the author will focus on the detection of three attack scenarios: the spreading of active worms throughout the Internet, distributed denial of service attacks, and routing attacks to wireless ad hoc networks...

  8. Nicotine Withdrawal Disrupts Contextual Learning but Not Recall of Prior Contextual Associations: Implications for Nicotine Addiction

    OpenAIRE

    Portugal, George S.; Gould, Thomas J.

    2008-01-01

    Interactions between nicotine and learning could contribute to nicotine addiction. Although previous research indicates that nicotine withdrawal disrupts contextual learning, the effects of nicotine withdrawal on contextual memories acquired before withdrawal are unknown. The present study investigated whether nicotine withdrawal disrupted recall of prior contextual memories by examining the effects of nicotine withdrawal on recall of nicotine conditioned place preference (CPP) and contextual...

  9. Brazilian readers and contextual reference Brazilian readers and contextual reference

    Directory of Open Access Journals (Sweden)

    Lilia M. O. Carioni

    2008-04-01

    Full Text Available This article describes an experiment carried out using Brazilian university students at UFSC, the purpose being to check comprehension relationships between two types of contextual reference and two languages, Portuguese and English. A major stimulus for the research was the question: are Brazilian students' difficulties in reading English related more to English language difficulties or to difficulties in processing text in general?

  10. Detection Capability Evaluation on Chang'e-5 Lunar Mineralogical Spectrometer (LMS)

    Science.gov (United States)

    Liu, Bin; Ren, Xin; Yan, Wei; Xu, Xuesen; Cai, Tingni; Liu, Dawei; Liu, Jianjun; Li, Chunlai

    2016-04-01

    The Chang'e-5 (CE-5) lunar sample return mission is scheduled to launch in 2017 to bring back lunar regolith and drill samples. The Chang'e-5 Lunar Mineralogical Spectrometer (LMS), as one of the three sets of scientific payload installed on the lander, is used to collect in-situ spectrum and analyze the mineralogical composition of the sampling site. It can also help to select the sampling site , and to compare the measured laboratory spectrum of returned sample with in-situ data. LMS employs acousto-optic tunable filters (AOTFs) and is composed of a VIS/NIR module (0.48μm-1.45μm) and an IR module (1.4μm -3.2μm). It has spectral resolution ranging from 3 to 25 nm, with a field of view (FOV) of 4.24°×4.24°. Unlike Chang'e-3 VIS/NIR Imaging Spectrometer (VNIS), the spectral coverage of LMS is extended from 2.4μm to 3.2μm, which has capability to identify H2O/OH absorption features around 2.7μm. An aluminum plate and an Infragold plate are fixed in the dust cover, being used as calibration targets in the VIS/NIR and IR spectral range respectively when the dust cover is open. Before launch, a ground verification test of LMS needs to be conducted in order to: 1) test and verify the detection capability of LMS through evaluation on the quality of image and spectral data collected for the simulated lunar samples; and 2) evaluate the accuracy of data processing methods by the simulation of instrument working on the moon. The ground verification test will be conducted both in the lab and field. The spectra of simulated lunar regolith/mineral samples will be collected simultaneously by the LMS and two calibrated spectrometers: a FTIR spectrometer (Model 102F) and an ASD FieldSpec 4 Hi-Res spectrometer. In this study, the results of the LMS ground verification test will be reported including the evaluation on the LMS spectral and image data quality, mineral identification and inversion ability, accuracy of calibration and geometric positioning .

  11. Competing definitions of contextual environments

    Directory of Open Access Journals (Sweden)

    Jerrett Michael

    2006-12-01

    Full Text Available Abstract Background The growing interest in the effects of contextual environments on health outcomes has focused attention on the strengths and weaknesses of alternate contextual unit definitions for use in multilevel analysis. The present research examined three methods to define contextual units for a sample of children already enrolled in a respiratory health study. The Inclusive Equal Weights Method (M1 and Inclusive Sample Weighted Method (M2 defined communities using the boundaries of the census blocks that incorporated the residences of the CHS participants, except that the former estimated socio-demographic variables by averaging the census block data within each community, while the latter used weighted proportion of CHS participants per block. The Minimum Bounding Rectangle Method (M3 generated minimum bounding rectangles that included 95% of the CHS participants and produced estimates of census variables using the weighted proportion of each block within these rectangles. GIS was used to map the locations of study participants, define the boundaries of the communities where study participants reside, and compute estimates of socio-demographic variables. The sensitivity of census variable estimates to the choice of community boundaries and weights was assessed using standard tests of significance. Results The estimates of contextual variables vary significantly depending on the choice of neighborhood boundaries and weights. The choice of boundaries therefore shapes the community profile and the relationships between its components (variables. Conclusion Multilevel analysis concerned with the effects of contextual environments on health requires careful consideration of what constitutes a contextual unit for a given study sample, because the alternate definitions may have differential impact on the results. The three alternative methods used in this research all carry some subjectivity, which is embedded in the decision as to what

  12. 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.

  13. Contextualizing Social Science in Nepal

    Directory of Open Access Journals (Sweden)

    Dev Raj Dahal

    2008-10-01

    Full Text Available Social science informs about the ideals and trains experts to deal with the complex social realities. It has a public purpose rooted in what we call dharma (professional and institutional responsibility as opposed to the arrogance of reason, self-will and self-rationalization intrinsic to contemporary rational choice and modernity. Learning has a synergy - establishing connection between the world of social science theories and the drama of social life. A lack of mutual learning between Nepal's traditional faith intellectuals and modern reason-based social scientists has created a big hiatus and contradiction. The academic life of social scientists in Nepal is completely outside of spiritual, moral and ethical influence experienced by ordinary public. The spiritual blindness of modern social scientists has thus opened multiple gaps between their worldview and those of the citizens on various frontiers--theoretical knowledge and practical experience, technical understanding and composite knowledge and secularity of social science and the vitality of the Hindu-Buddhist scriptures in the popular mind, culture, behavior and practices. This has reinforced a division between the system of knowledge of social scientists and the life-world of people. The proponents of new social movements in Nepal, such as women, Dalits, Janajatis, Madhesis, youths and marginalized population are seeking a structural shift in reason-based knowledge to both reason and feeling in social science knowledge discovery. This movement can open the "captive mind" to social learning of contextual knowledge, conduct research with the citizens, provide inputs to the policy makers and reverse their linear, structure-bound, rationalist and disciplinary thinking into the one that represents what the Nepal mandala, the Nepali space, is really like and how to improve it for the better. The renewal and indigenization of qualitative social science research is important to overcome the

  14. Techniques for land use change detection using Landsat imagery

    Science.gov (United States)

    Angelici, G. L.; Bryant, N. A.; Friedman, S. Z.

    1977-01-01

    A variety of procedures were developed for the delineation of areas of land use change using Landsat Multispectral Scanner data and the generation of statistics revealing the nature of the changes involved (i.e., number of acres changed from rural to urban). Techniques of the Image Based Information System were utilized in all stages of the procedure, from logging the Landsat data and registering two frames of imagery, to extracting the changed areas and printing tabulations of land use change in acres. Two alternative methods of delineating land use change are presented while enumerating the steps of the entire process. The Houston, Texas urban area, and the Orlando, Florida urban area, are used as illustrative examples of various procedures.

  15. Changing Habits using Contextualized Decision Making

    NARCIS (Netherlands)

    Mercuur, Rijk; Dignum, F.P.M.; Kashima, Yoshihisa

    2015-01-01

    In this paper we aim to present a new model in which context influences a combination of both habitual and intentional environmental behavior using the concept of social practices. We will illustrate the model using meat-eating behavior while dining out.

  16. Diagnosis of UAV Pitot Tube Defects Using Statistical Change Detection

    DEFF Research Database (Denmark)

    Hansen, Søren; Blanke, Mogens; Adrian, Jens

    2010-01-01

    Unmanned Aerial Vehicles need a large degree of tolerance to faults. One of the most important steps towards this is the ability to detect and isolate faults in sensors and actuators in real time and make remedial actions to avoid that faults develop to failure. This paper analyses the possibilit......Unmanned Aerial Vehicles need a large degree of tolerance to faults. One of the most important steps towards this is the ability to detect and isolate faults in sensors and actuators in real time and make remedial actions to avoid that faults develop to failure. This paper analyses...... the possibilities of detecting faults in the pitot tube of a small unmanned aerial vehicle, a fault that easily causes a crash if not diagnosed and handled in time. Using as redundant information the velocity measured from an onboard GPS receiver, the air-speed estimated from engine throttle and the pitot tube...

  17. Comparison of computed tomography and radiography for detecting changes induced by malignant nasal neoplasia in dogs

    International Nuclear Information System (INIS)

    Park, R.D.; Beck, E.R.; LeCouteur, R.A.

    1992-01-01

    The ability of computed tomography and radiography to detect changes associated with nasal neoplasia was compared in dogs. Eighteen areas or anatomic structures were evaluated in 21 dogs for changes indicative of neoplasia. Computed tomography was superior (P < or = 0.05) to radiography for detecting changes in 14 of 18 areas. Radiography was not superior for detecting changes in any structure or area. Computed tomography reveals vital information not always detected radiographically to assist in providing a prognosis and in planning treatment for nasal neoplasms in dogs

  18. SCALABLE TIME SERIES CHANGE DETECTION FOR BIOMASS MONITORING USING GAUSSIAN PROCESS

    Data.gov (United States)

    National Aeronautics and Space Administration — SCALABLE TIME SERIES CHANGE DETECTION FOR BIOMASS MONITORING USING GAUSSIAN PROCESS VARUN CHANDOLA AND RANGA RAJU VATSAVAI Abstract. Biomass monitoring,...

  19. Detecting CO/sub 2/-induced climatic change

    Energy Technology Data Exchange (ETDEWEB)

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

    1981-07-16

    Although it is widely believed that increasing atmospheric CO/sub 2/ levels will cause noticeable global warming, the effects are not yet detectable, possibly because of the 'noise' of natural climatic variability. An examination of the spatial and seasonal distribution of signal-to-noise ratio shows that the highest values occur in summer and annual mean surface temperatures averaged over the Northern Hemisphere or over mid-latitudes. The spatial and seasonal characteristics of the early twentieth century warming were similar to those expected from increasing CO/sub 2/ based on an equilibrium response model. This similarity may hinder the early detection of CO/sub 2/ effects on climate.

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

    Science.gov (United States)

    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.

  1. Grasp Preparation Improves Change Detection for Congruent Objects

    Science.gov (United States)

    Symes, Ed; Tucker, Mike; Ellis, Rob; Vainio, Lari; Ottoboni, Giovanni

    2008-01-01

    A series of experiments provided converging support for the hypothesis that action preparation biases selective attention to action-congruent object features. When visual transients are masked in so-called "change-blindness scenes," viewers are blind to substantial changes between 2 otherwise identical pictures that flick back and forth. The…

  2. Detecting change in processes using comparative trace clustering

    NARCIS (Netherlands)

    Hompes, B.F.A.; Buijs, J.C.A.M.; van der Aalst, W.M.P.; Dixit, P.M.; Buurman, J.

    2015-01-01

    Real-life business processes are complex and show a high degree of variability. Additionally, due to changing conditions and circumstances, these processes continuously evolve over time. For example, in the healthcare domain, advances in medicine trigger changes in diagnoses and treatment processes.

  3. Contextual approach to quantum formalism

    CERN Document Server

    Khrennikov, Andrei

    2009-01-01

    The aim of this book is to show that the probabilistic formalisms of classical statistical mechanics and quantum mechanics can be unified on the basis of a general contextual probabilistic model. By taking into account the dependence of (classical) probabilities on contexts (i.e. complexes of physical conditions), one can reproduce all distinct features of quantum probabilities such as the interference of probabilities and the violation of Bell’s inequality. Moreover, by starting with a formula for the interference of probabilities (which generalizes the well known classical formula of total probability), one can construct the representation of contextual probabilities by complex probability amplitudes or, in the abstract formalism, by normalized vectors of the complex Hilbert space or its hyperbolic generalization. Thus the Hilbert space representation of probabilities can be naturally derived from classical probabilistic assumptions. An important chapter of the book critically reviews known no-go theorems...

  4. Hypobaric hypoxia impairs cued and contextual fear memory in rats.

    Science.gov (United States)

    Kumari, Punita; Kauser, Hina; Wadhwa, Meetu; Roy, Koustav; Alam, Shahnawaz; Sahu, Surajit; Kishore, Krishna; Ray, Koushik; Panjwani, Usha

    2018-04-26

    Fear memory is essential for survival, and its dysregulation leads to disorders. High altitude hypobaric hypoxia (HH) is known to induce cognitive decline. However, its effect on fear memory is still an enigma. We aimed to investigate the temporal effect of HH on fear conditioning and the underlying mechanism. Adult male Sprague-Dawley rats were trained for fear conditioning and exposed to simulated HH equivalent to 25,000 ft for different durations (1, 3, 7, 14 and 21 days). Subsequently, rats were tested for cued and contextual fear conditioning. Neuronal morphology, apoptosis and DNA fragmentation were studied in the medial prefrontal cortex (mPFC), hippocampus and basolateral amygdala (BLA). We observed significant deficit in cued and contextual fear acquisition (at 1, 3 and 7 days) and consolidation (cued at 1 and 3 days and contextual fear at 1, 3 and 7 days) under HH. HH exposure with retraining showed the earlier restoration of contextual fear memory. Further, we found a gradual increase in the number of pyknotic and apoptotic neurons together with the increase in DNA fragmentation in mPFC, hippocampus, and BLA up to 7 days of HH exposure. The present study concludes that HH exposure equivalent to 25000 ft induced cued and contextual fear memory deficit (acquisition and consolidation) which is found to be correlated with the neurodegenerative changes in the limbic brain regions. Copyright © 2018. Published by Elsevier B.V.

  5. Trend analysis and change point detection of annual and seasonal ...

    Indian Academy of Sciences (India)

    elevation ranges from 0 m in the coastal areas of the. Persian Gulf to over ... been explained by Kang and Yusof (2012); Dhorde ...... J L 2004 Detection of statistically significant trends in ... Sun H, Chen Y, Li W, Li F, Chen Y, Hao X and Yang Y.

  6. Detecting Hacked Twitter Accounts based on Behavioural Change

    NARCIS (Netherlands)

    Nauta, Meike; Habib, Mena Badieh; van Keulen, Maurice

    Social media accounts are valuable for hackers for spreading phishing links, malware and spam. Furthermore, some people deliberately hack an acquaintance to damage his or her image. This paper describes a classification for detecting hacked Twitter accounts. The model is mainly based on features

  7. Contextualized B2B Registries

    OpenAIRE

    Radetzki, U; Boniface, M.J.; Surridge, M.

    2007-01-01

    Abstract. Service discovery is a fundamental concept underpinning the move towards dynamic service-oriented business partnerships. The business process for integrating service discovery and underlying registry technologies into busi-ness relationships, procurement and project management functions has not been examined and hence existing Web Service registries lack capabilities required by business today. In this paper we present a novel contextualized B2B registry that supports dynamic regist...

  8. DISCOURSE STYLISTICS AS CONTEXTUALIZED STYLISTICS

    Directory of Open Access Journals (Sweden)

    Marina Katnić-Bakaršić

    2003-01-01

    Full Text Available The focus of the paper is on discourse stylistics, viewed as contextualized discipline. Context includes various factors (sociohistorical, cognitive, cultural and intertextual. The paper investigates the most important approaches to discourse stylistics: pragmatic stylistics, discourse and/ or conversational analysis, cognitive stylistics, critical stylistics, feminists stylistics. In discourse stylistics analysis is always combined with interpretation, and description is followed by explanation and critique.

  9. PRESENTATION ON--LAND-COVER CHANGE DETECTION USING MULTI-TEMPORAL MODIS NDVI DATA

    Science.gov (United States)

    Monitoring the locations and distributions of land-cover changes is important for establishing linkages between policy decisions, regulatory actions and subsequent landuse activities. Past efforts incorporating two-date change detection using moderate resolution data (e.g., Lands...

  10. Kernel based orthogonalization for change detection in hyperspectral images

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg

    function and all quantities needed in the analysis are expressed in terms of this kernel function. This means that we need not know the nonlinear mappings explicitly. Kernel PCA and MNF analyses handle nonlinearities by implicitly transforming data into high (even infinite) dimensional feature space via...... analysis all 126 spectral bands of the HyMap are included. Changes on the ground are most likely due to harvest having taken place between the two acquisitions and solar effects (both solar elevation and azimuth have changed). Both types of kernel analysis emphasize change and unlike kernel PCA, kernel MNF...

  11. 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.

  12. Coherent Change Detection: Theoretical Description and Experimental Results

    Science.gov (United States)

    2006-08-01

    scene changes created using a rotary hoe and lawn mower . In the first collection the repeat pass delay is 24 hours and for a false alarm rate of 1 in 20...the rotary hoe and lawn mower . . . . . . . . . . . . . . . . . 65 35 Intensity SAR image of the scene used for repeat pass interferometry experi...ments. Superimposed on the image is a schematic showing the scene changes carried out with the rotary hoe and lawn mower . . . . . . . . . . . . . . . . . 66

  13. 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.

  14. Detecting and Reacting to Change: The Effect of Exposure to Narrow Categorizations

    Science.gov (United States)

    Chakravarti, Amitav; Fang, Christina; Shapira, Zur

    2011-01-01

    The ability to detect a change, to accurately assess the magnitude of the change, and to react to that change in a commensurate fashion are of critical importance in many decision domains. Thus, it is important to understand the factors that systematically affect people's reactions to change. In this article we document a novel effect: Decision…

  15. Quantile index for gradual and abrupt change detection from CFB boiler sensor data in online settings

    NARCIS (Netherlands)

    Maslov, A.; Pechenizkiy, M.; Kärkkäinen, T.; Tähtinen, M.

    2012-01-01

    In this paper we consider the problem of online detection of gradual and abrupt changes in sensor data having high levels of noise and outliers. We propose a simple heuristic method based on the Quantile Index (QI) and study how robust this method is for detecting both gradual and abrupt changes

  16. Graph-Theoretic Statistical Methods for Detecting and Localizing Distributional Change in Multivariate Data

    Science.gov (United States)

    2015-06-01

    context of regression. Tran, Gaber , and Sattler (2014) describe recent change-detection efforts as applied to streaming data. -2 -1 0 1 2 3 4 -2 -1 0 1 Y...human monitors: A signal detection analysis. Human-Computer Interaction, 1(1), 49–75. Tran, D. H., Gaber , M. M., & Sattler, K. U. (2014). Change

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

    NARCIS (Netherlands)

    Adal, K.M.; Van Etten, Peter G.; Martinez, Jose P; Rouwen, Kenneth; Vermeer, K.A.; van Vliet, L.J.; Armato, Samuel G.; Petrick, Nicholas A.

