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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. 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.

  3. 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.

  4. Cortical dynamics of visual change detection based on sensory memory.

    PubMed

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

    2010-08-01

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

  5. 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.

  6. Object-Based Change Detection Using Georeferenced Uav Images

    NASA Astrophysics Data System (ADS)

    Shi, J.; Wang, J.; Xu, Y.

    2011-09-01

    Unmanned aerial vehicles (UAV) have been widely used to capture and down-link real-time videos/images. However, their role as a low-cost airborne platform for capturing high-resolution, geo-referenced still imagery has not been fully utilized. The images obtained from UAV are advantageous over remote sensing images as they can be obtained at a low cost and potentially no risk to human life. However, these images are distorted due to the noise generated by the rotary wings which limits the usefulness of such images. One potential application of such images is to detect changes between the images of the same area which are collected over time. Change detection is of widespread interest due to a large number of applications, including surveillance and civil infrastructure. Although UAVs can provide images with high resolution in a portable and easy way, such images only cover small parts of the entire field of interest and are often with high deformation. Until now, there is not much application of change detection for UAV images. Also the traditional pixel-based change detection method does not give satisfactory results for such images. In this paper, we have proposed a novel object-based method for change detection using UAV images which can overcome the effect of deformation and can fully utilize the high resolution capability of UAV images. The developed method can be divided into five main blocks: pre-processing, image matching, image segmentation and feature extraction, change detection and accuracy evaluation. The pre-processing step is further divided into two sub-steps: the first sub-step is to geometrically correct the bi-temporal image based on the geo-reference information (GPS/INS) installed on the UAV system, and the second sub-step is the radiometric normalization using a histogram method. The image matching block uses the well-known scale-invariant feature transform (SIFT) algorithm to match the same areas in the images and then resample them. The

  7. 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.

  8. Ultrasound thermal change detection based on steerable filters.

    PubMed

    Sahba, Nima; Tavakoli, Vahid; Nambakhsh, MohamadSaleh

    2008-01-01

    Growing tendency toward utilization of Laser and RF knives has opened a new port for thermal control applications in which ultrasound thermal detection is crucial. Ultrasound velocity is dependent on the thermal properties of the environment. In this paper we focus on tissue temperature detection using multiresolution steerable filter-based motion estimation. The proposed technique was evaluated on simulated and real in-vivo cases during surgical occlusion and reopening of renal segmental artery and demonstrated promising results for observation of internal organ temperature changes using only digital ultrasound systems for diagnosis and therapy. It is proved that being oriented in space and time, steerable filters can achieve more accurate results. Performing thermal detection methods on synthetic phantoms demonstrated good correlation between speckle shifts and the ground truth temperature. For the simulated images average thermal error was 0.68 degrees Celsius with a standard deviation of 0.79.

  9. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2016-08-01

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

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. Change Detection and Dynamic Analysis Based on Remote Sensing Images

    NASA Astrophysics Data System (ADS)

    Luzi, G.; Crosetto, M.; Devanthéry, N.; Cuevas, M.; Meng, X.

    2013-08-01

    A radar uses the time elapsed between the transmission and reception of an electromagnetic waveform to locate targets present in the illuminated area. Different objects will reflect the radiation with different intensities and phase. The signal provided by standard radar is a profile of the intensity backscattered from the scene as a function of the distance. The resolution, i.e. the capability to distinguish different targets, is related to instrumental parameters and, for conventional radar, is in the range of tens of centimetres. The elementary sampling volume of a radar measurement is usually called radar bin. A radar image can be obtained when an azimuth and a range resolution is available, and this can be attained in different ways: performing a mechanical scanning of the antenna, the most familiar mode used for surveillance, meteorological radar etc, or modifying its spatial features by changing the characteristics of the radiated signal or finally through a specific processing of the acquired data, as in the case of Synthetic Aperture Radar (SAR). In this paper only 1D data without any cross range resolution are used. The vibration of a target corresponds to a small and rapid variation of the radar-target distance to which the phase of the received signal is related. Coherent radar is able to provide measurements of the phase variation along time exploiting the interferometric technique. The received radar signals permits to retrieve distance variations of the observed objects in the order of small fractions of the transmitted wavelength, by comparing the phase of signals acquired at different times. Use a short span bridge as a test-bed this study investigates the actual capability of a Real Aperture Radar (RAR) interferometer to detect the natural vibration caused by wind or pass pedestrians. It is found that RAR can pick up bridge displacements of a few tens of μm and detect a wide range of vibrations.

  16. [Change detection from high-resolution remote sensing image based on MSE model].

    PubMed

    Wei, Li-Fei; Wang, Hai-Bo

    2013-03-01

    At present, most of the traditional change detection methods from high-resolution remote sensing image are based on a feature information, the information of multi-feature information cannot be extracted, so it is difficult to detect the complete information. In order to solve this problem, a change detection algorithm of high-resolution remote sensing image based on multiview spectral embedding is proposed in the present paper. Firstly, change image is obtained using traditional difference change detection method, and multi-feature information is extracted. The feature vector information is fused by a MSE model and the complete change information can be obtained. The experimental results show that the detection accuracy of the proposed method is better than the accuracy of traditional methods, and its stability is outstanding.

  17. 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…

  18. 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.

  19. 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.

  20. Fast SAR image change detection using Bayesian approach based difference image and modified statistical region merging.

    PubMed

    Zhang, Han; 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.

  1. 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

  2. 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.

  3. 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.

  4. 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.

  5. Caries Detection Methods Based on Changes in Optical Properties between Healthy and Carious Tissue

    PubMed Central

    Karlsson, Lena

    2010-01-01

    A conservative, noninvasive or minimally invasive approach to clinical management of dental caries requires diagnostic techniques capable of detecting and quantifying lesions at an early stage, when progression can be arrested or reversed. Objective evidence of initiation of the disease can be detected in the form of distinct changes in the optical properties of the affected tooth structure. Caries detection methods based on changes in a specific optical property are collectively referred to as optically based methods. This paper presents a simple overview of the feasibility of three such technologies for quantitative or semiquantitative assessment of caries lesions. Two of the techniques are well-established: quantitative light-induced fluorescence, which is used primarily in caries research, and laser-induced fluorescence, a commercially available method used in clinical dental practice. The third technique, based on near-infrared transillumination of dental enamel is in the developmental stages. PMID:20454579

  6. 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.

  7. 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

  8. 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.

  9. 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).

  10. 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

  11. 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

  12. 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

    2016-10-01

    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.

  13. 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

  14. 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

  15. 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.

  16. 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).

  17. A Voxel-based Method for Forest Change Detection after Fire Using LiDAR Data

    NASA Astrophysics Data System (ADS)

    Xu, Z.

    2015-12-01

    A Voxel-based Method for Forest Change Detection after Fire Using LiDAR DataZewei Xu and Jonathan A. Greenberg Traditional methods of forest fire modeling focus on the patterns of burning in two-dimensions at relatively coarse resolutions. However, fires spread in complex, three-dimensional patterns related to the horizontal and vertical distributions of woody fuel as well as the prevailing climate conditions, and the micro-scale patterns of fuel distributions over scales of only meters can determine the path that fire can take through a complex landscape. One challenge in understanding the full three-dimensional (3D) path that a fire takes through a landscape is a lack of data at landscape scales of these burns. Remote sensing approaches, while operating at landscape scales, typically focus on two-dimensional analyses using standard image-based change detection techniques. In this research, we develop a 3D voxel-based change detection method applied to multitemporal LiDAR data collected before and after forest fires in California to quantify the full 3D pattern of vegetation loss. By changing the size of the voxel, forest loss at different spatial scales is revealed. The 3D tunnel of fuel loss created by the fire was used to examine ground-to-crown transitions, firebreaks, and other three-dimensional aspects of a forest fire.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

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

    PubMed

    Gong, Maoguo; Zhou, Zhiqiang; Ma, Jingjing

    2012-04-01

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

  3. Change-based threat detection in urban environments with a forward-looking camera

    NASA Astrophysics Data System (ADS)

    Morton, Kenneth, Jr.; Ratto, Christopher; Malof, Jordan; Gunter, Michael; Collins, Leslie; Torrione, Peter

    2012-06-01

    Roadside explosive threats continue to pose a significant risk to soldiers and civilians in conflict areas around the world. These objects are easy to manufacture and procure, but due to their ad hoc nature, they are difficult to reliably detect using standard sensing technologies. Although large roadside explosive hazards may be difficult to conceal in rural environments, urban settings provide a much more complicated background where seemingly innocuous objects (e.g., piles of trash, roadside debris) may be used to obscure threats. Since direct detection of all innocuous objects would flag too many objects to be of use, techniques must be employed to reduce the number of alarms generated and highlight only a limited subset of possibly threatening regions for the user. In this work, change detection techniques are used to reduce false alarm rates and increase detection capabilities for possible threat identification in urban environments. The proposed model leverages data from multiple video streams collected over the same regions by first applying video aligning and then using various distance metrics to detect changes based on image keypoints in the video streams. Data collected at an urban warfare simulation range at an Eastern US test site was used to evaluate the proposed approach, and significant reductions in false alarm rates compared to simpler techniques are illustrated.

  4. 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.

  5. 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.

  6. Unsupervised change detection based on improved Markov random field technique using multichannel synthetic aperture radar images

    NASA Astrophysics Data System (ADS)

    Salehi, Sara; Valadan Zoej, Mohammad Javad

    2014-01-01

    Change detection represents an important remote sensing tool in environmental monitoring and disaster management. In this respect, multichannel synthetic aperture radar (SAR) data offer great potential because of their insensitivity to atmospheric and sun-illumination conditions (over optical multispectral data) and the improved discrimination capability they may provide compared to single-channel SAR. The problem of detecting the changes caused by flooding is addressed by a contextual unsupervised technique based on a Markovian data fusion approach. However, the isotropic formulation of Markov random field (MRF) models causes oversmoothing of spatial boundaries in the final change maps. In order to reduce this drawback, an edge-preserving MRF model is proposed and formulated by using energy functions that combine the edge information extracted from the produced edge maps using competitive fuzzy rules and Canny technique, the information conveyed by each SAR channel, and the spatial contextual information. The proposed technique is experimentally validated with semisimulated data and real ASAR-ENVISAT images. Change detection results obtained by the improved MRF model exhibited a higher accuracy than its predecessors for both semisimulated (average 12%) and real (average 6%) data.

  7. 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.

  8. 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

  9. 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

  10. 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.

  11. 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.

  12. 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.

  13. 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

  14. A change detection algorithm for man-made objects based on remote sensing images

    NASA Astrophysics Data System (ADS)

    Wang, Wenwu; Cao, Zhiguo

    2011-12-01

    Radiometric difference, misregistration error and the determination of classification threshold for difference image seriously influenced the detection accuracy of traditional pixel-level change detection algorithms, and it is difficult to get the true changes of interest from various kinds of detected changes. Therefore, a novel change detection algorithm is proposed to detect changes of man-made objects in remote sensing images. Large-size images are divided into overlapping and multi-scale sub-images, and three kinds of multi-scale structural features (including interscale or intrascale features), such as central-shift moments, gradient-magnitude features, gradient-orientation features and line-length features are extracted by support vector machine (SVM) classification. Experimental results demonstrate the feasibility and effectiveness of the proposed algorithm.

  15. 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.

  16. Multiple Regression Model Based Sequential Probability Ratio Test for Structural Change Detection of Time Series

    NASA Astrophysics Data System (ADS)

    Takeda, Katsunori; Hattori, Tetsuo; Kawano, Hiromichi

    In real time analysis and forecasting of time series data, it is important to detect the structural change as immediately, correctly, and simply as possible. And it is necessary for rebuilding the next prediction model after the change point as soon as possible. For this kind of time series data analysis, in general, multiple linear regression models are used. In this paper, we present two methods, i.e., Sequential Probability Ratio Test (SPRT) and Chow Test that is well-known in economics, and describe those experimental evaluations of the effectiveness in the change detection using the multiple regression models. Moreover, we extend the definition of the detected change point in the SPRT method, and show the improvement of the change detection accuracy.

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

    NASA Technical Reports Server (NTRS)

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

    1990-01-01

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

  18. 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.

  19. 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.

  20. 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.

  1. [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.

  2. [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

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

    PubMed Central

    Duong, Tarn; Goud, Bruno; Schauer, Kristine

    2012-01-01

    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

  4. 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.

  5. 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.

  6. 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.

  7. Fluorescence-based detection of single-nucleotide changes in RNA using graphene oxide and DNAzyme.

    PubMed

    Hong, Chaesun; Kim, Dong-Min; Baek, Ahruem; Chung, Hyewon; Jung, Woong; Kim, Dong-Eun

    2015-04-01

    We report a simple fluorometric method for detection of single-nucleotide changes in RNA using graphene oxide (GO) and RNA-cleaving DNAzyme. The fluorescent DNA probe (F-DNA) was annealed to RNA fragments generated by RNA cleavage with DNAzyme specific to mutant RNA. The F-DNA-RNA duplex attenuated the quenching of F-DNA fluorescence by GO. PMID:25714982

  8. 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

  9. [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

  10. [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

  11. 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.

  12. Detecting and predicting changes.

    PubMed

    Brown, Scott D; Steyvers, Mark

    2009-02-01

    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 true temporal structure. In two experiments we demonstrate that participants often make correct statistical decisions when asked to infer the hidden state of the data generating process. However, when asked to make predictions about future outcomes, accuracy decreased even though normatively correct responses in the two tasks were identical. A particle filter model accounts for all data, describing performance in terms of a plausible psychological process. By varying the number of particles, and the prior belief about the probability of a change occurring in the data generating process, we were able to model most of the observed individual differences.

  13. Change detection: training and transfer.

    PubMed

    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.

  14. 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

  15. 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)

  16. 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.

  17. Height Change Detection in Antarctica Using ICESat Data Based on Kriging/Kalman Filtering Technique

    NASA Astrophysics Data System (ADS)

    Huang, H.

    2009-04-01

    Studies of the response of ice sheets to climate change require data sets with high accuracy and uniform ice sheet coverage. Measurements from the Geoscience Laser Altimeter System(GLAS) aboard NASA's ICESat satellite are used to estimate changes in the ice sheet surface heights and the secular change in Antarctic ice mass. Usually, the most common technique used in analyzing satellite altimetry data to study height change in the ice sheets is the dh/dt technique based on the cross-over geometry. However, this approach only uses less ten percent of the available data. So in this paper, Kriging is introduced as an alternative method, which will enable us to use all of the data and the data statistics to estimate height changes and other surface characteristics. Results of height change rate dh/dt in Antarctica for the years 2003-2005 produced using Kriging and cross-over analysis are compared. In the Amery Ice Shelf and in the West Antarctic coastal area and near latitude-81∘N , the difference in dh/dt between the two methods is statistically significant. Specifically, Kriging gives higher positive dh/dt at the Amery Ice Shelf, and does not show the pervasive negative dh/dt in the Pine Island/Thwaites Glaciers area. In addition, Kriging results also show a systematic positive difference of approximately 0.03

  18. 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.

  19. 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.

  20. Change detection methods for distinction task of stochastic textures based on nonparametric method

    NASA Astrophysics Data System (ADS)

    Sultanov, Albert K.

