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Sample records for change detection based

  1. Scene change detection based on multimodal integration

    NASA Astrophysics Data System (ADS)

    Zhu, Yingying; Zhou, Dongru

    2003-09-01

    Scene change detection is an essential step to automatic and content-based video indexing, retrieval and browsing. In this paper, a robust scene change detection and classification approach is presented, which analyzes audio, visual and textual sources and accounts for their inter-relations and coincidence to semantically identify and classify video scenes. Audio analysis focuses on the segmentation of audio stream into four types of semantic data such as silence, speech, music and environmental sound. Further processing on speech segments aims at locating speaker changes. Video analysis partitions visual stream into shots. Text analysis can provide a supplemental source of clues for scene classification and indexing information. We integrate the video and audio analysis results to identify video scenes and use the text information detected by the video OCR technology or derived from transcripts available to refine scene classification. Results from single source segmentation are in some cases suboptimal. By combining visual, aural features adn the accessorial text information, the scence extraction accuracy is enhanced, and more semantic segmentations are developed. Experimental results are proven to rather promising.

  2. SAR change detection based on intensity and texture changes

    NASA Astrophysics Data System (ADS)

    Gong, Maoguo; Li, Yu; Jiao, Licheng; Jia, Meng; Su, Linzhi

    2014-07-01

    In this paper, a novel change detection approach is proposed for multitemporal synthetic aperture radar (SAR) images. The approach is based on two difference images, which are constructed through intensity and texture information, respectively. In the extraction of the texture differences, robust principal component analysis technique is used to separate irrelevant and noisy elements from Gabor responses. Then graph cuts are improved by a novel energy function based on multivariate generalized Gaussian model for more accurately fitting. The effectiveness of the proposed method is proved by the experiment results obtained on several real SAR images data sets.

  3. Point pattern match-based change detection in a constellation of previously detected objects

    DOEpatents

    Paglieroni, David W.

    2016-06-07

    A method and system is provided that applies attribute- and topology-based change detection to objects that were detected on previous scans of a medium. The attributes capture properties or characteristics of the previously detected objects, such as location, time of detection, detection strength, size, elongation, orientation, etc. The locations define a three-dimensional network topology forming a constellation of previously detected objects. The change detection system stores attributes of the previously detected objects in a constellation database. The change detection system detects changes by comparing the attributes and topological consistency of newly detected objects encountered during a new scan of the medium to previously detected objects in the constellation database. The change detection system may receive the attributes of the newly detected objects as the objects are detected by an object detection system in real time.

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

    DOEpatents

    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.

  5. Vegetation change detection based on image fusion technique

    NASA Astrophysics Data System (ADS)

    Jia, Yonghong; Liu, Yueyan; Yu, Hui; Li, Deren

    2005-10-01

    The change detection of land use and land cover has always been the focus of remotely sensed study and application. Based on techniques of image fusion, a new approach of detecting vegetation change according to vector of brightness index (BI) and perpendicular vegetation index (PVI) extracted from multi-temporal remotely sensed imagery is proposed. The procedure is introduced. Firstly, the Landsat eTM+ imagery is geometrically corrected and registered. Secondly, band 2,3,4 and panchromatic images of Landsat eTM+ are fused by a trous wavelet fusion, and bands 1,2,3 of SPOT are registered to the fused images. Thirdly, brightness index and perpendicular vegetation index are respectively extracted from SPOT images and fused images. Finally, change vectors are obtained and used to detect vegetation change. The testing results show that the approach of detecting vegetation change is very efficient.

  6. A SAR ATR algorithm based on coherent change detection

    SciTech Connect

    Harmony, D.W.

    2000-12-01

    This report discusses an automatic target recognition (ATR) algorithm for synthetic aperture radar (SAR) imagery that is based on coherent change detection techniques. The algorithm relies on templates created from training data to identify targets. Objects are identified or rejected as targets by comparing their SAR signatures with templates using the same complex correlation scheme developed for coherent change detection. Preliminary results are presented in addition to future recommendations.

  7. Analytical assays based on detecting conformational changes of single molecules.

    PubMed

    Zocchi, Giovanni

    2006-03-13

    One common strategy for the detection of biomolecules is labeling either the target itself or an antibody that binds to it. Herein, a different approach, based on detecting the conformational change of a probe molecule induced by binding of the target is discussed. That is, what is being detected is not the presence of the target or the probe, but the conformational change of the probe. Recently, a single-molecule sensor has been developed that exploits this mechanism to detect hybridization of a single DNA oligomer to a DNA probe, as well as specific binding of a single protein to a DNA probe. Biomolecular recognition often involves large conformational changes of the molecules involved, and therefore this strategy may be applicable to other assays. PMID:16514690

  8. Automatic recognition of landslides based on change detection

    NASA Astrophysics Data System (ADS)

    Li, Song; Hua, Houqiang

    2009-07-01

    After Wenchuan earthquake disaster, landslide disaster becomes a common concern, and remote sensing becomes more and more important in the application of landslide monitoring. Now, the method of interpretation and recognition for landslides using remote sensing is visual interpretation mostly. Automatic recognition of landslide is a new and difficult but significative job. For the purpose of seeking a more effective method to recognize landslide automatically, this project analyzes the current methods for the recognition of landslide disasters, and their applicability to the practice of landslide monitoring. Landslide is a phenomenon and disaster triggered by natural and artificial reasons that a part of slope comprised of rock, soil and other fragmental materials slide alone a certain weak structural surface under the gravitation. Consequently, according to the geo-science principle of landslide, there is an obvious change in the sliding region between the pre-landslide and post-landslide, and it can be described in remote sensing imagery, so we develop the new approach to identify landslides, which uses change detection based on texture analysis in multi-temporal imageries. Preprocessing the remote sensing data including the following aspects of image enhancement and filtering, smoothing and cutting, image mosaics, registration and merge, geometric correction and radiation calibration, this paper does change detection base on texture characteristics in multi-temporal images to recognize landslide automatically. After change detection of multi-temporal remote sensing images based on texture analysis, if there is no change in remote sensing image, the image detected is relatively homogeneous, the image detected shows some clustering characteristics; if there is part change in image, the image detected will show two or more clustering centers; if there is complete change in remote sensing image, the image detected will show disorderly and unsystematic. At last, this

  9. Change detection of built-up land: A framework of combining pixel-based detection and object-based recognition

    NASA Astrophysics Data System (ADS)

    Xiao, Pengfeng; Zhang, Xueliang; Wang, Dongguang; Yuan, Min; Feng, Xuezhi; Kelly, Maggi

    2016-09-01

    This study proposed a new framework that combines pixel-level change detection and object-level recognition to detect changes of built-up land from high-spatial resolution remote sensing images. First, an adaptive differencing method was designed to detect changes at the pixel level based on both spectral and textural features. Next, the changed pixels were subjected to a set of morphological operations to improve the completeness and to generate changed objects, achieving the transition of change detection from the pixel level to the object level. The changed objects were further recognised through the difference of morphological building index in two phases to indicate changed objects on built-up land. The transformation from changed pixels to changed objects makes the proposed framework distinct with both the pixel-based and the object-based change detection methods. Compared with the pixel-based methods, the proposed framework can improve the change detection capability through the transformation and successive recognition of objects. Compared with the object-based method, the proposed framework avoids the issue of multitemporal segmentation and can generate changed objects directly from changed pixels. The experimental results show the effectiveness of the transformation from changed pixels to changed objects and the successive object-based recognition on improving the detection accuracy, which justify the application potential of the proposed change detection framework.

  10. Refractive index change detection based on porous silicon microarray

    NASA Astrophysics Data System (ADS)

    Chen, Weirong; Jia, Zhenhong; Li, Peng; Lv, Guodong; Lv, Xiaoyi

    2016-05-01

    By combining photolithography with the electrochemical anodization method, a microarray device of porous silicon (PS) photonic crystal was fabricated on the crystalline silicon substrate. The optical properties of the microarray were analyzed with the transfer matrix method. The relationship between refractive index and reflectivity of each array element of the microarray at 633 nm was also studied, and the array surface reflectivity changes were observed through digital imaging. By means of the reflectivity measurement method, reflectivity changes below 10-3 can be observed based on PS microarray. The results of this study can be applied to the detection of biosensor arrays.

  11. Object-based rapid change detection for disaster management

    NASA Astrophysics Data System (ADS)

    Thunig, Holger; Michel, Ulrich; Ehlers, Manfred; Reinartz, Peter

    2011-11-01

    Rapid change detection is used in cases of natural hazards and disasters. This analysis lead to quick information about areas of damage. In certain cases the lack of information after catastrophe events is obstructing supporting measures within disaster management. Earthquakes, tsunamis, civil war, volcanic eruption, droughts and floods have much in common: people are directly affected, landscapes and buildings are destroyed. In every case geospatial data is necessary to gain knowledge as basement for decision support. Where to go first? Which infrastructure is usable? How much area is affected? These are essential questions which need to be answered before appropriate, eligible help can be established. This study presents an innovative strategy to retrieve post event information by use of an object-based change detection approach. Within a transferable framework, the developed algorithms 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 normalized temporal change index (NTCI) panchromatic datasets are used to extract areas which are destroyed, areas which were not affected and in addition areas which are developing new for cases where rebuilding has already started. The results of the study are also feasible for monitoring urban growth.

  12. Vegetation change detection for urban areas based on extended change vector analysis

    NASA Astrophysics Data System (ADS)

    Yu, Hui; Jia, Yonghong

    2006-10-01

    This study sought to develop a modified change vector analysis(CVA) using normalized multi-temporal data to detect urban vegetation change. Because of complex change in urban areas, modified CVA application based on NDVI and mask techniques can minify the effect of non-vegetation changes and improve upon efficiency to a great extent. Moreover, drawing from methods in Polar plots, the extended CVA technique measures absolute angular changes and total magnitude of perpendicular vegetation index (PVI) and two of Tasseled Cap indices (greenness and wetness). Polar plots summarized change vectors to quantify and visualize both magnitude and direction of change, and magnitude is applied to determine change pixels through threshold segmentation while direction is applied as pixel's feature to classifying change pixels through supervised classification. Then this application is performed with Landsat ETM+ imageries of Wuhan in 2002 and 2005, and assessed by error matrix, which finds that it could detect change pixels 95.10% correct, and could classify change pixels 91.96% correct in seven change classes through performing supervised classification with direction angles. The technique demonstrates the ability of change vectors in multiple biophysical dimensions to vegetation change detection, and the application can be trended as an efficient alternative to urban vegetation change detection and classification.

  13. Updating National Topographic Data Base Using Change Detection Methods

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

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

    NASA Astrophysics Data System (ADS)

    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.

  15. A speaker change detection method based on coarse searching

    NASA Astrophysics Data System (ADS)

    Zhang, Xue-yuan; He, Qian-hua; Li, Yan-xiong; He, Jun

    2013-03-01

    The conventional speaker change detection (SCD) method using Bayesian Information Criterion (BIC) has been widely used. However, its performance relies on the choice of penalty factor and suffers from mass calculation. The twostep SCD is less time consuming but generates more detection errors. The limitation of conventional method's performance originates from the two adjacent data windows. We propose a strategy that inserts an interval between the two adjacent fixed-size data windows in each analysis window. The dissimilarity value between the data windows is regarded as the probability of a speaker identity change within the interval area. Then this analysis window is slid along the audio by a large step to locate the areas where speaker change points may appear. Afterwards we only focus on these areas and locate precisely where the change points are. Other areas where a speaker change point unlikely appears are abandoned. The proposed method is computationally efficient and more robust to noise and penalty factor compared with conventional method. Evaluated on the corpus of China Central Television (CCTV) news, the proposed method obtains 74.18% reduction in calculation time and 22.24% improvement in F1-measure compared with the conventional approach.

  16. Correlation based efficient face recognition and color change detection

    NASA Astrophysics Data System (ADS)

    Elbouz, M.; Alfalou, A.; Brosseau, C.; Alam, M. S.; Qasmi, S.

    2013-01-01

    Identifying the human face via correlation is a topic attracting widespread interest. At the heart of this technique lies the comparison of an unknown target image to a known reference database of images. However, the color information in the target image remains notoriously difficult to interpret. In this paper, we report a new technique which: (i) is robust against illumination change, (ii) offers discrimination ability to detect color change between faces having similar shape, and (iii) is specifically designed to detect red colored stains (i.e. facial bleeding). We adopt the Vanderlugt correlator (VLC) architecture with a segmented phase filter and we decompose the color target image using normalized red, green, and blue (RGB), and hue, saturation, and value (HSV) scales. We propose a new strategy to effectively utilize color information in signatures for further increasing the discrimination ability. The proposed algorithm has been found to be very efficient for discriminating face subjects with different skin colors, and those having color stains in different areas of the facial image.

  17. Object-Based Classification and Change Detection of Hokkaido, Japan

    NASA Astrophysics Data System (ADS)

    Park, J. G.; Harada, I.; Kwak, Y.

    2016-06-01

    Topography and geology are factors to characterize the distribution of natural vegetation. Topographic contour is particularly influential on the living conditions of plants such as soil moisture, sunlight, and windiness. Vegetation associations having similar characteristics are present in locations having similar topographic conditions unless natural disturbances such as landslides and forest fires or artificial disturbances such as deforestation and man-made plantation bring about changes in such conditions. We developed a vegetation map of Japan using an object-based segmentation approach with topographic information (elevation, slope, slope direction) that is closely related to the distribution of vegetation. The results found that the object-based classification is more effective to produce a vegetation map than the pixel-based classification.

  18. Object-based change detection for landslide monitoring based on SPOT imagery

    NASA Astrophysics Data System (ADS)

    Hölbling, Daniel; Friedl, Barbara; Eisank, Clemens

    2014-05-01

    The steadily increasing availability of Earth observation (EO) data from a wide range of sensors facilitates the long-time monitoring of mass movements and retrospective analysis. Pixel-based approaches are most commonly used for detecting changes based on optical remote sensing data. However, single pixels are not suitable for depicting natural phenomena such as landslides in their full complexity and their transformation over time. By applying semi-automated object-based change detection limitations inherent to pixel-based methods can be overcome to a certain extent. For instance, the problem of variant spectral reflectance for the same pixel location in images from different points in time can be minimized. Therefore, atmospheric and radiometric correction of input data sets - although highly recommended - seems to be not that important for developing a straightforward change detection approach based on object-based image analysis (OBIA). The object-based change detection approach was developed for a subset of the Baichi catchment, which is located in the Shihmen Reservoir watershed in northern Taiwan. The study area is characterized by mountainous terrain with steep slopes and is regularly affected by severe landslides and debris flows. Several optical satellite images, i.e. SPOT images from different years and seasons with a spatial resolution ranging from 2.5 to 6.25 m, have been used for monitoring the past evolution of landslides and landslide affected areas. A digital elevation model (DEM) with 5 m spatial resolution was integrated in the analysis for supporting the differentiation of landslides and debris flows. The landslide changes were identified by comparing feature values of segmentation-derived image objects between two subsequent images in eCognition (Trimble) software. To increase the robustness and transferability of the approach we identified changes by using the relative difference in values of band-specific relational features, spectral

  19. Environmental monitoring based on automatic change detection from remotely sensed data: kernel-based approach

    NASA Astrophysics Data System (ADS)

    Shah-Hosseini, Reza; Homayouni, Saeid; Safari, Abdolreza

    2015-01-01

    In the event of a natural disaster, such as a flood or earthquake, using fast and efficient methods for estimating the extent of the damage is critical. Automatic change mapping and estimating are important in order to monitor environmental changes, e.g., deforestation. Traditional change detection (CD) approaches are time consuming, user dependent, and strongly influenced by noise and/or complex spectral classes in a region. Change maps obtained by these methods usually suffer from isolated changed pixels and have low accuracy. To deal with this, an automatic CD framework-which is based on the integration of change vector analysis (CVA) technique, kernel-based C-means clustering (KCMC), and kernel-based minimum distance (KBMD) classifier-is proposed. In parallel with the proposed algorithm, a support vector machine (SVM) CD method is presented and analyzed. In the first step, a differential image is generated via two approaches in high dimensional Hilbert space. Next, by using CVA and automatically determining a threshold, the pseudo-training samples of the change and no-change classes are extracted. These training samples are used for determining the initial value of KCMC parameters and training the SVM-based CD method. Then optimizing a cost function with the nature of geometrical and spectral similarity in the kernel space is employed in order to estimate the KCMC parameters and to select the precise training samples. These training samples are used to train the KBMD classifier. Last, the class label of each unknown pixel is determined using the KBMD classifier and SVM-based CD method. In order to evaluate the efficiency of the proposed algorithm for various remote sensing images and applications, two different datasets acquired by Quickbird and Landsat TM/ETM+ are used. The results show a good flexibility and effectiveness of this automatic CD method for environmental change monitoring. In addition, the comparative analysis of results from the proposed method

  20. Efficient fold-change detection based on protein-protein interactions.

    PubMed

    Buijsman, W; Sheinman, M

    2014-02-01

    Various biological sensory systems exhibit a response to a relative change of the stimulus, often referred to as fold-change detection. In the past few years, fold-change detecting mechanisms, based on transcriptional networks, have been proposed. Here we present a fold-change detecting mechanism, based on protein-protein interactions, consisting of two interacting proteins. This mechanism does not consume chemical energy and is not subject to transcriptional and translational noise, in contrast to previously proposed mechanisms. We show by analytical and numerical calculations that the mechanism is robust and can have a fast, precise, and efficient response for parameters that are relevant to eukaryotic cells. PMID:25353514

  1. Molecular Recognition: Detection of Colorless Compounds Based on Color Change

    ERIC Educational Resources Information Center

    Khalafi, Lida; Kashani, Samira; Karimi, Javad

    2016-01-01

    A laboratory experiment is described in which students measure the amount of cetirizine in allergy-treatment tablets based on molecular recognition. The basis of recognition is competition of cetirizine with phenolphthalein to form an inclusion complex with ß-cyclodextrin. Phenolphthalein is pinkish under basic condition, whereas it's complex form…

  2. The study of target damage assessment system based on image change detection

    NASA Astrophysics Data System (ADS)

    Zhao, Ping; Yang, Fan; Feng, Xinxi

    2009-10-01

    Target Damage Assessment (TDA) system is an important component of the intelligent command and control system. The method of building TDA based on Image Change Detection can greatly improve the system efficiency and accuracy, thus get a fast and precise assessment results. This paper firstly analyzes the structure of TDA system. Then studies the key technology in this system. Finally, gives an evaluation criteria based on image change detection of the target damage assessment system.

  3. Change detection based on integration of multi-scale mixed-resolution information

    NASA Astrophysics Data System (ADS)

    Wei, Li; Wang, Cheng; Wen, Chenglu

    2016-03-01

    In this paper, a new method of unsupervised change detection is proposed by modeling multi-scale change detector based on local mixed information and we present a method of automated threshold. A theoretical analysis is presented to demonstrate that more comprehensive information is taken into account by the integration of multi-scale information. The ROC curves show that change detector based on multi-scale mixed information(MSM) is more effective than based on mixed information(MIX). Experiments on artificial and real-world datasets indicate that the multi-scale change detection of mixed information can eliminate the pseudo-change part of the area. Therefore, the proposed algorithm MSM is an effective method for the application of change detection.

  4. Fast SAR Image Change Detection Using Bayesian Approach Based Difference Image and Modified Statistical Region Merging

    PubMed Central

    Ni, Weiping; Yan, Weidong; Bian, Hui; Wu, Junzheng

    2014-01-01

    A novel fast SAR image change detection method is presented in this paper. Based on a Bayesian approach, the prior information that speckles follow the Nakagami distribution is incorporated into the difference image (DI) generation process. The new DI performs much better than the familiar log ratio (LR) DI as well as the cumulant based Kullback-Leibler divergence (CKLD) DI. The statistical region merging (SRM) approach is first introduced to change detection context. A new clustering procedure with the region variance as the statistical inference variable is exhibited to tailor SAR image change detection purposes, with only two classes in the final map, the unchanged and changed classes. The most prominent advantages of the proposed modified SRM (MSRM) method are the ability to cope with noise corruption and the quick implementation. Experimental results show that the proposed method is superior in both the change detection accuracy and the operation efficiency. PMID:25258740

  5. A supervised method for object-based 3D building change detection on aerial stereo images

    NASA Astrophysics Data System (ADS)

    Qin, R.; Gruen, A.

    2014-08-01

    There is a great demand for studying the changes of buildings over time. The current trend for building change detection combines the orthophoto and DSM (Digital Surface Models). The pixel-based change detection methods are very sensitive to the quality of the images and DSMs, while the object-based methods are more robust towards these problems. In this paper, we propose a supervised method for building change detection. After a segment-based SVM (Support Vector Machine) classification with features extracted from the orthophoto and DSM, we focus on the detection of the building changes of different periods by measuring their height and texture differences, as well as their shapes. A decision tree analysis is used to assess the probability of change for each building segment and the traffic lighting system is used to indicate the status "change", "non-change" and "uncertain change" for building segments. The proposed method is applied to scanned aerial photos of the city of Zurich in 2002 and 2007, and the results have demonstrated that our method is able to achieve high detection accuracy.

  6. Comparison of Pixel-Based and Object-Oriented Land Cover Change Detection Methods

    NASA Astrophysics Data System (ADS)

    Xie, Zhenlei; Shi, Ruoming; Zhu, Ling; Peng, Shu; Chen, Xu

    2016-06-01

    Change detection method is an efficient way in the aim of land cover product updating on the basis of the existing products, and at the same time saving lots of cost and time. Considering the object-oriented change detection method for 30m resolution Landsat image, analysis of effect of different segmentation scales on the method of the object-oriented is firstly carried out. On the other hand, for analysing the effectiveness and availability of pixel-based change method, the two indices which complement each other are the differenced Normalized Difference Vegetation Index (dNDVI), the Change Vector (CV) were used. To demonstrate the performance of pixel-based and object-oriented, accuracy assessment of these two change detection results will be conducted by four indicators which include overall accuracy, omission error, commission error and Kappa coefficient.

  7. Object-Oriented Change Detection for Remote Sensing Images Based on Multi-Scale Fusion

    NASA Astrophysics Data System (ADS)

    Feng, Wenqing; Sui, Haigang; Tu, Jihui

    2016-06-01

    In the process of object-oriented change detection, the determination of the optimal segmentation scale is directly related to the subsequent change information extraction and analysis. Aiming at this problem, this paper presents a novel object-level change detection method based on multi-scale segmentation and fusion. First of all, the fine to coarse segmentation is used to obtain initial objects of different sizes; then, according to the features of the objects, Change Vector Analysis is used to obtain the change detection results of various scales. Furthermore, in order to improve the accuracy of change detection, this paper introduces fuzzy fusion and two kinds of decision level fusion methods to get the results of multi-scale fusion. Based on these methods, experiments are done with SPOT5 multi-spectral remote sensing imagery. Compared with pixel-level change detection methods, the overall accuracy of our method has been improved by nearly 10%, and the experimental results prove the feasibility and effectiveness of the fusion strategies.

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

    NASA Astrophysics Data System (ADS)

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

    2015-08-01

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

  9. Scene change detection and content-based sampling of video sequences

    NASA Astrophysics Data System (ADS)

    Shahraray, Behzad

    1995-04-01

    Digital images and image sequences (video) are a significant component of multimedia information systems, and by far the most demanding in terms of storage and transmission requirements. Content-based temporal sampling of video frames is proposed as an efficient method for representing the visual information contained in the video sequence by using only a small subset of the video frames. This involves the identification and retention of frames at which the contents of the scene is `significantly' different from the previously retained frames. It is argued that the criteria used to measure the significance of a change in the contents of the video frames are subjective, and performing the task of content-based sampling of image sequences, in general, requires a high level of image understanding. However, a significant subset of the points at which the contextual information in the video frames change significantly can be detected by a `scene change detection' method. The definition of a scene change is generalized to include not only the abrupt transitions between shots, but also gradual transitions between shots resulting from video editing modes, and inter-shot changes induced by camera operations. A method for detecting abrupt and gradual scene changes is discussed. The criteria for detecting camera-induced scene changes from camera operations are proposed. Scene matching is proposed as a means of achieving further reductions in the storage and transmission requirements.

  10. Change Detection in Synthetic Aperture Radar Images Based on Deep Neural Networks.

    PubMed

    Gong, Maoguo; Zhao, Jiaojiao; Liu, Jia; Miao, Qiguang; Jiao, Licheng

    2016-01-01

    This paper presents a novel change detection approach for synthetic aperture radar images based on deep learning. The approach accomplishes the detection of the changed and unchanged areas by designing a deep neural network. The main guideline is to produce a change detection map directly from two images with the trained deep neural network. The method can omit the process of generating a difference image (DI) that shows difference degrees between multitemporal synthetic aperture radar images. Thus, it can avoid the effect of the DI on the change detection results. The learning algorithm for deep architectures includes unsupervised feature learning and supervised fine-tuning to complete classification. The unsupervised feature learning aims at learning the representation of the relationships between the two images. In addition, the supervised fine-tuning aims at learning the concepts of the changed and unchanged pixels. Experiments on real data sets and theoretical analysis indicate the advantages, feasibility, and potential of the proposed method. Moreover, based on the results achieved by various traditional algorithms, respectively, deep learning can further improve the detection performance. PMID:26068879

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

    NASA Astrophysics Data System (ADS)

    Saur, Günter; Krüger, Wolfgang

    2016-06-01

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

  12. Region-based automatic building and forest change detection on Cartosat-1 stereo imagery

    NASA Astrophysics Data System (ADS)

    Tian, J.; Reinartz, P.; d'Angelo, P.; Ehlers, M.

    2013-05-01

    In this paper a novel region-based method is proposed for change detection using space borne panchromatic Cartosat-1 stereo imagery. In the first step, Digital Surface Models (DSMs) from two dates are generated by semi-global matching. The geometric lateral resolution of the DSMs is 5 m × 5 m and the height accuracy is in the range of approximately 3 m (RMSE). In the second step, mean-shift segmentation is applied on the orthorectified images of two dates to obtain initial regions. A region intersection following a merging strategy is proposed to get minimum change regions and multi-level change vectors are extracted for these regions. Finally change detection is achieved by combining these features with weighted change vector analysis. The result evaluations demonstrate that the applied DSM generation method is well suited for Cartosat-1 imagery, and the extracted height values can largely improve the change detection accuracy, moreover it is shown that the proposed change detection method can be used robustly for both forest and industrial areas.

  13. Distance metric-based forest cover change detection using MODIS time series

    NASA Astrophysics Data System (ADS)

    Huang, Xiaoman; Friedl, Mark A.

    2014-06-01

    More than 12 years of global observations are now available from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS). As this time series grows, the MODIS archive provides new opportunities for identification and characterization of land cover at regional to global spatial scales and interannual to decadal temporal scales. In particular, the high temporal frequency of MODIS provides a rich basis for monitoring land cover dynamics. At the same time, the relatively coarse spatial resolution of MODIS (250-500 m) presents significant challenges for land cover change studies. In this paper, we present a distance metric-based change detection method for identifying changed pixels at annual time steps using 500 m MODIS time series data. The approach we describe uses distance metrics to measure (1) the similarity between a pixel's annual time series to annual time series for pixels of the same land cover class and (2) the similarity between annual time series from different years at the same pixel. Pre-processing, including gap-filling, smoothing and temporal subsetting of MODIS 500 m Nadir BRDF-adjusted Reflectance (NBAR) time series is essential to the success of our method. We evaluated our approach using three case studies. We first explored the ability of our method to detect change in temperate and boreal forest training sites in North America and Eurasia. We applied our method to map regional forest change in the Pacific Northwest region of the United States, and in tropical forests of the Xingu River Basin in Mato Grosso, Brazil. Results from these case studies show that the method successfully identified pixels affected by logging and fire disturbance in temperate and boreal forest sites. Change detection results in the Pacific Northwest compared well with a Landsat-based disturbance map, yielding a producer's accuracy of 85%. Assessment of change detection results for the Xingu River Basin demonstrated that detection accuracy improves as the fraction of

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

    NASA Astrophysics Data System (ADS)

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

    2011-11-01

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

  15. Point Cloud Based Change Detection - an Automated Approach for Cloud-based Services

    NASA Astrophysics Data System (ADS)

    Collins, Patrick; Bahr, Thomas

    2016-04-01

    The fusion of stereo photogrammetric point clouds with LiDAR data or terrain information derived from SAR interferometry has a significant potential for 3D topographic change detection. In the present case study latest point cloud generation and analysis capabilities are used to examine a landslide that occurred in the village of Malin in Maharashtra, India, on 30 July 2014, and affected an area of ca. 44.000 m2. It focuses on Pléiades high resolution satellite imagery and the Airbus DS WorldDEMTM as a product of the TanDEM-X mission. This case study was performed using the COTS software package ENVI 5.3. Integration of custom processes and automation is supported by IDL (Interactive Data Language). Thus, ENVI analytics is running via the object-oriented and IDL-based ENVITask API. The pre-event topography is represented by the WorldDEMTM product, delivered with a raster of 12 m x 12 m and based on the EGM2008 geoid (called pre-DEM). For the post-event situation a Pléiades 1B stereo image pair of the AOI affected was obtained. The ENVITask "GeneratePointCloudsByDenseImageMatching" was implemented to extract passive point clouds in LAS format from the panchromatic stereo datasets: • A dense image-matching algorithm is used to identify corresponding points in the two images. • A block adjustment is applied to refine the 3D coordinates that describe the scene geometry. • Additionally, the WorldDEMTM was input to constrain the range of heights in the matching area, and subsequently the length of the epipolar line. The "PointCloudFeatureExtraction" task was executed to generate the post-event digital surface model from the photogrammetric point clouds (called post-DEM). Post-processing consisted of the following steps: • Adding the geoid component (EGM 2008) to the post-DEM. • Pre-DEM reprojection to the UTM Zone 43N (WGS-84) coordinate system and resizing. • Subtraction of the pre-DEM from the post-DEM. • Filtering and threshold based classification of

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

    SciTech Connect

    Chandola, Varun; Vatsavai, Raju

    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).

  17. Object-oriented change detection based on weighted polarimetric scattering differences on POLSAR images

    NASA Astrophysics Data System (ADS)

    Shi, X.; Lu, L.; Yang, S.; Huang, G.; Zhao, Z.

    2015-06-01

    For wide application of change detection with SAR imagery, current processing technologies and methods are mostly based on pixels. It is difficult for pixel-based technologies to utilize spatial characteristics of images and topological relations of objects. Object-oriented technology takes objects as processing unit, which takes advantage of the shape and texture information of image. It can greatly improve the efficiency and reliability of change detection. Recently, with the development of polarimetric synthetic aperture radar (PolSAR), more backscattering features on different polarization state can be available for usage of object-oriented change detection study. In this paper, the object-oriented strategy will be employed. Considering the fact that the different target or target's state behaves different backscattering characteristics dependent on polarization state, an object-oriented change detection method that based on weighted polarimetric scattering difference of PolSAR images is proposed. The method operates on the objects generated by generalized statistical region merging (GSRM) segmentation processing. The merit of GSRM method is that image segmentation is executed on polarimetric coherence matrix, which takes full advantages of polarimetric backscattering features. And then, the measurement of polarimetric scattering difference is constructed by combining the correlation of covariance matrix and the difference of scattering power. Through analysing the effects of the covariance matrix correlation and the scattering echo power difference on the polarimetric scattering difference, the weighted method is used to balance the influences caused by the two parts, so that more reasonable weights can be chosen to decrease the false alarm rate. The effectiveness of the algorithm that proposed in this letter is tested by detection of the growth of crops with two different temporal radarsat-2 fully PolSAR data. First, objects are produced by GSRM algorithm

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

    PubMed

    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

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

    PubMed Central

    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

  20. A novel method for detecting abrupt dynamic change based on the changing Hurst exponent of spatial images

    NASA Astrophysics Data System (ADS)

    He, Wen-Ping; Liu, Qun-Qun; Gu, Bin; Zhao, Shan-Shan

    2016-01-01

    The climate system is a classical spatiotemporal evolutionary dynamic system with spatiotemporal correlation characteristics. Based on this, two-dimensional detrended fluctuation analysis (TD-DFA) is used to estimate the Hurst exponent of two-dimensional images. Then, we monitored the change of the Hurst exponent of the images to identify an abrupt dynamic change. We tested the performance of this method with a coupled spatiotemporal dynamic model and found that it works well. The changes in the Hurst exponents of the spatial images are stable when there is no dynamic change in the system, but there will be a clear non-stationary change of the Hurst exponents; for example, the abrupt mean values change if the dynamics of the system change. Thus, the TD-DFA method is suitable for detecting an abrupt dynamic change from natural and artificial images. The spatial images of the NCEP reanalysis of the daily average temperature exhibited fractality. Based on this, we found three non-stationary changes in the Hurst exponents for the NCEP reanalysis of the daily average temperature or for the annual average temperature in the region (60°S-60°N). It can be concluded that the climate system may have incurred three dynamic changes since 1961 on decadal timescales, i.e., in approximately the mid-1970s, the mid-1980s, and between the late 1990s and the early 2000s.

  1. ECG-based detection of body position changes in ischemia monitoring.

    PubMed

    García, José; Aström, Magnus; Mendive, Javier; Laguna, Pablo; Sörnmo, Leif

    2003-06-01

    The purpose of this paper is to analyze and detect changes in body position (BPC) during electrocardiogram (ECG) recording. These changes are often manifested as shifts in the electrical axis and may be misclassified as ischemic changes during ambulatory monitoring. We investigate two ECG signal processing methods for detecting BPCs. Different schemes for feature extraction are used (spatial and scalar), while preprocessing, trend postprocessing and detection are identical. The spatial approach is based on VCG loop rotation angles and the scalar approach is based on the Karhunen-Loève transform (KLT) coefficients. The methods are evaluated on two different databases: a database with annotated BPCs and the STAFF III database with recordings from rest and during angioplasty-induced ischemia but not including BPCs. The angle-based detector results in performance values of detection probability PD = 95%, false alarm probability PF = 3% in the BPC database and false alarm rate in the STAFF III database in control ECGs during rest RF(c) = 2 h(-1) (episodes per hour) and in ischemia recordings during angioplasty RF(a) = 7 h(-1), whereas the KLT-based detector produces values of PD = 89%, PF = 3%, RF(c) = 4 h(-1), and RF(a) = 11 h(-1), respectively. Including information on noise level in the detection process to reduce the number of false alarms, performance values of PD approximately equal to 90%, PF approximately equal to 1%, RF(c) approximately equal to 1 h(-1) and RF(a) approximately equal to 2 h(-1) are obtained with both methods. It is concluded that reliable detection of BPCs may be achieved using the ECG signal and should work in parallel to ischemia detectors. PMID:12814234

  2. Detection of perturbed quantization class stego images based on possible change modes

    NASA Astrophysics Data System (ADS)

    Zhang, Yi; Liu, Fenlin; Yang, Chunfang; Luo, Xiangyang; Song, Xiaofeng

    2015-11-01

    To improve the detection performance for perturbed quantization (PQ) class [PQ, energy-adaptive PQ (PQe), and texture-adaptive PQ (PQt)] stego images, a detection method based on possible change modes is proposed. First, by using the relationship between the changeable coefficients used for carrying secret messages and the second quantization steps, the modes having even second quantization steps are identified as possible change modes. Second, by referencing the existing features, the modified features that can accurately capture the embedding changes based on possible change modes are extracted. Next, feature sensitivity analyses based on the modifications performed before and after the embedding are carried out. These analyses show that the modified features are more sensitive to the original features. Experimental results indicate that detection performance of the modified features is better than that of the corresponding original features for three typical feature models [Cartesian calibrated PEVny (ccPEV), Cartesian calibrated co-occurrence matrix features (CF), and JPEG rich model (JRM)], and the integrated feature consisting of enhanced histogram features (EHF) and the modified JRM outperforms two current state-of-the-art feature models, namely, phase aware projection model (PHARM) and Gabor rich model (GRM).

  3. Trajectory-Based Analysis of Urban Land-Cover Change Detection

    NASA Astrophysics Data System (ADS)

    Zhang, Y. H.; Liu, H. P.

    2016-06-01

    China have occurred unprecedented urban growth over the last two decades. It is reported that the level of China's urbanization increased from 18 % in 1978 to 41 % in 2003, and this figure may exceed 65 % by 2050. The change detection of long time serious remote sensing images is the effective way to acquire the data of urban land-cover change to understand the pattern of urbanization. In this paper, we proposed the similarity index (SI) and apply it in long time series urban land-cover change detection. First of all, we built possible change trajectories in four times based on the normalized difference vegetation index (NDVI) and modified normalized difference water index (MNDWI) that extracted from time series Landsat images. Secondly, we applied SI in similarity comparison between the observed change trajectory and the possible trajectories. Lastly, verifying the accuracy of the results. The overall accuracy in four periods is 85.7 % and the overall accuracy of each two years is about 90 % and kappa statistic is about 0.85. The results show that this method is effective for time series land-cover change detection.

  4. Instantaneous dynamic change detection based on three-line-array stereoscopic images of TH-1 satellite

    NASA Astrophysics Data System (ADS)

    Zheng, Tuanjie; Cheng, Jiasheng; Li, Heyuan

    2014-05-01

    TH-1 satellite loading three-line array stereoscopic camera, can scanning 3 times from different directions on the same region or target within the time for about 1 minute, conducive to regional monitoring or target instantaneous change monitoring. Based on the time difference of forward, nadir and backward images of the three-line-array camera of TH-1 Satellite, this paper gives a method to get regional dynamic change image by processing of geometric and physical consistency under the principle of photogrammetry, and to construct the model of change detection by the quantitative results of change detection under the improvement and optimization of noise filtering algorithm. The experimental results show that, by using the detection results of forward, nadir and backward images of the three-line -array camera of TH-1 Satellite, moving distance and velocity can be accurately calculated, and quantitative monitoring of topography changes can be achieved, which not only has temporal resolution, but also can't be achieved by other environmental monitoring satellites. It's significant for flood, fire, clouds, or motion detectors. TH-1 satellite is China's first generation of transmission photogrammetry satellite. With the more satellites networking operation, and higher spatial and temporal resolution, The TH satellites will play a greater role in the field of Earth observation. This article merely uses the principles of photogrammetry to consider photography deformation from different directions, and thorough study will aim at shadow and sun elevation angle, to fully realize the monitoring of changes in topography and moving targets.

  5. ECG-based detection of body position changes using a Laplacian noise model.

    PubMed

    Mincholé, Ana; Sörnmo, Leif; Laguna, Pablo

    2011-01-01

    Body position changes (BPC), which are often manifested in the ECG as shifts in the electrical axis of the heart, result in ST changes, and thus, may be misclassified as ischemic events during ambulatory monitoring. We have developed a BPC detector by modeling shifts as changes in the Karhunen-Loève transform coefficients of the QRS complex and the ST-T waveform. The noise is assumed to have a Laplacian distribution. A generalized likelihood ratio test has been chosen as the strategy to detect BPCs. Two different databases have been used to assess detection performance. The obtained results were 93%/99% in terms of sensitivity/positive predictivity value (S/+PV) and a false alarm rate of 2 events/hour. The results clearly outperform current techniques (S/+PV: 85%/99%) based on the Gaussian noise assumption. PMID:22255932

  6. Change Detection with Multi-Source Defective Remote Sensing Images Based on Evidential Fusion

    NASA Astrophysics Data System (ADS)

    Chen, Xi; Li, Jing; Zhang, Yunfei; Tao, Liangliang

    2016-06-01

    Remote sensing images with clouds, shadows or stripes are usually considered as defective data which limit their application for change detection. This paper proposes a method to fuse a series of defective images as evidences for change detection. In the proposed method, post-classification comparison process is firstly performed on multi-source defective images. Then, the classification results of all the images, together with their corresponding confusion matrixes are used to calculate the Basic Belief Assignment (BBA) of each pixel. Further, based on the principle of Dempster-Shafer evidence theory, a BBA redistribution process is introduced to deal with the defective parts of multi-source data. At last, evidential fusion and decision making rules are applied on the pixel level, and the final map of change detection can be derived. The proposed method can finish change detection with data fusion and image completion in one integrated process, which makes use of the complementary and redundant information from the input images. The method is applied to a case study of landslide barrier lake formed in Aug. 3rd, 2014, with a series of multispectral images from different sensors of GF-1 satellite. Result shows that the proposed method can not only complete the defective parts of the input images, but also provide better change detection accuracy than post-classification comparison method with single pair of pre- and post-change images. Subsequent analysis indicates that high conflict degree between evidences is the main source of errors in the result. Finally, some possible reasons that result in evidence conflict on the pixel level are analysed.

  7. Object-Based Change Detection Using High-Resolution Remotely Sensed Data and GIS

    NASA Astrophysics Data System (ADS)

    Sofina, N.; Ehlers, M.

    2012-08-01

    High resolution remotely sensed images provide current, detailed, and accurate information for large areas of the earth surface which can be used for change detection analyses. Conventional methods of image processing permit detection of changes by comparing remotely sensed multitemporal images. However, for performing a successful analysis it is desirable to take images from the same sensor which should be acquired at the same time of season, at the same time of a day, and - for electro-optical sensors - in cloudless conditions. Thus, a change detection analysis could be problematic especially for sudden catastrophic events. A promising alternative is the use of vector-based maps containing information about the original urban layout which can be related to a single image obtained after the catastrophe. The paper describes a methodology for an object-based search of destroyed buildings as a consequence of a natural or man-made catastrophe (e.g., earthquakes, flooding, civil war). The analysis is based on remotely sensed and vector GIS data. It includes three main steps: (i) generation of features describing the state of buildings; (ii) classification of building conditions; and (iii) data import into a GIS. One of the proposed features is a newly developed 'Detected Part of Contour' (DPC). Additionally, several features based on the analysis of textural information corresponding to the investigated vector objects are calculated. The method is applied to remotely sensed images of areas that have been subjected to an earthquake. The results show the high reliability of the DPC feature as an indicator for change.

  8. Interactive change detection based on dissimilarity image and decision tree classification

    NASA Astrophysics Data System (ADS)

    Wang, Yan; Crouzil, Alain; Puel, Jean-Baptiste

    2015-02-01

    Our study mainly focus on detecting changed regions in two images of the same scene taken by digital cameras at different times. The images taken by digital cameras generally provide less information than multi-channel remote sensing images. Moreover, the application-dependent insignificant changes, such as shadows or clouds, may cause the failure of the classical methods based on image differences. The machine learning approach seems to be promising, but the lack of a sufficient volume of training data for photographic landscape observatories discards a lot of methods. So we investigate in this work the interactive learning approach and provide a discriminative model that is a 16-dimensional feature space comprising the textural appearance and contextual information. Dissimilarity measures in different neighborhood sizes are used to detect the difference within the neighborhood of an image pair. To detect changes between two images, the user designates change and non-change samples (pixel sets) in the images using a selection tool. This data is used to train a classifier using decision tree training method which is then applied to all the other pixels of the image pair. The experiments have proved the potential of the proposed approach.

  9. Object-based change detection on multiscale fusion for VHR remote sensing images

    NASA Astrophysics Data System (ADS)

    Zhang, Hansong; Chen, Jianyu; Liu, Xin

    2015-12-01

    This paper presents a novel Object-based context sensitive technique for unsupervised change detection in very high spatial resolution(VHR) remote sensing images. The proposed technique models the scene at different segment levels defining multiscale-level image objects. Multiscale-level image object change features is helpful for improving the discriminability between the changed class and unchanged class. Firstly according to the best classification principle as "homogeneity in class, heterogeneity between class", A set of optimal scales are determined. Then a multiscale level change vector analysis to each pixel of the considered images helps improve the accuracy and the degree of automation, which is implemented on multiscale features fusion. The technique properly analyzes the multiscale-level image objects' context information of the considered spatial position. The adaptive nature of optimal multiscale image objects and their multilevel representation allow one a proper modeling of complex scene in the investigated region. Experimental results confirm the effectiveness of the proposed approach.

  10. Change detection of polarimetric SAR images based on the KummerU Distribution

    NASA Astrophysics Data System (ADS)

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

    2014-11-01

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

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

    NASA Astrophysics Data System (ADS)

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

    1999-05-01

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

  12. Empirical likelihood based detection procedure for change point in mean residual life functions under random censorship.

    PubMed

    Chen, Ying-Ju; Ning, Wei; Gupta, Arjun K

    2016-05-01

    The mean residual life (MRL) function is one of the basic parameters of interest in survival analysis that describes the expected remaining time of an individual after a certain age. The study of changes in the MRL function is practical and interesting because it may help us to identify some factors such as age and gender that may influence the remaining lifetimes of patients after receiving a certain surgery. In this paper, we propose a detection procedure based on the empirical likelihood for the changes in MRL functions with right censored data. Two real examples are also given: Veterans' administration lung cancer study and Stanford heart transplant to illustrate the detecting procedure. Copyright © 2016 John Wiley & Sons, Ltd. PMID:26936529

  13. Object-Based Forest Change Detection Using High Resolution Satellite Images

    NASA Astrophysics Data System (ADS)

    Chehata, N.; Orny, C.; Boukir, S.; Guyon, D.

    2011-04-01

    An object-based approach for forest disaster change detection using High Resolution (HR) satellite images is proposed. An automatic feature selection process is used to optimize image segmentation via an original calibration-like procedure. A multitemporal classification then enables the separation of wind-fall from intact areas based on a new descriptor that depends on the level of fragmentation of the detected regions. The mean shift algorithm was used in both the segmentation and the classification processes. The method was tested on a high resolution Formosat-2 multispectral satellite image pair acquired before and after the Klaus storm. The obtained results are encouraging and the contribution of high resolution images for forest disaster mapping is discussed.

  14. Distance metric-based forest cover change detection using MODIS time series

    NASA Astrophysics Data System (ADS)

    Huang, X.; Friedl, M. A.; Sulla-menashe, D. J.

    2012-12-01

    More than a decade of global observations are now available from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS). The MODIS archive provides new opportunities for identification and characterization of land cover change processes at regional to global scales. In particular, the high temporal frequency of MODIS data provides new opportunities for remotely sensed land cover change detection. At the same time, the relatively coarse spatial resolution of MODIS (250-500m) presents significant challenges for land cover change studies. In this paper we present a simple yet effective distance metric-based change detection method for identifying changed pixels at annual time steps from MODIS time series data. The approach we have developed uses statistical metrics that measure the within-year distance of a pixel to pixels of the same land cover class, and the between-year distance between measurements acquired at two points in time. Both metrics make explicit use of annual MODIS time series at each pixel. The former metric measures the similarity of a pixel's temporal profile to the average multi-year baseline time series, and the latter measures the similarity of the pixel's temporal profile before and after the year of interest. We evaluate our approach using two case studies for data from 2003-2010. In the first case study we apply our method to detect sites that have experienced land cover change in the training site database used to create the MODIS land cover product, focusing on forested land cover sites. In the second case study we examine forest conversion in the Xingu River Basin in Mato Grosso, Brazil. We also describe the pre-processing steps necessary to apply our method, including gap-filling, smoothing and temporal sub-setting of MODIS Nadir BRDF-adjusted Reflectance (NBAR) time series. These steps are crucial for baseline characterization of forest classes in both case studies, but require refinements specific to each dataset. Results show that

  15. Change detection based on features invariant to monotonic transforms and spatially constrained matching

    NASA Astrophysics Data System (ADS)

    Rodrigues, Marco Túlio A. N.; Balbino de Mesquita, Daniel; Nascimento, Erickson R.; Schwartz, William Robson

    2016-01-01

    In several image processing applications, discovering regions that have changed in a set of images acquired from a scene at different times and possibly from different viewpoints plays a very important role. Remote sensing, visual surveillance, medical diagnosis, civil infrastructure, and underwater sensing are examples of such applications that operate in dynamic environments. We propose an approach to detect such changes automatically by using image analysis techniques and segmentation based on superpixels in two stages: (1) the tuning stage, which is focused on adjusting the parameters; and (2) the unsupervised stage that is executed in real scenarios without an appropriate ground truth. Unlike most common approaches, which are pixel-based, our approach combines superpixel extraction, hierarchical clustering, and segment matching. Experimental results demonstrate the effectiveness of the proposed approach compared to a remote sensing technique and a background subtraction technique, demonstrating the robustness of our algorithm against illumination variations.

  16. Change Detection Based on Persistent Scatterer Interferometry - Case Study of Monitoring AN Urban Area

    NASA Astrophysics Data System (ADS)

    Yang, C. H.; Soergel, U.

    2015-08-01

    Persistent Scatterer Interferometry (PSI) is a technique to extract subtle surface deformation from sets of scatterers identified in time-series of SAR images which feature temporally stable and strong radar signal (i.e., Persistent Scatterers, PS). Because of the preferred rectangular and regular structure of man-made objects, PSI works particularly well for monitoring of settlements. Usually, in PSI it is assumed that except for surface motion the scene is steady. In case this is not given, corresponding PS candidates are discarded during PSI processing. On the other hand, pixel-based change detection relying on local comparison of multi-temporal images typically highlights scene modifications of larger size rather than detail level. In this paper, we propose a method to combine these two types of change detection approaches. First, we introduce a local change-index based on PSI, which basically looks for PS candidates that remain stable over a certain period of time, but then break down suddenly. In addition, for the remaining PS candidates we apply common PSI processing which yields attributes like velocity in line-of-sight. In order to consider context, we apply now spatial filtering according to the derived attributes and morphology to exclude outliers and extract connect components of similar regions at the same time. We demonstrate our approach for test site Berlin, Germany, where, firstly, deformation-velocities on man-made structures are estimated and, secondly, some construction-sites are correctly recognized.

  17. Object-Oriented Change Detection Based on Multi-Scale Approach

    NASA Astrophysics Data System (ADS)

    Jia, Yonghong; Zhou, Mingting; Jinshan, Ye

    2016-06-01

    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.

  18. Detecting Unidentified Changes

    PubMed Central

    Howe, Piers D. L.; Webb, Margaret E.

    2014-01-01

    Does becoming aware of a change to a purely visual stimulus necessarily cause the observer to be able to identify or localise the change or can change detection occur in the absence of identification or localisation? Several theories of visual awareness stress that we are aware of more than just the few objects to which we attend. In particular, it is clear that to some extent we are also aware of the global properties of the scene, such as the mean luminance or the distribution of spatial frequencies. It follows that we may be able to detect a change to a visual scene by detecting a change to one or more of these global properties. However, detecting a change to global property may not supply us with enough information to accurately identify or localise which object in the scene has been changed. Thus, it may be possible to reliably detect the occurrence of changes without being able to identify or localise what has changed. Previous attempts to show that this can occur with natural images have produced mixed results. Here we use a novel analysis technique to provide additional evidence that changes can be detected in natural images without also being identified or localised. It is likely that this occurs by the observers monitoring the global properties of the scene. PMID:24454727

  19. Applications of the automatic change detection for disaster monitoring by the knowledge-based framework

    NASA Astrophysics Data System (ADS)

    Tadono, T.; Hashimoto, S.; Onosato, M.; Hori, M.

    2012-11-01

    Change detection is a fundamental approach in utilization of satellite remote sensing image, especially in multi-temporal analysis that involves for example extracting damaged areas by a natural disaster. Recently, the amount of data obtained by Earth observation satellites has increased significantly owing to the increasing number and types of observing sensors, the enhancement of their spatial resolution, and improvements in their data processing systems. In applications for disaster monitoring, in particular, fast and accurate analysis of broad geographical areas is required to facilitate efficient rescue efforts. It is expected that robust automatic image interpretation is necessary. Several algorithms have been proposed in the field of automatic change detection in past, however they are still lack of robustness for multi purposes, an instrument independency, and accuracy better than a manual interpretation. We are trying to develop a framework for automatic image interpretation using ontology-based knowledge representation. This framework permits the description, accumulation, and use of knowledge drawn from image interpretation. Local relationships among certain concepts defined in the ontology are described as knowledge modules and are collected in the knowledge base. The knowledge representation uses a Bayesian network as a tool to describe various types of knowledge in a uniform manner. Knowledge modules are synthesized and used for target-specified inference. The results applied to two types of disasters by the framework without any modification and tuning are shown in this paper.

  20. Interactive Change Detection Using High Resolution Remote Sensing Images Based on Active Learning with Gaussian Processes

    NASA Astrophysics Data System (ADS)

    Ru, Hui; Yu, Huai; Huang, Pingping; Yang, Wen

    2016-06-01

    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.

  1. A force measurement instrument for optical tweezers based on the detection of light momentum changes

    NASA Astrophysics Data System (ADS)

    Farré, Arnau; Marsà, Ferran; Montes-Usategui, Mario

    2014-09-01

    In this work, we present and discuss several developments implemented in an instrument that uses the detection of the light momentum change for measuring forces in an optical trap. A system based on this principle provides a direct determination of this magnitude regardless of the positional response of the sample under the effect of an external force, and it is therefore to be preferred when in situ calibrations of the trap stiffness are not attainable or are difficult to achieve. The possibility to obtain this information without relying upon a harmonic model of the force is more general and can be used in a wider range of situations. Forces can be measured on non-spherical samples or non-Gaussian beams, on complex and changing environments, such as the interior of cells, or on samples with unknown properties (size, viscosity, etc.). However, the practical implementation of the method entails some difficulties due to the strict conditions in the design and operation of an instrument based on this method. We have focused on some particularly conflicting points. We developed a process and a mechanism to determine and systematically set the correct axial position of the device. We further analyzed and corrected the non-uniform transmittance of the optical system and we finally compensated for the variations in the sensor responsivity with temperature. With all these improvements, we obtained an accuracy of ~5% in force measurements for samples of different kinds.

  2. Object based change detection of Central Asian Tugai vegetation with very high spatial resolution satellite imagery

    NASA Astrophysics Data System (ADS)

    Gärtner, Philipp; Förster, Michael; Kurban, Alishir; Kleinschmit, Birgit

    2014-09-01

    Ecological restoration of degraded riparian Tugai forests in north-western China is a key driver to combat desertification in this region. Recent restoration efforts attempt to recover the forest along with its most dominant tree species, Populus euphratica. The present research observed the response of natural vegetation using an object based change detection method on QuickBird (2005) and WorldView2 (2011) data. We applied the region growing approach to derived Normalized Difference Vegetation Index (NDVI) values in order to identify single P. euphratica trees, delineate tree crown areas and quantify crown diameter changes. Results were compared to 59 reference trees. The findings confirmed a positive tree crown growth and suggest a crown diameter increase of 1.14 m, on average. On a single tree basis, tree crown diameters of larger crowns were generally underestimated. Small crowns were slightly underestimated in QuickBird and overestimated in Worldview2 images. The results of the automated tree crown delineation show a moderate relation to field reference data with R20052: 0.36 and R20112: 0.48. The object based image analysis (OBIA) method proved to be applicable in sparse riparian Tugai forests and showed great suitability to evaluate ecological restoration efforts in an endangered ecosystem.

  3. Wavelet-based detection of abrupt changes in natural frequencies of time-variant systems

    NASA Astrophysics Data System (ADS)

    Dziedziech, K.; Staszewski, W. J.; Basu, B.; Uhl, T.

    2015-12-01

    Detection of abrupt changes in natural frequencies from vibration responses of time-variant systems is a challenging task due to the complex nature of physics involved. It is clear that the problem needs to be analysed in the combined time-frequency domain. The paper proposes an application of the input-output wavelet-based Frequency Response Function for this analysis. The major focus and challenge relate to ridge extraction of the above time-frequency characteristics. It is well known that classical ridge extraction procedures lead to ridges that are smooth. However, this property is not desired when abrupt changes in the dynamics are considered. The methods presented in the paper are illustrated using simulated and experimental multi-degree-of-freedom systems. The results are compared with the classical Frequency Response Function and with the output only analysis based on the wavelet auto-power response spectrum. The results show that the proposed method captures correctly the dynamics of the analysed time-variant systems.

  4. SAR-based change detection using hypothesis testing and Markov random field modelling

    NASA Astrophysics Data System (ADS)

    Cao, W.; Martinis, S.

    2015-04-01

    The objective of this study is to automatically detect changed areas caused by natural disasters from bi-temporal co-registered and calibrated TerraSAR-X data. The technique in this paper consists of two steps: Firstly, an automatic coarse detection step is applied based on a statistical hypothesis test for initializing the classification. The original analytical formula as proposed in the constant false alarm rate (CFAR) edge detector is reviewed and rewritten in a compact form of the incomplete beta function, which is a builtin routine in commercial scientific software such as MATLAB and IDL. Secondly, a post-classification step is introduced to optimize the noisy classification result in the previous step. Generally, an optimization problem can be formulated as a Markov random field (MRF) on which the quality of a classification is measured by an energy function. The optimal classification based on the MRF is related to the lowest energy value. Previous studies provide methods for the optimization problem using MRFs, such as the iterated conditional modes (ICM) algorithm. Recently, a novel algorithm was presented based on graph-cut theory. This method transforms a MRF to an equivalent graph and solves the optimization problem by a max-flow/min-cut algorithm on the graph. In this study this graph-cut algorithm is applied iteratively to improve the coarse classification. At each iteration the parameters of the energy function for the current classification are set by the logarithmic probability density function (PDF). The relevant parameters are estimated by the method of logarithmic cumulants (MoLC). Experiments are performed using two flood events in Germany and Australia in 2011 and a forest fire on La Palma in 2009 using pre- and post-event TerraSAR-X data. The results show convincing coarse classifications and considerable improvement by the graph-cut post-classification step.

  5. [Building Change Detection Based on Multi-Level Rules Classification with Airborne LiDAR Data and Aerial Images].