    2017-01-01

    Automated detection and quantification of spatio-temporal retinal changes is an important step to objectively assess disease progression and treatment effects for dynamic retinal diseases such as diabetic retinopathy (DR). However, detecting retinal changes caused by early DR lesions such as

  18. 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.

  19. Linear and kernel methods for multivariate change detection

    DEFF Research Database (Denmark)

    Canty, Morton J.; Nielsen, Allan Aasbjerg

    2012-01-01

    ), as well as maximum autocorrelation factor (MAF) and minimum noise fraction (MNF) analyses of IR-MAD images, both linear and kernel-based (nonlinear), may further enhance change signals relative to no-change background. IDL (Interactive Data Language) implementations of IR-MAD, automatic radiometric...... normalization, and kernel PCA/MAF/MNF transformations are presented that function as transparent and fully integrated extensions of the ENVI remote sensing image analysis environment. The train/test approach to kernel PCA is evaluated against a Hebbian learning procedure. Matlab code is also available...... that allows fast data exploration and experimentation with smaller datasets. New, multiresolution versions of IR-MAD that accelerate convergence and that further reduce no-change background noise are introduced. Computationally expensive matrix diagonalization and kernel image projections are programmed...

  20. Auditory cortical change detection in adults with Asperger syndrome.

    Science.gov (United States)

    Lepistö, Tuulia; Nieminen-von Wendt, Taina; von Wendt, Lennart; Näätänen, Risto; Kujala, Teija

    2007-03-06

    The present study investigated whether auditory deficits reported in children with Asperger syndrome (AS) are also present in adulthood. To this end, event-related potentials (ERPs) were recorded from adults with AS for duration, pitch, and phonetic changes in vowels, and for acoustically matched non-speech stimuli. These subjects had enhanced mismatch negativity (MMN) amplitudes particularly for pitch and duration deviants, indicating enhanced sound-discrimination abilities. Furthermore, as reflected by the P3a, their involuntary orienting was enhanced for changes in non-speech sounds, but tended to be deficient for changes in speech sounds. The results are consistent with those reported earlier in children with AS, except for the duration-MMN, which was diminished in children and enhanced in adults.

  1. Limited scleroderma and early detection of visceral changes

    International Nuclear Information System (INIS)

    Kalyuzhnaya, L.D.; Potsibina, V.V.; Stychinskaya, L.P.; Turik, N.V.

    1989-01-01

    The state of liver, kidneys, osteoarticular apparatus at the early stages of development of limited scleroderma and with the exclusion of visceral changes on the basis of clinical-laboratory studies is investigated. 11 patients with scleroderma in the age of 7-18 years were examined. Osteoscintigraphy with 99m TC-phosphone and dynamic scintigraphy of kidneys without additional introduction of RF, and hepatocholecyctoscintigraphy with 99m tc-HIPA of the patients were realized. The conclusion is made that radionuclide investigation methods permit to reveal various visceral changes, which are not recognizable by clinical methods

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

    Science.gov (United States)

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

    2012-12-01

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

  3. 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.

  4. Detecting Forest Cover and Ecosystem Service Change Using ...

    African Journals Online (AJOL)

    user

    Mpigi, than in Butambala by 5.99%, disturbed forest was 3%, farm land ... climate change impacts on ecosystem services requires more attention and ... While these conceptual models usually assume relatively a causal-effect ... images with relatively low cloud cover or free-cloud imagery during the time period of interest.

  5. Detecting changes in insect herbivore communities along a pollution gradient

    International Nuclear Information System (INIS)

    Eatough Jones, Michele; Paine, Timothy D.

    2006-01-01

    The forests surrounding the urban areas of the Los Angeles basin are impacted by ozone and nitrogen pollutants arising from urban areas. We examined changes in the herbivore communities of three prominent plant species (ponderosa pine, California black oak and bracken fern) at six sites along an air pollution gradient. Insects were extracted from foliage samples collected in spring, as foliage reached full expansion. Community differences were evaluated using total herbivore abundance, richness, Shannon-Weiner diversity, and discriminant function analysis. Even without conspicuous changes in total numbers, diversity or richness of herbivores, herbivore groups showed patterns of change that followed the air pollution gradient that were apparent through discriminant function analysis. For bracken fern and oak, chewing insects were more dominant at high pollution sites. Oak herbivore communities showed the strongest effect. These changes in herbivore communities may affect nutrient cycling in forest systems. - Differences in insect herbivore communities were associated with an ambient air pollution gradient in the mixed conifer forest outside the Los Angeles area

  6. Detecting areal changes in tidal flats after sea dike construction ...

    Indian Academy of Sciences (India)

    The main objective of this study was to estimate changes in the area of tidal flats that occurred after sea dike construction on the western coast of South Korea using Landsat-TM images. Applying the ISODATA method of unsupervised classification for Landsat-TM images, the tidal flats were identified, and the resulting areas ...

  7. Detecting changes in insect herbivore communities along a pollution gradient

    Energy Technology Data Exchange (ETDEWEB)

    Eatough Jones, Michele [Department of Entomology, University of California Riverside, Riverside, CA 92521 (United States)]. E-mail: michele.eatough@ucr.edu; Paine, Timothy D. [Department of Entomology, University of California Riverside, Riverside, CA 92521 (United States)]. E-mail: timothy.paine@ucr.edu

    2006-10-15

    The forests surrounding the urban areas of the Los Angeles basin are impacted by ozone and nitrogen pollutants arising from urban areas. We examined changes in the herbivore communities of three prominent plant species (ponderosa pine, California black oak and bracken fern) at six sites along an air pollution gradient. Insects were extracted from foliage samples collected in spring, as foliage reached full expansion. Community differences were evaluated using total herbivore abundance, richness, Shannon-Weiner diversity, and discriminant function analysis. Even without conspicuous changes in total numbers, diversity or richness of herbivores, herbivore groups showed patterns of change that followed the air pollution gradient that were apparent through discriminant function analysis. For bracken fern and oak, chewing insects were more dominant at high pollution sites. Oak herbivore communities showed the strongest effect. These changes in herbivore communities may affect nutrient cycling in forest systems. - Differences in insect herbivore communities were associated with an ambient air pollution gradient in the mixed conifer forest outside the Los Angeles area.

  8. Change detection in a series of Sentinel-1 SAR data

    DEFF Research Database (Denmark)

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

    2017-01-01

    Based on an omnibus likelihood ratio test statistic for the equality of several variance-covariance matrices following the complex Wishart distribution with an associated p-value and a factorization of this test statistic, change analysis in a time series of seven multilook, dual polarization...

  9. Ontology Versioning and Change Detection on the Web

    NARCIS (Netherlands)

    Klein, Michel; Fensel, Dieter; Kiryakov, Atanas; Ognyanov, Damyan

    2002-01-01

    To effectively use ontologies on the Web, it is essential that changes in ontologies are managed well. This paper analyzes the topic of ontology versioning in the context of the Web by looking at the characteristics of the version relation between ontologies and at the identification of online

  10. A New Statistic for Detection of Aberrant Answer Changes

    Science.gov (United States)

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

    2017-01-01

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

  11. Detecting forest cover and ecosystem service change using ...

    African Journals Online (AJOL)

    Natural forests in Uganda have experienced both spatial and temporal modifications from different drivers which need to be monitored to assess the impacts of such changes on ecosystems and prevent related risks of reduction in ecosystem service benefits. Ground investigations may be complex because of dual ...

  12. Detecting geomorphic processes and change with high resolution topographic data

    Science.gov (United States)

    Mudd, Simon; Hurst, Martin; Grieve, Stuart; Clubb, Fiona; Milodowski, David; Attal, Mikael

    2016-04-01

    The first global topographic dataset was released in 1996, with 1 km grid spacing. It is astonishing that in only 20 years we now have access to tens of thousands of square kilometres of LiDAR data at point densities greater than 5 points per square meter. This data represents a treasure trove of information that our geomorphic predecessors could only dream of. But what are we to do with this data? Here we explore the potential of high resolution topographic data to dig deeper into geomorphic processes across a wider range of landscapes and using much larger spatial coverage than previously possible. We show how this data can be used to constrain sediment flux relationships using relief and hillslope length, and how this data can be used to detect landscape transience. We show how the nonlinear sediment flux law, proposed for upland, soil mantled landscapes by Roering et al. (1999) is consistent with a number of topographic tests. This flux law allows us to predict how landscapes will respond to tectonic forcing, and we show how these predictions can be used to detect erosion rate perturbations across a range of tectonic settings.

  13. 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.

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

    Science.gov (United States)

    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

  15. Change Detection and Sustainable Policies of Mangrove Forests

    DEFF Research Database (Denmark)

    Malik, Abdul

    Deforestation and degradation of mangrove forests have become one of the main issues for coastal ecosystems in Indonesia and elsewhere in Southeast Asia. Over the past decades, over-exploitation of timber, firewood, charcoal production, housing materials, and commercial logging and conversion...... into other forms of land use such as agriculture, settlement, mining, and especially aquaculture have led to a reduction in the extent of mangrove forests and their biodiversity, which has had significant effects on local communities. This thesis addresses mangrove forest change over the past 33 years...... and the environmental and socioeconomic consequences of the observed changes for communities living around mangrove areas. In this connection, the effects of mangrove exploitation on biodiversity and ecosystem services, including forestry and fishery products, are explored. Finally, the total economic value...

  16. Methodological examination of UAR-based change detection

    Energy Technology Data Exchange (ETDEWEB)

    Racz, A.; Kiss, S. [Hungarian Academy of Sciences, Budapest (Hungary). Central Research Inst. for Physics

    1995-12-01

    A methodological examination was performed in order to investigate the applicability of the combination of the well-known Univariate AutoRegressive model and the classical binary SPRT method. The signal was recorded by a vibration detector fixed at a white-noise excited fuel rod. During the experiments, the following abnormality (or minor changes) were simulated: loosening of the detector, changes in the underlying system (constraints and the environment), rod impact. The residual time series were generated by an UAR model while the hypothesis testing was performed by a binary SPRT applied for checking the variation of the variance of the residual. Although the results are very promising, few disturbing effects were recognized also, which are as yet unexplained, therefore more careful application of this familiar combination is required. (author).

  17. Methodological examination of UAR-based change detection

    International Nuclear Information System (INIS)

    Racz, A.; Kiss, S.

    1994-07-01

    A methodological examination was performed in order to investigate the applicability of the combination of the well-known Univariate Auto Regressive (UAR) model and the classical binary Sequential Probability Ratio Testing (SPRT) method. The signal was recorded by a vibration detector fixed at a white-noise excited fuel rod. During the experiments, the following abnormality (or minor changes) were simulated: loosening of the detector, changes in the underlying system (constraints and the environment), rod impact. The residual time series were generated by an UAR model while the hypothesis testing was performed by a binary SPRT applied for checking the variation of the variance of the residual. Although the results are very promising, few disturbing effects were recognized also, which seem to be unexplained yet, therefore they need more careful application of this familiar combination. (author) 14 refs.; 21 figs.; 3 tabs

  18. Linear and kernel methods for multi- and hypervariate change detection

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg; Canty, Morton J.

    2010-01-01

    . Principal component analysis (PCA) as well as maximum autocorrelation factor (MAF) and minimum noise fraction (MNF) analyses of IR-MAD images, both linear and kernel-based (which are nonlinear), may further enhance change signals relative to no-change background. The kernel versions are based on a dual...... formulation, also termed Q-mode analysis, in which the data enter into the analysis via inner products in the Gram matrix only. In the kernel version the inner products of the original data are replaced by inner products between nonlinear mappings into higher dimensional feature space. Via kernel substitution......, also known as the kernel trick, these inner products between the mappings are in turn replaced by a kernel function and all quantities needed in the analysis are expressed in terms of the kernel function. This means that we need not know the nonlinear mappings explicitly. Kernel principal component...

  19. 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.

  20. 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.

  1. Contextualized pain management in newborns

    Directory of Open Access Journals (Sweden)

    Carlo Valerio Bellieni

    2016-08-01

    Full Text Available Neonatal pain treatment requires personalization, and pain assessment should be contextualized to be effective. Here we summarize the available tools in neonatal analgesia, paying a special attention to highlight the personalization of antalgic behavior, both in assessment and in treatment of neonatal pain. Proceedings of the 11th International Workshop on Neonatology and Satellite Meetings · Cagliari (Italy · October 26th-31st, 2015 · From the womb to the adultGuest Editors: Vassilios Fanos (Cagliari, Italy, Michele Mussap (Genoa, Italy, Antonio Del Vecchio (Bari, Italy, Bo Sun (Shanghai, China, Dorret I. Boomsma (Amsterdam, the Netherlands, Gavino Faa (Cagliari, Italy, Antonio Giordano (Philadelphia, USA

  2. Contextual logic for quantum systems

    International Nuclear Information System (INIS)

    Domenech, Graciela; Freytes, Hector

    2005-01-01

    In this work we build a quantum logic that allows us to refer to physical magnitudes pertaining to different contexts from a fixed one without the contradictions with quantum mechanics expressed in no-go theorems. This logic arises from considering a sheaf over a topological space associated with the Boolean sublattices of the ortholattice of closed subspaces of the Hilbert space of the physical system. Different from standard quantum logics, the contextual logic maintains a distributive lattice structure and a good definition of implication as a residue of the conjunction

  3. Memory cost of quantum contextuality

    International Nuclear Information System (INIS)

    Kleinmann, Matthias; Gühne, Otfried; Portillo, José R; Larsson, Jan-Åke; Cabello, Adán

    2011-01-01

    The simulation of quantum effects requires certain classical resources, and quantifying them is an important step to characterize the difference between quantum and classical physics. For a simulation of the phenomenon of state-independent quantum contextuality, we show that the minimum amount of memory used by the simulation is the critical resource. We derive optimal simulation strategies for important cases and prove that reproducing the results of sequential measurements on a two-qubit system requires more memory than the information-carrying capacity of the system. (paper)

  4. Information Foraging and Change Detection for Automated Science Exploration

    Science.gov (United States)

    Furlong, P. Michael; Dille, Michael

    2016-01-01

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

  5. Detecting Arctic Climate Change Using Koeppen Climate Classification

    Energy Technology Data Exchange (ETDEWEB)

    Wang, M. [Joint Institute for the Study of Atmosphere and Oceans, University of Washington, Seattle, Washington (United States); Overland, J.E. [NOAA/Pacific Marine Environmental Laboratory, Sand Point Way NE, Seattle, Washington (United States)

    2004-11-01

    Ecological impacts of the recent warming trend in the Arctic are already noted as changes in tree line and a decrease in tundra area with the replacement of ground cover by shrubs in northern Alaska and several locations in northern Eurasia. The potential impact of vegetation changes to feedbacks on the atmospheric climate system is substantial because of the large land area impacted and the multi-year persistence of the vegetation cover. Satellite NDVI estimates beginning in 1981 and the Koeppen climate classification, which relates surface types to monthly mean air temperatures from 1901 onward, track these changes on an Arctic-wide basis. Temperature fields from the NCEP/NCAR reanalysis and CRU analysis serve as proxy for vegetation cover over the century. A downward trend in the coverage of tundra group for the first 40 yr of the twentieth century was followed by two increases during 1940s and early 1960s, and then a rapid decrease in the last 20 yr. The decrease of tundra group in the 1920-40 period was localized, mostly over Scandinavia; whereas the decrease since 1990 is primarily pan-Arctic, but largest in NW Canada, and eastern and coastal Siberia. The decrease in inferred tundra coverage from 1980 to 2000 was 1.4 x 106 km{sup 2}, or about a 20% reduction in tundra area based on the CRU analyses. This rate of decrease is confirmed by the NDVI data. These tundra group changes in the last 20 yr are accompanied by increase in the area of both the boreal and temperate groups. During the tundra group decrease in the first half of the century boreal group area also decreased while temperate group area increased. The calculated minimum coverage of tundra group from both the Koeppen classification and NDVI indicates that the impact of warming on the spatial coverage of the tundra group in the 1990s is the strongest in the century, and will have multi-decadal consequences for the Arctic.

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

    Science.gov (United States)

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

    2016-01-01

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

  7. Change Detection of High-Resolution Remote Sensing Images Based on Adaptive Fusion of Multiple Features

    Science.gov (United States)

    Wang, G. H.; Wang, H. B.; Fan, W. F.; Liu, Y.; Chen, C.

    2018-04-01

    In view of the traditional change detection algorithm mainly depends on the spectral information image spot, failed to effectively mining and fusion of multi-image feature detection advantage, the article borrows the ideas of object oriented analysis proposed a multi feature fusion of remote sensing image change detection algorithm. First by the multi-scale segmentation of image objects based; then calculate the various objects of color histogram and linear gradient histogram; utilizes the color distance and edge line feature distance between EMD statistical operator in different periods of the object, using the adaptive weighted method, the color feature distance and edge in a straight line distance of combination is constructed object heterogeneity. Finally, the curvature histogram analysis image spot change detection results. The experimental results show that the method can fully fuse the color and edge line features, thus improving the accuracy of the change detection.

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

    Science.gov (United States)

    Akay, A. E.; Gencal, B.; Taş, İ.

    2017-11-01

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

  9. Inland wetland change detection using aircraft MSS [multispectral scanner] data

    International Nuclear Information System (INIS)

    Jensen, J.R.; Ramsey, E.W.; Mackey, H.E. Jr.; Sharitz, R.R.; Christensen, E.J.

    1986-01-01

    Nontidal wetlands in a portion of the Savannah River swamp forest affected by reactor cooling water discharges were mapped using March 31, 1981 and April 29, 1985 high-resolution aircraft multispectral scanner (MSS) data. Due to the inherent distortion in the aircraft MSS data and the complex spectral characteristics of the wetland vegetation, it was necessary to implement multiple techniques in the registration and classification of the MSS imagery of the Pen Branch Delta on each date. In particular, it was necessary to use a piecewise-linear registration process over relatively small regions to perform image-to-image registration. When performing unsupervised classification, an iterative ''cluster busting'' technique was used, which simplified the cluster labeling process. These procedures allowed important wetland vegetation categories to be identified on each date. The multiple-date classification maps were then evaluated using a post-classification comparison technique yielding change classes that were of value in determining the extent of inland wetland change in this region

  10. Contextual Teaching and Learning for Practitioners

    Directory of Open Access Journals (Sweden)

    Clemente Charles Hudson

    2008-08-01

    Full Text Available Contextual Teaching and Learning (CTL is defined as a way to introduce content using a variety of activelearning techniques designed to help students connect what they already know to what they are expected to learn, and to construct new knowledge from the analysis and synthesis of this learning process. A theoretical basis for CTL is outlined, with a focus on Connection, Constructivist, and Active Learning theories. A summary of brain activity during the learning process illustrates the physiological changes and connections that occur during educational activities. Three types of learning scenarios (project-based, goal-based, and inquiry-oriented are presented to illustrate how CTL can be applied by practitioners.