    2016-03-01

    The following article describes use of nonparametric method. This method is to be used to find multivariate change of random processes for image processing. It is aimed to find the borders of irregular phenomena in front of terrain. The current task of finding change and evaluation of a change point in consequent setting proposes test statistics based on value of sampling characteristic functions. The relevant criterion in a wide range of alternatives has a predetermined assessment of the asymptotic significance level. Current work also proposes an algorithm of texture segmentation for two-dimensional case. This algorithm is given as a consequence of processing operations in columns and rows of test statistics values, obtained during scanning of images. The test results are quoted.

  1. 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.

  2. 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

  3. 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

  4. 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…

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

    PubMed

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

    2015-05-01

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

  6. Assessing the Feasibility of Uav-Based LIDAR for High Resolution Forest Change Detection

    NASA Astrophysics Data System (ADS)

    Wallace, L. O.; Lucieer, A.; Watson, C. S.

    2012-08-01

    Airborne LiDAR data has become an important tool for both the scientific and industry based investigation of forest structure. The uses of discrete return observations have now reached a maturity level such that the operational use of this data is becoming increasingly common. However, due to the cost of data collection, temporal studies into forest change are often not feasible or completed at infrequent and at uneven intervals. To achieve high resolution temporal LiDAR surveys, this study has developed a micro-Unmanned Aerial Vehicle (UAV) equipped with a discrete return 4-layer LiDAR device and miniaturised positioning sensors. This UAV has been designed to be low-cost and to achieve maximum flying time. In order to achieve these objectives and overcome the accuracy restrictions presented by miniaturised sensors a novel processing strategy based on a Kalman smoother algorithm has been developed. This strategy includes the use of the structure from motion algorithm in estimating camera orientation, which is then used to restrain IMU drift. The feasibility of such a platform for monitoring forest change is shown by demonstrating that the pointing accuracy of this UAV LiDAR device is within the accuracy requirements set out by the Australian Intergovernmental Committee on Surveying and Mapping (ICSM) standards.

  7. Ground-based full-sky imaging polarimetry of rapidly changing skies and its use for polarimetric cloud detection.

    PubMed

    Horváth, Gábor; Barta, Andras; Gál, József; Suhai, Bence; Haiman, Ottó

    2002-01-20

    For elimination of the shortcomings of imaging polarimeters that take the necessary three pictures sequentially through linear-polarization filters, a three-lens, three-camera, full-sky imaging polarimeter was designed that takes the required pictures simultaneously. With this polarimeter, celestial polarization patterns can be measured even if rapid temporal changes occur in the sky: under cloudy sky conditions, or immediately after sunrise or prior to sunset. One of the possible applications of our polarimeter is the ground-based detection of clouds. With use of the additional information of the degree and the angle of polarization patterns of cloudy skies measured in the red (650 nm), green (550 nm), and blue (450 nm) spectral ranges, improved algorithms of radiometric cloud detection can be offered. We present a combined radiometric and polarimetric algorithm that performs the detection of clouds more efficiently and reliably as compared with an exclusively radiometric cloud-detection algorithm. The advantages and the limits of three-lens, three-camera, full-sky imaging polarimeters as well as the possibilities of improving our polarimetric cloud detection method are discussed briefly.

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

    PubMed

    Chen, Qiang; Chen, Yunhao; Jiang, Weiguo

    2016-07-30

    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.

  9. 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

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

    PubMed Central

    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. 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.

  12. 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

  13. 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...

  14. 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

  15. 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.

  16. 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

  17. 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

  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.

  19. 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.

  20. 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

  1. 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.

  2. Change Detection in Auditory Textures.

    PubMed

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

    2016-01-01

    Many natural sounds have spectrotemporal signatures only on a statistical level, e.g. wind, fire or rain. While their local structure is highly variable, the spectrotemporal statistics of these auditory textures can be used for recognition. This suggests the existence of a neural representation of these statistics. To explore their encoding, we investigated the detectability of changes in the spectral statistics in relation to the properties of the change. To achieve precise parameter control, we designed a minimal sound texture--a modified cloud of tones--which retains the central property of auditory textures: solely statistical predictability. Listeners had to rapidly detect a change in the frequency marginal probability of the tone cloud occurring at a random time.The size of change as well as the time available to sample the original statistics were found to correlate positively with performance and negatively with reaction time, suggesting the accumulation of noisy evidence. In summary we quantified dynamic aspects of change detection in statistically defined contexts, and found evidence of integration of statistical information.

  3. 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.

  4. 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.

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

    DOEpatents

    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.

  6. 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.

  7. 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.

  8. 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.

  9. Investigation of ionospheric TEC changes related to the 2008 Wenchuan earthquake based on statistic analysis and signal detection

    NASA Astrophysics Data System (ADS)

    Li, Jianyong; Meng, Guojie; Wang, Min; Liao, Hua; Shen, Xuhui

    2009-10-01

    Ionospheric TEC (total electron content) time series are derived from GPS measurements at 13 stations around the epicenter of the 2008 Wenchuan earthquake. Defining anomaly bounds for a sliding window by quartile and 2-standard deviation of TEC values, this paper analyzed the characteristics of ionospheric changes before and after the destructive event. The Neyman-Pearson signal detection method is employed to compute the probabilities of TEC abnormalities. Result shows that one week before the Wenchuan earthquake, ionospheric TEC over the epicenter and its vicinities displays obvious abnormal disturbances, most of which are positive anomalies. The largest TEC abnormal changes appeared on May 9, three days prior to the seismic event. Signal detection shows that the largest possibility of TEC abnormity on May 9 is 50.74%, indicating that ionospheric abnormities three days before the main shock are likely related to the preparation process of the M S8.0 Wenchuan earthquake.

  10. 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.

  11. 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.

  12. 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.

  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. 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.

  15. 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.

  16. Total least squares for anomalous change detection

    NASA Astrophysics Data System (ADS)

    Theiler, James; Matsekh, Anna M.

    2010-04-01

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

  17. 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

  18. 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.

  19. 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.

  20. Active change detection by pigeons and humans.

    PubMed

    Hagmann, Carl Erick; Cook, Robert G

    2013-10-01

    Detecting change is vital to both human and nonhuman animals' interactions with the environment. Using the go/no-go dynamic change detection task, we examined the capacity of four pigeons to detect changes in brightness of an area on a computer display. In contrast to our prior research, we reversed the response contingencies so that the animals had to actively inhibit pecking upon detecting change in brightness rather than its constancy. Testing eight rates of change revealed that this direct report change detection contingency produced results equivalent to the earlier indirect procedure. Corresponding tests with humans suggested that the temporal dynamics of detecting change were similar for both species. The results indicate the mechanisms of change detection in both pigeons and humans are organized in similar ways, although limitations in the operations of working memory may prevent pigeons from integrating information over the same time scale as humans.

  1. 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

  2. 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.

  3. 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.

  4. 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

  5. Study of vegetation index selection and changing detection thresholds in land cover change detection assessment using change vector analysis

    NASA Astrophysics Data System (ADS)

    Nguyen, Duy; Tran, Giang

    2012-07-01

    In recent years, Vietnamese rapidly developing economy has led to speedy changes in land cover. The study of changing detection of land cover plays an important role in making the strategy of the managers. There are two main approaches in changing detection research by using remote sensing and GIS: post- classification change detection analysis approach and pre-classification changing spectral determination approach. Each has their own different advantages and disadvantages. The second one is further divided into: Image Differencing, Multi-date Principal Component Analysis (MPCA); Change Vector Analysis (CVA). In this study, researchers introduce CVA method. This method is based on two important index to show the primary feature of land cover, such as: vegetation index (NDVI-) and barren land index (-BI). Ability to apply methods of CVA has been mentioned in the studies [1, 2, 3, and 4]. However, in these studies did not mention the NDVI index selection and changing detection threshold in changing detection assessment? This paper proposes application to solve these two problems.

  6. One new method for road data shape change detection

    NASA Astrophysics Data System (ADS)

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

    2009-10-01

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

  7. 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.

  8. 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

  9. T1ρ and T2 -based characterization of regional variations in intervertebral discs to detect early degenerative changes.

    PubMed

    Pandit, Prachi; Talbott, Jason F; Pedoia, Valentina; Dillon, William; Majumdar, Sharmila

    2016-08-01

    Lower back pain is one of the main contributors to morbidity and chronic disability in the United States. Despite the significance of the problem, it is still not well understood. There is a clear need for objective, non-invasive biomarkers to localize specific pain generators and identify early stage changes to enable reliable diagnosis and treatment. In this study we focus on intervertebral disc degeneration as a source of lower back pain. Quantitative imaging markers T1ρ and T2 have been shown to be promising techniques for in vivo diagnosis of biochemical degeneration in discs due to their sensitivity to macromolecular changes in proteoglycan content and collagen integrity. We describe a semi-automated technique for quantifying T1ρ and T2 relaxation time maps in the nucleus pulposus (NP) and the annulus fibrosus (AF) of the lumbar intervertebral discs. Compositional changes within the NP and AF associated with degeneration occur much earlier than the visually observable structural changes. The proposed technique rigorously quantifies these biochemical changes taking into account subtle regional variations to allow interpretation of early degenerative changes that are difficult to interpret with traditional MRI techniques and clinical subjective grading scores. T1ρ and T2 relaxation times in the NP decrease with degenerative severity in the disc. Moreover, standard deviation and texture measurements of these values show sharper and more significant changes during early degeneration compared to later degenerative stages. Our results suggest that future prospective studies should include automated T1ρ and T2 metrics as early biomarkers for disc degeneration-induced lower back pain. © 2016 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 34:1373-1381, 2016.

  10. T1ρ and T2 -based characterization of regional variations in intervertebral discs to detect early degenerative changes.

    PubMed

    Pandit, Prachi; Talbott, Jason F; Pedoia, Valentina; Dillon, William; Majumdar, Sharmila

    2016-08-01

    Lower back pain is one of the main contributors to morbidity and chronic disability in the United States. Despite the significance of the problem, it is still not well understood. There is a clear need for objective, non-invasive biomarkers to localize specific pain generators and identify early stage changes to enable reliable diagnosis and treatment. In this study we focus on intervertebral disc degeneration as a source of lower back pain. Quantitative imaging markers T1ρ and T2 have been shown to be promising techniques for in vivo diagnosis of biochemical degeneration in discs due to their sensitivity to macromolecular changes in proteoglycan content and collagen integrity. We describe a semi-automated technique for quantifying T1ρ and T2 relaxation time maps in the nucleus pulposus (NP) and the annulus fibrosus (AF) of the lumbar intervertebral discs. Compositional changes within the NP and AF associated with degeneration occur much earlier than the visually observable structural changes. The proposed technique rigorously quantifies these biochemical changes taking into account subtle regional variations to allow interpretation of early degenerative changes that are difficult to interpret with traditional MRI techniques and clinical subjective grading scores. T1ρ and T2 relaxation times in the NP decrease with degenerative severity in the disc. Moreover, standard deviation and texture measurements of these values show sharper and more significant changes during early degeneration compared to later degenerative stages. Our results suggest that future prospective studies should include automated T1ρ and T2 metrics as early biomarkers for disc degeneration-induced lower back pain. © 2016 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 34:1373-1381, 2016. PMID:27227485

  11. [Spatiotemporal dynamics of vegetation cover based on trajectory change detection: a case study in Dapeng Peninsula of Shenzhen].

    PubMed

    Liang, Yao-qin; Xie, Fang-yi; Li, Jing; Li, Gui-cai; Zeng, Hui

    2010-05-01

    By using the second-time developed ArcEngine component at pixel level, this paper studied the spatiotemporal dynamics of vegetation cover in the Dapeng Peninsula of Shenzhen, China in 1986-2007, and analyzed the characters and causes of the dynamics. To quantify this dynamics, the NDVI changes in 1986-2007 were extracted from 10 time-series TM/ETM+ remote sensing images, and the results showed that from 1986 to 2007, there were four trajectories of vegetation cover change in the Peninsula, including stable (a), stable-rising-stable (aba), stable-descending-stable (aca), and stable-descending-stable-rising-stable (acaba). The area with these four types occupied 71.54% of the total. Among the four types, type "a" was most common, occupying 1/3 of the study area, mainly in the mountains; and type "acaba" was the typical one, which was closely related to the deforestation and reforestation after the human disturbances of original vegetation. The areas at higher elevation or steeper slopes exhibited smaller vegetation change, mainly because of the constrained human disturbances. Timing of the vegetation cover change showed a relative stability in the mid-90s of 20th century, but a dramatic change after 2003, coinciding with the growth of Shenzhen City.

  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.

  13. Anger superiority effect for change detection and change blindness.

    PubMed

    Lyyra, Pessi; Hietanen, Jari K; Astikainen, Piia

    2014-11-01

    In visual search, an angry face in a crowd "pops out" unlike a happy or a neutral face. This "anger superiority effect" conflicts with views of visual perception holding that complex stimulus contents cannot be detected without focused top-down attention. Implicit visual processing of threatening changes was studied by recording event-related potentials (ERPs) using facial stimuli using the change blindness paradigm, in which conscious change detection is eliminated by presenting a blank screen before the changes. Already before their conscious detection, angry faces modulated relatively early emotion sensitive ERPs when appearing among happy and neutral faces, but happy faces only among neutral, not angry faces. Conscious change detection was more efficient for angry than happy faces regardless of background. These findings indicate that the brain can implicitly extract complex emotional information from facial stimuli, and the biological relevance of threatening contents can speed up their break up into visual consciousness.

  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. Change detection and change blindness in pigeons (Columba livia).

    PubMed

    Herbranson, Walter T; Trinh, Yvan T; Xi, Patricia M; Arand, Mark P; Barker, Michael S K; Pratt, Theodore H

    2014-05-01

    Change blindness is a phenomenon in which even obvious details in a visual scene change without being noticed. Although change blindness has been studied extensively in humans, we do not yet know if it is a phenomenon that also occurs in other animals. Thus, investigation of change blindness in a nonhuman species may prove to be valuable by beginning to provide some insight into its ultimate causes. Pigeons learned a change detection task in which pecks to the location of a change in a sequence of stimulus displays were reinforced. They were worse at detecting changes if the stimulus displays were separated by a brief interstimulus interval, during which the display was blank, and this primary result matches the general pattern seen in previous studies of change blindness in humans. A second experiment attempted to identify specific stimulus characteristics that most reliably produced a failure to detect changes. Change detection was more difficult when interstimulus intervals were longer and when the change was iterated fewer times.

  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. Change Point Detection in Correlation Networks.

    PubMed

    Barnett, Ian; Onnela, Jukka-Pekka

    2016-01-07

    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.

  18. Comparison of hyperspectral change detection algorithms

    NASA Astrophysics Data System (ADS)

    Pieper, M.; Manolakis, D.; Truslow, E.; Cooley, T.; Brueggeman, M.; Weisner, A.; Jacobson, J.