    PubMed

    Gong, Yi-long; Yan, Li

    2015-05-01

    The present paper proposes a new building change detection method combining Lidar point cloud with aerial image, using multi-level rules classification algorithm, to solve building change detection problem between these two kinds of heterogeneous data. Then, a morphological post-processing method combined with area threshold is proposed. Thus, a complete building change detection processing flow that can be applied to actual production is proposed. Finally, the effectiveness of the building change detection method is evaluated, processing the 2010 airborne LiDAR point cloud data and 2009 high resolution aerial image of Changchun City, Jilin province, China; in addition, compared with the object-oriented building change detection method based on support vector machine (SVM) classification, more analysis and evaluation of the suggested method is given. Experiment results show that the performance of the proposed building change detection method is ideal. Its Kappa index is 0. 90, and correctness is 0. 87, which is higher than the object-oriented building change detection method based on SVM classification. PMID:26415454

  6. Fluorescence-based DNA minisequence analysis for detection of known single-base changes in genomic DNA.

    PubMed

    Kobayashi, M; Rappaport, E; Blasband, A; Semeraro, A; Sartore, M; Surrey, S; Fortina, P

    1995-06-01

    We describe a rapid, automated method for direct detection of known single-base changes in genomic DNA. Fluorescence-based DNA minisequence analysis is employed in a template-dependent reaction which involves a single nucleotide extension of an oligonucleotide primer by the correct fluorescently-tagged dideoxynucleotide chain terminator. Detection following electrophoresis on denaturing acrylamide gels is facilitated by alkaline phosphatase treatment of reaction products after extension followed by isopropanol precipitation of the dye-tagged, single-base-extended primer to remove unincorporated deoxynucleotides. Fluorescence analysis of the incorporated dye tag reveals the identity of the template nucleotide immediately 3' to the primer site. This technique does not require radioactivity or biotinylated PCR product, relies on the incorporation of a single dideoxynucleotide terminator to extend the primer by one nucleotide and takes advantage of the sensitivity of fluorescent terminators developed for automated DNA sequence analysis. As a demonstration, we have applied the assay to human genomic DNA for detection of the sickle mutation in the beta-globin gene, and have also examined feasibility for simultaneous delineation using a multiplex-like strategy in a single gel-lane of some of the most common beta-thalassemia mutations in the Mediterranean basin. PMID:7477010

  7. [Primary Study on Noninvasive Detection of Vascular Function Based on Finger Temperature Change].

    PubMed

    Dong, Qing; Li, Xia; Wan, Yungao; Lu, Gaoquan; Wang, Xinxin; Zhang, Kuan

    2016-02-01

    By studying the relationship between fingertip temperature changes and arterial function during vascular reactivity test, we established a new non-invasive method for detecting vascular function, in order to provide an assistance for early diagnosis and prevention of cardiovascular diseases. We customized three modules respectively for blood occlusion, measurement of finger temperature and blood oxygen acquisition, and then we established the hardware of data acquisition system. And the software was programmed with Labview. Healthy subjects [group A, n = 24, (44.6 ± 9.0) years] and subjects with cardiovascular diseases [group B, n = 33, (57.2 ± 9.9) years)] were chosen for the study. Subject's finger temperature, blood oxygen and occlusion pressure of block side during and after unilateral arm brachial artery occlusion were recorded, as well as some other regular physiological indexes. By time-domain analysis, we extracted 12 parameters from fingertip temperature signal, including the initial temperature (Ti), temperature rebound (TR), the time of the temperature recovering to initial status (RIt) and other parameters from the finger temperature signal. We in the experiment also measured other regular physiological body mass index (BMI), systolic blood pressure (SBP), diastiolic blood pressure (DBP) and so on. Results showed that 8 parameters difference between the two group of data were significant. based on the statistical results. A discriminant function of vascular function status was established afterwards. We found in the study that the changes of finger temperature during unilateral arms brachial artery occlusion and open were closely related to vascular function. We hope that the method presented in this article could lay a foundation of early detection of vascular function. PMID:27382755

  8. Closed-form density-based framework for automatic detection of cellular morphology changes.

    PubMed

    Duong, Tarn; Goud, Bruno; Schauer, Kristine

    2012-05-29

    A primary method for studying cellular function is to examine cell morphology after a given manipulation. Fluorescent markers attached to proteins/intracellular structures of interest in conjunction with 3D fluorescent microscopy are frequently exploited for functional analysis. Despite the central role of morphology comparisons in cell biological approaches, few statistical tools are available that allow biological scientists without a high level of statistical training to quantify the similarity or difference of fluorescent images containing multifactorial information. We transform intracellular structures into kernels and develop a multivariate two-sample test that is nonparametric and asymptotically normal to directly and quantitatively compare cellular morphologies. The asymptotic normality bypasses the computationally intensive calculations used by the usual resampling techniques to compute the P-value. Because all parameters required for the statistical test are estimated directly from the data, it does not require any subjective decisions. Thus, we provide a black-box method for unbiased, automated comparison of cell morphology. We validate the performance of our test statistic for finite synthetic samples and experimental data. Employing our test for the comparison of the morphology of intracellular multivesicular bodies, we detect changes in their distribution after disruption of the cellular microtubule cytoskeleton with high statistical significance in fixed samples and live cell analysis. These results demonstrate that density-based comparison of multivariate image information is a powerful tool for automated detection of cell morphology changes. Moreover, the underlying mathematics of our test statistic is a general technique, which can be applied in situations where two data samples are compared. PMID:22586080

  9. An Unsupervised Change Detection Based on Test Statistic and KI from Multi-Temporal and Full Polarimetric SAR Images

    NASA Astrophysics Data System (ADS)

    Zhao, J. Q.; Yang, J.; Li, P. X.; Liu, M. Y.; Shi, Y. M.

    2016-06-01

    Accurate and timely change detection of Earth's surface features is extremely important for understanding relationships and interactions between people and natural phenomena. Many traditional methods of change detection only use a part of polarization information and the supervised threshold selection. Those methods are insufficiency and time-costing. In this paper, we present a novel unsupervised change-detection method based on quad-polarimetric SAR data and automatic threshold selection to solve the problem of change detection. First, speckle noise is removed for the two registered SAR images. Second, the similarity measure is calculated by the test statistic, and automatic threshold selection of KI is introduced to obtain the change map. The efficiency of the proposed method is demonstrated by the quad-pol SAR images acquired by Radarsat-2 over Wuhan of China.

  10. Effect of topographic correction on forest change detection using spectral trend analysis of Landsat pixel-based composites

    NASA Astrophysics Data System (ADS)

    Chance, Curtis M.; Hermosilla, Txomin; Coops, Nicholas C.; Wulder, Michael A.; White, Joanne C.

    2016-02-01

    Pixel-based image compositing enables production of large-area surface reflectance images that are largely devoid of clouds, cloud shadows, or haze. Change detection with spectral trend analysis uses a dense time series of images, such as pixel-based composites, to quantify the year, amount, and magnitude of landscape changes. Topographically-related shadows found in mountainous terrain may confound trend-based forest change detection approaches. In this study, we evaluate the impact of topographic correction on trend-based forest change detection outcomes by comparing the amount and location of changes identified on an image composite with and without a topographic correction. Moreover, we evaluated two different approaches to topographic correction that are relevant to pixel-based image composites: the first corrects each pixel according to the day of year (DOY) the pixel was acquired, whilst the second corrects all pixels to a single reference date (August 1st), which was also the target date for generating the pixel-based image composite. Our results indicate that a greater area of change is detected when no topographic correction is applied to the image composite, however, the difference in change area detected between no correction and either the DOY or the August 1st correction is minor and less than 1% (0.54-0.85%). The spatial correspondence of these different approaches is 96.2% for the DOY correction and 97.7% for the August 1st correction. The largest differences between the correction processes occur in valleys (0.71-1.14%), upper slopes (0.71-1.09%), and ridges (0.73-1.09%). While additional tests under different conditions and in other environments are encouraged, our results indicate that topographic correction may not be justified in change detection routines computing spectral trends from pixel-based composites.

  11. Land Cover Change Detection Based on Genetically Feature Aelection and Image Algebra Using Hyperion Hyperspectral Imagery

    NASA Astrophysics Data System (ADS)

    Seydi, S. T.; Hasanlou, M.

    2015-12-01

    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.

  12. Change detection based on the high-resolution remote sensing images

    NASA Astrophysics Data System (ADS)

    Zhou, Junqi; Sun, Jiabing; Zhang, Hong

    2005-10-01

    With the development of remote sensing technology, satellites can collect high spatial resolution images such as SPOT-5 and Quickbird. The SPOT-5 satellite simultaneously collects 5-m panchromatic and 10-m multispectral images, after interpolated in ground station 2.5-m panchromatic image can be provided (5 metres ground resolution in panchromatic mode and 2.5 metres in supermode). The Quick bird satellite simultaneously collects 0.61-m panchromatic and 2.44-m multispectral images. With Images Merged of 2.5-m panchromatic and 10-m multispectral images of SPOT-5, the approximate resolution images as Quick bird multispectral images were acquired. These images acquired with different satellites can be used to detect the change of urban. In this paper, the images of Wuhan University in China acquired with SPOT-5 and Quick bird are used to detect the change of trees in different season. The result shows it is possible to detect the change of trees and some factors that affect the change detection are listed.

  13. Automatic co-registration of space-based sensors for precision change detection and analysis

    NASA Technical Reports Server (NTRS)

    Bryant, N.; Zobrist, A.; Logan, T.

    2003-01-01

    A variety of techniques were developed at JPL to assure sub-pixel co-registration of scenes and ortho-rectification of satellite imagery to other georeferenced information to permit precise change detection and analysis of low and moderate resolution space sensors.

  14. A ground-based trace gas observing system for detection of Arctic and Boreal change

    NASA Astrophysics Data System (ADS)

    Karion, A.; Miller, J. B.; Sweeney, C.; Bruhwiler, L.; Newberger, T.; Miller, C. E.; Dinardo, S. J.; Wolter, S.; Ledlow, L.

    2012-12-01

    The large reservoir of below-ground organic carbon in the Arctic and Boreal region (ABR) permafrost, combined with large observed and predicted temperature changes leads to the expectation of increasing surface emissions of CO2 and/or CH4 this century. However, the near-term response of northern ecosystems could be enhanced ecosystem productivity and carbon sequestration via, among other causes, longer growing seasons and encroachment of woody species into Arctic tundra. Regardless of the temporal evolution of carbon (both CO2 and CH4) sources and sinks in the ABR, monitoring these changes at regional (~10^5 - 10^6 km^2) scales using trace gas mixing and isotopic ratios will be a critical complement to detailed process-based studies at the plot scale and remote sensing of the land surface. Turbulent mixing in the lower few kilometers of the atmosphere naturally integrates emissions from all known and unknown processes and can provide a powerful bottom-line constraint on the net result of both sources and sinks. We will present the first year of results of a trace-gas measurement system capable of daily or more frequent observations of more than 50 trace gas species, including CO2, CH4 and their stable and radio isotope ratios. The measurements were initiated as part of the Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE) and come from a 30 m tower located on a ridge in central Alaska. Central Alaska is dominated by discontinuous permafrost, which is likely to undergo significant changes in the coming decades. Footprint analysis suggests that mixing ratios measured at the tower are influenced by large swaths of central Alaska, although in winter, anthropogenic emissions form the city of Fairbanks are evident. In summer, as expected, we observe a large drawdown of CO2. The seasonal cycle of CH4 is dominated by the large-scale destruction of methane by hydroxyl radical (OH). However, based on previous measurements from other ABR sites, we expect summer

  15. [The Change Detection of High Spatial Resolution Remotely Sensed Imagery Based on OB-HMAD Algorithm and Spectral Features].

    PubMed

    Chen, Qiang; Chen, Yun-hao; Jiang, Wei-guo

    2015-06-01

    The high spatial resolution remotely sensed imagery has abundant detailed information of earth surface, and the multi-temporal change detection for the high resolution remotely sensed imagery can realize the variations of geographical unit. In terms of the high spatial resolution remotely sensed imagery, the traditional remote sensing change detection algorithms have obvious defects. In this paper, learning from the object-based image analysis idea, we proposed a semi-automatic threshold selection algorithm named OB-HMAD (object-based-hybrid-MAD), on the basis of object-based image analysis and multivariate alternative detection algorithm (MAD), which used the spectral features of remotely sensed imagery into the field of object-based change detection. Additionally, OB-HMAD algorithm has been compared with other the threshold segmentation algorithms by the change detection experiment. Firstly, we obtained the image object by the multi-solution segmentation algorithm. Secondly, we got the object-based difference image object using MAD and minimum noise fraction rotation (MNF) for improving the SNR of the image object. Then, the change objects or area are classified using histogram curvature analysis (HCA) method for the semi-automatic threshold selection, which determined the threshold by calculated the maximum value of curvature of the histogram, so the HCA algorithm has better automation than other threshold segmentation algorithms. Finally, the change detection results are validated using confusion matrix with the field sample data. Worldview-2 imagery of 2012 and 2013 in case study of Beijing were used to validate the proposed OB-HMAD algorithm. The experiment results indicated that OB-HMAD algorithm which integrated the multi-channel spectral information could be effectively used in multi-temporal high resolution remotely sensed imagery change detection, and it has basically solved the "salt and pepper" problem which always exists in the pixel-based change

  16. Age-Related Changes in Expectation-Based Modulation of Motion Detectability

    PubMed Central

    Zanto, Theodore P.; Sekuler, Robert; Dube, Chad; Gazzaley, Adam

    2013-01-01

    Expecting motion in some particular direction biases sensitivity to that direction, which speeds detection of motion. However, the neural processes underlying this effect remain underexplored, especially in the context of normal aging. To address this, we examined younger and older adults' performance in a motion detection task. In separate conditions, the probability was either 50% or 100% that a field of dots would move coherently in the direction a participant expected (either vertically or horizontally). Expectation and aging effects were assessed via response times (RT) to detect motion and electroencephalography (EEG). In both age groups, RTs were fastest when motion was similar to the expected direction of motion. RT tuning curves exhibited a characteristic U-shape such that detection time increased with an increasing deviation from the participant's expected direction. Strikingly, EEG results showed an analogous, hyperbolic curve for N1 amplitude, reflecting neural biasing. Though the form of behavioral and EEG curves did not vary with age, older adults displayed a clear decline in the speed of detection and a corresponding reduction in EEG N1 amplitude when horizontal (but not vertical) motion was expected. Our results suggest that expectation-based detection ability varies with age and, for older adults, also with axis of motion. PMID:23950903

  17. Conditionally fluorescent molecular probes for detecting single base changes in double-stranded DNA

    NASA Astrophysics Data System (ADS)

    Chen, Sherry Xi; Zhang, David Yu; Seelig, Georg

    2013-09-01

    Small variations in nucleic acid sequences can have far-reaching phenotypic consequences. Reliably distinguishing closely related sequences is therefore important for research and clinical applications. Here, we demonstrate that conditionally fluorescent DNA probes are capable of distinguishing variations of a single base in a stretch of target DNA. These probes use a novel programmable mechanism in which each single nucleotide polymorphism generates two thermodynamically destabilizing mismatch bubbles rather than the single mismatch formed during typical hybridization-based assays. Up to a 12,000-fold excess of a target that contains a single nucleotide polymorphism is required to generate the same fluorescence as one equivalent of the intended target, and detection works reliably over a wide range of conditions. Using these probes we detected point mutations in a 198 base-pair subsequence of the Escherichia coli rpoB gene. That our probes are constructed from multiple oligonucleotides circumvents synthesis limitations and enables long continuous DNA sequences to be probed.

  18. SAR change detection MTI

    NASA Astrophysics Data System (ADS)

    Scarborough, Steven; Lemanski, Christopher; Nichols, Howard; Owirka, Gregory; Minardi, Michael; Hale, Todd

    2006-05-01

    This paper examines the theory, application, and results of using single-channel synthetic aperture radar (SAR) data with Moving Reference Processing (MRP) to focus and geolocate moving targets. Moving targets within a standard SAR imaging scene are defocused, displaced, or completely missing in the final image. Building on previous research at AFRL, the SAR-MRP method focuses and geolocates moving targets by reprocessing the SAR data to focus the movers rather than the stationary clutter. SAR change detection is used so that target detection and focusing is performed more robustly. In the cases where moving target returns possess the same range versus slow-time histories, a geolocation ambiguity results. This ambiguity can be resolved in a number of ways. This paper concludes by applying the SAR-MRP method to high-frequency radar measurements from persistent continuous-dwell SAR observations of a moving target.

  19. Blind phone segmentation based on spectral change detection using Legendre polynomial approximation.

    PubMed

    Hoang, Dac-Thang; Wang, Hsiao-Chuan

    2015-02-01

    Phone segmentation involves partitioning a continuous speech signal into discrete phone units. In this paper, a method for automatic phone segmentation without prior knowledge of speech content is proposed. The signal spectrum was represented by band-energies. A segment of the band-energy curve was approximated using Legendre polynomial expansion, allowing Legendre polynomial coefficients to describe the properties of the segment. The spectral changes, which imply phone boundaries in the speech signal, were then detected by monitoring the variations of Legendre polynomial coefficients. A two-step algorithm for detecting phone boundaries was derived. The first step was to detect phone boundaries using first-order and second-order coefficients of the Legendre polynomial approximation. The second step was to locate slow spectral changes in the regions of concatenated voiced phones using zero-order coefficients of the Legendre polynomial approximation. This enabled the phone boundaries missed during the first step to be recovered. An evaluation using the TIMIT corpus indicated that the proposed method is comparable to or more accurate than previous methods. PMID:25698014

  20. Time-Based Retrieval of Soft Maps for Environmental Change Detection.

    ERIC Educational Resources Information Center

    Carrara, Paola; Fresta, Giuseppe; Rampini, Anna

    2003-01-01

    Discusses the need for tools that analyze Earth changes in time ranges, and describes a data structure for creating and managing archives of thematic maps derived by classifying remotely sensed images by soft techniques (soft maps). Considers time-based models and provides an example of the new data structure. (Author/LRW)

  1. Change Detection: Training and Transfer

    PubMed Central

    Gaspar, John G.; Neider, Mark B.; Simons, Daniel J.; McCarley, Jason S.; Kramer, Arthur F.

    2013-01-01

    Observers often fail to notice even dramatic changes to their environment, a phenomenon known as change blindness. If training could enhance change detection performance in general, then it might help to remedy some real-world consequences of change blindness (e.g. failing to detect hazards while driving). We examined whether adaptive training on a simple change detection task could improve the ability to detect changes in untrained tasks for young and older adults. Consistent with an effective training procedure, both young and older adults were better able to detect changes to trained objects following training. However, neither group showed differential improvement on untrained change detection tasks when compared to active control groups. Change detection training led to improvements on the trained task but did not generalize to other change detection tasks. PMID:23840775

  2. Delamination detection in composite laminates using dispersion change based on mode conversion of Lamb waves

    NASA Astrophysics Data System (ADS)

    Okabe, Yoji; Fujibayashi, Keiji; Shimazaki, Mamoru; Soejima, Hideki; Ogisu, Toshimichi

    2010-11-01

    A new ultrasonic propagation system has been constructed using macrofiber composite (MFC) actuators and fiber Bragg grating (FBG) sensors. The MFCs and FBGs can be integrated into composite laminates because of their small size and high fracture strain. The developed system can send and receive broadband Lamb waves. In this research, this system was used to detect delamination damage in composite laminates. First, the multiple modes of Lamb waves in a carbon-fiber-reinforced plastic (CFRP) quasi-isotropic laminate were identified by transmitting and receiving the symmetric and antisymmetric modes separately. Then, the mode conversions at both tips of a delamination were investigated through an experiment and a two-dimensional finite element analysis (FEA). A new delamination detection method was proposed on the basis of the mode conversions, and experiments were carried out on laminates with an artificial delamination. When antisymmetric modes were excited, the frequency dispersion of the received A1 mode changed, depending on the delamination length owing to the mode conversion between the A1 mode and the S0 mode. This phenomenon was confirmed through the FEA and these results prove that this new method is effective in detecting a delamination in CFRP laminates.

  3. Change detection based on deep feature representation and mapping transformation for multi-spatial-resolution remote sensing images

    NASA Astrophysics Data System (ADS)

    Zhang, Puzhao; Gong, Maoguo; Su, Linzhi; Liu, Jia; Li, Zhizhou

    2016-06-01

    Multi-spatial-resolution change detection is a newly proposed issue and it is of great significance in remote sensing, environmental and land use monitoring, etc. Though multi-spatial-resolution image-pair are two kinds of representations of the same reality, they are often incommensurable superficially due to their different modalities and properties. In this paper, we present a novel multi-spatial-resolution change detection framework, which incorporates deep-architecture-based unsupervised feature learning and mapping-based feature change analysis. Firstly, we transform multi-resolution image-pair into the same pixel-resolution through co-registration, followed by details recovery, which is designed to remedy the spatial details lost in the registration. Secondly, the denoising autoencoder is stacked to learn local and high-level representation/feature from the local neighborhood of the given pixel, in an unsupervised fashion. Thirdly, motivated by the fact that multi-resolution image-pair share the same reality in the unchanged regions, we try to explore the inner relationships between them by building a mapping neural network. And it can be used to learn a mapping function based on the most-unlikely-changed feature-pairs, which are selected from all the feature-pairs via a coarse initial change map generated in advance. The learned mapping function can bridge the different representations and highlight changes. Finally, we can build a robust and contractive change map through feature similarity analysis, and the change detection result is obtained through the segmentation of the final change map. Experiments are carried out on four real datasets, and the results confirmed the effectiveness and superiority of the proposed method.

  4. Space-based detection of wetlands' surface water level changes from L-band SAR interferometry

    USGS Publications Warehouse

    Wdowinski, S.; Kim, S.-W.; Amelung, F.; Dixon, T.H.; Miralles-Wilhelm, F.; Sonenshein, R.

    2008-01-01

    Interferometric processing of JERS-1 L-band Synthetic Aperture Radar (SAR) data acquired over south Florida during 1993-1996 reveals detectable surface changes in the Everglades wetlands. Although our study is limited to south Florida it has implication for other large-scale wetlands, because south Florida wetlands have diverse vegetation types and both managed and natural flow environments. Our analysis reveals that interferometric coherence level is sensitive to wetland vegetation type and to the interferogram time span. Interferograms with time spans less than six months maintain phase observations for all wetland types, allowing characterization of water level changes in different wetland environments. The most noticeable changes occur between the managed and the natural flow wetlands. In the managed wetlands, fringes are organized, follow patterns related to some of the managed water control structures and have high fringe-rate. In the natural flow areas, fringes are irregular and have a low fringe-rate. The high fringe rate in managed areas reflects dynamic water topography caused by high flow rate due to gate operation. Although this organized fringe pattern is not characteristic of most large-scale wetlands, the high level of water level change enables accurate estimation of the wetland InSAR technique, which lies in the range of 5-10??cm. The irregular and low rate fringe pattern in the natural flow area reflects uninterrupted flow that diffuses water efficiently and evenly. Most of the interferograms in the natural flow area show an elongated fringe located along the transitional zone between salt- and fresh-water wetlands, reflecting water level changes due to ocean tides. ?? 2007 Elsevier Inc. All rights reserved.

  5. Researches on the Land-Use Change Detection of Mine Area Based on Tm/etm Images

    NASA Astrophysics Data System (ADS)

    Qin, Y.; Liling, H.; Min, Y.; Yi, L.

    2013-07-01

    With the economic development and population growth, land use status is changing rapidly in Chinese urban. Since the remote sensing technology can analyze and detect the land use information quickly and accurately, it has been widely applied to obtain the land use/land cover change (LUCC) information today. The land surface destroy occurred in mineral resources exploration will result in a lot of environmental problems in coal mine areas. But there are few research in small and medium-sized cities and coal mine areas. So Peixian is used as the study area in the paper. The Landsat TM/ETM images spanning 3 years and thematic map are adopted to detect the land-use change of the area. In order to improve the classification results, we built an optimized classification model adapting classic SVM method, which was defined "a feature weighted SVM classifier using mixed kernel function". Based on geostatistic and multi-scale statistical knowledge, we calculated the transformation matrix and dynamic index of land-use types, from which we conducted quantitative analysis and the driving force on the mine land-use change of Peixian. Then, we can achieve resource dynamic change detection of four years in Peixian area, analyze the effect of the surface land-use change due to mineral exploration and obtain the causes of land-use change.

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

    PubMed

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

    2016-01-01

    Visual working memory (VWM) is a key cognitive system that enables people to hold visual information in mind after a stimulus has been removed and compare past and present to detect changes that have occurred. VWM is severely capacity limited to around 3-4 items, although there are robust individual differences in this limit. Importantly, these individual differences are evident in neural measures of VWM capacity. Here, we capitalized on recent work showing that capacity is lower for more complex stimulus dimension. In particular, we asked whether individual differences in capacity remain consistent if capacity is shifted by a more demanding task, and, further, whether the correspondence between behavioral and neural measures holds across a shift in VWM capacity. Participants completed a change detection (CD) task with simple colors and complex shapes in an fMRI experiment. As expected, capacity was significantly lower for the shape dimension. Moreover, there were robust individual differences in behavioral estimates of VWM capacity across dimensions. Similarly, participants with a stronger BOLD response for color also showed a strong neural response for shape within the lateral occipital cortex, intraparietal sulcus (IPS), and superior IPS. Although there were robust individual differences in the behavioral and neural measures, we found little evidence of systematic brain-behavior correlations across feature dimensions. This suggests that behavioral and neural measures of capacity provide different views onto the processes that underlie VWM and CD. Recent theoretical approaches that attempt to bridge between behavioral and neural measures are well positioned to address these findings in future work. PMID:27147986

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

    PubMed Central

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

    2016-01-01

    Visual working memory (VWM) is a key cognitive system that enables people to hold visual information in mind after a stimulus has been removed and compare past and present to detect changes that have occurred. VWM is severely capacity limited to around 3–4 items, although there are robust individual differences in this limit. Importantly, these individual differences are evident in neural measures of VWM capacity. Here, we capitalized on recent work showing that capacity is lower for more complex stimulus dimension. In particular, we asked whether individual differences in capacity remain consistent if capacity is shifted by a more demanding task, and, further, whether the correspondence between behavioral and neural measures holds across a shift in VWM capacity. Participants completed a change detection (CD) task with simple colors and complex shapes in an fMRI experiment. As expected, capacity was significantly lower for the shape dimension. Moreover, there were robust individual differences in behavioral estimates of VWM capacity across dimensions. Similarly, participants with a stronger BOLD response for color also showed a strong neural response for shape within the lateral occipital cortex, intraparietal sulcus (IPS), and superior IPS. Although there were robust individual differences in the behavioral and neural measures, we found little evidence of systematic brain-behavior correlations across feature dimensions. This suggests that behavioral and neural measures of capacity provide different views onto the processes that underlie VWM and CD. Recent theoretical approaches that attempt to bridge between behavioral and neural measures are well positioned to address these findings in future work. PMID:27147986

  8. Detection of Subtle Cognitive Changes after mTBI Using a Novel Tablet-Based Task.

    PubMed

    Fischer, Tara D; Red, Stuart D; Chuang, Alice Z; Jones, Elizabeth B; McCarthy, James J; Patel, Saumil S; Sereno, Anne B

    2016-07-01

    This study examined the potential for novel tablet-based tasks, modeled after eye tracking techniques, to detect subtle sensorimotor and cognitive deficits after mild traumatic brain injury (mTBI). Specifically, we examined whether performance on these tablet-based tasks (Pro-point and Anti-point) was able to correctly categorize concussed versus non-concussed participants, compared with performance on other standardized tests for concussion. Patients admitted to the emergency department with mTBI were tested on the Pro-point and Anti-point tasks, a current standard cognitive screening test (i.e., the Standard Assessment of Concussion [SAC]), and another eye movement-based tablet test, the King-Devick(®) (KD). Within hours after injury, mTBI patients showed significant slowing in response times, compared with both orthopedic and age-matched control groups, in the Pro-point task, demonstrating deficits in sensorimotor function. Mild TBI patients also showed significant slowing, compared with both control groups, on the Anti-point task, even when controlling for sensorimotor slowing, indicating deficits in cognitive function. Performance on the SAC test revealed similar deficits of cognitive function in the mTBI group, compared with the age-matched control group; however, the KD test showed no evidence of cognitive slowing in mTBI patients, compared with either control group. Further, measuring the sensitivity and specificity of these tasks to accurately predict mTBI with receiver operating characteristic analysis indicated that the Anti-point and Pro-point tasks reached excellent levels of accuracy and fared better than current standardized tools for assessment of concussion. Our findings suggest that these rapid tablet-based tasks are able to reliably detect and measure functional impairment in cognitive and sensorimotor control within hours after mTBI. These tasks may provide a more sensitive diagnostic measure for functional deficits that could prove key to

  9. The Development of Change Detection

    ERIC Educational Resources Information Center

    Shore, David I.; Burack, Jacob A.; Miller, Danny; Joseph, Shari; Enns, James T.

    2006-01-01

    Changes to a scene often go unnoticed if the objects of the change are unattended, making change detection an index of where attention is focused during scene perception. We measured change detection in school-age children and young adults by repeatedly alternating two versions of an image. To provide an age-fair assessment we used a bimanual…

  10. Genetic Particle Swarm Optimization-Based Feature Selection for Very-High-Resolution Remotely Sensed Imagery Object Change Detection.

    PubMed

    Chen, Qiang; Chen, Yunhao; Jiang, Weiguo

    2016-01-01

    In the field of multiple features Object-Based Change Detection (OBCD) for very-high-resolution remotely sensed images, image objects have abundant features and feature selection affects the precision and efficiency of OBCD. Through object-based image analysis, this paper proposes a Genetic Particle Swarm Optimization (GPSO)-based feature selection algorithm to solve the optimization problem of feature selection in multiple features OBCD. We select the Ratio of Mean to Variance (RMV) as the fitness function of GPSO, and apply the proposed algorithm to the object-based hybrid multivariate alternative detection model. Two experiment cases on Worldview-2/3 images confirm that GPSO can significantly improve the speed of convergence, and effectively avoid the problem of premature convergence, relative to other feature selection algorithms. According to the accuracy evaluation of OBCD, GPSO is superior at overall accuracy (84.17% and 83.59%) and Kappa coefficient (0.6771 and 0.6314) than other algorithms. Moreover, the sensitivity analysis results show that the proposed algorithm is not easily influenced by the initial parameters, but the number of features to be selected and the size of the particle swarm would affect the algorithm. The comparison experiment results reveal that RMV is more suitable than other functions as the fitness function of GPSO-based feature selection algorithm. PMID:27483285

  11. Detecting and Predicting Changes

    ERIC Educational Resources Information Center

    Brown, Scott D.; Steyvers, Mark

    2009-01-01

    When required to predict sequential events, such as random coin tosses or basketball free throws, people reliably use inappropriate strategies, such as inferring temporal structure when none is present. We investigate the ability of observers to predict sequential events in dynamically changing environments, where there is an opportunity to detect…

  12. A Method Based on Radiative Cooling for Detecting Structural Changes in Undercooled Metallic Liquids

    NASA Technical Reports Server (NTRS)

    Rulison, Aaron J.; Rhim, Won-Kyu

    1995-01-01

    We introduce a structure-sensitive parameter for undercooled melts which can be measured in containerless processing experiments. We have established that the ratio, R(T), of hemispherical total emissivity epsilon(sub T)(T) to constant-pressure specific heat c(sub p)(T) can serve as an indicator which is sensitive to any changes in short range atomic order in undercooled metallic melts. R(T) (triple bonds) epsilon(sub T)(T)/c(sub p)(T) values for nickel, zirconium, and silicon have been obtained using the high temperature electrostatic levitator while the levitated melts were undergoing purely radiative cooling into the deeply undercooled region. R(T) plots for undercooled liquid nickel and zirconium indicate no significant change in short-range structure from their melting temperatures to 15% undercooling. In contrast, liquid silicon shows marked short-range structural changes beginning above its melting temperature and extending throughout the undercooled region. The short-range structure of liquid silicon is related to the highly-directional covalent bonding which characterizes its solid form. The nickel and zirconium data show that epsilon(sub T) varies linearly with T, in support of metal emissivity theories.

  13. Optimum electrode configuration selection for electrical resistance change based damage detection in composites using an effective independence measure

    NASA Astrophysics Data System (ADS)

    Escalona, Luis; Díaz-Montiel, Paulina; Venkataraman, Satchi

    2016-04-01

    Laminated carbon fiber reinforced polymer (CFRP) composite materials are increasingly used in aerospace structures due to their superior mechanical properties and reduced weight. Assessing the health and integrity of these structures requires non-destructive evaluation (NDE) techniques to detect and measure interlaminar delamination and intralaminar matrix cracking damage. The electrical resistance change (ERC) based NDE technique uses the inherent changes in conductive properties of the composite to characterize internal damage. Several works that have explored the ERC technique have been limited to thin cross-ply laminates with simple linear or circular electrode arrangements. This paper investigates a method of optimum selection of electrode configurations for delamination detection in thick cross-ply laminates using ERC. Inverse identification of damage requires numerical optimization of the measured response with a model predicted response. Here, the electrical voltage field in the CFRP composite laminate is calculated using finite element analysis (FEA) models for different specified delamination size and locations, and location of ground and current electrodes. Reducing the number of sensor locations and measurements is needed to reduce hardware requirements, and computational effort needed for inverse identification. This paper explores the use of effective independence (EI) measure originally proposed for sensor location optimization in experimental vibration modal analysis. The EI measure is used for selecting the minimum set of resistance measurements among all possible combinations of selecting a pair of electrodes among the n electrodes. To enable use of EI to ERC required, it is proposed in this research a singular value decomposition SVD to obtain a spectral representation of the resistance measurements in the laminate. The effectiveness of EI measure in eliminating redundant electrode pairs is demonstrated by performing inverse identification of

  14. Change Detection via Morphological Comparative Filters

    NASA Astrophysics Data System (ADS)

    Vizilter, Y. V.; Rubis, A. Y.; Zheltov, S. Y.; Vygolov, O. V.

    2016-06-01

    In this paper we propose the new change detection technique based on morphological comparative filtering. This technique generalizes the morphological image analysis scheme proposed by Pytiev. A new class of comparative filters based on guided contrasting is developed. Comparative filtering based on diffusion morphology is implemented too. The change detection pipeline contains: comparative filtering on image pyramid, calculation of morphological difference map, binarization, extraction of change proposals and testing change proposals using local morphological correlation coefficient. Experimental results demonstrate the applicability of proposed approach.

  15. A Critique of Patch-Based Landscape Indicators for Detection of Temporal Change in Fragmentation

    EPA Science Inventory

    Since O’Neill et al. (1988), analysis of landscape indicators based on measurements from land-cover maps has been a core area of research in landscape ecology. Landscape indicator research has focused on development of new measurements, statistical properties, and indictor behav...

  16. Airborne hyperspectral detection of small changes.

    PubMed

    Eismann, Michael T; Meola, Joseph; Stocker, Alan D; Beaven, Scott G; Schaum, Alan P

    2008-10-01

    Hyperspectral change detection offers a promising approach to detect objects and features of remotely sensed areas that are too difficult to find in single images, such as slight changes in land cover and the insertion, deletion, or movement of small objects, by exploiting subtle differences in the imagery over time. Methods for performing such change detection, however, must effectively maintain invariance to typically larger image-to-image changes in illumination and environmental conditions, as well as misregistration and viewing differences between image observations, while remaining sensitive to small differences in scene content. Previous research has established predictive algorithms to overcome such natural changes between images, and these approaches have recently been extended to deal with space-varying changes. The challenges to effective change detection, however, are often exacerbated in an airborne imaging geometry because of the limitations in control over flight conditions and geometry, and some of the recent change detection algorithms have not been demonstrated in an airborne setting. We describe the airborne implementation and relative performance of such methods. We specifically attempt to characterize the effects of spatial misregistration on change detection performance, the efficacy of class-conditional predictors in an airborne setting, and extensions to the change detection approach, including physically motivated shadow transition classifiers and matched change filtering based on in-scene atmospheric normalization. PMID:18830283

  17. Detecting Driver Mental Fatigue Based on EEG Alpha Power Changes during Simulated Driving

    PubMed Central

    GHARAGOZLOU, Faramarz; NASL SARAJI, Gebraeil; MAZLOUMI, Adel; NAHVI, Ali; MOTIE NASRABADI, Ali; RAHIMI FOROUSHANI, Abbas; ARAB KHERADMAND, Ali; ASHOURI, Mohammadreza; SAMAVATI, Mehdi

    2015-01-01

    Background: Driver fatigue is one of the major implications in transportation safety and accounted for up to 40% of road accidents. This study aimed to analyze the EEG alpha power changes in partially sleep-deprived drivers while performing a simulated driving task. Methods: Twelve healthy male car drivers participated in an overnight study. Continuous EEG and EOG records were taken during driving on a virtual reality simulator on a monotonous road. Simultaneously, video recordings from the driver face and behavior were performed in lateral and front views and rated by two trained observers. Moreover, the subjective self-assessment of fatigue was implemented in every 10-min interval during the driving using Fatigue Visual Analog Scale (F-VAS). Power spectrum density and fast Fourier transform (FFT) were used to determine the absolute and relative alpha powers in the initial and final 10 minutes of driving. Results: The findings showed a significant increase in the absolute alpha power (P = 0.006) as well as F-VAS scores during the final section of driving (P = 0.001). Meanwhile, video ratings were consistent with subjective self-assessment of fatigue. Conclusion: The increase in alpha power in the final section of driving indicates the decrease in the level of alertness and attention and the onset of fatigue, which was consistent with F-VAS and video ratings. The study suggested that variations in alpha power could be a good indicator for driver mental fatigue, but for using as a countermeasure device needed further investigations. PMID:26811821

  18. Luminescence detection of cysteine based on Ag⁺-mediated conformational change of terbium ion-promoted G-quadruplex.

    PubMed

    Tan, Hongliang; Tang, Gonge; Ma, Chanjiao; Li, Qian

    2016-02-18

    In this work, we developed a simple and sensitive method for the detection of cysteine (Cys) by employing terbium ion (Tb(3+))-promoted G-qudraplex (G4/Tb) as a luminescent probe, which is based on Ag(+)-mediated conformational change of G4/Tb. Due to Ag(+) is able to compete with Tb(3+) to bind guanine at G4, the presence of Ag(+) can lead to the formation of G4/Tb-Ag(+) complex and disrupt the structure of G4/Tb. Meanwhile, the binding of Ag(+) with G4/Tb will also cause the alteration of the excited state of G4 and more efficient energy transfer from G4 to Tb(3+), enhancing the luminescence of G4/Tb. However, upon the addition of Cys, Ag(+) will be released from G4/Tb-Ag(+) complex because of the high affinity of Cys to Ag(+). This results in the re-formation of the conformation of G4/Tb and the decrease of the luminescence of G4/Tb. So, Ag(+)-enhanced luminescence of G4/Tb is associated with its conformational transformation. As a luminescent probe for Cys, G4/Tb not only shows excellent selectivity and sensitivity with a detection limit of 20 nM, but also possesses the features of simple preparation, easy reproducibility, and eliminating the interferences from background fluorescence. We envision that the presented strategy might provide new insight into the biosensing applications of lanthanide complex. PMID:26826698

  19. Image Change Detection via Ensemble Learning

    SciTech Connect

    Martin, Benjamin W; Vatsavai, Raju

    2013-01-01

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

  20. Multisensor Fusion for Change Detection

    NASA Astrophysics Data System (ADS)

    Schenk, T.; Csatho, B.

    2005-12-01

    Combining sensors that record different properties of a 3-D scene leads to complementary and redundant information. If fused properly, a more robust and complete scene description becomes available. Moreover, fusion facilitates automatic procedures for object reconstruction and modeling. For example, aerial imaging sensors, hyperspectral scanning systems, and airborne laser scanning systems generate complementary data. We describe how data from these sensors can be fused for such diverse applications as mapping surface erosion and landslides, reconstructing urban scenes, monitoring urban land use and urban sprawl, and deriving velocities and surface changes of glaciers and ice sheets. An absolute prerequisite for successful fusion is a rigorous co-registration of the sensors involved. We establish a common 3-D reference frame by using sensor invariant features. Such features are caused by the same object space phenomena and are extracted in multiple steps from the individual sensors. After extracting, segmenting and grouping the features into more abstract entities, we discuss ways on how to automatically establish correspondences. This is followed by a brief description of rigorous mathematical models suitable to deal with linear and area features. In contrast to traditional, point-based registration methods, lineal and areal features lend themselves to a more robust and more accurate registration. More important, the chances to automate the registration process increases significantly. The result of the co-registration of the sensors is a unique transformation between the individual sensors and the object space. This makes spatial reasoning of extracted information more versatile; reasoning can be performed in sensor space or in 3-D space where domain knowledge about features and objects constrains reasoning processes, reduces the search space, and helps to make the problem well-posed. We demonstrate the feasibility of the proposed multisensor fusion approach

  1. Comparison of pixel -based and artificial neural networks classification methods for detecting forest cover changes in Malaysia

    NASA Astrophysics Data System (ADS)

    Deilmai, B. R.; Kanniah, K. D.; Rasib, A. W.; Ariffin, A.

    2014-02-01

    According to the FAO (Food and Agriculture Organization), Malaysia lost 8.6% of its forest cover between 1990 and 2005. In forest cover change detection, remote sensing plays an important role. A lot of change detection methods have been developed, and most of them are semi-automated. These methods are time consuming and difficult to apply. One of the new and robust methods for change detection is artificial neural network (ANN). In this study, (ANN) classification scheme is used to detect the forest cover changes in the Johor state in Malaysia. Landsat Thematic Mapper images covering a period of 9 years (2000 and 2009) are used. Results obtained with ANN technique was compared with Maximum likelihood classification (MLC) to investigate whether ANN can perform better in the tropical environment. Overall accuracy of the ANN and MLC techniques are 75%, 68% (2000) and 80%, 75% (2009) respectively. Using the ANN method, it was found that forest area in Johor decreased as much as 1298 km2 between 2000 and 2009. The results also showed the potential and advantages of neural network in classification and change detection analysis.

  2. High-Resolution Antarctic Ice Shelves Change Detection Based on Time-Series Envisat Asar Data (2005-2012)

    NASA Astrophysics Data System (ADS)

    Cheng, X.; Liu, Y.; Hui, F.

    2012-12-01

    Antarctic ice shelves are most important parts of ice sheets due to their ice-ocean-atmosphere interface and their vulnerability to regional and global changes in atmospheric and oceanic temperatures. The majority of mass loss from the Antarctic ice sheet occurs at the ice shelves via either iceberg calving or basal melting. For most study of the Ice shelf change detection, MODIS or NOAA data at 1km level resolution are used. In order to fully understand the complex process of ice shelf mass balance, it is very necessary to monitor the ice shelf changes over an extended period of time using high-resolution remote sensing data. We developed an automatic system to fulfill the purposes, from data downloading, pre-process, precise processing to automatic change detection. Using this system, based on the time series of ENVISAT images from 2005 to 2012, we had a continuous 7-year monitoring of breakup location, type, area, and occurrence time of full-range of Antarctic breakups larger than 1km2. There are two types of breakups in Antarctica, the rift-opening breakups (R-breakup) driven by internal glaciological stress and the melt-related breakup (M-breakup) driven by external atmospheric and oceanic factors. The M-breakup and R-breakup were identified through the significant differences of surface failure features on images. The statistical analysis shows that the breakups whose area is less than 100 km2 in size accounting for up to 89.9% of the total event frequency. So their long-term contribution to the total ice loss of Antarctica should not be neglected. Analysis also shows that the R-breakup are mainly driven by internally glaciological stress, while the significant seasonal signature of its occurrence time suggested that rift propagation rates with seasonal trend is common to most R-breakups. Conversely, the occurrence of the M-breakup was constrained both by specific time (e.g., November-May) and by geographic location. Their largely consistent spatial

  3. Array-based comparative genomic hybridization for the detection of DNA sequence copy number changes in Barrett's adenocarcinoma.

    PubMed

    Albrecht, Bettina; Hausmann, Michael; Zitzelsberger, Horst; Stein, Hubert; Siewert, Jörg Rüdiger; Hopt, Ulrich; Langer, Rupert; Höfler, Heinz; Werner, Martin; Walch, Axel

    2004-07-01

    Array-based comparative genomic hybridization (aCGH) allows the identification of DNA sequence copy number changes at high resolution by co-hybridizing differentially labelled test and control DNAs to a micro-array of genomic clones. The present study has analysed a series of 23 formalin-fixed, paraffin wax-embedded tissue samples of Barrett's adenocarcinoma (BCA, n = 18) and non-neoplastic squamous oesophageal (n = 2) and gastric cardia mucosa (n = 3) by aCGH. The micro-arrays used contained 287 genomic targets covering oncogenes, tumour suppressor genes, and DNA sequences localized within chromosomal regions previously reported to be altered in BCA. DNA sequence copy number changes for a panel of approximately 50 genes were identified, most of which have not been previously described in BCA. DNA sequence copy number gains (mean 41 +/- 25/BCA) were more frequent than DNA sequence copy number losses (mean 20 +/- 15/BCA). The highest frequencies for DNA sequence copy number gains were detected for SNRPN (61%); GNLY (44%); NME1 (44%); DDX15, ABCB1 (MDR), ATM, LAMA3, MYBL2, ZNF217, and TNFRSF6B (39% each); and MSH2, TERC, SERPINE1, AFM137XA11, IGF1R, and PTPN1 (33% each). DNA sequence copy number losses were identified for PDGFB (44%); D17S125 (39%); AKT3 (28%); and RASSFI, FHIT, CDKN2A (p16), and SAS (CDK4) (28% each). In all non-neoplastic tissue samples of squamous oesophageal and gastric cardia mucosa, the measured mean ratios were 1.00 (squamous oesophageal mucosa) or 1.01 (gastric mucosa), indicating that no DNA sequence copy number chances were present. For validation, the DNA sequence copy number changes of selected clones (SNRPN, CMYC, HER2, ZNF217) detected by aCGH were confirmed by fluorescence in situ hybridization (FISH). These data show the sensitivity of aCGH for the identification of DNA sequence copy number changes at high resolution in BCA. The newly identified genes may include so far unknown biomarkers in BCA and are therefore a starting point for

  4. Object-based change detection in rapid urbanization regions with remotely sensed observations: a case study of Shenzhen, China

    NASA Astrophysics Data System (ADS)

    He, Lihuang; Dong, Guihua; Wang, Wei-Min; Yang, Lijun; Liang, Hong

    2013-10-01

    China, the most populous country on Earth, has experienced rapid urbanization which is one of the main causes of many environmental and ecological problems. Therefore, the monitoring of rapid urbanization regions and the environment is of critical importance for their sustainable development. In this study, the object-based classification is employed to detect the change of land cover in Shenzhen, which is located in South China and has been urbanized rapidly in recent three decades. First, four Landsat TM images, which were acquired on 1990, 2000 and 2010, respectively, are selected from the image database. Atmospheric corrections are conducted on these images with improved dark-object subtraction technique and surface meteorological observations. Geometric correction is processed with ground control points derived from topographic maps. Second, a region growing multi-resolution segmentation and a soft nearest neighbour classifier are used to finish object-based classification. After analyzing the fraction of difference classes over time series, we conclude that the comparison of derived land cover classes with socio-economic statistics demonstrates the strong positive correlation between built-up classes and urban population as well as gross GDP and GDPs in second and tertiary industries. Two different mechanisms of urbanization, namely new land development and redevelopment, are revealed. Consequently, we found that, the districts of Shenzhen were urbanized through different mechanisms.

  5. Detection of abrupt changes in dynamic systems

    NASA Technical Reports Server (NTRS)

    Willsky, A. S.

    1984-01-01

    Some of the basic ideas associated with the detection of abrupt changes in dynamic systems are presented. Multiple filter-based techniques and residual-based method and the multiple model and generalized likelihood ratio methods are considered. Issues such as the effect of unknown onset time on algorithm complexity and structure and robustness to model uncertainty are discussed.

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

    SciTech Connect

    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. Line matching for automatic change detection algorithm

    NASA Astrophysics Data System (ADS)

    Dhollande, Jérôme; Monnin, David; Gond, Laetitia; Cudel, Christophe; Kohler, Sophie; Dieterlen, Alain

    2012-06-01

    During foreign operations, Improvised Explosive Devices (IEDs) are one of major threats that soldiers may unfortunately encounter along itineraries. Based on a vehicle-mounted camera, we propose an original approach by image comparison to detect signicant changes on these roads. The classic 2D-image registration techniques do not take into account parallax phenomena. The consequence is that the misregistration errors could be detected as changes. According to stereovision principles, our automatic method compares intensity proles along corresponding epipolar lines by extrema matching. An adaptive space warping compensates scale dierence in 3D-scene. When the signals are matched, the signal dierence highlights changes which are marked in current video.

  8. Land-cover change detection

    USGS Publications Warehouse

    Chen, Xuexia; Giri, Chandra; Vogelmann, James

    2012-01-01

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

  9. Change detection in underwater imagery.

    PubMed

    Seemakurthy, Karthik; Rajagopalan, A N

    2016-03-01

    In this work, we deal with the problem of change detection in an underwater scenario given an unblurred-blurred image pair of a planar scene taken at different times. The blur is primarily due to the dynamic nature of the water surface and its nature is space-invariant in the presence of cyclic water flows. Exploiting the sparsity of the induced blur as well as the occlusions, we propose a distort-difference pipeline that employs an alternating minimization framework to perform change detection in the presence of geometric distortions (skew) as well as photometric degradations (blur and global illumination variations). The method can effectively yield both sharp and blurred occluder maps. Using synthetic as well as real data, we demonstrate how the proposed technique advances the state of the art. PMID:26974899

  10. Anomalous change detection in imagery

    DOEpatents

    Theiler, James P.; Perkins, Simon J.

    2011-05-31

    A distribution-based anomaly detection platform is described that identifies a non-flat background that is specified in terms of the distribution of the data. A resampling approach is also disclosed employing scrambled resampling of the original data with one class specified by the data and the other by the explicit distribution, and solving using binary classification.

  11. A wavelet-based approach to detect climate change on the coherent and turbulent component of the atmospheric circulation

    NASA Astrophysics Data System (ADS)

    Faranda, Davide; Defrance, Dimitri

    2016-06-01

    The modifications of atmospheric circulation induced by anthropogenic effects are difficult to capture because wind fields feature a complex spectrum where the signal of large-scale coherent structures (planetary, baroclinic waves and other long-term oscillations) is mixed up with turbulence. Our purpose is to study the effects of climate changes on these two components separately by applying a wavelet analysis to the 700 hPa wind fields obtained in climate simulations for different forcing scenarios. We study the coherent component of the signal via a correlation analysis to detect the persistence of large-scale or long-lasting structures, whereas we use the theory of autoregressive moving-average stochastic processes to measure the spectral complexity of the turbulent component. Under strong anthropogenic forcing, we detect a significant climate change signal. The analysis suggests that coherent structures will play a dominant role in future climate, whereas turbulent spectra will approach a classical Kolmogorov behaviour.

  12. Detecting change as it occurs

    NASA Technical Reports Server (NTRS)

    Radok, Uwe; Brown, Timothy J.

    1992-01-01

    Traditionally climate changes have been detected from long series of observations and long after they have happened. Our 'inverse sequential' procedure, for detecting change as soon as it occurs, describes the existing or most recent data by their frequency distribution. Its parameter(s) are estimated both from the existing set of observations and from the same set augmented by 1,2,....j new observations. Individual-value probability products ('likelihoods') are used to form ratios which yield two probabilities for erroneously accepting the existing parameter(s) as valid for the augmented data set, and vice versa. A genuine parameter change is signaled when these probabilities (or a more stable compound probability) show a progressive decrease. New parameter values can then be estimated from the new observations alone using standard statistical techniques. The inverse sequential procedure will be illustrated for global annual mean temperatures (assumed normally distributed), and for annual numbers of North Atlantic hurricanes (assumed to represent Poisson distributions). The procedure was developed, but not yet tested, for linear or exponential trends, and for chi-squared means or degrees of freedom, a special measure of autocorrelation.

  13. Web Based Rapid Mapping of Disaster Areas using Satellite Images, Web Processing Service, Web Mapping Service, Frequency Based Change Detection Algorithm and J-iView

    NASA Astrophysics Data System (ADS)

    Bandibas, J. C.; Takarada, S.

    2013-12-01

    Timely identification of areas affected by natural disasters is very important for a successful rescue and effective emergency relief efforts. This research focuses on the development of a cost effective and efficient system of identifying areas affected by natural disasters, and the efficient distribution of the information. The developed system is composed of 3 modules which are the Web Processing Service (WPS), Web Map Service (WMS) and the user interface provided by J-iView (fig. 1). WPS is an online system that provides computation, storage and data access services. In this study, the WPS module provides online access of the software implementing the developed frequency based change detection algorithm for the identification of areas affected by natural disasters. It also sends requests to WMS servers to get the remotely sensed data to be used in the computation. WMS is a standard protocol that provides a simple HTTP interface for requesting geo-registered map images from one or more geospatial databases. In this research, the WMS component provides remote access of the satellite images which are used as inputs for land cover change detection. The user interface in this system is provided by J-iView, which is an online mapping system developed at the Geological Survey of Japan (GSJ). The 3 modules are seamlessly integrated into a single package using J-iView, which could rapidly generate a map of disaster areas that is instantaneously viewable online. The developed system was tested using ASTER images covering the areas damaged by the March 11, 2011 tsunami in northeastern Japan. The developed system efficiently generated a map showing areas devastated by the tsunami. Based on the initial results of the study, the developed system proved to be a useful tool for emergency workers to quickly identify areas affected by natural disasters.

  14. Spatial-Temporal Detection of Changes on the Southern Coast of the Baltic Sea Based on Multitemporal Aerial Photographs

    NASA Astrophysics Data System (ADS)

    Michalowska, K.; Glowienka, E.; Pekala, A.

    2016-06-01

    Digital photogrammetry and remote sensing solutions applied under the project and combined with the geographical information system made it possible to utilize data originating from various sources and dating back to different periods. Research works made use of archival and up-to-date aerial images, satellite images, orthophotomaps. Multitemporal data served for mapping and monitoring intermediate conditions of the Baltic Sea shore zone without a need for a direct interference in the environment. The main objective of research was to determine the dynamics and volume of sea shore changes along the selected part of coast in the period of 1951-2004, and to assess the tendencies of shore development in that area. For each of the six annual data sets, the following were determined: front dune base line, water line and the beach width. The location of the dune base line, which reflects the course of the shoreline in a given year was reconstructed based on stereoscopic study of images from each annual set. Unidirectional changes in the period of 1951-2004 occurred only within 10% of the examined shore section length. The examined shore is marked by a high and considerable dynamics of changes. Almost half of the shore, in particular the middle coast shows big changes, in excess of 2 m/year. The limits of shoreline changes ranged from 120 to -90 m, and their velocity from 0 to 11 m/year, save that the middle and west parts of the examined coast section were subjected to definitely more intense shore transformations. Research based on the analysis of multitemporal aerial images made it possible to reconstruct the intermediate conditions of the Baltic Sea shoreline and determine the volume and rate of changes in the location of dune base line in the examined period of 53 years, and to find out tendencies of shore development and dynamics.

  15. Parametric probability distributions for anomalous change detection

    SciTech Connect

    Theiler, James P; Foy, Bernard R; Wohlberg, Brendt E; Scovel, James C

    2010-01-01

    The problem of anomalous change detection arises when two (or possibly more) images are taken of the same scene, but at different times. The aim is to discount the 'pervasive differences' that occur thoughout the imagery, due to the inevitably different conditions under which the images were taken (caused, for instance, by differences in illumination, atmospheric conditions, sensor calibration, or misregistration), and to focus instead on the 'anomalous changes' that actually take place in the scene. In general, anomalous change detection algorithms attempt to model these normal or pervasive differences, based on data taken directly from the imagery, and then identify as anomalous those pixels for which the model does not hold. For many algorithms, these models are expressed in terms of probability distributions, and there is a class of such algorithms that assume the distributions are Gaussian. By considering a broader class of distributions, however, a new class of anomalous change detection algorithms can be developed. We consider several parametric families of such distributions, derive the associated change detection algorithms, and compare the performance with standard algorithms that are based on Gaussian distributions. We find that it is often possible to significantly outperform these standard algorithms, even using relatively simple non-Gaussian models.

  16. A method of detecting land use change of remote sensing images based on texture features and DEM

    NASA Astrophysics Data System (ADS)

    Huang, Dong-ming; Wei, Chun-tao; Yu, Jun-chen; Wang, Jian-lin

    2015-12-01

    In this paper, a combination method, between the neural network and textures information, is proposed to remote sensing images classification. The methodology involves an extraction of texture features using the gray level co-occurrence matrix and image classification with BP artificial neural network. The combination of texture features and the digital elevation model (DEM) as classified bands to neural network were used to recognized different classes. This scheme shows high recognition accuracy in the classification of remote sensing images. In the experiments, the proposed method was successfully applied to remote sensing image classification and Land Use Change Detection, in the meanwhile, the effectiveness of the proposed method was verified.

  17. On Radar Resolution in Coherent Change Detection.

    SciTech Connect

    Bickel, Douglas L.

    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.

  18. Ladar-based IED detection

    NASA Astrophysics Data System (ADS)

    Engström, Philip; Larsson, Hâkan; Letalick, Dietmar

    2014-05-01

    An improvised explosive device (IED) is a bomb constructed and deployed in a non-standard manor. Improvised means that the bomb maker took whatever he could get his hands on, making it very hard to predict and detect. Nevertheless, the matters in which the IED's are deployed and used, for example as roadside bombs, follow certain patterns. One possible approach for early warning is to record the surroundings when it is safe and use this as reference data for change detection. In this paper a LADAR-based system for IED detection is presented. The idea is to measure the area in front of the vehicle when driving and comparing this to the previously recorded reference data. By detecting new, missing or changed objects the system can make the driver aware of probable threats.

  19. Efficient ensemble system based on the copper binding motif for highly sensitive and selective detection of cyanide ions in 100% aqueous solutions by fluorescent and colorimetric changes.