  11. Facets of contextual realism in quantum mechanics

    International Nuclear Information System (INIS)

    Pan, Alok Kumar; Home, Dipankar

    2011-01-01

    In recent times, there is an upsurge of interest in demonstrating the quantum contextuality. In this proceedings, we explore the two different forms of arguments that have been used for showing the contextual character of quantum mechanics. First line of study concerns the violations of the noncontextual realist models by quantum mechanics, where second line of study that is qualitatively distinct from the earlier one, demonstrates the contextuality within the formalism of quantum mechanics.

  12. Proliferative changes in nonpalpable breast lesions detected by mammography

    International Nuclear Information System (INIS)

    Vega, A.; Delgado, A.; Ortega, E.; Garijo, F.; Mosquera, J.; Sogo, C.; Alvarez, A.

    2000-01-01

    To analyze retrospectively the radiological findings in nonpalpable breast lesions detected by mammography that lead to the performance of surgical biopsy, resulting in a histological diagnosis of proliferative breast disease with and without atypia. From two Spanish hospitals, 421 women with 429 biopsies indicative of the presence of proliferative breast disease with and without atypia were selected out of a total of 1252 surgical biopsies in nonpalpable lesions that proved to be benign. Age, personal and familial history of breast cancer, reason for requesting the mammography and radiological findings that had indicated the need for surgical biopsy were recorded for each patient. The diagnosis was proliferative breast disease (epithelial hyperplasia) in 347 women with 354 biopsies and atypical hyperplasia in the remaining 74 women with 75 biopsies, representing 28% and 6%, respectively, of the 1252 biopsies of lesions found to be benign. In 221 of the 354 cases of epithelial hyperplasia (62%) and 45 of the 75 cases of atypical hyperplasia (60%), the presence of calcifications was the most common radiological findings leading to biopsy (p<0.05). Parenchymal distortion, with or without calcifications, was the second most common radiological sign. The histological study revealed a close relationship between these proliferative events and radial scars. Calcifications are the radiological finding that most frequently indicate the need for surgical biopsy in nonpalpable lesions that results in a diagnosis of proliferative breast disease with and without atypia. (Author) 12 refs

  13. Bivariate Genomic Footprinting Detects Changes in Transcription Factor Activity

    Directory of Open Access Journals (Sweden)

    Songjoon Baek

    2017-05-01

    Full Text Available In response to activating signals, transcription factors (TFs bind DNA and regulate gene expression. TF binding can be measured by protection of the bound sequence from DNase digestion (i.e., footprint. Here, we report that 80% of TF binding motifs do not show a measurable footprint, partly because of a variable cleavage pattern within the motif sequence. To more faithfully portray the effect of TFs on chromatin, we developed an algorithm that captures two TF-dependent effects on chromatin accessibility: footprinting and motif-flanking accessibility. The algorithm, termed bivariate genomic footprinting (BaGFoot, efficiently detects TF activity. BaGFoot is robust to different accessibility assays (DNase-seq, ATAC-seq, all examined peak-calling programs, and a variety of cut bias correction approaches. BaGFoot reliably predicts TF binding and provides valuable information regarding the TFs affecting chromatin accessibility in various biological systems and following various biological events, including in cases where an absolute footprint cannot be determined.

  14. Detecting change in dynamic process systems with immunocomputing

    Energy Technology Data Exchange (ETDEWEB)

    Yang, X.; Aldrich, C.; Maree, C. [University of Stellenbosch, Stellenbosch (South Africa). Dept. of Process Engineering

    2007-02-15

    The natural immune system is an adaptive distributed pattern recognition system with several functional components designed for recognition, memory acquisition, diversity and self-regulation. In artificial immune systems, some of these characteristics are exploited in order to design computational systems capable of detecting novel patterns or the anomalous behaviour of a system in some sense. Despite their obvious promise in the application of fault diagnostic systems in process engineering, their potential remains largely unexplored in this regard. In this paper, the application of real-valued negative selection algorithms to simulated and real-world systems is considered. These algorithms deal with the self-nonself discrimination problem in immunocomputing, where normal process behaviour is coded as the self and any deviations from normal behaviour is encoded as nonself. The case studies have indicated that immunocomputing based on negative selection can provide competitive options for fault diagnosis in nonlinear process systems, but further work is required on large systems characterized by many variables.

  15. Contextual inquiry for medical device design

    CERN Document Server

    Privitera, Mary Beth

    2015-01-01

    Contextual Inquiry for Medical Device Design helps users understand the everyday use of medical devices and the way their usage supports the development of better products and increased market acceptance. The text explains the concept of contextual inquiry using real-life examples to illustrate its application. Case studies provide a frame of reference on how contextual inquiry is successfully used during product design, ultimately producing safer, improved medical devices. Presents the ways contextual inquiry can be used to inform the evaluation and business case of technologyHelps users

  16. Templates and Queries in Contextual Hypermedia

    DEFF Research Database (Denmark)

    Anderson, Kenneth Mark; Hansen, Frank Allan; Bouvin, Niels Olof

    2006-01-01

    discuss a framework, HyConSC, that implements this model and describe how it can be used to build new contextual hypermedia systems. Our framework aids the developer in the iterative development of contextual queries (via a dynamic query browser) and offers support for con-text matching, a key feature...... of contextual hypermedia. We have tested the framework with data and sensors taken from the HyCon contextual hypermedia system and are now migrating HyCon to this new framework....

  17. Detecting settlement expansion in South Africa using a hyper-temporal SAR change detection approach

    CSIR Research Space (South Africa)

    Kleynhans, W

    2015-10-01

    Full Text Available by computing δSARk = k∑ τ=1 RSAR(τ). (7) From (7) it is evident that the new change metric uses a summation of the first k lags of RSAR(τ). By using the summation, the method is not as sensitive to the selection of a specific value of τ . A change or no...-change decision was made by comparing δSARk , which is computed for each pixel in the image, to a threshold value value δ∗ Change = { true if δSARk ≥ δ ∗ false if δSARk < δ ∗ (8) 3.2.1. Selection of the k parameter To evaluate how the overall accuracy is affected...

  18. Context-specific attentional sampling: Intentional control as a pre-requisite for contextual control.

    Science.gov (United States)

    Brosowsky, Nicholaus P; Crump, Matthew J C

    2016-08-01

    Recent work suggests that environmental cues associated with previous attentional control settings can rapidly and involuntarily adjust attentional priorities. The current study tests predictions from adaptive-learning and memory-based theories of contextual control about the role of intentions for setting attentional priorities. To extend the empirical boundaries of contextual control phenomena, and to determine whether theoretical principles of contextual control are generalizable we used a novel bi-dimensional stimulus sampling task. Subjects viewed briefly presented arrays of letters and colors presented above or below fixation, and identified specific stimuli according to a dimensional (letter or color) and positional cue. Location was predictive of the cued dimension, but not the position or identity. In contrast to previous findings, contextual control failed to develop through automatic, adaptive-learning processes. Instead, previous experience with intentionally changing attentional sampling priorities between different contexts was required for contextual control to develop. Copyright © 2016 Elsevier Inc. All rights reserved.

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

    Science.gov (United States)

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

    1990-01-01

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

  20. Contextual risk and child psychopathology.

    Science.gov (United States)

    Flouri, Eirini

    2008-10-01

    In developmental psychopathology it almost goes without saying that contextual risk factors do not occur in isolation and that it is the combination of various risk factors that portends numerous negative child outcomes. Despite this, the body of literature that examines the relation between multiple risk exposure and child psychopathology using a cumulative risk approach is still relatively small. Even when studies use a cumulative risk approach they rarely test properly whether the relation between cumulative risk and child psychopathology is linear or nonlinear, with consequences for both theory development and intervention design: if cumulative risk impacts problem behavior in a positively accelerated exponential manner, for instance, it means that exposure to multiple risk is especially difficult to manage as problem behavior accelerates at a critical level of risk. Furthermore, few studies have actually examined factors that protect from negative outcomes in those exposed to cumulative risk and even fewer have explored cumulative protection in relation to cumulative risk. On the other hand, there is the view that a cumulative risk approach at least implicitly assumes that risk factors are, in essence, interchangeable. According to this view, the importance of testing for specificity should not be underestimated. Finally, the renewed interest in the role of neighborhood risk in child development has initiated a lively debate as to whether contextual risk should be operationalized at the family or the area level. In this letter I discuss these issues, and offer some suggestions as to how future research can address them.

  1. Rapid contextual conditioning in autoshaping.

    Science.gov (United States)

    Balsam, P D; Schwartz, A L

    1981-10-01

    Two experiments are reported which investigate the speed of contextual conditioning in autoshaping. In both experiments, a procedure was employed in which ring doves were magazine trained in one context prior to the manipulation of background values in a second context. In Experiment 1, subjects were exposed to 4, 8, 64, 128, or 256 US-only presentations prior to autoshaping. Acquisition speed and maintained response measures were monotonically related to the number of pretraining trials. Subjects in Group 4 acquired the key-peck response fastest, and retardation was maximal within 64 pretraining trials. In Experiment 2, subjects given 20 pretraining trials were significantly more retarded than subjects given 2 pretraining trials, but only when pretraining and testing were conducted in the same context. Overall, the results of these experiments show that in autoshaping, contextual conditioning is very rapid; this demonstrates the plausibility of theoretical accounts of Pavlovian conditioning which assert that the development of the conditioned response depends on the associative values of both the CS and background stimuli.

  2. 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.

  3. Automatic change detection and quantification of dermatological diseases with an application to psoriasis images

    DEFF Research Database (Denmark)

    Gomez, David Delgado; Butakoff, C.; Ersbøll, Bjarne Kjær

    2007-01-01

    Change monitoring in skin lesion analysis has proven to be a useful adjunct in their assessment. This article presents a comparative study of the available change detection techniques applied to change visualization and quantification in bi-temporal psoriasis images. The chosen methods are evalua...

  4. Diagnosis of Wing Icing Through Lift and Drag Coefficient Change Detection for Small Unmanned Aircraft

    DEFF Research Database (Denmark)

    Sørensen, Kim Lynge; Blanke, Mogens; Johansen, Tor Arne

    2015-01-01

    This paper address the issue of structural change, caused by ice accretion, on UAVs by utilising a Neyman Pearson (NP) based statistical change detection approach, for the identification of structural changes of fixed wing UAV airfoils. A structural analysis is performed on the nonlinear aircraft...

  5. Two (or three) is one too many: testing the flexibility of contextual cueing with multiple target locations.

    Science.gov (United States)

    Zellin, Martina; Conci, Markus; von Mühlenen, Adrian; Müller, Hermann J

    2011-10-01

    Visual search for a target object is facilitated when the object is repeatedly presented within an invariant context of surrounding items ("contextual cueing"; Chun & Jiang, Cognitive Psychology, 36, 28-71, 1998). The present study investigated whether such invariant contexts can cue more than one target location. In a series of three experiments, we showed that contextual cueing is significantly reduced when invariant contexts are paired with two rather than one possible target location, whereas no contextual cueing occurs with three distinct target locations. Closer data inspection revealed that one "dominant" target always exhibited substantially more contextual cueing than did the other, "minor" target(s), which caused negative contextual-cueing effects. However, minor targets could benefit from the invariant context when they were spatially close to the dominant target. In sum, our experiments suggest that contextual cueing can guide visual attention to a spatially limited region of the display, only enhancing the detection of targets presented inside that region.

  6. Usher syndrome type 1: early detection of electroretinographic changes.

    Science.gov (United States)

    Flores-Guevara, Roberto; Renault, Francis; Loundon, Natalie; Marlin, Sandrine; Pelosse, Béatrice; Momtchilova, Martha; Auzoux-Chevé, Monique; Vermersch, Anne Isabelle; Richard, Pascal

    2009-11-01

    Usher syndrome type 1 needs to be diagnosed at early age in order to timely manage speech therapy, cochlear implantation, and genetic counseling. Few data are available regarding electroretinographic testing before the age of six years. To describe electroretinographic changes in young children with Usher syndrome type 1. Retrospective study of fourteen patients. Age at first neurophysiologic testing was between 17 months and 5 years 4 months. Electroretinogram was performed using flash stimulation in mesopic conditions in the conscious child. Analysis was focused on the amplitudes and latencies of a- and b-waves. Whatever the age, an abnormal fundus was always confirmed with an absent electroretinogram. The youngest patient with absent electroretinogram was 17 month-old. When recorded on and after the 29th month of age, electroretinogram was absent in all cases, including 6 patients with normal fundus. In three patients a low-amplitude electroretinogram was present at first recording within the 26th and 27th months. Electroretinogram showed retinopathy in young children with Usher syndrome type 1, even in the absence of fundoscopic signs of retinal degeneration.

  7. 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.

  8. [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

  9. INTERACTIVE CHANGE DETECTION USING HIGH RESOLUTION REMOTE SENSING IMAGES BASED ON ACTIVE LEARNING WITH GAUSSIAN PROCESSES

    Directory of Open Access Journals (Sweden)

    H. Ru

    2016-06-01

    Full Text Available Although there have been many studies for change detection, the effective and efficient use of high resolution remote sensing images is still a problem. Conventional supervised methods need lots of annotations to classify the land cover categories and detect their changes. Besides, the training set in supervised methods often has lots of redundant samples without any essential information. In this study, we present a method for interactive change detection using high resolution remote sensing images with active learning to overcome the shortages of existing remote sensing image change detection techniques. In our method, there is no annotation of actual land cover category at the beginning. First, we find a certain number of the most representative objects in unsupervised way. Then, we can detect the change areas from multi-temporal high resolution remote sensing images by active learning with Gaussian processes in an interactive way gradually until the detection results do not change notably. The artificial labelling can be reduced substantially, and a desirable detection result can be obtained in a few iterations. The experiments on Geo-Eye1 and WorldView2 remote sensing images demonstrate the effectiveness and efficiency of our proposed method.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

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

    Directory of Open Access Journals (Sweden)

    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.

  15. 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.

  16. Synchronous contextual irregularities affect early scene processing: replication and extension.

    Science.gov (United States)

    Mudrik, Liad; Shalgi, Shani; Lamy, Dominique; Deouell, Leon Y

    2014-04-01

    Whether contextual regularities facilitate perceptual stages of scene processing is widely debated, and empirical evidence is still inconclusive. Specifically, it was recently suggested that contextual violations affect early processing of a scene only when the incongruent object and the scene are presented a-synchronously, creating expectations. We compared event-related potentials (ERPs) evoked by scenes that depicted a person performing an action using either a congruent or an incongruent object (e.g., a man shaving with a razor or with a fork) when scene and object were presented simultaneously. We also explored the role of attention in contextual processing by using a pre-cue to direct subjects׳ attention towards or away from the congruent/incongruent object. Subjects׳ task was to determine how many hands the person in the picture used in order to perform the action. We replicated our previous findings of frontocentral negativity for incongruent scenes that started ~ 210 ms post stimulus presentation, even earlier than previously found. Surprisingly, this incongruency ERP effect was negatively correlated with the reaction times cost on incongruent scenes. The results did not allow us to draw conclusions about the role of attention in detecting the regularity, due to a weak attention manipulation. By replicating the 200-300 ms incongruity effect with a new group of subjects at even earlier latencies than previously reported, the results strengthen the evidence for contextual processing during this time window even when simultaneous presentation of the scene and object prevent the formation of prior expectations. We discuss possible methodological limitations that may account for previous failures to find this an effect, and conclude that contextual information affects object model selection processes prior to full object identification, with semantic knowledge activation stages unfolding only later on. Copyright © 2014 Elsevier Ltd. All rights reserved.

  17. Precise Automatic Image Coregistration Tools to Enable Pixel-Level Change Detection, Phase II

    Data.gov (United States)

    National Aeronautics and Space Administration — Automated detection of land cover changes between multitemporal images (i.e., images captured at different times) has long been a goal of the remote sensing...

  18. Perspectives on contextual vulnerability in discourses of climate conflict

    Science.gov (United States)

    Okpara, U. T.; Stringer, L. C.; Dougill, A. J.

    2016-02-01

    The science of climate security and conflict is replete with controversies. Yet the increasing vulnerability of politically fragile countries to the security consequences of climate change is widely acknowledged. Although climate conflict reflects a continuum of conditional forces that coalesce around the notion of vulnerability, how different portrayals of vulnerability influence the discursive formation of climate conflict relations remains an exceptional but under-researched issue. This paper combines a systematic discourse analysis with a vulnerability interpretation diagnostic tool to explore (i) how discourses of climate conflict are constructed and represented, (ii) how vulnerability is communicated across discourse lines, and (iii) the strength of contextual vulnerability against a deterministic narrative of scarcity-induced conflict, such as that pertaining to land. Systematically characterising climate conflict discourses based on the central issues constructed, assumptions about mechanistic relationships, implicit normative judgements and vulnerability portrayals, provides a useful way of understanding where discourses differ. While discourses show a wide range of opinions "for" and "against" climate conflict relations, engagement with vulnerability has been less pronounced - except for the dominant context centrism discourse concerned about human security (particularly in Africa). In exploring this discourse, we observe an increasing sense of contextual vulnerability that is oriented towards a concern for complexity rather than predictability. The article concludes by illustrating that a turn towards contextual vulnerability thinking will help advance a constructivist theory-informed climate conflict scholarship that recognises historicity, specificity, and variability as crucial elements of contextual totalities of any area affected by climate conflict.

  19. 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....

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

    Directory of Open Access Journals (Sweden)

    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.

  1. Exploiting Novel Radiation-Induced Electromagnetic Material Changes for Remote Detection and Monitoring: Final Progress Report

    Science.gov (United States)

    2016-04-01

    Exploiting Novel Radiation -Induced Electromagnetic Material Changes for Remote Detection and Monitoring: Final Progress Report Distribution...assess the effects of ionizing radiation on at least three classes of electromagnetic materials. The proposed approach for radiation detection was...that was desired to be monitored remotely. Microwave or low millimeter wave electromagnetic radiation would be used to interrogate the device

  2. Research in Model-Based Change Detection and Site Model Updating

    National Research Council Canada - National Science Library

    Nevatia, R

    1998-01-01

    .... Some of these techniques also are applicable to automatic site modeling and some of our change detection techniques may apply to detection of larger mobile objects, such as airplanes. We have implemented an interactive modeling system that works in conjunction with our automatic system to minimize the need for tedious interaction.

  3. A method for unsupervised change detection and automatic radiometric normalization in multispectral data

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg; Canty, Morton John

    2011-01-01

    Based on canonical correlation analysis the iteratively re-weighted multivariate alteration detection (MAD) method is used to successfully perform unsupervised change detection in bi-temporal Landsat ETM+ images covering an area with villages, woods, agricultural fields and open pit mines in North...... to carry out the analyses is available from the authors' websites....