    2015-09-01

    There are a multitude of civilian and military applications for the detection of anomalous changes in hyper-spectral images. Anomalous changes occur when the material within a pixel is replaced. Environmental factors that change over time, such as illumination, will affect the radiance of all the pixels in a scene, despite the materials within remaining constant. The goal of an anomalous change detection algorithm is to suppress changes caused by the environment, and detect pixels where the materials within have changed. Anomalous change detection is a two step process. Two co-registered images of a scene are first transformed to maximize the overall correlation between the images, then an anomalous change detector (ACD) is applied to the transformed images. The transforms maximize the correlation between the two images to attenuate the environmental differences that distract from the anomalous changes of importance. Several categories of transforms with different optimization parameters are discussed and compared. One of two types of ACDs are then applied to the transformed images. The first ACD uses the difference of the two transformed images. The second concatenates the spectra of two images and uses an aggregated ACD. A comparison of the two ACD methods and their effectiveness with the different transforms is done for the first time.

  19. 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.

  20. 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.

  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. 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.

  5. Holistic processing improves change detection but impairs change identification.

    PubMed

    Mathis, Katherine M; Kahan, Todd A

    2014-10-01

    It has been just over a century since Gestalt psychologists described the factors that contribute to the holistic processing of visually presented stimuli. Recent research indicates that holistic processing may come at a cost; specifically, the perception of holistic forms may reduce the visibility of constituent parts. In the present experiment, we examined change detection and change identification accuracy with Kanizsa rectangle patterns that were arranged to either form a Gestalt whole or not. Results from an experiment with 62 participants support this trade-off in processing holistic forms. Holistic processing improved the detection of change but obstructed its identification. Results are discussed in terms of both their theoretical significance and their application in areas ranging from baggage screening and the detection of changes in radiological images to the systems that are used to generate composite images of perpetrators on the basis of eyewitness reports.

  6. 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.

  7. 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.

  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. Change-point detection for recursive Bayesian geoacoustic inversions.

    PubMed

    Tan, Bien Aik; Gerstoft, Peter; Yardim, Caglar; Hodgkiss, William S

    2015-04-01

    In order to carry out geoacoustic inversion in low signal-to-noise ratio (SNR) conditions, extended duration observations coupled with source and/or receiver motion may be necessary. As a result, change in the underlying model parameters due to time or space is anticipated. In this paper, an inversion method is proposed for cases when the model parameters change abruptly or slowly. A model parameter change-point detection method is developed to detect the change in the model parameters using the importance samples and corresponding weights that are already available from the recursive Bayesian inversion. If the model parameters change abruptly, a change-point will be detected and the inversion will restart with the pulse measurement after the change-point. If the model parameters change gradually, the inversion (based on constant model parameters) may proceed until the accumulated model parameter mismatch is significant and triggers the detection of a change-point. These change-point detections form the heuristics for controlling the coherent integration time in recursive Bayesian inversion. The method is demonstrated in simulation with parameters corresponding to the low SNR, 100-900 Hz linear frequency modulation pulses observed in the Shallow Water 2006 experiment [Tan, Gerstoft, Yardim, and Hodgkiss, J. Acoust. Soc. Am. 136, 1187-1198 (2014)].

  11. 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…

  12. 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.

  13. 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.

  14. 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.

  15. Optical detection of argon gas flow based on vibration-induced change in photoluminescence of a semiconducting single-walled carbon nanotube bundle.

    PubMed

    Kim, Hong-Seok; Kim, Woo-Jae; Strano, Michael S; Hanl, Jae-Hee

    2014-12-01

    In this work, we demonstrate that Ar gas flow can be optically detected using mechanical vibration of a semiconducting single-walled carbon nanotube (SWCNT) bundle as a platform. A change in the photoluminescence (PL) intensity was induced by out-of-focusing of the SWCNT bundle of interest due to vibration caused by the introduced gas stream, for which a gas flow control system was installed in an optical microscope. The PL intensity was found to change systemically with the Ar flow rates in a range of relatively large flow rate intervals [0.70 to 3.0 standard cubic liters per minute (SLM) with 0.1-0.5 SLM intervals] with a noticeable hysteresis. It was, however, difficult to obtain a detectable PL change in a range of very small flow rate intervals (0.67 to 0.70 SLM with a 0.01 SLM interval). The detailed results and underlying mechanism are discussed in detail.

  16. 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.

  17. 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.

  18. Detecting genetic responses to environmental change.

    PubMed

    Hoffmann, Ary A; Willi, Yvonne

    2008-06-01

    Changes in environmental conditions can rapidly shift allele frequencies in populations of species with relatively short generation times. Frequency shifts might be detectable in neutral genetic markers when stressful conditions cause a population decline. However, frequency shifts that are diagnostic of specific conditions depend on isolating sets of genes that are involved in adaptive responses. Shifts at candidate loci underlying adaptive responses and DNA regions that control their expression have now been linked to evolutionary responses to pollution, global warming and other changes. Conversely, adaptive constraints, particularly in physiological traits, are recognized through DNA decay in candidate genes. These approaches help researchers and conservation managers understand the power and constraints of evolution.

  19. Evaluation of object level change detection techniques

    NASA Astrophysics Data System (ADS)

    Irvine, John M.; Bergeron, Stuart; Hugo, Doug; O'Brien, Michael A.

    2007-04-01

    A variety of change detection (CD) methods have been developed and employed to support imagery analysis for applications including environmental monitoring, mapping, and support to military operations. Evaluation of these methods is necessary to assess technology maturity, identify areas for improvement, and support transition to operations. This paper presents a methodology for conducting this type of evaluation, discusses the challenges, and illustrates the techniques. The evaluation of object-level change detection methods is more complicated than for automated techniques for processing a single image. We explore algorithm performance assessments, emphasizing the definition of the operating conditions (sensor, target, and environmental factors) and the development of measures of performance. Specific challenges include image registration; occlusion due to foliage, cultural clutter and terrain masking; diurnal differences; and differences in viewing geometry. Careful planning, sound experimental design, and access to suitable imagery with image truth and metadata are critical.

  20. 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.

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

    DOE PAGES

    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

  2. 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.

  3. 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

  4. 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.

  5. 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.

  6. 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

  7. 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.

  8. 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.

  9. A novel video dataset for change detection benchmarking.

    PubMed

    Goyette, Nil; Jodoin, Pierre-Marc; Porikli, Fatih; Konrad, Janusz; Ishwar, Prakash

    2014-11-01

    Change detection is one of the most commonly encountered low-level tasks in computer vision and video processing. A plethora of algorithms have been developed to date, yet no widely accepted, realistic, large-scale video data set exists for benchmarking different methods. Presented here is a unique change detection video data set consisting of nearly 90 000 frames in 31 video sequences representing six categories selected to cover a wide range of challenges in two modalities (color and thermal infrared). A distinguishing characteristic of this benchmark video data set is that each frame is meticulously annotated by hand for ground-truth foreground, background, and shadow area boundaries-an effort that goes much beyond a simple binary label denoting the presence of change. This enables objective and precise quantitative comparison and ranking of video-based change detection algorithms. This paper discusses various aspects of the new data set, quantitative performance metrics used, and comparative results for over two dozen change detection algorithms. It draws important conclusions on solved and remaining issues in change detection, and describes future challenges for the scientific community. The data set, evaluation tools, and algorithm rankings are available to the public on a website and will be updated with feedback from academia and industry in the future.

  10. 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...

  11. 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.

  12. 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.

  13. PCA feature extraction for change detection in multidimensional unlabeled data.

    PubMed

    Kuncheva, Ludmila I; Faithfull, William J

    2014-01-01

    When classifiers are deployed in real-world applications, it is assumed that the distribution of the incoming data matches the distribution of the data used to train the classifier. This assumption is often incorrect, which necessitates some form of change detection or adaptive classification. While there has been a lot of work on change detection based on the classification error monitored over the course of the operation of the classifier, finding changes in multidimensional unlabeled data is still a challenge. Here, we propose to apply principal component analysis (PCA) for feature extraction prior to the change detection. Supported by a theoretical example, we argue that the components with the lowest variance should be retained as the extracted features because they are more likely to be affected by a change. We chose a recently proposed semiparametric log-likelihood change detection criterion that is sensitive to changes in both mean and variance of the multidimensional distribution. An experiment with 35 datasets and an illustration with a simple video segmentation demonstrate the advantage of using extracted features compared to raw data. Further analysis shows that feature extraction through PCA is beneficial, specifically for data with multiple balanced classes.

  14. Scene change detection for video retrieval on MPEG streams

    NASA Astrophysics Data System (ADS)

    Kang, Eung-Kwan; Kim, Sung-Joo; Jahng, SurngGabb; Song, Ho-Keun; Choi, Jong S.

    2000-05-01

    IN this paper, we propose a new scene change detection (SCD) algorithm, and also provide a novel video-indexing scheme for fast content-based browsing and retrieval in video databases. We detect scene changes from the MPEG video sequence, and extract key frames to represent contents of a shot. Then, we perform the video indexing by applying the rosette pattern to the extracted key frames, and retrieve them. Our SCD method is better than the conventional ones in terms of the SCD performance. Moreover, by applying the rosette pattern for indexing, we can remarkably reduce the number of pixels required to index and excellently retrieve the video scene.

  15. 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.

  16. 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.

  17. 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

  18. 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.

  19. 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.

  20. Detecting past changes of effective population size.

    PubMed

    Nikolic, Natacha; Chevalet, Claude

    2014-06-01

    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.

  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. 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.

  3. Environmental Change Detection Using Multi-Temporal SAR Imagery

    NASA Astrophysics Data System (ADS)

    Fazel, Mohammad A.; Homayouni, Saeid; Aghakarimi, Armin

    2013-04-01

    Monitoring of environmental phenomena in short-, mid- and long-term periods is the first step of any study or plan for natural resource management. As a result, detection and identification of the environmental changes became a main area of research for different applications. Remotely sensed data and especially Synthetic Aperture Radar (SAR) imagery thanks to its independence to weather conditions and sun illumination, and its spatial and temporal resolution ability is a valuable source of information for change detection analysis and provides reliable data for information extraction for various applications. In general, change detection methods are grouped into supervised and unsupervised methods. Supervised methods work based on multi-temporal land-cover mapping of satellite images. While, unsupervised techniques include the very simple idea of image differencing to more sophisticated statistical modeling of changes in images. Unsupervised methods because of their advantages are more important in many applications. In recent years, the use of kernel based methods in change detection applications became an interesting topic in remote sensing community. Kernel-based methods and machine learning algorithms are the unsupervised paradigms which introduced powerful tools to deal with nonlinear classification. In this paper, we have presented a fully unsupervised framework for detecting the Urmia Lake changes during 2007 to 2010. This method uses the kernel-based clustering technique. The kernel k-means algorithm separates the changes from no-change classes of speckle free images. This method is a non-linear algorithm which considers the contextual information. For this purpose, at first, difference maps are calculated from multi-temporal data. Then these maps are projected into a higher dimensional space by using kernel function. Finally an unsupervised k-means clustering algorithm is used to obtain change and no-change classes. The proposed methodology is applied to

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

    NASA Astrophysics Data System (ADS)

    Saur, Günter; Krüger, Wolfgang; Schumann, Arne

    2014-03-01

    Change detection is one of the most important tasks when using unmanned aerial vehicles (UAV) for video reconnaissance and surveillance. We address changes of short time scale, i.e. the observations are taken in time distances from several minutes up to a few hours. Each observation is a short video sequence acquired by the UAV in near-nadir view and the relevant changes are, e.g., recently parked or moved vehicles. In this paper we extend our previous approach of image differencing for single video frames to video mosaics. A precise image-to-image registration combined with a robust matching approach is needed to stitch the video frames to a mosaic. Additionally, this matching algorithm is applied to mosaic pairs in order to align them to a common geometry. The resulting registered video mosaic pairs are the input of the change detection procedure based on extended image differencing. A change mask is generated by an adaptive threshold applied to a linear combination of difference images of intensity and gradient magnitude. The change detection algorithm has to distinguish between relevant and non-relevant changes. Examples for non-relevant changes are stereo disparity at 3D structures of the scene, changed size of shadows, and compression or transmission artifacts. The special effects of video mosaicking such as geometric distortions and artifacts at moving objects have to be considered, too. In our experiments we analyze the influence of these effects on the change detection results by considering several scenes. The results show that for video mosaics this task is more difficult than for single video frames. Therefore, we extended the image registration by estimating an elastic transformation using a thin plate spline approach. The results for mosaics are comparable to that of single video frames and are useful for interactive image exploitation due to a larger scene coverage.

  5. Direct detection of ABCA1-dependent HDL formation based on lipidation-induced hydrophobicity change in apoA-I[S

    PubMed Central

    Omura, Risa; Nagao, Kohjiro; Kobayashi, Norihiro; Ueda, Kazumitsu; Saito, Hiroyuki

    2014-01-01

    ABCA1 mediates the efflux of cholesterol and phospholipids into apoA-I to form HDL, which is important in the prevention of atherosclerosis. To develop a novel method for the evaluation of HDL formation, we prepared an apoA-I-POLARIC by labeling the specific residue of an apoA-I variant with a hydrophobicity-sensitive fluorescence probe that detects the environmental change around apoA-I during HDL formation. apoA-I-POLARIC possesses the intact ABCA1-dependent HDL formation activity and shows 4.0-fold higher fluorescence intensity in HDL particles than in the lipid-free state. Incubation of apoA-I-POLARIC with ABCA1-expressing cells, but not ABCA1-non-expressing cells, caused a 1.7-fold increase in fluorescence intensity. Gel filtration analysis demonstrated that the increase in fluorescence intensity of apoA-I-POLARIC represents the amount of apoA-I incorporated into the discoidal HDL particles rather than the amount of secreted cholesterol. THP-1 macrophage-mediated HDL formation and inhibition of HDL formation by cyclosporine A could also be measured using apoA-I-POLARIC. Furthermore, HDL formation-independent lipid release induced by microparticle formation or cell death was not detected by apoA-I-POLARIC. These results demonstrate that HDL formation by ABCA1-expressing cells can be specifically detected by sensing hydrophobicity change in apoA-I, thus providing a novel method for assessing HDL formation and screening of the HDL formation modulator. PMID:25214539

  6. 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.

  7. 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.

  8. Detection of the onset of upper-limb movements based on the combined analysis of changes in the sensorimotor rhythms and slow cortical potentials

    NASA Astrophysics Data System (ADS)

    Ibáñez, J.; Serrano, J. I.; del Castillo, M. D.; Monge-Pereira, E.; Molina-Rueda, F.; Alguacil-Diego, I.; Pons, J. L.