    PubMed

    Jung, Kwan Ho; Lee, Keun-Hyeung

    2015-09-15

    A peptide-based ensemble for the detection of cyanide ions in 100% aqueous solutions was designed on the basis of the copper binding motif. 7-Nitro-2,1,3-benzoxadiazole-labeled tripeptide (NBD-SSH, NBD-SerSerHis) formed the ensemble with Cu(2+), leading to a change in the color of the solution from yellow to orange and a complete decrease of fluorescence emission. The ensemble (NBD-SSH-Cu(2+)) sensitively and selectively detected a low concentration of cyanide ions in 100% aqueous solutions by a colorimetric change as well as a fluorescent change. The addition of cyanide ions instantly removed Cu(2+) from the ensemble (NBD-SSH-Cu(2+)) in 100% aqueous solutions, resulting in a color change of the solution from orange to yellow and a "turn-on" fluorescent response. The detection limits for cyanide ions were lower than the maximum allowable level of cyanide ions in drinking water set by the World Health Organization. The peptide-based ensemble system is expected to be a potential and practical way for the detection of submicromolar concentrations of cyanide ions in 100% aqueous solutions. PMID:26320594

  20. Development of a HOG-based real-time PCR method to detect stress response changes in mycotoxigenic moulds.

    PubMed

    Rodríguez, Alicia; Medina, Ángel; Córdoba, Juan J; Magan, Naresh

    2016-08-01

    There is a need to understand the mechanism of adaptation of toxigenic fungal species which are able to colonise highly specialised foods such as cured meats where there is a high osmotic stress due to the presence up to 20-22% NaCl during the ripening process. A new tool able to detect changes in stress related genes would be useful to understand the ecological reasons for the ability of these species to grow in specialised niches. In this work a real-time PCR (qPCR) using SYBR Green was developed. Primers were designed from the Hog1 gene involved in osmo-adaptation in fungi. For this, conserved regions resulting from the alignment of 26 published partial sequences of such gene were used. Specificity of primers HogF2/R2 was demonstrated when amplified, producing a unique 131-bp PCR product with a Tm value of 84 °C. The qPCR method showed an efficiency of 98%, R(2) value > 0.99 and a detection limit of 0.7 log Hog1 gene copies. The qPCR method to measure changes in the Hog1 gene expression in relation to growth in ionic and non-ionic stressed environments (using 10-40% NaCl and sorbitol concentrations) was found to be suitable for two mycotoxigenic species (Penicillium nordicum, P. expansum). This assay will be a valuable tool for generating relevant Hog1 expression data from different mould species in relation to different stresses in food habitats. It will also be a good tool for a better understanding of the ability of xerophilic and xerotolerant species to colonise extreme environments. PMID:27052709

  1. Nationwide Hybrid Change Detection of Buildings

    NASA Astrophysics Data System (ADS)

    Hron, V.; Halounova, L.

    2016-06-01

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

  2. Trajectory based detection of forest-change impacts on surface soil moisture at a basin scale [Poyang Lake Basin, China

    NASA Astrophysics Data System (ADS)

    Feng, Huihui; Liu, Yuanbo

    2014-06-01

    Surface soil moisture plays a critical role in hydrological processes, but varies with both natural and anthropogenic influences. Land cover change unavoidably alters surface property and subsequent soil moisture, and its contribution is yet hard to isolate from the mixed influences. In combination with trajectory analysis, this paper proposes a novel approach for detection of forest-change impacts on surface soil moisture variation with an examination over the Poyang Lake Basin, China from 2003 to 2009. Soil moisture in permanent forest trajectory represents a synthetic result of natural influences and serves as a reference for isolating soil moisture alternation due to land cover change at a basin scale. Our results showed that soil moisture decreased in all forest trajectories, while the absolute decrease was lower for permanent forest trajectory (2.53%) than the whole basin (2.61%), afforestation trajectories (2.70%) and deforestation trajectories (2.81%). Moreover, afforestation has a high capacity to hold more soil moisture, but may take more than 6 years to reach its maximum capacity. Soil moisture increased from 14.09% to 14.94% for the afforestation trajectories with tree aging from 1 to 6 years. Finally, land cover change may affect soil moisture alternation toward different transformation directions. Absolute soil moisture decreases by 0.08% for the whole basin, 0.17% for afforestation and 0.28% for deforestation trajectories, accounting for 3.13%, 6.47% and 10.07% of the total decrease in soil moisture. More specifically, the transformation from woody Savannas, cropland and other lands to forest generated absolute soil moisture deceases of 0.20%, -0.08% and 0.27%, accounting for 7.26%, -3.52% and 9.57% of the decreases. On the other hand, the reverse transformation generated soil moisture deceases of 0.29%, 0.21% and 0.35%, accounting for 10.43%, 7.69% and 12.14% of the total decrease. Our findings should be valuable for evaluating the impacts of land

  3. Total least squares for anomalous change detection

    SciTech Connect

    Theiler, James P; Matsekh, Anna M

    2010-01-01

    A family of difference-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 TLSQ-based 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 furthermore it is shown to be equivalent to the optimized covariance equalization algorithm. What whitened TLSQ offers, in addition to connecting with a common language the derivations of two of the most popular anomalous change detection algorithms - chronochrome and covariance equalization - is a generalization of these algorithms with the potential for better performance.

  4. Ischemia detection from morphological QRS angle changes.

    PubMed

    Romero, Daniel; Martínez, Juan Pablo; Laguna, Pablo; Pueyo, Esther

    2016-07-01

    In this paper, an ischemia detector is presented based on the analysis of QRS-derived angles. The detector has been developed by modeling ischemic effects on the QRS angles as a gradual change with a certain transition time and assuming a Laplacian additive modeling error contaminating the angle series. Both standard and non-standard leads were used for analysis. Non-standard leads were obtained by applying the PCA technique over specific lead subsets to represent different potential locations of the ischemic zone. The performance of the proposed detector was tested over a population of 79 patients undergoing percutaneous coronary intervention in one of the major coronary arteries (LAD (n  =  25), RCA (n  =  16) and LCX (n  =  38)). The best detection performance, obtained for standard ECG leads, was achieved in the LAD group with values of sensitivity and specificity of [Formula: see text], [Formula: see text], followed by the RCA group with [Formula: see text], Sp  =  94.4 and the LCX group with [Formula: see text], [Formula: see text], notably outperforming detection based on the ST series in all cases, with the same detector structure. The timing of the detected ischemic events ranged from 30 s up to 150 s (mean  =  66.8 s) following the start of occlusion. We conclude that changes in the QRS angles can be used to detect acute myocardial ischemia. PMID:27243441

  5. The development of a temporal-BRDF model-based approach to change detection, an application to the identification and delineation of fire affected areas

    NASA Astrophysics Data System (ADS)

    Rebelo, Lisa-Maria

    Although large quantities of southern Africa burn every year, minimal information is available relating to the fire regimes of this area. This study develops a new, generic approach to change detection, applicable to the identification of land cover change from high temporal and moderate spatial resolution satellite data. Traditional change detection techniques have several key limitations which are identified and addressed in this work. In particular these approaches fail to account for directional effects in the remote sensing signal introduced by variations in the solar and sensing geometry, and are sensitive to underlying phenological changes in the surface as well as noise in the data due to cloud or atmospheric contamination. This research develops a bi-directional, model-based change detection algorithm. An empirical temporal component is incorporated into a semi-empirical linear BRDF model. This may be fitted to a long time series of reflectance with less sensitivity to the presence of underlying phenological change. Outliers are identified based on an estimation of noise in the data and the calculation of uncertainty in the model parameters and are removed from the sequence. A "step function kernel" is incorporated into the formulation in order to detect explicitly sudden step-like changes in the surface reflectance induced by burning. The change detection model is applied to the problem of locating and mapping fire affected areas from daily moderate spatial resolution satellite data, and an indicator of burn severity is introduced. Monthly burned area datasets for a 2400km by 1200km area of southern Africa detailing the day and severity of burning are created for a five year period (2000-2004). These data are analysed and the fire regimes of southern African ecosystems during this time are characterised. The results highlight the extent of the burning which is taking place within southern Africa, with between 27-32% of the study area burning during each

  6. Evaluation of change detection techniques for monitoring coastal zone environments

    NASA Technical Reports Server (NTRS)

    Weismiller, R. A.; Kristof, S. J.; Scholz, D. K.; Anuta, P. E.; Momin, S. M.

    1977-01-01

    Development of satisfactory techniques for detecting change in coastal zone environments is required before operational monitoring procedures can be established. In an effort to meet this need a study was directed toward developing and evaluating different types of change detection techniques, based upon computer aided analysis of LANDSAT multispectral scanner (MSS) data, to monitor these environments. The Matagorda Bay estuarine system along the Texas coast was selected as the study area. Four change detection techniques were designed and implemented for evaluation: (1) post classification comparison change detection, (2) delta data change detection, (3) spectral/temporal change classification, and (4) layered spectral/temporal change classification. Each of the four techniques was used to analyze a LANDSAT MSS temporal data set to detect areas of change of the Matagorda Bay region.

  7. Satellite mapping and automated feature extraction: Geographic information system-based change detection of the Antarctic coast

    NASA Astrophysics Data System (ADS)

    Kim, Kee-Tae

    Declassified Intelligence Satellite Photograph (DISP) data are important resources for measuring the geometry of the coastline of Antarctica. By using the state-of-art digital imaging technology, bundle block triangulation based on tie points and control points derived from a RADARSAT-1 Synthetic Aperture Radar (SAR) image mosaic and Ohio State University (OSU) Antarctic digital elevation model (DEM), the individual DISP images were accurately assembled into a map quality mosaic of Antarctica as it appeared in 1963. The new map is one of important benchmarks for gauging the response of the Antarctic coastline to changing climate. Automated coastline extraction algorithm design is the second theme of this dissertation. At the pre-processing stage, an adaptive neighborhood filtering was used to remove the film-grain noise while preserving edge features. At the segmentation stage, an adaptive Bayesian approach to image segmentation was used to split the DISP imagery into its homogenous regions, in which the fuzzy c-means clustering (FCM) technique and Gibbs random field (GRF) model were introduced to estimate the conditional and prior probability density functions. A Gaussian mixture model was used to estimate the reliable initial values for the FCM technique. At the post-processing stage, image object formation and labeling, removal of noisy image objects, and vectorization algorithms were sequentially applied to segmented images for extracting a vector representation of coastlines. Results were presented that demonstrate the effectiveness of the algorithm in segmenting the DISP data. In the cases of cloud cover and little contrast scenes, manual editing was carried out based on intermediate image processing and visual inspection in comparison of old paper maps. Through a geographic information system (GIS), the derived DISP coastline data were integrated with earlier and later data to assess continental scale changes in the Antarctic coast. Computing the area of

  8. Detecting hydrological changes through conceptual model

    NASA Astrophysics Data System (ADS)

    Viola, Francesco; Caracciolo, Domenico; Pumo, Dario; Francipane, Antonio; Valerio Noto, Leonardo

    2015-04-01

    Circulation Models (GCMs) for the future scenarios 2046-2065 and 2081-2100. Land use changes (i.e., changes in the fraction of impervious area due to increasing urbanization) are explicitly simulated, while the reference hydrological responses are assessed by the spatially distributed, process-based hydrological model tRIBS, the TIN-based Real-time Integrated Basin Simulator. Several scenarios have been created, describing hypothetical centuries with steady conditions, climate change conditions, land use change conditions and finally complex conditions involving both transient climatic modifications and gradual land use changes. A conceptual lumped model, the EHSM (EcoHydrological Streamflow Model) is calibrated for the above mentioned scenarios with regard to different time-windows. The calibrated parameters show high sensitivity to anthropic variations in land use and/or climatic variability. Land use changes are clearly visible from parameters evolution especially when steady climatic conditions are considered. When the increase in urbanization is coupled with rainfall reduction the ability to detect human interventions through the analysis of conceptual model parameters is weakened.

  9. A novel detection of radon based on its decay product inducing conformational changes of an aptamer probe.

    PubMed

    Long, Minzhi; Deng, Han; Tian, Gang; Song, Chunli; Liu, Hongwen; Shen, Yi; Lv, Changyin

    2016-09-14

    This study proposes a novel method for the detection of inert gas radon using a label-free, specific, fluorescence-sensing aptamer in the context of PW17-OG system. This method utilizes the cyanine dye OliGreen (OG) as a signal reactor and the aptamer PW17 as a fluorescent identification probe. When OG integrates into the free curling PW17, a strong fluorescence signal is generated. After radon decays, the long lived naturally occurring radon progeny Pb being disposed and introduced to the system. Lead ions induce PW17 to form a stable G-quadruplex, thereby inhibiting the interaction between OG and PW17 and resulting in a reduction of the fluorescence intensity. The fluorescence intensity show a good linear relationship with lead ion and the radon concentration (D), thereinto, We fitted linear regression of radon concentration in the range of 0.92-4.22 (×10(4) Bqhm(-3)) to receive a good relationship between ΔF and the concentration of radon with the detection limit of 1963 Bqhm(-3). This method has been successfully applied for detecting standard cumulative concentration of radon and the detection limit reached the national standard of China. This sensitive method can exclude radiation damage in field testing, furthermore, it explores a new field in biological analysis using an aptamer to detected inorganic, gaseous, and radioactive materials. PMID:27566356

  10. Lake Chapala change detection using time series

    NASA Astrophysics Data System (ADS)

    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.

  11. Detecting Concentration Changes with Cooperative Receptors

    NASA Astrophysics Data System (ADS)

    Bo, Stefano; Celani, Antonio

    2016-03-01

    Cells constantly need to monitor the state of the environment to detect changes and timely respond. The detection of concentration changes of a ligand by a set of receptors can be cast as a problem of hypothesis testing, and the cell viewed as a Neyman-Pearson detector. Within this framework, we investigate the role of receptor cooperativity in improving the cell's ability to detect changes. We find that cooperativity decreases the probability of missing an occurred change. This becomes especially beneficial when difficult detections have to be made. Concerning the influence of cooperativity on how fast a desired detection power is achieved, we find in general that there is an optimal value at finite levels of cooperation, even though easy discrimination tasks can be performed more rapidly by noncooperative receptors.

  12. Indigenous people's detection of rapid ecological change.

    PubMed

    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. PMID:24528101

  13. A sequential framework for image change detection.

    PubMed

    Lingg, Andrew J; Zelnio, Edmund; Garber, Fred; Rigling, Brian D

    2014-05-01

    We present a sequential framework for change detection. This framework allows us to use multiple images from reference and mission passes of a scene of interest in order to improve detection performance. It includes a change statistic that is easily updated when additional data becomes available. Detection performance using this statistic is predictable when the reference and image data are drawn from known distributions. We verify our performance prediction by simulation. Additionally, we show that detection performance improves with additional measurements on a set of synthetic aperture radar images and a set of visible images with unknown probability distributions. PMID:24818249

  14. Airborne change detection system for the detection of route mines

    NASA Astrophysics Data System (ADS)

    Donzelli, Thomas P.; Jackson, Larry; Yeshnik, Mark; Petty, Thomas E.

    2003-09-01

    The US Army is interested in technologies that will enable it to maintain the free flow of traffic along routes such as Main Supply Routes (MSRs). Mines emplaced in the road by enemy forces under cover of darkness represent a major threat to maintaining a rapid Operational Tempo (OPTEMPO) along such routes. One technique that shows promise for detecting enemy mining activity is Airborne Change Detection, which allows an operator to detect suspicious day-to-day changes in and around the road that may be indicative of enemy mining. This paper presents an Airborne Change Detection that is currently under development at the US Army Night Vision and Electronic Sensors Directorate (NVESD). The system has been tested using a longwave infrared (LWIR) sensor on a vertical take-off and landing unmanned aerial vehicle (VTOL UAV) and a midwave infrared (MWIR) sensor on a fixed wing aircraft. The system is described and results of the various tests conducted to date are presented.

  15. Object-based automatic change detection in forested areas of Poland between 2000 and 2006 using NDVI times series at moderate resolution.

    NASA Astrophysics Data System (ADS)

    Lamarche, C.; Tomaszewska, M.; Dabrowska-Zielinska, K.; Defourny, P.

    2012-04-01

    In the framework of the Geoland2 project, the Seasonal and Annual Change Monitoring Service (SATChMo) was initiated in order to close the gap between low-resolution global coverage and the high-resolution land cover (LC) and land cover change (LCC) parameters. The SM-14 product aims at developing timely continental and dynamic land cover change indicator maps over Europe and Africa, at moderate resolution. These land cover specific maps indicate where a major land cover change occurs but do not aim to identify the type of change. It can refer to land cover classes as well as to major events affecting temporarily the land surface such as flooding events, volcano, large burnt scarce, etc. In this context, this work applied an automatic and probabilistic change detection algorithm to spot changed objects of the forest of Poland between 2000 and 2006. By the adjustment of the change thresholds, this algorithm allows producing change probability maps rather than binary change/no change according to the needs of end-users. A multispectral segmentation simultaneously using yearly 250m MODIS composites of NDVI of 2000 and 2006 was applied over the coniferous forest defined by the Corine Land Cover 2000 map. This produced spatially homogeneous objects with similar behaviour over time. Under the hypothesis of minor changes in the study area, each object is statistically compared to an unchanged reference using the Mahalanobis distance. All the objects detected as changed by this trimming procedure are then flagged and spatially represented as a change probability map. An assessment of correct detection was performed by confronting the detected changed objects to the Corine Land Cover Change Map 2000-2006. Results show a strong dependency between agreements and the size of changed objects. Both user's and producer's accuracy improve with bigger objects. In the assessment of accurate coverage, taking into account the 250m MODIS pixels and assuming the low reliability of small

  16. Change Detection Experiments Using Low Cost UAVs

    NASA Technical Reports Server (NTRS)

    Logan, Michael J.; Vranas, Thomas L.; Motter, Mark; Hines, Glenn D.; Rahman, Zia-ur

    2005-01-01

    This paper presents the progress in the development of a low-cost change-detection system. This system is being developed to provide users with the ability to use a low-cost unmanned aerial vehicle (UAV) and image processing system that can detect changes in specific fixed ground locations using video provided by an autonomous UAV. The results of field experiments conducted with the US Army at Ft. A.P.Hill are presented.

  17. Voxel-based morphometry (VBM) studies in schizophrenia—can white matter changes be reliably detected with VBM?

    PubMed Central

    Melonakos, Eric; Shenton, Martha; Rathi, Yogesh; Terry, Doug; Bouix, Sylvain; Kubicki, Marek

    2012-01-01

    Voxel-Based Morphometry (VBM) is a hypothesis-free, whole-brain, voxel-by-voxel analytic method that attempts to compare imaging data between populations. Schizophrenia studies have utilized this method to localize differences in Diffusion Tensor Imaging (DTI) derived Fractional Anisotropy (FA), a measure of white matter integrity, between patients and healthy controls. The number of publications has grown, although it is unclear how reliable and reproducible this method is, given the subtle white matter abnormalities expected in schizophrenia. Here we analyze and combine results from 23 studies published to date that use VBM to study schizophrenia in order to evaluate the reproducibility of this method in DTI analysis. Coordinates of each region reported in DTI VBM studies published thus far in schizophrenia were plotted onto a Montreal Neurological Institute atlas, and their anatomical locations were recorded. Results indicated that the reductions of FA in patients with schizophrenia were scattered across the brain. Moreover, even the most consistently reported regions were reported independently in less than 35% of the papers studied. Other instances of reduced FA were replicated at an even lower rate. Our findings demonstrate striking inconsistency, with none of the regions reported in much more than a third of the published papers. Poor replication rate suggests that the application of VBM to DTI data may not be the optimal way for studying the subtle microstructural abnormalities that are being hypothesized in schizophrenia. PMID:21684124

  18. Change Point Detection in Correlation Networks

    PubMed Central

    Barnett, Ian; Onnela, Jukka-Pekka

    2016-01-01

    Many systems of interacting elements can be conceptualized as networks, where network nodes represent the elements and network ties represent interactions between the elements. In systems where the underlying network evolves, it is useful to determine the points in time where the network structure changes significantly as these may correspond to functional change points. We propose a method for detecting change points in correlation networks that, unlike previous change point detection methods designed for time series data, requires minimal distributional assumptions. We investigate the difficulty of change point detection near the boundaries of the time series in correlation networks and study the power of our method and competing methods through simulation. We also show the generalizable nature of the method by applying it to stock price data as well as fMRI data. PMID:26739105

  19. Sensor for detecting changes in magnetic fields

    DOEpatents

    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.

  20. Sensor for detecting changes in magnetic fields

    DOEpatents

    Praeg, W.F.

    1980-02-26

    A sensor is described for detecting changes in the magnetic field of the equilibrium-field coil of a Tokamak plasma device that 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.

  1. lidar change detection using building models

    NASA Astrophysics Data System (ADS)

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

    2014-06-01

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

  2. Comparing Several Algorithms for Change Detection of Wetland

    NASA Astrophysics Data System (ADS)

    Yan, F.; Zhang, S.; Chang, L.

    2015-12-01

    As "the kidneys of the landscape" and "ecological supermarkets", wetland plays an important role in ecological equilibrium and environmental protection.Therefore, it is of great significance to understand the dynamic changes of the wetland. Nowadays, many index and many methods have been used in dynamic Monitoring of Wetland. However, there are no single method and no single index are adapted to detect dynamic change of wetland all over the world. In this paper, three digital change detection algorithms are applied to 2005 and 2010 Landsat Thematic Mapper (TM) images of a portion of the Northeast China to detect wetland dynamic between the two dates. The change vector analysis method (CVA) uses 6 bands of TM images to detect wetland dynamic. The tassled cap transformation is used to create three change images (change in brightness, greenness, and wetness). A new method--- Comprehensive Change Detection Method (CCDM) is introduced to detect forest dynamic change. 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 (differenced Normalized Burn Ratio (dNBR), differenced Normalized Difference Vegetation Index (dNDVI), the Change Vector (CV) and a new index called the Relative Change Vector Maximum (RCVMAX)) 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. Related test proved that CCDM method is simple, easy to operate, widely applicable, and capable of capturing a variety of natural and anthropogenic disturbances potentially associated with land cover changes on

  3. The impact of misregistration on change detection

    NASA Technical Reports Server (NTRS)

    Townshend, John R. G.; Justice, Christopher O.; Gurney, Charlotte; Mcmanus, James

    1992-01-01

    The impact of images misregistration on the detection of changes in land cover was studied using spatially degraded Landsat MSS images. Emphasis is placed on simulated images of the Normalized Difference Vegetation Index (NDVI) at spatial resolutions of 250 and 500 m. It is pointed out that there is the need to achieve high values of registration accuracy. The evidence from simulations suggests that misregistrations can have a marked effect on the ability of remotely sensed data to detect changes in land cover. Even subpixel misregistrations can have a major impact, and the most marked proportional changes will tend to occur at the finest misregistrations.

  4. Image change detection algorithms: a systematic survey.

    PubMed

    Radke, Richard J; Andra, Srinivas; Al-Kofahi, Omar; Roysam, Badrinath

    2005-03-01

    Detecting regions of change in multiple images of the same scene taken at different times is of widespread interest due to a large number of applications in diverse disciplines, including remote sensing, surveillance, medical diagnosis and treatment, civil infrastructure, and underwater sensing. This paper presents a systematic survey of the common processing steps and core decision rules in modern change detection algorithms, including significance and hypothesis testing, predictive models, the shading model, and background modeling. We also discuss important preprocessing methods, approaches to enforcing the consistency of the change mask, and principles for evaluating and comparing the performance of change detection algorithms. It is hoped that our classification of algorithms into a relatively small number of categories will provide useful guidance to the algorithm designer. PMID:15762326

  5. Automated change detection for synthetic aperture sonar

    NASA Astrophysics Data System (ADS)

    G-Michael, Tesfaye; Marchand, Bradley; Tucker, J. D.; Sternlicht, Daniel D.; Marston, Timothy M.; Azimi-Sadjadi, Mahmood R.

    2014-05-01

    In this paper, an automated change detection technique is presented that compares new and historical seafloor images created with sidescan synthetic aperture sonar (SAS) for changes occurring over time. The method consists of a four stage process: a coarse navigational alignment; fine-scale co-registration using the scale invariant feature transform (SIFT) algorithm to match features between overlapping images; sub-pixel co-registration to improves phase coherence; and finally, change detection utilizing canonical correlation analysis (CCA). The method was tested using data collected with a high-frequency SAS in a sandy shallow-water environment. By using precise co-registration tools and change detection algorithms, it is shown that the coherent nature of the SAS data can be exploited and utilized in this environment over time scales ranging from hours through several days.

  6. Priming effects under correct change detection and change blindness.

    PubMed

    Caudek, Corrado; Domini, Fulvio

    2013-03-01

    In three experiments, we investigated the priming effects induced by an image change on a successive animate/inanimate decision task. We studied both perceptual (Experiments 1 and 2) and conceptual (Experiment 3) priming effects, under correct change detection and change blindness (CB). Under correct change detection, we found larger positive priming effects on congruent trials for probes representing animate entities than for probes representing artifactual objects. Under CB, we found performance impairment relative to a "no-change" baseline condition. This inhibition effect induced by CB was modulated by the semantic congruency between the changed item and the probe in the case of probe images, but not for probe words. We discuss our results in the context of the literature on the negative priming effect. PMID:22964454

  7. Land Cover Change Detection Using Saliency Andwavelet Transformation

    NASA Astrophysics Data System (ADS)

    Zhang, Haopeng; Jiang, Zhiguo; Cheng, Yan

    2016-06-01

    How to obtain accurate difference map remains an open challenge in change detection. To tackle this problem, we propose a change detection method based on saliency detection and wavelet transformation. We do frequency-tuned saliency detection in initial difference image (IDI) obtained by logarithm ratio to get a salient difference image (SDI). Then, we calculate local entropy of SDI to obtain an entropic salient difference image (ESDI). The final difference image (FDI) is the wavelet fusion of IDI and ESDI, and Otsu thresholding is used to extract difference map from FDI. Experimental results validate the effectiveness and feasibility.

  8. Change detection and characterization of volcanic activity using ground based low-light and near infrared cameras to monitor incandescence and thermal signatures

    NASA Astrophysics Data System (ADS)

    Harrild, Martin; Webley, Peter; Dehn, Jonathan

    2015-04-01

    Knowledge and understanding of precursory events and thermal signatures are vital for monitoring volcanogenic processes, as activity can often range from low level lava effusion to large explosive eruptions, easily capable of ejecting ash up to aircraft cruise altitudes. Using ground based remote sensing techniques to monitor and detect this activity is essential, but often the required equipment and maintenance is expensive. Our investigation explores the use of low-light cameras to image volcanic activity in the visible to near infrared (NIR) portion of the electromagnetic spectrum. These cameras are ideal for monitoring as they are cheap, consume little power, are easily replaced and can provide near real-time data. We focus here on the early detection of volcanic activity, using automated scripts, that capture streaming online webcam imagery and evaluate image pixel brightness values to determine relative changes and flag increases in activity. The script is written in Python, an open source programming language, to reduce the overall cost to potential consumers and increase the application of these tools across the volcanological community. In addition, by performing laboratory tests to determine the spectral response of these cameras, a direct comparison of collocated low-light and thermal infrared cameras has allowed approximate eruption temperatures and effusion rates to be determined from pixel brightness. The results of a field campaign in June, 2013 to Stromboli volcano, Italy, are also presented here. Future field campaigns to Latin America will include collaborations with INSIVUMEH in Guatemala, to apply our techniques to Fuego and Santiaguito volcanoes.

  9. Change detection and characterization of volcanic activity using ground based low-light and near infrared cameras to monitor incandescence and thermal signatures

    NASA Astrophysics Data System (ADS)

    Harrild, M.; Webley, P.; Dehn, J.

    2014-12-01

    Knowledge and understanding of precursory events and thermal signatures are vital for monitoring volcanogenic processes, as activity can often range from low level lava effusion to large explosive eruptions, easily capable of ejecting ash up to aircraft cruise altitudes. Using ground based remote sensing techniques to monitor and detect this activity is essential, but often the required equipment and maintenance is expensive. Our investigation explores the use of low-light cameras to image volcanic activity in the visible to near infrared (NIR) portion of the electromagnetic spectrum. These cameras are ideal for monitoring as they are cheap, consume little power, are easily replaced and can provide near real-time data. We focus here on the early detection of volcanic activity, using automated scripts, that capture streaming online webcam imagery and evaluate image pixel brightness values to determine relative changes and flag increases in activity. The script is written in Python, an open source programming language, to reduce the overall cost to potential consumers and increase the application of these tools across the volcanological community. In addition, by performing laboratory tests to determine the spectral response of these cameras, a direct comparison of collocated low-light and thermal infrared cameras has allowed approximate eruption temperatures and effusion rates to be determined from pixel brightness. The results of a field campaign in June, 2013 to Stromboli volcano, Italy, are also presented here. Future field campaigns to Latin America will include collaborations with INSIVUMEH in Guatemala, to apply our techniques to Fuego and Santiaguito volcanoes.

  10. Real-time 3D change detection of IEDs

    NASA Astrophysics Data System (ADS)

    Wathen, Mitch; Link, Norah; Iles, Peter; Jinkerson, John; Mrstik, Paul; Kusevic, Kresimir; Kovats, David

    2012-06-01

    Road-side bombs are a real and continuing threat to soldiers in theater. CAE USA recently developed a prototype Volume based Intelligence Surveillance Reconnaissance (VISR) sensor platform for IED detection. This vehicle-mounted, prototype sensor system uses a high data rate LiDAR (1.33 million range measurements per second) to generate a 3D mapping of roadways. The mapped data is used as a reference to generate real-time change detection on future trips on the same roadways. The prototype VISR system is briefly described. The focus of this paper is the methodology used to process the 3D LiDAR data, in real-time, to detect small changes on and near the roadway ahead of a vehicle traveling at moderate speeds with sufficient warning to stop the vehicle at a safe distance from the threat. The system relies on accurate navigation equipment to geo-reference the reference run and the change-detection run. Since it was recognized early in the project that detection of small changes could not be achieved with accurate navigation solutions alone, a scene alignment algorithm was developed to register the reference run with the change detection run prior to applying the change detection algorithm. Good success was achieved in simultaneous real time processing of scene alignment plus change detection.

  11. NOVELTY DETECTION UNDER CHANGING ENVIRONMENTAL CONDITIONS

    SciTech Connect

    H. SOHN; K. WORDER; C. R. FARRAR

    2001-04-01

    The primary objective of novelty detection is to examine a system's dynamic response to determine if the system significantly deviates from an initial baseline condition. In reality, the system is often subject to changing environmental and operation conditions that affect its dynamic characteristics. Such variations include changes in loading, boundary conditions, temperature, and moisture. Most damage diagnosis techniques, however, generally neglect the effects of these changing ambient conditions. Here, a novelty detection technique is developed explicitly taking into account these natural variations of the system in order to minimize false positive indications of true system changes. Auto-associative neural networks are employed to discriminate system changes of interest such as structural deterioration and damage from the natural variations of the system.

  12. Method to detect environmental change for an arid land

    NASA Astrophysics Data System (ADS)

    Ito, A.; Miyamoto, J.; Tsuchiya, K.; Ishiyama, T.

    A method to detect natural environmental change for an arid land is developed based on 17 bands Visible NIR SWIR and Thermal IR ASTER Advanced SpaceborneThermal Emission and Reflection radiometer aboard Terra and in situ ground truth survey in Taklimakan Desert The method first extracts an area of macroscopic change then detailed or microscopic changes are detected Although the procedure is described in two steps the actual precessing is performed automatically and nearly simultaneously The method is named as ECD Environmental Change Automatic Discrimination model method for the sake of convenience

  13. Detecting Landscape Change: The View from Above

    ERIC Educational Resources Information Center

    Porter, Jess

    2008-01-01

    This article will demonstrate an approach for discovering and assessing local landscape change through the use of remotely sensed images. A brief introduction to remotely sensed imagery is followed by a discussion of relevant ways to introduce this technology into the college science classroom. The Map Detective activity demonstrates the…

  14. Development of o.a.s.i.s., a new automated blood culture system in which detection is based on measurement of bottle headspace pressure changes.

    PubMed Central

    Stevens, C M; Swaine, D; Butler, C; Carr, A H; Weightman, A; Catchpole, C R; Healing, D E; Elliott, T S

    1994-01-01

    o.a.s.i.s. (Unipath Ltd., Basingstoke, United Kingdom) is a new automated blood culture system. The metabolism of microorganisms is detected by measuring changes in the pressure of the headspace of blood culture bottles. These changes are measured by monitoring the position of a flexible sealing septum, every 5 min, with a scanning laser sensor. This noninvasive system can detect both gas absorption and production and does not rely solely on measuring increasing carbon dioxide levels. A research prototype instrument was used to carry out an evaluation of the media, the detection system, and its associated detection algorithm. In simulated blood cultures, o.a.s.i.s. supported growth and detected a range of clinical isolates. Times to positivity were significantly shorter in o.a.s.i.s. than in the BACTEC 460 system. Results of a clinical feasibility study, with a manual blood culture system as a control, confirmed that o.a.s.i.s. was able to support the growth and detection of a variety of clinically significant organisms. On the basis of these findings, full-scale comparative clinical trials of o.a.s.i.s. with other automated blood culture systems are warranted. PMID:7929769

  15. Change detection in urban areas by object-based analysis and on-the-fly comparison of multi-view ALS data

    NASA Astrophysics Data System (ADS)

    Hebel, Marcus; Arens, Michael; Stilla, Uwe

    2013-12-01

    The use of helicopters as a sensor platform offers flexible fields of application due to adaptable flying speed at low flight levels. Modern helicopters are equipped with radar altimeters, inertial navigation systems (INS), forward-looking cameras and even laser scanners for automatic obstacle avoidance. If the 3D geometry of the terrain is already available, the analysis of airborne laser scanner (ALS) measurements may also be used for terrain-referenced navigation and change detection. In this paper, we present a framework for on-the-fly comparison of current ALS data to given reference data of an urban area. In contrast to classical difference methods, our approach extends the concept of occupancy grids known from robot mapping. However, it does not blur the measured information onto the grid cells. The proposed change detection method applies the Dempster-Shafer theory to identify conflicting evidence along the laser pulse propagation path. Additional attributes are considered to decide whether detected changes are of man-made origin or occurring due to seasonal effects. The concept of online change detection has been successfully validated in offline experiments with recorded ALS data streams. Results are shown for an urban test site at which multi-view ALS data were acquired at an interval of 1 year.

  16. Automatic change detection using mobile laser scanning

    NASA Astrophysics Data System (ADS)

    Hebel, M.; Hammer, M.; Gordon, M.; Arens, M.

    2014-10-01

    Automatic change detection in 3D environments requires the comparison of multi-temporal data. By comparing current data with past data of the same area, changes can be automatically detected and identified. Volumetric changes in the scene hint at suspicious activities like the movement of military vehicles, the application of camouflage nets, or the placement of IEDs, etc. In contrast to broad research activities in remote sensing with optical cameras, this paper addresses the topic using 3D data acquired by mobile laser scanning (MLS). We present a framework for immediate comparison of current MLS data to given 3D reference data. Our method extends the concept of occupancy grids known from robot mapping, which incorporates the sensor positions in the processing of the 3D point clouds. This allows extracting the information that is included in the data acquisition geometry. For each single range measurement, it becomes apparent that an object reflects laser pulses in the measured range distance, i.e., space is occupied at that 3D position. In addition, it is obvious that space is empty along the line of sight between sensor and the reflecting object. Everywhere else, the occupancy of space remains unknown. This approach handles occlusions and changes implicitly, such that the latter are identifiable by conflicts of empty space and occupied space. The presented concept of change detection has been successfully validated in experiments with recorded MLS data streams. Results are shown for test sites at which MLS data were acquired at different time intervals.

  17. Improved instrumental line shape monitoring for the ground-based, high-resolution FTIR spectrometers of the Network for the Detection of Atmospheric Composition Change

    NASA Astrophysics Data System (ADS)

    Hase, F.

    2012-03-01

    We propose an improved monitoring scheme for the instrumental line shape (ILS) of high-resolution, ground-based FTIR (Fourier Transform InfraRed) spectrometers used for chemical monitoring of the atmosphere by the Network for Detection of Atmospheric Composition Change (NDACC). Good ILS knowledge is required for the analysis of the recorded mid-infrared spectra. The new method applies a sequence of measurements using different gas cells instead of a single calibration cell. Three cells are used: cell C1 is a refillable cell offering 200 mm path length and equipped with a pressure gauge (filled with 100 Pa N2O), cells C2 and C3 are sealed cells offering 75 mm path length. C2 is filled with 5 Pa of pure N2O. Cell C3 is filled with 16 Pa N2O in 200 hPa technical air, so provides pressure-broadened N2O lines. We demonstrate that an ILS retrieval using C1 improves significantly the sensitivity of the ILS retrieval over the current calibration cells used in the network, because this cell provides narrow fully saturated N2O lines. The N2O columns derived from C2 and C3 allow the performance of a highly valuable closure experiment: adopting the ILS retrieved from C1, the N2O columns of C2 and C3 are derived. Because N2O is an inert gas, both columns should be constant on long timescales. Apparent changes in the columns would immediately attract attention and indicate either inconsistent ILS results or instrumental problems of other origin. Two different cells are applied for the closure experiment, because the NDACC spectrometers observe both stratospheric and tropospheric gases: C2 mimics signatures of stratospheric gases, whereas C3 mimics signatures of tropospheric gases.

  18. Intrusion detection robust to slow and abrupt lighting changes

    NASA Astrophysics Data System (ADS)

    Makarov, Aleksej; Vesin, Jean-Marc; Reymond, Florian

    1996-03-01

    In this communication we present an image based object detection algorithm which is applied to intrusion detection. The algorithm is based on the comparison of input edges and temporally filtered edges of the background. It is characterized by very low computational and memory loads, high sensitivity to the presence of physical intruders and high robustness to slow and abrupt lighting changes. The algorithm is implementable on a cheap digital signal processor. It was tested on a data base of about one thousand gray-level CIF-format frames representing static scenes with various contents (light sources, intruders, lighting changes), and neither false alarm nor detection failure occurred. The number of parameters involved by the algorithm is very low, and their values do not require a fine tuning. The same set of parameters performs equally well in different conditions: different scenes, various lighting changes, various object sizes.

  19. Modelling Visual Change Detection and Identification under Free Viewing Conditions.

    PubMed

    McAnally, Ken; Martin, Russell

    2016-01-01

    We examined whether the abilities of observers to perform an analogue of a real-world monitoring task involving detection and identification of changes to items in a visual display could be explained better by models based on signal detection theory (SDT) or high threshold theory (HTT). Our study differed from most previous studies in that observers were allowed to inspect the initial display for 3s, simulating the long inspection times typical of natural viewing, and their eye movements were not constrained. For the majority of observers, combined change detection and identification performance was best modelled by a SDT-based process that assumed that memory resources were distributed across all eight items in our displays. Some observers required a parameter to allow for sometimes making random guesses at the identities of changes they had missed. However, the performance of a small proportion of observers was best explained by a HTT-based model that allowed for lapses of attention. PMID:26882348

  20. Olfactory processing: detection of rapid changes.

    PubMed

    Croy, Ilona; Krone, Franziska; Walker, Susannah; Hummel, Thomas

    2015-06-01

    Changes in the olfactory environment have a rather poor chance of being detected. Aim of the present study was to determine, whether the same (cued) or different (uncued) odors can generally be detected at short inter stimulus intervals (ISI) below 2.5 s. Furthermore we investigated, whether inhibition of return, an attentional phenomenon facilitating the detection of new stimuli at longer ISI, is present in the domain of olfaction. Thirteen normosmic people (3 men, 10 women; age range 19-27 years; mean age 23 years) participated. Stimulation was performed using air-dilution olfactometry with 2 odors: phenylethylalcohol and hydrogen disulfide. Reaction time to target stimuli was assessed in cued and uncued conditions at ISIs of 1, 1.5, 2, and 2.5 s. There was a significant main effect of ISI, indicating that odors presented only 1 s apart are missed frequently. Uncued presentation facilitated detection at short ISIs, implying that changes of the olfactory environment are detected better than presentation of the same odor again. Effects in relation to "olfactory inhibition of return," on the other hand, are not supported by our results. This suggests that attention works different for the olfactory system compared with the visual and auditory systems. PMID:25911421

  1. Automated baseline change detection phase I. Final report

    SciTech Connect

    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.

  2. Online change detection: Monitoring land cover from remotely sensed data

    SciTech Connect

    Fang, Yi; Ganguly, Auroop R; Singh, Nagendra; Vijayaraj, Veeraraghavan; Feierabend, Robert Neal; Potere, David T

    2006-01-01

    We present a fast and statistically principled approach to land cover change detection. A reference statistical distribution is fitted to prior data based on off-line analysis, and an adaptive metric based on the exponentially weighted moving average (EWMA) of normal scores derived from p-values are tracked for new or streaming data, leading to alarms for large or sustained change. Methods which can track the origin of the change are also discussed. The approach is illustrated with a geographic application which involves monitoring remotely sensed data to detect changes in the normalized difference vegetation index (NDVI) in near real-time. We use Wal-Mart store openings as a nontraditional way to monitor and validate known cases of NDVI change. The proposed approach performs well on this validation dataset.

  3. Enhancing implicit change detection through action.

    PubMed

    Tseng, Philip; Tuennermann, Jan; Roker-Knight, Nancy; Winter, Dorina; Scharlau, Ingrid; Bridgeman, Bruce

    2010-01-01

    Implicit change detection demonstrates how the visual system can benefit from stored information that is not immediately available to conscious awareness. We investigated the role of motor action in this context. In the first two experiments, using a one-shot implicit change-detection paradigm, participants responded to unperceived changes either with an action (jabbing the screen at the guessed location of a change) or with words (verbal report), and sat either 60 cm or 300 cm (with a laser pointer) away from the display. Our observers guessed the locations of changes at a reachable distance better with an action than with a verbal judgment. At 300 cm, beyond reach, the motor advantage disappeared. In experiment 3, this advantage was also unavailable when participants sat at a reachable distance but responded with hand-held laser pointers near their bodies. We conclude that a motor system specialized for real-time visually guided behavior has access to additional visual information. Importantly, this system is not activated by merely executing an action (experiment 2) or presenting stimuli in one's near space (experiment 3). It is activated only when both conditions are fulfilled, which implies that it is the actual contact that matters to the visual system. PMID:21180353

  4. Detecting changes during pregnancy with Raman spectroscopy

    NASA Astrophysics Data System (ADS)

    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.

  5. A new maximum-likelihood change estimator for two-pass SAR coherent change detection

    DOE PAGESBeta

    Wahl, Daniel E.; Yocky, David A.; Jakowatz, Jr., Charles V.; Simonson, Katherine Mary

    2016-01-11

    In past research, two-pass repeat-geometry synthetic aperture radar (SAR) coherent change detection (CCD) predominantly utilized the sample degree of coherence as a measure of the temporal change occurring between two complex-valued image collects. Previous coherence-based CCD approaches tend to show temporal change when there is none in areas of the image that have a low clutter-to-noise power ratio. Instead of employing the sample coherence magnitude as a change metric, in this paper, we derive a new maximum-likelihood (ML) temporal change estimate—the complex reflectance change detection (CRCD) metric to be used for SAR coherent temporal change detection. The new CRCD estimatormore » is a surprisingly simple expression, easy to implement, and optimal in the ML sense. As a result, this new estimate produces improved results in the coherent pair collects that we have tested.« less

  6. Seabed change detection in challenging environments

    NASA Astrophysics Data System (ADS)

    Matthews, Cameron A.; Sternlicht, Daniel D.

    2011-06-01

    Automatic Change Detection (ACD) compares new and stored terrain images for alerting to changes occurring over time. These techniques, long used in airborne radar, are just beginning to be applied to sidescan sonar. Under the right conditions ACD by image correlation-comparing multi-temporal image data at the pixel or parcel level-can be used to detect new objects on the seafloor. Synthetic aperture sonars (SAS)-coherent sensors that produce fine-scale, range-independent resolution seafloor images-are well suited for this approach; however, dynamic seabed environments can introduce "clutter" to the process. This paper explores an ACD method that uses salience mapping in a global-to-local analysis architecture. In this method, termed Temporally Invariant Saliency (TIS), variance ratios of median-filtered repeat-pass images are used to detect new objects, while deemphasizing modest environmental or radiometric-induced changes in the background. Successful tests with repeat-pass data from two SAS systems mounted on autonomous undersea vehicles (AUV) demonstrate the feasibility of the technique.

  7. Unsupervised Change Detection in SAR Images Using Gaussian Mixture Models

    NASA Astrophysics Data System (ADS)

    Kiana, E.; Homayouni, S.; Sharifi, M. A.; Farid-Rohani, M.

    2015-12-01

    In this paper, we propose a method for unsupervised change detection in Remote Sensing Synthetic Aperture Radar (SAR) images. This method is based on the mixture modelling of the histogram of difference image. In this process, the difference image is classified into three classes; negative change class, positive change class and no change class. However the SAR images suffer from speckle noise, the proposed method is able to map the changes without speckle filtering. To evaluate the performance of this method, two dates of SAR data acquired by Uninhabited Aerial Vehicle Synthetic from an agriculture area are used. Change detection results show better efficiency when compared to the state-of-the-art methods.

  8. Short-term change detection for UAV video

    NASA Astrophysics Data System (ADS)

    Saur, Günter; Krüger, Wolfgang

    2012-11-01

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

  9. Time series change detection: Algorithms for land cover change

    NASA Astrophysics Data System (ADS)

    Boriah, Shyam

    can be used for decision making and policy planning purposes. In particular, previous change detection studies have primarily relied on examining differences between two or more satellite images acquired on different dates. Thus, a technological solution that detects global land cover change using high temporal resolution time series data will represent a paradigm-shift in the field of land cover change studies. To realize these ambitious goals, a number of computational challenges in spatio-temporal data mining need to be addressed. Specifically, analysis and discovery approaches need to be cognizant of climate and ecosystem data characteristics such as seasonality, non-stationarity/inter-region variability, multi-scale nature, spatio-temporal autocorrelation, high-dimensionality and massive data size. This dissertation, a step in that direction, translates earth science challenges to computer science problems, and provides computational solutions to address these problems. In particular, three key technical capabilities are developed: (1) Algorithms for time series change detection that are effective and can scale up to handle the large size of earth science data; (2) Change detection algorithms that can handle large numbers of missing and noisy values present in satellite data sets; and (3) Spatio-temporal analysis techniques to identify the scale and scope of disturbance events.

  10. A Hopfield neural network for image change detection.

    PubMed

    Pajares, Gonzalo

    2006-09-01

    This paper outlines an optimization relaxation approach based on the analog Hopfield neural network (HNN) for solving the image change detection problem between two images. A difference image is obtained by subtracting pixel by pixel both images. The network topology is built so that each pixel in the difference image is a node in the network. Each node is characterized by its state, which determines if a pixel has changed. An energy function is derived, so that the network converges to stable states. The analog Hopfield's model allows each node to take on analog state values. Unlike most widely used approaches, where binary labels (changed/unchanged) are assigned to each pixel, the analog property provides the strength of the change. The main contribution of this paper is reflected in the customization of the analog Hopfield neural network to derive an automatic image change detection approach. When a pixel is being processed, some existing image change detection procedures consider only interpixel relations on its neighborhood. The main drawback of such approaches is the labeling of this pixel as changed or unchanged according to the information supplied by its neighbors, where its own information is ignored. The Hopfield model overcomes this drawback and for each pixel allows a tradeoff between the influence of its neighborhood and its own criterion. This is mapped under the energy function to be minimized. The performance of the proposed method is illustrated by comparative analysis against some existing image change detection methods. PMID:17001985

  11. Evaluation of change detection techniques for monitoring coastal zone environments

    NASA Technical Reports Server (NTRS)

    Weismiller, R. A. (Principal Investigator); Kristof, S. J.; Scholz, D. K.; Anuta, P. E.; Momin, S. M.

    1977-01-01

    The author has identified the following significant results. Four change detection techniques were designed and implemented for evaluation: (1) post classification comparison change detection, (2) delta data change detection, (3) spectral/temporal change classification, and (4) layered spectral/temporal change classification. The post classification comparison technique reliably identified areas of change and was used as the standard for qualitatively evaluating the other three techniques. The layered spectral/temporal change classification and the delta data change detection results generally agreed with the post classification comparison technique results; however, many small areas of change were not identified. Major discrepancies existed between the post classification comparison and spectral/temporal change detection results.

  12. Statistically normalized coherent change detection for synthetic aperture sonar imagery

    NASA Astrophysics Data System (ADS)

    G-Michael, Tesfaye; Tucker, J. D.; Roberts, Rodney G.

    2016-05-01

    Coherent Change Detection (CCD) is a process of highlighting an area of activity in scenes (seafloor) under survey and generated from pairs of synthetic aperture sonar (SAS) images of approximately the same location observed at two different time instances. The problem of CCD and subsequent anomaly feature extraction/detection is complicated due to several factors such as the presence of random speckle pattern in the images, changing environmental conditions, and platform instabilities. These complications make the detection of weak target activities even more difficult. Typically, the degree of similarity between two images measured at each pixel locations is the coherence between the complex pixel values in the two images. Higher coherence indicates little change in the scene represented by the pixel and lower coherence indicates change activity in the scene. Such coherence estimation scheme based on the pixel intensity correlation is an ad-hoc procedure where the effectiveness of the change detection is determined by the choice of threshold which can lead to high false alarm rates. In this paper, we propose a novel approach for anomalous change pattern detection using the statistical normalized coherence and multi-pass coherent processing. This method may be used to mitigate shadows by reducing the false alarms resulting in the coherent map due to speckles and shadows. Test results of the proposed methods on a data set of SAS images will be presented, illustrating the effectiveness of the normalized coherence in terms statistics from multi-pass survey of the same scene.

  13. Improved forest change detection with terrain illumination corrected landsat images

    Technology Transfer Automated Retrieval System (TEKTRAN)

    An illumination correction algorithm has been developed to improve the accuracy of forest change detection from Landsat reflectance data. This algorithm is based on an empirical rotation model and was tested on the Landsat imagery pair over Cherokee National Forest, Tennessee, Uinta-Wasatch-Cache N...

  14. Microwave-Based Biosensor for Glucose Detection

    NASA Astrophysics Data System (ADS)

    Salim, N. S. M.; Khalid, K.; Yusof, N. A.

    2010-07-01

    In this project, microwave-based biosensor for glucose detection has been studied. The study is based on the dielectric properties changes at microwave frequency for glucose-enzyme reaction. Glucose interaction with glucose oxidase (GOD) produced gluconic acid and hydrogen peroxide. The reaction of the glucose solutions with an enzyme was carried out in 1:3 of glucose and enzyme respectively. The measurements were done using the Open Ended Coaxial Probe (OECP) coupled with computer controlled software automated network analyzer (ANA) with frequency range from 200MHz to 20GHz at room temperature (25 °C). The differences of enzyme and glucose-enzyme reaction were calculated and plotted. In the microwave interaction with the glucose-enzyme reaction, ionic conduction and dipole molecules was detected at 0.99GHz and 16.44GHz respectively based on changes of dielectric loss factor.

  15. SAR image change detection using watershed and spectral clustering

    NASA Astrophysics Data System (ADS)

    Niu, Ruican; Jiao, L. C.; Wang, Guiting; Feng, Jie

    2011-12-01

    A new method of change detection in SAR images based on spectral clustering is presented in this paper. Spectral clustering is employed to extract change information from a pair images acquired on the same geographical area at different time. Watershed transform is applied to initially segment the big image into non-overlapped local regions, leading to reduce the complexity. Experiments results and system analysis confirm the effectiveness of the proposed algorithm.

  16. Use of a novel rule-based expert system in the detection of changes in the ST segment and the T wave in long duration ECGs.

    PubMed

    Papaloukas, Costas; Fotiadis, Dimitrios I; Likas, Aristidis; Stroumbis, Christos S; Michalis, Lampros K

    2002-01-01

    The development of a new fast and robust computerised system is examined in detecting electrocardiogram (ECG) changes in long duration ECG recordings. The system distinguishes these changes between ST-segment deviation and T-wave alterations and can support the produced diagnosis by providing explanations for the decisions made. The European Society of Cardiology ST-T Database was used for evaluating the performance of the system. Sensitivity and positive predictive accuracy were the performance measures used and the proposed system scored 92.02% and 93.77%, respectively, in detecting ST-segment episodes and 91.09% and 80.09% in detecting T-wave episodes. By using the chi-square test we also compared the performance of the system between ECG recordings with minimal and substantial amount of noise. The sensitivity of the proposed system is higher than of other algorithms reported in the literature and the positive predictive accuracy is comparable to, or better than, most of them. PMID:11786944

  17. Immunohistochemical Detection of Changes in Tumor Hypoxia

    SciTech Connect

    Russell, James Carlin, Sean; Burke, Sean A.; Wen Bixiu; Yang, Kwang Mo; Ling, C. Clifton

    2009-03-15

    Purpose: Although hypoxia is a known prognostic factor, its effect will be modified by the rate of reoxygenation and the extent to which the cells are acutely hypoxic. We tested the ability of exogenous and endogenous markers to detect reoxygenation in a xenograft model. Our technique might be applicable to stored patient samples. Methods and Materials: The human colorectal carcinoma line, HT29, was grown in nude mice. Changes in tumor hypoxia were examined by injection of pimonidazole, followed 24 hours later by EF5. Cryosections were stained for these markers and for carbonic anhydrase IX (CAIX) and hypoxia-inducible factor 1{alpha} (HIF1{alpha}). Tumor hypoxia was artificially manipulated by carbogen exposure. Results: In unstressed tumors, all four markers showed very similar spatial distributions. After carbogen treatment, pimonidazole and EF5 could detect decreased hypoxia. HIF1{alpha} staining was also decreased relative to CAIX, although the effect was less pronounced than for EF5. Control tumors displayed small regions that had undergone spontaneous changes in tumor hypoxia, as judged by pimonidazole relative to EF5; most of these changes were reflected by CAIX and HIF1{alpha}. Conclusion: HIF1{alpha} can be compared with either CAIX or a previously administered nitroimidazole to provide an estimate of reoxygenation.

  18. Immunohistochemical Detection of Changes in Tumor Hypoxia

    PubMed Central

    Russell, James; Carlin, Sean; Burke, Sean A.; Wen, Bixiu; Yang, Kwang Mo; Ling, C Clifton

    2009-01-01

    Purpose Although hypoxia is a known prognostic factor, its impact will be modified by the rate of reoxygenation and the extent to which cells are acutely hypoxic. We tested the ability of exogenous and endogenous markers to detect reoxygenation in a xenograft model. Our technique may be applicable to stored patient samples. Methods and Materials The human colorectal carcinoma line, HT29 was grown in nude mice. Changes in tumor hypoxia were examined by injection of pimonidazole followed 24 hours later by EF5. Cryosections were stained for these markers and for CAIX and HIF1α. Tumor hypoxia was artificially manipulated by carbogen exposure. Results In unstressed tumors, all four markers showed very similar spatial distributions. After carbogen treatment, pimonidazole and EF5 could detect decreased hypoxia. HIF1α staining was also decreased relative to CAIX, though the effect was less pronounced than for EF5. Control tumors displayed small regions that had undergone spontaneous changes in tumor hypoxia, as judged by pimonidazole relative to EF5; most of these changes were reflected by CAIX and HIF1α Conclusions HIF1α can be compared to either CAIX or a previously administered nitroimidazole to provide an estimate of reoxygenation. PMID:19251089

  19. Urban development change detection based on Multi-Temporal Satellite Images as a fast tracking approach--a case study of Ahwaz County, southwestern Iran.

    PubMed

    Malmir, Maryam; Zarkesh, Mir Masoud Kheirkhah; Monavari, Seyed Masoud; Jozi, Seyed Ali; Sharifi, Esmail

    2015-03-01

    Rapid land-use/land-cover changes in suburbs of metropolitan cities of Iran have recently caused serious environmental damages. Detection of these changes can be a very important step in urban planning and optimal use of natural resources. Accordingly, the present study was carried out to track land-use/land-cover (LULC) changes of Ahwaz County in southwestern Iran using remote sensing techniques over a period of 26 years, from 1987 to 2013. For this, ISODATA algorithm and Maximum Likelihood were initially used for unsupervised and supervised classifications of the satellite images. The accuracy of the LULC maps was checked by the Kappa Coefficient and the Overall Accuracy methods. As the final step, the LULC changes were detected using the cross-tabulation technique. The obtained results indicated that urban and agricultural areas have been increased about 57.5 and 84.5 %, respectively, from 1987 to 2013. Further, the area of poorly vegetated regions, in the same period, has been decreased to approximately 36 %. The largest land conversion area belongs to the poorly vegetated regions, which have been declined to about 10,371 and 1,334 ha during 1987-2007 and 2007-2013, respectively. Approximately 1,670 and 382 ha of the agricultural lands have also been changed to built-up areas by about 1,670 and 382 ha during the same periods. As a result, it was found that the northwest, southwest, and south of the county were highly subjected to urban development. This would be of great importance for urban planning decision-making faced by the planners of the city in the present and future. PMID:25673271

  20. Development of a spatial analysis method using ground-based repeat photography to detect changes in the alpine treeline ecotone, Glacier National Park, Montana, U.S.A.

    USGS Publications Warehouse

    Roush, W.; Munroe, J.S.; Fagre, D.B.

    2007-01-01

    Repeat photography is a powerful tool for detection of landscape change over decadal timescales. Here a novel method is presented that applies spatial analysis software to digital photo-pairs, allowing vegetation change to be categorized and quantified. This method is applied to 12 sites within the alpine treeline ecotone of Glacier National Park, Montana, and is used to examine vegetation changes over timescales ranging from 71 to 93 years. Tree cover at the treeline ecotone increased in 10 out of the 12 photo-pairs (mean increase of 60%). Establishment occurred at all sites, infilling occurred at 11 sites. To demonstrate the utility of this method, patterns of tree establishment at treeline are described and the possible causes of changes within the treeline ecotone are discussed. Local factors undoubtedly affect the magnitude and type of the observed changes, however the ubiquity of the increase in tree cover implies a common forcing mechanism. Mean minimum summer temperatures have increased by 1.5??C over the past century and, coupled with variations in the amount of early spring snow water equivalent, likely account for much of the increase in tree cover at the treeline ecotone. Lastly, shortcomings of this method are presented along with possible solutions and areas for future research. ?? 2007 Regents of the University of Colorado.