  4. 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.

  5. Moral contextualism and the problem of triviality

    NARCIS (Netherlands)

    Evers, Daan

    Moral contextualism is the view that claims like ‘A ought to X’ are implicitly relative to some (contextually variable) standard. This leads to a problem: what are fundamental moral claims like ‘You ought to maximize happiness’ relative to? If this claim is relative to a utilitarian standard, then

  6. Contextual Factors in Adolescent Substance Use.

    Science.gov (United States)

    Hochhauser, Mark; And Others

    Research on adolescent substance use has focused on prevalence and incidence; however, contextual factors have been largely ignored. A survey of 155 adolescents from a Minneapolis suburb was conducted to assess contextual factors affecting adolescent substance use. Subjects reported their use of alcohol, cigarettes, and marihuana with respect to…

  7. Moral contextualism and the problem of triviality

    NARCIS (Netherlands)

    Evers, H.W.A.

    2013-01-01

    Moral contextualism is the view that claims like ‘A ought to X’ are implicitly relative to some (contextually variable) standard. This leads to a problem: what are fundamental moral claims like ‘You ought to maximize happiness’ relative to? If the claim is relative to a utilitarian standard, then

  8. Contextual factors and effective school improvement

    NARCIS (Netherlands)

    Sun, Hechuan; Creemers, Bert P. M.; de Jong, Rob

    This research provides policy-makers, researchers, and educators at all levels with a glimpse of the contextual influence on effective school improvement (ESI) in 8 European countries. What are the factors at the contextual level, particularly at the national level, which influence ESI? Are there

  9. Contextual Cueing Effects across the Lifespan

    Science.gov (United States)

    Merrill, Edward C.; Conners, Frances A.; Roskos, Beverly; Klinger, Mark R.; Klinger, Laura Grofer

    2013-01-01

    The authors evaluated age-related variations in contextual cueing, which reflects the extent to which visuospatial regularities can facilitate search for a target. Previous research produced inconsistent results regarding contextual cueing effects in young children and in older adults, and no study has investigated the phenomenon across the life…

  10. 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.

  11. Reliable computation from contextual correlations

    Science.gov (United States)

    Oestereich, André L.; Galvão, Ernesto F.

    2017-12-01

    An operational approach to the study of computation based on correlations considers black boxes with one-bit inputs and outputs, controlled by a limited classical computer capable only of performing sums modulo-two. In this setting, it was shown that noncontextual correlations do not provide any extra computational power, while contextual correlations were found to be necessary for the deterministic evaluation of nonlinear Boolean functions. Here we investigate the requirements for reliable computation in this setting; that is, the evaluation of any Boolean function with success probability bounded away from 1 /2 . We show that bipartite CHSH quantum correlations suffice for reliable computation. We also prove that an arbitrarily small violation of a multipartite Greenberger-Horne-Zeilinger noncontextuality inequality also suffices for reliable computation.

  12. 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

  13. TOWARDS CHANGE DETECTION IN URBAN AREA BY SAR INTERFEROMETRY AND RADARGRAMMETRY

    Directory of Open Access Journals (Sweden)

    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.

  14. 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.

  15. Dissociation - a preliminary contextual model

    Directory of Open Access Journals (Sweden)

    C Krüger

    2007-02-01

    Full Text Available Background. The Diagnostic and Statistical Manual of Mental Disorders (DSM system has certain limitations when applied to two South African examples of dissociation, because it is descriptive (non-explanatory and focuses on intrapsychic (non-communal processes. Even the existing Western explanatory models of dissociation fail to accommodate fully the communal aspects of dissociation in our South African context. Objectives and methods. The aim was to explore an expanded perspective on dissociation that does not limit it to an intrapsychic phenomenon, but that accounts for the interrelatedness of individuals within their social context. Auto-ethnography was used. In this article a collective, socially orientated, contextual hermeneutic was applied to two local examples of dissociation. Three existing Western models were expanded along multicontextual, collective lines, for them to be more useful in the pluralistic South African context. Results. This preliminary contextual model of dissociation includes a person’s interpersonal, socio-cultural, and spiritual contexts, in addition to the intrapsychic context. Dissociation is considered to be a normal information-processing tool that maintains balanced, coherent selves-in-society, i.e. individuals connected to each other. In the South African context dissociation appears mostly as a normal phenomenon and seldom as a sign of mental illness. Dissociation is pivotal for the normal construction of individual and communal identities in the face of conflicting sets of information from various contexts. Dissociation may help individuals or communities to survive in a world of conflicting messages, where conflict is often interpersonal/cultural/societal in nature, rather than primarily intrapsychic. Conclusions. This model should be developed and evaluated further. Such evaluation would require suitable new local terminology.

  16. Automatic detection of lexical change: an auditory event-related potential study.

    Science.gov (United States)

    Muller-Gass, Alexandra; Roye, Anja; Kirmse, Ursula; Saupe, Katja; Jacobsen, Thomas; Schröger, Erich

    2007-10-29

    We investigated the detection of rare task-irrelevant changes in the lexical status of speech stimuli. Participants performed a nonlinguistic task on word and pseudoword stimuli that occurred, in separate conditions, rarely or frequently. Task performance for pseudowords was deteriorated relative to words, suggesting unintentional lexical analysis. Furthermore, rare word and pseudoword changes had a similar effect on the event-related potentials, starting as early as 165 ms. This is the first demonstration of the automatic detection of change in lexical status that is not based on a co-occurring acoustic change. We propose that, following lexical analysis of the incoming stimuli, a mental representation of the lexical regularity is formed and used as a template against which lexical change can be detected.

  17. Considerations and methods for the changes detection using satellite images in the Municipality of Paipa

    International Nuclear Information System (INIS)

    Riano M, Orlando

    2002-01-01

    In this article the considerations and methods are presented for the changes detection in the earth covering, using two images Landsat TM of different dates for an area of the municipality of Paipa, Boyaca. The changes detection has become an important application of the multi-spectral data and multi-temporal of the satellites programs for studies of natural resources Landsat, TM and Spot, in such a way that is possible to determine the types and extension of the changes that are given in the environment. To carry out this process some digital techniques they have been used for changes detection, such as: images superposition, differences between images and analysis of main components. These techniques allowed to observe and to analyze changes in the use and covering of the earth in this municipality

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    Ajadi, Olaniyi A.

    Radar remote sensing can play a critical role in operational monitoring of natural and anthropogenic disasters. Despite its all-weather capabilities, and its high performance in mapping, and monitoring of change, the application of radar remote sensing in operational monitoring activities has been limited. This has largely been due to: (1) the historically high costs associated with obtaining radar data; (2) slow data processing, and delivery procedures; and (3) the limited temporal sampling that was provided by spaceborne radar-based satellites. Recent advances in the capabilities of spaceborne Synthetic Aperture Radar (SAR) sensors have developed an environment that now allows for SAR to make significant contributions to disaster monitoring. New SAR processing strategies that can take full advantage of these new sensor capabilities are currently being developed. Hence, with this PhD dissertation, I aim to: (i) investigate unsupervised change detection techniques that can reliably extract signatures from time series of SAR images, and provide the necessary flexibility for application to a variety of natural, and anthropogenic hazard situations; (ii) investigate effective methods to reduce the effects of speckle and other noise on change detection performance; (iii) automate change detection algorithms using probabilistic Bayesian inferencing; and (iv) ensure that the developed technology is applicable to current, and future SAR sensors to maximize temporal sampling of a hazardous event. This is achieved by developing new algorithms that rely on image amplitude information only, the sole image parameter that is available for every single SAR acquisition.. The motivation and implementation of the change detection concept are described in detail in Chapter 3. In the same chapter, I demonstrated the technique's performance using synthetic data as well as a real-data application to map wildfire progression. I applied Radiometric Terrain Correction (RTC) to the data to

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

    Science.gov (United States)

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

    2018-03-01

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

  1. 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

  2. Acceptance of lean redesigns in primary care: A contextual analysis.

    Science.gov (United States)

    Hung, Dorothy; Gray, Caroline; Martinez, Meghan; Schmittdiel, Julie; Harrison, Michael I

    Lean is a leading change strategy used in health care to achieve short-term efficiency and quality improvement while promising longer-term system transformation. Most research examines Lean intervention to address isolated problems, rather than to achieve broader systemic changes to care delivery. Moreover, no studies examine contextual influences on system-wide Lean implementation efforts in primary care. The aim of this study was to identify contextual factors most critical to implementing and scaling Lean redesigns across all primary care clinics in a large, ambulatory care delivery system. Over 100 interviews and focus groups were conducted with frontline physicians, clinical staff, and operational leaders. Data analysis was guided by a modified Consolidated Framework for Implementation Research (CFIR), a popular implementation science framework. On the basis of expert recommendations, the modified framework targets factors influencing the implementation of process redesigns. This modified framework, the CFIR-PR, informed our identification of contextual factors that most impacted Lean acceptance among frontline physicians and staff. Several domains identified by the CFIR-PR were critical to acceptance of Lean redesigns. Regarding the implementation process acceptance was influenced by time and intensity of exposure to changes, "top-down" versus "bottom-up" implementation styles, and degrees of employee engagement in developing new workflows. Important factors in the inner setting were the clinic's culture and style of leadership, along with availability of information about Lean's effectiveness. Last, implementation efforts were impacted by individual and team characteristics regarding changed work roles and related issues of professional identity, authority, and autonomy. This study underscores the need for change leaders to consider the contextual factors that surround efforts to implement Lean in primary care. As Lean redesigns are scaled across a system

  3. Detecting Brain State Changes via Fiber-Centered Functional Connectivity Analysis

    Science.gov (United States)

    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

  4. Building change detection via a combination of CNNs using only RGB aerial imageries

    Science.gov (United States)

    Nemoto, Keisuke; Hamaguchi, Ryuhei; Sato, Masakazu; Fujita, Aito; Imaizumi, Tomoyuki; Hikosaka, Shuhei

    2017-10-01

    Building change information extracted from remote sensing imageries is important for various applications such as urban management and marketing planning. The goal of this work is to develop a methodology for automatically capturing building changes from remote sensing imageries. Recent studies have addressed this goal by exploiting 3-D information as a proxy for building height. In contrast, because in practice it is expensive or impossible to prepare 3-D information, we do not rely on 3-D data but focus on using only RGB aerial imageries. Instead, we employ deep convolutional neural networks (CNNs) to extract effective features, and improve change detection accuracy in RGB remote sensing imageries. We consider two aspects of building change detection, building detection and subsequent change detection. Our proposed methodology was tested on several areas, which has some differences such as dominant building characteristics and varying brightness values. On all over the tested areas, the proposed method provides good results for changed objects, with recall values over 75 % with a strict overlap requirement of over 50% in intersection-over-union (IoU). When the IoU threshold was relaxed to over 10%, resulting recall values were over 81%. We conclude that use of CNNs enables accurate detection of building changes without employing 3-D information.

  5. Change detection in multitemporal synthetic aperture radar images using dual-channel convolutional neural network

    Science.gov (United States)

    Liu, Tao; Li, Ying; Cao, Ying; Shen, Qiang

    2017-10-01

    This paper proposes a model of dual-channel convolutional neural network (CNN) that is designed for change detection in SAR images, in an effort to acquire higher detection accuracy and lower misclassification rate. This network model contains two parallel CNN channels, which can extract deep features from two multitemporal SAR images. For comparison and validation, the proposed method is tested along with other change detection algorithms on both simulated SAR images and real-world SAR images captured by different sensors. The experimental results demonstrate that the presented method outperforms the state-of-the-art techniques by a considerable margin.

  6. Change detection in a short time sequence of polarimetric C-band SAR data

    DEFF Research Database (Denmark)

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

    2016-01-01

    in the covariance matrix representation is carried out. The omnibus test statistic and its factorization detect if and when change(s) occur. The technique is demonstrated on airborne EMISAR C-band data but may be applied to ALOS, COSMO-SkyMed, RadarSat-2 Sentinel-1, TerraSAR-X, and Yaogan data also....

  7. Omnibus test for change detection in a time sequence of polarimetric SAR data

    DEFF Research Database (Denmark)

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

    2016-01-01

    in the covariance matrix representation is carried out. The omnibus test statistic and its factorization detect if and when change(s) occur. The technique is demonstrated on airborne EMISAR C-band data but may be applied to ALOS, COSMO-SkyMed, RadarSat-2, Sentinel-1, TerraSAR-X, and Yoagan or other dual- and quad...

  8. Land-Cover Change Detection Using Multi-Temporal MODIS NDVI Imagery

    Science.gov (United States)

    Monitoring the locations and distributions of land-cover change is important for establishing linkages between policy decisions, regulatory actions and subsequent land-use activities. Past studies incorporating two-date change detection using Landsat data have tended to be perfor...

  9. Detecting land cover change using an extended Kalman filter on MODIS NDVI time-series data

    CSIR Research Space (South Africa)

    Kleynhans, W

    2011-05-01

    Full Text Available A method for detecting land cover change using NDVI time-series data derived from 500-m MODIS satellite data is proposed. The algorithm acts as a per-pixel change alarm and takes the NDVI time series of a 3 × 3 grid of MODIS pixels as the input...

  10. Temporal change detection of land use/land cover using GIS and ...

    African Journals Online (AJOL)

    Satellite images for the years 1972, 1989, 1999 and 2016 were used for LULC ... built-up areas, pastures and bare land, agricultural land and water bodies. For the accuracy of assessment classifications, matrix error and KAPPA ... Keywords: land use/land cover change; change detection; classification; remote sensing; GIS ...

  11. 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.

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

    Science.gov (United States)

    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

  13. Study on Method of Geohazard Change Detection Based on Integrating Remote Sensing and GIS

    International Nuclear Information System (INIS)

    Zhao, Zhenzhen; Yan, Qin; Liu, Zhengjun; Luo, Chengfeng

    2014-01-01

    Following a comprehensive literature review, this paper looks at analysis of geohazard using remote sensing information. This paper compares the basic types and methods of change detection, explores the basic principle of common methods and makes an respective analysis of the characteristics and shortcomings of the commonly used methods in the application of geohazard. Using the earthquake in JieGu as a case study, this paper proposes a geohazard change detection method integrating RS and GIS. When detecting the pre-earthquake and post-earthquake remote sensing images at different phases, it is crucial to set an appropriate threshold. The method adopts a self-adapting determination algorithm for threshold. We select a training region which is obtained after pixel information comparison and set a threshold value. The threshold value separates the changed pixel maximum. Then we apply the threshold value to the entire image, which could also make change detection accuracy maximum. Finally, we output the result to the GIS system to make change analysis. The experimental results show that this method of geohazard change detection based on integrating remote sensing and GIS information has higher accuracy with obvious advantages compared with the traditional methods

  14. Early pack-off diagnosis in drilling using an adaptive observer and statistical change detection

    DEFF Research Database (Denmark)

    Willersrud, Anders; Imsland, Lars; Blanke, Mogens

    2015-01-01

    in the well. A model-based adaptive observer is used to estimate these friction parameters as well as flow rates. Detecting changes to these estimates can then be used for pack-off diagnosis, which due to measurement noise is done using statistical change detection. Isolation of incident type and location...... is done using a multivariate generalized likelihood ratio test, determining the change direction of the estimated mean values. The method is tested on simulated data from the commercial high-fidelity multi-phase simulator OLGA, where three different pack-offs at different locations and with different...

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

    Directory of Open Access Journals (Sweden)

    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

  16. Quest for automated land cover change detection using satellite time series data

    CSIR Research Space (South Africa)

    Salmon, BP

    2009-07-01

    Full Text Available and surface climate in the next fifty years,” Global Change Biology, vol. 8, no. 5, pp. 438–458, May 2002. [3] J. A. Foley et al., “Global consequences of land use,” Science, vol. 309, no. 5734, pp. 570–574, July 2005. [4] R. S. Lunetta et al., “Land... (class 1). These four subsets were used to produce a confusion matrix to test if the operational MLP can detect change reliably in an automated fashion on subsets 1 and 2, while not falsely detecting change for subsets 3 and 4. This particular splic...

  17. Detection and localization of change points in temporal networks with the aid of stochastic block models

    Science.gov (United States)

    De Ridder, Simon; Vandermarliere, Benjamin; Ryckebusch, Jan

    2016-11-01

    A framework based on generalized hierarchical random graphs (GHRGs) for the detection of change points in the structure of temporal networks has recently been developed by Peel and Clauset (2015 Proc. 29th AAAI Conf. on Artificial Intelligence). We build on this methodology and extend it to also include the versatile stochastic block models (SBMs) as a parametric family for reconstructing the empirical networks. We use five different techniques for change point detection on prototypical temporal networks, including empirical and synthetic ones. We find that none of the considered methods can consistently outperform the others when it comes to detecting and locating the expected change points in empirical temporal networks. With respect to the precision and the recall of the results of the change points, we find that the method based on a degree-corrected SBM has better recall properties than other dedicated methods, especially for sparse networks and smaller sliding time window widths.

  18. Detection of Changes in Ground-Level Ozone Concentrations via Entropy

    Directory of Open Access Journals (Sweden)

    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.

  19. Contribution to the detection of changes in multi-modal 3D MRI sequences

    International Nuclear Information System (INIS)

    Bosc, Marcel

    2003-01-01

    This research thesis reports the study of automatic techniques for the detection of changes in image sequences of brain magnetic resonance imagery (MRI), and more particularly the study of localised intensity changes occurring during pathological evolutions such as evolutions of lesions into multiple sclerosis. Thus, this work focused on the development of image processing tools allowing to decide whether changes are statistically significant or not. The author developed automatic techniques of identification and correction of the main artefacts (position, deformations, intensity variation, and so on), and proposes an original technique for cortex segmentation which introduced anatomic information for an improved automatic detection. The developed change detection system has been assessed within the frame of the study of the evolution of lesions of multiple sclerosis. Performance have been determined on a large number of multi-modal images, and the automatic system has shown better performance than a human expert [fr

  20. Using contextual advertising in Internet marketing

    Directory of Open Access Journals (Sweden)

    Тетяна Олександрівна Левицька

    2017-07-01

    Full Text Available This article is devoted to the substantiation of the use of contextual advertising in Internet marketing as one of the most universal and expedient tools of modern advertising, applied for the first time in 1994, describing the principles of its implementation and the prospects for using it. The shortcomings and advantages of Internet marketing and contextual advertising in particular, its types and technologies, on which it is implemented, the possibilities, as well as the purposes of application, are considered. The main characteristics of contextual advertising, namely its characteristic properties as compared to the other types of Internet marketing, were highlighted. The use of contextual advertising in the search, on partner sites of the advertising network and an example of the report that was received by means of the Yandex.Metrika service have been shown. On the basis of the analysis the use of contextual advertising has been proved and its basic types and methods of measuring the effectiveness of advertising campaigns using deep analytics services have been demonstrated. The factor of the complexity of the configuration process has been singled out, and in this connection, a variant of professional intervention in setting up contextual advertising by specialized agencies has been offered. In the long term, the tools of contextual advertising are to expand. Every year, more and more services are being created for a deeper analysis of statistics, end-to-end analytics, and the improvement of the campaign management interface

  1. A More Efficient Contextuality Distillation Protocol

    Science.gov (United States)

    Meng, Hui-xian; Cao, Huai-xin; Wang, Wen-hua; Fan, Ya-jing; Chen, Liang

    2018-03-01

    Based on the fact that both nonlocality and contextuality are resource theories, it is natural to ask how to amplify them more efficiently. In this paper, we present a contextuality distillation protocol which produces an n-cycle box B ∗ B ' from two given n-cycle boxes B and B '. It works efficiently for a class of contextual n-cycle ( n ≥ 4) boxes which we termed as "the generalized correlated contextual n-cycle boxes". For any two generalized correlated contextual n-cycle boxes B and B ', B ∗ B ' is more contextual than both B and B '. Moreover, they can be distilled toward to the maximally contextual box C H n as the times of iteration goes to infinity. Among the known protocols, our protocol has the strongest approximate ability and is optimal in terms of its distillation rate. What is worth noting is that our protocol can witness a larger set of nonlocal boxes that make communication complexity trivial than the protocol in Brunner and Skrzypczyk (Phys. Rev. Lett. 102, 160403 2009), this might be helpful for exploring the problem that why quantum nonlocality is limited.