    2014-10-01

    Objective. Characterizing the intention to move by means of electroencephalographic activity can be used in rehabilitation protocols with patients’ cortical activity taking an active role during the intervention. In such applications, the reliability of the intention estimation is critical both in terms of specificity ‘number of misclassifications’ and temporal accuracy. Here, a detector of the onset of voluntary upper-limb reaching movements based on the cortical rhythms and the slow cortical potentials is proposed. The improvement in detections due to the combination of these two cortical patterns is also studied. Approach. Upper-limb movements and cortical activity were recorded in healthy subjects and stroke patients performing self-paced reaching movements. A logistic regression combined the output of two classifiers: (i) a naïve Bayes classifier trained to detect the event-related desynchronization preceding the movement onset and (ii) a matched filter detecting the bereitschaftspotential. The proposed detector was compared with the detectors by using each one of these cortical patterns separately. In addition, differences between the patients and healthy subjects were analysed. Main results. On average, 74.5 ± 13.8% and 82.2 ± 10.4% of the movements were detected with 1.32 ± 0.87 and 1.50 ± 1.09 false detections generated per minute in the healthy subjects and the patients, respectively. A significantly better performance was achieved by the combined detector (as compared to the detectors of the two cortical patterns separately) in terms of true detections (p = 0.099) and false positives (p = 0.0083). Significance. A rationale is provided for combining information from cortical rhythms and slow cortical potentials to detect the onsets of voluntary upper-limb movements. It is demonstrated that the two cortical processes supply complementary information that can be summed up to boost the performance of the detector. Successful results have been also

  9. Water quality change detection: multivariate algorithms

    NASA Astrophysics Data System (ADS)

    Klise, Katherine A.; McKenna, Sean A.

    2006-05-01

    In light of growing concern over the safety and security of our nation's drinking water, increased attention has been focused on advanced monitoring of water distribution systems. The key to these advanced monitoring systems lies in the combination of real time data and robust statistical analysis. Currently available data streams from sensors provide near real time information on water quality. Combining these data streams with change detection algorithms, this project aims to develop automated monitoring techniques that will classify real time data and denote anomalous water types. Here, water quality data in 1 hour increments over 3000 hours at 4 locations are used to test multivariate algorithms to detect anomalous water quality events. The algorithms use all available water quality sensors to measure deviation from expected water quality. Simulated anomalous water quality events are added to the measured data to test three approaches to measure this deviation. These approaches include multivariate distance measures to 1) the previous observation, 2) the closest observation in multivariate space, and 3) the closest cluster of previous water quality observations. Clusters are established using kmeans classification. Each approach uses a moving window of previous water quality measurements to classify the current measurement as normal or anomalous. Receiver Operating Characteristic (ROC) curves test the ability of each approach to discriminate between normal and anomalous water quality using a variety of thresholds and simulated anomalous events. These analyses result in a better understanding of the deviation from normal water quality that is necessary to sound an alarm.

  10. Detecting Thermohaline Circulation Changes from Ocean properties

    NASA Astrophysics Data System (ADS)

    Hu, A.; Meehl, G. A.; Han, W.

    2003-12-01

    height gradient (SHG) between 30oS and 60oN in Atlantic. In HOS and CON, it shows a higher SSS contrast related to a stronger THC, but opposite in TRC. However, a colder NP (warmer NA) is related to a stronger THC for both forced runs. The SHG in Atlantic gives the most consistent result among these 3 runs, however, the linear regression shows a 17 Sv change in THC vs a change of one cm/deg-lat in SHG for CON and HOS, but a number increased to 29 for TRC. EOF analyses of the global SST indicate that the first EOF in CON, explaining 14% of the total variance, is a ENSO related pattern with a 2.6-year frequency. In the forced runs, this pattern becomes the second EOF with a frequency of 3.3- to 4.5-year, explaining 11% and 3% of the total variance for HOS and TRC, respectively. The first EOFs are a general cooling in Northern Hemisphere and warming in Southern Hemisphere in HOS (explaining 12% of the variance) and a global warming in TRC (explaining 70% of the variance). The general conclusion is that the proposed mechanisms used to detecting the THC strength are held for past and current climate condition, but not perfectly held for the future (at least in NCAR's CCSM2.0). The increase in atmospheric CO2 level seems changed the behavior of the THC, and causes a breakdown of many teleconnections between THC and others.

  11. 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.

  12. Angular velocity-based structural damage detection

    NASA Astrophysics Data System (ADS)

    Liao, Yizheng; Kiremidjian, Anne S.; Rajagopal, Ram; Loh, Chin-Hsiung

    2016-04-01

    Damage detection is an important application of structural health monitoring. With the recent development of sensing technology, additional information about structures, angular velocity, has become available. In this paper, the angular velocity signals obtained from gyroscopes are modeled as an autoregressive (AR) model. The damage sensitive features (DSFs) are defined as a function of the AR coefficients. It is found that the mean values of the DSF for the damaged and undamaged signals are different. Also, we show that the angular velocity- based AR model has a linear relationship with the acceleration-based AR model. To test the proposed damage detection method, the algorithm has been tested with the experimental data from a recent shake table test where the damage is introduced systemically. The results indicate that the change of DSF means is statistically significant, and the angular velocity-based DSFs are sensitive to damage.

  13. Techniques of UAV system land use changes detection application

    NASA Astrophysics Data System (ADS)

    Zhang, Youying; Cui, Hongxia

    2011-02-01

    The unmanned aerial vehicle( UAV) was able to acquire remote sensing images with low cost, precise and high spatial resolution information needed by management of Land use at desired time. The aim of this paper was to present an overview of the ongoing research on the potential and techniques of low-altitude UAV system for land use applications. The development of crucial subsystems consisting of the UAV platforms, multiple camera system, camera calibration and photogrammetric production, was introduced together. A procedure of images acquisition and photogrammetric processing was proposed. To detect land use changes, methods based on DSMs and DLG were discussed and adopted in this paper. Finally, analysis of land use research based UAVs was realized on real flight experiments of two study areas. The results of this study show that UAVs can be used successfully for land use change detection.

  14. 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.

  15. Bacteriophage-Based Pathogen Detection

    NASA Astrophysics Data System (ADS)

    Ripp, Steven

    Considered the most abundant organism on Earth, at a population approaching 1031, bacteriophage, or phage for short, mediate interactions with myriad bacterial hosts that has for decades been exploited in phage typing schemes for signature identification of clinical, food-borne, and water-borne pathogens. With over 5,000 phage being morphologically characterized and grouped as to susceptible host, there exists an enormous cache of bacterial-specific sensors that has more recently been incorporated into novel bio-recognition assays with heightened sensitivity, specificity, and speed. These assays take many forms, ranging from straightforward visualization of labeled phage as they attach to their specific bacterial hosts to reporter phage that genetically deposit trackable signals within their bacterial hosts to the detection of progeny phage or other uniquely identifiable elements released from infected host cells. A comprehensive review of these and other phage-based detection assays, as directed towards the detection and monitoring of bacterial pathogens, will be provided in this chapter.

  16. 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.

  17. 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.

  18. Multiscale object-oriented change detection over urban areas

    NASA Astrophysics Data System (ADS)

    Wang, Jianmei; Li, Deren

    2006-10-01

    Urban growth induces urban spatial expansion in many cities in China. There is a great need for up-to-date information for effective urban decision-making and sustainable development. Many researches have demonstrated that satellite images, especial high resolution images, are very suitable for urban growth studies. However, change detection technique is the key to keep current with the rapid urban growth rate, taking advantage of tremendous amounts of satellite data. In this paper, a multi-scale object-oriented change detection approach integrating GIS and remote sensing is introduced. Firstly, a subset of image is cropped based on existing parcel boundaries stored in GIS database, then a multi-scale watershed transform is carried out to obtain the image objects. The image objects are classified into different land cover types by supervised classification based on their spectral, geometry and texture attributes. Finally a rule-based system is set up to judge every parcel one by one whether or not change happened comparing to existing GIS land use types. In order to verify the application validity of the presented methodology, the rural-urban fringe of Shanghai in China with the support of QuickBird date and GIS is tested, the result shown that it is effective to detect illegal land use parcel.

  19. 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.

  20. 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.

  1. 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.

  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.

  3. Color changing photonic crystals detect blast exposure.

    PubMed

    Cullen, D Kacy; Xu, Yongan; Reneer, Dexter V; Browne, Kevin D; Geddes, James W; Yang, Shu; Smith, Douglas H

    2011-01-01

    Blast-induced traumatic brain injury (bTBI) is the "signature wound" of the current wars in Iraq and Afghanistan. However, with no objective information of relative blast exposure, warfighters with bTBI may not receive appropriate medical care and are at risk of being returned to the battlefield. Accordingly, we have created a colorimetric blast injury dosimeter (BID) that exploits material failure of photonic crystals to detect blast exposure. Appearing like a colored sticker, the BID is fabricated in photosensitive polymers via multi-beam interference lithography. Although very stable in the presence of heat, cold or physical impact, sculpted micro- and nano-structures of the BID are physically altered in a precise manner by blast exposure, resulting in color changes that correspond with blast intensity. This approach offers a lightweight, power-free sensor that can be readily interpreted by the naked eye. Importantly, with future refinement this technology may be deployed to identify soldiers exposed to blast at levels suggested to be supra-threshold for non-impact blast-induced mild TBI.

  4. Color changing photonic crystals detect blast exposure

    PubMed Central

    Cullen, D. Kacy; Xu, Yongan; Reneer, Dexter V.; Browne, Kevin D.; Geddes, James W.; Yang, Shu; Smith, Douglas H.

    2010-01-01

    Blast-induced traumatic brain injury (bTBI) is the “signature wound” of the current wars in Iraq and Afghanistan. However, with no objective information of relative blast exposure, warfighters with bTBI may not receive appropriate medical care and are at risk of being returned to the battlefield. Accordingly, we have created a colorimetric blast injury dosimeter (BID) that exploits material failure of photonic crystals to detect blast exposure. Appearing like a colored sticker, the BID is fabricated in photosensitive polymers via multi-beam interference lithography. Although very stable in the presence of heat, cold or physical impact, sculpted micro- and nano-structures of the BID are physically altered in a precise manner by blast exposure, resulting in color changes that correspond with blast intensity. This approach offers a lightweight, power-free sensor that can be readily interpreted by the naked eye. Importantly, with future refinement this technology may be deployed to identify soldiers exposed to blast at levels suggested to be supra-threshold for non-impact blast-induced mild TBI. PMID:21040795

  5. A semi-automated system for the assessment of toxicity to cultured mammalian cells based on detection of changes in staining properties.

    PubMed

    Barer, M R; Mann, G F; Drasar, B S

    1986-01-01

    We have established a semi-automated microtiter-based system for the quantification of dye binding to cultured eukaryotic cells. This system has been applied to the quantitation of toxic activities that disrupt cell monolayers and their neutralization. We have used this background as a basis for developing a detection and characterization system for activities that do not cause such gross toxicity. A prototype system has been established based on three staining procedures which in broad terms assess cellular dehydrogenase activity, and protein, DNA, and RNA content. The activity of several agents affecting cyclic nucleotide metabolism, including cholera toxin, on the staining properties of exposed monolayers has been assessed. Several new categories of cellular response are readily discernible in this latter system indicating that biological activities may be identified on the basis of the pattern of such responses. Since microtiter based systems show considerable potential for automation, it is suggested that the further development of this approach could offer a realistic prospect for numerous forms of toxicity testing on an industrial scale.

  6. 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…

  7. Automatic detection of LUCC based on SIFT

    NASA Astrophysics Data System (ADS)

    Ammala, Keonuchan; Liu, YaoLin; Tai, Ji Rong

    2009-10-01

    Land use cover change (LUCC) provide important information for environmental management and planning. It is one of the most prominent characteristics in globe environment change, and not only limited by natural factor, but also affected by the factor of social, economics, technique and histories. Traditionally, field surveys of land cover and land use are time consuming and costly and provide tabular statistics with out geographic location information. Remote sensing and GIS are the most modern technologies which have been widely used in the field of natural resource management and monitoring. Change detection in land use and updating information on the distribution and dynamics of land use have long term significance in policy making and scientific research. In this paper, we use multistpectral images of Spot period two different of time 2002 and 2007 for detection on LUCC base on Scale Invariant Feature Transform (SIFT) method. An automatic image matching technique based on SIFT was proposed by using the rotation and scale invariant property of SIFT. Keypoints are first extracted by searching over all scales and image locations, then the descriptors defined on the keypoint neighborhood are computed. The proposed algorithm is robust to translation, rotation, noise and scaling. Experimental results, urban is the most part of Huangpi area which have been changed.

  8. 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``.

  9. Instantaneous crack detection under changing operational and environmental variations

    NASA Astrophysics Data System (ADS)

    Kim, Seung Bum; Sohn, Hoon

    2007-04-01

    A new methodology of guided wave based nondestructive testing (NDT) is developed to detect crack damage in a thin metal structure without using prior baseline data or a predetermined decision boundary. In conventional guided wave based techniques, damage is often identified by comparing the "current" data obtained from a potentially damaged condition of a structure with the "past" baseline data collected at the pristine condition of the structure. However, it has been reported that this type of pattern comparison with the baseline data can lead to increased false alarms due to its susceptibility to varying operational and environmental conditions of the structure. To develop a more robust damage diagnosis technique, a new concept of NDT is conceived so that cracks can be detected even when the system being monitored is subjected to changing operational and environmental conditions. The proposed NDT technique utilizes the polarization characteristics of the piezoelectric wafers attached on the both sides of the thin metal structure. Crack formation creates Lamb wave mode conversion due to a sudden change in the thickness of the structure. Then, the proposed technique instantly detects the appearance of the crack by extracting this mode conversion from the measured Lamb waves, and the threshold value from damage classification is also obtained only from the current data set. Numerical and experimental results are presented to demonstrate the applicability of the proposed technique to instantaneous crack detection.

  10. Eye movements and display change detection during reading.

    PubMed

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

    2011-12-01

    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 are reported in which we combined eye movement data with signal detection analyses to investigate display change detection. On each trial, readers had to indicate if they saw a display change in addition to reading for meaning. On half the trials the display change occurred during the saccade (immediate condition); on the other half, it was slowed by 15-25 ms (delay condition) to increase the likelihood that a change would be detected. Sentences were presented in an alternating case fashion allowing us to investigate the influence of both letter identity and case. In the immediate condition, change detection was higher when letters changed than when case changed corroborating findings that word processing utilizes abstract (case independent) letter identities. However, in the delay condition (where d' was much higher than the immediate condition), detection was equal for letter and case changes. The results of both experiments indicate that sensitivity to display changes was related to how close the eyes were to the invalid preview on the fixation prior to the display change, as well as the timing of the completion of this change relative to the start of the post-change fixation.

  11. Neural network for change detection of remotely sensed imagery

    NASA Astrophysics Data System (ADS)

    Chen, C. F.; Chen, Kun S.; Chang, J. S.

    1995-11-01

    The use of a neural network for determining the change of landcover/land-use with remotely sensed data is proposed. In this study, a single image contains both spectral and temporal information is created from a multidate satellite imagery. The proposed change detection method can be divided into two main steps: training data selection and change detection. At the training step, the training set, basically consists of the classes of no-change and possible change data, is obtained from the composited image. Then the training data is used to input the neural network and obtain the network's weights. At the change detection step, the network's weights is employed to detect the change and no-change classes in the combined image. The proposed method is tested using a multidate SPOT imageries and a satisfied change pattern detection is obtained.

  12. Site change detection for RADIUS using thermophysical algebraic invariants

    NASA Astrophysics Data System (ADS)

    Nandhakumar, Nagaraj; Michel, Johnathan D.; Arnold, D. Gregory; Velten, Vincent J.; Tsihrintzis, George A.