  1. Land cover change detection using a GIS-guided, feature-based classification of Landsat thematic mapper data. [Geographic Information System

    NASA Technical Reports Server (NTRS)

    Enslin, William R.; Ton, Jezching; Jain, Anil

    1987-01-01

    Landsat TM data were combined with land cover and planimetric data layers contained in the State of Michigan's geographic information system (GIS) to identify changes in forestlands, specifically new oil/gas wells. A GIS-guided feature-based classification method was developed. The regions extracted by the best image band/operator combination were studied using a set of rules based on the characteristics of the GIS oil/gas pads.

  2. Towards a Framework for Change Detection in Data Sets

    NASA Astrophysics Data System (ADS)

    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.

  3. Analytical and numerical studies of approximate phase velocity matching based nonlinear S0 mode Lamb waves for the detection of evenly distributed microstructural changes

    NASA Astrophysics Data System (ADS)

    Wan, X.; Tse, P. W.; Xu, G. H.; Tao, T. F.; Zhang, Q.

    2016-04-01

    the primary and secondary horizontal displacements generated from nonlinear S0 mode Lamb waves are closest to the real value, which indicates that using horizontal displacements is more suitable for detecting evenly distributed microstructural changes in large thin plate-like structure. Successful application to evaluating material at different levels of evenly distributed fatigue damage is also numerically conducted.

  4. Detecting past changes of effective population size

    PubMed Central

    Nikolic, Natacha; Chevalet, Claude

    2014-01-01

    Understanding and predicting population abundance is a major challenge confronting scientists. Several genetic models have been developed using microsatellite markers to estimate the present and ancestral effective population sizes. However, to get an overview on the evolution of population requires that past fluctuation of population size be traceable. To address the question, we developed a new model estimating the past changes of effective population size from microsatellite by resolving coalescence theory and using approximate likelihoods in a Monte Carlo Markov Chain approach. The efficiency of the model and its sensitivity to gene flow and to assumptions on the mutational process were checked using simulated data and analysis. The model was found especially useful to provide evidence of transient changes of population size in the past. The times at which some past demographic events cannot be detected because they are too ancient and the risk that gene flow may suggest the false detection of a bottleneck are discussed considering the distribution of coalescence times. The method was applied on real data sets from several Atlantic salmon populations. The method called VarEff (Variation of Effective size) was implemented in the R package VarEff and is made available at https://qgsp.jouy.inra.fr and at http://cran.r-project.org/web/packages/VarEff. PMID:25067949

  5. An Investigation of Automatic Change Detection for Topographic Map Updating

    NASA Astrophysics Data System (ADS)

    Duncan, P.; Smit, J.

    2012-08-01

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

  6. On event-based optical flow detection

    PubMed Central

    Brosch, Tobias; Tschechne, Stephan; Neumann, Heiko

    2015-01-01

    Event-based sensing, i.e., the asynchronous detection of luminance changes, promises low-energy, high dynamic range, and sparse sensing. This stands in contrast to whole image frame-wise acquisition by standard cameras. Here, we systematically investigate the implications of event-based sensing in the context of visual motion, or flow, estimation. Starting from a common theoretical foundation, we discuss different principal approaches for optical flow detection ranging from gradient-based methods over plane-fitting to filter based methods and identify strengths and weaknesses of each class. Gradient-based methods for local motion integration are shown to suffer from the sparse encoding in address-event representations (AER). Approaches exploiting the local plane like structure of the event cloud, on the other hand, are shown to be well suited. Within this class, filter based approaches are shown to define a proper detection scheme which can also deal with the problem of representing multiple motions at a single location (motion transparency). A novel biologically inspired efficient motion detector is proposed, analyzed and experimentally validated. Furthermore, a stage of surround normalization is incorporated. Together with the filtering this defines a canonical circuit for motion feature detection. The theoretical analysis shows that such an integrated circuit reduces motion ambiguity in addition to decorrelating the representation of motion related activations. PMID:25941470

  7. Network for the detection of stratospheric change (NDSC)

    NASA Technical Reports Server (NTRS)

    Kurylo, Michael J.

    1991-01-01

    The notion of a ground-based long-term measuring network specifically designed to provide the earliest possible detection of changes in the composition and structure of the stratosphere and to understand the causes of those changes is examined. The network's short-term goals are: to study the temporal and spatial variability of atmospheric composition and structure; to provide the basis for ground truth and complementary measurements for satellite systems such as the NASA Upper Atmosphere Research Satellite; and to critically test multidimensional stratospheric models and provide the broad data base required for improved model development. Priorities, instrumentation, station considerations, and site requirements are also discussed.

  8. Segmentation of Arteries in Minimally Invasive Surgery Using Change Detection

    NASA Astrophysics Data System (ADS)

    Akbari, Hamed; Kosugi, Yukio; Kojima, Kazuyuki

    In laparoscopic surgery, the lack of tactile sensation and 3D visual feedback make it difficult to identify the position of a blood vessel intraoperatively. An unintentional partial tear or complete rupture of a blood vessel may result in a serious complication; moreover, if the surgeon cannot manage this situation, open surgery will be necessary. Differentiation of arteries from veins and other structures and the ability to independently detect them has a variety of applications in surgical procedures involving the head, neck, lung, heart, abdomen, and extremities. We have used the artery's pulsatile movement to detect and differentiate arteries from veins. The algorithm for change detection in this study uses edge detection for unsupervised image registration. Changed regions are identified by subtracting the systolic and diastolic images. As a post-processing step, region properties, including color average, area, major and minor axis lengths, perimeter, and solidity, are used as inputs of the LVQ (Learning Vector Quantization) network. The output results in two object classes: arteries and non-artery regions. After post-processing, arteries can be detected in the laparoscopic field. The registration method used here is evaluated in comparison with other linear and nonlinear elastic methods. The performance of this method is evaluated for the detection of arteries in several laparoscopic surgeries on an animal model and on eleven human patients. The performance evaluation criteria are based on false negative and false positive rates. This algorithm is able to detect artery regions, even in cases where the arteries are obscured by other tissues.

  9. Census cities experiment in urban change detection

    NASA Technical Reports Server (NTRS)

    Wray, J. R. (Principal Investigator)

    1973-01-01

    The author has identified the following significant results. Work continues on mapping of 1970 urban land use from 1970 census contemporaneous aircraft photography. In addition, change detection analysis from 1972 aircraft photography is underway for several urban test sites. Land use maps, mosaics, and census overlays for the two largest urban test sites are nearing publication readiness. Preliminary examinations of ERTS-1 imagery of San Francisco Bay have been conducted which show that tracts of land of more than 10 acres in size which are undergoing development in an urban setting can be identified. In addition, each spectral band is being evaluated as to its utility for urban analyses. It has been found that MSS infrared band 7 helps to differentiate intra-urban land use details not found in other MSS bands or in the RBV coverage of the same scene. Good quality false CIR composites have been generated from 9 x 9 inch positive MSS bands using the Diazo process.

  10. Custom oligonucleotide array-based CGH: a reliable diagnostic tool for detection of exonic copy-number changes in multiple targeted genes

    PubMed Central

    Vasson, Aurélie; Leroux, Céline; Orhant, Lucie; Boimard, Mathieu; Toussaint, Aurélie; Leroy, Chrystel; Commere, Virginie; Ghiotti, Tiffany; Deburgrave, Nathalie; Saillour, Yoann; Atlan, Isabelle; Fouveaut, Corinne; Beldjord, Cherif; Valleix, Sophie; Leturcq, France; Dodé, Catherine; Bienvenu, Thierry; Chelly, Jamel; Cossée, Mireille

    2013-01-01

    The frequency of disease-related large rearrangements (referred to as copy-number mutations, CNMs) varies among genes, and search for these mutations has an important place in diagnostic strategies. In recent years, CGH method using custom-designed high-density oligonucleotide-based arrays allowed the development of a powerful tool for detection of alterations at the level of exons and made it possible to provide flexibility through the possibility of modeling chips. The aim of our study was to test custom-designed oligonucleotide CGH array in a diagnostic laboratory setting that analyses several genes involved in various genetic diseases, and to compare it with conventional strategies. To this end, we designed a 12-plex CGH array (135k; 135 000 probes/subarray) (Roche Nimblegen) with exonic and intronic oligonucleotide probes covering 26 genes routinely analyzed in the laboratory. We tested control samples with known CNMs and patients for whom genetic causes underlying their disorders were unknown. The contribution of this technique is undeniable. Indeed, it appeared reproducible, reliable and sensitive enough to detect heterozygous single-exon deletions or duplications, complex rearrangements and somatic mosaicism. In addition, it improves reliability of CNM detection and allows determination of boundaries precisely enough to direct targeted sequencing of breakpoints. All of these points, associated with the possibility of a simultaneous analysis of several genes and scalability ‘homemade' make it a valuable tool as a new diagnostic approach of CNMs. PMID:23340513

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

    NASA Astrophysics Data System (ADS)

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

    2013-06-01

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

  12. A targeted change-detection procedure by combining change vector analysis and post-classification approach

    NASA Astrophysics Data System (ADS)

    Ye, Su; Chen, Dongmei; Yu, Jie

    2016-04-01

    In remote sensing, conventional supervised change-detection methods usually require effective training data for multiple change types. This paper introduces a more flexible and efficient procedure that seeks to identify only the changes that users are interested in, here after referred to as "targeted change detection". Based on a one-class classifier "Support Vector Domain Description (SVDD)", a novel algorithm named "Three-layer SVDD Fusion (TLSF)" is developed specially for targeted change detection. The proposed algorithm combines one-class classification generated from change vector maps, as well as before- and after-change images in order to get a more reliable detecting result. In addition, this paper introduces a detailed workflow for implementing this algorithm. This workflow has been applied to two case studies with different practical monitoring objectives: urban expansion and forest fire assessment. The experiment results of these two case studies show that the overall accuracy of our proposed algorithm is superior (Kappa statistics are 86.3% and 87.8% for Case 1 and 2, respectively), compared to applying SVDD to change vector analysis and post-classification comparison.

  13. Detection of nanoscale structural changes in bone using random lasers

    PubMed Central

    Song, Qinghai; Xu, Zhengbin; Choi, Seung Ho; Sun, Xuanhao; Xiao, Shumin; Akkus, Ozan; Kim, Young L.

    2010-01-01

    We demonstrate that the unique characteristics of random lasing in bone can be used to assess nanoscale structural alterations as a mechanical or structural biosensor, given that bone is a partially disordered biological nanostructure. In this proof-of-concept study, we conduct photoluminescence experiments on cortical bone specimens that are loaded in tension under mechanical testing. The ultra-high sensitivity, the large detection area, and the simple detection scheme of random lasers allow us to detect prefailure damage in bone at very small strains before any microscale damage occurs. Random laser-based biosensors could potentially open a new possibility for highly sensitive detection of nanoscale structural and mechanical alterations prior to overt microscale changes in hard tissue and biomaterials. PMID:21258558

  14. Nanomaterials based biosensors for cancer biomarker detection

    NASA Astrophysics Data System (ADS)

    Malhotra, Bansi D.; Kumar, Saurabh; Mouli Pandey, Chandra

    2016-04-01

    Biosensors have enormous potential to contribute to the evolution of new molecular diagnostic techniques for patients suffering with cancerous diseases. A major obstacle preventing faster development of biosensors pertains to the fact that cancer is a highly complex set of diseases. The oncologists currently rely on a few biomarkers and histological characterization of tumors. Some of the signatures include epigenetic and genetic markers, protein profiles, changes in gene expression, and post-translational modifications of proteins. These molecular signatures offer new opportunities for development of biosensors for cancer detection. In this context, conducting paper has recently been found to play an important role towards the fabrication of a biosensor for cancer biomarker detection. In this paper we will focus on results of some of the recent studies obtained in our laboratories relating to fabrication and application of nanomaterial modified paper based biosensors for cancer biomarker detection.

  15. Impact of LANDSAT MSS sensor differences on change detection analysis

    NASA Technical Reports Server (NTRS)

    Likens, W. C.; Wrigley, R. C.

    1983-01-01

    Some 512 by 512 pixel subwindows for simultaneously acquired scene pairs obtained by LANDSAT 2,3 and 4 multispectral band scanners were coregistered using LANDSAT 4 scenes as the base to which the other images were registered. Scattergrams between the coregistered scenes (a form of contingency analysis) were used to radiometrically compare data from the various sensors. Mode values were derived and used to visually fit a linear regression. Root mean square errors of the registration varied between .1 and 1.5 pixels. There appear to be no major problem preventing the use of LANDSAT 4 MSS with previous MSS sensors for change detection, provided the noise interference can be removed or minimized. Data normalizations for change detection should be based on the data rather than solely on calibration information. This allows simultaneous normalization of the atmosphere as well as the radiometry.

  16. Thiazole orange as a fluorescent probe: Label-free and selective detection of silver ions based on the structural change of i-motif DNA at neutral pH.

    PubMed

    Kang, Bei Hua; Gao, Zhong Feng; Li, Na; Shi, Yan; Li, Nian Bing; Luo, Hong Qun

    2016-08-15

    Silver ions have been widely applied to many fields and have harmful effects on environments and human health. Herein, a label-free optical sensor for Ag(+) detection is constructed based on thiazole orange (TO) as a fluorescent probe for the recognition of i-motif DNA structure change at neutral pH. Ag(+) can fold a C-rich single stranded DNA sequence into i-motif DNA structure at neutral pH and that folding is reversible by chelation with cysteine (Cys). The DNA folding process can be indicated by the fluorescence change of TO, which is non-fluorescent in free molecule state and emits strong fluorescence after the incorporation with i-motif DNA. Thus, a rapid, sensitive, and selective method for the detection of Ag(+) and Cys is developed with a detection limit of 17 and 280nM, respectively. It is worth noting that the mechanism underlying the increase of the fluorescence of thiazole orange in the presence of i-motif structure is explained. Moreover, a fluorescent DNA logic gate is successfully designed based on the Ag(+)/Cys-mediated reversible fluorescence changes. The proposed detection strategy is label-free and economical. In addition, this system shows a great promise for i-motif/TO complex to analyze Ag(+) in the real samples. PMID:27260446

  17. Street environment change detection from mobile laser scanning point clouds

    NASA Astrophysics Data System (ADS)

    Xiao, Wen; Vallet, Bruno; Brédif, Mathieu; Paparoditis, Nicolas

    2015-09-01

    Mobile laser scanning (MLS) has become a popular technique for road inventory, building modelling, infrastructure management, mobility assessment, etc. Meanwhile, due to the high mobility of MLS systems, it is easy to revisit interested areas. However, change detection using MLS data of street environment has seldom been studied. In this paper, an approach that combines occupancy grids and a distance-based method for change detection from MLS point clouds is proposed. Unlike conventional occupancy grids, our occupancy-based method models space based on scanning rays and local point distributions in 3D without voxelization. A local cylindrical reference frame is presented for the interpolation of occupancy between rays according to the scanning geometry. The Dempster-Shafer theory (DST) is utilized for both intra-data evidence fusion and inter-data consistency assessment. Occupancy of reference point cloud is fused at the location of target points and then the consistency is evaluated directly on the points. A point-to-triangle (PTT) distance-based method is combined to improve the occupancy-based method. Because it is robust to penetrable objects, e.g. vegetation, which cause self-conflicts when modelling occupancy. The combined method tackles irregular point density and occlusion problems, also eliminates false detections on penetrable objects.

  18. Ensembles of detectors for online detection of transient changes

    NASA Astrophysics Data System (ADS)

    Artemov, Alexey; Burnaev, Evgeny

    2015-12-01

    Classical change-point detection procedures assume a change-point model to be known and a change consisting in establishing a new observations regime, i.e. the change lasts infinitely long. These modeling assumptions contradicts applied problems statements. Therefore, even theoretically optimal statistics in practice very often fail when detecting transient changes online. In this work in order to overcome limitations of classical change-point detection procedures we consider approaches to constructing ensembles of change-point detectors, i.e. algorithms that use many detectors to reliably identify a change-point. We propose a learning paradigm and specific implementations of ensembles for change detection of short-term (transient) changes in observed time series. We demonstrate by means of numerical experiments that the performance of an ensemble is superior to that of the conventional change-point detection procedures.

  19. Groundwater storage change detection using micro-gravimetric technology

    NASA Astrophysics Data System (ADS)

    El-Diasty, Mohammed

    2016-06-01

    In this paper, new perspectives and developments in applying a ground-based micro-gravimetric method to detect groundwater storage change in Waterloo Moraine are investigated. Four epochs of gravity survey were conducted using absolute gravimeter (FG5), two relative gravity meters (CG5) and two geodetic global positioning systems (GPS) in the Waterloo Moraine in May and August of 2010 and 2011, respectively. Data were processed using the parametric least-squares method and integrated with geological and hydrological studies. The gravity differences between May and August for 2010 and 2011 epochs were inverted to provide the estimated total water storage changes. Changes in soil water content obtained from land surface models of Ecological Assimilation of Land and Climate Observations (EALCO) and the Global Land Data Assimilation System (GLDAS) program were employed to estimate the groundwater storage change. The ratios between the estimated groundwater storage changes and measured water table changes (specific yields) were determined at a local monitoring well located in the survey area. The results showed that the estimates of specific yields between May and August of 2010 and 2011 were consistent at a significant confidence level and are also within the range of the specific yield from geological and hydrological studies. Therefore, the micro-gravimetric (absolute and relative gravity meters) technology has demonstrated the great potential in detecting groundwater storage change and specific yield for local scale aquifers such as Waterloo Moraine.

  20. Effects of Disease Detection on Changes in Smoking Behavior

    PubMed Central

    Kwon, Jeoung A; Jeon, Wooman; Park, Eun-Cheol; Kim, Jae-Hyun; Kim, Sun Jung; Yoo, Ki-Bong; Lee, Minjee

    2015-01-01

    Purpose This study was conducted to investigate the effect that detection of chronic disease via health screening programs has on health behaviors, particularly smoking. Materials and Methods We analyzed national health insurance data from 2007 and 2009. Subjects who were 40 years of age in 2007 and eligible for the life cycle-based national health screening program were included. The total study population comprised 153518 individuals who participated in the screening program in 2007 and follow-up screening in 2009. Multiple logistic regression analyses were conducted by sex, with adjustment for health insurance type, socioeconomic status, body mass index, diabetes, hypertension, hyperlipidemia, and family history of cardiovascular and/or neurovascular disease. Results Among men with smoking behavior changes, those newly diagnosed with hyperlipidemia were more likely to show a positive health behavior change, such as smoking cessation, and were less likely to have a negative behavior change (e.g., smoking initiation). Additionally, men newly diagnosed with diabetes showed lower rates of negative health behavior changes compared to those without disease. Body mass index (BMI)≥25, compared to BMI<23, showed higher rates of positive health behavior changes and lower rates of negative health behavior changes. Newly diagnosed chronic disease did not influence smoking behavior in women. Conclusion Smoking behavior changes were only detected in men who participated in health screening programs. In particular, those newly diagnosed with hyperlipidemia were more likely to stop smoking and less likely to start smoking. PMID:26069141

  1. Visible light communication based motion detection.

    PubMed

    Sewaiwar, Atul; Tiwari, Samrat Vikramaditya; Chung, Yeon-Ho

    2015-07-13

    In this paper, a unique and novel visible light communication based motion detection is presented. The proposed motion detection is performed based on white light LEDs and an array of photodetectors from existing visible light communication (VLC) links, thus providing VLC with three functionalities of illumination, communication and motion detection. The motion is detected by observing the pattern created by intentional obstruction of the VLC link. Experimental and simulation results demonstrate the validity of the proposed VLC based motion detection technique. The VLC based motion detection can benefit smart devices control in VLC based smart home environments. PMID:26191937

  2. Population variability complicates the accurate detection of climate change responses.

    PubMed

    McCain, Christy; Szewczyk, Tim; Bracy Knight, Kevin

    2016-06-01

    The rush to assess species' responses to anthropogenic climate change (CC) has underestimated the importance of interannual population variability (PV). Researchers assume sampling rigor alone will lead to an accurate detection of response regardless of the underlying population fluctuations of the species under consideration. Using population simulations across a realistic, empirically based gradient in PV, we show that moderate to high PV can lead to opposite and biased conclusions about CC responses. Between pre- and post-CC sampling bouts of modeled populations as in resurvey studies, there is: (i) A 50% probability of erroneously detecting the opposite trend in population abundance change and nearly zero probability of detecting no change. (ii) Across multiple years of sampling, it is nearly impossible to accurately detect any directional shift in population sizes with even moderate PV. (iii) There is up to 50% probability of detecting a population extirpation when the species is present, but in very low natural abundances. (iv) Under scenarios of moderate to high PV across a species' range or at the range edges, there is a bias toward erroneous detection of range shifts or contractions. Essentially, the frequency and magnitude of population peaks and troughs greatly impact the accuracy of our CC response measurements. Species with moderate to high PV (many small vertebrates, invertebrates, and annual plants) may be inaccurate 'canaries in the coal mine' for CC without pertinent demographic analyses and additional repeat sampling. Variation in PV may explain some idiosyncrasies in CC responses detected so far and urgently needs more careful consideration in design and analysis of CC responses. PMID:26725404

  3. Eye Movements and Display Change Detection during Reading

    ERIC Educational Resources Information Center

    Slattery, Timothy J.; Angele, Bernhard; Rayner, Keith

    2011-01-01

    In the boundary change paradigm (Rayner, 1975), when a reader's eyes cross an invisible boundary location, a preview word is replaced by a target word. Readers are generally unaware of such changes due to saccadic suppression. However, some readers detect changes on a few trials and a small percentage of them detect many changes. Two experiments…

  4. Change detection in remote sensing images using modified polynomial regression and spatial multivariate alteration detection

    NASA Astrophysics Data System (ADS)

    Dianat, Rouhollah; Kasaei, Shohreh

    2009-11-01

    A new and efficient method for incorporating the spatiality into difference-based change detection (CD) algorithms is introduced in this paper. It uses the spatial derivatives of image pixels to extract spatial relations among them. Based on this methodology, the performances of two famous difference-based CD methods, conventional polynomial regression (CPR) and multivariate alteration detection (MAD), are improved and called modified polynomial regression (MPR) and spatial multivariate alteration detection (SMAD), respectively. Various quantitative and qualitative evaluations have shown the superiority of MPR over CPR and SMAD over MAD. Also, the superiority of SMAD over all mentioned CD algorithms is shown. Moreover, it has been proved that both proposed methods enjoy the affine invariance property.

  5. A method for detecting changes in long time series

    SciTech Connect

    Downing, D.J.; Lawkins, W.F.; Morris, M.D.; Ostrouchov, G.

    1995-09-01

    Modern scientific activities, both physical and computational, can result in time series of many thousands or even millions of data values. Here the authors describe a statistically motivated algorithm for quick screening of very long time series data for the presence of potentially interesting but arbitrary changes. The basic data model is a stationary Gaussian stochastic process, and the approach to detecting a change is the comparison of two predictions of the series at a time point or contiguous collection of time points. One prediction is a ``forecast``, i.e. based on data from earlier times, while the other a ``backcast``, i.e. based on data from later times. The statistic is the absolute value of the log-likelihood ratio for these two predictions, evaluated at the observed data. A conservative procedure is suggested for specifying critical values for the statistic under the null hypothesis of ``no change``.

  6. DOM Based XSS Detecting Method Based on Phantomjs

    NASA Astrophysics Data System (ADS)

    Dong, Ri-Zhan; Ling, Jie; Liu, Yi

    Because malicious code does not appear in html source code, DOM based XSS cannot be detected by traditional methods. By analyzing the causes of DOM based XSS, this paper proposes a detection method of DOM based XSS based on phantomjs. This paper uses function hijacking to detect dangerous operation and achieves a prototype system. Comparing with existing tools shows that the system improves the detection rate and the method is effective to detect DOM based XSS.

  7. Detecting the significance of changes in performance on the Stroop Color-Word Test, Rey's Verbal Learning Test, and the Letter Digit Substitution Test: the regression-based change approach.

    PubMed

    Van der Elst, Wim; Van Boxtel, Martin P J; Van Breukelen, Gerard J P; Jolles, Jelle

    2008-01-01

    Serial neuropsychological assessment is often conducted to monitor changes in the cognitive abilities of individuals over time. Because practice effects occur and the reliability of test scores is less than perfect, it is difficult to judge whether varying test results should be attributed to chance trends or to real changes in underlying cognitive abilities. In a large sample of adults (age range, 49-81 years), we evaluated the influence of age, gender, and education on test-retest changes in performance after 3 years on Rey's Verbal Learning Test (VLT), the Stroop Color-Word Test (SCWT), and the Letter Digit Substitution Test (LDST). A new statistical method was applied to assess the significance of changes in test performance (i.e., the regression-based change method). The results showed that test-retest changes differed as a function of age for the VLT Total recall 1-3, VLT Total recall 1-5, VLT Delayed recall, and LDST measures. An age x gender interaction was found for the SCWT Interference change score, suggesting that the age-related decline in executive functioning after 3 years was more pronounced for males than for females. A normative change table with appropriate corrections for the relevant independent variables was established. PMID:18078533

  8. What factors determine Belgian general practitioners’ approaches to detecting and managing substance abuse? A qualitative study based on the I-Change Model

    PubMed Central

    2014-01-01

    Background General practitioners (GPs) are considered to play a major role in detecting and managing substance abuse. However, little is known about how or why they decide to manage it. This study investigated the factors that influence GP behaviours with regard to the abuse of alcohol, illegal drugs, hypnotics, and tranquilisers among working Belgians. Methods Twenty Belgian GPs were interviewed. De Vries’ Integrated Change Model was used to guide the interviews and qualitative data analyses. Results GPs perceived higher levels of substance abuse in urban locations and among lower socioeconomic groups. Guidelines, if they existed, were primarily used in Flanders. Specific training was unevenly applied but considered useful. GPs who accepted abuse management cited strong interpersonal skills and available multidisciplinary networks as facilitators. GPs relied on their clinical common sense to detect abuse or initiate management. Specific patients’ situations and their social, psychological, or professional dysfunctions were cited as cues to action. GPs were strongly influenced by their personal representations of abuse, which included the balance between their professional responsibilities toward their patients and the patients’ responsibilities in managing their own health as well the GPs’ abilities to cope with unsatisfying patient outcomes without reaching professional exhaustion. GPs perceived substance abuse along a continuum ranging from a chronic disease (whose management was part of their responsibility) to a moral failing of untrustworthy people. Alcohol and cannabis were more socially acceptable than other drugs. Personal experiences of emotional burdens (including those regarding substance abuse) increased feelings of empathy or rejection toward patients. Multidisciplinary practices and professional experiences were cited as important factors with regard to engaging GPs in substance abuse management. Time constraints and personal investments were

  9. Preparing an E-learning-based Speech Therapy (EST) efficacy study: Identifying suitable outcome measures to detect within-subject changes of speech intelligibility in dysarthric speakers.

    PubMed

    Beijer, L J; Rietveld, A C M; Ruiter, M B; Geurts, A C H

    2014-12-01

    We explored the suitability of perceptual and acoustic outcome measures to prepare E-learning based Speech Therapy (EST) efficacy tests regarding speech intelligibility in dysarthric speakers. Eight speakers with stroke (n=3), Parkinson's disease (n=4) and traumatic brain injury (n=1) participated in a 4 weeks EST trial. A repeated measures design was employed. Perceptual measures were (a) scale ratings for "ease of intelligibility" and "pleasantness" in continuous speech and (b) orthographic transcription scores of semantically unpredictable sentences. Acoustic measures were (c) "intensity during closure" (ΔIDC) in the occlusion phase of voiceless plosives, (d) changes in the vowel space of /a/, /e/ and /o/ and (e) the F0 variability in semantically unpredictable sentences. The only consistent finding concerned an increased (instead of the expected decreased) ΔIDC after EST, possibly caused by increased speech intensity without articulatory adjustments. The importance of suitable perceptual and acoustic measures for efficacy research is discussed. PMID:25025268

  10. Detection of temporal changes in earthquake rates

    NASA Astrophysics Data System (ADS)

    Touati, S.

    2012-12-01

    Many statistical analyses of earthquake rates and time-dependent forecasting of future rates involve the detection of changes in the basic rate of events, independent of the fluctuations caused by aftershock sequences. We examine some of the statistical techniques for inferring these changes, using both real and synthetic earthquake data to check the statistical significance of these inferences. One common method is to use the Akaike Information Criterion (AIC) to choose between a single model and a double model with a changepoint; this criterion evaluates the strength of the fit and incorporates a penalty for the extra parameters. We test this method on many realisations of the ETAS model, with and without changepoints present, to see how often it chooses the correct model. A more rigorous method is to calculate the Bayesian evidence, or marginal likelihood, for each model and then compare these. The evidence is essentially the likelihood of the model integrated over the whole of the model space, giving a measure of how likely the data is for that model. It does not rely on estimation of best-fit parameters, making it a better comparator than the AIC; Occam's razor also arises naturally in this process due to the fact that more complex models tend to be able to explain a larger range of observations, and therefore the relative likelihood of any particular observations will be smaller than for a simpler model. Evidence can be calculated using Markov Chain Monte Carlo techniques. We compare these two approaches on synthetic data. We also look at the 1997-98 Colfiorito sequence in Umbria-Marche, Italy, using maximum likelihood to fit the ETAS model and then simulating the ETAS model to create synthetic versions of the catalogue for comparison. We simulate using ensembles of parameter values sampled from the posterior for each parameter, with the largest events artificially inserted, to compare the resultant event rates, inter-event time distributions and other

  11. Water Detection Based on Color Variation

    NASA Technical Reports Server (NTRS)

    Rankin, Arturo L.

    2012-01-01

    This software has been designed to detect water bodies that are out in the open on cross-country terrain at close range (out to 30 meters), using imagery acquired from a stereo pair of color cameras mounted on a terrestrial, unmanned ground vehicle (UGV). This detector exploits the fact that the color variation across water bodies is generally larger and more uniform than that of other naturally occurring types of terrain, such as soil and vegetation. Non-traversable water bodies, such as large puddles, ponds, and lakes, are detected based on color variation, image intensity variance, image intensity gradient, size, and shape. At ranges beyond 20 meters, water bodies out in the open can be indirectly detected by detecting reflections of the sky below the horizon in color imagery. But at closer range, the color coming out of a water body dominates sky reflections, and the water cue from sky reflections is of marginal use. Since there may be times during UGV autonomous navigation when a water body does not come into a perception system s field of view until it is at close range, the ability to detect water bodies at close range is critical. Factors that influence the perceived color of a water body at close range are the amount and type of sediment in the water, the water s depth, and the angle of incidence to the water body. Developing a single model of the mixture ratio of light reflected off the water surface (to the camera) to light coming out of the water body (to the camera) for all water bodies would be fairly difficult. Instead, this software detects close water bodies based on local terrain features and the natural, uniform change in color that occurs across the surface from the leading edge to the trailing edge.

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

    SciTech Connect

    Byler, E.

    1997-10-31

    The primary objective of this project is to apply robotic and optical sensor technology to the operational inspection of mixed toxic and radioactive waste stored in barrels, using Automated Baseline Change Detection (ABCD), based on image subtraction. Absolute change detection is based on detecting any visible physical changes, regardless of cause, between a current inspection image of a barrel and an archived baseline image of the same barrel. Thus, in addition to rust, the ABCD system can also detect corrosion, leaks, dents, and bulges. The ABCD approach and method rely on precise camera positioning and repositioning relative to the 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.

  13. Multi-lane detection based on multiple vanishing points detection

    NASA Astrophysics Data System (ADS)

    Li, Chuanxiang; Nie, Yiming; Dai, Bin; Wu, Tao

    2015-03-01

    Lane detection plays a significant role in Advanced Driver Assistance Systems (ADAS) for intelligent vehicles. In this paper we present a multi-lane detection method based on multiple vanishing points detection. A new multi-lane model assumes that a single lane, which has two approximately parallel boundaries, may not parallel to others on road plane. Non-parallel lanes associate with different vanishing points. A biological plausibility model is used to detect multiple vanishing points and fit lane model. Experimental results show that the proposed method can detect both parallel lanes and non-parallel lanes.

  14. Probabilistic Change Detection Framework for Analyzing Settlement Dynamics Using Very High-resolution Satellite Imagery

    SciTech Connect

    Vatsavai, Raju; Graesser, Jordan B

    2012-01-01

    Global human population growth and an increasingly urbanizing world have led to rapid changes in human settlement landscapes and patterns. Timely monitoring and assessment of these changes and dissemination of accurate information is important for policy makers, city planners, and humanitarian relief workers. Satellite imagery provides useful data for the aforementioned applications, and remote sensing can be used to identify and quantify change areas. We explore a probabilistic framework to identify changes in human settlements using very high-resolution satellite imagery. As compared to predominantly pixel-based change detection systems which are highly sensitive to image registration errors, our grid (block) based approach is more robust to registration errors. The presented framework is an automated change detection system applicable to both panchromatic and multi-spectral imagery. The detection system provides comprehensible information about change areas, and minimizes the post-detection thresholding procedure often needed in traditional change detection algorithms.

  15. Detection of building changes from aerial images and light detection and ranging (LIDAR) data

    NASA Astrophysics Data System (ADS)

    Chen, Liang-Chien; Lin, Li-Jer

    2010-11-01

    Building models are built to provide three-dimensional (3-D) spatial information, which is needed in a variety of applications including city planning, construction management, location-based services of urban infrastructures, and the like. However, 3-D building models have to be updated on a timely manner to meet the changing demand. Rather than reconstructing building models for the entire area, it would be more convenient and effective to only update parts of the areas where there were changes. This paper aims at developing a new method, namely double-threshold strategy, to find such changes within 3-D building models in the region of interest with the aid of light detection and ranging (LIDAR) data. The proposed modeling scheme comprises three steps, namely, data pre-processing, change detection in building areas, and validation. In the first step for data pre-processing, data registration was carried out based on multi-source data. The second step for data pre-processing requires using the triangulation of an irregular network of data points collected by Light Detection And Ranging (LIDAR), focusing on those locations containing walls or other above-ground objects that were ever removed. Then, change detection in the building models can be made possible for finding differences in height by comparing the LIDAR point measurements and the estimates of the building models. The results may be further refined using spectral and feature information collected from aerial imagery. A double-threshold strategy was applied to cope with the highly sensitive thresholding often encountered when using the rule-based approach. Finally, ground truth data were used for model validation. Research findings clearly indicate that the double-threshold strategy improves the overall accuracy from 93.1% to 95.9%.

  16. Object-based analysis and change detection of the major wetland cover types during the low water period at Poyang Lake, PRC

    NASA Astrophysics Data System (ADS)

    Dronova, I.; Wang, L.; Gong, P.

    2010-12-01

    Productive wetland systems at the land-water interfaces that provide unique ecosystem and habitat services are challenging to study because of the dynamic water table, complex surface cover and constrained ground access. We applied object-based image analysis (OBIA) to 32-m spatial resolution Beijing-1 microsatellite imagery to examine broad-scale surface cover composition and its change during November 2007-March 2008 low water season at Poyang Lake, the largest freshwater lake-wetland system in China (>4000 km2). We explored a novel method for semi-automated selection of training objects in a heterogeneous natural landscape using the extreme values of spectral indices (SIs) estimated from satellite data. We found that spatial extent of the water table did not decline over the whole low water period but instead followed a variable trajectory declining during Nov07-Jan08 and increasing again during Jan-Mar08. Among the major cover types of Water, Mudflat, Sand and Vegetation, the latter was the dominant class. Vegetation expanded from 33% to 45% of the total Poyang Lake area during Nov07-Jan08 and continued colonizing exposed bottomland during Jan-Mar 08, consistent to the progression of the cool growing season. Mudflat appeared to be the most “fuzzy” class mixed with both Water and Vegetation at finer spatial scales. Our results suggest that considering vegetation phenology is important for interpretation of change trajectories, since senescence of aquatic plant beds may expose new Water and Mudlfat areas without the expansion or shrinking of the existing water table. The observed variation in broad-scale cover types has important implications for fluxes of carbon and other nutrients and wildlife habitat features in this heterogeneous landscape. The mapped classes can be used as meaningful strata for future analyses of the ecological components of the Poyang Lake system and for targeting field sampling efforts.

  17. Detecting holocene changes in thermohaline circulation.

    PubMed

    Keigwin, L D; Boyle, E A

    2000-02-15

    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. PMID:10677463

  18. A modified approach for change detection using change vector analysis in posterior probability space

    NASA Astrophysics Data System (ADS)

    Azzouzi, S. A.; Vidal, A.; Bentounes, H. A.

    2015-04-01

    The multispectral and multitemporal data coming from satellites allow us to extract valuable spatiotemporal change. Consequently, Earth surface change detection analysis has been used in the past to monitor land cover changes caused by different reasons. Several techniques have been used for that purpose and change vector analysis (CVA) has been frequently employed to carry out automatic spatiotemporal information extraction. This work describes a modified methodology based on Supervised Change Vector Analysis in Posterior probability Space (SCVAPS) with the final aim of obtaining a change detection map in Blida, Algeria. The proposed technique is a Modified version of Supervised Change Vector Analysis Posterior probability Space (MSCVAPS) and it is applied at the same region that the original technique studied in the literature. The classical Maximum Likelihood classifier is the selected method for supervised classification since it provides good properties in the posterior probability map. An improved method for threshold determination based on Double Flexible Pace Search (DFPS) is proposed in this work and it is employed to obtain the most adequate threshold value. Then, the MSCVAPS approach is evaluated by two cases study of the land cover change detection in the region of Blida, Algeria, and in the region of Shunyi District, Beijing, China, using a pair of Landsat Thematic Mapper images and pair of Landsat Enhanced Thematic Mapper images, respectively. The final evaluation is given by the overall accuracy of changed and unchanged pixels and the kappa coefficient. The results show that the modified approach gives excellent results using the same area of study that was selected in the literature.

  19. Cardiovascular magnetic resonance imaging-based computational fluid dynamics/fluid-structure interaction pilot study to detect early vascular changes in pediatric patients with type 1 diabetes.

    PubMed

    Samyn, Margaret M; Dholakia, Ronak; Wang, Hongfeng; Co-Vu, Jennifer; Yan, Ke; Widlansky, Michael E; LaDisa, John F; Simpson, Pippa; Alemzadeh, Ramin

    2015-04-01

    We hypothesized that pediatric patients with type 1 diabetes have cardiac magnetic resonance (CMR) detectable differences in thoracic aortic wall properties and hemodynamics leading to significant local differences in indices of wall shear stress, when compared with age-matched control subjects without diabetes. Pediatric patients with type 1 diabetes were recruited from Children's Hospital of Wisconsin and compared with controls. All underwent morning CMR scanning, 4-limb blood pressure, brachial artery reactivity testing, and venipuncture. Patient-specific computational fluid dynamics modeling with fluid-structure interaction, based on CMR data, determined regional time-averaged wall shear stress (TAWSS) and oscillatory shear index (OSI). Twenty type 1 diabetic subjects, median age 15.8 years (11.6-18.4) and 8 controls 15.4 years (10.3-18.2) were similar except for higher glucose, hemoglobin A1c, and triglycerides for type 1 diabetic subjects. Lower flow-mediated dilation was seen for those with type 1 diabetes (6.5) versus controls (7.8), p = 0.036. For type 1 diabetic subjects, the aorta had more regions with high TAWSS when compared to controls. OSI maps appeared similar. Flow-mediated dilation positively correlated with age at diabetes diagnosis (r = 0.468, p = 0.038) and hemoglobin A1c (r = 0.472, p = 0.036), but did not correlate with aortic distensibility, TAWSS, or OSI. TAWSS did not correlate with any clinical parameter for either group. CMR shows regional differences in aortic wall properties for young diabetic patients. Some local differences in wall shear stress indices were also observed, but a longitudinal study is now warranted. PMID:25577225

  20. Change detection on a hunch: pre-attentive vision allows "sensing" of unique feature changes.

    PubMed

    Ball, Felix; Busch, Niko A

    2015-11-01

    Studies on change detection and change blindness have investigated the nature of visual representations by testing the conditions under which observers are able to detect when an object in a complex scene changes from one moment to the next. Several authors have proposed that change detection can occur without identification of the changing object, but the perceptual processes underlying this phenomenon are currently unknown. We hypothesized that change detection without localization or identification occurs when the change happens outside the focus of attention. Such changes would usually go entirely unnoticed, unless the change brings about a modification of one of the feature maps representing the scene. Thus, the appearance or disappearance of a unique feature might be registered even in the absence of focused attention and without feature binding, allowing for change detection, but not localization or identification. We tested this hypothesis in three experiments, in which changes either involved colors that were already present elsewhere in the display or entirely unique colors. Observers detected whether any change had occurred and then localized or identified the change. Change detection without localization occurred almost exclusively when changes involved a unique color. Moreover, change detection without localization for unique feature changes was independent of the number of objects in the display and independent of change identification. These findings suggest that pre-attentive registration of a change on a feature map can give rise to a conscious experience even when feature binding has failed: that something has changed without knowing what or where. PMID:26353860

  1. Automated image based prominent nucleoli detection

    PubMed Central

    Yap, Choon K.; Kalaw, Emarene M.; Singh, Malay; Chong, Kian T.; Giron, Danilo M.; Huang, Chao-Hui; Cheng, Li; Law, Yan N.; Lee, Hwee Kuan

    2015-01-01

    Introduction: Nucleolar changes in cancer cells are one of the cytologic features important to the tumor pathologist in cancer assessments of tissue biopsies. However, inter-observer variability and the manual approach to this work hamper the accuracy of the assessment by pathologists. In this paper, we propose a computational method for prominent nucleoli pattern detection. Materials and Methods: Thirty-five hematoxylin and eosin stained images were acquired from prostate cancer, breast cancer, renal clear cell cancer and renal papillary cell cancer tissues. Prostate cancer images were used for the development of a computer-based automated prominent nucleoli pattern detector built on a cascade farm. An ensemble of approximately 1000 cascades was constructed by permuting different combinations of classifiers such as support vector machines, eXclusive component analysis, boosting, and logistic regression. The output of cascades was then combined using the RankBoost algorithm. The output of our prominent nucleoli pattern detector is a ranked set of detected image patches of patterns of prominent nucleoli. Results: The mean number of detected prominent nucleoli patterns in the top 100 ranked detected objects was 58 in the prostate cancer dataset, 68 in the breast cancer dataset, 86 in the renal clear cell cancer dataset, and 76 in the renal papillary cell cancer dataset. The proposed cascade farm performs twice as good as the use of a single cascade proposed in the seminal paper by Viola and Jones. For comparison, a naive algorithm that randomly chooses a pixel as a nucleoli pattern would detect five correct patterns in the first 100 ranked objects. Conclusions: Detection of sparse nucleoli patterns in a large background of highly variable tissue patterns is a difficult challenge our method has overcome. This study developed an accurate prominent nucleoli pattern detector with the potential to be used in the clinical settings. PMID:26167383

  2. An unsupervised support vector method for change detection

    NASA Astrophysics Data System (ADS)

    Bovolo, F.; Camps-Valls, G.; Bruzzone, L.

    2007-10-01

    This paper formulates the problem of distinguishing changed from unchanged pixels in remote sensing images as a minimum enclosing ball (MEB) problem with changed pixels as target class. The definition of the sphere shaped decision boundary with minimal volume that embraces changed pixels is approached in the context the support vector formalism adopting a support vector domain description (SVDD) one-class classifier. The SVDD maps the data into a high dimensional feature space where the spherical support of the high dimensional distribution of changed pixels is computed. The proposed formulation of the SVDD uses both target and outlier samples for defining the MEB, and is included here in an unsupervised system for change detection. For this purpose, nearly certain examples for the classes of both targets (i.e., changed pixels) and outliers (i.e., unchanged pixels) for training are identified based on thresholding the magnitude of spectral change vectors. Experimental results obtained on two different multitemporal and multispectral remote sensing images pointed out the effectiveness of the proposed method.

  3. Integration of Landsat TM and SPOT HRG Images for Vegetation Change Detection in the Brazilian Amazon

    PubMed Central

    Lu, Dengsheng; Batistella, Mateus; Moran, Emilio

    2009-01-01

    Traditional change detection approaches have been proven to be difficult in detecting vegetation changes in the moist tropical regions with multitemporal images. This paper explores the integration of Landsat Thematic Mapper (TM) and SPOT High Resolution Geometric (HRG) instrument data for vegetation change detection in the Brazilian Amazon. A principal component analysis was used to integrate TM and HRG panchromatic data. Vegetation change/non-change was detected with the image differencing approach based on the TM and HRG fused image and the corresponding TM image. A rule-based approach was used to classify the TM and HRG multispectral images into thematic maps with three coarse land-cover classes: forest, non-forest vegetation, and non-vegetation lands. A hybrid approach combining image differencing and post-classification comparison was used to detect vegetation change trajectories. This research indicates promising vegetation change techniques, especially for vegetation gain and loss, even if very limited reference data are available. PMID:19789721

  4. Geocentric position preliminary detection from the extreme ultraviolet images of Chang'E-3

    NASA Astrophysics Data System (ADS)

    Zheng, Chen; Ping, Jinsong; Wang, Mingyuan; Li, Wenxiao

    2015-08-01

    An Extreme ultraviolet (EUV) Camera was installed onboard the Chinese lunar surface landing mission, the Chang'E-3 lander, as a useful method to observe the Earth plasmasphere. This EUV optical payload obtained more than 600 moon-based Earth plasmasphere images since December 14, 2013. However, due to errors of unknown size and origin in the platform attitude control of the lander and in the EUV telescope pointing control during the mission operating periods, the geocentric coordinates in these EUV images are not fixed in the same position of CCD pixel. Before adequately calibrating, these positioning offsets will introduce extra errors into the analysis of the plasmaspheric structure. With only a little insufficient telemetry information, an effective calibrating method of circle-based differential algorithm is suggested and demonstrated, for automatically and precisely detecting the geocentric position in each EUV image of Chang'E-3 mission. In each EUV image, the tested method uses the outline of a circle as the basic unit to capture the contour for the bright region based on the spectral characteristic. Then, the center of the extracted circle is adopted as the geocentric position for the image. The preliminary analysis shows that this method can effectively detect the geocentric position being always consistent with the recognition result by the basic hand labor method. It is found that the radius of the circles varies from month to month from December, 2013 to May, 2014. The monthly averages of radius show relative notable positive correlation and negative correlation with the changes of both Zenith angle of the Earth at the landing area of Chang'E-3 lander, and the Earth-moon distance, respectively. This method and results here will benefit the Chang'E-3 EUV study.

  5. Symmetrized local co-registration optimization for anomalous change detection

    SciTech Connect

    Wohlberg, Brendt E; Theiler, James P

    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.

  6. Occupancy change detection system and method

    SciTech Connect

    Bruemmer, David J; Few, Douglas A

    2009-09-01

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

  7. Two stages of parafoveal processing during reading: Evidence from a display change detection task.

    PubMed

    Angele, Bernhard; Slattery, Timothy J; Rayner, Keith

    2016-08-01

    We used a display change detection paradigm (Slattery, Angele, & Rayner Human Perception and Performance, 37, 1924-1938 2011) to investigate whether display change detection uses orthographic regularity and whether detection is affected by the processing difficulty of the word preceding the boundary that triggers the display change. Subjects were significantly more sensitive to display changes when the change was from a nonwordlike preview than when the change was from a wordlike preview, but the preview benefit effect on the target word was not affected by whether the preview was wordlike or nonwordlike. Additionally, we did not find any influence of preboundary word frequency on display change detection performance. Our results suggest that display change detection and lexical processing do not use the same cognitive mechanisms. We propose that parafoveal processing takes place in two stages: an early, orthography-based, preattentional stage, and a late, attention-dependent lexical access stage. PMID:26769246

  8. Transistor-based particle detection systems and methods

    DOEpatents

    Jain, Ankit; Nair, Pradeep R.; Alam, Muhammad Ashraful

    2015-06-09

    Transistor-based particle detection systems and methods may be configured to detect charged and non-charged particles. Such systems may include a supporting structure contacting a gate of a transistor and separating the gate from a dielectric of the transistor, and the transistor may have a near pull-in bias and a sub-threshold region bias to facilitate particle detection. The transistor may be configured to change current flow through the transistor in response to a change in stiffness of the gate caused by securing of a particle to the gate, and the transistor-based particle detection system may configured to detect the non-charged particle at least from the change in current flow.

  9. Automated Detection of Changes on the Lunar Surface

    NASA Astrophysics Data System (ADS)

    Cook, A.; Gibbens, M.

    2005-08-01

    Although the Moon is considered to be geologically dormant, surface altering events visible to orbiting spacecraft must still occur, albeit infrequently e.g. fresh impact craters detected from Apollo imagery. Given a surface area of 3.8E7 km2 and the 40 year time frame spanning Lunar Orbiter to SMART-1 missions, it is likely that 10's-100's of surface changes measurable in the > 50m scale range may be detected by automatically comparing temporal images of the same areas under similar (< 5 deg difference) incidence and emission angles. Automated tie-pointing and image footprint overlap detection developed from Clementine stereo research can be used to select suitable overlapping temporal image pairs of a given area. These can then be automatically registered/warped together, photometrically calibrated to each other and subtracted to leave a difference image. Differences that exceed 3 standard deviations across the image can then be compared to the most recent mosaics of optical maturity in order to confirm whether a suspected area of change is aligned with fresh non-spaceweathered parts of the surface. Knowledge that could be gained from such a study could include: 1) confirmation of cratering rate assumptions that were made from the Apollo ALSEP seismometers, 2) identification of surface disturbances by ejecta from impacts detected by Apollo seismometer, or Earth based telescopic impact flash observations; these can then be used to help relate estimated impact energy to crater size, 3) the areal extent of dust transport from impact ejecta, landslides, or other suspected mechanisms such as residual outgassing or electrostaic levitation of dust. All three of these have important implications for future surface based exploration in identifying sites of interest that can be either monitored over time to study the progression of space weathering, or for studying freshly excavated underlying geology.

  10. Competitive SWIFT cluster templates enhance detection of aging changes

    PubMed Central

    Rebhahn, Jonathan A.; Roumanes, David R.; Qi, Yilin; Khan, Atif; Thakar, Juilee; Rosenberg, Alex; Lee, F. Eun‐Hyung; Quataert, Sally A.; Sharma, Gaurav

    2015-01-01

    Abstract Clustering‐based algorithms for automated analysis of flow cytometry datasets have achieved more efficient and objective analysis than manual processing. Clustering organizes flow cytometry data into subpopulations with substantially homogenous characteristics but does not directly address the important problem of identifying the salient differences in subpopulations between subjects and groups. Here, we address this problem by augmenting SWIFT—a mixture model based clustering algorithm reported previously. First, we show that SWIFT clustering using a “template” mixture model, in which all subpopulations are represented, identifies small differences in cell numbers per subpopulation between samples. Second, we demonstrate that resolution of inter‐sample differences is increased by “competition” wherein a joint model is formed by combining the mixture model templates obtained from different groups. In the joint model, clusters from individual groups compete for the assignment of cells, sharpening differences between samples, particularly differences representing subpopulation shifts that are masked under clustering with a single template model. The benefit of competition was demonstrated first with a semisynthetic dataset obtained by deliberately shifting a known subpopulation within an actual flow cytometry sample. Single templates correctly identified changes in the number of cells in the subpopulation, but only the competition method detected small changes in median fluorescence. In further validation studies, competition identified a larger number of significantly altered subpopulations between young and elderly subjects. This enrichment was specific, because competition between templates from consensus male and female samples did not improve the detection of age‐related differences. Several changes between the young and elderly identified by SWIFT template competition were consistent with known alterations in the elderly, and additional

  11. Detection of ocean color changes from high altitudes

    NASA Technical Reports Server (NTRS)

    Hovis, W. A.; Forman, M. L.; Blaine, L. R.

    1973-01-01

    The detection of ocean color changes, thought to be due to chlorophyll concentrations and gelbstoffe variations, is attempted from high altitude (11.3km) and low altitude (0.3km). The atmospheric back scattering is shown to reduce contrast, but not sufficiently to obscure color change detection at high altitudes.

  12. Uncertainty in Estimation of Bioenergy Induced Lulc Change: Development of a New Change Detection Technique.

    NASA Astrophysics Data System (ADS)

    Singh, N.; Vatsavai, R. R.; Patlolla, D.; Bhaduri, B. L.; Lim, S. J.

    2015-12-01

    Recent estimates of bioenergy induced land use land cover change (LULCC) have large uncertainty due to misclassification errors in the LULC datasets used for analysis. These uncertainties are further compounded when data is modified by merging classes, aggregating pixels and change in classification methods over time. Hence the LULCC computed using these derived datasets is more a reflection of change in classification methods, change in input data and data manipulation rather than reflecting actual changes ion ground. Furthermore results are constrained by geographic extent, update frequency and resolution of the dataset. To overcome this limitation we have developed a change detection system to identify yearly as well as seasonal changes in LULC patterns. Our method uses hierarchical clustering which works by grouping objects into a hierarchy based on phenological similarity of different vegetation types. The algorithm explicitly models vegetation phenology to reduce spurious changes. We apply our technique on globally available Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI data at 250-meter resolution. We analyze 10 years of bi-weekly data to predict changes in the mid-western US as a case study. The results of our analysis are presented and its advantages over existing techniques are discussed.

  13. Detecting abrupt climate changes on different time scales

    NASA Astrophysics Data System (ADS)

    Matyasovszky, István

    2011-10-01

    Two concepts are introduced for detecting abrupt climate changes. In the first case, the sampling frequency of climate data is high as compared to the frequency of climate events examined. The method is based on a separation of trend and noise in the data and is applicable to any dataset that satisfies some mild smoothness and statistical dependence conditions for the trend and the noise, respectively. We say that an abrupt change occurs when the first derivative of the trend function has a discontinuity and the task is to identify such points. The technique is applied to Northern Hemisphere temperature data from 1850 to 2009, Northern Hemisphere temperature data from proxy data, a.d. 200-1995 and Holocene δ18O values going back to 11,700 years BP. Several abrupt changes are detected that are, among other things, beneficial for determining the Medieval Warm Period, Little Ice Age and Holocene Climate Optimum. In the second case, the sampling frequency is low relative to the frequency of climate events studied. A typical example includes Dansgaard-Oeschger events. The methodology used here is based on a refinement of autoregressive conditional heteroscedastic models. The key element of this approach is the volatility that characterises the time-varying variance, and abrupt changes are defined by high volatilities. The technique applied to δ18O values going back to 122,950 years BP is suitable for identifying DO events. These two approaches for the two cases are closely related despite the fact that at first glance, they seem quite different.

  14. Mutual Comparative Filtering for Change Detection in Videos with Unstable Illumination Conditions

    NASA Astrophysics Data System (ADS)

    Sidyakin, Sergey V.; Vishnyakov, Boris V.; Vizilter, Yuri V.; Roslov, Nikolay I.

    2016-06-01

    In this paper we propose a new approach for change detection and moving objects detection in videos with unstable, abrupt illumination changes. This approach is based on mutual comparative filters and background normalization. We give the definitions of mutual comparative filters and outline their strong advantage for change detection purposes. Presented approach allows us to deal with changing illumination conditions in a simple and efficient way and does not have drawbacks, which exist in models that assume different color transformation laws. The proposed procedure can be used to improve a number of background modelling methods, which are not specifically designed to work under illumination changes.

  15. Detection of DNA utilizing a fluorescent reversible change of a biosensor based on the electron transfer from quantum dots to polymyxin B sulfate.

    PubMed

    Wang, Linlin; Liu, Shaopu; Liang, Wanjun; Li, Dan; Yang, Jidong; He, Youqiu

    2015-06-15

    A fluorescent "turn off-on" pattern for the detection of herring sperm DNA (hsDNA) had been designed through utilizing the interaction between polymyxin B sulfate (PMBS) and hsDNA as an inherent performance and the fluorescent transformation of glutathione (GSH)-capped CdTe quantum dots (QDs) as an external manifestation. Due to the occurrence of the photoinduced electron transfer from the QDs to PMBS, the fluorescence of GSH-capped CdTe QDs could be effectively quenched by PMBS, causing the system into "off" state. With the addition of hsDNA, the quenched fluorescence of GSH-capped CdTe QDs could be restored for the reason that PMBS embedded into hsDNA double helix structure to form new complex and peeled off from the surface of GSH-capped CdTe QDs, leading the system into "on" condition. Corresponding experimental results illustrated that the relative recovered fluorescence intensity of GSH-capped CdTe QDs-PMBS system was near proportional to the concentration of hsDNA within the range of 0.059-15.0 μg mL(-1). This proposed method demonstrated a good linear correlation coefficient of 0.9937 and a detection limit (3 σ/K) of 0.018 μg mL(-1) for hsDNA. This dual-directional fluorescent biosensor overcame the selectivity problem commonly existed in the traditional mono-directional fluorescence detection mode and owned perfect analysis applications in biochemical DNA monitoring. PMID:25744859

  16. Simulation framework for spatio-spectral anomalous change detection

    SciTech Connect

    Theiler, James P; Harvey, Neal R; Porter, Reid B; Wohlberg, Brendt E

    2009-01-01

    The authors describe the development of a simulation framework for anomalous change detection that considers both the spatial and spectral aspects of the imagery. A purely spectral framework has previously been introduced, but the extension to spatio-spectral requires attention to a variety of new issues, and requires more careful modeling of the anomalous changes. Using this extended framework, they evaluate the utility of spatial image processing operators to enhance change detection sensitivity in (simulated) remote sensing imagery.