  2. 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.

  3. 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.

  4. Emotion has no impact on attention in a change detection flicker task

    Directory of Open Access Journals (Sweden)

    Robert Colin Alan Bendall

    2015-10-01

    Full Text Available Past research provides conflicting findings regarding the influence of emotion on visual attention. Early studies suggested a broadening of attentional resources in relation to positive mood. However, more recent evidence indicates that positive emotions may not have a beneficial impact on attention, and that the relationship between emotion and attention may be mitigated by factors such as task demand or stimulus valence. The current study explored the effect of emotion on attention using the change detection flicker paradigm. Participants were induced into positive, neutral, and negative mood states and then completed a change detection task. A series of neutral scenes were presented and participants had to identify the location of a disappearing item in each scene. The change was made to the centre or the periphery of each scene and it was predicted that peripheral changes would be detected quicker in the positive mood condition and slower in the negative mood condition, compared to the neutral condition. In contrast to previous findings emotion had no influence on attention and whilst central changes were detected faster than peripheral changes, change blindness was not affected by mood. The findings suggest that the relationship between emotion and visual attention is influenced by the characteristics of a task, and any beneficial impact of positive emotion may be related to processing style rather than a broadening of attentional resources.

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

    Science.gov (United States)

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

    2018-04-01

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

  6. Change Analysis and Decision Tree Based Detection Model for Residential Objects across Multiple Scales

    Directory of Open Access Journals (Sweden)

    CHEN Liyan

    2018-03-01

    Full Text Available Change analysis and detection plays important role in the updating of multi-scale databases.When overlap an updated larger-scale dataset and a to-be-updated smaller-scale dataset,people usually focus on temporal changes caused by the evolution of spatial entities.Little attention is paid to the representation changes influenced by map generalization.Using polygonal building data as an example,this study examines the changes from different perspectives,such as the reasons for their occurrence,their performance format.Based on this knowledge,we employ decision tree in field of machine learning to establish a change detection model.The aim of the proposed model is to distinguish temporal changes that need to be applied as updates to the smaller-scale dataset from representation changes.The proposed method is validated through tests using real-world building data from Guangzhou city.The experimental results show the overall precision of change detection is more than 90%,which indicates our method is effective to identify changed objects.

  7. Detecting Historical Vegetation Changes in the Dunhuang Oasis Protected Area Using Landsat Images

    Directory of Open Access Journals (Sweden)

    Xiuxia Zhang

    2017-09-01

    Full Text Available Abstract: Given its proximity to an artificial oasis, the Donghu Nature Reserve in the Dunhuang Oasis has faced environmental pressure and vegetation disturbances in recent decades. Satellite vegetation indices (VIs can be used to detect such changes in vegetation if the satellite images are calibrated to surface reflectance (SR values. The aim of this study was to select a suitable VI based on the Landsat Climate Data Record (CDR products and the absolute radiation-corrected results of Landsat L1T images to detect the spatio-temporal changes in vegetation for the Donghu Reserve during 1986–2015. The results showed that the VI difference (ΔVI images effectively reduced the changes in the source images. Compared with the other VIs, the soil-adjusted vegetation index (SAVI displayed greater robustness to atmospheric effects in the two types of SR images and was more responsive to vegetation changes caused by human factors. From 1986 to 2015, the positive changes in vegetation dominated the overall change trend, with changes in vegetation in the reserve decreasing during 1990–1995, increasing until 2005–2010, and then decreasing again. The vegetation changes were mainly distributed at the edge of the artificial oasis outside the reserve. The detected changes in vegetation in the reserve highlight the increased human pressure on the reserve.

  8. Change Detection in High-Resolution Remote Sensing Images Using Levene-Test and Fuzzy Evaluation

    Science.gov (United States)

    Wang, G. H.; Wang, H. B.; Fan, W. F.; Liu, Y.; Liu, H. J.

    2018-04-01

    High-resolution remote sensing images possess complex spatial structure and rich texture information, according to these, this paper presents a new method of change detection based on Levene-Test and Fuzzy Evaluation. It first got map-spots by segmenting two overlapping images which had been pretreated, extracted features such as spectrum and texture. Then, changed information of all map-spots which had been treated by the Levene-Test were counted to obtain the candidate changed regions, hue information (H component) was extracted through the IHS Transform and conducted change vector analysis combined with the texture information. Eventually, the threshold was confirmed by an iteration method, the subject degrees of candidate changed regions were calculated, and final change regions were determined. In this paper experimental results on multi-temporal ZY-3 high-resolution images of some area in Jiangsu Province show that: Through extracting map-spots of larger difference as the candidate changed regions, Levene-Test decreases the computing load, improves the precision of change detection, and shows better fault-tolerant capacity for those unchanged regions which are of relatively large differences. The combination of Hue-texture features and fuzzy evaluation method can effectively decrease omissions and deficiencies, improve the precision of change detection.

  9. Comparative performance of a modified change vector analysis in forest change detection

    NARCIS (Netherlands)

    Nackaerts, Kris; Vaesen, K.; Muys, Bart; Coppin, P.

    2005-01-01

    Sustainable forest management requires accurate and up-to-date information, which can nowadays be obtained using digital earth observation technology. This paper introduces a modified change vector analysis (mCVA) approach and conceptually contrasts it against traditional CVA. The results of a

  10. The Contextual Antecedents of Organizational Trust

    DEFF Research Database (Denmark)

    Li, Peter Ping; Bai, Yuntao; Xi, Youmin

    2012-01-01

    In this article we seek to explore the contextual antecedents of organizational trust. In light of the complex links between organizational contexts and organizational behaviours, we focus on the effects of the three most critical contextual antecedents, i.e., leadership role, structural rule...... in China, lent support for our multidimensional cross-level model of context–trust–behaviour link. We extend the research on organizational trust by treating it as a cross-level phenomenon and by specifying its core contextual antecedents and behavioural consequences....

  11. Testing quantum contextuality. The problem of compatibility

    International Nuclear Information System (INIS)

    Szangolies, Jochen

    2015-01-01

    Jochen Szangolies contributes a novel way of dealing with the problem of the experimental testability of the Kochen-Specker theorem posed by realistic, that is, noisy, measurements. Such noise spoils perfect compatibility between successive measurements, which however is a necessary requirement to test the notion of contextuality in usual approaches. To overcome this difficulty, a new, extended notion of contextuality that reduces to Kochen-Specker contextuality in the limit of perfect measurement implementations is proposed by the author, together with a scheme to test this notion experimentally. Furthermore, the behaviour of these tests under realistic noise conditions is investigated.

  12. A Gaussian Process Based Online Change Detection Algorithm for Monitoring Periodic Time Series

    Energy Technology Data Exchange (ETDEWEB)

    Chandola, Varun [ORNL; Vatsavai, Raju [ORNL

    2011-01-01

    Online time series change detection is a critical component of many monitoring systems, such as space and air-borne remote sensing instruments, cardiac monitors, and network traffic profilers, which continuously analyze observations recorded by sensors. Data collected by such sensors typically has a periodic (seasonal) component. Most existing time series change detection methods are not directly applicable to handle such data, either because they are not designed to handle periodic time series or because they cannot operate in an online mode. We propose an online change detection algorithm which can handle periodic time series. The algorithm uses a Gaussian process based non-parametric time series prediction model and monitors the difference between the predictions and actual observations within a statistically principled control chart framework to identify changes. A key challenge in using Gaussian process in an online mode is the need to solve a large system of equations involving the associated covariance matrix which grows with every time step. The proposed algorithm exploits the special structure of the covariance matrix and can analyze a time series of length T in O(T^2) time while maintaining a O(T) memory footprint, compared to O(T^4) time and O(T^2) memory requirement of standard matrix manipulation methods. We experimentally demonstrate the superiority of the proposed algorithm over several existing time series change detection algorithms on a set of synthetic and real time series. Finally, we illustrate the effectiveness of the proposed algorithm for identifying land use land cover changes using Normalized Difference Vegetation Index (NDVI) data collected for an agricultural region in Iowa state, USA. Our algorithm is able to detect different types of changes in a NDVI validation data set (with ~80% accuracy) which occur due to crop type changes as well as disruptive changes (e.g., natural disasters).

  13. The impact of signal-to-noise ratio on contextual cueing in children and adults.

    Science.gov (United States)

    Yang, Yingying; Merrill, Edward C

    2015-04-01

    Contextual cueing refers to a form of implicit spatial learning where participants incidentally learn to associate a target location with its repeated spatial context. Successful contextual learning produces an efficient visual search through familiar environments. Despite the fact that children exhibit the basic ability of implicit spatial learning, their general effectiveness in this form of learning can be compromised by other development-dependent factors. Learning to extract useful information (signal) in the presence of various amounts of irrelevant or distracting information (noise) characterizes one of the most important changes that occur with cognitive development. This research investigated whether signal-to-noise ratio (S/N) affects contextual cueing differently in children and adults. S/N was operationally defined as the ratio of repeated versus new displays encountered over time. Three ratio conditions were created: high (100%), medium (67%), and low (33%) conditions. Results suggested no difference in the acquisition of contextual learning effects in the high and medium conditions across three age groups (6- to 8-year-olds, 10- to 12-year-olds, and young adults). However, a significant developmental difference emerged in the low S/N condition. As predicted, adults exhibited significant contextual cueing effects, whereas older children showed marginally significant contextual cueing and younger children did not show cueing effects. Group differences in the ability to exhibit implicit contextual learning under low S/N conditions and the implications of this difference are discussed. Copyright © 2015 Elsevier Inc. All rights reserved.

  14. Contextual Advantage for State Discrimination

    Science.gov (United States)

    Schmid, David; Spekkens, Robert W.

    2018-02-01

    Finding quantitative aspects of quantum phenomena which cannot be explained by any classical model has foundational importance for understanding the boundary between classical and quantum theory. It also has practical significance for identifying information processing tasks for which those phenomena provide a quantum advantage. Using the framework of generalized noncontextuality as our notion of classicality, we find one such nonclassical feature within the phenomenology of quantum minimum-error state discrimination. Namely, we identify quantitative limits on the success probability for minimum-error state discrimination in any experiment described by a noncontextual ontological model. These constraints constitute noncontextuality inequalities that are violated by quantum theory, and this violation implies a quantum advantage for state discrimination relative to noncontextual models. Furthermore, our noncontextuality inequalities are robust to noise and are operationally formulated, so that any experimental violation of the inequalities is a witness of contextuality, independently of the validity of quantum theory. Along the way, we introduce new methods for analyzing noncontextuality scenarios and demonstrate a tight connection between our minimum-error state discrimination scenario and a Bell scenario.

  15. Contextual cueing by global features

    Science.gov (United States)

    Kunar, Melina A.; Flusberg, Stephen J.; Wolfe, Jeremy M.

    2008-01-01

    In visual search tasks, attention can be guided to a target item, appearing amidst distractors, on the basis of simple features (e.g. find the red letter among green). Chun and Jiang’s (1998) “contextual cueing” effect shows that RTs are also speeded if the spatial configuration of items in a scene is repeated over time. In these studies we ask if global properties of the scene can speed search (e.g. if the display is mostly red, then the target is at location X). In Experiment 1a, the overall background color of the display predicted the target location. Here the predictive color could appear 0, 400 or 800 msec in advance of the search array. Mean RTs are faster in predictive than in non-predictive conditions. However, there is little improvement in search slopes. The global color cue did not improve search efficiency. Experiments 1b-1f replicate this effect using different predictive properties (e.g. background orientation/texture, stimuli color etc.). The results show a strong RT effect of predictive background but (at best) only a weak improvement in search efficiency. A strong improvement in efficiency was found, however, when the informative background was presented 1500 msec prior to the onset of the search stimuli and when observers were given explicit instructions to use the cue (Experiment 2). PMID:17355043

  16. Contextual Advantage for State Discrimination

    Directory of Open Access Journals (Sweden)

    David Schmid

    2018-02-01

    Full Text Available Finding quantitative aspects of quantum phenomena which cannot be explained by any classical model has foundational importance for understanding the boundary between classical and quantum theory. It also has practical significance for identifying information processing tasks for which those phenomena provide a quantum advantage. Using the framework of generalized noncontextuality as our notion of classicality, we find one such nonclassical feature within the phenomenology of quantum minimum-error state discrimination. Namely, we identify quantitative limits on the success probability for minimum-error state discrimination in any experiment described by a noncontextual ontological model. These constraints constitute noncontextuality inequalities that are violated by quantum theory, and this violation implies a quantum advantage for state discrimination relative to noncontextual models. Furthermore, our noncontextuality inequalities are robust to noise and are operationally formulated, so that any experimental violation of the inequalities is a witness of contextuality, independently of the validity of quantum theory. Along the way, we introduce new methods for analyzing noncontextuality scenarios and demonstrate a tight connection between our minimum-error state discrimination scenario and a Bell scenario.

  17. Object-Location Training Elicits an Overlapping but Temporally Distinct Transcriptional Profile from Contextual Fear Conditioning

    OpenAIRE

    Poplawski, Shane G.; Schoch, Hannah; Wimmer, Mathieu; Hawk, Joshua D.; Walsh, Jennifer L.; Giese, Karl P.; Abel, Ted

    2014-01-01

    Hippocampus-dependent learning is known to induce changes in gene expression, but information on gene expression differences between different learning paradigms that require the hippocampus is limited. The bulk of studies investigating RNA expression after learning use the contextual fear conditioning task, which couples a novel environment with a footshock. Although contextual fear conditioning has been useful in discovering gene targets, gene expression after spatial memory tasks has recei...

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

    Science.gov (United States)

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

    2018-04-01

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

  19. 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

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

    Science.gov (United States)

    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.

  1. 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.

  2. Contextualization: Memory Formation and Retrieval in a Nested Environment

    Science.gov (United States)

    Piefke, Martina; Markowitsch, Hans J.

    Episodic memory functions are highly context-dependent. This is true for both experimental and autobiographical episodic memory. We here review neuropsychological and neuroimaging evidence for effects of differential encoding and retrieval contexts on episodic memory performance as well as the underlying neurofunctional mechanisms. In studies of laboratory episodic memory, the influence of context parameters can be assessed by experimental manipulations. Such experiments suggest that contextual variables mainly affect prefrontal functions supporting executive processes involved in episodic learning and retrieval. Context parameters affecting episodic autobiographical memory are far more complex and cannot easily be controlled. Data support the view that not only prefrontal, but also further medial temporal and posterior parietal regions mediating the re-experience and emotional evaluation of personal memories are highly influenced by changing contextual variables of memory encoding and retrieval. Based on our review of available data, we thus suggest that experimental and autobiographical episodic memories are influenced by both overlapping and differential context parameters.

  3. [Effect of object consistency in a spatial contextual cueing paradigm].

    Science.gov (United States)

    Takeda, Yuji

    2008-04-01

    Previous studies demonstrated that attention can be quickly guided to a target location in a visual search task when the spatial configurations of search items and/or the object identities were repeated in the previous trials. This phenomenon is termed contextual cueing. Recently, it was reported that spatial configuration learning and object identity learning occurred independently, when novel contours were used as search items. The present study examined whether this learning occurred independently even when the search items were meaningful. The results showed that the contextual cueing effect was observed even if the relationships between the spatial locations and object identities were jumbled (Experiment 1). However, it disappeared when the search items were changed into geometric patterns (Experiment 2). These results suggest that the spatial configuration can be learned independent of the object identities; however, the use of the learned configuration is restricted by the learning situations.

  4. Contextual and social influences on valuation and choice.

    Science.gov (United States)

    Engelmann, Jan B; Hein, Grit

    2013-01-01

    To survive in our complex environment, we have to adapt to changing contexts. Prior research that investigated how contextual changes are processed in the human brain has demonstrated important modulatory influences on multiple cognitive processes underlying decision-making, including perceptual judgments, working memory, as well as cognitive and attentional control. However, in everyday life, the importance of context is even more obvious during economic and social interactions, which often have implicit rule sets that need to be recognized by a decision-maker. Here, we review recent evidence from an increasing number of studies in the fields of Neuroeconomics and Social Neuroscience that investigate the neurobiological basis of contextual effects on valuation and social choice. Contrary to the assumptions of rational choice theory, multiple contextual factors, such as the availability of alternative choice options, shifts in reference point, and social context, have been shown to modulate behavior, as well as signals in task-relevant neural networks. A consistent picture that emerges from neurobiological results is that valuation-related activity in striatum and ventromedial prefrontal cortex is highly context dependent during both social and nonsocial choice. Alternative approaches to model and explain choice behavior, such as comparison-based choice models, as well as implications for future research are discussed. Copyright © 2013 Elsevier B.V. All rights reserved.

  5. Contextualizing Asian American College Student Psychological Health

    Science.gov (United States)

    Liang, Christopher T. H.; Liu, Jessica; Nguyen, David; Song, Ge

    2017-01-01

    With attention to race, culture, and gender, this chapter contextualizes the help-seeking behaviors and psychological aspects of health facing Asian American college students. Recommendations are provided to student affairs professionals and counselors.