    1996-02-01

    Research on the formulation of invariant features for model-based object recognition has mostly been concerned with geometric constructs either of the object or in the imaging process. We describe a new method that identifies invariant features computed from long wave infrared (LWIR) imagery. These features are called thermophysical invariants and depend primarily on the material composition of the object. Features are defined that are functions of only the thermophysical properties of the imaged materials. A physics-based model is derived from the principle of conservation of energy applied at the surface of the imaged regions. A linear form of the model is used to derive features that remain constant despite changes in scene parameters/driving conditions. Simulated and real imagery, as well as ground truth thermo-couple measurements were used to test the behavior of such features. A method of change detection in outdoor scenes is investigated. The invariants are used to detect when a hypothesized material no longer exists at a given location. For example, one can detect when a patch of clay/gravel has been replaced with concrete at a given site. This formulation yields promising results, but it can produce large values outside a normally small range. Therefore, we adopt a new feature classification algorithm based on the theories of symmetric alpha- stable (S(alpha) S) distributions. We show that symmetric, alpha-stable distributions model the thermophysical invariant data much better than the Gaussian model and suggest a classifier with superior performance.

  13. 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.

  14. 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.

  15. 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

  16. 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.

  17. 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

  18. 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.

  19. 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.

  20. 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

  1. Detecting Holocene changes in thermohaline circulation

    PubMed Central

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

    2000-01-01

    Throughout the last glacial cycle, reorganizations of deep ocean water masses were coincident with rapid millennial-scale changes in climate. Climate changes have been less severe during the present interglacial, but evidence for concurrent deep ocean circulation change is ambiguous. PMID:10677463

  2. 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.

  3. Change Detection in Naturalistic Pictures among Children with Autism

    ERIC Educational Resources Information Center

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

    2009-01-01

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

  4. 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.

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

    PubMed

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

    2014-08-01

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

  6. 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.

  7. 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

  8. 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.

  9. 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.

  10. Is a pre-change object representation weakened under correct detection of a change?

    PubMed

    Yeh, Yei-Yu; Yang, Cheng-Ta

    2009-03-01

    We investigated whether a pre-change representation is inhibited or weakened under correct change detection. Two arrays of six objects were rapidly presented for change detection in three experiments. After detection, the perceptual identification of degraded stimuli was tested in Experiments 1 and 2. The weakening of a pre-change representation was not observed under correct detection. The repetition priming effect was observed for a pre-change object and the magnitude was equivalent to the effect for a post-change object. Under change blindness, repetition priming for a pre-change representation was observed when detection did not require report of location in Experiment 1 and was not observed when location was required to be reported in Experiment 2. The results of Experiment 3 showed that a pre-change representation was recognized at a higher rate under correct detection than under change blindness, reflecting a stronger rather than a weaker pre-change representation in the former context.

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

    PubMed

    Lu, Dengsheng; Batistella, Mateus; Moran, Emilio

    2008-01-01

    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.

  12. 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.

  13. 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.

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

    NASA Astrophysics Data System (ADS)

    Wohlberg, Brendt; Theiler, James

    2010-01-01

    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.

  15. Occupancy change detection system and method

    DOEpatents

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

    2009-09-01

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

  16. Detecting Temporal Change in Watershed Nutrient Yields

    NASA Astrophysics Data System (ADS)

    Wickham, James D.; Wade, Timothy G.; Riitters, Kurt H.

    2008-08-01

    Meta-analyses reveal that nutrient yields tend to be higher for watersheds dominated by anthropogenic uses (e.g., urban, agriculture) and lower for watersheds dominated by natural vegetation. One implication of this pattern is that loss of natural vegetation will produce increases in watershed nutrient yields. Yet, the same meta-analyses also reveal that, absent land-cover change, watershed nutrient yields vary from one year to the next due to many exogenous factors. The interacting effects of land cover and exogenous factors suggest nutrient yields should be treated as distributions, and the effect of land-cover change should be examined by looking for significant changes in the distributions. We compiled nutrient yield distributions from published data. The published data included watersheds with homogeneous land cover that typically reported two or more years of annual nutrient yields for the same watershed. These data were used to construct statistical models, and the models were used to estimate changes in the nutrient yield distributions as a result of land-cover change. Land-cover changes were derived from the National Land Cover Database (NLCD). Total nitrogen (TN) yield distributions increased significantly for 35 of 1550 watersheds and decreased significantly for 51. Total phosphorus (TP) yield distributions increased significantly for 142 watersheds and decreased significantly for 17. The amount of land-cover change required to produce significant shifts in nutrient yield distributions was not constant. Small land-cover changes led to significant shifts in nutrient yield distributions when watersheds were dominated by natural vegetation, whereas much larger land-cover changes were needed to produce significant shifts when watersheds were dominated by urban or agriculture. We discuss our results in the context of the Clean Water Act.

  17. Detecting temporal change in watershed nutrient yields.

    PubMed

    Wickham, James D; Wade, Timothy G; Riitters, Kurt H

    2008-08-01

    Meta-analyses reveal that nutrient yields tend to be higher for watersheds dominated by anthropogenic uses (e.g., urban, agriculture) and lower for watersheds dominated by natural vegetation. One implication of this pattern is that loss of natural vegetation will produce increases in watershed nutrient yields. Yet, the same meta-analyses also reveal that, absent land-cover change, watershed nutrient yields vary from one year to the next due to many exogenous factors. The interacting effects of land cover and exogenous factors suggest nutrient yields should be treated as distributions, and the effect of land-cover change should be examined by looking for significant changes in the distributions. We compiled nutrient yield distributions from published data. The published data included watersheds with homogeneous land cover that typically reported two or more years of annual nutrient yields for the same watershed. These data were used to construct statistical models, and the models were used to estimate changes in the nutrient yield distributions as a result of land-cover change. Land-cover changes were derived from the National Land Cover Database (NLCD). Total nitrogen (TN) yield distributions increased significantly for 35 of 1550 watersheds and decreased significantly for 51. Total phosphorus (TP) yield distributions increased significantly for 142 watersheds and decreased significantly for 17. The amount of land-cover change required to produce significant shifts in nutrient yield distributions was not constant. Small land-cover changes led to significant shifts in nutrient yield distributions when watersheds were dominated by natural vegetation, whereas much larger land-cover changes were needed to produce significant shifts when watersheds were dominated by urban or agriculture. We discuss our results in the context of the Clean Water Act. PMID:18446405

  18. Automatic background updating for video-based vehicle detection

    NASA Astrophysics Data System (ADS)

    Hu, Chunhai; Li, Dongmei; Liu, Jichuan

    2008-03-01

    Video-based vehicle detection is one of the most valuable techniques for the Intelligent Transportation System (ITS). The widely used video-based vehicle detection technique is the background subtraction method. The key problem of this method is how to subtract and update the background effectively. In this paper an efficient background updating scheme based on Zone-Distribution for vehicle detection is proposed to resolve the problems caused by sudden camera perturbation, sudden or gradual illumination change and the sleeping person problem. The proposed scheme is robust and fast enough to satisfy the real-time constraints of vehicle detection.

  19. 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.

  20. 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

  1. A Dual-Process Account of Auditory Change Detection

    ERIC Educational Resources Information Center

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

    2010-01-01

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

  2. 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

  3. Change detection for objects on surfaces slanted in depth.

    PubMed

    Ozkan, Kerem; Braunstein, Myron L

    2010-09-15

    Change detection for objects associated with a surface extended in depth might be more difficult than for a frontal surface if it is easier to shift attention within a frontal surface. On the other hand, previous research has shown that ground surfaces have a special role in organizing the 3-D layout of objects shown against scene backgrounds. In the current study, we examined whether a frontal background or a ground surface background would result in superior change detection performance using a change detection flicker paradigm. In the first experiment, we considered whether background slant affects change detection performance. In Experiment 2, we examined the effect of height in the image on change detection performance. In Experiment 3, we examined change detection performance on slanted ceiling surfaces. The results of these experiments indicate that change detection is more efficient on near-ground planes than on surfaces at intermediate slants or ceiling surfaces. This suggests that any superiority of frontal plane backgrounds in a change detection task may be equivalent to the superiority of a near-ground plane in organizing a scene, with the lowest level of performance occurring for surfaces that are not frontal but further from a ground surface orientation.

  4. 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.

  5. Detection of the change point in oxygen uptake during an incremental exercise test using recursive residuals: relationship to the plasma lactate accumulation and blood acid base balance.

    PubMed

    Zoladz, J A; Szkutnik, Z; Majerczak, J; Duda, K

    1998-09-01

    The purpose of this study was to develop a method to determine the power output at which oxygen uptake (VO2) during an incremental exercise test begins to rise non-linearly. A group of 26 healthy non-smoking men [mean age 22.1 (SD 1.4) years, body mass 73.6 (SD 7.4) kg, height 179.4 (SD 7.5) cm, maximal oxygen uptake (VO2max) 3.726 (SD 0.363) l x min(-1)], experienced in laboratory tests, were the subjects in this study. They performed an incremental exercise test on a cycle ergometer at a pedalling rate of 70 rev x min(-1). The test started at a power output of 30 W, followed by increases amounting to 30 W every 3 min. At 5 min prior to the first exercise intensity, at the end of each stage of exercise protocol, blood samples (1 ml each) were taken from an antecubital vein. The samples were analysed for plasma lactate concentration [La]pl, partial pressure of O2 and CO2 and hydrogen ion concentration [H+]b. The lactate threshold (LT) in this study was defined as the highest power output above which [La-]pl showed a sustained increase of more than 0.5 mmol x l(-1) x step(-1). The VO2 was measured breath-by-breath. In the analysis of the change point (CP) of VO2 during the incremental exercise test, a two-phase model was assumed for the 3rd-min-data of each step of the test: Xi = at(i) + b + epsilon(i) for i = 1,2, ..., T, and E(Xi) > at(i) + b for i = T + 1, ..., n, where X1, ..., Xn are independent and epsilon(i) approximately N(0, sigma2). In the first phase, a linear relationship between VO2 and power output was assumed, whereas in the second phase an additional increase in VO2 above the values expected from the linear model was allowed. The power output at which the first phase ended was called the change point in oxygen uptake (CP-VO2). The identification of the model consisted of two steps: testing for the existence of CP and estimating its location. Both procedures were based on suitably normalised recursive residuals. We showed that in 25 out of 26 subjects

  6. Change magnitude does not guide attention in an object change detection task.

    PubMed

    Favelle, Simone K; Palmisano, Stephen

    2015-01-01

    Investigations of change detection consistently reveal an effect of change magnitude: changes involving more object parts are detected more easily than those involving fewer parts. Whether large changes improve detection by providing stronger preattentive signals to the change location is subject to debate. We report a cued object change detection experiment that tested this hypothesis while controlling for stimulus familiarity, semantic knowledge, and change type (addition versus deletion). We found strong magnitude effects regardless of whether trials were validly or invalidly cued. The size of the cueing effects, which were exhibited for all the change magnitudes examined, did not decrease with the number of parts changing. These findings provide little support for a preattentive guidance hypothesis and instead support the thesis that change detection requires attention.

  7. Multiplexed detection of molecular biomarkers with phase-change nanoparticles

    PubMed Central

    Su, Ming

    2014-01-01

    This review describes a new biosensing method based on nanoparticles of solid-to-liquid phase-change materials, in which a panel of metallic nanoparticles (metals and eutectic alloys) that have different compositions and melting temperatures are used as thermal reporters. Each type of nanoparticle will be conjugated to a ligand that can specifically bind to one type of molecular biomarker (protein or DNA) and then immobilized onto a substrate that is comodified with multiple ligands by forming sandwiched antibody–antigen complexes or DNA double helices. After removing unbound nanoparticles by washing, the nature and concentration of the biomarkers are determined by detecting the melting temperature and fusion enthalpy of the nanoparticles using differential scanning calorimetry. Furthermore, an even larger panel of thermal barcodes can be formed by encapsulating selected phase-change nanoparticles inside non-melting shells, such as silica, where each microparticle will have a characteristic signature that can be determined from its thermal signatures. PMID:23394155

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

    PubMed

    Xu, Yuan; Ding, Kun; Huo, Chunlei; Zhong, Zisha; Li, Haichang; Pan, Chunhong

    2015-01-01

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

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

    PubMed Central

    Xu, Yuan; Ding, Kun; Huo, Chunlei; Zhong, Zisha; Li, Haichang; Pan, Chunhong

    2015-01-01

    Very high resolution (VHR) image change detection is challenging due to the low discriminative ability of change feature and the difficulty of change decision in utilizing the multilevel contextual information. Most change feature extraction techniques put emphasis on the change degree description (i.e., in what degree the changes have happened), while they ignore the change pattern description (i.e., how the changes changed), which is of equal importance in characterizing the change signatures. Moreover, the simultaneous consideration of the classification robust to the registration noise and the multiscale region-consistent fusion is often neglected in change decision. To overcome such drawbacks, in this paper, a novel VHR image change detection method is proposed based on sparse change descriptor and robust discriminative dictionary learning. Sparse change descriptor combines the change degree component and the change pattern component, which are encoded by the sparse representation error and the morphological profile feature, respectively. Robust change decision is conducted by multiscale region-consistent fusion, which is implemented by the superpixel-level cosparse representation with robust discriminative dictionary and the conditional random field model. Experimental results confirm the effectiveness of the proposed change detection technique. PMID:25918748

  10. 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.

  11. Online scene change detection of multicast (MBone) video

    NASA Astrophysics Data System (ADS)

    Zhou, Wensheng; Shen, Ye; Vellaikal, Asha; Kuo, C.-C. Jay

    1998-10-01

    Many multimedia applications, such as multimedia data management systems and communication systems, require efficient representation of multimedia content. Thus semantic interpretation of video content has been a popular research area. Currently, most content-based video representation involves the segmentation of video based on key frames which are generated using scene change detection techniques as well as camera/object motion. Then, video features can be extracted from key frames. However most of such research performs off-line video processing in which the whole video scope is known as a priori which allows multiple scans of the stored video files during video processing. In comparison, relatively not much research has been done in the area of on-line video processing, which is crucial in video communication applications such as on-line collaboration, news broadcasts and so on. Our research investigates on-line real-time scene change detection of multicast video over the Internet. Our on-line processing system are designed to meet the requirements of real-time video multicasting over the Internet and to utilize the successful video parsing techniques available today. The proposed algorithms extract key frames from video bitstreams sent through the MBone network, and the extracted key frames are multicasted as annotations or metadata over a separate channel to assist in content filtering such as those anticipated to be in use by on-line filtering proxies in the Internet. The performance of the proposed algorithms are demonstrated and discussed in this paper.

  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. Spatiotemporal quantile regression for detecting distributional changes in environmental processes.