  17. A new statistical approach to climate change detection and attribution

    NASA Astrophysics Data System (ADS)

    Ribes, Aurélien; Zwiers, Francis W.; Azaïs, Jean-Marc; Naveau, Philippe

    2016-04-01

    We propose here a new statistical approach to climate change detection and attribution that is based on additive decomposition and simple hypothesis testing. Most current statistical methods for detection and attribution rely on linear regression models where the observations are regressed onto expected response patterns to different external forcings. These methods do not use physical information provided by climate models regarding the expected response magnitudes to constrain the estimated responses to the forcings. Climate modelling uncertainty is difficult to take into account with regression based methods and is almost never treated explicitly. As an alternative to this approach, our statistical model is only based on the additivity assumption; the proposed method does not regress observations onto expected response patterns. We introduce estimation and testing procedures based on likelihood maximization, and show that climate modelling uncertainty can easily be accounted for. Some discussion is provided on how to practically estimate the climate modelling uncertainty based on an ensemble of opportunity. Our approach is based on the "models are statistically indistinguishable from the truth" paradigm, where the difference between any given model and the truth has the same distribution as the difference between any pair of models, but other choices might also be considered. The properties of this approach are illustrated and discussed based on synthetic data. Lastly, the method is applied to the linear trend in global mean temperature over the period 1951-2010. Consistent with the last IPCC assessment report, we find that most of the observed warming over this period (+0.65 K) is attributable to anthropogenic forcings (+0.67 ± 0.12 K, 90 % confidence range), with a very limited contribution from natural forcings (-0.01± 0.02 K).

  18. Changing Diagnostic Methods and Increased Detection of Verotoxigenic Escherichia coli, Ireland.

    PubMed

    Rice, Thomas; Quinn, Noreen; Sleator, Roy D; Lucey, Brigid

    2016-09-01

    The recent paradigm shift in infectious disease diagnosis from culture-based to molecular-based approaches is exemplified in the findings of a national study assessing the detection of verotoxigenic Escherichia coli infections in Ireland. The methodologic changes have been accompanied by a dramatic increase in detections of non-O157 verotoxigenic E. coli serotypes. PMID:27322897

  19. Changing Diagnostic Methods and Increased Detection of Verotoxigenic Escherichia coli, Ireland

    PubMed Central

    Rice, Thomas; Quinn, Noreen; Lucey, Brigid

    2016-01-01

    The recent paradigm shift in infectious disease diagnosis from culture-based to molecular-based approaches is exemplified in the findings of a national study assessing the detection of verotoxigenic Escherichia coli infections in Ireland. The methodologic changes have been accompanied by a dramatic increase in detections of non-O157 verotoxigenic E. coli serotypes. PMID:27322897

  20. Improved change detection with local co-registration adjustments

    SciTech Connect

    Wohlberg, Brendt E; Theiler, James P

    2009-01-01

    We introduce a simple approach for compensating for residual misregistration error on the performance of anomalous change detection algorithms. Using real data with a simulation framework for anomalous change and with a real anomalous change, we illustrate the approach and investigate its effectiveness.

  1. Vibration-Based Damage Detection in Rotating Machinery

    SciTech Connect

    Farrar, C.R.; Duffey, T.A.

    1999-06-28

    Damage detection as determined from changes in the vibration characteristics of a system has been a popular research topic for the last thirty years. Numerous damage identification algorithms have been proposed for detecting and locating damage in structural and mechanical systems. To date, these damage-detection methods have shown mixed results. A particular application of vibration-based damage detection that has perhaps enjoyed the greatest success is that of damage detection in rotating machinery. This paper summarizes the state of technology in vibration-based damage detection applied to rotating machinery. The review interprets the damage detection process in terms of a statistical pattern recognition paradigm that encompasses all vibration-based damage detection methods and applications. The motivation for the study reported herein is to identify the reasons that vibration-based damage detection has been successfully applied to rotating machinery, but has yet to show robust applications to civil engineering infrastructure. The paper concludes by comparing and contrasting the vibration-based damage detection applied to rotating machinery with large civil engineering infrastructure applications.

  2. Relative Saliency in Change Signals Affects Perceptual Comparison and Decision Processes in Change Detection

    ERIC Educational Resources Information Center

    Yang, Cheng-Ta

    2011-01-01

    Change detection requires perceptual comparison and decision processes on different features of multiattribute objects. How relative salience between two feature-changes influences the processes has not been addressed. This study used the systems factorial technology to investigate the processes when detecting changes in a Gabor patch with visual…

  3. Detecting data and schema changes in scientific documents

    SciTech Connect

    Adiwijaya, I; Critchlow, T; Musick, R

    1999-06-08

    Data stored in a data warehouse must be kept consistent and up-to-date with the underlying information sources. By providing the capability to identify, categorize and detect changes in these sources, only the modified data needs to be transferred and entered into the warehouse. Another alternative, periodically reloading from scratch, is obviously inefficient. When the schema of an information source changes, all components that interact with, or make use of, data originating from that source must be updated to conform to the new schema. In this paper, the authors present an approach to detecting data and schema changes in scientific documents. Scientific data is of particular interest because it is normally stored as semi-structured documents, and it incurs frequent schema updates. They address the change detection problem by detecting data and schema changes between two versions of the same semi-structured document. This paper presents a graph representation of semi-structured documents and their schema before describing their approach to detecting changes while parsing the document. It also discusses how analysis of a collection of schema changes obtained from comparing several individual can be used to detect complex schema changes.

  4. An example of fingerprint detection of greenhouse climate changes

    SciTech Connect

    Karoly, D.J.; Cohen, J.A.; Meehl, G.A.

    1994-07-01

    As an example of the technique of fingerprint detection of greenhouse climate change, a multivariate signal or fingerprint of the enhanced greenhouse effect is defined using the zonal mean atmospheric temperature change as a function of height and latitude between equilibrium climate model simulations with control and doubled CO{sub 2} concentrations. This signal is compared with observed atmospheric temperature variations over the period 1963 to 1988 from radiosonde-based global analyses. There is a signiificant increase of this greenhouse signal in the observational data over this period. These results must be treated with caution. Upper air data are available for a short period only, possibly, to be able to resolve any real greenhouse climate change. The greenhouse fingerprint used in this study may not be unique to the enhanced greenhouse effect and may be due to other forcing mechanisms. However, it is shown that the patterns of atmospheric temperature change associated with uniform global increases of sea surface temperature, with El Nino-Southern Oscillation events and with decreases of stratospheric ozone concentrations individually are different from the greenhouse fingerprint used here. 30 refs., 6 figs., 2 tabs.

  5. Detection of light transformations and concomitant changes in surface albedo

    PubMed Central

    Gerhard, Holly E.; Maloney, Laurence T.

    2010-01-01

    We report two experiments demonstrating that (1) observers are sensitive to information about changes in the light field not captured by local scene statistics and that (2) they can use this information to enhance detection of changes in surface albedo. Observers viewed scenes consisting of matte surfaces at many orientations illuminated by a collimated light source. All surfaces were achromatic, all lights neutral. In the first experiment, observers attempted to discriminate small changes in direction of the collimated light source (light transformations) from matched changes in the albedos of all surfaces (non-light transformations). Light changes and non-light changes shared the same local scene statistics and edge ratios, but the latter were not consistent with any change in direction to the collimated source. We found that observers could discriminate light changes as small as 5 degrees with sensitivity d′ > 1 and accurately judge the direction of change. In a second experiment, we measured observers' ability to detect a change in the surface albedo of an isolated surface patch during either a light change or a surface change. Observers were more accurate in detecting isolated albedo changes during light changes. Measures of sensitivity d′ were more than twice as great. PMID:20884599

  6. Detecting and isolating abrupt changes in linear switching systems

    NASA Astrophysics Data System (ADS)

    Nazari, Sohail; Zhao, Qing; Huang, Biao

    2015-04-01

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

  7. Classification of change detection and change blindness from near-infrared spectroscopy signals

    NASA Astrophysics Data System (ADS)

    Tanaka, Hirokazu; Katura, Takusige

    2011-08-01

    Using a machine-learning classification algorithm applied to near-infrared spectroscopy (NIRS) signals, we classify a success (change detection) or a failure (change blindness) in detecting visual changes for a change-detection task. Five subjects perform a change-detection task, and their brain activities are continuously monitored. A support-vector-machine algorithm is applied to classify the change-detection and change-blindness trials, and correct classification probability of 70-90% is obtained for four subjects. Two types of temporal shapes in classification probabilities are found: one exhibiting a maximum value after the task is completed (postdictive type), and another exhibiting a maximum value during the task (predictive type). As for the postdictive type, the classification probability begins to increase immediately after the task completion and reaches its maximum in about the time scale of neuronal hemodynamic response, reflecting a subjective report of change detection. As for the predictive type, the classification probability shows an increase at the task initiation and is maximal while subjects are performing the task, predicting the task performance in detecting a change. We conclude that decoding change detection and change blindness from NIRS signal is possible and argue some future applications toward brain-machine interfaces.

  8. Detection and Attribution of Regional Climate Change

    SciTech Connect

    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.

  9. Detection of changes in DNA methylation induced by different doses of ground-base ion radiation in rice(oryza sativa L.)

    NASA Astrophysics Data System (ADS)

    Zhao, Qian; Sun, Yeqing; Wang, Wei; Wen, Bin

    Spaceflight represents a very complex environmental condition with highly ionizing radiations (HZE). To further investigate the incentives of ion effects in space environment, we performed on-ground simulated HZE particle radiations to rice seeds with different cumulative doses (0Gy, 0.01Gy, 0.02Gy, 0.1Gy, 0.2Gy, 1Gy , 2Gy, 5Gy, 20Gy ). Using Methylation-Sensitive Amplification Polymorphism (MSAP) analysis technology, differential polymorphism sites of DNA methylation of seedlings were analysed and acquired. The results showed that changes of methylation and demethylation on CCGG sites had taken place after irradiated treatments in all doses. It was noted that there was a stimulating effect in low-dose radiation(≤1 Gy). The minimum proportion of DNA methylation polymorphism level was 3.15% in 0.1Gy, whereas the maximum proportion was 9.87% in 2Gy, interestingly the proportion reduced with radiation doses increased, suggesting the dosage effects of radiation. We further found that the CG site tended to have a higher proportion of cytosine methylation alterations than CNG site in six of the eight dose groups. The results also indicated that different dose treatment groups showed various frequencies of methylation variation patterns: The type of CG hypermethylation was higher than CG hypormethylation in four low-dose groups (<≤2 Gy) ,whereas the result presented the opposite trends in all high-dose groups(>≥1 Gy). In addition, the type of CNG hypormethylation was obviously higher than the CNG hypermethylation in seven dose groups. This result indicated that the methylation variation patterns caused by radiation had site preferences. To investigate the mechanisms of sequences underlying alterations in DNA methylation after ion irradiation, we isolated, cloned and sequenced a subset of bands which showed obvious mutational bias. BLAST analysis indicated that many sequences showed significant homology to known function genes, most of which were related to

  10. Daytime Water Detection Based on Sky Reflections

    NASA Technical Reports Server (NTRS)

    Rankin, Arturo; Matthies, Larry; Bellutta, Paolo

    2011-01-01

    A water body s surface can be modeled as a horizontal mirror. Water detection based on sky reflections and color variation are complementary. A reflection coefficient model suggests sky reflections dominate the color of water at ranges > 12 meters. Water detection based on sky reflections: (1) geometrically locates the pixel in the sky that is reflecting on a candidate water pixel on the ground (2) predicts if the ground pixel is water based on color similarity and local terrain features. Water detection has been integrated on XUVs.

  11. Change detection using the synchronous impulse reconstruction (SIRE) radar

    NASA Astrophysics Data System (ADS)

    Ranney, Kenneth; Nguyen, Lam; Ressler, Marc; Stanton, Brian; Wong, David; Koenig, Francois; Tran, Chi; Kirose, Getachew; Martone, Anthony; Smith, Greg; Sichina, Jeff; Kappra, Karl

    2008-04-01

    Change detection provides a powerful tool for detecting the introduction of weapons or hazardous materials into an area under surveillance, as demonstrated in past work carried out at the Army Research Laboratory (ARL). This earlier work demonstrated the potential for detecting recently emplaced surface landmines using an X-Band, synthetic aperture radar (SAR) sensor. Recent experiments conducted at ARL have extended these change detection results to imagery collected by the synthetic impulse reconstruction (SIRE) radar - a lower-frequency system developed at ARL. In this paper we describe the algorithms adopted for this change detection experiment and present results obtained by applying these algorithms to the SIRE data set. Results indicate the potential for utilizing systems such as the SIRE as surveillance tools.

  12. Universal scene change detection on MPEG-coded data domain

    NASA Astrophysics Data System (ADS)

    Nakajima, Yasuyuki; Ujihara, Kiyono; Yoneyama, Akio

    1997-01-01

    In this paper, we propose scene decomposition algorithm from MPEG compressed video data. As a preprocessing for scene decomposition, partial reconstruction methods of DC image for P- and B-pictures as well as I-pictures directly from MPEG bitstream are used. As for detection algorithms, we have exploited several methods for detection of abrupt scene change, dissolve and wipe transitions using comparison of DC images between frames and coding information such as motion vectors. It is also proposed the method for exclusion of undesired detection such as flashlight in order to enhance scene change detection accuracy. It is shown that more than 95 percent of decomposition accuracy has been obtained in the experiment using more than one hour TV program. It is also found that in the proposed algorithm scene change detection can be performed more than 5 times faster than normal playback speed using 130MIPS workstation.

  13. Detection of Greenhouse-Gas-Induced Climatic Change

    SciTech Connect

    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.

  14. Fast Change Point Detection for Electricity Market Analysis

    SciTech Connect

    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.

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

    NASA Technical Reports Server (NTRS)

    Morizumi, N.; Kimura, H.

    1986-01-01

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

  16. Intelligent-based Structural Damage Detection Model

    SciTech Connect

    Lee, Eric Wai Ming; Yu, K.F.

    2010-05-21

    This paper presents the application of a novel Artificial Neural Network (ANN) model for the diagnosis of structural damage. The ANN model, denoted as the GRNNFA, is a hybrid model combining the General Regression Neural Network Model (GRNN) and the Fuzzy ART (FA) model. It not only retains the important features of the GRNN and FA models (i.e. fast and stable network training and incremental growth of network structure) but also facilitates the removal of the noise embedded in the training samples. Structural damage alters the stiffness distribution of the structure and so as to change the natural frequencies and mode shapes of the system. The measured modal parameter changes due to a particular damage are treated as patterns for that damage. The proposed GRNNFA model was trained to learn those patterns in order to detect the possible damage location of the structure. Simulated data is employed to verify and illustrate the procedures of the proposed ANN-based damage diagnosis methodology. The results of this study have demonstrated the feasibility of applying the GRNNFA model to structural damage diagnosis even when the training samples were noise contaminated.

  17. Sociolect-Based Community Detection

    SciTech Connect

    Reynolds, William N.; Salter, William J.; Farber, Robert M.; Corley, Courtney D.; Dowling, Chase P.; Beeman, William O.; Smith-Lovin, Lynn; Choi, Joon Nak

    2013-06-06

    "Sociolects" are specialized vocabularies used by social subgroups defined by common interests or origins. We applied methods to retrieve large quantities of Twitter data based on expert-identified sociolects and then applied and developed network-analysis methods to relate sociolect use to network (sub-) structure. We show that novel methods including consideration of node populations, as well as edge counts, provide substantially enhanced performance compared to standard assortativity. We explain these methods, show their utility in analyzing large corpora of social media data, and discuss their further extensions and potential applications.

  18. Real-time SAR change-detection using neural networks

    NASA Astrophysics Data System (ADS)

    Oliver, Christopher J.; White, Richard G.

    1990-11-01

    This paper describes the techniques evolved at RSRE for the production of undistorted, focused synthetic aperture radar (SAR) images, target detection using a neural network method and the automatic detection of changes between pairs of SAR images. All these processes are achievable in a single pipelined process operating on an input data rate in excess of 10 Mbytes/second.

  19. Collaborative regression-based anatomical landmark detection

    NASA Astrophysics Data System (ADS)

    Gao, Yaozong; Shen, Dinggang

    2015-12-01

    Anatomical landmark detection plays an important role in medical image analysis, e.g. for registration, segmentation and quantitative analysis. Among the various existing methods for landmark detection, regression-based methods have recently attracted much attention due to their robustness and efficiency. In these methods, landmarks are localised through voting from all image voxels, which is completely different from the classification-based methods that use voxel-wise classification to detect landmarks. Despite their robustness, the accuracy of regression-based landmark detection methods is often limited due to (1) the inclusion of uninformative image voxels in the voting procedure, and (2) the lack of effective ways to incorporate inter-landmark spatial dependency into the detection step. In this paper, we propose a collaborative landmark detection framework to address these limitations. The concept of collaboration is reflected in two aspects. (1) Multi-resolution collaboration. A multi-resolution strategy is proposed to hierarchically localise landmarks by gradually excluding uninformative votes from faraway voxels. Moreover, for informative voxels near the landmark, a spherical sampling strategy is also designed at the training stage to improve their prediction accuracy. (2) Inter-landmark collaboration. A confidence-based landmark detection strategy is proposed to improve the detection accuracy of ‘difficult-to-detect’ landmarks by using spatial guidance from ‘easy-to-detect’ landmarks. To evaluate our method, we conducted experiments extensively on three datasets for detecting prostate landmarks and head & neck landmarks in computed tomography images, and also dental landmarks in cone beam computed tomography images. The results show the effectiveness of our collaborative landmark detection framework in improving landmark detection accuracy, compared to other state-of-the-art methods.

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

    SciTech Connect

    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.

  1. Vegetation cover change detection in Chamela-Cuixamala, Mexico

    NASA Astrophysics Data System (ADS)

    De la Barreda Bautista, Betsabé; López-Caloca, Alejandra A.

    2009-09-01

    In Mexico, and everywhere else, the ecosystems are constantly changing either by natural factors or anthropogenic activity. Remote sensing has been a key tool to monitoring these changes throughout history and also to understanding the ecological dynamics. Hence, sustainable development plans have been created in order to improve the decisionmaking process; thus, this paper analyses deforestation impact in a very important natural resourcing area in Mexico, considering land cover changes. The study area is located in the coast of Jalisco, Mexico, where deforestation and fragmentation as well as high speed touristic development have been the causes of enormous biodiversity losses; the Chamela-Cuixamala Biosphere Reserve is located within this area. It has great species richness and vast endemism. The exploitation of this biome is widespread all over the country and it has already had an impact in the reserve. The change detection multi-temporal study uses Landsat satellite imagery during the 1970-2003 time period. Thus, the objective of change detection analysis is to detect and localize environmental changes through time. The change detection method consists in producing an image of change likelihood (by post-classification, multivariate alteration detection) and thresholding it in order to produce the change map. Experimental results confirmed that the patterns of land use and land cover changes have increased significantly over the last decade. This study also analyzes the deforestation impact on biodiversity. The analysis validation was carried out using field and statistic data. Spatial-temporal changing range enables the analysis of the structural and dynamic effects on the ecosystem and it enhances better decision-making and public environmental policies to decrease or eliminate deforestation, the creation of natural protected areas as a biodiversity conservation method, and counteracting the global warming phenomena.

  2. Detection and Attribution of Anthropogenic Climate Change Impacts

    NASA Technical Reports Server (NTRS)

    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.

  3. Monitoring land-cover changes in the Terminos Lagoon region, Mexico: A comparison of change detection techniques

    SciTech Connect

    Mas, J.F.

    1997-06-01

    Six change detection procedures were tested using Landsat MSS images for detecting areas of changes in the region of the Terminos Lagoon, a coastal zone of the State of Campeche, Mexico. The change detection techniques considered were image differencing, vegetative index differencing, selective principal components analysis, direct multidate unsupervised classification, post-classification change differencing and a combination of image enhancement and post-classification comparison. Accuracy of the results obtained by each technique was evaluated by comparison with aerial photographs through Kappa coefficient calculation. Post-classification comparison was found to be the most accurate procedure and presents the advantage to indicate the nature of the changes. Poor performances obtained by image enhancement procedures were attributed to the spectral variation due to differences of soil moisture and of vegetation phenology between both scenes. Methods based on classification were found less sensitive at these spectral variations.

  4. Edge detection based on gradient ghost imaging.

    PubMed

    Liu, Xue-Feng; Yao, Xu-Ri; Lan, Ruo-Ming; Wang, Chao; Zhai, Guang-Jie

    2015-12-28

    We present an experimental demonstration of edge detection based on ghost imaging (GI) in the gradient domain. Through modification of a random light field, gradient GI (GGI) can directly give the edge of an object without needing the original image. As edges of real objects are usually sparser than the original objects, the signal-to-noise ratio (SNR) of the edge detection result will be dramatically enhanced, especially for large-area, high-transmittance objects. In this study, we experimentally perform one- and two-dimensional edge detection with a double-slit based on GI and GGI. The use of GGI improves the SNR significantly in both cases. Gray-scale objects are also studied by the use of simulation. The special advantages of GI will make the edge detection based on GGI be valuable in real applications. PMID:26832041

  5. Context sensitivity in the detection of changes in facial emotion.

    PubMed

    Yamashita, Yuichi; Fujimura, Tomomi; Katahira, Kentaro; Honda, Manabu; Okada, Masato; Okanoya, Kazuo

    2016-01-01

    In social contexts, reading subtle changes in others' facial expressions is a crucial communication skill. To measure this ability, we developed an expression-change detection task, wherein a series of pictures of changes in an individual's facial expressions within contextual scenes were presented. The results demonstrated that the detection of subtle changes was highly sensitive to contextual stimuli. That is, participants identified the direction of facial-expression changes more accurately and more quickly when they were 'appropriate'-consistent with the valence of the contextual stimulus change-than when they were 'inappropriate'. Moreover, individual differences in sensitivity to contextual stimuli were correlated with scores on the Toronto Alexithymia Scale, a commonly used measure of alexithymia tendencies. These results suggest that the current behavioural task might facilitate investigations of the role of context in human social cognition. PMID:27291099

  6. Neural dynamics of change detection in crowded acoustic scenes.

    PubMed

    Sohoglu, Ediz; Chait, Maria

    2016-02-01

    Two key questions concerning change detection in crowded acoustic environments are the extent to which cortical processing is specialized for different forms of acoustic change and when in the time-course of cortical processing neural activity becomes predictive of behavioral outcomes. Here, we address these issues by using magnetoencephalography (MEG) to probe the cortical dynamics of change detection in ongoing acoustic scenes containing as many as ten concurrent sources. Each source was formed of a sequence of tone pips with a unique carrier frequency and temporal modulation pattern, designed to mimic the spectrotemporal structure of natural sounds. Our results show that listeners are more accurate and quicker to detect the appearance (than disappearance) of an auditory source in the ongoing scene. Underpinning this behavioral asymmetry are change-evoked responses differing not only in magnitude and latency, but also in their spatial patterns. We find that even the earliest (~50 ms) cortical response to change is predictive of behavioral outcomes (detection times), consistent with the hypothesized role of local neural transients in supporting change detection. PMID:26631816

  7. Neural dynamics of change detection in crowded acoustic scenes

    PubMed Central

    Sohoglu, Ediz; Chait, Maria

    2016-01-01

    Two key questions concerning change detection in crowded acoustic environments are the extent to which cortical processing is specialized for different forms of acoustic change and when in the time-course of cortical processing neural activity becomes predictive of behavioral outcomes. Here, we address these issues by using magnetoencephalography (MEG) to probe the cortical dynamics of change detection in ongoing acoustic scenes containing as many as ten concurrent sources. Each source was formed of a sequence of tone pips with a unique carrier frequency and temporal modulation pattern, designed to mimic the spectrotemporal structure of natural sounds. Our results show that listeners are more accurate and quicker to detect the appearance (than disappearance) of an auditory source in the ongoing scene. Underpinning this behavioral asymmetry are change-evoked responses differing not only in magnitude and latency, but also in their spatial patterns. We find that even the earliest (~ 50 ms) cortical response to change is predictive of behavioral outcomes (detection times), consistent with the hypothesized role of local neural transients in supporting change detection. PMID:26631816

  8. Daytime Water Detection Based on Sky Reflections

    NASA Technical Reports Server (NTRS)

    Rankin, Arturo L.; Matthies, Larry H.; Bellutta, Paolo

    2011-01-01

    Robust water detection is a critical perception requirement for unmanned ground vehicle (UGV) autonomous navigation. This is particularly true in wide-open areas where water can collect in naturally occurring terrain depressions during periods of heavy precipitation and form large water bodies. One of the properties of water useful for detecting it is that its surface acts as a horizontal mirror at large incidence angles. Water bodies can be indirectly detected by detecting reflections of the sky below the horizon in color imagery. The Jet Propulsion Laboratory (JPL) has implemented a water detector based on sky reflections that geometrically locates the pixel in the sky that is reflecting on a candidate water pixel on the ground and predicts if the ground pixel is water based on color similarity and local terrain features. This software detects water bodies in wide-open areas on cross-country terrain at mid- to far-range using imagery acquired from a forward-looking stereo pair of color cameras mounted on a terrestrial UGV. In three test sequences approaching a pond under a clear, overcast, and cloudy sky, the true positive detection rate was 100% when the UGV was beyond 7 meters of the water's leading edge and the largest false positive detection rate was 0.58%. The sky reflection based water detector has been integrated on an experimental unmanned vehicle and field tested at Ft. Indiantown Gap, PA, USA.

  9. Identifying localized changes in large systems: Change-point detection for biomolecular simulations

    PubMed Central

    Fan, Zhou; Dror, Ron O.; Mildorf, Thomas J.; Piana, Stefano; Shaw, David E.

    2015-01-01

    Research on change-point detection, the classical problem of detecting abrupt changes in sequential data, has focused predominantly on datasets with a single observable. A growing number of time series datasets, however, involve many observables, often with the property that a given change typically affects only a few of the observables. We introduce a general statistical method that, given many noisy observables, detects points in time at which various subsets of the observables exhibit simultaneous changes in data distribution and explicitly identifies those subsets. Our work is motivated by the problem of identifying the nature and timing of biologically interesting conformational changes that occur during atomic-level simulations of biomolecules such as proteins. This problem has proved challenging both because each such conformational change might involve only a small region of the molecule and because these changes are often subtle relative to the ever-present background of faster structural fluctuations. We show that our method is effective in detecting biologically interesting conformational changes in molecular dynamics simulations of both folded and unfolded proteins, even in cases where these changes are difficult to detect using alternative techniques. This method may also facilitate the detection of change points in other types of sequential data involving large numbers of observables—a problem likely to become increasingly important as such data continue to proliferate in a variety of application domains. PMID:26025225

  10. Electrophysiological correlates of auditory change detection and change deafness in complex auditory scenes.

    PubMed

    Puschmann, Sebastian; Sandmann, Pascale; Ahrens, Janina; Thorne, Jeremy; Weerda, Riklef; Klump, Georg; Debener, Stefan; Thiel, Christiane M

    2013-07-15

    Change deafness describes the failure to perceive even intense changes within complex auditory input, if the listener does not attend to the changing sound. Remarkably, previous psychophysical data provide evidence that this effect occurs independently of successful stimulus encoding, indicating that undetected changes are processed to some extent in auditory cortex. Here we investigated cortical representations of detected and undetected auditory changes using electroencephalographic (EEG) recordings and a change deafness paradigm. We applied a one-shot change detection task, in which participants listened successively to three complex auditory scenes, each of them consisting of six simultaneously presented auditory streams. Listeners had to decide whether all scenes were identical or whether the pitch of one stream was changed between the last two presentations. Our data show significantly increased middle-latency Nb responses for both detected and undetected changes as compared to no-change trials. In contrast, only successfully detected changes were associated with a later mismatch response in auditory cortex, followed by increased N2, P3a and P3b responses, originating from hierarchically higher non-sensory brain regions. These results strengthen the view that undetected changes are successfully encoded at sensory level in auditory cortex, but fail to trigger later change-related cortical responses that lead to conscious perception of change. PMID:23466938

  11. Region Duplication Forgery Detection Technique Based on SURF and HAC

    PubMed Central

    Mishra, Parul; Sharma, Sanjeev; Patel, Ravindra

    2013-01-01

    Region duplication forgery detection is a special type of forgery detection approach and widely used research topic under digital image forensics. In copy move forgery, a specific area is copied and then pasted into any other region of the image. Due to the availability of sophisticated image processing tools, it becomes very hard to detect forgery with naked eyes. From the forged region of an image no visual clues are often detected. For making the tampering more robust, various transformations like scaling, rotation, illumination changes, JPEG compression, noise addition, gamma correction, and blurring are applied. So there is a need for a method which performs efficiently in the presence of all such attacks. This paper presents a detection method based on speeded up robust features (SURF) and hierarchical agglomerative clustering (HAC). SURF detects the keypoints and their corresponding features. From these sets of keypoints, grouping is performed on the matched keypoints by HAC that shows copied and pasted regions. PMID:24311972

  12. ENZYME-BASED DETECTION OF CHLORINATED HYDROCARBONS

    EPA Science Inventory

    Recent advances in immobilized enzyme-based analytical methods, e.g., the cholinesterase-based water monitor 'CAM' (cholinesterase antagonsist monitor), have proved useful in the detection of organophosphate and carbamate pesticides. This work has now been extended to the detecti...

  13. Detecting changes in maps of gamma spectra with Kolmogorov-Smirnov tests

    NASA Astrophysics Data System (ADS)

    Reinhart, Alex; Ventura, Valérie; Athey, Alex

    2015-12-01

    Various security, regulatory, and consequence management agencies are interested in continuously monitoring wide areas for unexpected changes in radioactivity. Existing detection systems are designed to search for radioactive sources but are not suited to repeat mapping and change detection. Using a set of daily spectral observations collected at the Pickle Research Campus, we improved on the prior Spectral Comparison Ratio Anomaly Mapping (SCRAM) algorithm and developed a new method based on two-sample Kolmogorov-Smirnov tests to detect sudden spectral changes. We also designed simulations and visualizations of statistical power to compare methods and guide deployment scenarios.

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

    NASA Astrophysics Data System (ADS)

    Nielsen, Allan A.; Canty, Morton J.

    2010-10-01

    The iteratively re-weighted multivariate alteration detection (IR-MAD) algorithm may be used both for unsuper- vised change detection in multi- and hyperspectral remote sensing imagery as well as for automatic radiometric normalization of multi- or hypervariate multitemporal image sequences. 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 analysis (PCA), kernel MAF and kernel MNF analyses handle nonlinearities by implicitly transforming data into high (even innite) dimensional feature space via the kernel function and then performing a linear analysis in that space. In image analysis the Gram matrix is often prohibitively large (its size is the number of pixels in the image squared). In this case we may sub-sample the image and carry out the kernel eigenvalue analysis on a set of training data samples only. To obtain a transformed version of the entire image we then project all pixels, which we call the test data, mapped nonlinearly onto the primal eigenvectors. IDL (Interactive Data Language) implementations of IR-MAD, automatic radiometric normalization and kernel PCA/MAF/MNF transformations have been written

  15. Change-Point Detection of Natural Frequency Using Dynamic Model Selection and Clustering

    NASA Astrophysics Data System (ADS)

    Matsuoka, Kodai; Kaito, Kiyoyuki; Sogabe, Masamichi

    In order to apply structural monitoring into practice, it is indispensable to develop a method for change-point detection of bridge vibrational properties. In this study, the authors have developed a methodology using sequential prediction, dynamic model selection, and clustering, with the purpose of evaluating vibrational properties and its change timings. In order to examine the validity, the time series that had the change in frequency was calculated, and proposal method was applied. As a results, it was found that the natural frequency is detected. As for change timings, these were evaluated as change intervals. On the other hand, when the proposed method was applied to the acceleration response of a bridge when a train passes, it was found that bridge frequency can be extracted stably, and it is difficult to detect change timings when the change is small. Based on these results, factors were studied, and some solutions to the problems were proposed.

  16. Recent advances in biosensor based endotoxin detection.

    PubMed

    Das, A P; Kumar, P S; Swain, S

    2014-01-15

    Endotoxins also referred to as pyrogens are chemically lipopolysaccharides habitually found in food, environment and clinical products of bacterial origin and are unavoidable ubiquitous microbiological contaminants. Pernicious issues of its contamination result in high mortality and severe morbidities. Standard traditional techniques are slow and cumbersome, highlighting the pressing need for evoking agile endotoxin detection system. The early and prompt detection of endotoxin assumes prime importance in health care, pharmacological and biomedical sectors. The unparalleled recognition abilities of LAL biosensors perched with remarkable sensitivity, high stability and reproducibility have bestowed it with persistent reliability and their possible fabrication for commercial applicability. This review paper entails an overview of various trends in current techniques available and other possible alternatives in biosensor based endotoxin detection together with its classification, epidemiological aspects, thrust areas demanding endotoxin control, commercially available detection sensors and a revolutionary unprecedented approach narrating the influence of omics for endotoxin detection. PMID:23934306

  17. Driver fatigue detection system based on DSP

    NASA Astrophysics Data System (ADS)

    Wang, Qian; Yu, Fu liang; Song, Lixin

    2012-01-01

    To detect driver fatigue states effectively and in real time, a driver fatigue detection system was built, which take ICETEK-DM6347 module as system core, near-infrared LED as light source, and CCD camera as picture gathering device. An improved PER-NORFACE detection method combined several simple and efficient image processing algorithms was proposed, which based on principle of PERCLOS method and take the human face location as the main detection target. To ensure the ability of real-time processing, the algorithms on the DM6437 DaVinci processor were optimized. Experiments show that the system could complete the driver fatigue states detection accurately and in real time.

  18. Context sensitivity in the detection of changes in facial emotion

    PubMed Central

    Yamashita, Yuichi; Fujimura, Tomomi; Katahira, Kentaro; Honda, Manabu; Okada, Masato; Okanoya, Kazuo

    2016-01-01

    In social contexts, reading subtle changes in others’ facial expressions is a crucial communication skill. To measure this ability, we developed an expression-change detection task, wherein a series of pictures of changes in an individual’s facial expressions within contextual scenes were presented. The results demonstrated that the detection of subtle changes was highly sensitive to contextual stimuli. That is, participants identified the direction of facial-expression changes more accurately and more quickly when they were ‘appropriate’—consistent with the valence of the contextual stimulus change—than when they were ‘inappropriate’. Moreover, individual differences in sensitivity to contextual stimuli were correlated with scores on the Toronto Alexithymia Scale, a commonly used measure of alexithymia tendencies. These results suggest that the current behavioural task might facilitate investigations of the role of context in human social cognition. PMID:27291099

  19. Immunity-Based Aircraft Fault Detection System

    NASA Technical Reports Server (NTRS)

    Dasgupta, D.; KrishnaKumar, K.; Wong, D.; Berry, M.

    2004-01-01

    In the study reported in this paper, we have developed and applied an Artificial Immune System (AIS) algorithm for aircraft fault detection, as an extension to a previous work on intelligent flight control (IFC). Though the prior studies had established the benefits of IFC, one area of weakness that needed to be strengthened was the control dead band induced by commanding a failed surface. Since the IFC approach uses fault accommodation with no detection, the dead band, although it reduces over time due to learning, is present and causes degradation in handling qualities. If the failure can be identified, this dead band can be further A ed to ensure rapid fault accommodation and better handling qualities. The paper describes the application of an immunity-based approach that can detect a broad spectrum of known and unforeseen failures. The approach incorporates the knowledge of the normal operational behavior of the aircraft from sensory data, and probabilistically generates a set of pattern detectors that can detect any abnormalities (including faults) in the behavior pattern indicating unsafe in-flight operation. We developed a tool called MILD (Multi-level Immune Learning Detection) based on a real-valued negative selection algorithm that can generate a small number of specialized detectors (as signatures of known failure conditions) and a larger set of generalized detectors for unknown (or possible) fault conditions. Once the fault is detected and identified, an adaptive control system would use this detection information to stabilize the aircraft by utilizing available resources (control surfaces). We experimented with data sets collected under normal and various simulated failure conditions using a piloted motion-base simulation facility. The reported results are from a collection of test cases that reflect the performance of the proposed immunity-based fault detection algorithm.

  20. Laser-based detection of chemical contraband

    NASA Astrophysics Data System (ADS)

    Clemmer, Robert G.; Kelly, James F.; Martin, Steven W.; Mong, Gary M.; Sharpe, Steven W.

    1997-02-01

    The goal of our work is tow fold; 1) develop a portable and rapid laser based air sampler for detection of specific chemical contraband and 2) compile a spectral data base in both the near- and mid-IR of sufficiently high quality to be useful for gas phase spectroscopic identification of chemical contraband. During the synthesis or 'cooking' of many illicit chemical substances, relatively high concentrations of volatile solvents, chemical precursors and byproducts are unavoidably released to the atmosphere. In some instances, the final product may have sufficient vapor pressure to be detectable in the surrounding air. The detection of a single high-value effluent or the simultaneous detection of two or more low-value effluents can be used as reliable indicators of a nearby clandestine cooking operation. The designation of high- versus low-value effluent reflects both the commercial availability and legitimate usage of a specific chemical. This paper will describe PNNL's progress and efforts towards the development of a portable laser based air sampling system for the detection of clandestine manufacturing of methamphetamine. Although our current efforts ar focused on methamphetamine, we see no fundamental limitations on detection of other forms of chemical contraband manufacturing. This also includes the synthesis of certain classes of chemical weapons that have recently been deployed by terrorist groups.

  1. Folded Compact Range Development and Coherent Change Detection Measurement Project

    SciTech Connect

    Sorensen, K.W.

    1995-03-01

    A novel, folded compact range configuration has been developed at the Sandia National Laboratories compact range antenna and radar cross section measurement facility, operated by the Radar/Antenna Department 2343, as a means of performing indoor, environmentally-controlled, far-field simulations of synthetic aperture radar (SAR) coherent change detection (CCD) measurements. This report describes the development of the folded compact range configuration, as well as the initial set of coherent change detection measurements made with the system. These measurements have been highly successful, and have demonstrated the viability of the folded compact range concept in simulating SAR CCD measurements. It is felt that follow-on measurements have the potential of contributing significantly to the body of knowledge available to the scientific community involved in CCD image generation and processing, and that this tool will be a significant aid in the research and development of change detection methodologies.

  2. Fiber-Optic Based Compact Gas Leak Detection System

    NASA Technical Reports Server (NTRS)

    deGroot, Wim A.

    1995-01-01

    A propellant leak detection system based on Raman scattering principles is introduced. The proposed system is flexible and versatile as the result of the use of optical fibers. It is shown that multiple species can be monitored simultaneously. In this paper oxygen, nitrogen, carbon monoxide, and hydrogen are detected and monitored. The current detection sensitivity for both hydrogen and carbon monoxide is 1% partial pressure at ambient conditions. The sensitivity for oxygen and nitrogen is 0.5% partial pressure. The response time to changes in species concentration is three minutes. This system can be used to monitor multiple species at several locations.

  3. Detecting regional patterns of changing CO2 flux in Alaska.

    PubMed

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

    2016-07-12

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

  4. Detecting regional patterns of changing CO2 flux in Alaska

    NASA Astrophysics Data System (ADS)

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

    2016-07-01

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

  5. Optical and SAR data integration for automatic change pattern detection

    NASA Astrophysics Data System (ADS)

    Mishra, B.; Susaki, J.

    2014-09-01

    Automatic change pattern mapping in urban and sub-urban area is important but challenging due to the diversity of urban land use pattern. With multi-sensor imagery, it is possible to generate multidimensional unique information of Earth surface features that allow developing a relationship between a response of each feature to synthetic aperture radar (SAR) and optical sensors to track the change automatically. Thus, a SAR and optical data integration framework for change detection and a relationship for automatic change pattern detection were developed. It was carried out in three steps: (i) Computation of indicators from SAR and optical images, namely: normalized difference ratio (NDR) from multi-temporal SAR images and the normalized difference vegetation index difference (NDVI) from multi-temporal optical images, (ii) computing the change magnitude image from NDR and ΔNDVI and delineating the change area and (iii) the development of an empirical relationship, for automatic change pattern detection. The experiment was carried out in an outskirts part of Ho Chi Minh City, one of the fastest growing cities in the world. The empirical relationship between the response of surface feature to optical and SAR imagery has successfully delineated six changed classes in a very complex urban sprawl area that was otherwise impossible with multi-spectral imagery. The improvement of the change detection results by making use of the unique information on both sensors, optical and SAR, is also noticeable with a visual inspection and the kappa index was increased by 0.13 (0.75 to 0.88) in comparison to only optical images.

  6. Integrated data processing of remotely sensed and vector data for building change detection

    NASA Astrophysics Data System (ADS)

    Sofina, N.; Ehlers, M.; Michel, U.

    2012-10-01

    In recent years natural disasters have had an increasing impact leading to tremendous economic and human losses. Remote sensing technologies are being used more often for rapid detection and visualization of changes in the affected areas, providing essential information for damage assessment, planning and coordination of recovery activities. This study presents a GIS-based approach for the detection of damaged buildings. The methodology is based on the integrated analysis of vector data containing information about the original urban layout and remotely sensed images obtained after a catastrophic event. For the classification of building integrity a new `Detected Part of Contour' (DPC) feature was developed. The DPC feature defines a part of the building contour that can be detected in the related remotely sensed image. It reaches maximum value (100%) if the investigated building contour is intact. Next, several features based on the analysis of textural information of the remotely sensed image are considered. Finally, a binary classification of building conditions concludes the change detection analysis. The proposed method was applied to the 2010 earthquake in Qinghai (China). The results indicate that a GIS-based analysis can markedly improve the accuracy of change detection analysis. The proposed methodology has been developed solely within the Open Source Software environment (GRASS GIS, Python, Orange). The employment of Open Source Software provides the way for an innovative, flexible and costeffective implementation of change detection operations.

  7. Real-time change detection for countering improvised explosive devices

    NASA Astrophysics Data System (ADS)

    van de Wouw, Dennis W. J. M.; van Rens, Kris; van Lint, Hugo; Jaspers, Egbert G. T.; de With, Peter H. N.

    2014-03-01

    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 bypassed. While driving, images of the scenes are acquired by the camera and stored with their GPS positions. At the same time, the best matching reference image (from a previous patrol) is retrieved and registered to the live image. Next a change mask is generated by differencing the reference and live image, followed by an adaptive thresholding technique. Post-processing steps such as Markov Random Fields, local texture comparisons and change tracking, further improve time- and space-consistency of changes and suppress noise. The resulting changes are visualized as an overlay on the live video content. The system has been extensively tested on 28 videos, containing over 10,000 manually annotated objects. The system is capable of detecting small test objects of 10 cm3 at a range of 40 meters. Although the system shows an acceptable performance in multiple cases, the performance degrades under certain circumstances for which extensions are discussed.

  8. Landsat change detection can aid in water quality monitoring

    NASA Technical Reports Server (NTRS)

    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.

  9. Using adversary text to detect adversary phase changes.

    SciTech Connect

    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.

  10. Detection of cardiac activity changes from human speech

    NASA Astrophysics Data System (ADS)

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

    2015-05-01

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

  11. Climate Change Detection and Attribution of Infrared Spectrum Measurements

    NASA Technical Reports Server (NTRS)

    Phojanamongkolkij, Nipa; Parker, Peter A.; Mlynczak, Martin G.

    2012-01-01

    Climate change occurs when the Earth's energy budget changes due to natural or possibly anthropogenic forcings. These forcings cause the climate system to adjust resulting in a new climate state that is warmer or cooler than the original. The key question is how to detect and attribute climate change. The inference of infrared spectral signatures of climate change has been discussed in the literature for nearly 30 years. Pioneering work in the 1980s noted that distinct spectral signatures would be evident in changes in the infrared radiance emitted by the Earth and its atmosphere, and that these could be observed from orbiting satellites. Since then, a number of other studies have advanced the concepts of spectral signatures of climate change. Today the concept of using spectral signatures to identify and attribute atmospheric composition change is firmly accepted and is the foundation of the Climate Absolute Radiance and Refractivity Observatory (CLARREO) satellite mission being developed at NASA. In this work, we will present an overview of the current climate change detection concept using climate model calculations as surrogates for climate change. Any future research work improving the methodology to achieve this concept will be valuable to our society.

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

    PubMed Central

    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

  13. Water Detection Based on Sky Reflections

    NASA Technical Reports Server (NTRS)

    Rankin, Arturo L.; Matthies, Larry H.

    2010-01-01

    This software has been designed to detect water bodies that are out in the open on cross-country terrain at mid- to far-range (approximately 20 100 meters), using imagery acquired from a stereo pair of color cameras mounted on a terrestrial, unmanned ground vehicle (UGV). Non-traversable water bodies, such as large puddles, ponds, and lakes, are indirectly detected by detecting reflections of the sky below the horizon in color imagery. The appearance of water bodies in color imagery largely depends on the ratio of light reflected off the water surface to the light coming out of the water body. When a water body is far away, the angle of incidence is large, and the light reflected off the water surface dominates. We have exploited this behavior to detect water bodies out in the open at mid- to far-range. When a water body is detected at far range, a UGV s path planner can begin to look for alternate routes to the goal position sooner, rather than later. As a result, detecting water hazards at far range generally reduces the time required to reach a goal position during autonomous navigation. This software implements a new water detector based on sky reflections that geometrically locates the exact pixel in the sky that is reflecting on a candidate water pixel on the ground, and predicts if the ground pixel is water based on color similarity and local terrain features

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

    PubMed

    Busch, Niko A

    2013-07-01

    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. PMID:23685191

  15. Detecting human influence in observed changes in precipitation

    NASA Astrophysics Data System (ADS)

    Polson, Debbie; Hegerl, Gabriele; Bollasina, Massimo; Wilcox, Laura; Zhang, Xuebin; Osborn, Timothy; Balan Sarojini, Beena

    2015-04-01

    Human induced changes to the precipitation could cause some of the most serious impacts of climate change, with potential consequences for water resources, health, agriculture and ecosystems. However, quantifying and understanding the drivers of changes to precipitation is challenging due to its large spatial and temporal variability, the lack of long-term observational records over much of the globe and the counteracting affects of greenhouse gases and aerosols. Nevertheless, detection and attribution studies have shown that human influence has changed both global and regional precipitation over the latter half of the 20th century. Using climates models to derive fingerprints of external forcing, we are able to show that greenhouse gas warming has driven large scale changes in precipitation. Greenhouse gas forcing is detectable in observed changes to zonal mean precipitation over land (Polson et al., 2012a). It has also been shown to have caused the intensification of the water cycle, enhancing existing patterns of the precipitation in the tropics and subtropics, over both land and ocean (Polson et al., 2012b). While at global scales, the influence of greenhouse gases is detectable in observations, separating the response of precipitation to anthropogenic aerosol forcing is more difficult. However, in some regions the influence of aerosols dominate, making it possible to detect aerosol forcing. Observed precipitation in the monsoon regions underwent substantial changes during the second half of the twentieth century, with drying from the 1950s to mid-1980s and increasing precipitation in recent decades. Climate model simulations are used to derive fingerprints of individual climate forcings (i.e., greenhouse gas, anthropogenic aerosol, and natural) and detection and attribution methods applied to determine which, if any, have driven these changes to monsoon precipitation. Even when accounting for internal variability of the climate, a clear signal of anthropogenic

  16. Performance evaluation of supervised change detection tool on DubaiSat-2 multispectral and pansharp images

    NASA Astrophysics Data System (ADS)

    Almatroushi, Hessa R.

    2014-10-01

    Supervised Change Detection Tool (SCDT) is an in-house developed tool in Emirates Institution for Advanced Science and Technology (EIAST). The developed tool is based on Algebra Change Detection algorithm and multi-class Support Vector Machine classifier and is capable of highlighting the areas of change, describing them, and discarding any falsedetections that result from shadow. Further, it can collect the analysis results, which include the change of class an area went through and the overall change percentage of each class defined, in a Microsoft Word document automatically. This paper evaluates the performance of the SCDT, which was initially developed for DubaiSat-1 multispectral images, on DubaiSat-2 multispectral and pansharp images. Moreover, it compares its performance opposed to Change Detection Analysis (i.e. Post-Classification) in ENVI.

  17. Simple road detection based on vanishing point

    NASA Astrophysics Data System (ADS)

    Ziyu, Chen; Zhen, He

    2014-05-01

    Vision-based road detection is one of the key techniques of autonomous driving, intelligent vehicles, and visual navigation. At present, methods based on vanishing point perform best with general roads. However, it is difficult for them to meet the needs of a real-time system due to high time consumption. This paper presents a fast detection method, namely simple road detection, which achieves high efficiency by employing sky segmentation and two new optimization schemes-sample convolution and fast voting. The optimizations are based on lookup tables, sample computing, and computing simplification. The interval sampling in sample convolution makes the proposed method flexible to meet various efficiency and accuracy demands by different sample-step values. Mean filter and vote orientation limitation are also proposed to help improve detection accuracy. Experiments have been conducted with a large number of road images under different environmental conditions, and the results demonstrate that our proposed method is efficient and effective in detecting both structured and unstructured roads.

  18. Detecting Changes in Terrain Using Unmanned Aerial Vehicles

    NASA Technical Reports Server (NTRS)

    Rahman, Zia-ur; Hines, Glenn D.; Logan, Michael J.

    2005-01-01

    In recent years, small unmanned aerial vehicles (UAVs) have been used for more than the thrill they bring to model airplane enthusiasts. Their flexibility and low cost have made them a viable option for low-altitude reconnaissance. In a recent effort, we acquired video data from a small UAV during several passes over the same flight path. The objective of the exercise was to determine if objects had been added to the terrain along the flight path between flight passes. Several issues accrue to this simple-sounding problem: (1) lighting variations may cause false detection of objects because of changes in shadow orientation and strength between passes; (2) variations in the flight path due to wind-speed, and heading change may cause misalignment of gross features making the task of detecting changes between the frames very difficult; and (3) changes in the aircraft orientation and altitude lead to a change in size of the features from frame-to-frame making a comparison difficult. In this paper, we discuss our efforts to perform this change detection, and the lessons that we learned from this exercise.

  19. A change detection approach to moving object detection in low fame-rate video

    NASA Astrophysics Data System (ADS)

    Porter, Reid; Harvey, Neal; Theiler, James

    2009-05-01

    Moving object detection is of significant interest in temporal image analysis since it is a first step in many object identification and tracking applications. A key component in almost all moving object detection algorithms is a pixellevel classifier, where each pixel is predicted to be either part of a moving object or part of the background. In this paper we investigate a change detection approach to the pixel-level classification problem and evaluate its impact on moving object detection. The change detection approach that we investigate was previously applied to multi- and hyper-spectral datasets, where images were typically taken several days, or months apart. In this paper, we apply the approach to lowframe rate (1-2 frames per second) video datasets.

  20. A change detection approach to moving object detection in low frame-rate video

    SciTech Connect

    Porter, Reid B; Harvey, Neal R; Theiler, James P

    2009-01-01

    Moving object detection is of significant interest in temporal image analysis since it is a first step in many object identification and tracking applications. A key component in almost all moving object detection algorithms is a pixel-level classifier, where each pixel is predicted to be either part of a moving object or part of the background. In this paper we investigate a change detection approach to the pixel-level classification problem and evaluate its impact on moving object detection. The change detection approach that we investigate was previously applied to multi-and hyper-spectral datasets, where images were typically taken several days, or months apart. In this paper, we apply the approach to low-frame rate (1-2 frames per second) video datasets.

  1. Graph-based pigment network detection in skin images

    NASA Astrophysics Data System (ADS)

    Sadeghi, M.; Razmara, M.; Ester, M.; Lee, T. K.; Atkins, M. S.

    2010-03-01

    Detecting pigmented network is a crucial step for melanoma diagnosis. In this paper, we present a novel graphbased pigment network detection method that can find and visualize round structures belonging to the pigment network. After finding sharp changes of the luminance image by an edge detection function, the resulting binary image is converted to a graph, and then all cyclic sub-graphs are detected. Theses cycles represent meshes that belong to the pigment network. Then, we create a new graph of the cyclic structures based on their distance. According to the density ratio of the new graph of the pigment network, the image is classified as "Absent" or "Present". Being Present means that a pigment network is detected in the skin lesion. Using this approach, we achieved an accuracy of 92.6% on five hundred unseen images.

  2. Targeted cell detection based on microchannel gating.

    PubMed

    Javanmard, Mehdi; Talasaz, Amirali H; Nemat-Gorgani, Mohsen; Pease, Fabian; Ronaghi, Mostafa; Davis, Ronald W

    2007-01-01

    Currently, microbiological techniques such as culture enrichment and various plating techniques are used for detection of pathogens. These expensive and time consuming methods can take several days. Described below is the design, fabrication, and testing of a rapid and inexpensive sensor, involving the use of microelectrodes in a microchannel, which can be used to detect single bacterial cells electrically (label-free format) in real time. As a proof of principle, we have successfully demonstrated real-time detection of target yeast cells by measuring instantaneous changes in ionic impedance. We have also demonstrated the selectivity of our sensors in responding to target cells while remaining irresponsive to nontarget cells. Using this technique, it can be possible to multiplex an array of these sensors onto a chip and probe a complex mixture for various types of bacterial cells. PMID:19693402

  3. Tornado Detection Based on Seismic Signal.

    NASA Astrophysics Data System (ADS)

    Tatom, Frank B.; Knupp, Kevin R.; Vitton, Stanley J.

    1995-02-01

    At the present time the only generally accepted method for detecting when a tornado is on the ground is human observation. Based on theoretical considerations combined with eyewitness testimony, there is strong reason to believe that a tornado in contact with the ground transfers a significant amount of energy into the ground. The amount of energy transferred depends upon the intensity of the tornado and the characteristics of the surface. Some portion of this energy takes the form of seismic waves, both body and surface waves. Surface waves (Rayleigh and possibly Love) represent the most likely type of seismic signal to be detected. Based on the existence of such a signal, a seismic tornado detector appears conceptually possible. The major concerns for designing such a detector are range of detection and discrimination between the tornadic signal and other types of surface waves generated by ground transportation equipment, high winds, or other nontornadic sources.

  4. Climate change and the detection of trends in annual runoff

    USGS Publications Warehouse

    McCabe, G.J., Jr.; Wolock, D.M.

    1997-01-01

    This study examines the statistical likelihood of detecting a trend in annual runoff given an assumed change in mean annual runoff, the underlying year-to-year variability in runoff, and serial correlation of annual runoff. Means, standard deviations, and lag-1 serial correlations of annual runoff were computed for 585 stream gages in the conterminous United States, and these statistics were used to compute the probability of detecting a prescribed trend in annual runoff. Assuming a linear 20% change in mean annual runoff over a 100 yr period and a significance level of 95%, the average probability of detecting a significant trend was 28% among the 585 stream gages. The largest probability of detecting a trend was in the northwestern U.S., the Great Lakes region, the northeastern U.S., the Appalachian Mountains, and parts of the northern Rocky Mountains. The smallest probability of trend detection was in the central and southwestern U.S., and in Florida. Low probabilities of trend detection were associated with low ratios of mean annual runoff to the standard deviation of annual runoff and with high lag-1 serial correlation in the data.

  5. Robust Detection of Examinees with Aberrant Answer Changes

    ERIC Educational Resources Information Center

    Belov, Dmitry I.

    2015-01-01

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

  6. A three-component method for timely detection of land cover changes using polarimetric SAR images

    NASA Astrophysics Data System (ADS)

    Qi, Zhixin; Yeh, Anthony Gar-On; Li, Xia; Zhang, Xiaohu

    2015-09-01

    This study proposes a new three-component method for timely detection of land cover changes using polarimetric synthetic aperture radar (PolSAR) images. The three components are object-oriented image analysis (OOIA), change vector analysis (CVA), and post-classification comparison (PCC). First, two PolSAR images acquired over the same area at different dates are segmented hierarchically to delineate land parcels (image objects). Then, parcel-based CVA is performed with the coherency matrices of the PolSAR data to detect changed parcels. Finally, PCC based on a parcel-based classification algorithm integrating polarimetric decomposition, decision tree algorithms, and support vector machines is used to determine the type of change for the changed parcels. Compared with conventional PCC based on the widely used Wishart supervised classification, the three-component method achieves much higher accuracy for land cover change detection with PolSAR images. The contribution of each component is evaluated by excluding it from the method. The integration of OOIA in the method greatly reduces the false alarms caused by speckle noise in PolSAR images as well as improves the accuracy of PolSAR image classification. CVA contributes to the method by significantly reducing the effect of the classification errors on the change detection. The use of PCC in the method not only identifies different types of land cover change but also reduces the false alarms introduced by the change in the environment. The three-component method is validated in land development detection, which is important to many developing countries that are confronting a growing problem of unauthorized construction land expansion. The results show that the three-component method is effective in detecting land developments with PolSAR images.

  7. Photogrammetric processing of hexagon stereo data for change detection studies

    NASA Astrophysics Data System (ADS)

    Padmanabha, E. Anantha; Shashivardhan Reddy, P.; Narender, B.; Muralikrishnan, S.; Dadhwal, V. K.

    2014-11-01

    Hexagon satellite data acquired as a part of USA Corona program has been declassified and is accessible to general public. This image data was acquired in high resolution much before the launch of civilian satellites. However the non availability of interior and exterior orientation parameters is the main bottle neck in photogrammetric processing of this data. In the present study, an attempt was made to orient and adjust Hexagon stereo pair through Rigorous Sensor Model (RSM) and Rational Function Models (RFM). The study area is part of Western Ghats in India. For rigorous sensor modelling an arbitrary camera file is generated based on the information available in the literature and few assumptions. A terrain dependent RFM was generated for the stereo data using Cartosat-1 reference data. The model accuracy achieved for both RSM and RFM was better than one pixel. DEM and orthoimage were generated with a spacing of 50 m and Ground Sampling Distance (GSD) of 6 m to carry out the change detection with a special emphasis on water bodies with reference to recent Cartosat-1 data. About 72 new water bodies covering an area of 2300 hectares (23 sq. km) were identified in Cartosat-1 orthoimage that were not present in Hexagon data. The image data from various Corona programs like Hexagon provide a rich source of information for temporal studies. However photogrammetric processing of the data is a bit tedious due to lack of information about internal sensor geometry.