  6. An Order-Theoretic Quantification of Contextuality

    Directory of Open Access Journals (Sweden)

    Ian T. Durham

    2014-09-01

    Full Text Available In this essay, I develop order-theoretic notions of determinism and contextuality on domains and topoi. In the process, I develop a method for quantifying contextuality and show that the order-theoretic sense of contextuality is analogous to the sense embodied in the topos-theoretic statement of the Kochen–Specker theorem. Additionally, I argue that this leads to a relation between the entropy associated with measurements on quantum systems and the second law of thermodynamics. The idea that the second law has its origin in the ordering of quantum states and processes dates to at least 1958 and possibly earlier. The suggestion that the mechanism behind this relation is contextuality, is made here for the first time.

  7. Study on Uncertainty and Contextual Modelling

    Czech Academy of Sciences Publication Activity Database

    Klimešová, Dana; Ocelíková, E.

    2007-01-01

    Roč. 1, č. 1 (2007), s. 12-15 ISSN 1998-0140 Institutional research plan: CEZ:AV0Z10750506 Keywords : Knowledge * contextual modelling * temporal modelling * uncertainty * knowledge management Subject RIV: BD - Theory of Information

  8. A Fast Framework for Abrupt Change Detection Based on Binary Search Trees and Kolmogorov Statistic

    Science.gov (United States)

    Qi, Jin-Peng; Qi, Jie; Zhang, Qing

    2016-01-01

    Change-Point (CP) detection has attracted considerable attention in the fields of data mining and statistics; it is very meaningful to discuss how to quickly and efficiently detect abrupt change from large-scale bioelectric signals. Currently, most of the existing methods, like Kolmogorov-Smirnov (KS) statistic and so forth, are time-consuming, especially for large-scale datasets. In this paper, we propose a fast framework for abrupt change detection based on binary search trees (BSTs) and a modified KS statistic, named BSTKS (binary search trees and Kolmogorov statistic). In this method, first, two binary search trees, termed as BSTcA and BSTcD, are constructed by multilevel Haar Wavelet Transform (HWT); second, three search criteria are introduced in terms of the statistic and variance fluctuations in the diagnosed time series; last, an optimal search path is detected from the root to leaf nodes of two BSTs. The studies on both the synthetic time series samples and the real electroencephalograph (EEG) recordings indicate that the proposed BSTKS can detect abrupt change more quickly and efficiently than KS, t-statistic (t), and Singular-Spectrum Analyses (SSA) methods, with the shortest computation time, the highest hit rate, the smallest error, and the highest accuracy out of four methods. This study suggests that the proposed BSTKS is very helpful for useful information inspection on all kinds of bioelectric time series signals. PMID:27413364

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

    Science.gov (United States)

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

    2018-03-01

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

  10. Fault diagnosis of downhole drilling incidents using adaptive observers and statistical change detection

    DEFF Research Database (Denmark)

    Willersrud, Anders; Blanke, Mogens; Imsland, Lars

    2015-01-01

    Downhole abnormal incidents during oil and gas drilling causes costly delays, any may also potentially lead to dangerous scenarios. Dierent incidents willcause changes to dierent parts of the physics of the process. Estimating thechanges in physical parameters, and correlating these with changes ...... expectedfrom various defects, can be used to diagnose faults while in development.This paper shows how estimated friction parameters and ow rates can de-tect and isolate the type of incident, as well as isolating the position of adefect. Estimates are shown to be subjected to non......-Gaussian,t-distributednoise, and a dedicated multivariate statistical change detection approach isused that detects and isolates faults by detecting simultaneous changes inestimated parameters and ow rates. The properties of the multivariate di-agnosis method are analyzed, and it is shown how detection and false alarmprobabilities...... are assessed and optimized using data-based learning to obtainthresholds for hypothesis testing. Data from a 1400 m horizontal ow loop isused to test the method, and successful diagnosis of the incidents drillstringwashout (pipe leakage), lost circulation, gas in ux, and drill bit plugging aredemonstrated....

  11. A Fast Framework for Abrupt Change Detection Based on Binary Search Trees and Kolmogorov Statistic.

    Science.gov (United States)

    Qi, Jin-Peng; Qi, Jie; Zhang, Qing

    2016-01-01

    Change-Point (CP) detection has attracted considerable attention in the fields of data mining and statistics; it is very meaningful to discuss how to quickly and efficiently detect abrupt change from large-scale bioelectric signals. Currently, most of the existing methods, like Kolmogorov-Smirnov (KS) statistic and so forth, are time-consuming, especially for large-scale datasets. In this paper, we propose a fast framework for abrupt change detection based on binary search trees (BSTs) and a modified KS statistic, named BSTKS (binary search trees and Kolmogorov statistic). In this method, first, two binary search trees, termed as BSTcA and BSTcD, are constructed by multilevel Haar Wavelet Transform (HWT); second, three search criteria are introduced in terms of the statistic and variance fluctuations in the diagnosed time series; last, an optimal search path is detected from the root to leaf nodes of two BSTs. The studies on both the synthetic time series samples and the real electroencephalograph (EEG) recordings indicate that the proposed BSTKS can detect abrupt change more quickly and efficiently than KS, t-statistic (t), and Singular-Spectrum Analyses (SSA) methods, with the shortest computation time, the highest hit rate, the smallest error, and the highest accuracy out of four methods. This study suggests that the proposed BSTKS is very helpful for useful information inspection on all kinds of bioelectric time series signals.

  12. Detectability of changes in cosmic-ray counting rate measured with the Liulin detector

    International Nuclear Information System (INIS)

    Malusek, A.; Kubancak, J.; Ambrozova, I.

    2011-05-01

    Experimental data are needed to improve and validate models predicting the dynamics of solar particle events because the mechanisms of processes leading to the acceleration of solar energetic particles are not yet fully understood. The aim of this work was to examine whether the spectrometer of deposited energy, Liulin, positioned at the Lomnický štít mountain observatory can collect such data. Decision thresholds and detection limits for the increase or decrease in the average number of particles detected by Liulin were determined for a period in February 2011. The changes in counts corresponding to the decision thresholds and detection limits relative to the average number of detected particles were about 17% and 33%, respectively. The Forbush decrease with a maximum change of about 6.8%, which started on February 18, was detectable neither during the 10-minute acquisition time nor during any other, longer period. Statistical analysis showed that an acquisition time about 7 hours would be needed to detect a 5% decrease. As this time was shorter than the duration of the Forbush decrease (about 56 hours), we theorize that the current placement of the Liulin detector inside a living room shielded by a thick concrete ceiling may have had an adverse impact on the detectability of the the cosmic ray counting rate decrease. To test this hypothesis, we recommend positioning the Liulin detector outside the main observatory building.. (author)

  13. Theory, simulation and experimental results of the acoustic detection of magnetization changes in superparamagnetic iron oxide

    Directory of Open Access Journals (Sweden)

    Borgert Jörn

    2011-06-01

    Full Text Available Abstract Background Magnetic Particle Imaging is a novel method for medical imaging. It can be used to measure the local concentration of a tracer material based on iron oxide nanoparticles. While the resulting images show the distribution of the tracer material in phantoms or anatomic structures of subjects under examination, no information about the tissue is being acquired. To expand Magnetic Particle Imaging into the detection of soft tissue properties, a new method is proposed, which detects acoustic emissions caused by magnetization changes in superparamagnetic iron oxide. Methods Starting from an introduction to the theory of acoustically detected Magnetic Particle Imaging, a comparison to magnetically detected Magnetic Particle Imaging is presented. Furthermore, an experimental setup for the detection of acoustic emissions is described, which consists of the necessary field generating components, i.e. coils and permanent magnets, as well as a calibrated microphone to perform the detection. Results The estimated detection limit of acoustic Magnetic Particle Imaging is comparable to the detection limit of magnetic resonance imaging for iron oxide nanoparticles, whereas both are inferior to the theoretical detection limit for magnetically detected Magnetic Particle Imaging. Sufficient data was acquired to perform a comparison to the simulated data. The experimental results are in agreement with the simulations. The remaining differences can be well explained. Conclusions It was possible to demonstrate the detection of acoustic emissions of magnetic tracer materials in Magnetic Particle Imaging. The processing of acoustic emission in addition to the tracer distribution acquired by magnetic detection might allow for the extraction of mechanical tissue parameters. Such parameters, like for example the velocity of sound and the attenuation caused by the tissue, might also be used to support and improve ultrasound imaging. However, the method

  14. A comprehensive change detection method for updating the National Land Cover Database to circa 2011

    Science.gov (United States)

    Jin, Suming; Yang, Limin; Danielson, Patrick; Homer, Collin G.; Fry, Joyce; Xian, George

    2013-01-01

    The importance of characterizing, quantifying, and monitoring land cover, land use, and their changes has been widely recognized by global and environmental change studies. Since the early 1990s, three U.S. National Land Cover Database (NLCD) products (circa 1992, 2001, and 2006) have been released as free downloads for users. The NLCD 2006 also provides land cover change products between 2001 and 2006. To continue providing updated national land cover and change datasets, a new initiative in developing NLCD 2011 is currently underway. We present a new Comprehensive Change Detection Method (CCDM) designed as a key component for the development of NLCD 2011 and the research results from two exemplar studies. The CCDM integrates spectral-based change detection algorithms including a Multi-Index Integrated Change Analysis (MIICA) model and a novel change model called Zone, which extracts change information from two Landsat image pairs. The MIICA model is the core module of the change detection strategy and uses four spectral indices (CV, RCVMAX, dNBR, and dNDVI) to obtain the changes that occurred between two image dates. The CCDM also includes a knowledge-based system, which uses critical information on historical and current land cover conditions and trends and the likelihood of land cover change, to combine the changes from MIICA and Zone. For NLCD 2011, the improved and enhanced change products obtained from the CCDM provide critical information on location, magnitude, and direction of potential change areas and serve as a basis for further characterizing land cover changes for the nation. An accuracy assessment from the two study areas show 100% agreement between CCDM mapped no-change class with reference dataset, and 18% and 82% disagreement for the change class for WRS path/row p22r39 and p33r33, respectively. The strength of the CCDM is that the method is simple, easy to operate, widely applicable, and capable of capturing a variety of natural and

  15. The detection of climate change due to the enhanced greenhouse effect

    Science.gov (United States)

    Schiffer, Robert A.; Unninayar, Sushel

    1991-01-01

    The greenhouse effect is accepted as an undisputed fact from both theoretical and observational considerations. In Earth's atmosphere, the primary greenhouse gas is water vapor. The specific concern today is that increasing concentrations of anthropogenically introduced greenhouse gases will, sooner or later, irreversibly alter the climate of Earth. Detecting climate change has been complicated by uncertainties in historical observations and measurements. Thus, the primary concern for the GEDEX project is how can climate change and enhanced greenhouse effects be unambiguously detected and quantified. Specifically examined are the areas of: Earth surface temperature; the free atmosphere (850 millibars and above); space-based measurements; measurement uncertainties; and modeling the observed temperature record.

  16. The detection of climate change due to the enhanced greenhouse effect

    International Nuclear Information System (INIS)

    Schiffer, R.A.; Unninayar, S.

    1991-01-01

    The greenhouse effect is accepted as an undisputed fact from both theoretical and observational considerations. In Earth's atmosphere, the primary greenhouse gas is water vapor. The specific concern today is that increasing concentrations of anthropogenically introduced greenhouse gases will, sooner or later, irreversibly alter the climate of Earth. Detecting climate change has been complicated by uncertainties in historical observations and measurements. Thus, the primary concern for the GEDEX project is how can climate change and enhanced greenhouse effects be unambiguously detected and quantified. Specifically examined are the areas of: Earth surface temperature; the free atmosphere (850 millibars and above); space-based measurements; measurement uncertainties; and modeling the observed temperature record

  17. Soil Carbon Variability and Change Detection in the Forest Inventory Analysis Database of the United States

    Science.gov (United States)

    Wu, A. M.; Nater, E. A.; Dalzell, B. J.; Perry, C. H.

    2014-12-01

    The USDA Forest Service's Forest Inventory Analysis (FIA) program is a national effort assessing current forest resources to ensure sustainable management practices, to assist planning activities, and to report critical status and trends. For example, estimates of carbon stocks and stock change in FIA are reported as the official United States submission to the United Nations Framework Convention on Climate Change. While the main effort in FIA has been focused on aboveground biomass, soil is a critical component of this system. FIA sampled forest soils in the early 2000s and has remeasurement now underway. However, soil sampling is repeated on a 10-year interval (or longer), and it is uncertain what magnitude of changes in soil organic carbon (SOC) may be detectable with the current sampling protocol. We aim to identify the sensitivity and variability of SOC in the FIA database, and to determine the amount of SOC change that can be detected with the current sampling scheme. For this analysis, we attempt to answer the following questions: 1) What is the sensitivity (power) of SOC data in the current FIA database? 2) How does the minimum detectable change in forest SOC respond to changes in sampling intervals and/or sample point density? Soil samples in the FIA database represent 0-10 cm and 10-20 cm depth increments with a 10-year sampling interval. We are investigating the variability of SOC and its change over time for composite soil data in each FIA region (Pacific Northwest, Interior West, Northern, and Southern). To guide future sampling efforts, we are employing statistical power analysis to examine the minimum detectable change in SOC storage. We are also investigating the sensitivity of SOC storage changes under various scenarios of sample size and/or sample frequency. This research will inform the design of future FIA soil sampling schemes and improve the information available to international policy makers, university and industry partners, and the public.

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

    Science.gov (United States)

    Kumar, Lalit; Ghosh, Manoj Kumer

    2012-01-01

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

  19. Detection and Classification of Changes in Buildings from Airborne Laser Scanning Data

    Directory of Open Access Journals (Sweden)

    Sudan Xu

    2015-12-01

    Full Text Available The difficulty associated with the Lidar data change detection method is lack of data, which is mainly caused by occlusion or pulse absorption by the surface material, e.g., water. To address this challenge, we present a new strategy for detecting buildings that are “changed”, “unchanged”, or “unknown”, and quantifying the changes. The designation “unknown” is applied to locations where, due to lack of data in at least one of the epochs, it is not possible to reliably detect changes in the structure. The process starts with classified data sets in which buildings are extracted. Next, a point-to-plane surface difference map is generated by merging and comparing the two data sets. Context rules are applied to the difference map to distinguish between “changed”, “unchanged”, and “unknown”. Rules are defined to solve problems caused by the lack of data. Further, points labelled as “changed” are re-classified into changes to roofs, walls, dormers, cars, constructions above the roof line, and undefined objects. Next, all the classified changes are organized as changed building objects, and the geometric indices are calculated from their 3D minimum bounding boxes. Performance analysis showed that 80%–90% of real changes are found, of which approximately 50% are considered relevant.

  20. LAND COVER CHANGE DETECTION BASED ON GENETICALLY FEATURE AELECTION AND IMAGE ALGEBRA USING HYPERION HYPERSPECTRAL IMAGERY

    Directory of Open Access Journals (Sweden)

    S. T. Seydi

    2015-12-01

    Full Text Available The Earth has always been under the influence of population growth and human activities. This process causes the changes in land use. Thus, for optimal management of the use of resources, it is necessary to be aware of these changes. Satellite remote sensing has several advantages for monitoring land use/cover resources, especially for large geographic areas. Change detection and attribution of cultivation area over time present additional challenges for correctly analyzing remote sensing imagery. In this regards, for better identifying change in multi temporal images we use hyperspectral images. Hyperspectral images due to high spectral resolution created special placed in many of field. Nevertheless, selecting suitable and adequate features/bands from this data is crucial for any analysis and especially for the change detection algorithms. This research aims to automatically feature selection for detect land use changes are introduced. In this study, the optimal band images using hyperspectral sensor using Hyperion hyperspectral images by using genetic algorithms and Ratio bands, we select the optimal band. In addition, the results reveal the superiority of the implemented method to extract change map with overall accuracy by a margin of nearly 79% using multi temporal hyperspectral imagery.

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

    Science.gov (United States)

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

    2017-09-01

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

  2. A FRAMEWORK OF CHANGE DETECTION BASED ON COMBINED MORPHOLOGICA FEATURES AND MULTI-INDEX CLASSIFICATION

    Directory of Open Access Journals (Sweden)

    S. Li

    2017-09-01

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

  3. Intact memory for implicit contextual information in Korsakoff's amnesia

    NARCIS (Netherlands)

    Oudman, Erik; Van der Stigchel, Stefan; Wester, Arie J.; Kessels, Roy P. C.; Postma, Albert

    Implicit contextual learning is the ability to acquire contextual information from our surroundings without conscious awareness. Such contextual information facilitates the localization of objects in space. In a typical implicit contextual learning paradigm, subjects need to find a target among a

  4. Intact memory for implicit contextual information in Korsakoff's amnesia

    NARCIS (Netherlands)

    Oudman, E.; Stigchel, S. van der; Wester, A.J.; Kessels, R.P.C.; Postma, A.

    2011-01-01

    Implicit contextual learning is the ability to acquire contextual information from our surroundings without conscious awareness. Such contextual information facilitates the localization of objects in space. In a typical implicit contextual learning paradigm, subjects need to find a target among a

  5. Building Change Detection from Bi-Temporal Dense-Matching Point Clouds and Aerial Images.

    Science.gov (United States)

    Pang, Shiyan; Hu, Xiangyun; Cai, Zhongliang; Gong, Jinqi; Zhang, Mi

    2018-03-24

    In this work, a novel building change detection method from bi-temporal dense-matching point clouds and aerial images is proposed to address two major problems, namely, the robust acquisition of the changed objects above ground and the automatic classification of changed objects into buildings or non-buildings. For the acquisition of changed objects above ground, the change detection problem is converted into a binary classification, in which the changed area above ground is regarded as the foreground and the other area as the background. For the gridded points of each period, the graph cuts algorithm is adopted to classify the points into foreground and background, followed by the region-growing algorithm to form candidate changed building objects. A novel structural feature that was extracted from aerial images is constructed to classify the candidate changed building objects into buildings and non-buildings. The changed building objects are further classified as "newly built", "taller", "demolished", and "lower" by combining the classification and the digital surface models of two periods. Finally, three typical areas from a large dataset are used to validate the proposed method. Numerous experiments demonstrate the effectiveness of the proposed algorithm.

  6. Improving the measurement of longitudinal change in renal function: automated detection of changes in laboratory creatinine assay

    Directory of Open Access Journals (Sweden)

    Norman Poh

    2015-04-01

    Full Text Available IntroductionRenal function is reported using the estimates of glomerular filtration rate (eGFR. However, eGFR values are recorded without reference to the particular serum creatinine (SCr assays used to derive them, and newer assays were introduced at different time points across the laboratories in the United Kingdom. These changes may cause systematic bias in eGFR reported in routinely collected data, even though laboratory-reported eGFR values have a correction factor applied.DesignAn algorithm to detect changes in SCr that in turn affect eGFR calculation method was developed. It compares the mapping of SCr values on to eGFR values across a time series of paired eGFR and SCr measurements.SettingRoutinely collected primary care data from 20,000 people with the richest renal function data from the quality improvement in chronic kidney disease trial.ResultsThe algorithm identified a change in eGFR calculation method in 114 (90% of the 127 included practices. This change was identified in 4736 (23.7% patient time series analysed. This change in calibration method was found to cause a significant step change in the reported eGFR values, producing a systematic bias. The eGFR values could not be recalibrated by applying the Modification of Diet in Renal Disease equation to the laboratory reported SCr values.ConclusionsThis algorithm can identify laboratory changes in eGFR calculation methods and changes in SCr assay. Failure to account for these changes may misconstrue renal function changes over time. Researchers using routine eGFR data should account for these effects.  