    PubMed

    Reich, Brian J

    2012-08-01

    Climate change may lead to changes in several aspects of the distribution of climate variables, including changes in the mean, increased variability, and severity of extreme events. In this paper, we propose using spatiotemporal quantile regression as a flexible and interpretable method for simultaneously detecting changes in several features of the distribution of climate variables. The spatiotemporal quantile regression model assumes that each quantile level changes linearly in time, permitting straight-forward inference on the time trend for each quantile level. Unlike classical quantile regression which uses model-free methods to analyze a single quantile or several quantiles separately, we take a model-based approach which jointly models all quantiles, and thus the entire response distribution. In the spatiotemporal quantile regression model, each spatial location has its own quantile function that evolves over time, and the quantile functions are smoothed spatially using Gaussian process priors. We propose a basis expansion for the quantile function that permits a closed-form for the likelihood, and allows for residual correlation modeling via a Gaussian spatial copula. We illustrate the methods using temperature data for the southeast US from the years 1931-2009. For these data, borrowing information across space identifies more significant time trends than classical non-spatial quantile regression. We find a decreasing time trend for much of the spatial domain for monthly mean and maximum temperatures. For the lower quantiles of monthly minimum temperature, we find a decrease in Georgia and Florida, and an increase in Virginia and the Carolinas.

  14. Long-term memory guidance of visuospatial attention in a change-detection paradigm.

    PubMed

    Rosen, Maya L; Stern, Chantal E; Somers, David C

    2014-01-01

    Visual task performance is generally stronger in familiar environments. One reason for this familiarity benefit is that we learn where to direct our visual attention and effective attentional deployment enhances performance. Visual working memory plays a central role in supporting long-term memory guidance of visuospatial attention. We modified a change detection task to create a new paradigm for investigating long-term memory guidance of attention. During the training phase, subjects viewed images in a flicker paradigm and were asked to detect between one and three changes in the images. The test phase required subjects to detect a single change in a one-shot change detection task in which they held all possible locations of changes in visual working memory and deployed attention to those locations to determine if a change occurred. Subjects detected significantly more changes in images for which they had been trained to detect the changes, demonstrating that memory of the images guided subjects in deploying their attention. Moreover, capacity to detect changes was greater for images that had multiple changes during the training phase. In Experiment 2, we observed that capacity to detect changes for the 3-studied change condition increased significantly with more study exposures and capacity was significantly higher than 1, indicating that subjects were able to attend to more than one location. Together, these findings suggest memory and attentional systems interact via working memory such that long-term memory can be used to direct visual spatial attention to multiple locations based on previous experience.

  15. Synthetic circuit for exact adaptation and fold-change detection.

    PubMed

    Kim, Jongmin; Khetarpal, Ishan; Sen, Shaunak; Murray, Richard M

    2014-05-01

    Biological organisms use their sensory systems to detect changes in their environment. The ability of sensory systems to adapt to static inputs allows wide dynamic range as well as sensitivity to input changes including fold-change detection, a response that depends only on fold changes in input, and not on absolute changes. This input scale invariance underlies an important strategy for search that depends solely on the spatial profile of the input. Synthetic efforts to reproduce the architecture and response of cellular circuits provide an important step to foster understanding at the molecular level. We report the bottom-up assembly of biochemical systems that show exact adaptation and fold-change detection. Using a malachite green aptamer as the output, a synthetic transcriptional circuit with the connectivity of an incoherent feed-forward loop motif exhibits pulse generation and exact adaptation. A simple mathematical model was used to assess the amplitude and duration of pulse response as well as the parameter regimes required for fold-change detection. Upon parameter tuning, this synthetic circuit exhibits fold-change detection for four successive rounds of two-fold input changes. The experimental realization of fold-change detection circuit highlights the programmability of transcriptional switches and the ability to obtain predictive dynamical systems in a cell-free environment for technological applications.

  16. Detecting land-use/land-cover change in rural-urban fringe areas using extended change-vector analysis

    NASA Astrophysics Data System (ADS)

    He, Chunyang; Wei, Anni; Shi, Peijun; Zhang, Qiaofeng; Zhao, Yuanyuan

    2011-08-01

    Detecting land-use/land-cover (LULC) changes in rural-urban fringe areas (RUFAs) timely and accurately using satellite imagery is essential for land-use planning and management in China. Although traditional spectral-based change-vector analysis (CVA) can effectively detect LULC change in many cases, it encounters difficulties in RUFAs because of deficiencies in the spectral information of satellite images. To detect LULC changes in RUFAs effectively, this paper proposes an extended CVA approach that incorporates textural change information into the traditional spectral-based CVA. The extended CVA was applied to three different pilot RUFAs in China with different remotely sensed data, including Landsat Thematic Mapper (TM), China-Brazil Earth Resources Satellite (CBERS) and Advanced Land Observing Satellite (ALOS) images. The results demonstrated the improvement of the extended CVA compared to the traditional spectral-based CVA with the overall accuracy increased between 4.66% and 8.00% and the kappa coefficient increased between 0.10 and 0.15, respectively. The advantage of the extended CVA lies in its integration of both spectral and textural change information to detect LULC changes, allowing for effective discrimination of LULC changes that are spectrally similar but texturally different in RUFAs. The extended CVA has great potential to be widely used for LULC-change detection in RUFAs, which are often heterogeneous and fragmental in nature, with rich textural information.

  17. 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.

  18. High-Sensitivity Surface-Enhanced Raman Scattering (SERS) Substrate Based on a Gold Colloid Solution with a pH Change for Detection of Trace-Level Polycyclic Aromatic Hydrocarbons in Aqueous Solution.

    PubMed

    Shi, Xiaofeng; Liu, Shu; Han, Xiaohong; Ma, Jun; Jiang, Yongchao; Yu, Guifeng

    2015-05-01

    In this study, a gold colloid solution whose parameters were optimized, and without any surfactants, was developed as a surface-enhanced Raman scattering (SERS) substrate for the detection of trace-level polycyclic aromatic hydrocarbons (PAHs). A gold colloid solution with 57 nm gold particles and pH 13 was prepared to be the SERS substrate. It had impressive enhancement that was two orders of magnitude higher than that of a gold colloid solution with 57 nm gold particles and without pH change (pH 6). Even with a compact field-based Raman spectrometer, naphthalene, phenanthrene, anthracene, fluoranthene, and pyrene were detected, with limits of detection at 6.8 nM, 3.4 nM, 1.8 nM, 0.68 nM (680 pM), and 0.44 nM (440 pM), respectively. The significant enhancement was ascribed to an electromagnetic mechanism and a charge-transfer mechanism. Quantitative analyses for these five PAHs in water were also performed. The SERS intensities of PAHs were found to have good linear dependence relations with the concentrations in low concentration. This high-sensitivity, easily prepared substrate offers a promising technology for the quantitative detection of trace-level PAHs.

  19. 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.

  20. A network of superconducting gravimeters detects submicrogal coseismic gravity changes.

    PubMed

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

    2004-10-15

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

  1. 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).

  2. 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

  3. The Nature of Change Detection and Online Representations of Scenes

    ERIC Educational Resources Information Center

    Ryan,J ennifer D.; Cohen, Neal J.

    2004-01-01

    This article provides evidence for implicit change detection and for the contribution of multiple memory sources to online representations. Multiple eye-movement measures distinguished original from changed scenes, even when college students had no conscious awareness for the change. Patients with amnesia showed a systematic deficit on 1 class of…

  4. 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.

  5. 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.

  6. 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…

  7. 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.

  8. 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

  9. 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.

  10. 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.

  11. 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.

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

    PubMed

    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.

  13. 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.

  14. 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.

  15. 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.

  16. 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

  17. Electrophysiological evidence for different types of change detection and change blindness.

    PubMed

    Busch, Niko A; Fründ, Ingo; Herrmann, Christoph S

    2010-08-01

    Numerous studies have demonstrated that observers often fail to notice large changes in visual scenes, a phenomenon known as change blindness. Some experiments have suggested that phenomenological experience in change blindness experiments is more diverse than the common distinction between change detection and change blindness allows to resolve. Recently, it has been debated whether changes in visual scenes can be detected ("sensed") without a corresponding perception of the changing object ("seeing") and whether these phenomena build on fundamentally different perceptual processes. The present study investigated whether phenomenologically different perceptual processes such as sensing and seeing rely on different or similar neural processes. We studied ERP effects of visual change processing (as compared to change blindness) when observers merely detected the presence of a change ("sensing") and when they identified the changing object in addition to detection ("seeing"). Although the visual awareness negativity (VAN)/selection negativity was similar for detection with and without identification, a change-related positivity and the N2pc contralateral to changes were found exclusively when the change was fully identified. This finding indicates that change identification requires perceptual and neural processes that are not involved in mere detection. In a second experiment, we demonstrated that the VAN and N2pc effects are similar to effects of selective attention in a visual search task. By contrast, the change-related positivity was specific for conscious processing of visual changes. The results suggest that changes can be detected ("sensed") without perception of the changing object. Furthermore, sensing and seeing seem to rely on different neural processes and seem to constitute different types of visual perception. These findings bear implications for how different categories of visual awareness are related to different stages in visual processing.

  18. Moving target detection algorithm based on Gaussian mixture model

    NASA Astrophysics Data System (ADS)

    Wang, Zhihua; Kai, Du; Zhang, Xiandong

    2013-07-01

    In real-time video surveillance system, background noise and disturbance for the detection of moving objects will have a significant impact. The traditional Gaussian mixture model;GMM&;has strong adaptive various complex background ability, but slow convergence speed and vulnerable to illumination change influence. the paper proposes an improved moving target detection algorithm based on Gaussian mixture model which increase the convergence rate of foreground to the background model transformation and introducing the concept of the changing factors, through the three frame differential method solved light mutation problem. The results show that this algorithm can improve the accuracy of the moving object detection, and has good stability and real-time.

  19. 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.

  20. Glacier Change Detection in the Hindu Kush of Afghanistan

    NASA Astrophysics Data System (ADS)

    Shroder, J. F.; Bishop, M. P.

    2004-12-01

    A half century of intermittently collected cryospheric and hydrologic data in Afghanistan has involved diverse field surveys, aerial photography, and satellite imagery that enable change detection in the war-torn, drought-stricken region. Afghanistan relies heavily upon snow-and ice-melt for vital irrigation and ground-water recharge, yet the past two decades of war have only exacerbated the originally already deficient information collection and analysis of such data. Glacier field studies and base-line inventory work initiated in the pre-war 1960-1970 period are now providing limited change detection information for the vital physical analysis necessary in the reconstruction of the country. Five case study areas were selected for renewed assessment over the intervening half century, from the western-most ice masses of the Koh-i-Foladi region in central Afghanistan, through the Mir Samir and Sakhi regions of the central Hindu Kush, to the Keshnikhan and Pamir areas of the Wakhan Corridor. Certain incompatibilities or ambiguities exist between Soviet-era and Western-derived data sets. In general, however, glaciers of Afghanistan are continuing to downwaste and retreat, with smaller ice masses disappearing altogether, presumably as the climatic snowline continues to rise above the peaks, a trend first noticed in the 1960s. Glacier survival in the lower central areas is now in part determined by topographic shielding from solar radiation high in shadowed cirques, or being preserved beneath increasing debris covers, whereas in the higher regions to the northeast, fewer changes to the larger, higher altitude glaciers are apparent. Renewed assessment of all Afghanistan glaciers is now underway as a part of the USGS- and NASA-supported GLIMS (Global Land-Ice Measurements from Space) project, and is viewed as an important element in the primary geodata collection and hazard assessment necessary for aiding in rebuilding the infrastructure of the beleaguered nation.

  1. 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.

  2. An Intrusion Detection Algorithm Based On NFPA

    NASA Astrophysics Data System (ADS)

    Anming, Zhong

    A process oriented intrusion detection algorithm based on Probabilistic Automaton with No Final probabilities (NFPA) is introduced, system call sequence of process is used as the source data. By using information in system call sequence of normal process and system call sequence of anomaly process, the anomaly detection and the misuse detection are efficiently combined. Experiments show better performance of our algorithm compared to the classical algorithm in this field.

  3. 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.

  4. Intelligent-based Structural Damage Detection Model

    NASA Astrophysics Data System (ADS)

    Lee, Eric Wai Ming; Yu, Kin Fung

    2010-05-01

    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.

  5. Design of fire detection equipment based on ultraviolet detection technology

    NASA Astrophysics Data System (ADS)

    Liu, Zhenji; Liu, Jin; Chu, Sheng; Ping, Chao; Yuan, Xiaobing

    2015-03-01

    Utilized the feature of wide bandgap semiconductor of MgZnO, researched and developed a kind of Mid-Ultraviolet-Band(MUV) ultraviolet detector which has passed the simulation experiment in the sun circumstance. Based on the ultraviolet detector, it gives out a design scheme of gun-shot detection device, which is composed of twelve ultraviolet detectors, signal amplifier, processor, annunciator , azimuth indicator and the bracket. Through Analysing the feature of solar blind, ultraviolet responsivity, fire feature of gunshots and detection distance, the feasibility of this design scheme is proved.

  6. 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.

  7. 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.

  8. Evaluating coverage changes in national parks using a hybrid change detection algorithm and remote sensing

    NASA Astrophysics Data System (ADS)

    Ghofrani, Zahra; Mokhtarzade, Mehdi; Reza Sahebi, Mahmod; Beykikhoshk, Adham

    2014-01-01

    Remote sensing is a useful tool for detecting change over time. We introduce a hybrid change-detection method for forest and protected-area vegetation and demonstrate its use with two satellite images of Golestan National Park in northern Iran (1998 and 2010). We report on the advantages and disadvantages of the hybrid method relative to the standard change-detection method. In the proposed hybrid algorithm, the change vector analysis technique was used to determine changes in vegetation. Following this, we used postclassification comparison to determine the nature of the changes observed and their accuracy and to evaluate the effects of different parameters on the performance of the proposed method. We determined 85% accuracy for the proposed hybrid change-detection method, thus demonstrating a method for discovering and assessing environmental threats to natural treasures.

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. No evidence for an item limit in change detection.

    PubMed

    Keshvari, Shaiyan; van den Berg, Ronald; Ma, Wei Ji

    2013-01-01

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

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

    PubMed

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

    2015-06-16

    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.

  15. Change detection in very high resolution multisensor optical images

    NASA Astrophysics Data System (ADS)

    Solano Correa, Yady T.; Bovolo, Francesca; Bruzzone, Lorenzo

    2014-10-01

    This work aims at developing an approach to the detection of changes in multisensor multitemporal VHR optical images. The main steps of the proposed method are: i) multisensor data homogenization; and ii) change detection in multisensor multitemporal VHR optical images. The proposed approach takes advantage of: the conversion to physical quantities suggested by Pacifici et. al.1 , the framework for the design of systems for change detection in VHR images presented by Bruzzone and Bovolo2 and the framework for unsupervised change detection presented by Bovolo and Bruzzone3. Multisensor data homogenization is achieved during pre-processing by taking into account differences in both radiometric and geometric dimensions. Whereas change detection was approached by extracting proper features from multisensor images such that they result to be comparable (at a given level of abstraction) even if extracted from images acquired by different sensors. In order to illustrate the results, a data set made up of a QuickBird and a WorldView-2 images - acquired in 2006 and 2010 respectively - over an area located in the Trentino region of Italy were used. However, the proposed approach is thought to be exportable to multitemporal images coming from passive sensors other than the two mentioned above. The experimental results obtained on the QuickBird and WorlView-2 image pair are accurate. Thus opening to further experiments on multitemporal images acquired by other sensors.

  16. 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

  17. 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.

  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. Unsupervised change detection of satellite images using low rank matrix completion.