  8. Water Detection Based on Object Reflections

    NASA Technical Reports Server (NTRS)

    Rankin, Arturo L.; Matthies, Larry H.

    2012-01-01

    Water bodies are challenging terrain hazards for terrestrial unmanned ground vehicles (UGVs) for several reasons. Traversing through deep water bodies could cause costly damage to the electronics of UGVs. Additionally, a UGV that is either broken down due to water damage or becomes stuck in a water body during an autonomous operation will require rescue, potentially drawing critical resources away from the primary operation and increasing the operation cost. Thus, robust water detection is a critical perception requirement for UGV autonomous navigation. One of the properties useful for detecting still water bodies is that their surface acts as a horizontal mirror at high incidence angles. Still water bodies in wide-open areas can be detected by geometrically locating the exact pixels in the sky that are reflecting on candidate water pixels on the ground, predicting if ground pixels are water based on color similarity to the sky and local terrain features. But in cluttered areas where reflections of objects in the background dominate the appearance of the surface of still water bodies, detection based on sky reflections is of marginal value. Specifically, this software attempts to solve the problem of detecting still water bodies on cross-country terrain in cluttered areas at low cost.

  9. Community detection based on network communicability

    NASA Astrophysics Data System (ADS)

    Estrada, Ernesto

    2011-03-01

    We propose a new method for detecting communities based on the concept of communicability between nodes in a complex network. This method, designated as N-ComBa K-means, uses a normalized version of the adjacency matrix to build the communicability matrix and then applies K-means clustering to find the communities in a graph. We analyze how this method performs for some pathological cases found in the analysis of the detection limit of communities and propose some possible solutions on the basis of the analysis of the ratio of local to global densities in graphs. We use four different quality criteria for detecting the best clustering and compare the new approach with the Girvan-Newman algorithm for the analysis of two "classical" networks: karate club and bottlenose dolphins. Finally, we analyze the more challenging case of homogeneous networks with community structure, for which the Girvan-Newman completely fails in detecting any clustering. The N-ComBa K-means approach performs very well in these situations and we applied it to detect the community structure in an international trade network of miscellaneous manufactures of metal having these characteristics. Some final remarks about the general philosophy of community detection are also discussed.

  10. Satellite Observations for Detecting and Tracking Changes in Atmospheric Composition

    NASA Technical Reports Server (NTRS)

    Neil, Doreen O.; Kondragunbta, Shobha; Osterman, Gregory; Pickering, Kenneth; Pinder, Robert W.; Prados, Ana I.; Szykman, James

    2009-01-01

    The satellite observations provide constraints on detailed atmospheric modeling, including emissions inventories, indications of transport, harmonized data over vast areas suitable for trends analysis, and a link between spatial scales ranging from local to global, and temporal scales from diurnal to interannual. 1 The National Oceanic and Atmospheric Administration's (NOAA) long-term commitments help provide these observations in cooperation with international meteorological organizations. NASA s long-term commitments will advance scientifically important observations as part of its Earth Science Program, and will assist the transition of the science measurements to applied analyses through the Applied Science Program. Both NASA and NOAA have begun to provide near realtime data and tools to visualize and analyze satellite data,2 while maintaining data quality, validation, and standards. Consequently, decision-makers can expect satellite data services to support air quality decision making now and in the future. The international scientific community's Integrated Global Atmosphere Chemistry Observation System Report3 outlined a plan for ground-based, airborne and satellite measurements and models to integrate the observations into a four-dimensional representation of the atmosphere (space and time) to support assessment and policy information needs. This plan is being carried out under the Global Earth Observation System of Systems (GEOSS). Demonstrations of such an integrated capability4 provide new understanding of the changing atmosphere and link policy decisions to benefits for society. In this article, we highlight the use of satellite data to constrain biomass burning emissions, to assess oxides of nitrogen (NO(x)) emission reductions, and to contribute to state implementation plans, as examples of the use of satellite observations for detecting and tracking changes in atmospheric composition.

  11. Silicon chips detect intracellular pressure changes in living cells

    NASA Astrophysics Data System (ADS)

    Gómez-Martínez, Rodrigo; Hernández-Pinto, Alberto M.; Duch, Marta; Vázquez, Patricia; Zinoviev, Kirill; de La Rosa, Enrique J.; Esteve, Jaume; Suárez, Teresa; Plaza, José A.

    2013-07-01

    The ability to measure pressure changes inside different components of a living cell is important, because it offers an alternative way to study fundamental processes that involve cell deformation. Most current techniques such as pipette aspiration, optical interferometry or external pressure probes use either indirect measurement methods or approaches that can damage the cell membrane. Here we show that a silicon chip small enough to be internalized into a living cell can be used to detect pressure changes inside the cell. The chip, which consists of two membranes separated by a vacuum gap to form a Fabry-Pérot resonator, detects pressure changes that can be quantified from the intensity of the reflected light. Using this chip, we show that extracellular hydrostatic pressure is transmitted into HeLa cells and that these cells can endure hypo-osmotic stress without significantly increasing their intracellular hydrostatic pressure.

  12. Detecting Abrupt Changes in a Piecewise Locally Stationary Time Series

    PubMed Central

    Last, Michael; Shumway, Robert

    2007-01-01

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

  13. Single and Multiple Change Point Detection in Spike Trains: Comparison of Different CUSUM Methods.

    PubMed

    Koepcke, Lena; Ashida, Go; Kretzberg, Jutta

    2016-01-01

    In a natural environment, sensory systems are faced with ever-changing stimuli that can occur, disappear or change their properties at any time. For the animal to react adequately the sensory systems must be able to detect changes in external stimuli based on its neuronal responses. Since the nervous system has no prior knowledge of the stimulus timing, changes in stimulus need to be inferred from the changes in neuronal activity, in particular increase or decrease of the spike rate, its variability, and shifted response latencies. From a mathematical point of view, this problem can be rephrased as detecting changes of statistical properties in a time series. In neuroscience, the CUSUM (cumulative sum) method has been applied to recorded neuronal responses for detecting a single stimulus change. Here, we investigate the applicability of the CUSUM approach for detecting single as well as multiple stimulus changes that induce increases or decreases in neuronal activity. Like the nervous system, our algorithm relies exclusively on previous neuronal population activities, without using knowledge about the timing or number of external stimulus changes. We apply our change point detection methods to experimental data obtained by multi-electrode recordings from turtle retinal ganglion cells, which react to changes in light stimulation with a range of typical neuronal activity patterns. We systematically examine how variations of mathematical assumptions (Poisson, Gaussian, and Gamma distributions) used for the algorithms may affect the detection of an unknown number of stimulus changes in our data and compare these CUSUM methods with the standard Rate Change method. Our results suggest which versions of the CUSUM algorithm could be useful for different types of specific data sets. PMID:27445714

  14. Single and Multiple Change Point Detection in Spike Trains: Comparison of Different CUSUM Methods

    PubMed Central

    Koepcke, Lena; Ashida, Go; Kretzberg, Jutta

    2016-01-01

    In a natural environment, sensory systems are faced with ever-changing stimuli that can occur, disappear or change their properties at any time. For the animal to react adequately the sensory systems must be able to detect changes in external stimuli based on its neuronal responses. Since the nervous system has no prior knowledge of the stimulus timing, changes in stimulus need to be inferred from the changes in neuronal activity, in particular increase or decrease of the spike rate, its variability, and shifted response latencies. From a mathematical point of view, this problem can be rephrased as detecting changes of statistical properties in a time series. In neuroscience, the CUSUM (cumulative sum) method has been applied to recorded neuronal responses for detecting a single stimulus change. Here, we investigate the applicability of the CUSUM approach for detecting single as well as multiple stimulus changes that induce increases or decreases in neuronal activity. Like the nervous system, our algorithm relies exclusively on previous neuronal population activities, without using knowledge about the timing or number of external stimulus changes. We apply our change point detection methods to experimental data obtained by multi-electrode recordings from turtle retinal ganglion cells, which react to changes in light stimulation with a range of typical neuronal activity patterns. We systematically examine how variations of mathematical assumptions (Poisson, Gaussian, and Gamma distributions) used for the algorithms may affect the detection of an unknown number of stimulus changes in our data and compare these CUSUM methods with the standard Rate Change method. Our results suggest which versions of the CUSUM algorithm could be useful for different types of specific data sets. PMID:27445714

  15. Evaluation of the capability of the Lombard test in detecting abrupt changes in variance

    NASA Astrophysics Data System (ADS)

    Nayak, Munir A.; Villarini, Gabriele

    2016-03-01

    Hydrologic time series are often characterized by temporal changes that give rise to non-stationarity. When the distribution describing the data changes over time, it is important to detect these changes so that correct inferences can be drawn from the data. The Lombard test, a non-parametric rank-based test to detect change points in the moments of a time series, has been recently used in the hydrologic literature to detect change points in the mean and variance. Little is known, however, about the performance of this test in detecting changes in variance, despite the potentially large impacts that these changes (shifts) could have when dealing with extremes. Here we address this issue in a Monte Carlo simulation framework. We consider a number of different situations that can manifest themselves in hydrologic time series, including the dependence of the results on the magnitude of the shift, significance level, sample size and location of the change point within the series. Analyses are performed considering abrupt changes in variance occurring with and without shifts in the mean. The results show that the power of the test in detecting change points in variance is small when the changes are small. It is large when the change point occurs close to the middle of the time series, and it increases nonlinearly with increasing sample size. Moreover, the power of the test is greatly reduced by the presence of change points in mean. We propose removing the change in the mean before testing for change points in variance. Simulation results demonstrate that this strategy effectively increases the power of the test. Finally, the Lombard test is applied to annual peak discharge records from 3686 U.S. Geological Survey stream-gaging stations across the conterminous United States, and the results are discussed in light of the insights from the simulations' results.

  16. Detection and attribution of changes in flood probability

    NASA Astrophysics Data System (ADS)

    Merz, Bruno; Delgado, Jose; Hundecha, Yeshewa; Zimmer, Janek

    2010-05-01

    The frequency, magnitude and type of extreme hydrological events are expected to change with climate change. However, other influences, such as construction of reservoirs, river training or land cover change, additionally affect the flood behaviour. Based on flood time series of more than 150 catchments in Germany, we analyse spatial patterns of changes in frequency, magnitude and probabilities of floods across Germany. In particular, we study the changes in the variability (or scale parameter) versus the changes in the mean (or location parameter), and the sensitivity of flood probability to changes in these parameters. In order to differentiate between climate-induced change and land cover change, we investigate if changes at inter-annual, decadal and multidecadal time scales are regionally stable, and if these changes can be linked to climatic variables. For selected catchments, an attempt is made to relate changes in flood behaviour to human-induced interventions in the catchments and to climatic change. Regionally and seasonally coherent results point to the influence of climate on changing flood probabilities in Germany in the last decades.

  17. Differential Search Algorithm Based Edge Detection

    NASA Astrophysics Data System (ADS)

    Gunen, M. A.; Civicioglu, P.; Beşdok, E.

    2016-06-01

    In this paper, a new method has been presented for the extraction of edge information by using Differential Search Optimization Algorithm. The proposed method is based on using a new heuristic image thresholding method for edge detection. The success of the proposed method has been examined on fusion of two remote sensed images. The applicability of the proposed method on edge detection and image fusion problems have been analysed in detail and the empirical results exposed that the proposed method is useful for solving the mentioned problems.

  18. Vision-based threat detection in dynamic environments.

    SciTech Connect

    Carlson, Jeffrey J.

    2007-08-01

    This report addresses the development of automated video-screening technology to assist security forces in protecting our homeland against terrorist threats. A prevailing threat is the covert placement of bombs inside crowded public facilities. Although video-surveillance systems are increasingly common, current systems cannot detect the placement of bombs. It is also unlikely that security personnel could detect a bomb or its placement by observing video from surveillance cameras. The problems lie in the large number of cameras required to monitor large areas, the limited number of security personnel employed to protect these areas, and the intense diligence required to effectively screen live video from even a single camera. Different from existing video-detection systems designed to operate in nearly static environments, we are developing technology to detect changes in the background of dynamic environments: environments where motion and human activities are persistent over long periods. Our goal is to quickly detect background changes, even if the background is visible to the camera less than 5 percent of the time and possibly never free from foreground activity. Our approach employs statistical scene models based on mixture densities. We hypothesized that the background component of the mixture has a small variance compared to foreground components. Experiments demonstrate this hypothesis is true under a wide variety of operating conditions. A major focus involved the development of robust background estimation techniques that exploit this property. We desire estimation algorithms that can rapidly produce accurate background estimates and detection algorithms that can reliably detect background changes with minimal nuisance alarms. Another goal is to recognize unusual activities or foreground conditions that could signal an attack (e.g., large numbers of running people, people falling to the floor, etc.). Detection of background changes and/or unusual

  19. Change detection is impaired in children with dyslexia.

    PubMed

    Rutkowski, Jacqueline S; Crewther, David P; Crewther, Sheila G

    2003-01-01

    The severe deficits in rapid automatized naming demonstrated by children with developmental dyslexia has usually been interpreted in terms of a deficit in speed of access to the lexicon rather than as a possible deficit in speed of visual object recognition. Yet fluent reading requires rapid visual recognition and semantic interpretation of new letters and words appearing in successive fixations of the eyes. Thus we wondered whether change detection performance was related to reading ability. We investigated whether children with developmental dyslexia (DD) were less able to detect change in a simple display--gap--display paradigm than normal reading (NR) children of the same age and children with impaired reading and mentation (LD). In a first experimental phase, the DDs required a longer initial exposure of four letter items in order to detect change of a single letter at a level of 71% correct, compared with NRs performing at the same level. Thus the deficit in reading in DD is associated with a deficit in early processes associated with visual recognition. In a second experimental phase (using the individual target display exposures measured in the first phase), cues appeared during the 250 ms gap for a period of either 0 (no cue), 50 or 200 ms immediately prior to the presentation of the second (comparison) display. Children of all groups showed dependence on the presence of the cue to help make a judgement of change (versus no change), with the NRs least affected. When change was detected in the presence of a cue, the NRs were better able to identify the new letter than either of the other groups. However, only about 50% of the correct detections were accompanied by a correct identification. Despite published reports of a mini-neglect for left visual field in dyslexic adults, none of our groups showed such an effect. However, a significant upper visual field (UpVF) advantage in change detection performance was found across groups, which we interpret in terms

  20. Resonant energy transfer based biosensor for detection of multivalent proteins.

    SciTech Connect

    Song, X.; Swanson, Basil I.

    2001-01-01

    We have developed a new fluorescence-based biosensor for sensitive detection of species involved in a multivslent interaction. The biosensor system utilizes specific interactions between proteins and cell surface receptors, which trigger a receptor aggregation process. Distance-dependent fluorescence self-quenching and resonant energy transfer mechanisms were coupled with a multivalent interaction to probe the receptor aggregation process, providing a sensitive and specific signal transduction method for such a binding event. The fluorescence change induced by the aggregation process can be monitored by different instrument platforms, e.g. fluorimetry and flow cytometry. In this article, a sensitive detection of pentavalent cholera toxin which recognizes ganglioside GM1 has been demonstrated through the resonant energy transfer scheme, which can achieve a double color change simultaneously. A detection sensitivity as high as 10 pM has been achieved within a few minutes (c.a. 5 minutes). The simultaneous double color change (an increase of acceptor fluorescence and a decrease of donor fluorescence intensity) of two similar fluorescent probes provides particularly high detection reliability owing to the fact that they act as each other's internal reference. Any external perturbation such as environmental temperature change causes no significant change in signal generation. Besides the application for biological sensing, the method also provides a useful tool for investigation of kinetics and thermodynamics of a multivalent interaction. Keywords: Biosensor, Fluorescence resonant energy transfer, Multivalent interaction, Cholera Toxin, Ganglioside GM1, Signal Transduction

  1. Change point detection in risk adjusted control charts.

    PubMed

    Assareh, Hassan; Smith, Ian; Mengersen, Kerrie

    2015-12-01

    Precise identification of the time when a change in a clinical process has occurred enables experts to identify a potential special cause more effectively. In this article, we develop change point estimation methods for a clinical dichotomous process in the presence of case mix. We apply Bayesian hierarchical models to formulate the change point where there exists a step change in the odds ratio and logit of risk of a Bernoulli process. Markov Chain Monte Carlo is used to obtain posterior distributions of the change point parameters including location and magnitude of changes and also corresponding probabilistic intervals and inferences. The performance of the Bayesian estimator is investigated through simulations and the result shows that precise estimates can be obtained when they are used in conjunction with the risk-adjusted CUSUM and EWMA control charts. In comparison with alternative EWMA and CUSUM estimators, more accurate and precise estimates are obtained by the Bayesian estimator. These superiorities enhance when probability quantification, flexibility and generaliability of the Bayesian change point detection model are also considered. The Deviance Information Criterion, as a model selection criterion in the Bayesian context, is applied to find the best change point model for a given dataset where there is no prior knowledge about the change type in the process. PMID:22025415

  2. Regional principal color based saliency detection.

    PubMed

    Lou, Jing; Ren, Mingwu; Wang, Huan

    2014-01-01

    Saliency detection is widely used in many visual applications like image segmentation, object recognition and classification. In this paper, we will introduce a new method to detect salient objects in natural images. The approach is based on a regional principal color contrast modal, which incorporates low-level and medium-level visual cues. The method allows a simple computation of color features and two categories of spatial relationships to a saliency map, achieving higher F-measure rates. At the same time, we present an interpolation approach to evaluate resulting curves, and analyze parameters selection. Our method enables the effective computation of arbitrary resolution images. Experimental results on a saliency database show that our approach produces high quality saliency maps and performs favorably against ten saliency detection algorithms. PMID:25379960

  3. A Web Based Cardiovascular Disease Detection System.

    PubMed

    Alshraideh, Hussam; Otoom, Mwaffaq; Al-Araida, Aseel; Bawaneh, Haneen; Bravo, José

    2015-10-01

    Cardiovascular Disease (CVD) is one of the most catastrophic and life threatening health issue nowadays. Early detection of CVD is an important solution to reduce its devastating effects on health. In this paper, an efficient CVD detection algorithm is identified. The algorithm uses patient demographic data as inputs, along with several ECG signal features extracted automatically through signal processing techniques. Cross-validation results show a 98.29 % accuracy for the decision tree classification algorithm. The algorithm has been integrated into a web based system that can be used at anytime by patients to check their heart health status. At one end of the system is the ECG sensor attached to the patient's body, while at the other end is the detection algorithm. Communication between the two ends is done through an Android application. PMID:26293754

  4. Statistical method for detecting structural change in the growth process.

    PubMed

    Ninomiya, Yoshiyuki; Yoshimoto, Atsushi

    2008-03-01

    Due to competition among individual trees and other exogenous factors that change the growth environment, each tree grows following its own growth trend with some structural changes in growth over time. In the present article, a new method is proposed to detect a structural change in the growth process. We formulate the method as a simple statistical test for signal detection without constructing any specific model for the structural change. To evaluate the p-value of the test, the tube method is developed because the regular distribution theory is insufficient. Using two sets of tree diameter growth data sampled from planted forest stands of Cryptomeria japonica in Japan, we conduct an analysis of identifying the effect of thinning on the growth process as a structural change. Our results demonstrate that the proposed method is useful to identify the structural change caused by thinning. We also provide the properties of the method in terms of the size and power of the test. PMID:17608782

  5. Ionizing particle detection based on phononic crystals

    SciTech Connect

    Aly, Arafa H. E-mail: arafa.hussien@science.bsu.edu.eg; Mehaney, Ahmed; Eissa, Mostafa F.

    2015-08-14

    Most conventional radiation detectors are based on electronic or photon collections. In this work, we introduce a new and novel type of ionizing particle detector based on phonon collection. Helium ion radiation treats tumors with better precision. There are nine known isotopes of helium, but only helium-3 and helium-4 are stable. Helium-4 is formed in fusion reactor technology and in enormous quantities during Big Bang nucleo-synthesis. In this study, we introduce a technique for helium-4 ion detection (sensing) based on the innovative properties of the new composite materials known as phononic crystals (PnCs). PnCs can provide an easy and cheap technique for ion detection compared with conventional methods. PnC structures commonly consist of a periodic array of two or more materials with different elastic properties. The two materials are polymethyl-methacrylate and polyethylene polymers. The calculations showed that the energies lost to target phonons are maximized at 1 keV helium-4 ion energy. There is a correlation between the total phonon energies and the transmittance of PnC structures. The maximum transmission for phonons due to the passage of helium-4 ions was found in the case of making polyethylene as a first layer in the PnC structure. Therefore, the concept of ion detection based on PnC structure is achievable.

  6. Ionizing particle detection based on phononic crystals

    NASA Astrophysics Data System (ADS)

    Aly, Arafa H.; Mehaney, Ahmed; Eissa, Mostafa F.

    2015-08-01

    Most conventional radiation detectors are based on electronic or photon collections. In this work, we introduce a new and novel type of ionizing particle detector based on phonon collection. Helium ion radiation treats tumors with better precision. There are nine known isotopes of helium, but only helium-3 and helium-4 are stable. Helium-4 is formed in fusion reactor technology and in enormous quantities during Big Bang nucleo-synthesis. In this study, we introduce a technique for helium-4 ion detection (sensing) based on the innovative properties of the new composite materials known as phononic crystals (PnCs). PnCs can provide an easy and cheap technique for ion detection compared with conventional methods. PnC structures commonly consist of a periodic array of two or more materials with different elastic properties. The two materials are polymethyl-methacrylate and polyethylene polymers. The calculations showed that the energies lost to target phonons are maximized at 1 keV helium-4 ion energy. There is a correlation between the total phonon energies and the transmittance of PnC structures. The maximum transmission for phonons due to the passage of helium-4 ions was found in the case of making polyethylene as a first layer in the PnC structure. Therefore, the concept of ion detection based on PnC structure is achievable.

  7. Shearlet-based detection of flame fronts

    NASA Astrophysics Data System (ADS)

    Reisenhofer, Rafael; Kiefer, Johannes; King, Emily J.

    2016-03-01

    Identifying and characterizing flame fronts is the most common task in the computer-assisted analysis of data obtained from imaging techniques such as planar laser-induced fluorescence (PLIF), laser Rayleigh scattering (LRS), or particle imaging velocimetry (PIV). We present Complex Shearlet-Based Ridge and Edge Measure (CoShREM), a novel edge and ridge (line) detection algorithm based on complex-valued wavelet-like analyzing functions—so-called complex shearlets—displaying several traits useful for the extraction of flame fronts. In addition to providing a unified approach to the detection of edges and ridges, our method inherently yields estimates of local tangent orientations and local curvatures. To examine the applicability for high-frequency recordings of combustion processes, the algorithm is applied to mock images distorted with varying degrees of noise and real-world PLIF images of both OH and CH radicals. Furthermore, we compare the performance of the newly proposed complex shearlet-based measure to well-established edge and ridge detection techniques such as the Canny edge detector, another shearlet-based edge detector, and the phase congruency measure.

  8. Change-point detection in time-series data by relative density-ratio estimation.

    PubMed

    Liu, Song; Yamada, Makoto; Collier, Nigel; Sugiyama, Masashi

    2013-07-01

    The objective of change-point detection is to discover abrupt property changes lying behind time-series data. In this paper, we present a novel statistical change-point detection algorithm based on non-parametric divergence estimation between time-series samples from two retrospective segments. Our method uses the relative Pearson divergence as a divergence measure, and it is accurately and efficiently estimated by a method of direct density-ratio estimation. Through experiments on artificial and real-world datasets including human-activity sensing, speech, and Twitter messages, we demonstrate the usefulness of the proposed method. PMID:23500502

  9. SERS-based detection of biomolecules

    NASA Astrophysics Data System (ADS)

    Cialla, Dana; Pollok, Sibyll; Steinbrücker, Carolin; Weber, Karina; Popp, Jürgen

    2014-12-01

    In order to detect biomolecules, different approaches using for instance biological, spectroscopic or imaging techniques are established. Due to the broad variety of these methods, this review is focused on surface enhanced Raman spectroscopy (SERS) as an analytical tool in biomolecule detection. Here, the molecular specificity of Raman spectroscopy is combined with metallic nanoparticles as sensor platform, which enhances the signal intensity by several orders of magnitude. Within this article, the characterization of diverse biomolecules by means of SERS is explained and moreover current application fields are presented. The SERS intensity and as a consequence thereof the reliable detection of the biomolecule of interest is effected by distance, orientation and affinity of the molecule towards the metal surface. Furthermore, the great capability of the SERS technique for cutting-edge applications like pathogen detection and cancer diagnosis is highlighted. We wish to motivate by this comprehensive and critical summary researchers from various scientific background to create their own ideas and schemes for a SERS-based detection and analysis of biomolecules.

  10. Detection of Rooftop Cooling Unit Faults Based on Electrical Measurements

    SciTech Connect

    Armstrong, Peter R.; Laughman, C R.; Leeb, S B.; Norford, L K.

    2006-01-31

    Non-intrusive load monitoring (NILM) is accomplished by sampling voltage and current at high rates and reducing the resulting start transients or harmonic contents to concise ''signatures''. Changes in these signatures can be used to detect, and in many cases directly diagnose, equipment and component faults associated with roof-top cooling units. Use of the NILM for fault detection and diagnosis (FDD) is important because (1) it complements other FDD schemes that are based on thermo-fluid sensors and analyses and (2) it is minimally intrusive (one measuring point in the relatively protected confines of the control panel) and therefore inherently reliable. This paper describes changes in the power signatures of fans and compressors that were found, experimentally and theoretically, to be useful for fault detection.

  11. Wavelet based detection of manatee vocalizations

    NASA Astrophysics Data System (ADS)

    Gur, Berke M.; Niezrecki, Christopher

    2005-04-01

    The West Indian manatee (Trichechus manatus latirostris) has become endangered partly because of watercraft collisions in Florida's coastal waterways. Several boater warning systems, based upon manatee vocalizations, have been proposed to reduce the number of collisions. Three detection methods based on the Fourier transform (threshold, harmonic content and autocorrelation methods) were previously suggested and tested. In the last decade, the wavelet transform has emerged as an alternative to the Fourier transform and has been successfully applied in various fields of science and engineering including the acoustic detection of dolphin vocalizations. As of yet, no prior research has been conducted in analyzing manatee vocalizations using the wavelet transform. Within this study, the wavelet transform is used as an alternative to the Fourier transform in detecting manatee vocalizations. The wavelet coefficients are analyzed and tested against a specified criterion to determine the existence of a manatee call. The performance of the method presented is tested on the same data previously used in the prior studies, and the results are compared. Preliminary results indicate that using the wavelet transform as a signal processing technique to detect manatee vocalizations shows great promise.

  12. Detecting Land Cover Change by Trend and Seasonality of Remote Sensing Time Series

    NASA Astrophysics Data System (ADS)

    Oliveira, J. C.; Epiphanio, J. N.; Mello, M. P.

    2013-05-01

    Natural resource managers demand knowledge of information on the spatiotemporal dynamics of land use and land cover change, and detection and characteristics change over time is an initial step for the understanding of the mechanism of change. The propose of this research is the use the approach BFAST (Breaks For Additive Seasonal and Trend) for detects trend and seasonal changes within Normalized Difference Vegetation Index (NDVI) time series. BFAST integrates the decomposition of time series into trend, seasonal, and noise components with methods for detecting change within time series without the need to select a reference period, set a threshold, or define a change trajectory. BFAST iteratively estimates the time and number of changes, and characterizes change by its magnitude and direction. The general model is of the form Yt = Tt + St + et (t= 1,2,3,…, n) where Yt is the observed data at time t, Tt is the trend component, St is the seasonal component, and et is the remainder component. In this study was used MODIS NDVI time series datasets (MOD13Q1) over 11 years (2000 - 2010) on an intensive agricultural area in Mato Grosso - Brazil. At first it was applied a filter for noise reduction (4253H twice) over spectral curve of each MODIS pixel, and subsequently each time series was decomposed into seasonal, trend, and remainder components by BFAST. Were detected one abrupt change from a single pixel of forest and two abrupt changes on trend component to a pixel of the agricultural area. Figure 1 shows the number of phonological change with base in seasonal component for study area. This paper demonstrated the ability of the BFAST to detect long-term phenological change by analyzing time series while accounting for abrupt and gradual changes. The algorithm iteratively estimates the dates and number of changes occurring within seasonal and trend components, and characterizes changes by extracting the magnitude and direction of change. Changes occurring in the

  13. Background updating and shadow detection based on spatial, color, and texture information of detected objects

    NASA Astrophysics Data System (ADS)

    Hamad, Ahmed Mahmoud; Tsumura, Norimichi

    2012-05-01

    Background model updating is a vital process for any background subtraction technique. This paper presents an updating mechanism that can be applied efficiently to any background subtraction technique. This updating mechanism exploits the color and spatial features to characterize each detected object. Spatial and color features are used to classify each detected object as a moving background object, a ghost, or a real moving object. The starting position of each detected object is the cue for updating background images. In addition, this paper presents a hybrid scheme to detect and remove cast shadows based on texture and color features. The robustness of the proposed method and its effectiveness in overcoming challenging problems such as gradual and sudden illumination changes, ghost appearance, non-stationary background objects, the stability of moving objects most of the time, and cast shadows are verified quantitatively and qualitatively.

  14. An EEG-Based Fatigue Detection and Mitigation System.

    PubMed

    Huang, Kuan-Chih; Huang, Teng-Yi; Chuang, Chun-Hsiang; King, Jung-Tai; Wang, Yu-Kai; Lin, Chin-Teng; Jung, Tzyy-Ping

    2016-06-01

    Research has indicated that fatigue is a critical factor in cognitive lapses because it negatively affects an individual's internal state, which is then manifested physiologically. This study explores neurophysiological changes, measured by electroencephalogram (EEG), due to fatigue. This study further demonstrates the feasibility of an online closed-loop EEG-based fatigue detection and mitigation system that detects physiological change and can thereby prevent fatigue-related cognitive lapses. More importantly, this work compares the efficacy of fatigue detection and mitigation between the EEG-based and a nonEEG-based random method. Twelve healthy subjects participated in a sustained-attention driving experiment. Each participant's EEG signal was monitored continuously and a warning was delivered in real-time to participants once the EEG signature of fatigue was detected. Study results indicate suppression of the alpha- and theta-power of an occipital component and improved behavioral performance following a warning signal; these findings are in line with those in previous studies. However, study results also showed reduced warning efficacy (i.e. increased response times (RTs) to lane deviations) accompanied by increased alpha-power due to the fluctuation of warnings over time. Furthermore, a comparison of EEG-based and nonEEG-based random approaches clearly demonstrated the necessity of adaptive fatigue-mitigation systems, based on a subject's cognitive level, to deliver warnings. Analytical results clearly demonstrate and validate the efficacy of this online closed-loop EEG-based fatigue detection and mitigation mechanism to identify cognitive lapses that may lead to catastrophic incidents in countless operational environments. PMID:27121994

  15. The failure to detect tactile change: a tactile analogue of visual change blindness.

    PubMed

    Gallace, Alberto; Tan, Hong Z; Spence, Charles

    2006-04-01

    A large body of empirical research now shows that people are surprisingly poor at detecting significant changes in visually presented scenes. This phenomenon is known as change blindness in vision. A similar phenomenon occurs in audition, but to date no such effect has been documented in touch. In the present study, we explored the ability of people to detect changes introduced between two consecutively presented vibrotactile patterns presented over the body surface. The patterns consisted of two or three vibrotactile stimuli presented for 200 msec. The position of one of the vibrotactile stimuli composing the display was repeatedly changed (alternating between two different positions) on 50% of the trials, but the same pattern was presented repeatedly on the remaining trials. Three conditions were investigated: No interval between the patterns, an empty interval between the patterns, and a masked interval between the patterns. Change detection was near perfect in the no-interval block. Performance deteriorated somewhat in the empty-interval block, but by far the worst change detection performance occurred in the masked-interval block. These results demonstrate that "change blindness" can also affect tactile perception. PMID:16892998

  16. When visual transients impair tactile change detection: a novel case of crossmodal change blindness?

    PubMed

    Gallace, Alberto; Auvray, Malika; Tan, Hong Z; Spence, Charles

    2006-05-01

    The inability of people to detect changes between consecutively presented visual displays, when separated by a blank screen or distractor, is known as "change blindness". This phenomenon has recently been reported to occur within the auditory and tactile modalities as well. To date, however, only distractors presented within the same sensory modality as the change have been demonstrated to produce change blindness. In the present experiment, we studied whether tactile change blindness might also be elicited by the presentation of a visual mask. Participants made same versus different judgments regarding two successively presented displays composed of two to three vibrotactile stimuli. While change detection performance was near-perfect when the two displays were presented one directly after the other, participants failed to detect many of the changes between the tactile displays when they were separated by an empty temporal interval. Critically, performance deteriorated still further when the presentation of a local (i.e., a mudsplash) or global visual transient coincided with the onset of the second tactile pattern. Analysis of the results using signal detection theory revealed that this crossmodal effect reflected a genuine perceptual impairment. PMID:16480821

  17. Raman LIDAR Detection of Cloud Base

    NASA Technical Reports Server (NTRS)

    Demoz, Belay; Starr, David; Whiteman, David; Evans, Keith; Hlavka, Dennis; Peravali, Ravindra

    1999-01-01

    Advantages introduced by Raman lidar systems for cloud base determination during precipitating periods are explored using two case studies of light rain and virga conditions. A combination of the Raman lidar derived profiles of water vapor mixing ratio and aerosol scattering ratio, together with the Raman scattered signals from liquid drops, can minimize or even eliminate some of the problems associated with cloud boundary detection using elastic backscatter lidars.

  18. General SIC measurement-based entanglement detection

    NASA Astrophysics Data System (ADS)

    Chen, Bin; Li, Tao; Fei, Shao-Ming

    2015-06-01

    We study the quantum separability problem by using general symmetric informationally complete measurements and present separability criteria for both -dimensional bipartite and multipartite systems. The criterion for bipartite quantum states is effective in detecting several well-known classes of quantum states. For isotropic states, it becomes both necessary and sufficient. Furthermore, our criteria can be experimentally implemented, and the criterion for two-qudit states requires less local measurements than the one based on mutually unbiased measurements.

  19. A structural framework for anomalous change detection and characterization

    SciTech Connect

    Prasad, Lakshman; Theiler, James P

    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.

  20. Theory of optimal weighting of data to detect climatic change

    NASA Technical Reports Server (NTRS)

    Bell, T. L.

    1986-01-01

    A search for climatic change predicted by climate models can easily yield unconvincing results because of 'climatic noise,' the inherent, unpredictable variability of time-average atmospheric data. A weighted average of data that maximizes the probability of detecting predicted climatic change is presented. To obtain the optimal weights, an estimate of the covariance matrix of the data from a prior data set is needed. This introduces additional sampling error into the method. This is presently taken into account. A form of the weighted average is found whose probability distribution is independent of the true (but unknown) covariance statistics of the data and of the climate model prediction.

  1. Visual analysis for live LIDAR battlefield change detection

    NASA Astrophysics Data System (ADS)

    Butkiewicz, Thomas; Chang, Remco; Wartell, Zachary; Ribarsky, William

    2008-04-01

    We present the framework for a battlefield change detection system that allows military analysts to coordinate and utilize live collection of airborne LIDAR range data in a highly interactive visual interface. The system consists of three major components: The adaptive and self-maintaining model of the battlefield selectively incorporates the minority of new data it deems significant, while discarding the redundant majority. The interactive interface presents the analyst with only the minute portion of the data the system deems relevant, provides tools to facilitate the decision making process, and adjusts its behavior to reflect the analyst's objectives. Finally, the cycle is completed by the generation of a goal map for the LIDAR collection hardware that instructs as to which areas should be sampled next in order to best advance the change detection task. All together, the system empowers analysts with the ability to make sense of a deluge of measurements by extracting the salient features and continually refining its definitions of relevancy.

  2. Biotoxin detection using cell-based sensors.

    PubMed

    Banerjee, Pratik; Kintzios, Spyridon; Prabhakarpandian, Balabhaskar

    2013-12-01

    Cell-based biosensors (CBBs) utilize the principles of cell-based assays (CBAs) by employing living cells for detection of different analytes from environment, food, clinical, or other sources. For toxin detection, CBBs are emerging as unique alternatives to other analytical methods. The main advantage of using CBBs for probing biotoxins and toxic agents is that CBBs respond to the toxic exposures in the manner related to actual physiologic responses of the vulnerable subjects. The results obtained from CBBs are based on the toxin-cell interactions, and therefore, reveal functional information (such as mode of action, toxic potency, bioavailability, target tissue or organ, etc.) about the toxin. CBBs incorporate both prokaryotic (bacteria) and eukaryotic (yeast, invertebrate and vertebrate) cells. To create CBB devices, living cells are directly integrated onto the biosensor platform. The sensors report the cellular responses upon exposures to toxins and the resulting cellular signals are transduced by secondary transducers generating optical or electrical signals outputs followed by appropriate read-outs. Examples of the layout and operation of cellular biosensors for detection of selected biotoxins are summarized. PMID:24335754

  3. Biotoxin Detection Using Cell-Based Sensors

    PubMed Central

    Banerjee, Pratik; Kintzios, Spyridon; Prabhakarpandian, Balabhaskar

    2013-01-01

    Cell-based biosensors (CBBs) utilize the principles of cell-based assays (CBAs) by employing living cells for detection of different analytes from environment, food, clinical, or other sources. For toxin detection, CBBs are emerging as unique alternatives to other analytical methods. The main advantage of using CBBs for probing biotoxins and toxic agents is that CBBs respond to the toxic exposures in the manner related to actual physiologic responses of the vulnerable subjects. The results obtained from CBBs are based on the toxin-cell interactions, and therefore, reveal functional information (such as mode of action, toxic potency, bioavailability, target tissue or organ, etc.) about the toxin. CBBs incorporate both prokaryotic (bacteria) and eukaryotic (yeast, invertebrate and vertebrate) cells. To create CBB devices, living cells are directly integrated onto the biosensor platform. The sensors report the cellular responses upon exposures to toxins and the resulting cellular signals are transduced by secondary transducers generating optical or electrical signals outputs followed by appropriate read-outs. Examples of the layout and operation of cellular biosensors for detection of selected biotoxins are summarized. PMID:24335754

  4. Trend change detection in vegetation greenness time series: Contrasting methodologies, data sets and global vegetation models

    NASA Astrophysics Data System (ADS)

    Forkel, Matthias; Carvalhais, Nuno; Verbesselt, Jan; Mahecha, Miguel; Neigh, Christopher; Thonicke, Kirsten; Reichstein, Markus

    2014-05-01

    Newly developed satellite datasets and time series analysis methods allow the quantification of changes in vegetation greenness. However, the estimation of trends and trend changes depend often on the applied time series analysis method and the used satellite dataset. Thus, the environmental plausibility of the estimated trends and trend breakpoints is often questionable. We compared four trend and trend change detection methods to assess their performance. We applied the methods to NDVI and FAPAR time series from global satellite datasets and from global vegetation models. We generated surrogate time series with known trends and breakpoints and applied the methods to re-detect the known trends and trend changes. Our results demonstrate that the performance of methods decrease with increasing inter-annual variability of the time series. An overestimation of breakpoints in NDVI time series can result in wrong or even opposite trend estimates. Trend slope estimates based on annual aggregated time series or based on a seasonal-trend model show better performances than methods that remove the seasonal cycle of the time series. The application of the trend change detection methods to real time series allows assessing the multi-method ensemble of trend estimates. Nevertheless, the interpretation of the environmental plausibility of these trend estimates is challenging. For example, some methods suggest a weakening of greening trends in the Tundra after the early 2000s while other methods suggest an ongoing greening. Comparison with vegetation model simulations suggest that this weakening is not an artefact of the satellite dataset or of the applied trend change detection method but might be caused by real changes in environmental conditions. Our results demonstrate the need for a critical appraisal of trend change detection methods. All methods require a careful assessment of the environmental plausibility of detected trend changes in vegetation greenness time series.

  5. Impedance-based damage detection for civil infrastructures

    NASA Astrophysics Data System (ADS)

    Park, Seunghee; Roh, YongRae; Yi, JinHak; Yun, Chung-Bang; Kwak, Hyo-Gyoung; Lee, SangHan

    2004-07-01

    The objective of this study is to investigate the feasibility of an impedance-based damage detection technique using piezoelectric (PZT) transducers for civil infrastructures such as steel bridges. The basic concept of the technique is to monitor the changes in the electrical impedance to detect structural damages. Those changes in the electrical impedance are due to the electro-mechanical coupling property of piezoelectric materials. The smart PZT transducers which act as both actuators and sensors in a self-analyzing manner are emerging to be effective in non-parametric health monitoring of structural systems. This health monitoring technique can be easily adapted to existing structures, since only a small number of PZT patches are needed for continuous monitoring of their structural integrity. This impedance-based method operates at high frequencies (above 100 kHz), which enables it to detect incipient-type damage. It is not interfered by normal operating conditions, vibrations of the host structure, and changes in the host external body. The results of the experimental study on three kinds of structural members indicate that cracks or loosened bolts/nuts near the PZT sensors may be effectively detected by monitoring the shifts of the resonant frequencies of the impedance functions.

  6. Neural correlates of auditory sensory memory and automatic change detection.

    PubMed

    Sabri, Merav; Kareken, David A; Dzemidzic, Mario; Lowe, Mark J; Melara, Robert D

    2004-01-01

    An auditory event-related potential component, the mismatch negativity (MMN), reflects automatic change detection and its prerequisite, sensory memory. This study examined the neural correlates of automatic change detection using BOLD fMRI and two rates of presentation previously shown to induce either a large or no MMN. A boxcar block design was employed in two functional scans, each performed twice. A block consisting of 1000-Hz standards (S) alternated with one consisting of 1000-Hz standards and 2000-Hz infrequent deviants (S + D). Presentation rate was either 150 or 2400 ms. Fourteen participants were instructed to ignore all auditory stimulation and concentrate on a film (no audio) by reading subtitles. Data analysis used SPM99 and random effects approach. Cluster statistics (P < 0.05, corrected) were employed at a height threshold of P < 0.001. At the short ISI, there was a significant BOLD response in the right superior temporal gyrus (STG), the left insula, and the left STG (including parts of primary auditory cortex). There were no suprathreshold clusters at the long rate, with S + D blocks inducing no greater activity than S blocks. These results support the hypothesis that the automatic detection of auditory change occurs in the STG bilaterally and relies on the maintenance of sensory memory traces. PMID:14741643

  7. Urban land-cover change detection through sub-pixel imperviousness mapping using remotely sensed data

    USGS Publications Warehouse

    Yang, Limin; Xian, George Z.; Klaver, Jacqueline M.; Deal, Brian

    2003-01-01

    We developed a Sub-pixel Imperviousness Change Detection (SICD) approach to detect urban land-cover changes using Landsat and high-resolution imagery. The sub-pixel percent imperviousness was mapped for two dates (09 March 1993 and 11 March 2001) over western Georgia using a regression tree algorithm. The accuracy of the predicted imperviousness was reasonable based on a comparison using independent reference data. The average absolute error between predicted and reference data was 16.4 percent for 1993 and 15.3 percent for 2001. The correlation coefficient (r) was 0.73 for 1993 and 0.78 for 2001, respectively. Areas with a significant increase (greater than 20 percent) in impervious surface from 1993 to 2001 were mostly related to known land-cover/land-use changes that occurred in this area, suggesting that the spatial change of an impervious surface is a useful indicator for identifying spatial extent, intensity, and, potentially, type of urban land-cover/land-use changes. Compared to other pixel-based change-detection methods (band differencing, rationing, change vector, post-classification), information on changes in sub-pixel percent imperviousness allow users to quantify and interpret urban land-cover/land-use changes based on their own definition. Such information is considered complementary to products generated using other change-detection methods. In addition, the procedure for mapping imperviousness is objective and repeatable, hence, can be used for monitoring urban land-cover/land-use change over a large geographic area. Potential applications and limitations of the products developed through this study in urban environmental studies are also discussed.

  8. A Weld Defects Detection System Based on a Spectrometer

    PubMed Central

    Bebiano, Daniel; Alfaro, Sadek C. A.

    2009-01-01

    Improved product quality and production methods, and decreased production costs are important objectives of industries. Welding processes are part of this goal. There are many studies about monitoring and controlling welding process. This work presents a non-intrusive on-line monitoriment system and some algorithms capable of detecting GTAW weld defects. Some experiments were made to simulate weld defects by disturbing the electric arc. The data comes from a spectrometer which captures perturbations on the electric arc by the radiation emission of chosen lines. Algorithms based on change detection methods are used to indicate the presence and localization of those defects. PMID:22574049

  9. Vibration-based damage detection algorithm for WTT structures

    NASA Astrophysics Data System (ADS)

    Nguyen, Tuan-Cuong; Kim, Tae-Hwan; Choi, Sang-Hoon; Ryu, Joo-Young; Kim, Jeong-Tae

    2016-04-01

    In this paper, the integrity of a wind turbine tower (WTT) structure is nondestructively estimated using its vibration responses. Firstly, a damage detection algorithm using changes in modal characteristics to predict damage locations and severities in structures is outlined. Secondly, a finite element (FE) model based on a real WTT structure is established by using a commercial software, Midas FEA. Thirdly, forced vibration tests are performed on the FE model of the WTT structure under various damage scenarios. The changes in modal parameters such as natural frequencies and mode shapes are examined for damage monitoring in the structure. Finally, the feasibility of the vibration-based damage detection method is numerically verified by predicting locations and severities of the damage in the FE model of the WTT structure.

  10. Advances in neutron based bulk explosive detection

    NASA Astrophysics Data System (ADS)

    Gozani, Tsahi; Strellis, Dan

    2007-08-01

    Neutron based explosive inspection systems can detect a wide variety of national security threats. The inspection is founded on the detection of characteristic gamma rays emitted as the result of neutron interactions with materials. Generally these are gamma rays resulting from thermal neutron capture and inelastic scattering reactions in most materials and fast and thermal neutron fission in fissile (e.g.235U and 239Pu) and fertile (e.g.238U) materials. Cars or trucks laden with explosives, drugs, chemical agents and hazardous materials can be detected. Cargo material classification via its main elements and nuclear materials detection can also be accomplished with such neutron based platforms, when appropriate neutron sources, gamma ray spectroscopy, neutron detectors and suitable decision algorithms are employed. Neutron based techniques can be used in a variety of scenarios and operational modes. They can be used as stand alones for complete scan of objects such as vehicles, or for spot-checks to clear (or validate) alarms indicated by another inspection system such as X-ray radiography. The technologies developed over the last two decades are now being implemented with good results. Further advances have been made over the last few years that increase the sensitivity, applicability and robustness of these systems. The advances range from the synchronous inspection of two sides of vehicles, increasing throughput and sensitivity and reducing imparted dose to the inspected object and its occupants (if any), to taking advantage of the neutron kinetic behavior of cargo to remove systematic errors, reducing background effects and improving fast neutron signals.

  11. Detection of base-pair mismatches in DNA using graphene-based nanopore device

    NASA Astrophysics Data System (ADS)

    Kundu, Sourav; Karmakar, S. N.

    2016-04-01

    We present a unique way to detect base-pair mismatches in DNA, leading to a different epigenetic disorder by the method of nanopore sequencing. Based on a tight-binding formulation of a graphene-based nanopore device, using the Green’s function approach we study the changes in the electronic transport properties of the device as we translocate a double-stranded DNA through the nanopore embedded in a zigzag graphene nanoribbon. In the present work we are not only successful in detecting the usual AT and GC pairs but also a set of possible mismatches in the complementary base pairing.

  12. Daytime Water Detection Based on Color Variation

    NASA Technical Reports Server (NTRS)

    Rankin, Arturo L.; Matthies, Larry H.

    2010-01-01

    Robust water detection is a critical perception requirement for unmanned ground vehicle (UGV) autonomous navigation. This is particularly true in wide open areas where water can collect in naturally occurring terrain depressions during periods of heavy precipitation and form large water bodies (such as ponds). At far range, reflections of the sky provide a strong cue for water. But at close range, the color coming out of a water body dominates sky reflections and the water cue from sky reflections is of marginal use. We model this behavior by using water body intensity data from multiple frames of RGB imagery to estimate the total reflection coefficient contribution from surface reflections and the combination of all other factors. Then we describe an algorithm that uses one of the color cameras in a forward- looking, UGV-mounted stereo-vision perception system to detect water bodies in wide open areas. This detector exploits the knowledge that the change in saturation-to-brightness ratio across a water body from the leading to trailing edge is uniform and distinct from other terrain types. In test sequences approaching a pond under clear, overcast, and cloudy sky conditions, the true positive and false negative water detection rates were (95.76%, 96.71%, 98.77%) and (0.45%, 0.60%, 0.62%), respectively. This software has been integrated on an experimental unmanned vehicle and field tested at Ft. Indiantown Gap, PA.

  13. Global Contrast Based Salient Region Detection.

    PubMed

    Cheng, Ming-Ming; Mitra, Niloy J; Huang, Xiaolei; Torr, Philip H S; Hu, Shi-Min

    2015-03-01

    Automatic estimation of salient object regions across images, without any prior assumption or knowledge of the contents of the corresponding scenes, enhances many computer vision and computer graphics applications. We introduce a regional contrast based salient object detection algorithm, which simultaneously evaluates global contrast differences and spatial weighted coherence scores. The proposed algorithm is simple, efficient, naturally multi-scale, and produces full-resolution, high-quality saliency maps. These saliency maps are further used to initialize a novel iterative version of GrabCut, namely SaliencyCut, for high quality unsupervised salient object segmentation. We extensively evaluated our algorithm using traditional salient object detection datasets, as well as a more challenging Internet image dataset. Our experimental results demonstrate that our algorithm consistently outperforms 15 existing salient object detection and segmentation methods, yielding higher precision and better recall rates. We also show that our algorithm can be used to efficiently extract salient object masks from Internet images, enabling effective sketch-based image retrieval (SBIR) via simple shape comparisons. Despite such noisy internet images, where the saliency regions are ambiguous, our saliency guided image retrieval achieves a superior retrieval rate compared with state-of-the-art SBIR methods, and additionally provides important target object region information. PMID:26353262

  14. QRS detection based ECG quality assessment.

    PubMed

    Hayn, Dieter; Jammerbund, Bernhard; Schreier, Günter

    2012-09-01

    Although immediate feedback concerning ECG signal quality during recording is useful, up to now not much literature describing quality measures is available. We have implemented and evaluated four ECG quality measures. Empty lead criterion (A), spike detection criterion (B) and lead crossing point criterion (C) were calculated from basic signal properties. Measure D quantified the robustness of QRS detection when applied to the signal. An advanced Matlab-based algorithm combining all four measures and a simplified algorithm for Android platforms, excluding measure D, were developed. Both algorithms were evaluated by taking part in the Computing in Cardiology Challenge 2011. Each measure's accuracy and computing time was evaluated separately. During the challenge, the advanced algorithm correctly classified 93.3% of the ECGs in the training-set and 91.6 % in the test-set. Scores for the simplified algorithm were 0.834 in event 2 and 0.873 in event 3. Computing time for measure D was almost five times higher than for other measures. Required accuracy levels depend on the application and are related to computing time. While our simplified algorithm may be accurate for real-time feedback during ECG self-recordings, QRS detection based measures can further increase the performance if sufficient computing power is available. PMID:22902864

  15. Motion detection based on recurrent network dynamics

    PubMed Central

    Joukes, Jeroen; Hartmann, Till S.; Krekelberg, Bart

    2014-01-01

    The detection of visual motion requires temporal delays to compare current with earlier visual input. Models of motion detection assume that these delays reside in separate classes of slow and fast thalamic cells, or slow and fast synaptic transmission. We used a data-driven modeling approach to generate a model that instead uses recurrent network dynamics with a single, fixed temporal integration window to implement the velocity computation. This model successfully reproduced the temporal response dynamics of a population of motion sensitive neurons in macaque middle temporal area (MT) and its constituent parts matched many of the properties found in the motion processing pathway (e.g., Gabor-like receptive fields (RFs), simple and complex cells, spatially asymmetric excitation and inhibition). Reverse correlation analysis revealed that a simplified network based on first and second order space-time correlations of the recurrent model behaved much like a feedforward motion energy (ME) model. The feedforward model, however, failed to capture the full speed tuning and direction selectivity properties based on higher than second order space-time correlations typically found in MT. These findings support the idea that recurrent network connectivity can create temporal delays to compute velocity. Moreover, the model explains why the motion detection system often behaves like a feedforward ME network, even though the anatomical evidence strongly suggests that this network should be dominated by recurrent feedback. PMID:25565992

  16. Vegetation change detection in the Savannah River swamp

    SciTech Connect

    Jensen, J.R.; Christensen, E.J.; Mackey, H.E. Jr.

    1986-01-01

    Portions of Pen Branch, Four Mile Creek, Steel Creek, and Beaver Dam Creek deltas in the Savannah River swamp were evaluated for wetlands vegetation change using aircraft multispectral scanner (MSS) data acquired at 2440 meters altitude. Areas of 190 hectares on the Pen Branch, Four Mile Creek, and Beaver Dam Creek deltas, and a 240-hectare portion of Steel Creek delta were registered, classified, and wetlands vegetation change detection categories determined. Pen Branch and Four Mile Creek deltas each lost about 12 hectares of swamp forest from 1981 to 1984. Secondary successional forest regrew on portions of the Four Mile Creek delta (2.4 hectares) and the Beaver Dam Creek delta (15.4 hectares). About 5 hectares of swamp forest regrew on the Steel Creek delta. This may be the first study to detect wetlands vegetation change over several years using aircraft MSS data. One reason could be due to difficulties similar to those encountered in this study. Data distortion from aircraft movement in some areas of the swamp made image-to-image registration difficult. Best results were obtained on Beaver Dam Creek and Steel Creek deltas which had average registration accuracies within one data element, or pixel, of 5.6 x 5.6 meters. Phenological differences and shadows caused difficulties in vegetation-type discrimination and classification. As a result, the number of vegetation change classes were sometimes limited.

  17. The Challenge of Automated Change Detection: Developing a Method for the Updating of Land Parcels

    NASA Astrophysics Data System (ADS)

    Matikainen, L.; Karila, K.; Litkey, P.; Ahokas, E.; Munck, A.; Karjalainen, M.; Hyyppä, J.

    2012-07-01

    Development of change detection methods that are functional and reliable enough for operational work is still a demanding task. This article discusses automated change detection from the viewpoint of one case study: the Finnish Land Parcel Identification System (FLPIS). The objective of the study is to develop a change detection method that could be used as an aid in the updating of the FLPIS. The method is based on object-based interpretation, and it uses existing parcel boundaries and new aerial ortho images as input data. Rules for classifying field and non-field objects are defined automatically by using the classification tree method and training data. Additional, manually created rules are used to improve the results. Classification tests carried out during the development work suggest that real changes can be detected relatively well. According to a recent visual evaluation, 96% of changes larger than 100 m2 were detected, at least partly. The overall accuracy of the change detection results was 93% when compared with reference data pixel-by-pixel. On the other hand, there are also missing changes and numerous false alarms. The main challenges encountered in the method development include the wide diversity of agricultural fields and other land cover objects locally, across the country, and at different times of the spring and summer, variability in the digital numbers (DNs) of the aerial images, the different nature of visual and automatic interpretation, and the small percentage of the total field area that has really changed. These challenges and possible solutions are discussed in the article.

  18. Evaluation of Landsat-7 SLC-off image products for forest change detection

    USGS Publications Warehouse

    Wulder, Michael A.; Ortlepp, Stephanie M.; White, Joanne C.; Maxwell, Susan

    2008-01-01

    Since July 2003, Landsat-7 ETM+ has been operating without the scan line corrector (SLC), which compensates for the forward motion of the satellite in the imagery acquired. Data collected in SLC-off mode have gaps in a systematic wedge-shaped pattern outside of the central 22 km swath of the imagery; however, the spatial and spectral quality of the remaining portions of the imagery are not diminished. To explore the continued use of Landsat-7 ETM+ SLC-off imagery to characterize change in forested environments, we compare the change detection results generated from a reference image pair (a 1999 Landsat-7 ETM+ image and a 2003 Landsat-5 TM image) with change detection results generated from the same 1999 Landsat-7 ETM+ image coupled with three different 2003 Landsat-7 SLC-off products: unremediated SLC-off (i.e., with gaps); histogram-based gap-filled; and segment-based gap-filled. The results are compared on both a pixel and polygon basis; on a pixel basis, the unremediated SLC-off product missed 35% of the change identified by the reference data, and the histogram- and segment-based gap-filled products missed 23% and 21% of the change, respectively. When using forest inventory polygons as a context for change (to reduce commission error), the amount of change missed was 31%, 14%, and 12% for the each of the unremediated, histogram-based gap-filled, and segment-based gap-filled products, respectively. Our results indicate that over the time period considered, and given the types and spatial distribution of change events within our study area, the gap-filled products can provide a useful data source for change detection in forested environments. The selection of which product to use is, however, very dependent on the nature of the application and the spatial configuration of change events. ?? 2008 Government of Canada.

  19. Detecting a trend change in cross-border epidemic transmission

    NASA Astrophysics Data System (ADS)

    Maeno, Yoshiharu

    2016-09-01

    A method for a system of Langevin equations is developed for detecting a trend change in cross-border epidemic transmission. The equations represent a standard epidemiological SIR compartment model and a meta-population network model. The method analyzes a time series of the number of new cases reported in multiple geographical regions. The method is applicable to investigating the efficacy of the implemented public health intervention in managing infectious travelers across borders. It is found that the change point of the probability of travel movements was one week after the WHO worldwide alert on the SARS outbreak in 2003. The alert was effective in managing infectious travelers. On the other hand, it is found that the probability of travel movements did not change at all for the flu pandemic in 2009. The pandemic did not affect potential travelers despite the WHO alert.