  7. Normalizing Landsat and ASTER Data Using MODIS Data Products for Forest Change Detection

    Science.gov (United States)

    Gao, Feng; Masek, Jeffrey G.; Wolfe, Robert E.; Tan, Bin

    2010-01-01

    Monitoring forest cover and its changes are a major application for optical remote sensing. In this paper, we present an approach to integrate Landsat, ASTER and MODIS data for forest change detection. Moderate resolution (10-100m) images (e.g. Landsat and ASTER) acquired from different seasons and times are normalized to one "standard" date using MODIS data products as reference. The normalized data are then used to compute forest disturbance index for forest change detection. Comparing to the results from original data, forest disturbance index from the normalized images is more consistent spatially and temporally. This work demonstrates an effective approach for mapping forest change over a large area from multiple moderate resolution sensors on various acquisition dates.

  8. 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

  9. Change detection on LOD 2 building models with very high resolution spaceborne stereo imagery

    Science.gov (United States)

    Qin, Rongjun

    2014-10-01

    Due to the fast development of the urban environment, the need for efficient maintenance and updating of 3D building models is ever increasing. Change detection is an essential step to spot the changed area for data (map/3D models) updating and urban monitoring. Traditional methods based on 2D images are no longer suitable for change detection in building scale, owing to the increased spectral variability of the building roofs and larger perspective distortion of the very high resolution (VHR) imagery. Change detection in 3D is increasingly being investigated using airborne laser scanning data or matched Digital Surface Models (DSM), but rare study has been conducted regarding to change detection on 3D city models with VHR images, which is more informative but meanwhile more complicated. This is due to the fact that the 3D models are abstracted geometric representation of the urban reality, while the VHR images record everything. In this paper, a novel method is proposed to detect changes directly on LOD (Level of Detail) 2 building models with VHR spaceborne stereo images from a different date, with particular focus on addressing the special characteristics of the 3D models. In the first step, the 3D building models are projected onto a raster grid, encoded with building object, terrain object, and planar faces. The DSM is extracted from the stereo imagery by hierarchical semi-global matching (SGM). In the second step, a multi-channel change indicator is extracted between the 3D models and stereo images, considering the inherent geometric consistency (IGC), height difference, and texture similarity for each planar face. Each channel of the indicator is then clustered with the Self-organizing Map (SOM), with "change", "non-change" and "uncertain change" status labeled through a voting strategy. The "uncertain changes" are then determined with a Markov Random Field (MRF) analysis considering the geometric relationship between faces. In the third step, buildings are

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

    Directory of Open Access Journals (Sweden)

    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.

  11. Shoreline change detection from Karwar to Gokarna - South West coast of India using remotely Sensed data

    Digital Repository Service at National Institute of Oceanography (India)

    Choudhary, R.; Gowthaman, R.; SanilKumar, V.

    -494 #02060313 Copyright ©2013 CAFET-INNOVA TECHNICAL SOCIETY. All rights reserved. Shoreline change detection from Karwar to Gokarna - South West coast of India using remotely Sensed data RICHA CHOUDHARY 1 , R. GOWTHAMAN 2 AND V. SANIL KUMAR 2 1... years period. Gangavali river mouth has narrowed due to siltation. Significant changes in the geomorphic features like spit growth, braided island, creeks, tidal flat are observed near Kali and Gangavali river mouth. Keywords: Remote sensing...

  12. Statistical Change Detection for Diagnosis of Buoyancy Element Defects on Moored Floating Vessels

    DEFF Research Database (Denmark)

    Blanke, Mogens; Fang, Shaoji; Galeazzi, Roberto

    2012-01-01

    . After residual generation, statistical change detection scheme is derived from mathematical models supported by experimental data. To experimentally verify loss of an underwater buoyancy element, an underwater line breaker is designed to create realistic replication of abrupt faults. The paper analyses...... the properties of residuals and suggests a dedicated GLRT change detector based on a vector residual. Special attention is paid to threshold selection for non ideal (non-IID) test statistics....

  13. Detection of anthropogenic climate change in satellite records of ocean chlorophyll and productivity

    Directory of Open Access Journals (Sweden)

    S. A. Henson

    2010-02-01

    Full Text Available Global climate change is predicted to alter the ocean's biological productivity. But how will we recognise the impacts of climate change on ocean productivity? The most comprehensive information available on its global distribution comes from satellite ocean colour data. Now that over ten years of satellite-derived chlorophyll and productivity data have accumulated, can we begin to detect and attribute climate change-driven trends in productivity? Here we compare recent trends in satellite ocean colour data to longer-term time series from three biogeochemical models (GFDL, IPSL and NCAR. We find that detection of climate change-driven trends in the satellite data is confounded by the relatively short time series and large interannual and decadal variability in productivity. Thus, recent observed changes in chlorophyll, primary production and the size of the oligotrophic gyres cannot be unequivocally attributed to the impact of global climate change. Instead, our analyses suggest that a time series of ~40 years length is needed to distinguish a global warming trend from natural variability. In some regions, notably equatorial regions, detection times are predicted to be shorter (~20–30 years. Analysis of modelled chlorophyll and primary production from 2001–2100 suggests that, on average, the climate change-driven trend will not be unambiguously separable from decadal variability until ~2055. Because the magnitude of natural variability in chlorophyll and primary production is larger than, or similar to, the global warming trend, a consistent, decades-long data record must be established if the impact of climate change on ocean productivity is to be definitively detected.

  14. Using the Virtual Reality-Cognitive Rehabilitation Approach to Improve Contextual Processing in Children with Autism

    Directory of Open Access Journals (Sweden)

    Michelle Wang

    2013-01-01

    Full Text Available Background. This pilot study investigated the efficacy of a novel virtual reality-cognitive rehabilitation (VR-CR intervention to improve contextual processing of objects in children with autism. Previous research supports that children with autism show deficits in contextual processing, as well as deficits in its elementary components: abstraction and cognitive flexibility. Methods. Four children with autism participated in a multiple-baseline, single-subject study. The children were taught how to see objects in context by reinforcing attention to pivotal contextual information. Results. All children demonstrated statistically significant improvements in contextual processing and cognitive flexibility. Mixed results were found on the control test and changes in context-related behaviours. Conclusions. Larger-scale studies are warranted to determine the effectiveness and usability in comprehensive educational programs.

  15. Using the Virtual Reality-Cognitive Rehabilitation Approach to Improve Contextual Processing in Children with Autism

    Science.gov (United States)

    Reid, Denise

    2013-01-01

    Background. This pilot study investigated the efficacy of a novel virtual reality-cognitive rehabilitation (VR-CR) intervention to improve contextual processing of objects in children with autism. Previous research supports that children with autism show deficits in contextual processing, as well as deficits in its elementary components: abstraction and cognitive flexibility. Methods. Four children with autism participated in a multiple-baseline, single-subject study. The children were taught how to see objects in context by reinforcing attention to pivotal contextual information. Results. All children demonstrated statistically significant improvements in contextual processing and cognitive flexibility. Mixed results were found on the control test and changes in context-related behaviours. Conclusions. Larger-scale studies are warranted to determine the effectiveness and usability in comprehensive educational programs. PMID:24324379

  16. Change Detection in Full and Dual Polarization, Single- and Multifrequency SAR Data

    DEFF Research Database (Denmark)

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

    2015-01-01

    of obtaining a smaller value of the test statistic are given. In a case study, airborne EMISAR C- and L-band SAR images from the spring of 1998 covering agricultural fields and wooded areas near Foulum, Denmark, are used in single- and bifrequency, bitemporal change detection with full and dual polarimetry...

  17. Change detection in quad and dual pol, single- and bi-frequency SAR data

    DEFF Research Database (Denmark)

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

    2015-01-01

    -value are given. In a case study airborne EMISAR C- and L-band SAR images covering agricultural fields and wooded areas near Foulum, Denmark, are used in single- and bi-frequency, bi-temporal change detection with full and dual polarimetry data. © (2015) COPYRIGHT Society of Photo-Optical Instrumentation...

  18. Visual working memory and threat monitoring: Spider fearfuls show disorder-specific change detection

    NARCIS (Netherlands)

    Reinecke, A.; Becker, E.S.; Rinck, M.

    2010-01-01

    Previous studies of biased information processing in anxiety addressed biases of attention and memory, but little is known about the processes taking place between them: visual working memory (VWM) and monitoring of threat. We investigated these processes with a change detection paradigm. In

  19. A novel Spatio-temporal change detection approach using hyper-temporal satellite data

    CSIR Research Space (South Africa)

    Kleynhans, W

    2014-07-01

    Full Text Available The use of hyper-temporal MODIS time-series data for the detection of land cover change in South Africa has been an active research area the last few year. This paper expands on previous studies that show that this type of data can be effectively...

  20. Simulation of TanDEM-X interferograms for urban change detection

    Science.gov (United States)

    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.

  1. Gender differences in pre-attentive change detection for visual but not auditory stimuli.

    Science.gov (United States)

    Yang, Xiuxian; Yu, Yunmiao; Chen, Lu; Sun, Hailian; Qiao, Zhengxue; Qiu, Xiaohui; Zhang, Congpei; Wang, Lin; Zhu, Xiongzhao; He, Jincai; Zhao, Lun; Yang, Yanjie

    2016-01-01

    Despite ongoing debate about gender differences in pre-attention processes, little is known about gender effects on change detection for auditory and visual stimuli. We explored gender differences in change detection while processing duration information in auditory and visual modalities. We investigated pre-attentive processing of duration information using a deviant-standard reverse oddball paradigm (50 ms/150 ms) for auditory and visual mismatch negativity (aMMN and vMMN) in males and females (n=21/group). In the auditory modality, decrement and increment aMMN were observed at 150-250 ms after the stimulus onset, and there was no significant gender effect on MMN amplitudes in temporal or fronto-central areas. In contrast, in the visual modality, only increment vMMN was observed at 180-260 ms after the onset of stimulus, and it was higher in males than in females. No gender effect was found in change detection for auditory stimuli, but change detection was facilitated for visual stimuli in males. Gender effects should be considered in clinical studies of pre-attention for visual stimuli. Copyright © 2015 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

  2. Corine land cover change detection in Europe (case studies of the Netherlands and Slovakia)

    NARCIS (Netherlands)

    Feranec, J.; Hazeu, G.W.; Christensen, S.; Jaffrain, G.

    2007-01-01

    We present a land cover change detection methodology in the framework of the IMAGE and CORINE Land Cover 2000 (I&CLC2000) project managed jointly by the European Environment Agency in Copenhagen, Denmark and the Joint Research Centre of the European Commission in Ispra, Italy. The generated data

  3. AN APPROACH TO ALLEVIATE THE FALSE ALARM IN BUILDING CHANGE DETECTION FROM URBAN VHR IMAGE

    Directory of Open Access Journals (Sweden)

    J. Chen

    2016-06-01

    Full Text Available Building change detection from very-high-resolution (VHR urban remote sensing image frequently encounter the challenge of serious false alarm caused by different illumination or viewing angles in bi-temporal images. An approach to alleviate the false alarm in urban building change detection is proposed in this paper. Firstly, as shadows casted by urban buildings are of distinct spectral and shape feature, it adopts a supervised object-based classification technique to extract them in this paper. Secondly, on the opposite direction of sunlight illumination, a straight line is drawn along the principal orientation of building in every extracted shadow region. Starting from the straight line and moving toward the sunlight direction, a rectangular area is constructed to cover partial shadow and rooftop of each building. Thirdly, an algebra and geometry invariant based method is used to abstract the spatial topological relationship of the potential unchanged buildings from all central points of the rectangular area. Finally, based on an oriented texture curvature descriptor, an index is established to determine the actual false alarm in building change detection result. The experiment results validate that the proposed method can be used as an effective framework to alleviate the false alarm in building change detection from urban VHR image.

  4. An electronic apparatus for early detection of changes in red cell ...

    African Journals Online (AJOL)

    An electronic apparatus was developed for anaesthetists to use to detect changes in red cell concentration during surgery. The mechanism is based on the relationship between the red cell content and the electrical conductivity of blood. In a pilot study of 170 blood samples, a correlation coefficient of 0,9806 was obtained ...

  5. An electronic apparatus for early detection of changes in red cell ...

    African Journals Online (AJOL)

    1989-08-19

    Aug 19, 1989 ... An electronic apparatus was developed for anaesthetists to use to detect changes in red cell concentration during sur- gery. The mechanism is based on the relationship between the red cell content and the electrical conductivity of blood. In a pilot study of 170 blood samples, a correlation coefficient.

  6. Change detection in polarimetric SAR data and the complex Wishart distribution

    DEFF Research Database (Denmark)

    Conradsen, Knut; Nielsen, Allan Aasbjerg; Schou, Jesper

    2001-01-01

    . Based on this distribution a test statistic for equality of two such matrices and an associated asymptotic probability for obtaining a smaller value of the test statistic are given and applied to change detection in polarimetric SAR data. In a case study EMISAR L-band data from 17 April 1998 and 20 May...

  7. An Approach for Unsupervised Change Detection in Multitemporal VHR Images Acquired by Different Multispectral Sensors

    Directory of Open Access Journals (Sweden)

    Yady Tatiana Solano-Correa

    2018-03-01

    Full Text Available This paper proposes an approach for the detection of changes in multitemporal Very High Resolution (VHR optical images acquired by different multispectral sensors. The proposed approach, which is inspired by a recent framework developed to support the design of change-detection systems for single-sensor VHR remote sensing images, addresses and integrates in the general approach a strategy to effectively deal with multisensor information, i.e., to perform change detection between VHR images acquired by different multispectral sensors on two dates. This is achieved by the definition of procedures for the homogenization of radiometric, spectral and geometric image properties. These procedures map images into a common feature space where the information acquired by different multispectral sensors becomes comparable across time. Although the approach is general, here we optimize it for the detection of changes in vegetation and urban areas by employing features based on linear transformations (Tasseled Caps and Orthogonal Equations, which are shown to be effective for representing the multisensor information in a homogeneous physical way irrespectively of the considered sensor. Experiments on multitemporal images acquired by different VHR satellite systems (i.e., QuickBird, WorldView-2 and GeoEye-1 confirm the effectiveness of the proposed approach.

  8. Hierarchical 2.5D scene alignment for change detection with large viewpoint differences

    NARCIS (Netherlands)

    van de Wouw, D.; Dubbelman, G.; de With, P.H.N.

    2016-01-01

    Change detection from mobile platforms is a relevant topic in the field of intelligent vehicles and has many applications, such as countering improvised explosive devices (C-IED). Existing real-time C-IED systems are not robust against large viewpoint differences, which are unavoidable under

  9. How to measure working memory capacity in the change detection paradigm

    NARCIS (Netherlands)

    Rouder, Jeffrey N.; Morey, Richard D.; Morey, Candice C.; Cowan, Nelson

    Although the measurement of working memory capacity is crucial to understanding working memory and its interaction with other cognitive faculties, there are inconsistencies in the literature on how to measure capacity. We address the measurement in the change detection paradigm, popularized by Luck

  10. 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.

  11. A spatio-temporal autocorrelation change detection approach using hyper-temporal satellite data

    CSIR Research Space (South Africa)

    Kleynhans, W

    2013-07-01

    Full Text Available -1 IEEE International Geoscience and Remote Sensing Symposium, Melbourne, Australia 21-26 July 2013 A SPATIO-TEMPORAL AUTOCORRELATION CHANGE DETECTION APPROACH USING HYPER-TEMPORAL SATELLITE DATA yzW. Kleynhans, yz,B.P Salmon,zK. J. Wessels...

  12. Invasive species change detection using artificial neural networks and CASI hyperspectral imagery

    Science.gov (United States)

    For monitoring and controlling the extent and intensity of an invasive species, a direct multi-date image classification method was applied in invasive species (saltcedar) change detection in the study area of Lovelock, Nevada. With multi-date Compact Airborne Spectrographic Imager (CASI) hyperspec...

  13. Satellite detection of land-use change and effects on regional forest aboveground biomass estimates

    Science.gov (United States)

    Daolan Zheng; Linda S. Heath; Mark J. Ducey

    2008-01-01

    We used remote-sensing-driven models to detect land-cover change effects on forest aboveground biomass (AGB) density (Mg·ha−1, dry weight) and total AGB (Tg) in Minnesota, Wisconsin, and Michigan USA, between the years 1992-2001, and conducted an evaluation of the approach. Inputs included remotely-sensed 1992 reflectance data...

  14. Detecting changes in the nutritional value and elemental composition of transgenic sorghum grain

    CSIR Research Space (South Africa)

    Ndimba, R

    2015-09-01

    Full Text Available Instruments and Methods in Physics Research B 363 (2015) 183–187 Detecting changes in the nutritional value and elemental composition of transgenic sorghum grain R. Ndimba a,c,, A.W. Grootboom b, L. Mehlo b, N.L. Mkhonza b, J. Kossmann c, A...

  15. Change detection of bare areas in the Xolobeni region, South Africa ...

    African Journals Online (AJOL)

    Rebekah

    study used remote sensing as a tool to provide some information on the ... seasonal crop lands have been severely degraded by water and wind .... the accuracy of classified data was critical to the quality of the post .... Agone, V & Bhamare, SM 2012, ' Change detection of vegetation cover using remote sensing and GIS',.

  16. Investigation of Raman chemical imaging for detection of Lycopene changes in tomatoes during postharvest ripening

    Science.gov (United States)

    Lycopene is a major carotenoid in tomatoes and detecting changes in lycopene content can be used to monitor the ripening of tomatoes. Raman chemical imaging is a new technique that shows promise for mapping constituents of interest in complex food matrices. In this study, a benchtop point-scanning...

  17. Combining voxel-based morphometry and diffusion tensor imaging to detect age-related brain changes.

    Science.gov (United States)

    Lehmbeck, Jan T; Brassen, Stefanie; Weber-Fahr, Wolfgang; Braus, Dieter F

    2006-04-03

    The present study combined optimized voxel-based morphometry and diffusion tensor imaging to detect age-related brain changes. We compared grey matter density maps (grey matter voxel-based morphometry) and white matter fractional anisotropy maps (diffusion tensor imaging-voxel-based morphometry) between two groups of 17 younger and 17 older women. Older women exhibited reduced white matter fractional anisotropy as well as decreased grey matter density most prominently in the frontal, limbic, parietal and temporal lobes. A discriminant analysis identified four frontal and limbic grey and white matter areas that separated the two groups most effectively. We conclude that grey matter voxel-based morphometry and diffusion tensor imaging voxel-based morphometry are well suited for the detection of age-related changes and their combination provides high accuracy when detecting the neural correlates of aging.