    PubMed

    Gao, Shibo; Cheng, Yongmei; Zhao, Yongqiang

    2013-12-01

    Traditional unsupervised change detection methods need to generate a difference image (DI) for subsequent processing to produce a binary change map. In addition, few methods explore global structures. This Letter presents a novel unsupervised change detection approach based on low rank matrix completion. Other than generating a DI, the changed pixels are modeled as the estimated missing values for matrix completion, where the changed pixels are represented by a sparse term. A common low rank matrix is recovered by two temporal images. The changed pixels are separated out from the low rank matrix, in which the local information is introduced via graph cuts. The global and local structures are utilized in our model. Experimental results validate the effectiveness of the proposed approach. The proposed method is a new view for change detection.

  20. 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.

  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. Label-free visual detection of nucleic acids in biological samples with single-base mismatch detection capability.

    PubMed

    Song, Yanling; Zhang, Weiting; An, Yuan; Cui, Liang; Yu, Chundong; Zhu, Zhi; Yang, Chaoyong James

    2012-01-14

    We have combined an allosteric molecular beacon for target recognition and guanine-rich DNAzyme for signal amplification to develop a new platform for visual detection of nucleic acids with single-base mismatch detection capability. The fully DNA-structured platform can undergo color change in response to target DNA/RNA, which enables sensitive and selective visual detection in biological samples.

  3. 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

  4. 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.

  5. 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.

  6. 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

  7. 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.

  8. 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.

  9. Long-term memory guidance of visuospatial attention in a change-detection paradigm

    PubMed Central

    Rosen, Maya L.; Stern, Chantal E.; Somers, David C.

    2014-01-01

    Visual task performance is generally stronger in familiar environments. One reason for this familiarity benefit is that we learn where to direct our visual attention and effective attentional deployment enhances performance. Visual working memory plays a central role in supporting long-term memory guidance of visuospatial attention. We modified a change detection task to create a new paradigm for investigating long-term memory guidance of attention. During the training phase, subjects viewed images in a flicker paradigm and were asked to detect between one and three changes in the images. The test phase required subjects to detect a single change in a one-shot change detection task in which they held all possible locations of changes in visual working memory and deployed attention to those locations to determine if a change occurred. Subjects detected significantly more changes in images for which they had been trained to detect the changes, demonstrating that memory of the images guided subjects in deploying their attention. Moreover, capacity to detect changes was greater for images that had multiple changes during the training phase. In Experiment 2, we observed that capacity to detect changes for the 3-studied change condition increased significantly with more study exposures and capacity was significantly higher than 1, indicating that subjects were able to attend to more than one location. Together, these findings suggest memory and attentional systems interact via working memory such that long-term memory can be used to direct visual spatial attention to multiple locations based on previous experience. PMID:24744744

  10. 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.

  11. 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.

  12. 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.

  13. Change-point models to estimate the limit of detection.

    PubMed

    May, Ryan C; Chu, Haitao; Ibrahim, Joseph G; Hudgens, Michael G; Lees, Abigail C; Margolis, David M

    2013-12-10

    In many biological and environmental studies, measured data is subject to a limit of detection. The limit of detection is generally defined as the lowest concentration of analyte that can be differentiated from a blank sample with some certainty. Data falling below the limit of detection is left censored, falling below a level that is easily quantified by a measuring device. A great deal of interest lies in estimating the limit of detection for a particular measurement device. In this paper, we propose a change-point model to estimate the limit of detection by using data from an experiment with known analyte concentrations. Estimation of the limit of detection proceeds by a two-stage maximum likelihood method. Extensions are considered that allow for censored measurements and data from multiple experiments. A simulation study is conducted demonstrating that in some settings the change-point model provides less biased estimates of the limit of detection than conventional methods. The proposed method is then applied to data from an HIV pilot study.

  14. 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.

  15. 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.

  16. 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.

  17. Quantitative naturalistic methods for detecting change points in psychotherapy research: an illustration with alliance ruptures.

    PubMed

    Eubanks-Carter, Catherine; Gorman, Bernard S; Muran, J Christopher

    2012-01-01

    Analysis of change points in psychotherapy process could increase our understanding of mechanisms of change. In particular, naturalistic change point detection methods that identify turning points or breakpoints in time series data could enhance our ability to identify and study alliance ruptures and resolutions. This paper presents four categories of statistical methods for detecting change points in psychotherapy process: criterion-based methods, control chart methods, partitioning methods, and regression methods. Each method's utility for identifying shifts in the alliance is illustrated using a case example from the Beth Israel Psychotherapy Research program. Advantages and disadvantages of the various methods are discussed.

  18. 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

  19. 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.

  20. 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.

  1. 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.

  2. Detecting changes in terrain using unmanned aerial vehicles

    NASA Astrophysics Data System (ADS)

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

    2005-05-01

    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.

  3. 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.

  4. Detection of epigenetic changes using ANOVA with spatially varying coefficients.

    PubMed

    Guanghua, Xiao; Xinlei, Wang; Quincey, LaPlant; Nestler, Eric J; Xie, Yang

    2013-03-13

    Identification of genome-wide epigenetic changes, the stable changes in gene function without a change in DNA sequence, under various conditions plays an important role in biomedical research. High-throughput epigenetic experiments are useful tools to measure genome-wide epigenetic changes, but the measured intensity levels from these high-resolution genome-wide epigenetic profiling data are often spatially correlated with high noise levels. In addition, it is challenging to detect genome-wide epigenetic changes across multiple conditions, so efficient statistical methodology development is needed for this purpose. In this study, we consider ANOVA models with spatially varying coefficients, combined with a hierarchical Bayesian approach, to explicitly model spatial correlation caused by location-dependent biological effects (i.e., epigenetic changes) and borrow strength among neighboring probes to compare epigenetic changes across multiple conditions. Through simulation studies and applications in drug addiction and depression datasets, we find that our approach compares favorably with competing methods; it is more efficient in estimation and more effective in detecting epigenetic changes. In addition, it can provide biologically meaningful results.

  5. 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.

  6. 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…

  7. Cryosphere Change Detection With The Autonomous Sciencecraft Experiment

    NASA Astrophysics Data System (ADS)

    Davies, A. G.; Doggett, T. C.

    2006-05-01

    The Autonomous Sciencecraft Experiment (ASE) is operating on-board Earth Observing - 1 (EO-1) with the Hyperion hyper-spectral visible to short-wave infrared spectrometer. ASE science activities include autonomous monitoring of cryospheric changes, triggering the collection of additional data when change is detected and filtering of null data such as no change or cloud cover. A cryosphere classification algorithm, developed with Support Vector Machine (SVM) machine learning techniques [1], replacing a manually derived classifier used in earlier operations [2], has been used in conjunction with on-board autonomous software application to execute over two hundred on-board scenarios in 2005 and early 2006, to detect and autonomously respond to sea ice break-up and formation, lake freeze and thaw, as well as the onset and melting of snow cover on land. This demonstrates an approach which could be applied to the monitoring of cryospheres on Earth and Mars as well as the search for dynamic activity on the icy moons of the outer solar system. [1] Castano et al. (2005) Learning classifiers for event detection in remote sensing imagery, i-SAIRAS, [2] Doggett et al. (2006), Autonomous detection of cryospheric change with Hyperion on-board Earth Observing-1, Rem. Sens. Env. (in press)

  8. 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

  9. Genetic base changes for December 2014

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Genetic bases were updated previously in the United States in 1965, 1974, 1984, 1989, 1995, 2000, 2005, and 2010, and the next base change is scheduled for December 2014. Base changes for yield, health, fertility, and type traits in December 2014 are reported. Stepwise genetic bases allow predicted ...

  10. 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.

  11. Testing Distributed Parameter Hypotheses for the Detection of Climate Change.

    NASA Astrophysics Data System (ADS)

    Kheshgi, Haroon S.; White, Benjamin S.

    2001-08-01

    A general statistical methodology, based on testing alternative distributed parameter hypotheses, is proposed as a method for deciding whether or not anthropogenic influences are causing climate change. This methodology provides a framework for including known uncertainties in the definition of the hypotheses by allowing model parameters to be specified by probability distributions and thereby allowing the definition of more realistic hypotheses. The method can be used to derive the unique statistical test that minimizes errors in test conclusions. The method is applied to illustrative detection problems by first defining alternative hypotheses for global mean temperature; second, deriving the most powerful test and calculating its statistics; third, applying the test to observed temperature records; and finally, illustrating the test statistics and results on a receiver or relative operating characteristic curve showing the relation between false positive and false negative test errors. It is demonstrated, with an illustrative example, that proper accounting for the uncertainty in all the parameters can produce very different statistical conclusions than the conclusions that would be obtained by simply fixing some parameters at nominal values.

  12. 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.

  13. 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.

  14. Silicon chips detect intracellular pressure changes in living cells.

    PubMed

    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.

  15. 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.

  16. Light Scattering based detection of food pathogens

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The current methods for detecting foodborne pathogens are mostly destructive (i.e., samples need to be pretreated), and require time, personnel, and laboratories for analyses. Optical methods including light scattering based techniques have gained a lot of attention recently due to its their rapid a...

  17. 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

  18. 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.

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

    PubMed

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

    2014-11-01

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

  20. 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

  1. 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

  2. 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.

  3. 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.

  4. 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.

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

    PubMed

    Conci, Markus; Müller, Hermann J

    2014-01-01

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

  6. 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

  7. 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.

  8. Automatic analysis of the slight change image for unsupervised change detection

    NASA Astrophysics Data System (ADS)

    Yang, Jilian; Sun, Weidong

    2015-01-01

    We propose an unsupervised method for slight change extraction and detection in multitemporal hyperspectral image sequence. To exploit the spectral signatures in hyperspectral images, autoregressive integrated moving average and fitting models are employed to create a prediction of single-band and multiband time series. Minimum mean absolute error index is then applied to obtain the preliminary change information image (PCII), which contains slight change information. After that, feature vectors are created for each pixel in the PCII using block processing and locally linear embedding. The final change detection (CD) mask is obtained by clustering the extracted feature vectors into changed and unchanged classes using k-means clustering algorithm with k=2. Experimental results demonstrate that the proposed method extracts the slight change information efficiently in the hyperspectral image sequence and outperforms the state-of-the-art CD methods quantitatively and qualitatively.

  9. 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

  10. Genetic Base Changes for January 2010

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Genetic bases were updated previously in the United States in 1965, 1974, 1984, 1989, 1995, 2000, and 2005, and the next base change is scheduled for January 2010. Changing the base every 5 years subtracts accumulated genetic gain so that all animals are compared with a more recent cow population, w...

  11. 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

  12. Detection of Epigenetic Changes Using ANOVA with Spatially Varying Coefficients

    PubMed Central

    Xiao, Guanghua; Wang, Xinlei; LaPlant, Quincey; Nestler, Eric; Xie, Yang

    2016-01-01

    Identification of genome-wide epigenetic changes, the stable changes in gene function without a change in DNA sequence, under various conditions plays an important role in biomedical research. High-throughput epigenetic experiments are useful tools to measure genome-wide epigenetic changes, but the measured intensity levels from these high-resolution genome-wide epigenetic profiling data are often spatially correlated with high noise levels. In addition, no formal statistical method was developed to compare genome-wide epigenetic changes across multiple conditions. In this study, we consider ANOVA models with spatially varying coefficients, combined with a hierarchical Bayes approach, to explicitly model spatial correlation caused by location-dependent biological effects (i.e., epigenetic changes) and borrow strength among neighboring probes to compare epigenetic changes across multiple conditions. Through simulation studies and applications in drug addiction and depression models, we find that our approach compares favorably with competing methods; it is more efficient in estimation and more effective in detecting epigenetic changes. In addition, it can provide biologically meaningful results. PMID:23502341

  13. 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

  14. 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

  15. Optimized PCR-based detection of mycoplasma.

    PubMed

    Dobrovolny, Paige L; Bess, Dan

    2011-06-20

    The maintenance of contamination-free cell lines is essential to cell-based research. Among the biggest contaminant concerns are mycoplasma contamination. Although mycoplasma do not usually kill contaminated cells, they are difficult to detect and can cause a variety of effects on cultured cells, including altered metabolism, slowed proliferation and chromosomal aberrations. In short, mycoplasma contamination compromises the value of those cell lines in providing accurate data for life science research. The sources of mycoplasma contamination in the laboratory are very challenging to completely control. As certain mycoplasma species are found on human skin, they can be introduced through poor aseptic technique. Additionally, they can come from contaminated supplements such as fetal bovine serum, and most importantly from other contaminated cell cultures. Once mycoplasma contaminates a culture, it can quickly spread to contaminate other areas of the lab. Strict adherence to good laboratory practices such as good aseptic technique are key, and routine testing for mycoplasma is highly recommended for successful control of mycoplasma contamination. PCR-based detection of mycoplasma has become a very popular method for routine cell line maintenance. PCR-based detection methods are highly sensitive and can provide rapid results, which allows researchers to respond quickly to isolate and eliminate contamination once it is detected in comparison to the time required using microbiological techniques. The LookOut Mycoplasma PCR Detection Kit is highly sensitive, with a detection limit of only 2 genomes per μl. Taking advantage of the highly specific JumpStart Taq DNA Polymerase and a proprietary primer design, false positives are greatly reduced. The convenient 8-tube format, strips pre-coated with dNTPs, and associated primers helps increase the throughput to meet the needs of customers with larger collections of cell lines. Given the extreme sensitivity of the kit, great

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  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. 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.

  2. 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.

  3. 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.

  4. 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.

  5. Ice Sheet Change Detection by Satellite Image Differencing

    NASA Technical Reports Server (NTRS)

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

    2010-01-01

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

  6. Techniques for land use change detection using Landsat imagery

    NASA Technical Reports Server (NTRS)

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

    1977-01-01

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

  7. 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.

  8. 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.

  9. Polymer-based sensor array for phytochemical detection

    NASA Astrophysics Data System (ADS)

    Weerakoon, Kanchana A.; Hiremath, Nitilaksha; Chin, Bryan A.

    2012-05-01

    Monitoring for the appearance of volatile organic compounds emitted by plants which correspond to time of first insect attack can be used to detect the early stages of insect infestation. This paper reports a chemical sensor array consisting of polymer based chemiresistor sensors that could detect insect infestation effectively. The sensor array consists of sensors with micro electronically fabricated interdigitated electrodes, and twelve different types of electro active polymer layers. The sensor array was cheap, easy to fabricate, and could be used easily in agricultural fields. The polymer array was found to be sensitive to a variety of volatile organic compounds emitted by plants including γ-terpinene α-pinene, pcymene, farnesene, limonene and cis-hexenyl acetate. The sensor array was not only able to detect but also distinguish between these compounds. The twelve sensors produced a resistance change for each of the analytes detected, and each of these responses together produced a unique fingerprint, enabling to distinguish among these chemicals.