  20. Visual detection of body weight change in young women.

    PubMed

    Alley, T R

    1991-12-01

    To assess whether small changes in body weight can be visually detected, college students (58 women and 42 men) were asked to select the less heavy person shown in two photographs for each of 33 young women. All of these women had been photographed twice in a standardized pose and attire, separated by an 8-wk. interval during which most of them lost weight. These pairs were presented in varying orders to control for the order and side of presentation. One photograph was reliably selected as the lighter person for 64% of the pairs, but the picture selected was in fact lighter only 57% of the time. The accuracy of selecting the lighter photograph was not correlated with the percent weight change for the person shown in the pairs of photographs. The results suggest that small changes in women's weight may not have a significant perceptual effect, particularly for male perceivers. PMID:1792140

  1. Reset tree-based optical fault detection.

    PubMed

    Lee, Dong-Geon; Choi, Dooho; Seo, Jungtaek; Kim, Howon

    2013-01-01

    In this paper, we present a new reset tree-based scheme to protect cryptographic hardware against optical fault injection attacks. As one of the most powerful invasive attacks on cryptographic hardware, optical fault attacks cause semiconductors to misbehave by injecting high-energy light into a decapped integrated circuit. The contaminated result from the affected chip is then used to reveal secret information, such as a key, from the cryptographic hardware. Since the advent of such attacks, various countermeasures have been proposed. Although most of these countermeasures are strong, there is still the possibility of attack. In this paper, we present a novel optical fault detection scheme that utilizes the buffers on a circuit's reset signal tree as a fault detection sensor. To evaluate our proposal, we model radiation-induced currents into circuit components and perform a SPICE simulation. The proposed scheme is expected to be used as a supplemental security tool. PMID:23698267

  2. Reset Tree-Based Optical Fault Detection

    PubMed Central

    Lee, Dong-Geon; Choi, Dooho; Seo, Jungtaek; Kim, Howon

    2013-01-01

    In this paper, we present a new reset tree-based scheme to protect cryptographic hardware against optical fault injection attacks. As one of the most powerful invasive attacks on cryptographic hardware, optical fault attacks cause semiconductors to misbehave by injecting high-energy light into a decapped integrated circuit. The contaminated result from the affected chip is then used to reveal secret information, such as a key, from the cryptographic hardware. Since the advent of such attacks, various countermeasures have been proposed. Although most of these countermeasures are strong, there is still the possibility of attack. In this paper, we present a novel optical fault detection scheme that utilizes the buffers on a circuit's reset signal tree as a fault detection sensor. To evaluate our proposal, we model radiation-induced currents into circuit components and perform a SPICE simulation. The proposed scheme is expected to be used as a supplemental security tool. PMID:23698267

  3. Analysis of quantitative phase detection based on optical information processing

    NASA Astrophysics Data System (ADS)

    Tao, Wang; Tu, Jiang-Chen; Chun, Kuang-Tao; Yu, Han-Wang; Xin, Du

    2009-07-01

    Phase object exists widely in nature, such as biological cells, optical components, atmospheric flow field and so on. The phase detection of objects has great significance in the basic research, nondestructive testing, aerospace, military weapons and other areas. The usual methods of phase object detection include interference method, grating method, schlieren method, and phase-contrast method etc. These methods have their own advantages, but they also have some disadvantages on detecting precision, environmental requirements, cost, detection rate, detection range, detection linearity in various applications, even the most sophisticated method-phase contrast method mainly used in microscopic structure, lacks quantitative analysis of the size of the phase of the object and the relationship between the image contrast and the optical system. In this paper, various phase detection means and the characteristics of different applications are analyzed based on the optical information processing, and a phase detection system based on optical filtering is formed. Firstly the frequency spectrum of the phase object is achieved by Fourier transform lens in the system, then the frequency spectrum is changed reasonably by the filter, at last the image which can represent the phase distribution through light intensity is achieved by the inverse Fourier transform. The advantages and disadvantages of the common used filters such as 1/4 wavelength phase filter, high-pass filter and edge filter are analyzed, and their phase resolution is analyzed in the same optical information processing system, and the factors impacting phase resolution are pointed out. The paper draws a conclusion that there exists an optimal filter which makes the detect accuracy best for any application. At last, we discussed how to design an optimal filter through which the ability of the phase testing of optical information processing system can be improved most.

  4. Enhanced climate change and its detection over the Rocky Mountains

    SciTech Connect

    Fyfe, J.C.; Flato, G.M.

    1999-01-01

    Results from an ensemble of climate change experiments with increasing greenhouse gas and aerosols using the Canadian Centre for Climate Modeling and Analysis Coupled Climate Model are presented with a focus on surface quantities over the Rocky Mountains. There is a marked elevation dependency of the simulated surface screen temperature increase over the Rocky Mountains in the winter and spring seasons, with more pronounced changes at higher elevations. The elevation signal is linked to a rise in the snow line in the winter and spring seasons, which amplifies the surface warming via the snow-albedo feedback. Analysis of the winter surface energy budget shows that large changes in the solar component of the radiative input are the direct consequence of surface albedo changes caused by decreasing snow cover. Although the warming signal is enhanced at higher elevations, a two-way analysis of variance reveals that the elevation effect has no potential for early climate change detection. In the early stages of surface warming the elevation effect is masked by relatively large noise, so that the signal-to-noise ratio over the Rocky Mountains is no larger than elsewhere. Only after significant continental-scale warming does the local Rocky Mountain signal begin to dominate the pattern of climate change over western North America (and presumably also the surrounding ecosystems and hydrological networks).

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

    PubMed

    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. PMID:20935169

  6. Indigenous Knowledge and Long-term Ecological Change: Detection, Interpretation, and Responses to Changing Ecological Conditions in Pacific Island Communities

    PubMed Central

    Aswani, Shankar

    2010-01-01

    When local resource users detect, understand, and respond to environmental change they can more effectively manage environmental resources. This article assesses these abilities among artisanal fishers in Roviana Lagoon, Solomon Islands. In a comparison of two villages, it documents local resource users’ abilities to monitor long-term ecological change occurring to seagrass meadows near their communities, their understandings of the drivers of change, and their conceptualizations of seagrass ecology. Local observations of ecological change are compared with historical aerial photography and IKONOS satellite images that show 56 years of actual changes in seagrass meadows from 1947 to 2003. Results suggest that villagers detect long-term changes in the spatial cover of rapidly expanding seagrass meadows. However, for seagrass meadows that showed no long-term expansion or contraction in spatial cover over one-third of respondents incorrectly assumed changes had occurred. Examples from a community-based management initiative designed around indigenous ecological knowledge and customary sea tenure governance show how local observations of ecological change shape marine resource use and practices which, in turn, can increase the management adaptability of indigenous or hybrid governance systems. PMID:20336296

  7. Indigenous Knowledge and Long-term Ecological Change: Detection, Interpretation, and Responses to Changing Ecological Conditions in Pacific Island Communities

    NASA Astrophysics Data System (ADS)

    Lauer, Matthew; Aswani, Shankar

    2010-05-01

    When local resource users detect, understand, and respond to environmental change they can more effectively manage environmental resources. This article assesses these abilities among artisanal fishers in Roviana Lagoon, Solomon Islands. In a comparison of two villages, it documents local resource users’ abilities to monitor long-term ecological change occurring to seagrass meadows near their communities, their understandings of the drivers of change, and their conceptualizations of seagrass ecology. Local observations of ecological change are compared with historical aerial photography and IKONOS satellite images that show 56 years of actual changes in seagrass meadows from 1947 to 2003. Results suggest that villagers detect long-term changes in the spatial cover of rapidly expanding seagrass meadows. However, for seagrass meadows that showed no long-term expansion or contraction in spatial cover over one-third of respondents incorrectly assumed changes had occurred. Examples from a community-based management initiative designed around indigenous ecological knowledge and customary sea tenure governance show how local observations of ecological change shape marine resource use and practices which, in turn, can increase the management adaptability of indigenous or hybrid governance systems.

  8. Indigenous knowledge and long-term ecological change: detection, interpretation, and responses to changing ecological conditions in Pacific Island communities.

    PubMed

    Lauer, Matthew; Aswani, Shankar

    2010-05-01

    When local resource users detect, understand, and respond to environmental change they can more effectively manage environmental resources. This article assesses these abilities among artisanal fishers in Roviana Lagoon, Solomon Islands. In a comparison of two villages, it documents local resource users' abilities to monitor long-term ecological change occurring to seagrass meadows near their communities, their understandings of the drivers of change, and their conceptualizations of seagrass ecology. Local observations of ecological change are compared with historical aerial photography and IKONOS satellite images that show 56 years of actual changes in seagrass meadows from 1947 to 2003. Results suggest that villagers detect long-term changes in the spatial cover of rapidly expanding seagrass meadows. However, for seagrass meadows that showed no long-term expansion or contraction in spatial cover over one-third of respondents incorrectly assumed changes had occurred. Examples from a community-based management initiative designed around indigenous ecological knowledge and customary sea tenure governance show how local observations of ecological change shape marine resource use and practices which, in turn, can increase the management adaptability of indigenous or hybrid governance systems. PMID:20336296

  9. How minimum detectable displacement in a GNSS Monitoring Network change?

    NASA Astrophysics Data System (ADS)

    Hilmi Erkoç, Muharrem; Doǧan, Uǧur; Aydın, Cüneyt

    2016-04-01

    The minimum detectable displacement in a geodetic monitoring network shows the displacement magnitude which may be just discriminated with known error probabilities. This displacement, which is originally deduced from sensitivity analysis, depends on network design, observation accuracy, datum of the network, direction of the displacement and power of the statistical test used for detecting the displacements. One may investigate how different scenarios on network design and observation accuracies influence the minimum detectable displacements for the specified datum, a-priorly forecasted directions and assumed power of the test and decide which scenario is the best or most optimum. It is sometimes difficult to forecast directions of the displacements. In that case, the minimum detectable displacements in a geodetic monitoring network are derived on the eigen-directions associated with the maximum eigen-values of the network stations. This study investigates how minimum detectable displacements in a GNSS monitoring network change depending on the accuracies of the network stations. For this, CORS-TR network in Turkey with 15 stations (a station fixed) is used. The data with 4h, 6h, 12 h and 24 h observing session duration in three sequential days of 2011, 2012 and 2013 were analyzed with Bernese 5.2 GNSS software. The repeatabilities of the daily solutions belonging to each year were analyzed carefully to scale the Bernese cofactor matrices properly. The root mean square (RMS) values for daily repeatability with respect to the combined 3-day solution are computed (the RMS values are generally less than 2 mm in the horizontal directions (north and east) and < 5 mm in the vertical direction for 24 h observing session duration). With the obtained cofactor matrices for these observing sessions, the minimum detectable displacements along the (maximum) eigen directions are compared each other. According to these comparisons, more session duration less minimum detectable

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

    NASA Astrophysics Data System (ADS)

    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.

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

    PubMed

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

    2016-01-01

    Detecting changes, in performance, sales, markets, risks, social relations, or public opinions, constitutes an important adaptive function. In a sequential paradigm devised to investigate detection of change, every trial provides a sample of binary outcomes (e.g., correct vs. incorrect student responses). Participants have to decide whether the proportion of a focal feature (e.g., correct responses) in the population from which the sample is drawn has decreased, remained constant, or increased. Strong and persistent anomalies in change detection arise when changes in proportional quantities vary orthogonally to changes in absolute sample size. Proportional increases are readily detected and nonchanges are erroneously perceived as increases when absolute sample size increases. Conversely, decreasing sample size facilitates the correct detection of proportional decreases and the erroneous perception of nonchanges as decreases. These anomalies are however confined to experienced samples of elementary raw events from which proportions have to be inferred inductively. They disappear when sample proportions are described as percentages in a normalized probability format. To explain these challenging findings, it is essential to understand the inductive-learning constraints imposed on decisions from experience. PMID:26179055

  12. DETECTING LAND COVER CHANGE AT THE JORNADA EXPERIMENT RANGE, NEW MEXICO, WITH ASTER EMISSIVITIES

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Multispectral thermal infrared remote sensing of surface emissivities can detect and monitor long term land cover changes over arid regions. The technique is based on the association between broadband emissivity and density of sparsely covered terrains. The association exists regardless of plant col...

  13. Seasonal Change Detection and Attribution of Surface Temperature changes over Interior Peninsular Region of India

    NASA Astrophysics Data System (ADS)

    Pattanayak, Sonali; Nagesh Kumar, Dasika

    2015-04-01

    A good number of studies have investigated recent trends in the observed and simulated hydrometeorological variables across the world. It has been challenging for the research community to address whether the significant change in climate over the course of 2nd half of 20th century is caused either due to natural or manmade effects. Although evidences for an anthropogenic contribution to climatic trends have been accumulated rapidly worldwide, for India these are scarce. Hence the formal efforts have been undertaken to distinguish whether the recent changes in seasonal temperature over India occurred due to natural internal variation of climate system or human influence using rigorous detection and attribution (D&A) procedure. The surface temperature is the most widely cited indicator of climate fluctuation. Hence maximum and minimum temperatures (Tmax & Tmin) which are among the six most commonly used variables for impact assessment studies are analyzed here. Seasonal divisions are based on conventional meteorological seasons: January-February (winter); March-May (pre monsoon); June-September (monsoon); October-December (post monsoon). Time span considered for this study is 1950-2005. Climate Research Unit (Version 3.21) gridded monthly temperature datasets are considered as observed data. Initially TFPW-MK (Trend Free Pre Whitening Mann Kendall) test is used to search the significant trends in the four seasons over all India. Temporal change detection analysis in evapotranspiration (which is one of the key processes in hydrological cycle) is essential for progress in water resources planning and management. Hence along with Tmax and Tmin, potential evapotranspiration (PET) has also been analyzed for the similar conditions. Significant upward trends in Tmax, Tmin and PET are observed over most of the grid points in Interior Peninsula (IP) region over India. Significant correlation was obtained between PET and Tmax compared to PET and Tmin. Trends in Tmin clearly

  14. Asynchronous event-based corner detection and matching.

    PubMed

    Clady, Xavier; Ieng, Sio-Hoi; Benosman, Ryad

    2015-06-01

    This paper introduces an event-based luminance-free method to detect and match corner events from the output of asynchronous event-based neuromorphic retinas. The method relies on the use of space-time properties of moving edges. Asynchronous event-based neuromorphic retinas are composed of autonomous pixels, each of them asynchronously generating "spiking" events that encode relative changes in pixels' illumination at high temporal resolutions. Corner events are defined as the spatiotemporal locations where the aperture problem can be solved using the intersection of several geometric constraints in events' spatiotemporal spaces. A regularization process provides the required constraints, i.e. the motion attributes of the edges with respect to their spatiotemporal locations using local geometric properties of visual events. Experimental results are presented on several real scenes showing the stability and robustness of the detection and matching. PMID:25828960

  15. Mobile Recommendation Based on Link Community Detection

    PubMed Central

    Zhang, Jianpei; Yang, Jing

    2014-01-01

    Since traditional mobile recommendation systems have difficulty in acquiring complete and accurate user information in mobile networks, the accuracy of recommendation is not high. In order to solve this problem, this paper proposes a novel mobile recommendation algorithm based on link community detection (MRLD). MRLD executes link label diffusion algorithm and maximal extended modularity (EQ) of greedy search to obtain the link community structure, and overlapping nodes belonging analysis (ONBA) is adopted to adjust the overlapping nodes in order to get the more accurate community structure. MRLD is tested on both synthetic and real-world networks, and the experimental results show that our approach is valid and feasible. PMID:25243204

  16. 3D change detection at street level using mobile laser scanning point clouds and terrestrial images

    NASA Astrophysics Data System (ADS)

    Qin, Rongjun; Gruen, Armin

    2014-04-01

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

  17. SU-E-J-191: Automated Detection of Anatomic Changes in H'N Patients

    SciTech Connect

    Usynin, A; Ramsey, C

    2014-06-01

    Purpose: To develop a novel statistics-based method for automated detection of anatomical changes using cone-beam CT data. A method was developed that can provide a reliable and automated early warning system that enables a “just-in-time” adaptation of the treatment plan. Methods: Anatomical changes were evaluated by comparing the original treatment planning CT with daily CBCT images taken prior treatment delivery. The external body contour was computed on a given CT slice and compared against the corresponding contour on the daily CBCT. In contrast to threshold-based techniques, a statistical approach was employed to evaluate the difference between the contours using a given confidence level. The detection tool used the two-sample Kolmogorov-Smirnov test, which is a non-parametric technique that compares two samples drawn from arbitrary probability distributions. 11 H'N patients were retrospectively selected from a clinical imaging database with a total of 186 CBCT images. Six patients in the database were confirmed to have anatomic changes during the course of radiotherapy. Five of the H'N patients did not have significant changes. The KS test was applied to the contour data using a sliding window analysis. The confidence level of 0.99 was used to moderate false detection. Results: The algorithm was able to correctly detect anatomical changes in 6 out of 6 patients with an excellent spatial accuracy as early as at the 14th elapsed day. The algorithm provided a consistent and accurate delineation of the detected changes. The output of the anatomical change tool is easy interpretable, and can be shown overlaid on a 3D rendering of the patient's anatomy. Conclusion: The detection method provides the basis for one of the key components of Adaptive Radiation Therapy. The method uses tools that are readily available in the clinic, including daily CBCT imaging, and image co-registration facilities.

  18. Automatic detection of unattended changes in room acoustics.

    PubMed

    Frey, Johannes Daniel; Wendt, Mike; Jacobsen, Thomas

    2015-01-01

    Previous research has shown that the human auditory system continuously monitors its acoustic environment, detecting a variety of irregularities (e.g., deviance from prior stimulation regularity in pitch, loudness, duration, and (perceived) sound source location). Detection of irregularities can be inferred from a component of the event-related brain potential (ERP), referred to as the mismatch negativity (MMN), even in conditions in which participants are instructed to ignore the auditory stimulation. The current study extends previous findings by demonstrating that auditory irregularities brought about by a change in room acoustics elicit a MMN in a passive oddball protocol (acoustic stimuli with differing room acoustics, that were otherwise identical, were employed as standard and deviant stimuli), in which participants watched a fiction movie (silent with subtitles). While the majority of participants reported no awareness for any changes in the auditory stimulation, only one out of 14 participants reported to have become aware of changing room acoustics or sound source location. Together, these findings suggest automatic monitoring of room acoustics. PMID:25301567

  19. FRET-based biosensors to detect infectious agents

    NASA Astrophysics Data System (ADS)

    Xu, Juntao; Grant, Sheila A.

    2002-02-01

    We report herein on the development of a FRET-based method to detect changes caused by viral protein-receptor binding. FRET fluorophore pairs (donor and acceptor fluorophores) were tagged to two specific receptors, both which bind to a viral protein. When the binding event occurs, the distance between the donor and acceptor FRET fluorophores is decreased, thus initiating the fluorescence resonance energy transfer (FRET). Since the binding event is unique to the viral protein, fluorescent change indicates the present of the virus. In this paper, the viral protein gp120, which is the featured protein on the surface of HIV-1, was detected. The receptors, CD4 and gp120-antibody which specifically bind to gp120, were conjugated to the FRET fluorophore pair, AMCA-NHS (succinimidyl-7-amino-4-methylcoumarin-3-acetic acid) and FITC (fluorescein isothiocyanate) respectively. Spectrofluorimetry was used to detect the fluorescent change between AMCA-NHS and FITC peak intensities when the receptors bind to the gp120. Specific binding gp120 and non-specific binding gp120 were used to test the selectivity of the sensor. The results indicated that FRET-conjugated receptors can efficiently detect the presence of gp120.

  20. Visual change detection recruits auditory cortices in early deafness.

    PubMed

    Bottari, Davide; Heimler, Benedetta; Caclin, Anne; Dalmolin, Anna; Giard, Marie-Hélène; Pavani, Francesco

    2014-07-01

    Although cross-modal recruitment of early sensory areas in deafness and blindness is well established, the constraints and limits of these plastic changes remain to be understood. In the case of human deafness, for instance, it is known that visual, tactile or visuo-tactile stimuli can elicit a response within the auditory cortices. Nonetheless, both the timing of these evoked responses and the functional contribution of cross-modally recruited areas remain to be ascertained. In the present study, we examined to what extent auditory cortices of deaf humans participate in high-order visual processes, such as visual change detection. By measuring visual ERPs, in particular the visual MisMatch Negativity (vMMN), and performing source localization, we show that individuals with early deafness (N=12) recruit the auditory cortices when a change in motion direction during shape deformation occurs in a continuous visual motion stream. Remarkably this "auditory" response for visual events emerged with the same timing as the visual MMN in hearing controls (N=12), between 150 and 300 ms after the visual change. Furthermore, the recruitment of auditory cortices for visual change detection in early deaf was paired with a reduction of response within the visual system, indicating a shift from visual to auditory cortices of part of the computational process. The present study suggests that the deafened auditory cortices participate at extracting and storing the visual information and at comparing on-line the upcoming visual events, thus indicating that cross-modally recruited auditory cortices can reach this level of computation. PMID:24636881

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

    NASA Astrophysics Data System (ADS)

    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.

  2. A liquid-crystal-based DNA biosensor for pathogen detection

    NASA Astrophysics Data System (ADS)

    Khan, Mashooq; Khan, Abdur Rahim; Shin, Jae-Ho; Park, Soo-Young

    2016-03-01

    A liquid-crystal (LC)-filled transmission electron microscopy (TEM) grid cell coated with the cationic surfactant dodecyltrimethylammonium bromide (DTAB), to which a single-stranded deoxyribonucleic acid probe (ssDNAprobe) was adsorbed at the LC/aqueous interface (TEMDTAB/DNA), was applied for the highly specific detection of target DNA molecules. The DTAB-coated E7 (used LC mixture) in the TEM grid (TEMDTAB) exhibited a homeotropic orientation, and changed to a planar orientation upon adsorption of the ssDNAprobe. The TEMDTAB/DNA was then exposed to complementary (target) ssDNA, which resulted in a planar-to-homeotropic configurational change of E7 that could be observed through a polarized optical microscope under crossed polarizers. The optimum adsorption density (2 μM) of ssDNAprobe enabled the detection of ≥0.05 nM complementary ssDNA. This TEMDTAB/DNA biosensor could differentiate complementary ssDNA from mismatched ssDNA as well as double-stranded DNA. It also successfully detected the genomic DNAs of the bacterium Erwinia carotovora and the fungi Rhazictonia solani. Owe to the high specificity, sensitivity, and label-free detection, this biosensor may broaden the applications of LC-based biosensors to pathogen detection.

  3. A liquid-crystal-based DNA biosensor for pathogen detection.

    PubMed

    Khan, Mashooq; Khan, Abdur Rahim; Shin, Jae-Ho; Park, Soo-Young

    2016-01-01

    A liquid-crystal (LC)-filled transmission electron microscopy (TEM) grid cell coated with the cationic surfactant dodecyltrimethylammonium bromide (DTAB), to which a single-stranded deoxyribonucleic acid probe (ssDNAprobe) was adsorbed at the LC/aqueous interface (TEMDTAB/DNA), was applied for the highly specific detection of target DNA molecules. The DTAB-coated E7 (used LC mixture) in the TEM grid (TEMDTAB) exhibited a homeotropic orientation, and changed to a planar orientation upon adsorption of the ssDNAprobe. The TEMDTAB/DNA was then exposed to complementary (target) ssDNA, which resulted in a planar-to-homeotropic configurational change of E7 that could be observed through a polarized optical microscope under crossed polarizers. The optimum adsorption density (2 μM) of ssDNAprobe enabled the detection of ≥0.05 nM complementary ssDNA. This TEMDTAB/DNA biosensor could differentiate complementary ssDNA from mismatched ssDNA as well as double-stranded DNA. It also successfully detected the genomic DNAs of the bacterium Erwinia carotovora and the fungi Rhazictonia solani. Owe to the high specificity, sensitivity, and label-free detection, this biosensor may broaden the applications of LC-based biosensors to pathogen detection. PMID:26940532

  4. A liquid-crystal-based DNA biosensor for pathogen detection

    PubMed Central

    Khan, Mashooq; Khan, Abdur Rahim; Shin, Jae-Ho; Park, Soo-Young

    2016-01-01

    A liquid-crystal (LC)-filled transmission electron microscopy (TEM) grid cell coated with the cationic surfactant dodecyltrimethylammonium bromide (DTAB), to which a single-stranded deoxyribonucleic acid probe (ssDNAprobe) was adsorbed at the LC/aqueous interface (TEMDTAB/DNA), was applied for the highly specific detection of target DNA molecules. The DTAB-coated E7 (used LC mixture) in the TEM grid (TEMDTAB) exhibited a homeotropic orientation, and changed to a planar orientation upon adsorption of the ssDNAprobe. The TEMDTAB/DNA was then exposed to complementary (target) ssDNA, which resulted in a planar-to-homeotropic configurational change of E7 that could be observed through a polarized optical microscope under crossed polarizers. The optimum adsorption density (2 μM) of ssDNAprobe enabled the detection of ≥0.05 nM complementary ssDNA. This TEMDTAB/DNA biosensor could differentiate complementary ssDNA from mismatched ssDNA as well as double-stranded DNA. It also successfully detected the genomic DNAs of the bacterium Erwinia carotovora and the fungi Rhazictonia solani. Owe to the high specificity, sensitivity, and label-free detection, this biosensor may broaden the applications of LC-based biosensors to pathogen detection. PMID:26940532

  5. Overlapping Community Detection based on Network Decomposition

    NASA Astrophysics Data System (ADS)

    Ding, Zhuanlian; Zhang, Xingyi; Sun, Dengdi; Luo, Bin

    2016-04-01

    Community detection in complex network has become a vital step to understand the structure and dynamics of networks in various fields. However, traditional node clustering and relatively new proposed link clustering methods have inherent drawbacks to discover overlapping communities. Node clustering is inadequate to capture the pervasive overlaps, while link clustering is often criticized due to the high computational cost and ambiguous definition of communities. So, overlapping community detection is still a formidable challenge. In this work, we propose a new overlapping community detection algorithm based on network decomposition, called NDOCD. Specifically, NDOCD iteratively splits the network by removing all links in derived link communities, which are identified by utilizing node clustering technique. The network decomposition contributes to reducing the computation time and noise link elimination conduces to improving the quality of obtained communities. Besides, we employ node clustering technique rather than link similarity measure to discover link communities, thus NDOCD avoids an ambiguous definition of community and becomes less time-consuming. We test our approach on both synthetic and real-world networks. Results demonstrate the superior performance of our approach both in computation time and accuracy compared to state-of-the-art algorithms.

  6. Overlapping Community Detection based on Network Decomposition

    PubMed Central

    Ding, Zhuanlian; Zhang, Xingyi; Sun, Dengdi; Luo, Bin

    2016-01-01

    Community detection in complex network has become a vital step to understand the structure and dynamics of networks in various fields. However, traditional node clustering and relatively new proposed link clustering methods have inherent drawbacks to discover overlapping communities. Node clustering is inadequate to capture the pervasive overlaps, while link clustering is often criticized due to the high computational cost and ambiguous definition of communities. So, overlapping community detection is still a formidable challenge. In this work, we propose a new overlapping community detection algorithm based on network decomposition, called NDOCD. Specifically, NDOCD iteratively splits the network by removing all links in derived link communities, which are identified by utilizing node clustering technique. The network decomposition contributes to reducing the computation time and noise link elimination conduces to improving the quality of obtained communities. Besides, we employ node clustering technique rather than link similarity measure to discover link communities, thus NDOCD avoids an ambiguous definition of community and becomes less time-consuming. We test our approach on both synthetic and real-world networks. Results demonstrate the superior performance of our approach both in computation time and accuracy compared to state-of-the-art algorithms. PMID:27066904

  7. Overlapping Community Detection based on Network Decomposition.

    PubMed

    Ding, Zhuanlian; Zhang, Xingyi; Sun, Dengdi; Luo, Bin

    2016-01-01

    Community detection in complex network has become a vital step to understand the structure and dynamics of networks in various fields. However, traditional node clustering and relatively new proposed link clustering methods have inherent drawbacks to discover overlapping communities. Node clustering is inadequate to capture the pervasive overlaps, while link clustering is often criticized due to the high computational cost and ambiguous definition of communities. So, overlapping community detection is still a formidable challenge. In this work, we propose a new overlapping community detection algorithm based on network decomposition, called NDOCD. Specifically, NDOCD iteratively splits the network by removing all links in derived link communities, which are identified by utilizing node clustering technique. The network decomposition contributes to reducing the computation time and noise link elimination conduces to improving the quality of obtained communities. Besides, we employ node clustering technique rather than link similarity measure to discover link communities, thus NDOCD avoids an ambiguous definition of community and becomes less time-consuming. We test our approach on both synthetic and real-world networks. Results demonstrate the superior performance of our approach both in computation time and accuracy compared to state-of-the-art algorithms. PMID:27066904

  8. Waveguide-Based Biosensors for Pathogen Detection

    PubMed Central

    Mukundan, Harshini; Anderson, Aaron S.; Grace, W. Kevin; Grace, Karen M.; Hartman, Nile; Martinez, Jennifer S.; Swanson, Basil I.

    2009-01-01

    Optical phenomena such as fluorescence, phosphorescence, polarization, interference and non-linearity have been extensively used for biosensing applications. Optical waveguides (both planar and fiber-optic) are comprised of a material with high permittivity/high refractive index surrounded on all sides by materials with lower refractive indices, such as a substrate and the media to be sensed. This arrangement allows coupled light to propagate through the high refractive index waveguide by total internal reflection and generates an electromagnetic wave—the evanescent field—whose amplitude decreases exponentially as the distance from the surface increases. Excitation of fluorophores within the evanescent wave allows for sensitive detection while minimizing background fluorescence from complex, “dirty” biological samples. In this review, we will describe the basic principles, advantages and disadvantages of planar optical waveguide-based biodetection technologies. This discussion will include already commercialized technologies (e.g., Corning’s EPIC® Ô, SRU Biosystems’ BIND™, Zeptosense®, etc.) and new technologies that are under research and development. We will also review differing assay approaches for the detection of various biomolecules, as well as the thin-film coatings that are often required for waveguide functionalization and effective detection. Finally, we will discuss reverse-symmetry waveguides, resonant waveguide grating sensors and metal-clad leaky waveguides as alternative signal transducers in optical biosensing. PMID:22346727

  9. Trend Analysis and Detection of Changes in the Stratospheric Circulation

    NASA Technical Reports Server (NTRS)

    Oman, Luke; Douglass, A. R.; Rodriquez, J. M.; Stolarski, R. S.; Waugh, D. W.

    2010-01-01

    Increases in the circulation of the stratosphere appear to be a robust result of climate change in chemistry-climate models over decadal time scales. To date observations have yet to show a significant change in this circulation. It is important for the design of future observational missions to identify suitable atmospheric constituents and to determine the accuracy and length of record needed to identify a significant trend that can be attributed to circulation change. First, we determine what atmospheric variables can be used as proxies for stratospheric circulation changes. A few examples are changes in tropical lower stratospheric ozone, phase lag of the water vapor tape recorder, CO2, and SF6. Then, using both the Goddard Earth Observing System Chemistry-Climate Model (GEOS CCM) and observations from satellites and balloon soundings, we calculate the number of years needed to detect a significant trend, taking into account observational uncertainty. Model simulations will be evaluated to see how well they represent observed variability. In addition, the impacts of autocorrelation among the output or data and gaps in the observational record will be discussed.

  10. Performance of a community detection algorithm based on semidefinite programming

    NASA Astrophysics Data System (ADS)

    Ricci-Tersenghi, Federico; Javanmard, Adel; Montanari, Andrea

    2016-03-01

    The problem of detecting communities in a graph is maybe one the most studied inference problems, given its simplicity and widespread diffusion among several disciplines. A very common benchmark for this problem is the stochastic block model or planted partition problem, where a phase transition takes place in the detection of the planted partition by changing the signal-to-noise ratio. Optimal algorithms for the detection exist which are based on spectral methods, but we show these are extremely sensible to slight modification in the generative model. Recently Javanmard, Montanari and Ricci-Tersenghi [1] have used statistical physics arguments, and numerical simulations to show that finding communities in the stochastic block model via semidefinite programming is quasi optimal. Further, the resulting semidefinite relaxation can be solved efficiently, and is very robust with respect to changes in the generative model. In this paper we study in detail several practical aspects of this new algorithm based on semidefinite programming for the detection of the planted partition. The algorithm turns out to be very fast, allowing the solution of problems with O(105) variables in few second on a laptop computer.

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

    NASA Technical Reports Server (NTRS)

    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.

  12. Phase retrieval-based distribution detecting method for transparent objects

    NASA Astrophysics Data System (ADS)

    Wu, Liang; Tao, Shaohua; Xiao, Si

    2015-11-01

    A distribution detecting method to recover the distribution of transparent objects from their diffraction intensities is proposed. First, on the basis of the Gerchberg-Saxton algorithm, a wavefront function involving the phase change of the object is retrieved from the incident light intensity and the diffraction intensity, then the phase change of the object is calculated from the retrieved wavefront function by using a gradient field-based phase estimation algorithm, which circumvents the common phase wrapping problem. Finally, a linear model between the distribution of the object and the phase change is set up, and the distribution of the object can be calculated from the obtained phase change. The effectiveness of the proposed method is verified with simulations and experiments.

  13. Multi-Scale Change Detection Research of Remotely Sensed Big Data in CyberGIS

    NASA Astrophysics Data System (ADS)

    Xing, J.; Sieber, R.

    2015-12-01

    Big remotely sensed data, the heterogeneity of satellite platforms and file formats along with increasing volumes and velocities, offers new types of analyses. This makes big remotely sensed data a good candidate for CyberGIS, the aim of which is to enable knowledge discovery of big data in the cloud. We apply CyberGIS to feature-based multi-scale land use/cover change (LUCC) detection. There have been attempts to do multi-scale LUCC. However, studies were done with small data and could not consider the mismatch between multi-scale analysis and computational scale. They have yet to consider the possibilities for scalar research across numerous temporal and spatial scales afforded by big data, especially if we want to advance beyond pixel-based analysis and also reduce preprocessing requirements. We create a geospatial cyberinfrastructure (GCI) to handle multi-spatio-temporal scale change detection. We first clarify different meanings of scale in CyberGIS and LUCC to derive a feature scope layer in the GCI based on Stommel modelling. Our analysis layer contains a multi-scale segmentation-based method based on normalized cut image segmentation and wavelet-based image scaling algorithms. Our computer resource utilization layer uses Wang and Armstrong's (2009) method for mainly for memory, I/O and CPU time. Our case is urban-rural change detection in the Greater Montreal Area (5 time periods, 2006-2012, 100 virtual machines), 36,000km2 and varying from 0.6m to 38m resolution. We present a ground truthed accuracy assessment of a change matrix that is composed of 6 feature classes at 12 different spatio-temporal scales, and the performance of the change detection GCI for multi-scale LUCC study. The GCI allows us to extract and coordinate different types of changes by varying spatio-temporal scales from the big imagery datasets.

  14. Capacitance-based damage detection sensing for aerospace structural composites

    NASA Astrophysics Data System (ADS)

    Bahrami, P.; Yamamoto, N.; Chen, Y.; Manohara, H.

    2014-04-01

    Damage detection technology needs improvement for aerospace engineering application because detection within complex composite structures is difficult yet critical to avoid catastrophic failure. Damage detection is challenging in aerospace structures because not all the damage detection technology can cover the various defect types (delamination, fiber fracture, matrix crack etc.), or conditions (visibility, crack length size, etc.). These defect states are expected to become even more complex with future introduction of novel composites including nano-/microparticle reinforcement. Currently, non-destructive evaluation (NDE) methods with X-ray, ultrasound, or eddy current have good resolutions (< 0.1 mm), but their detection capabilities is limited by defect locations and orientations and require massive inspection devices. System health monitoring (SHM) methods are often paired with NDE technologies to signal out sensed damage, but their data collection and analysis currently requires excessive wiring and complex signal analysis. Here, we present a capacitance sensor-based, structural defect detection technology with improved sensing capability. Thin dielectric polymer layer is integrated as part of the structure; the defect in the structure directly alters the sensing layer's capacitance, allowing full-coverage sensing capability independent of defect size, orientation or location. In this work, capacitance-based sensing capability was experimentally demonstrated with a 2D sensing layer consisting of a dielectric layer sandwiched by electrodes. These sensing layers were applied on substrate surfaces. Surface indentation damage (~1mm diameter) and its location were detected through measured capacitance changes: 1 to 250 % depending on the substrates. The damage detection sensors are light weight, and they can be conformably coated and can be part of the composite structure. Therefore it is suitable for aerospace structures such as cryogenic tanks and rocket

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

    DOEpatents

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

    2010-01-05

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

  16. Urban area change detection procedures with remote sensing data

    NASA Technical Reports Server (NTRS)

    Maxwell, E. L. (Principal Investigator); Riordan, C. J.

    1980-01-01

    The underlying factors affecting the detection and identification of nonurban to urban land cover change using satellite data were studied. Computer programs were developed to create a digital scene and to simulate the effect of the sensor point spread function (PSF) on the transfer of modulation from the scene to an image of the scene. The theory behind the development of a digital filter representing the PSF is given as well as an example of its application. Atmospheric effects on modulation transfer are also discussed. A user's guide and program listings are given.

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

    SciTech Connect

    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.

  18. Student Concept Changes in Acids and Bases.

    ERIC Educational Resources Information Center

    Ye, Renmin; Wells, Raymond R.

    This study focuses on student concept changes in acids and bases. Variables include field dependent level, personal independence level, interest in science or chemistry, teaching strategy, and student gender. This study of Grade 10 students (N=81) provides information relevant to secondary school chemistry learning, teaching, and concept change.…

  19. Adversary phase change detection using SOMs and text data.

    SciTech Connect

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

    2010-05-01

    In this work, we developed a self-organizing map (SOM) technique for using web-based text analysis to forecast when a group is undergoing a phase change. By 'phase change', we mean that an organization has fundamentally shifted attitudes or behaviors. For instance, when ice melts into water, the characteristics of the substance change. A formerly peaceful group may suddenly adopt violence, or a violent organization may unexpectedly agree to a ceasefire. SOM techniques were used to analyze text obtained from organization postings on the world-wide web. Results suggest it may be possible to forecast phase changes, and determine if an example of writing can be attributed to a group of interest.

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

    NASA Astrophysics Data System (ADS)

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

    2013-05-01

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

  1. Human visual system-based smoking event detection

    NASA Astrophysics Data System (ADS)

    Odetallah, Amjad D.; Agaian, Sos S.

    2012-06-01

    Human action (e.g. smoking, eating, and phoning) analysis is an important task in various application domains like video surveillance, video retrieval, human-computer interaction systems, and so on. Smoke detection is a crucial task in many video surveillance applications and could have a great impact to raise the level of safety of urban areas, public parks, airplanes, hospitals, schools and others. The detection task is challenging since there is no prior knowledge about the object's shape, texture and color. In addition, its visual features will change under different lighting and weather conditions. This paper presents a new scheme of a system for detecting human smoking events, or small smoke, in a sequence of images. In developed system, motion detection and background subtraction are combined with motion-region-saving, skin-based image segmentation, and smoke-based image segmentation to capture potential smoke regions which are further analyzed to decide on the occurrence of smoking events. Experimental results show the effectiveness of the proposed approach. As well, the developed method is capable of detecting the small smoking events of uncertain actions with various cigarette sizes, colors, and shapes.

  2. An Approach to Alleviate the False Alarm in Building Change Detection from Urban Vhr Image

    NASA Astrophysics Data System (ADS)

    Chen, J.; Hou, J. L.; Deng, M.

    2016-06-01

    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.

  3. Biological agent detection based on principal component analysis

    NASA Astrophysics Data System (ADS)

    Mudigonda, Naga R.; Kacelenga, Ray

    2006-05-01

    This paper presents an algorithm, based on principal component analysis for the detection of biological threats using General Dynamics Canada's 4WARN Sentry 3000 biodetection system. The proposed method employs a statistical method for estimating background biological activity so as to make the algorithm adaptive to varying background situations. The method attempts to characterize the pattern of change that occurs in the fluorescent particle counts distribution and uses the information to suppress false-alarms. The performance of the method was evaluated using a total of 68 tests including 51 releases of Bacillus Globigii (BG), six releases of BG in the presence of obscurants, six releases of obscurants only, and five releases of ovalbumin at the Ambient Breeze Tunnel Test facility, Battelle, OH. The peak one-minute average concentration of BG used in the tests ranged from 10 - 65 Agent Containing Particles per Liter of Air (ACPLA). The obscurants used in the tests included diesel smoke, white grenade smoke, and salt solution. The method successfully detected BG at a sensitivity of 10 ACPLA and resulted in an overall probability of detection of 94% for BG without generating any false-alarms for obscurants at a detection threshold of 0.6 on a scale of 0 to 1. Also, the method successfully detected BG in the presence of diesel smoke and salt water fumes. The system successfully responded to all the five ovalbumin releases with noticeable trends in algorithm output and alarmed for two releases at the selected detection threshold.

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

    NASA Astrophysics Data System (ADS)

    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

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

    NASA Astrophysics Data System (ADS)

    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.

  6. PDM-16QAM vector signal generation and detection based on intensity modulation and direct detection

    NASA Astrophysics Data System (ADS)

    Chen, Long; Yu, Jianjun; Li, Xinying

    2016-07-01

    We experimentally demonstrate a novel and simple method to generate and detect high speed polarization-division-multiplexing 16-ary quadrature-amplitude-modulation (PDM-16QAM) vector signal enabled by Mach-Zehnder modulator-based (MZM-based) optical-carrier-suppression (OCS) intensity modulation and direct detection. Due to the adoption of OCS intensity modulation, carrier beating can be avoided at the receiver, and thus polarization de-multiplexing can be implemented by digital-signal-processing-based (DSP-based) cascaded multi-modulus algorithm (CMMA) equalization instead of a polarization tracking system. The change of both amplitude and phase information due to the adoption of OCS modulation can be equalized by DSP-based amplitude and phase precoding at the transmitter. Up to 64-Gb/s PDM-16QAM vector signal is generated and detected after 2-km single-mode fiber-28 (SMF-28) or 20-km large-effective-area fiber (LEAF) transmission with a bit-error-ratio (BER) less than the hard-decision forward-error-correction (HD-FEC) threshold of 3.8×10-3.

  7. Detecting Climate Change and Its Impacts on Crop Yield in the Continental United States

    NASA Astrophysics Data System (ADS)

    Ge, Y.; Cai, X.

    2012-12-01

    Climatic variables, temperature and precipitation in particular, play critical roles in crop growth. Changes in climate, i.e., the change of mean and/or variance in climatic time series have brought up concerns for agriculture. Detecting past climate change and its impact is essential to understand the causes on what have already occurred. This study uses a novel change point detection method, which is based on Bayesian local posterior density and Pettitt test to detect multiple change points in a given time series, and to classify change patterns (graduate and step change) based on the final posterior probability density. The detection method is then applied to the United States Historical Climate Network (USHCN) covering thousands of sites; the change patterns of precipitation, and maximum, average and minimum temperature in crop growing periods and growing years are examined in details. The impacts of the identified climate changes on the yield of grain corn in the US are assessed. A regression model with climate variables is developed to model crop yield responses to the climate since 1970. Through various testing scenarios, it is found that the impacts of climate change on corn yield vary by region (Figure 1), temperature component (minimum, maximum or average), time periods for the assessment (crop growing period or year), and irrigated and rainfed crops. The change in minimum temperature has the largest impact on the gross corn yield over the Continental U.S among those climate variables; warming of maximum temperature boosts the gross corn yield, while warming of average temperature and minimum temperature slows it. In the Midwest, precipitation change has much larger impact on rainfed than on irrigated corn, which shows an evidence of irrigation adaptation to climate change in the region. Figure 1 shows the estimated impact of minimum temperature change (mean monthly minimum daily temperature in the growing season) in the growing season during 1970-2010 on

  8. Onboard Data Processor for Change-Detection Radar Imaging

    NASA Technical Reports Server (NTRS)

    Lou, Yunling; Muellerschoen, Ronald J.; Chien, Steve A.; Saatchi, Sasan S.; Clark, Duane

    2008-01-01

    A computer system denoted a change-detection onboard processor (CDOP) is being developed as a means of processing the digitized output of a synthetic-aperture radar (SAR) apparatus aboard an aircraft or spacecraft to generate images showing changes that have occurred in the terrain below between repeat passes of the aircraft or spacecraft over the terrain. When fully developed, the CDOP is intended to be capable of generating SAR images and/or SAR differential interferograms in nearly real time. The CDOP is expected to be especially useful for understanding some large-scale natural phenomena and/or mitigating natural hazards: For example, it could be used for near-real-time observation of surface changes caused by floods, landslides, forest fires, volcanic eruptions, earthquakes, glaciers, and sea ice movements. It could also be used to observe such longer-term surface changes as those associated with growth of vegetation (relevant to estimation of wildfire fuel loads). The CDOP is, essentially, an interferometric SAR processor designed to operate aboard a radar platform.

  9. Fusion techniques using distributed Kalman filtering for detecting changes in systems

    NASA Technical Reports Server (NTRS)

    Belcastro, Celeste M.; Fischl, Robert; Kam, Moshe

    1991-01-01

    A comparison is made of the performances of two detection strategies that are based on different data fusion techniques. The strategies detect changes in a linear system. One detection strategy involves combining the estimates and error covariance matrices of distributed Kalman filters, generating a residual from the used estimates, comparing this residual to a threshold, and making a decision. The other detection strategy involves a distributed decision process in which estimates from distributed Kalman filters are used to generate distributed residuals which are compared locally to a threshold. Local decisions are made and these decisions are then fused into a global decision. The performances of each of these detection schemes are compared, and it is concluded that better performance is achieved when local decisions are made and then fused into a global decision.

  10. Illumination robust change detection with CMOS imaging sensors

    NASA Astrophysics Data System (ADS)

    Rengarajan, Vijay; Gupta, Sheetal B.; Rajagopalan, A. N.; Seetharaman, Guna

    2015-05-01

    Change detection between two images in the presence of degradations is an important problem in the computer vision community, more so for the aerial scenario which is particularly challenging. Cameras mounted on moving platforms such as aircrafts or drones are subject to general six-dimensional motion as the motion is not restricted to a single plane. With CMOS cameras increasingly in vogue due to their low power consumption, the inevitability of rolling-shutter (RS) effect adds to the challenge. This is caused by sequential exposure of rows in CMOS cameras unlike conventional global shutter cameras where all pixels are exposed simultaneously. The RS effect is particularly pronounced in aerial imaging since each row of the imaging sensor is likely to experience a different motion. For fast-moving platforms, the problem is further compounded since the rows are also affected by motion blur. Moreover, since the two images are shot at different times, illumination differences are common. In this paper, we propose a unified computational framework that elegantly exploits the scarcity constraint to deal with the problem of change detection in images degraded by RS effect, motion blur as well as non-global illumination differences. We formulate an optimization problem where each row of the distorted image is approximated as a weighted sum of the corresponding rows in warped versions of the reference image due to camera motion within the exposure period to account for geometric as well as photometric differences. The method has been validated on both synthetic and real data.

  11. Managing and reviewing evidence-based changes.

    PubMed

    Carter, Helen; Price, Lynda

    Nurses lead many projects to manage change aimed at improving patient safety and care. This two-part series offers practical guidance on how to bring about an evidence-based change in practice, and how to demonstrate the success, or otherwise, of that change. Part 2 is concerned with discovering why the practice is falling short, how to implement improvements and measure the effect of the changes. It also highlights ways in which nurses can use their work as part of the revalidation process. PMID:27089753

  12. Detecting floodplain inundation based on the upstream-downstream relationship

    NASA Astrophysics Data System (ADS)

    Zhao, Tongtiegang; Shao, Quanxi

    2015-11-01

    The rise in river stage (water depth) can lead to disastrous floodplain inundation. On the basis of hydraulic simulation data, this study proposes novel data-analytical methods to infer the threshold river stage and detect floodplain inundation. A quasi-Muskingum model is derived from the classical Muskingum model to characterise the relationship between upstream and downstream river stages. Based on this model, F-test and modified Akaike information criterion AICc are introduced to test if there is a change of the upstream-downstream relationship. Furthermore, a bootstrap-based calibration-validation experiment is set up to evaluate the performance of the quasi-Muskingum model. The proposed methods are applied to a case study of the 1991 and 2001 floods in the Flinders and Norman Rivers in Northern Australia. The results show that floodplain inundation does change the upstream-downstream relationship as it drastically alters the stage-discharge relationship. To combine the quasi-Muskingum model with F-test and AICc facilitates an efficient approach to detect the change and infer the threshold river stage. The analytical testing is in concert with visual examination - the time when the river stage becomes higher than the detected threshold coincides with the beginning of floodplain inundation. Despite the change, the quasi-Muskingum model effectively captures the upstream-downstream relationship and requires a small number of samples in calibration. This study highlights the effectiveness of the data-analytical methods in dealing with the change of the upstream-downstream relationship.

  13. Volumetric Forest Change Detection Through Vhr Satellite Imagery

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

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

    PubMed

    Hou, Bin; Wang, Yunhong; Liu, Qingjie

    2016-01-01

    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. PMID:27618903

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

    USGS Publications Warehouse

    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

  16. Change detection for hyperspectral sensing in a transformed low-dimensional space

    SciTech Connect

    Foy, Bernard R; Theiler, James

    2010-01-01

    We present an approach to the problem of change in hyperspectral imagery that operates in a two-dimensional space. The coordinates in the space are related to Mahalanobis distances for the combined ('stacked') data and the individual hyperspectral scenes. Although it is only two-dimensional, this space is rich enough to include several well-known change detection algorithms, including the hyperbolic anomalous change detector, based on Gaussian scene clutter, and the EC-uncorrelated detector based on heavy-tailed (elliptically contoured) clutter. Because this space is only two-dimensional, adaptive machine learning methods can produce new change detectors without being stymied by the curse of dimensionality. We investigate, in particular, the utility of the support vector machine for learning boundaries in this 2-D space, and compare the performance of the resulting nonlinearly adaptjve detector to change detectors that have themselves shown good performance.

  17. Detection of Deforestation and Land Conversion in Rondonia, Brazil Using Change Detection Techniques

    NASA Technical Reports Server (NTRS)

    Guild, Liane S.; Cohen, Warren B,; Kauffman, J. Boone; Peterson, David L. (Technical Monitor)

    2001-01-01

    Fires associated with tropical deforestation, land conversion, and land use greatly contribute to emissions as well as the depletion of carbon and nutrient pools. The objective of this research was to compare change detection techniques for identifying deforestation and cattle pasture formation during a period of early colonization and agricultural expansion in the vicinity of Jamari, Rond6nia. Multi-date Landsat Thematic Mapper (TM) data between 1984 and 1992 was examined in a 94 370-ha area of active deforestation to map land cover change. The Tasseled Cap (TC) transformation was used to enhance the contrast between forest, cleared areas, and regrowth. TC images were stacked into a composite multi-date TC and used in a principal components (PC) transformation to identify change components. In addition, consecutive TC image pairs were differenced and stacked into a composite multi-date differenced image. A maximum likelihood classification of each image composite was compared for identification of land cover change. The multi-date TC composite classification had the best accuracy of 78.1% (kappa). By 1984, only 5% of the study area had been cleared, but by 1992, 11% of the area had been deforested, primarily for pasture and 7% lost due to hydroelectric dam flooding. Finally, discrimination of pasture versus cultivation was improved due to the ability to detect land under sustained clearing opened to land exhibiting regrowth with infrequent clearing.

  18. Land Cover Change Detection from MODIS Vegetation Index Time Series Data

    NASA Astrophysics Data System (ADS)

    Mithal, V.; O'Connor, Z.; Steinhaeuser, K.; Boriah, S.; Kumar, V.; Potter, C. S.; Klooster, S. A.

    2012-12-01

    Quantifiable knowledge about changes occurring in land cover and land use at a global scale is key to effective planning for sustainable use of diminishing natural resources such as forest cover and agricultural land. Accurate and timely information about land cover and land use changes is therefore of significant interest to earth and climate scientists as well as policy and decision makers. Recently, global time series data sets, such as Moderate Resolution Imaging Spectroradiometer Enhanced Vegetation Index (EVI), have become publicly available and have been used to identify changes in vegetation cover. In this talk, we will discuss our work that analyzes the MODIS EVI time series data sets for global land cover change detection. Our group has developed a suite of time series change detection methods that are used to identify EVI time series with patterns indicative of land cover disturbance such as abrupt or gradual change, or changes in the recurring annual vegetation pattern. These algorithms can successfully identify different land cover change events such as deforestation, forest fires, agricultural conversions, and degradation due to insect damage at a global scale. In context of land cover monitoring, one of the significant challenges is posed by the differences in inter-annual variability and noise characteristics of different land cover types. These data characteristics can significantly impact change detection performance especially in land cover types such as farms, grasslands and tropical forests. We will discuss our recent work that incorporates a bootstrap-based normalization of change detection scores to account for the natural variability present in vegetation time series data. We studied the strengths and weakness of our proposed normalizing approaches in the context of characteristics of land cover data such as seasonality and noise and showed that relative performance of normalization approaches vary significantly depending on the

  19. Comic image understanding based on polygon detection

    NASA Astrophysics Data System (ADS)

    Li, Luyuan; Wang, Yongtao; Tang, Zhi; Liu, Dong

    2013-01-01

    Comic image understanding aims to automatically decompose scanned comic page images into storyboards and then identify the reading order of them, which is the key technique to produce digital comic documents that are suitable for reading on mobile devices. In this paper, we propose a novel comic image understanding method based on polygon detection. First, we segment a comic page images into storyboards by finding the polygonal enclosing box of each storyboard. Then, each storyboard can be represented by a polygon, and the reading order of them is determined by analyzing the relative geometric relationship between each pair of polygons. The proposed method is tested on 2000 comic images from ten printed comic series, and the experimental results demonstrate that it works well on different types of comic images.

  20. Texture-Based Polyp Detection in Colonoscopy

    NASA Astrophysics Data System (ADS)

    Ameling, Stefan; Wirth, Stephan; Paulus, Dietrich; Lacey, Gerard; Vilarino, Fernando

    Colonoscopy is one of the best methods for screening colon cancer. A variety of research groups have proposed methods for automatic detection of polyps in colonoscopic images to support the doctors during examination. However, the problem can still not be assumed as solved. The major drawback of many approaches is the amount and quality of images used for classifier training and evaluation. Our database consists of more than four hours of high resolution video from colonoscopies which were examined and labeled by medical experts. We applied four methods of texture feature extraction based on Grey-Level-Co-occurence and Local-Binary-Patterns. Using this data, we achieved classification results with an area under the ROC-curve of up to 0.96.

  1. Low complexity pixel-based halftone detection

    NASA Astrophysics Data System (ADS)

    Ok, Jiheon; Han, Seong Wook; Jarno, Mielikainen; Lee, Chulhee

    2011-10-01

    With the rapid advances of the internet and other multimedia technologies, the digital document market has been growing steadily. Since most digital images use halftone technologies, quality degradation occurs when one tries to scan and reprint them. Therefore, it is necessary to extract the halftone areas to produce high quality printing. In this paper, we propose a low complexity pixel-based halftone detection algorithm. For each pixel, we considered a surrounding block. If the block contained any flat background regions, text, thin lines, or continuous or non-homogeneous regions, the pixel was classified as a non-halftone pixel. After excluding those non-halftone pixels, the remaining pixels were considered to be halftone pixels. Finally, documents were classified as pictures or photo documents by calculating the halftone pixel ratio. The proposed algorithm proved to be memory-efficient and required low computation costs. The proposed algorithm was easily implemented using GPU.

  2. Detecting Soft Errors in Stencil based Computations

    SciTech Connect

    Sharma, V.; Gopalkrishnan, G.; Bronevetsky, G.

    2015-05-06

    Given the growing emphasis on system resilience, it is important to develop software-level error detectors that help trap hardware-level faults with reasonable accuracy while minimizing false alarms as well as the performance overhead introduced. We present a technique that approaches this idea by taking stencil computations as our target, and synthesizing detectors based on machine learning. In particular, we employ linear regression to generate computationally inexpensive models which form the basis for error detection. Our technique has been incorporated into a new open-source library called SORREL. In addition to reporting encouraging experimental results, we demonstrate techniques that help reduce the size of training data. We also discuss the efficacy of various detectors synthesized, as well as our future plans.

  3. [Digital subtraction radiography for the detection of periodontal bone changes].

    PubMed

    Mera, T

    1989-03-01

    This study was performed to evaluate the efficacy of digital subtraction radiography in detecting alveolar bone changes. In order to test the sensitivity of quantitative evaluation by subtraction radiography, a copper equivalent thickness obtained from digitized radiographs was compared with the actual mineral content of bone phantoms with 15 different minerals and 25 bone specimens. Results demonstrated that the copper equivalent thickness correlated well with the actual mineral content (bone phantoms: gamma s = 1.0, bone specimens: gamma s = 0.985). In order to test the ability of digitized subtraction radiography in assessing alveolar bone changes in vivo, subtraction images were compared with histological features. The experimental angular bony defects were treated with conservative periodontal therapy in 3 monkeys. The standardized radiographs were taken longitudinally after therapy, and subtraction images were made from the sequentially obtained radiographs. In addition, for fluorescent histomorphometrical evaluations of new bone formations, the animals were dosed with oxytetracycline, calsein solution and arizarin complex solution. Radiographic and histological evaluations were scheduled to provide healing periods of 2, 3, 4, 5, 6 and 9 weeks after periodontal therapy. Subtraction radiography offered an objective method to follow histological changes of alveolar bone, and the copper equivalent thickness obtained from subtraction radiographs correlated with the histometric bone volume (gamma s = 0.9023, p less than 0.01). The results of these studies indicated that subtraction radiography was useful in monitoring alveolar bone changes associated with periodontal disease and treatment and that the quanitative measurement of periodontal bone changes by subtraction radiography was feasible. PMID:2517790

  4. [Vegetation change in Shenzhen City based on NDVI change classification].