  18. 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.

  19. Detecting dynamical changes in time series by using the Jensen Shannon divergence

    Science.gov (United States)

    Mateos, D. M.; Riveaud, L. E.; Lamberti, P. W.

    2017-08-01

    Most of the time series in nature are a mixture of signals with deterministic and random dynamics. Thus the distinction between these two characteristics becomes important. Distinguishing between chaotic and aleatory signals is difficult because they have a common wide band power spectrum, a delta like autocorrelation function, and share other features as well. In general, signals are presented as continuous records and require to be discretized for being analyzed. In this work, we introduce different schemes for discretizing and for detecting dynamical changes in time series. One of the main motivations is to detect transitions between the chaotic and random regime. The tools here used here originate from the Information Theory. The schemes proposed are applied to simulated and real life signals, showing in all cases a high proficiency for detecting changes in the dynamics of the associated time series.

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

    Science.gov (United States)

    Mainali, Shraddha; Wahba, Mervat; Elijovich, Lucas

    2014-01-01

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

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

    Science.gov (United States)

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

    2015-01-01

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

  2. Structural Damage Detection Using Changes in Natural Frequencies: Theory and Applications

    Science.gov (United States)

    He, K.; Zhu, W. D.

    2011-07-01

    A vibration-based method that uses changes in natural frequencies of a structure to detect damage has advantages over conventional nondestructive tests in detecting various types of damage, including loosening of bolted joints, using minimum measurement data. Two major challenges associated with applications of the vibration-based damage detection method to engineering structures are addressed: accurate modeling of structures and the development of a robust inverse algorithm to detect damage, which are defined as the forward and inverse problems, respectively. To resolve the forward problem, new physics-based finite element modeling techniques are developed for fillets in thin-walled beams and for bolted joints, so that complex structures can be accurately modeled with a reasonable model size. To resolve the inverse problem, a logistical function transformation is introduced to convert the constrained optimization problem to an unconstrained one, and a robust iterative algorithm using a trust-region method, called the Levenberg-Marquardt method, is developed to accurately detect the locations and extent of damage. The new methodology can ensure global convergence of the iterative algorithm in solving under-determined system equations and deal with damage detection problems with relatively large modeling error and measurement noise. The vibration-based damage detection method is applied to various structures including lightning masts, a space frame structure and one of its components, and a pipeline. The exact locations and extent of damage can be detected in the numerical simulation where there is no modeling error and measurement noise. The locations and extent of damage can be successfully detected in experimental damage detection.

  3. Structural Damage Detection Using Changes in Natural Frequencies: Theory and Applications

    International Nuclear Information System (INIS)

    He, K; Zhu, W D

    2011-01-01

    A vibration-based method that uses changes in natural frequencies of a structure to detect damage has advantages over conventional nondestructive tests in detecting various types of damage, including loosening of bolted joints, using minimum measurement data. Two major challenges associated with applications of the vibration-based damage detection method to engineering structures are addressed: accurate modeling of structures and the development of a robust inverse algorithm to detect damage, which are defined as the forward and inverse problems, respectively. To resolve the forward problem, new physics-based finite element modeling techniques are developed for fillets in thin-walled beams and for bolted joints, so that complex structures can be accurately modeled with a reasonable model size. To resolve the inverse problem, a logistical function transformation is introduced to convert the constrained optimization problem to an unconstrained one, and a robust iterative algorithm using a trust-region method, called the Levenberg-Marquardt method, is developed to accurately detect the locations and extent of damage. The new methodology can ensure global convergence of the iterative algorithm in solving under-determined system equations and deal with damage detection problems with relatively large modeling error and measurement noise. The vibration-based damage detection method is applied to various structures including lightning masts, a space frame structure and one of its components, and a pipeline. The exact locations and extent of damage can be detected in the numerical simulation where there is no modeling error and measurement noise. The locations and extent of damage can be successfully detected in experimental damage detection.

  4. Taking in account of contextual parameters in post accidental radioecology

    International Nuclear Information System (INIS)

    Renaud, Ph.; Maubert, H.; Bernie, J.C.

    1997-01-01

    The consequences on agricultural or breeding products of a radioactive accidental release are strongly linked to the context in which radioactive deposits occur: for example conditions of deposition in relation with agricultural and feeding schedules. These contextual parameters lead to a variation of results given by models greater than transfer factors uncertainties. For example, cow milk contamination stretches on several decades during the months following deposit as a function of feeding practices. In the same way, if a wheat plant receives the deposit during grain development, harvested grains will have a contamination level 10 3 to 10 4 times higher that if deposition occurs before the growing stage. To create a decision support system like the ASTRAL software, the need to realize a modelling of these contextual parameters has been encountered. Moreover, to help experts for evaluations, default informations relative to agricultural and breeding practices for France are given through databases. However, in case of a real accident, it would be important to re-initialize these contextual parameters which change from year to year, in order to obtain more precise assessments. (authors)

  5. Climatic change in French Polynesia: detection of observed changes and projections evaluation

    International Nuclear Information System (INIS)

    Hopuare, Marania

    2014-01-01

    The effects of climate change on Pacific islands is a major concern for the local populations. The rainfall parameter, specifically, appears as one of the sensitive parameters, as it determines water resources. The goal of this thesis is to bring a first insight into the 21. century evolution of precipitation in Tahiti. The first step was to characterize rainfall in Tahiti using data records from the observation network of Meteo France. The 'rainfall season', lasting from November to April, is the season of interest, as rainfall amounts are the highest at this time of the year. Indeed, the South Pacific Convergence Zone (SPCZ), host of deep convection, remains the principal source of rainfall in Tahiti in austral summer (December-January-February). On inter-annual and inter-decadal timescales, the El nino Southern Oscillation (ENSO) and the Inter-decadal Pacific Oscillation (IPO) imply north/south and east/west migrations of the SPCZ, drawing it away, or closer to Tahiti. The positive phase of the IPO involves a north-eastward displacement of the SPCZ, which causes higher rainfall amounts in Tahiti. The SPCZ is displaced towards the southwest during negative IPO phase, leading to a decrease of rainfall in Tahiti. The study reveals that the IPO positive phase favor the occurrence of intense El nino events. In those cases, the SPCZ is critically displaced to the northeast and lies zonally just south of the equator. Accordingly, the SPCZ is drawn away from Tahiti and alters the southeast flow of trade winds. As a result, substantial orographic precipitation affect the southeast coasts of Tahiti. Following the assessment of observed precipitation for the period 1961-2011, an original method has been set up to obtain a model able to resolve the island and capture the orographic effects at best. Two successive down-scaling steps have been necessary to get the limited area model ALADINClimat over Tahiti (at the resolution of 12 km), starting from the global coupled model

  6. A travel time forecasting model based on change-point detection method

    Science.gov (United States)

    LI, Shupeng; GUANG, Xiaoping; QIAN, Yongsheng; ZENG, Junwei

    2017-06-01

    Travel time parameters obtained from road traffic sensors data play an important role in traffic management practice. A travel time forecasting model is proposed for urban road traffic sensors data based on the method of change-point detection in this paper. The first-order differential operation is used for preprocessing over the actual loop data; a change-point detection algorithm is designed to classify the sequence of large number of travel time data items into several patterns; then a travel time forecasting model is established based on autoregressive integrated moving average (ARIMA) model. By computer simulation, different control parameters are chosen for adaptive change point search for travel time series, which is divided into several sections of similar state.Then linear weight function is used to fit travel time sequence and to forecast travel time. The results show that the model has high accuracy in travel time forecasting.

  7. A quality control method for detecting energy changes of medical accelerators

    International Nuclear Information System (INIS)

    McGinley, P.H.

    2000-01-01

    A description is presented of a simple and sensitive method for detecting a change in the energy of the electrons bombarding the target of medical accelerators. This technique is useful for x-ray beams with end point energy in the range of 15.7 to 25 MeV. The method is based on the photoactivation of 16 O and 14 N in a small sample of ammonium nitrate. It was found that the ratio of the activity induced in the oxygen divided by that produced in the nitrogen can be used as a quality control technique to detect a change in the energy of the electrons that bombard the target of the accelerator. An electron energy change of the order of 0.2 MeV can be determined using this method. (author)

  8. Automatic registration of remote sensing images based on SIFT and fuzzy block matching for change detection

    Directory of Open Access Journals (Sweden)

    Cai Guo-Rong

    2011-10-01

    Full Text Available This paper presents an automated image registration approach to detecting changes in multi-temporal remote sensing images. The proposed algorithm is based on the scale invariant feature transform (SIFT and has two phases. The first phase focuses on SIFT feature extraction and on estimation of image transformation. In the second phase, Structured Local Binary Haar Pattern (SLBHP combined with a fuzzy similarity measure is then used to build a new and effective block similarity measure for change detection. Experimental results obtained on multi-temporal data sets show that compared with three mainstream block matching algorithms, the proposed algorithm is more effective in dealing with scale, rotation and illumination changes.

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

    Directory of Open Access Journals (Sweden)

    Tim J Smith

    2015-02-01

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

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

    Science.gov (United States)

    Smith, Tim J

    2015-01-01

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

  11. Contextual control of discriminated operant behavior.

    Science.gov (United States)

    Bouton, Mark E; Todd, Travis P; León, Samuel P

    2014-01-01

    Previous research has suggested that changing the context after instrumental (operant) conditioning can weaken the strength of the operant response. That result contrasts with the results of studies of Pavlovian conditioning, in which a context switch often does not affect the response elicited by a conditioned stimulus. To begin to make the methods more similar, Experiments 1-3 tested the effects of a context switch in rats on a discriminated operant response (R; lever pressing or chain pulling) that had been reinforced only in the presence of a 30-s discriminative stimulus (S; tone or light). As in Pavlovian conditioning, responses and reinforcers became confined to presentations of the S during training. However, in Experiment 1, after training in Context A, a switch to Context B caused a decrement in responding during S. In Experiment 2, a switch to Context B likewise decreased responding in S when Context B was equally familiar, equally associated with reinforcement, or equally associated with the training of a discriminated operant (a different R reinforced in a different S). However, there was no decrement if Context B had been associated with the same response that was trained in Context A (Experiments 2 and 3). The effectiveness of S transferred across contexts, whereas the strength of the response did not. Experiment 4 found that a continuously reinforced response was also disrupted by context change when the same response manipulandum was used in both training and testing. Overall, the results suggest that the context can have a robust general role in the control of operant behavior. Mechanisms of contextual control are discussed.

  12. On multi-fingerprint detection and attribution of greenhouse gas- and aerosol forced climate change

    Energy Technology Data Exchange (ETDEWEB)

    Hegerl, G C [Max-Planck-Institut fuer Meteorologie, Hamburg (Germany); Hasselmann, K [Max-Planck-Institut fuer Meteorologie, Hamburg (Germany); Cubasch, U [Deutsches Klimarechenzentrum (DKRZ), Hamburg (Germany); Mitchell, J F.B. [Hadley Centre for Climate Prediction and Research, Bracknell (United Kingdom). Meteorological Office; Roeckner, E [Max-Planck-Institut fuer Meteorologie, Hamburg (Germany); Voss, R [Deutsches Klimarechenzentrum (DKRZ), Hamburg (Germany); Waszkewitz, J [Deutsches Klimarechenzentrum (DKRZ), Hamburg (Germany)

    1996-07-01

    A multi-fingerprint analysis is applied to the detection and attribution of anthropogenic climate change. While a single fingerprint, as applied in a previous paper by Hegerl et al. (1996), is optimal for detecting a significant climate change, the simultaneous use of several fingerprints allows one to investigate additionally the consistency between observations and model predicted climate change signals for competing candidate forcing mechanisms. Thus the multi-fingerprint method is a particularly useful technique for attributing an observed climate change to a proposed cause. Different model-predicted climate change signals are derived from three global warming simulations for the period 1880 to 2049. In one simulation, the forcing was by greenhouse gases only, while in the remaining two simulations the influence of aerosols was also included. The two dominant climate change signals derived from these simulations are optimized statistically by weighting the model-predicted climate change pattern towards low-noise directions. These optimized fingerprints are then applied to observed near surface temperature trends. The space-time structure of natural climate variability (needed to determine the signal-to-noise ratio) is estimated from several multi-century control simulations with different CGCMs and from instrumental data over the last 134 years. (orig.)

  13. Detecting Changes in Forest Structure over Time with Bi-Temporal Terrestrial Laser Scanning Data

    Directory of Open Access Journals (Sweden)

    Timo Melkas

    2012-10-01

    Full Text Available Changes to stems caused by natural forces and timber harvesting constitute an essential input for many forestry-related applications and ecological studies, especially forestry inventories based on the use of permanent sample plots. Conventional field measurement is widely acknowledged as being time-consuming and labor-intensive. More automated and efficient alternatives or supportive methods are needed. Terrestrial laser scanning (TLS has been demonstrated to be a promising method in forestry field inventories. Nevertheless, the applicability of TLS in recording changes in the structure of forest plots has not been studied in detail. This paper presents a fully automated method for detecting changes in forest structure over time using bi-temporal TLS data. The developed method was tested on five densely populated forest plots including 137 trees and 50 harvested trees in point clouds. The present study demonstrated that 90 percent of tree stem changes could be automatically located from single-scan TLS data. These changes accounted for 92 percent of the changed basal area. The results indicate that the processing of TLS data collected at different times to detect tree stem changes can be fully automated.

  14. Data Fusion and Fuzzy Clustering on Ratio Images for Change Detection in Synthetic Aperture Radar Images

    Directory of Open Access Journals (Sweden)

    Wenping Ma

    2014-01-01

    Full Text Available The unsupervised approach to change detection via synthetic aperture radar (SAR images becomes more and more popular. The three-step procedure is the most widely used procedure, but it does not work well with the Yellow River Estuary dataset obtained by two synthetic aperture radars. The difference of the two radars in imaging techniques causes severe noise, which seriously affects the difference images generated by a single change detector in step two, producing the difference image. To deal with problem, we propose a change detector to fuse the log-ratio (LR and the mean-ratio (MR images by a context independent variable behavior (CIVB operator and can utilize the complement information in two ratio images. In order to validate the effectiveness of the proposed change detector, the change detector will be compared with three other change detectors, namely, the log-ratio (LR, mean-ratio (MR, and the wavelet-fusion (WR operator, to deal with three datasets with different characteristics. The four operators are applied not only in a widely used three-step procedure but also in a new approach. The experiments show that the false alarms and overall errors of change detection are greatly reduced, and the kappa and KCC are improved a lot. And its superiority can also be observed visually.

  15. Trend analysis and change point detection of annual and seasonal temperature series in Peninsular Malaysia

    Science.gov (United States)

    Suhaila, Jamaludin; Yusop, Zulkifli

    2017-06-01

    Most of the trend analysis that has been conducted has not considered the existence of a change point in the time series analysis. If these occurred, then the trend analysis will not be able to detect an obvious increasing or decreasing trend over certain parts of the time series. Furthermore, the lack of discussion on the possible factors that influenced either the decreasing or the increasing trend in the series needs to be addressed in any trend analysis. Hence, this study proposes to investigate the trends, and change point detection of mean, maximum and minimum temperature series, both annually and seasonally in Peninsular Malaysia and determine the possible factors that could contribute to the significance trends. In this study, Pettitt and sequential Mann-Kendall (SQ-MK) tests were used to examine the occurrence of any abrupt climate changes in the independent series. The analyses of the abrupt changes in temperature series suggested that most of the change points in Peninsular Malaysia were detected during the years 1996, 1997 and 1998. These detection points captured by Pettitt and SQ-MK tests are possibly related to climatic factors, such as El Niño and La Niña events. The findings also showed that the majority of the significant change points that exist in the series are related to the significant trend of the stations. Significant increasing trends of annual and seasonal mean, maximum and minimum temperatures in Peninsular Malaysia were found with a range of 2-5 °C/100 years during the last 32 years. It was observed that the magnitudes of the increasing trend in minimum temperatures were larger than the maximum temperatures for most of the studied stations, particularly at the urban stations. These increases are suspected to be linked with the effect of urban heat island other than El Niño event.

  16. The Decay of Motor Memories Is Independent of Context Change Detection.

    Directory of Open Access Journals (Sweden)

    Andrew E Brennan

    2015-06-01

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

  17. The Decay of Motor Memories Is Independent of Context Change Detection

    Science.gov (United States)

    Brennan, Andrew E.; Smith, Maurice A.

    2015-01-01

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

  18. Physics-Based Predictions for Coherent Change Detection Using X-Band Synthetic Aperture Radar

    Directory of Open Access Journals (Sweden)

    Mark Preiss

    2005-12-01

    Full Text Available A theoretical model is developed to describe the interferometric coherency between pairs of SAR images of rough soil surfaces. The model is derived using a dyadic form for surface reflectivity in the Kirchhoff approximation. This permits the combination of Kirchhoff theory and spotlight synthetic aperture radar (SAR image formation theory. The resulting model is used to describe the interferometric coherency between pairs of SAR images of rough soil surfaces. The theoretical model is applied to SAR images formed before and after surface changes observed by a repeat-pass SAR system. The change in surface associated with a tyre track following vehicle passage is modelled and SAR coherency estimates are obtained. Predicted coherency distributions for both the change and no-change scenarios are used to estimate receiver operator curves for the detection of the changes using a high-resolution, X-band SAR system.

  19. Automatic Threshold Determination for a Local Approach of Change Detection in Long-Term Signal Recordings

    Directory of Open Access Journals (Sweden)

    David Hewson

    2007-01-01

    Full Text Available CUSUM (cumulative sum is a well-known method that can be used to detect changes in a signal when the parameters of this signal are known. This paper presents an adaptation of the CUSUM-based change detection algorithms to long-term signal recordings where the various hypotheses contained in the signal are unknown. The starting point of the work was the dynamic cumulative sum (DCS algorithm, previously developed for application to long-term electromyography (EMG recordings. DCS has been improved in two ways. The first was a new procedure to estimate the distribution parameters to ensure the respect of the detectability property. The second was the definition of two separate, automatically determined thresholds. One of them (lower threshold acted to stop the estimation process, the other one (upper threshold was applied to the detection function. The automatic determination of the thresholds was based on the Kullback-Leibler distance which gives information about the distance between the detected segments (events. Tests on simulated data demonstrated the efficiency of these improvements of the DCS algorithm.

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

    Science.gov (United States)

    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.