    PubMed

    Li, Yi-Jing; Zeng, Hui; Wel, Jian-Bing

    2008-05-01

    Based on the TM images of 1988 and 2003 as well as the land-use change survey data in 2004, the vegetation change in Shenzhen City was assessed by a NDVI (normalized difference vegetation index) change classification method, and the impacts from natural and social constraining factors were analyzed. The results showed that as a whole, the rapid urbanization in 1988-2003 had less impact on the vegetation cover in the City, but in its plain areas with low altitude, the vegetation cover degraded more obviously. The main causes of the localized ecological degradation were the invasion of built-ups to woods and orchards, land transformation from woods to orchards at the altitude of above 100 m, and low percentage of green land in some built-ups areas. In the future, the protection and construction of vegetation in Shenzhen should focus on strengthening the protection and restoration of remnant woods, trying to avoid the built-ups' expansion to woods and orchards where are better vegetation-covered, rectifying the unreasonable orchard constructions at the altitude of above 100 m, and consolidating the greenbelt construction inside the built-ups. It was considered that the NDVI change classification method could work well in efficiently uncovering the trend of macroscale vegetation change, and avoiding the effect of random noise in data. PMID:18655594

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

    PubMed

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

    2016-01-01

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

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

    PubMed Central

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

    2016-01-01

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

  7. Change Detection Module for New Orleans City of USA Using

    NASA Astrophysics Data System (ADS)

    Singh, Dharmendra

    accuracy. The New Orleans city of USA is taken as study area because this is reported that this city is shrinking. RADARSAT SLC (Single look complex) images acquired from January 2002 to March 2007 were obtained for the study area. Image pairs with perpendicular baselines less than 100 km are chosen. Selection of suitable image pairs is crucial since baseline distance between them affects the altitude ambiguity in resultant change detection map. Coherence is computed for the image pairs. If the coherence is greater than 0.25, such image pairs are considered for further analysis. Three pass differential InSAR is used for the analysis of change detection. Images 1 and 2 of the study area with lesser temporal span (minimum of 24 day interval) is chosen to make a digital elevation model and then images 1 and 3 of the same area with one year of temporal span is chosen to make an interferogram. The topographic phase estimated with images 1 and 2 is then subtracted to make a differential interferogram showing change from image 2 to 3. Image pairs with approximately one month temporal span, are considered for generating interferogram. Changes occurred in every one year is measured by subtracting topographic phase of the year corresponding to master image, from interferogram. From the change detection map obtained from both methods show that areas of larger changes are identified near Lake Borgne, and in the boundaries of Mississippi river. Lake Borgne is reported to be identified as an area of major land subsidence as found by other studies also. On comparing our result with this interferometric study, it is found that both are showing some common regions with high changes near water bodies. Surface deformation can be monitored quantitatively in the scale of mm with the help of temporal analysis of D-InSAR.

  8. Trend Estimation and Change Point Detection in Climatic Series

    NASA Astrophysics Data System (ADS)

    Bates, B. C.; Chandler, R. E.

    2011-12-01

    The problems of trend estimation and change point detection in climatic series have received substantial attention in recent years. Key issues include the magnitudes and directions of underlying trends, and the existence (or otherwise) of abrupt shifts in the mean background state. There are many procedures in use including: t-tests, Mann-Whitney and Pettit tests, linear and piecewise linear regression; cumulative sum analysis; hierarchical Bayesian change point analysis; Markov chain Monte Carlo methods; and reversible jump Markov chain Monte Carlo. The purpose of our presentation is to motivate wider use of modern regression techniques for trend estimation and change point detection in climatic series. We pay particular attention to the underlying statistical assumptions as their violation can lead to serious errors in data interpretation and study conclusions. In this context we consider two case studies. The first involves the application of local linear regression and a test for discontinuities in the regression function to the winter (December-March) North Atlantic Oscillation (NAO) index series for the period 1864-2010. This series exhibits a reversal from strongly negative values in the late 1960s to strongly positive NAO index values in the mid-1990s. The second involves the analysis of a seasonal (June to October) series of typhoon counts in the vicinity of Taiwan for the period 1970-2006. A previous investigation by other researchers concluded that an abrupt shift in this series occurred between 1999 and 2000. For both case studies, our findings indicate little evidence for abrupt shifts: rather, the decadal to multidecadal changes in the mean levels of both series appear well described by smooth trends. For the winter NAO index series, the trend is non-monotonic; for the typhoon counts, it can be regarded as linear on the square root scale. Our statistical results do not contradict those obtained by other researchers: our interpretation of these results

  9. SPRi-based adenovirus detection using a surrogate antibody method.

    PubMed

    Abadian, Pegah N; Yildirim, Nimet; Gu, April Z; Goluch, Edgar D

    2015-12-15

    Adenovirus infection, which is a waterborne viral disease, is one of the most prevelant causes of human morbidity in the world. Thus, methods for rapid detection of this infectious virus in the environment are urgently needed for public health protection. In this study, we developed a rapid, real-time, sensitive, and label-free SPRi-based biosensor for rapid, sensitive and highly selective detection of adenoviruses. The sensing protocol consists of mixing the sample containing adenovirus with a predetermined concentration of adenovirus antibody. The mixture was filtered to remove the free antibodies from the sample. A secondary antibody, which was specific to the adenovirus antibody, was immobilized onto the SPRi chip surface covalently and the filtrate was flowed over the sensor surface. When the free adenovirus antibodies bound to the surface-immobilized secondary antibodies, we observed this binding via changes in reflectivity. In this approach, a higher amount of adenoviruses resulted in fewer free adenovirus antibodies and thus smaller reflectivity changes. A dose-response curve was generated, and the linear detection range was determined to be from 10 PFU/mL to 5000 PFU/mL with an R(2) value greater than 0.9. The results also showed that the developed biosensing system had a high specificity towards adenovirus (less than 20% signal change when tested in a sample matrix containing rotavirus and lentivirus). PMID:26232675

  10. Longitudinal change detection in diffusion MRI using multivariate statistical testing on tensors.

    PubMed

    Grigis, Antoine; Noblet, Vincent; Heitz, Fabrice; Blanc, Frédéric; de Sèze, Jérome; Kremer, Stéphane; Rumbach, Lucien; Armspach, Jean-Paul

    2012-05-01

    This paper presents a longitudinal change detection framework for detecting relevant modifications in diffusion MRI, with application to neuromyelitis optica (NMO) and multiple sclerosis (MS). The core problem is to identify image regions that are significantly different between two scans. The proposed method is based on multivariate statistical testing which was initially introduced for tensor population comparison. We use this method in the context of longitudinal change detection by considering several strategies to build sets of tensors characterizing the variability of each voxel. These strategies make use of the variability existing in the diffusion weighted images (thanks to a bootstrap procedure), or in the spatial neighborhood of the considered voxel, or a combination of both. Results on synthetic evolutions and on real data are presented. Interestingly, experiments on NMO patients highlight the ability of the proposed approach to detect changes in the normal-appearing white matter (according to conventional MRI) that are related with physical status outcome. Experiments on MS patients highlight the ability of the proposed approach to detect changes in evolving and non-evolving lesions (according to conventional MRI). These findings might open promising prospects for the follow-up of NMO and MS pathologies. PMID:22387171

  11. Effect of projective viewpoint in detecting temporal density changes

    NASA Astrophysics Data System (ADS)

    Raundahl, Jakob; Nielsen, Mads; Olsen, Ole F.; Bagger, Yu Z.

    2004-05-01

    An important question in mammographic image analysis is the importance of the projected view of the breast. Can temporal changes in density be detected equally well using either one of the commonly available views Medio-Lateral (ML) and Cranio-Caudal (CC) or a combination of the two? Two sets of mammograms of 50 patients in a double-blind, placebo controlled hormone replacement therapy (HRT) experiment were used. One set of ML and CC view from 1999 and one from 2001. HRT increases density which means that the degree of separation of the populations (one group receiving HRT and the other placebo) can be used as a measure of how much density change information is carried in a particular view or combination of views. Earlier results have shown a high correlation between CC and ML views leading to the conclusion that only one of them is needed for density assessment purposes. A similar high correlation coefficient was observed in this study (0.85), while the correlation between changes was a bit lower (0.71). Using both views to separate the patients receiving hormones from the ones receiving placebo increased the area under corresponding ROC curves from 0.76 +/- 0.04 to 0.79 +/- 0.04.

  12. An area change detection method of remote sensing image using historical land use graph

    NASA Astrophysics Data System (ADS)

    Li, Xiangjun; Deng, Xiaolian; Niu, Zheng; Ye, Famao

    2005-11-01

    Kinds of historical vector graphs have been gradually accumulated by ground truth data or other reliable sources, but these data have not been fully adopted to detect change in remote sensing circle. In this paper we describe a novel change detection method. The key feature of the new method is the use of a piece of historical land using vector graph. By combing one satellite image and the vector graph after necessary geometric rectification, we could detect change region of the satellite image corresponding to patches in the vector graph. Through adopting coefficient of part change and coefficient of entire change, the study calculates statistics indexes of image corresponding to patches of vector graph with different coefficient groups and assesses the computing results by kappa matrix. According to analytical results, the coefficient of entire change is more important to the number of commission error than the coefficient of part change. This method is benefit to the reuse of historical vector graphs. As the image-processing work of this method is based on patches of historical vector graph, it helps to the development of different vector graphs.

  13. Lunar Crescent Detection Based on Image Processing Algorithms

    NASA Astrophysics Data System (ADS)

    Fakhar, Mostafa; Moalem, Peyman; Badri, Mohamad Ali

    2014-11-01

    For many years lunar crescent visibility has been studied by many astronomers. Different criteria have been used to predict and evaluate the visibility status of new Moon crescents. Powerful equipment such as telescopes and binoculars have changed capability of observations. Most of conventional statistical criteria made wrong predictions when new observations (based on modern equipment) were reported. In order to verify such reports and modify criteria, not only previous statistical parameters should be considered but also some new and effective parameters like high magnification, contour effect, low signal to noise, eyestrain and weather conditions should be viewed. In this paper a new method is presented for lunar crescent detection based on processing of lunar crescent images. The method includes two main steps, first, an image processing algorithm that improves signal to noise ratio and detects lunar crescents based on circular Hough transform (CHT). Second using an algorithm based on image histogram processing to detect the crescent visually. Final decision is made by comparing the results of visual and CHT algorithms. In order to evaluate the proposed method, a database, including 31 images are tested. The illustrated method can distinguish and extract the crescent that even the eye can't recognize. Proposed method significantly reduces artifacts, increases SNR and can be used easily by both groups astronomers and who want to develop a new criterion as a reliable method to verify empirical observation.

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

    USGS Publications Warehouse

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

    2009-01-01

    This article applies formal detection and attribution techniques to investigate the nature of observed shifts in the timing of streamflow in the western United States. Previous studies have shown that the snow hydrology of the western United States has changed in the second half of the twentieth century. Such changes manifest themselves in the form of more rain and less snow, in reductions in the snow water contents, and in earlier snowmelt and associated advances in streamflow "center" timing (the day in the "water-year" on average when half the water-year flow at a point has passed). However, with one exception over a more limited domain, no other study has attempted to formally attribute these changes to anthropogenic increases of greenhouse gases in the atmosphere. Using the observations together with a set of global climate model simulations and a hydrologic model (applied to three major hydrological regions of the western United States_the California region, the upper Colorado River basin, and the Columbia River basin), it is found that the observed trends toward earlier "center" timing of snowmelt-driven streamflows in the western United States since 1950 are detectably different from natural variability (significant at the p < 0.05 level). Furthermore, the nonnatural parts of these changes can be attributed confidently to climate changes induced by anthropogenic greenhouse gases, aerosols, ozone, and land use. The signal from the Columbia dominates the analysis, and it is the only basin that showed a detectable signal when the analysis was performed on individual basins. It should be noted that although climate change is an important signal, other climatic processes have also contributed to the hydrologic variability of large basins in the western United States. ?? 2009 American Meteorological Society.

  15. Change detection for Finnish CORINE land cover classification

    NASA Astrophysics Data System (ADS)

    Törmä, Markus; Härmä, Pekka; Hatunen, Suvi; Teiniranta, Riitta; Kallio, Minna; Järvenpää, Elise

    2011-11-01

    This paper describes the ideas, data and methods to produce Finnish Corine Land Cover 2006 (CLC2006) classification. This version is based on use of existing national GIS data and satellite images and their automated processing, instead of visual interpretation of satellite images. The main idea is that land use information is based on GIS datasets and land cover information interpretation of satellite images. Because Finland participated to CLC2000-project, also changes between years 2000 and 2006 are determined. Finnish approach is good example how national GIS data is used to produce data fulfilling European needs in bottom-up fashion.

  16. Shoreline Delineation and Land Reclamation Change Detection Using Landsat Image

    NASA Astrophysics Data System (ADS)

    Rosli, M. I.; Ahmad, M. A.; Kaamin, M.; Izhar, M. F. N.

    2016-07-01

    This study is conducted on the usage of remote sensing images from several different years in order to analyze the changes of shoreline and land cover of the area. Remote sensing images used in this study are the data captured by the Landsat satellite. The images are projecting the land surface in 30 by 30 meter resolution and it is processed by the ENVI software. ENVI is able to change each digital number of the pixels on the images into specific value according to the applied model for classification in which could be used as an approach in calculating the area different classes based from the images itself. Therefore, using this method, the changes on the coastal area are possible to be determined. Analysis of the shoreline and land reclamation around the coastal area is integrated with the land use changes to determine its impact. The study shows that Batu Pahat area might have undergone land reclamation whereas in Pasir Gudang is experiencing substantial amount of erosion. Besides, the changes of land use in both areas were considered to be rapid and due to the results obtained from this study, the issues may be brought about for the local authority awareness action.

  17. Updating Landsat-derived land-cover maps using change detection and masking techniques

    NASA Technical Reports Server (NTRS)

    Likens, W.; Maw, K.

    1982-01-01

    The California Integrated Remote Sensing System's San Bernardino County Project was devised to study the utilization of a data base at a number of jurisdictional levels. The present paper discusses the implementation of change-detection and masking techniques in the updating of Landsat-derived land-cover maps. A baseline landcover classification was first created from a 1976 image, then the adjusted 1976 image was compared with a 1979 scene by the techniques of (1) multidate image classification, (2) difference image-distribution tails thresholding, (3) difference image classification, and (4) multi-dimensional chi-square analysis of a difference image. The union of the results of methods 1, 3 and 4 was used to create a mask of possible change areas between 1976 and 1979, which served to limit analysis of the update image and reduce comparison errors in unchanged areas. The techniques of spatial smoothing of change-detection products, and of combining results of difference change-detection algorithms are also shown to improve Landsat change-detection accuracies.

  18. Stimulus change detection in phasic auditory units in the frog midbrain: frequency and ear specific adaptation

    PubMed Central

    Ponnath, Abhilash; Hoke, Kim L.

    2013-01-01

    Neural adaptation, a reduction in the response to a maintained stimulus, is an important mechanism for detecting stimulus change. Contributing to change detection is the fact that adaptation is often stimulus specific: adaptation to a particular stimulus reduces excitability to a specific subset of stimuli, while the ability to respond to other stimuli is unaffected. Phasic cells (e.g., cells responding to stimulus onset) are good candidates for detecting the most rapid changes in natural auditory scenes, as they exhibit fast and complete adaptation to an initial stimulus presentation. We made recordings of single phasic auditory units in the frog midbrain to determine if adaptation was specific to stimulus frequency and ear of input. In response to an instantaneous frequency step in a tone, 28 % of phasic cells exhibited frequency specific adaptation based on a relative frequency change (delta-f = ±16 %). Frequency specific adaptation was not limited to frequency steps, however, as adaptation was also overcome during continuous frequency modulated stimuli and in response to spectral transients interrupting tones. The results suggest that adaptation is separated for peripheral (e.g., frequency) channels. This was tested directly using dichotic stimuli. In 45 % of binaural phasic units, adaptation was ear specific: adaptation to stimulation of one ear did not affect responses to stimulation of the other ear. Thus, adaptation exhibited specificity for stimulus frequency and lateralization at the level of the midbrain. This mechanism could be employed to detect rapid stimulus change within and between sound sources in complex acoustic environments. PMID:23344947

  19. A New Change Detection Technique Applied to COSMO-SkyMed Stripmap Himage Data

    NASA Astrophysics Data System (ADS)

    Losurdo, A.; Marzo, C.; Guariglia, A.

    2015-05-01

    Change Detection techniques in SAR images is very relevant for the locationing and the monitoring of interesting land changes. At present, it is a very important topic due to the high repetitiveness and of the new SAR satellite instruments (e.g. COSMO-SkyMed and Sentinel-1). Geocart S.p.A. has reached important results about SAR change detection techniques within a technological project designed and implemented for the Italian Space Agency. The project's title is Integrated Monitoring System: application to the GAS pipeline". The aim of the project is the development of a new remote sensing service integrating aerial and satellite data for GAS pipeline monitoring. An important Work-Package of the project aims to develop algorithms regarding the change detection to be applied on COSMO-SkyMed Stripmap Himage data in order to identify heavy lorries on pipelines. Particularly, the paper presents a new change detection technique based on a probabilistic approach and the corresponding applicative results.

  20. APTAMER-BASED SERRS SENSOR FOR THROMBIN DETECTION

    SciTech Connect

    Cho, H; Baker, B R; Wachsmann-Hogiu, S; Pagba, C V; Laurence, T A; Lane, S M; Lee, L P; Tok, J B

    2008-07-02

    We describe an aptamer-based Surface Enhanced Resonance Raman Scattering (SERRS) sensor with high sensitivity, specificity, and stability for the detection of a coagulation protein, human a-thrombin. The sensor achieves high sensitivity and a limit of detection of 100 pM by monitoring the SERRS signal change upon the single step of thrombin binding to immobilized thrombin binding aptamer. The selectivity of the sensor is demonstrated by the specific discrimination of thrombin from other protein analytes. The specific recognition and binding of thrombin by the thrombin binding aptamer is essential to the mechanism of the aptamer-based sensor, as shown through measurements using negative control oligonucleotides. In addition, the sensor can detect 1 nM thrombin in the presence of complex biofluids, such as 10% fetal calf serum, demonstrating that the immobilized, 5{prime}-capped, 3{prime}-capped aptamer is sufficiently robust for clinical diagnostic applications. Furthermore, the proposed sensor may be implemented for multiplexed detection using different aptamer-Raman probe complexes.

  1. Aptamer-based SERRS sensor for thrombin detection.

    PubMed

    Cho, Hansang; Baker, Brian R; Wachsmann-Hogiu, Sebastian; Pagba, Cynthia V; Laurence, Ted A; Lane, Stephen M; Lee, Luke P; Tok, Jeffrey B H

    2008-12-01

    We describe an aptamer-based surface enhanced resonance Raman scattering (SERRS) sensor with high sensitivity, specificity, and stability for the detection of a coagulation protein, human alpha-thrombin. The sensor achieves high sensitivity and a limit of detection of 100 pM by monitoring the SERRS signal change upon the single-step of thrombin binding to immobilized thrombin binding aptamer. The selectivity of the sensor is demonstrated by the specific discrimination of thrombin from other protein analytes. The specific recognition and binding of thrombin by the thrombin binding aptamer is essential to the mechanism of the aptamer-based sensor, as shown through measurements using negative control oligonucleotides. In addition, the sensor can detect 1 nM thrombin in the presence of complex biofluids, such as 10% fetal calf serum, demonstrating that the immobilized, 5'-capped, 3'-capped aptamer is sufficiently robust for clinical diagnostic applications. Furthermore, the proposed sensor may be implemented for multiplexed detection using different aptamer-Raman probe complexes. PMID:19367849

  2. Change Detection of Mobile LIDAR Data Using Cloud Computing

    NASA Astrophysics Data System (ADS)

    Liu, Kun; Boehm, Jan; Alis, Christian

    2016-06-01

    Change detection has long been a challenging problem although a lot of research has been conducted in different fields such as remote sensing and photogrammetry, computer vision, and robotics. In this paper, we blend voxel grid and Apache Spark together to propose an efficient method to address the problem in the context of big data. Voxel grid is a regular geometry representation consisting of the voxels with the same size, which fairly suites parallel computation. Apache Spark is a popular distributed parallel computing platform which allows fault tolerance and memory cache. These features can significantly enhance the performance of Apache Spark and results in an efficient and robust implementation. In our experiments, both synthetic and real point cloud data are employed to demonstrate the quality of our method.

  3. SAR coherent change detection (CCD) for search and rescue

    NASA Astrophysics Data System (ADS)

    Mansfield, Arthur W.; Poehler, Paul L.; Rais, Houra

    1997-06-01

    Recent advances in the areas of phase history processing, interferometry, and radargrammetric adjustment have made possible extremely accurate information extraction from synthetic aperture radar (SAR) image pairs by means of interferometric techniques. The potential gain in accuracy is significant since measurements can theoretically be determined to within a fraction of a wavelength (subcentimeter accuracy) as opposed to a fraction of pixel distance (meter accuracy). One promising application of interferometric SAR (IFSAR) is the use of coherent change detection (CCD) over large areas to locate downed aircraft. This application poses an additional challenge since IFSAR must be processed at longer wavelengths to achieve foliage penetration. In this paper a combination of advanced techniques is described for using airborne SAR imagery to carry out this mission. Performance parameters are derived, and some examples are given from actual data.

  4. Image animation for theme enhancement and change detection. [LANDSAT 1

    NASA Technical Reports Server (NTRS)

    Evans, W. E.

    1976-01-01

    Animated displays are useful in enhancing subtle temporally related changes in scenes viewed by satellites capable of providing repetitive coverage. The detectability of fixed features is also improved through the help of the powerful visual integration process. To expedite the process of assembling and displaying well-registered, time-lapse sequences and to provide means for making quantitative measurements of radiances, displacements, and areas, an electronic satellite image analysis console was constructed. During the LANDSAT-1 program, this equipment was applied to the needs of a number of earth resource investigators with interests principally related to dynamic hydrology. The measurement of the areal extent of snow cover within defined drainage basins is discussed as a representative applications example.

  5. A voxel-based morphometric magnetic resonance imaging study of the brain detects age-related gray matter volume changes in healthy subjects of 21-45 years old.

    PubMed

    Bourisly, Ali K; El-Beltagi, Ahmed; Cherian, Jigi; Gejo, Grace; Al-Jazzaf, Abrar; Ismail, Mohammad

    2015-10-01

    Previous and more recent work of analyzing structural changes in the brain suggest that certain brain regions such as the frontal lobe are among the brain regions profoundly affected by the aging process across males and females. Also, a unified model of structural changes in a normally aging brain is still lacking. The present study investigated age-related structural brain changes in gray matter from young to early middle-age adulthood for males and females. Magnetic resonance images of 215 normal and healthy participants between the ages of 21-45 years were acquired. Changes in gray matter were assessed using voxel-based morphometry and gray matter volumetric analysis. The results showed significant decrease in gray matter volume between the youngest and oldest groups in the following brain regions: frontal, temporal, and parietal lobes. Grey matter loss in the frontal lobe was among the most widespread of all brain regions across the comparison groups that showed significant age-related changes in grey matter for both males and females. This work provides a unique pattern of age-related decline of normal and healthy adult males and females that can aid in the future development of a unified model of normal brain aging. PMID:26306927

  6. Prompt Earthquake Detection based on Transient Gravity Signals.

    NASA Astrophysics Data System (ADS)

    Juhel, K.; Montagner, J. P.; Barsuglia, M.; Ampuero, J. P.; Chassande-Mottin, E.; Harms, J.; Whiting, B. F.; Bernard, P.; Clevede, E.; Lognonne, P. H.

    2015-12-01

    The deformation caused by an earthquake induces changes in the Earth's gravitational field known as coseismic gravity changes, especially during mega-earthquakes. So far, only static gravity changes have been detected, considerably after the end of the rupture. Since gravity changes propagate at the speed of light, a dynamic gravity signal is produced everywhere on Earth during the rupture, even before the arrival of seismic waves. Here we confirm the evidence of this prompt gravity signal. We have analyzed, with a statistical blind method, the data recorded during the 2011 Mw 9.0 Tohoku-oki earthquake by a superconducting gravimeter in the underground Kamioka observatory, about 500 km away from the earthquake centroid. We find that a gravity signal is present before the P wave arrival, with a statistical significance of more than 99%. The signal amplitude is a fraction of μGal, consistent in sign and order-of-magnitude with theoretical predictions. A similar analysis is being conducted on data recorded by the broadband seismometers of the japanese network Fnet. Numerical simulations based on normal-mode method and an analytical model of dynamic gravity signals are used to compute synthetic seismograms, and thus characterize the prompt gravity signal. The robust detection of this prompt gravity signal with instruments more immune to the background seismic noise could, in principle, open new directions in earthquake seismology and overcome limitations of current earthquake early-warning systems imposed by the propagation speed of seismic waves.

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

    NASA Astrophysics Data System (ADS)

    Müller, Thomas

    2015-05-01

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

  8. Shearlet-based edge detection: flame fronts and tidal flats

    NASA Astrophysics Data System (ADS)

    King, Emily J.; Reisenhofer, Rafael; Kiefer, Johannes; Lim, Wang-Q.; Li, Zhen; Heygster, Georg

    2015-09-01

    Shearlets are wavelet-like systems which are better suited for handling geometric features in multi-dimensional data than traditional wavelets. A novel method for edge and line detection which is in the spirit of phase congruency but is based on a complex shearlet transform will be presented. This approach to detection yields an approximate tangent direction of detected discontinuities as a byproduct of the computation, which then yields local curvature estimates. Two applications of the edge detection method will be discussed. First, the tracking and classification of flame fronts is a critical component of research in technical thermodynamics. Quite often, the flame fronts are transient or weak and the images are noisy. The standard methods used in the field for the detection of flame fronts do not handle such data well. Fortunately, using the shearlet-based edge measure yields good results as well as an accurate approximation of local curvature. Furthermore, a modification of the method will yield line detection, which is important for certain imaging modalities. Second, the Wadden tidal flats are a biodiverse region along the North Sea coast. One approach to surveying the delicate region and tracking the topographical changes is to use pre-existing Synthetic Aperture Radar (SAR) images. Unfortunately, SAR data suffers from multiplicative noise as well as sensitivity to environmental factors. The first large-scale mapping project of that type showed good results but only with a tremendous amount of manual interaction because there are many edges in the data which are not boundaries of the tidal flats but are edges of features like fields or islands. Preliminary results will be presented.

  9. Long-term change detection from historical photography

    NASA Astrophysics Data System (ADS)

    Yoon, T.; Schenk, T.

    2006-12-01

    There is an increasing awareness in the science community about the potential of utilizing old photography and derived products together with new data for change detection and for extending the timeline as far back as possible. For example recent observations have revealed dramatic changes in the behavior of many ice streams and outlet glaciers in Greenland and Antarctica, ranging from complete shutdown of ice streams to manifold increases in velocity. Most observations are typically from the comparatively short time period since the beginning of the civilian satellite imagery (1980s), with most quantitative measurements starting only 10-15 years ago. To evaluate whether ongoing observed changes are climatically significant, changes must be determined over longer time frames. Earlier terrestrial and aerial photography and maps indeed exist and the objective of the project to disseminate these historical data and to develop techniques and tools for combining (fusing) old and new data in order to compile long-term time series of changes in the polar regions, for example in ice extent, velocity and surface elevations. The presentation focuses on new methodologies and interdisciplinary approaches that greatly facilitate the use of old photography for quantitative studies in the polar regions. An absolute prerequisite for the successful use of old photography is a rigorous registration, either with other sensory input data or with respect to 3D reference systems. Recent advances in digital photogrammetry allow registration with linear features, such as lines, curves and free-form lines without the need for identifying identical points. The concept of sensor invariant features was developed to register such disparate data sets as aerial imagery and 3D laser point clouds, originating from satellite laser altimetry or airborne laser scanning systems. Examples illustrating these concepts are shown from the Transantarctic Mountains, including the registration of aerial

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

    EPA Science Inventory

    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...

  11. Cellular telephone-based radiation detection instrument

    DOEpatents

    Craig, William W.; Labov, Simon E.

    2011-06-14

    A network of radiation detection instruments, each having a small solid state radiation sensor module integrated into a cellular phone for providing radiation detection data and analysis directly to a user. The sensor module includes a solid-state crystal bonded to an ASIC readout providing a low cost, low power, light weight compact instrument to detect and measure radiation energies in the local ambient radiation field. In particular, the photon energy, time of event, and location of the detection instrument at the time of detection is recorded for real time transmission to a central data collection/analysis system. The collected data from the entire network of radiation detection instruments are combined by intelligent correlation/analysis algorithms which map the background radiation and detect, identify and track radiation anomalies in the region.

  12. Non-Parametric Change-Point Method for Differential Gene Expression Detection

    PubMed Central

    Wang, Yao; Wu, Chunguo; Ji, Zhaohua; Wang, Binghong; Liang, Yanchun

    2011-01-01

    Background We proposed a non-parametric method, named Non-Parametric Change Point Statistic (NPCPS for short), by using a single equation for detecting differential gene expression (DGE) in microarray data. NPCPS is based on the change point theory to provide effective DGE detecting ability. Methodology NPCPS used the data distribution of the normal samples as input, and detects DGE in the cancer samples by locating the change point of gene expression profile. An estimate of the change point position generated by NPCPS enables the identification of the samples containing DGE. Monte Carlo simulation and ROC study were applied to examine the detecting accuracy of NPCPS, and the experiment on real microarray data of breast cancer was carried out to compare NPCPS with other methods. Conclusions Simulation study indicated that NPCPS was more effective for detecting DGE in cancer subset compared with five parametric methods and one non-parametric method. When there were more than 8 cancer samples containing DGE, the type I error of NPCPS was below 0.01. Experiment results showed both good accuracy and reliability of NPCPS. Out of the 30 top genes ranked by using NPCPS, 16 genes were reported as relevant to cancer. Correlations between the detecting result of NPCPS and the compared methods were less than 0.05, while between the other methods the values were from 0.20 to 0.84. This indicates that NPCPS is working on different features and thus provides DGE identification from a distinct perspective comparing with the other mean or median based methods. PMID:21655325

  13. Urban vegetation land covers change detection using multi-temporal MODIS Terra/Aqua data

    NASA Astrophysics Data System (ADS)

    Zoran, Maria A.; Savastru, Roxana S.; Savastru, Dan M.; Dida, Adrian I.; Ionescu, Ovidiu M.

    2013-10-01

    Urban vegetation land cover change is a direct measure of quantitative increase or decrease in sources of urban pollution and the dimension of extreme climate events and changes that determine environment quality. Spatio- temporal monitoring of urban vegetation land cover changes is a very important task for establishing the links between policy decisions, regulatory actions and subsequent land use activities. Former studies incorporating two-date change detection using Landsat TM/ETM data had limited performance for urban biophysically complex systems applications. In this paper, we describe recent results using data from NASA's Moderate Resolution Imaging Spectroradiometer and NOAA/AVHRR satellite to study urban vegetation land cover dynamics. This study explored the use of time-series MODIS Terra/Aqua Normalized Difference Vegetation Index (NDVI) and Leaf Area Index (LAI), data to provide change detection information for metropolitan area of Bucharest in Romania. Training and validation are based on a reference dataset collected from IKONOS high resolution remote sensing data. The mean detection accuracy for period 2002- 2012 was assessed to be of 89%, with a reasonable balance between change commission errors (21.7%), change omission errors (28.5%), and Kappa coefficient of 0.69. Annual change detection rates across the urban/periurban areas over the study period (2002-2012) were estimated at 0.78% per annum in the range of 0.45% (2002) to 0.75% (2012).Vegetation dynamics in urban areas at seasonal and longer timescales reflect large-scale interactions between the terrestrial biosphere and the climate system.

  14. Protein-based nanobiosensor for direct detection of hydrogen sulfide

    NASA Astrophysics Data System (ADS)

    Omidi, Meisam; Amoabediny, Ghasem; Yazdian, Fatemeh; Habibi-Rezaei, M.

    2015-01-01

    The chemically modified cytochrome c from equine heart, EC (232-700-9), was immobilized onto gold nanoparticles in order to develop a specific biosensing system for monitoring hydrogen sulfide down to the micromolar level, by means of a localized surface plasmon resonance spectroscopy. The sensing mechanism is based on the cytochrome-c conformational changes in the presence of H2S which alter the dielectric properties of the gold nanoparticles and the surface plasmon resonance peak undergoes a redshift. According to the experiments, it is revealed that H2S can be detected at a concentration of 4.0 μ \\text{M} (1.3 \\text{ppb}) by the fabricated biosensor. This simple, quantitative and sensitive sensing platform provides a rapid and convenient detection for H2S at concentrations far below the hazardous limit.

  15. Detection and Attribution of temperature changes in the mountainous western United States.

    NASA Astrophysics Data System (ADS)

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

    2007-12-01

    Under climate change, one of the major challenges that water managers face in the western United States is adequately meeting the water demand while minimizing the flood risk. It has been shown that, in the second half of the 20th century, winters and springs have warmed, the partition of precipitations has changed, the snow pack melts earlier and that the timing of streamflows has shifted towards the winter. A better understanding of the primary causes of these changes are crucial to reliably project future water availability. Hydrological changes can be driven by temperature or by precipitation changes, or a combination of the two. In this study, which is part of a more integrated analysis focusing on the detection and attribution of changes in the hydrological cycle, we raise the following questions: What are the causes of temperatures changes in the mountainous regions in the second half of the 20th century? Can we verify whether the observed earlier melting of snow is driven by human-induced temperature changes, rather than by changes in precipitation or natural internal climate variability? To address these questions, we conduct a detection and attribution analysis based on daily minimum and maximum temperatures, and on temperature variables that are more relevant to a potential shift in snowmelt (number of frost days and number of degree-days below 0C). We find that natural internal climate variability alone cannot explain the increase in temperature, the reduction of frost days and the decline in degree-days below 0C. External forcings agents such as the solar variability and volcanic eruptions cannot explain those changes either. Instead, we find a positive detection when the influence of anthropogenic greenhouse gases and sulphate aerosols effects are included in the climate forcings.

  16. Avoidance behavior and swimming activity of fish to detect pH changes

    SciTech Connect

    Nakamura, F.

    1986-12-01

    Usually, the initial response of an animal to an environmental perturbation is changing its behavior. With fish, this may hold an alteration in swimming activity or reactions like avoidance or attraction. The usefulness of fish behavior to detect the changes in chemical water quality was recognized more than 70 years ago. Since that time, many laboratory studies have been performed on the behavioral reactions of aquatic organisms to pollutants, including those resulting from pH changes. However, still there is no conclusive evidence that fish behavior offers an adequate tool to detect chemical pollution. In this study, the use of R-value for swimming activity and D/sup 2/-value for avoidance behavior of toxic warning methods to indicate the development of toxic condition is discussed based on experimental data on pH effects.

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

    PubMed

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

    2015-01-01

    Foreground/background segmentation via change detection in video sequences is often used as a stepping stone in high-level analytics and applications. Despite the wide variety of methods that have been proposed for this problem, none has been able to fully address the complex nature of dynamic scenes in real surveillance tasks. In this paper, we present a universal pixel-level segmentation method that relies on spatiotemporal binary features as well as color information to detect changes. This allows camouflaged foreground objects to be detected more easily while most illumination variations are ignored. Besides, instead of using manually set, frame-wide constants to dictate model sensitivity and adaptation speed, we use pixel-level feedback loops to dynamically adjust our method's internal parameters without user intervention. These adjustments are based on the continuous monitoring of model fidelity and local segmentation noise levels. This new approach enables us to outperform all 32 previously tested state-of-the-art methods on the 2012 and 2014 versions of the ChangeDetection.net dataset in terms of overall F-Measure. The use of local binary image descriptors for pixel-level modeling also facilitates high-speed parallel implementations: our own version, which used no low-level or architecture-specific instruction, reached real-time processing speed on a midlevel desktop CPU. A complete C++ implementation based on OpenCV is available online. PMID:25494507

  18. Biomimetic visual detection based on insect neurobiology

    NASA Astrophysics Data System (ADS)

    O'Carroll, David C.

    2001-11-01

    With a visual system that accounts for as much as 30% of the lifted mass, flying insects such as dragonflies and hoverflies invest more in vision than any other animal. Impressive visual performance is subserved by a surprisingly simple visual system. In a typical insect eye, between 2,000 and 30,000 pixels in the image are analyzed by fewer than 200,000 neurons in underlying neural circuits. The combination of sophisticated visual processing with an approachable level of complexity has made the insect visual system a leading model for biomimetic approaches to computer vision. Much neurobiological research has focused on neural circuits used for detection of moving patterns (e.g. optical flow during flight) and moving targets (e.g. prey). Research from several labs has led to great advances in our understanding of the neural mechanisms involved, and has spawned neuromorphic hardware based on key processes identified in neurobiological experiments. Despite its attractions, the highly non-linear nature of several key stages in insect visual processing presents a challenge to understanding. I will describe examples of adaptive elements of neural circuits in the fly visual system which analyze the direction and velocity of wide-field optical flow patterns and the result of experiments that suggest that these non-linearities may contribute to robust responses to natural image motion.

  19. Lagrangian based methods for coherent structure detection

    SciTech Connect

    Allshouse, Michael R.; Peacock, Thomas

    2015-09-15

    There has been a proliferation in the development of Lagrangian analytical methods for detecting coherent structures in fluid flow transport, yielding a variety of qualitatively different approaches. We present a review of four approaches and demonstrate the utility of these methods via their application to the same sample analytic model, the canonical double-gyre flow, highlighting the pros and cons of each approach. Two of the methods, the geometric and probabilistic approaches, are well established and require velocity field data over the time interval of interest to identify particularly important material lines and surfaces, and influential regions, respectively. The other two approaches, implementing tools from cluster and braid theory, seek coherent structures based on limited trajectory data, attempting to partition the flow transport into distinct regions. All four of these approaches share the common trait that they are objective methods, meaning that their results do not depend on the frame of reference used. For each method, we also present a number of example applications ranging from blood flow and chemical reactions to ocean and atmospheric flows.

  20. Lagrangian based methods for coherent structure detection.

    PubMed

    Allshouse, Michael R; Peacock, Thomas

    2015-09-01

    There has been a proliferation in the development of Lagrangian analytical methods for detecting coherent structures in fluid flow transport, yielding a variety of qualitatively different approaches. We present a review of four approaches and demonstrate the utility of these methods via their application to the same sample analytic model, the canonical double-gyre flow, highlighting the pros and cons of each approach. Two of the methods, the geometric and probabilistic approaches, are well established and require velocity field data over the time interval of interest to identify particularly important material lines and surfaces, and influential regions, respectively. The other two approaches, implementing tools from cluster and braid theory, seek coherent structures based on limited trajectory data, attempting to partition the flow transport into distinct regions. All four of these approaches share the common trait that they are objective methods, meaning that their results do not depend on the frame of reference used. For each method, we also present a number of example applications ranging from blood flow and chemical reactions to ocean and atmospheric flows. PMID:26428570

  1. GIS-based detection of grain boundaries

    NASA Astrophysics Data System (ADS)

    Li, Yingkui; Onasch, Charles M.; Guo, Yonggui

    2008-04-01

    The recognition of grain boundaries in deformed rocks from images of thin-sections or polished slabs is an essential step in describing and quantifying various fabric elements and strain. However, many of the methods in use today require labor-intensive manual digitization of grain boundary information. Here, we propose an automated, GIS-based method to detect grain boundaries and construct a grain boundary database in which the shape, orientation, and spatial distribution of grains can be quantified and analyzed in a reproducible manner. The proposed method includes a series of operations and functions to identify grain boundaries and construct the grain boundary database. These processes are integrated into a GIS model using ArcGIS ModelBuilder; thus, little or no operator intervention is required to perform the entire analysis. The method was evaluated using thin section images taken from three sandstone samples. The results indicate that the proposed method can correctly identify >70% of grains recognized manually without any intervention and is especially suitable for analyses where large numbers of grains are required.

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

    ERIC Educational Resources Information Center

    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…

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

    NASA Astrophysics Data System (ADS)

    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

  4. Underwater video as a monitoring tool to detect change in seagrass cover.

    PubMed

    McDonald, Justin I; Coupland, Grey T; Kendrick, Gary A

    2006-07-01

    To date seagrass monitoring has involved the removal of seagrass from its environment. In fragile or highly disturbed systems, monitoring using destructive techniques may interfere with the environment or add to the burden of disturbance. Video photography is a form of non-destructive monitoring that does not require the removal of seagrass or interference with the environment and has the potential to be a valuable tool in monitoring seagrass systems. This study investigated the efficacy of video photography as a tool for detecting change in seagrass cover, using the temperate Australian species Amphibolis antarctica (Labill.) Sonder ex Aschers. Using visual and random point estimates of seagrass cover from video footage, it was possible to determine the minimum sample size (number of random video frames) needed to detect change in seagrass cover, the minimum detectable change in cover and the probability of the monitoring design committing a Type II error. Video footage was examined at three scales: transects (m apart), sites (km apart) and regions (tens of km apart). Using visual and random point estimation techniques, a minimum sample size of ten quadrats per transect was required to detect change in uniform and variable seagrass cover. With ten quadrats it was possible to identify a minimum detectable change in cover of 15% for uniform and 30% for variable seagrass cover. Power analysis was used to determine the probability of committing a Type II error from the data. Region level data had low power, corresponding to a high risk of committing a Type II error. Site and transect level data had high power corresponding to a low risk of committing a Type II error. Based on this study's data, managers using video to monitor for change in seagrass cover are advised to use data from the smaller scale, for example, site and transect level data. By using data from the smaller scale, managers will have a low risk of incorrectly concluding there has not been a disturbance

  5. Change detection from very high resolution satellite time series with variable off-nadir angle

    NASA Astrophysics Data System (ADS)

    Barazzetti, Luigi; Brumana, Raffaella; Cuca, Branka; Previtali, Mattia

    2015-06-01

    Very high resolution (VHR) satellite images have the potential for revealing changes occurred overtime with a superior level of detail. However, their use for metric purposes requires accurate geo-localization with ancillary DEMs and GCPs to achieve sub-pixel terrain correction, in order to obtain images useful for mapping applications. Change detection with a time series of VHS images is not a simple task because images acquired with different off-nadir angles have a lack of pixel-to-pixel image correspondence, even after accurate geo-correction. This paper presents a procedure for automatic change detection able to deal with variable off-nadir angles. The case study concerns the identification of damaged buildings from pre- and post-event images acquired on the historic center of L'Aquila (Italy), which was struck by an earthquake in April 2009. The developed procedure is a multi-step approach where (i) classes are assigned to both images via object-based classification, (ii) an initial alignment is provided with an automated tile-based rubber sheeting interpolation on the extracted layers, and (iii) change detection is carried out removing residual mis-registration issues resulting in elongated features close to building edges. The method is fully automated except for some thresholds that can be interactively set to improve the visualization of the damaged buildings. The experimental results proved that damages can be automatically found without additional information, such as digital surface models, SAR data, or thematic vector layers.

  6. Liquid crystal based biosensors for bile acid detection

    NASA Astrophysics Data System (ADS)

    He, Sihui; Liang, Wenlang; Tanner, Colleen; Fang, Jiyu; Wu, Shin-Tson

    2013-03-01

    The concentration level of bile acids is a useful indicator for early diagnosis of liver diseases. The prevalent measurement method in detecting bile acids is the chromatography coupled with mass spectrometry, which is precise yet expensive. Here we present a biosensor platform based on liquid crystal (LC) films for the detection of cholic acid (CA). This platform has the advantage of low cost, label-free, solution phase detection and simple analysis. In this platform, LC film of 4-Cyano-4'-pentylbiphenyl (5CB) was hosted by a copper grid supported with a polyimide-coated glass substrate. By immersing into sodium dodecyl sulfate (SDS) solution, the LC film was coated with SDS which induced a homeotropic anchoring of 5CB. Addition of CA introduced competitive adsorption between CA and SDS at the interface, triggering a transition from homeotropic to homogeneous anchoring. The detection limit can be tuned by changing the pH value of the solution from 12uM to 170uM.

  7. Nuclear based techniques for detection of contraband

    SciTech Connect

    Gozani, T.

    1993-12-31

    The detection of contraband such as explosives and drugs concealed in luggage or other container can be quite difficult. Nuclear techniques offer capabilities which are essential to having effective detection devices. This report describes the features of various nuclear techniques and instrumentation.

  8. Laser-based Sensors for Chemical Detection

    SciTech Connect

    Myers, Tanya L.; Phillips, Mark C.; Taubman, Matthew S.; Bernacki, Bruce E.; Schiffern, John T.; Cannon, Bret D.

    2010-05-10

    Stand-off detection of hazardous materials ensures that the responder is located at a safe distance from the suspected source. Remote detection and identification of hazardous materials can be accomplished using a highly sensitive and portable device, at significant distances downwind from the source or the threat. Optical sensing methods, in particular infrared absorption spectroscopy combined with quantum cascade lasers (QCLs), are highly suited for the detection of chemical substances since they enable rapid detection and are amenable for autonomous operation in a compact and rugged package. This talk will discuss the sensor systems developed at Pacific Northwest National Laboratory and will discuss the progress to reduce the size and power while maintaining sensitivity to enable stand-off detection of multiple chemicals.

  9. Network Anomaly Detection Based on Wavelet Analysis

    NASA Astrophysics Data System (ADS)

    Lu, Wei; Ghorbani, Ali A.

    2008-12-01

    Signal processing techniques have been applied recently for analyzing and detecting network anomalies due to their potential to find novel or unknown intrusions. In this paper, we propose a new network signal modelling technique for detecting network anomalies, combining the wavelet approximation and system identification theory. In order to characterize network traffic behaviors, we present fifteen features and use them as the input signals in our system. We then evaluate our approach with the 1999 DARPA intrusion detection dataset and conduct a comprehensive analysis of the intrusions in the dataset. Evaluation results show that the approach achieves high-detection rates in terms of both attack instances and attack types. Furthermore, we conduct a full day's evaluation in a real large-scale WiFi ISP network where five attack types are successfully detected from over 30 millions flows.

  10. Detection of anthropogenic influence on multi-decadal changes in ocean stratification

    NASA Astrophysics Data System (ADS)

    Andrews, Oliver; Le Quéré, Corinne

    2016-04-01

    Signals of anthropogenic climate change have been identified in the ocean system using established detection and attribution methods to examine historical records of ocean temperature, salinity and dissolved oxygen concentration. Strengthened stratification of the upper ocean is another likely consequence of climate-driven warming and freshening of near surface waters. However, whilst qualitative links have been made between climate forcing and observed and projected future ocean stratification, the relative contribution of natural and anthropogenic processes remains uncertain. Elevated density stratification reduces physical exchange between the surface and interior ocean, impacting upon ventilation processes and biogeochemical cycling. Here, we combine recent temperature and salinity measurements to assess the extent to which large-scale changes in ocean stratification between the 1960s and 2000s can be attributed to anthropogenic climate change using a suite of coupled climate model simulations. Applying formal, regression-based fingerprinting methods we show that external climate forcing has had a detectable influence on observed changes in density stratification and that these changes cannot be explained by climate variability or natural external factors such as volcanism or solar output. Our study indicates that human influence has already significantly altered the density structure of the upper ocean. We discuss the implications and potential for detecting the variability and trends in carbon and oxygen storage in the ocean and in heat uptake efficiency.

  11. Scalable time series change detection for biomass monitoring using gaussian process

    SciTech Connect

    Chandola, Varun; Vatsavai, Raju

    2010-01-01

    Biomass monitoring, specifically detecting changes in the biomass or vegetation of a geographical region, is vital for studying the carbon cycle of the system and has significant implications in the context of understanding climate change and its impacts. Recently, several time series change detection methods have been proposed to identify land cover changes in temporal profiles (time series) of vegetation collected using remote sensing instruments. In this paper, we adapt Gaussian process regression to detect changes in such time series in an online fashion. While Gaussian process (GP) has been widely used as a kernel based learning method for regression and classification, their applicability to massive spatio-temporal data sets, such as remote sensing data, has been limited owing to the high computational costs involved. In this paper we address the scalability aspect of GP based time series change detection. Specifically, we exploit the special structure of the covariance matrix generated for GP analysis to come up with methods that can efficiently estimate the hyper-parameters associated with GP as well as identify changes in the time series while requiring a memory footprint which is linear in the size of input data, as compared to traditional method which involves solving a linear system of equations for the Choleksy decomposition of the quadratic sized covariance matrix. Experimental results show that our proposed method achieves significant speedups, as high as 1000, when processing long time series, while maintaining a small memory footprint. To further improve the computational complexity of the proposed method, we provide a parallel version which can concurrently process multiple input time series using the same set of hyper-parameters. The parallel version exploits the natural parallelization potential of the serial algorithm and is shown to perform significantly better than the serial version, with speedups as high as 10. Finally, we demonstrate the

  12. Improving seroreactivity-based detection of glioma.

    PubMed

    Ludwig, Nicole; Keller, Andreas; Heisel, Sabrina; Leidinger, Petra; Klein, Veronika; Rheinheimer, Stefanie; Andres, Claudia U; Stephan, Bernhard; Steudel, Wolf-Ingo; Graf, Norbert M; Burgeth, Bernhard; Weickert, Joachim; Lenhof, Hans-Peter; Meese, Eckart

    2009-12-01

    Seroreactivity profiling emerges as valuable technique for minimal invasive cancer detection. Recently, we provided first evidence for the applicability of serum profiling of glioma using a limited number of immunogenic antigens. Here, we screened 57 glioma and 60 healthy sera for autoantibodies against 1827 Escherichia coli expressed clones, including 509 in-frame peptide sequences. By a linear support vector machine approach, we calculated mean specificity, sensitivity, and accuracy of 100 repetitive classifications. We were able to differentiate glioma sera from sera of the healthy controls with a specificity of 90.28%, a sensitivity of 87.31% and an accuracy of 88.84%. We were also able to differentiate World Health Organization grade IV glioma sera from healthy sera with a specificity of 98.45%, a sensitivity of 80.93%, and an accuracy of 92.88%. To rank the antigens according to their information content, we computed the area under the receiver operator characteristic curve value for each clone. Altogether, we found 46 immunogenic clones including 16 in-frame clones that were informative for the classification of glioma sera versus healthy sera. For the separation of glioblastoma versus healthy sera, we found 91 informative clones including 26 in-frame clones. The best-suited in-frame clone for the classification glioma sera versus healthy sera corresponded to the vimentin gene (VIM) that was previously associated with glioma. In the future, autoantibody signatures in glioma not only may prove useful for diagnosis but also offer the prospect for a personalized immune-based therapy. PMID:20019846

  13. Radome effects on coherent change detection radar systems

    NASA Astrophysics Data System (ADS)

    Raynal, Ann Marie; Dubbert, Dale F.; Burns, Bryan L.; Hensley, William H.

    2015-05-01

    A radome, or radar dome, protects a radar system from exposure to the elements. Unfortunately, radomes can affect the radiation pattern of the enclosed antenna. The co-design of a platform's radome and radar is ideal to mitigate any deleterious effects of the radome. However, maintaining structural integrity and other platform flight requirements, particularly when integrating a new radar onto an existing platform, often limits radome electrical design choices. Radars that rely heavily on phase measurements such as monopulse, interferometric, or coherent change detection (CCD) systems require particular attention be paid to components, such as the radome, that might introduce loss and phase variations as a function of the antenna scan angle. Material properties, radome wall construction, overall dimensions, and shape characteristics of a radome can impact insertion loss and phase delay, antenna beamwidth and sidelobe level, polarization, and ultimately the impulse response of the radar, among other things, over the desired radar operating parameters. The precision-guided munitions literature has analyzed radome effects on monopulse systems for well over half a century. However, to the best of our knowledge, radome-induced errors on CCD performance have not been described. The impact of radome material and wall construction, shape, dimensions, and antenna characteristics on CCD is examined herein for select radar and radome examples using electromagnetic simulations.

  14. Detection of greenhouse-gas-induced climatic change. Progress report, July 1, 1994--July 31, 1995

    SciTech Connect

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

    1995-07-21

    The objective of this research is to assembly and analyze instrumental climate data and to develop and apply climate models as a basis for detecting greenhouse-gas-induced climatic change, and validation of General Circulation Models. In addition to changes due to variations in anthropogenic forcing, including greenhouse gas and aerosol concentration changes, the global climate system exhibits a high degree of internally-generated and externally-forced natural variability. To detect the anthropogenic effect, its signal must be isolated from the ``noise`` of this natural climatic variability. A high quality, spatially extensive data base is required to define the noise and its spatial characteristics. To facilitate this, available land and marine data bases will be updated and expanded. The data will be analyzed to determine the potential effects on climate of greenhouse gas and aerosol concentration changes and other factors. Analyses will be guided by a variety of models, from simple energy balance climate models to coupled atmosphere ocean General Circulation Models. These analyses are oriented towards obtaining early evidence of anthropogenic climatic change that would lead either to confirmation, rejection or modification of model projections, and towards the statistical validation of General Circulation Model control runs and perturbation experiments.

  15. Northwestern Black Sea coastal zone environmental changes detection by satellite remote sensing data

    NASA Astrophysics Data System (ADS)

    Zoran, Maria A.

    2004-02-01

    The Romanian North Western coastal and shelf zones of the Black Sea and Danube delta are a mosaic of complex, interacting ecosystems, rich natural resources and socio-economic activity. Dramatic changes in the Black Sea's ecosystem and resources are due to natural and anthropogenic causes (increase in the nutrient and pollutant load of rivers input, industrial and municipal wastewater pollution along the coast, and dumping on the open sea). A scientific management system for protection, conservation and restoration must be based on reliable information on bio-geophysical and geomorphologic processes, coastal erosion, sedimentation dynamics, mapping of macrophyte fields, water quality, climatic change effects. A multitemporal data set consisting of LANDSAT MSS, TM and SAR ERS-1 images was used for comparing and mapping landcover change via change detection. Synergetic use of quasi-simultaneously acquired multi-sensor data may therefore allow for a better approach of change detection of coastal area. The main aim of this paper is to conduct a comprehensive analysis based on existing historical and more recent in situ and remote sensing data to establish the link between phytoplankton bloom development, increasing erosion and diminishing of beaches and related coastal zone harmful phenomena.

  16. Instructional changes based on cogenerative physics reform

    NASA Astrophysics Data System (ADS)

    Samuels, Natan; Brewe, Eric; Kramer, Laird

    2013-01-01

    We describe changes in a physics teacher's pedagogy and cultural awareness that resulted from her students' involvement in reforming their classroom. For this case study, we examined a veteran high school teacher's semester-long use of CMPLE (the Cogenerative Mediation Process for Learning Environments) in her Modeling Instruction classroom. CMPLE is a formative intervention designed to help students and instructors collaborate to change classroom dynamics, based on how closely the environment matches their learning preferences. Analysis of classroom videos, interviews, and other artifacts indicates that adapting the environment to align with the preferences of that shared culture affected the instructor in complex ways. We will trace her teaching practices and her self-described awareness of the culture of learning, to highlight notable changes. The teacher espoused deeper understanding of her students' physics learning experience, which she gained from including students in responding to their own individual and collective learning preferences.

  17. TCSPC based approaches for multiparameter detection in living cells

    NASA Astrophysics Data System (ADS)

    Jahn, Karolina; Buschmann, Volker; Koberling, Felix; Hille, Carsten

    2014-03-01

    In living cells a manifold of processes take place simultaneously. This implies a precise regulation of intracellular ion homeostasis. In order to understand their spatio-temporal pattern comprehensively, the development of multiplexing concepts is essential. Due to the multidimensional characteristics of fluorescence dyes (absorption and emission spectra, decay time, anisotropy), the highly sensitive and non-invasive fluorescence microscopy is a versatile tool for realising multiplexing concepts. A prerequisite are analyte-specific fluorescence dyes with low cross-sensitivity to other dyes and analytes, respectively. Here, two approaches for multiparameter detection in living cells are presented. Insect salivary glands are well characterised secretory active tissues which were used as model systems to evaluate multiplexing concepts. Salivary glands secrete a KCl-rich or NaCl-rich fluid upon stimulation which is mainly regulated by intracellular Ca2+ as second messenger. Thus, pairwise detection of intracellular Na+, Cl- and Ca2+ with the fluorescent dyes ANG2, MQAE and ACR were tested. Therefore, the dyes were excited simultaneously (2-photon excitation) and their corresponding fluorescence decay times were recorded within two spectral ranges using time-correlated singlephoton counting (TCSPC). A second approach presented here is based on a new TCSPC-platform covering decay time detection from picoseconds to milliseconds. Thereby, nanosecond decaying cellular fluorescence and microsecond decaying phosphorescence of Ruthenium-complexes, which is quenched by oxygen, were recorded simultaneously. In both cases changes in luminescence decay times can be linked to changes in analyte concentrations. In consequence of simultaneous excitation as well as detection, it is possible to get a deeper insight into spatio-temporal pattern in living tissues.

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

    NASA Technical Reports Server (NTRS)

    Potter, Christopher S.

    2013-01-01

    Landsat satellite imagery was analyzed to generate a detailed record of 10 years of vegetation disturbance and regrowth for Pacific coastal areas of Marin and San Francisco Counties. The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) methodology, a transformation of Tasseled-Cap data space, was applied to detected changes in perennial coastal shrubland, woodland, and forest cover from 1999 to 2009. Results showed several principal points of interest, within which extensive contiguous areas of similar LEDAPS vegetation change (either disturbed or restored) were detected. Regrowth areas were delineated as burned forest areas in the Point Reyes National Seashore (PRNS)