  10. 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

  11. Fast dual graph-based hotspot detection

    NASA Astrophysics Data System (ADS)

    Kahng, Andrew B.; Park, Chul-Hong; Xu, Xu

    2006-10-01

    As advanced technologies in wafer manufacturing push patterning processes toward lower-k I subwavelength printing, lithography for mass production potentially suffers from decreased patterning fidelity. This results in generation of many hotspots, which are actual device patterns with relatively large CD and image errors with respect to on-wafer targets. Hotspots can be formed under a variety of conditions such as the original design being unfriendly to the RET that is applied, unanticipated pattern combinations in rule-based OPC, or inaccuracies in model-based OPC. When these hotspots fall on locations that are critical to the electrical performance of a device, device performance and parametric yield can be significantly degraded. Previous rule-based hotspot detection methods suffer from long runtimes for complicated patterns. Also, the model generation process that captures process variation within simulation-based approaches brings significant overheads in terms of validation, measurement and parameter calibration. In this paper, we first describe a novel detection algorithm for hotspots induced by lithographic uncertainty. Our goal is to rapidly detect all lithographic hotspots without significant accuracy degradation. In other words, we propose a filtering method: as long as there are no "false negatives", i.e., we successfully have a superset of actual hotspots, then our method can dramatically reduce the layout area for golden hotspot analysis. The first step of our hotspot detection algorithm is to build a layout graph which reflects pattern-related CD variation. Given a layout L, the layout graph G = (V, E c union E p) consists of nodes V, corner edges E c and proximity edges E p. A face in the layout graph includes several close features and the edges between them. Edge weight can be calculated from a traditional 2-D model or a lookup table. We then apply a three-level hotspot detection: (1) edge-level detection finds the hotspot caused by two close

  12. 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.

  13. Topographic Change Detection using Full-waveform Imaging Lidar

    NASA Astrophysics Data System (ADS)

    Blair, B.; Hofton, M. A.

    2001-12-01

    The capability of wide-footprint (i.e. 10 m or greater), full-waveform laser altimeters to penetrate beneath dense vegetation to directly measure the sub-canopy topography provides us with a unique capability for sensing topographic change in the presence of vegetation. We evaluate the feasibility of using a geolocated laser altimeter return waveform instead of individual elevation measurements to measure vertical elevation change within a laser footprint. The method, dubbed the return pulse correlation method, maximizes the shape similarity of near-coincident, vertically-geolocated laser return waveforms from two observation epochs as they are vertically-shifted relative to each other. First, we evaluate the inherent accuracy of the pulse correlation method using models and simulations under "bare-Earth" conditions. We then analyze the effects of vegetation and vegetation growth on the change detection capability. The use of this method, combined with order of magnitude improvements to laser altimeter swath widths (from 1 km to 10 km) and the potential for a future spaceborne imaging lidar, may provide sub-centimeter level relative change detection beneath vegetation to complement IFSAR's ability to make similar measurements in low or vegetation-free conditions.

  14. Topographic Change Detection Using Full-Waveform Imaging Lidar

    NASA Technical Reports Server (NTRS)

    Blair, Bryan; Hofton, Michele A.; Smith, David E. (Technical Monitor)

    2001-01-01

    The capability of wide-footprint (i.e. 10m or greater), full-waveform laser altimeters to penetrate beneath dense vegetation to directly measure the sub-canopy topography provides us with a unique capability for sensing topographic change in the presence of vegetation. We evaluate the feasibility of using a geolocated laser altimeter return waveform instead of individual elevation measurements to measure vertical elevation change within a laser footprint. The method, dubbed the return pulse correlation method, maximizes the shape similarity of nea-coincident, vertically- geolocated laser return waveforms from two observation epochs as they are vertically-shifted relative to each other. First, we evaluate the inherent accuracy of the pulse correlation method using models and simulations under "bare-Earth" conditions. We then analyze the effects of vegetation and vegetation growth on the change detection capability. The use of this method, combined with order of magnitude improvements to laser altimeter swath widths (from 1 km to 10 km) and the potential for a future spaceborne imaging lidar, may provide subcentimeter level relative change detection beneath vegetation to complement IFSAR's ability to make similar measurements in low or vegetation-free conditions.

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

    NASA Astrophysics Data System (ADS)

    Hu, Y.; Jia, G.

    2009-12-01

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

  16. 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

  17. 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.

  18. 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.

  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. 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.

  1. Multi-driver attribution of detected hydrological change

    NASA Astrophysics Data System (ADS)

    Harrigan, Shaun; Murphy, Conor; Hall, Julia; Wilby, Robert L.; Sweeney, John

    2014-05-01

    There is growing evidence that significant links between large-scale climate indices and streamflow over decadal time-scales can be established. However identifying the dominant driving mechanism(s) of detected changes in streamflow (i.e. attribution) at the catchment scale is a challenging task due to the confounding influence of human disturbances such as land-use changes, water abstractions, and river engineering. This study addresses this challenge by examining the utility of the multiple working hypotheses framework in moving towards more rigorous attribution of changes using the Boyne catchment in the east of Ireland as a case study. Previous research on this catchment found that a large upward change point in streamflow during the mid-1970s corresponded with a shift in the North Atlantic Oscillation (NAO) index towards a more positive phase, bringing increased precipitation, and hence increased risk of flooding. Here, the single-driver analysis is extended to include multiple factors causing change within the catchment (both climatic and internal) in order to establish relative contributions of hypothesised drivers. Rainfall-runoff models were employed to reconstruct streamflow to isolate the effect of climate taking account of both model structure and parameter uncertainty. The Mann-Kendall test for monotonic trend and Pettitt change point test were applied to explore signatures of change. Results show that the detected increase in annual mean and high flows was not predominantly driven by changes in precipitation as a result of a shift in the NAO index. Rather we assert that the dominant driver of change was arterial drainage and the contemporaneous onset of agricultural field drainage in the 1970s and early 1980s. It is also demonstrated that attribution can be more complex at different time-scales with multiple drivers acting simultaneously. This study emphasises the quantity and range of data types needed for rigorous attribution, especially when

  2. 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).

  3. 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.

  4. 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

  5. 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

  6. 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.

  7. 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

  8. Bacteriophage based probes for pathogen detection.

    PubMed

    Singh, Amit; Arutyunov, Denis; Szymanski, Christine M; Evoy, Stephane

    2012-08-01

    Rapid and specific detection of pathogenic bacteria is important for the proper treatment, containment and prevention of human, animal and plant diseases. Identifying unique biological probes to achieve a high degree of specificity and minimize false positives has therefore garnered much interest in recent years. Bacteriophages are obligate intracellular parasites that subvert bacterial cell resources for their own multiplication and production of disseminative new virions, which repeat the cycle by binding specifically to the host surface receptors and injecting genetic material into the bacterial cells. The precision of host recognition in phages is imparted by the receptor binding proteins (RBPs) that are often located in the tail-spike or tail fiber protein assemblies of the virions. Phage host recognition specificity has been traditionally exploited for bacterial typing using laborious and time consuming bacterial growth assays. At the same time this feature makes phage virions or RBPs an excellent choice for the development of probes capable of selectively capturing bacteria on solid surfaces with subsequent quick and automatic detection of the binding event. This review focuses on the description of pathogen detection approaches based on immobilized phage virions as well as pure recombinant RBPs. Specific advantages of RBP-based molecular probes are also discussed.

  9. 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.

  10. 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

  11. 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...

  12. 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

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

    PubMed Central

    van Dommelen, Paula; van Wouwe, Jacobus P; Breuning‐Boers, Jacqueline M; van Buuren, Stef; Verkerk, Paul H

    2007-01-01

    Objective The validity of the rule of thumb that infants may have a weight loss of 10% in the first days after birth is unknown. We assessed the validity of this and other rules to detect breast‐fed infants with hypernatraemic dehydration. Design A reference chart for relative weight change was constructed by the LMS method. The reference group was obtained by a retrospective cohort study. Participants 1544 healthy, exclusively breast‐fed infants with 3075 weight measurements born in the Netherlands and 83 cases of breast‐fed infants with hypernatraemic dehydration obtained from literature. Results The rule of thumb had a sensitivity of 90.4%, a specificity of 98.3% and a positive predictive value of 3.7%. Referring infants if their weight change is below −2.5 SDS (0.6th centile) in the reference chart in the first week of life and using the rule of thumb in the second week had a sensitivity of 85.5%, a specificity of 99.4% and a positive predictive value of 9.2%. Conclusions The rule of thumb is likely to produce too many false positive results, assuming that for screening purposes the specificity needs to be high. A chart for relative weight change can be helpful to detect infants with hypernatraemic dehydration. PMID:16880225

  14. ROLE OF SPATIAL RESOLUTION AND SPECTRAL CONTENT IN CHANGE DETECTION.

    USGS Publications Warehouse

    Milazzo, Valerie A.

    1984-01-01

    Summary form only given, as follows. Advancements in remote sensing technology have brought improvements and sophistication to modern remote sensor systems, especially those aboard earth resources satellites. These improvements have considerbly expanded the capabilities of the newer sensor systems, particularly the capability to achieve greatly increased spatial and spectral resolution levels. The debate still lingers, however, over whether future systems should maximize spatial resolution or spectral information, or both. As yet, the high costs and large volumes of data associated with even modest incremental improvements in spatial and spectral content have precluded the design of a single system that attempts to fully optimize both. Thus, the user is faced with having to choose between those systems providing high spatial resolutions but limited spectral information and those which offer a broad range of spectral data but hold spatial resolution to a less than optimum level. In this study, the contribution of both spatial resolution and spectral content to land cover change detection is examined. Ten-meter SPOT simulation imagery is compared with multispectral images acquired by the Thematic Mapper sensor system for use in the visual interpretation and mapping of changes. Several image processing and enhancement techniques are utilized to maximize the spatial and spectral data content offered by each system. Results indicate that when using visual image interpretation techniques to detect change, higher spatial resolutions are generally preferred over increased spectral content.

  15. 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.

  16. 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.

  17. 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

  18. 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.

  19. 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.

  20. Memory strength versus memory variability in visual change detection.

    PubMed

    Nosofsky, Robert M; Gold, Jason

    2016-01-01

    Observers made change-detection judgments for colored squares in a paradigm that manipulated the retention interval, the magnitude of change, and objective change probability. The probability of change judgments increased across the retention interval for “same” and “small-change” test items but stayed the same or decreased for “large-change” and “far” test items. A variety of formal models were fitted to the individual-subject data. The modeling results provided evidence that, beyond changes in visual-memory precision, there were decreases in memory strength of individual study items across the retention interval. In addition, the modeling results provided evidence of a zero-information, absence-of-memory state that required guessing. The data were not sufficiently strong to sharply distinguish whether the losses in memory strength across the retention interval were continuous in nature or all-or-none. The authors argue that the construct of memory strength as distinct from memory variability is an important component of the nature of forgetting from visual working memory.

  1. Memory strength versus memory variability in visual change detection.

    PubMed

    Nosofsky, Robert M; Gold, Jason

    2016-01-01

    Observers made change-detection judgments for colored squares in a paradigm that manipulated the retention interval, the magnitude of change, and objective change probability. The probability of change judgments increased across the retention interval for “same” and “small-change” test items but stayed the same or decreased for “large-change” and “far” test items. A variety of formal models were fitted to the individual-subject data. The modeling results provided evidence that, beyond changes in visual-memory precision, there were decreases in memory strength of individual study items across the retention interval. In addition, the modeling results provided evidence of a zero-information, absence-of-memory state that required guessing. The data were not sufficiently strong to sharply distinguish whether the losses in memory strength across the retention interval were continuous in nature or all-or-none. The authors argue that the construct of memory strength as distinct from memory variability is an important component of the nature of forgetting from visual working memory. PMID:26480836

  2. A sensitive sequential 'on/off' SERS assay for heparin with wider detection window and higher reliability based on the reversed surface charge changes of functionalized Au@Ag nanoparticles.

    PubMed

    Zeng, Yi; Pei, Jin-Ju; Wang, Li-Hua; Shen, Ai-Guo; Hu, Ji-Ming

    2015-04-15

    A sequential 'on/off' dual mode SERS assay platform for heparin with wider detection window and higher reliability is constructed based on electrostatic forces, in which the highly protonated chitosan encapsulated p-Mercaptobenzoic acid coated Au@Ag core-shell nanoparticles undergo sequential aggregation/segregation upon the additive of heparin with a limit of detection of 43.74ng/mL (5.69U/mL) and a continuous concentration range of 50-800ng/mL (6.5-104U/mL), which are lower in sensitivity and wider in detection window than the most reported assay for heparin. Remarkably, the latter declined window over a range of 350-800ng/mL in contrast, which has not reported before, is extremely important in reliable and practical assay of heparin.

  3. 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.

  4. 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.

  5. 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.

  6. Block diagonal representations for covariance based anomalous change detectors

    SciTech Connect

    Matsekh, Anna; Theiler, James

    2009-01-01

    Change detection methods are of crucial importance in many remote sensing applications such as monitoring and surveillance, where the goal is to identify and separate changes of interest from pervasive changes inevitably present in images taken at different times and in different environmental and illumination conditions. Anomalous change detection (ACD) methods aim to identify rare, unusual, or anomalous changes among the changes of interest. Covariance-based ACD methods provide a powerful tool for detection of unusual changes in hyper-spectral images. In this paper we study the properties of the eigenvalue spectra of a family of ACD matrices in order to better understand the algebraic and numerical behavior of the covariance-based quadratic ACD methods. We propose to use singular vectors of covariance matrices of two hyper-spectral images in whitened coordinates for obtaining block-diagonal representations of the matrices of quadratic ACD methods. SVD transformation gives an equivalent representation of ACD matrices in compact block-diagonal form. In the paper we show that the eigenvalue spectrum of a block-diagonal ACD matrix can be identified analytically as a function of the singular value spectrum of the corresponding covariance matrix in whitened coordinates.

  7. 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.

  8. 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.

  9. 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.

  10. Probable detection of climatically significant change of the solar constant

    NASA Technical Reports Server (NTRS)

    Sofia, S.; Endal, A. S.

    1980-01-01

    It is suggested that the decrease in the solar radius inferred from solar eclipse observations made from 1715 to 1979 reflects a variation of the solar constant that may be of considerable climatic significance. A general, time-averaged relationship between changes in the solar constant and changes in the solar radius is derived based on a model of the contraction and expansion of the convective zone. A preliminary numerical calculation of radius changes due to changes in the mixing length of the solar envelope is presented which indicates that a decrease in solar radius of 0.5 arcsec, as observed in the last 264 years, would correspond to a decrease of 0.7% in the solar constant, a value of large climatic significance. Limitations of the observational method and the numerical approach are pointed out, and required additional theoretical and observational efforts are indicated.

  11. 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

  12. 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.

  13. 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

  14. 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.

  15. Classification, change-detection and accuracy assessment: Toward fuller automation

    NASA Astrophysics Data System (ADS)

    Podger, Nancy E.

    This research aims to automate methods for conducting change detection studies using remotely sensed images. Five major objectives were tested on two study sites, one encompassing Madison, Wisconsin, and the other Fort Hood, Texas. (Objective 1) Enhance accuracy assessments by estimating standard errors using bootstrap analysis. Bootstrap estimates of the standard errors were found to be comparable to parametric statistical estimates. Also, results show that bootstrapping can be used to evaluate the consistency of a classification process. (Objective 2) Automate the guided clustering classifier. This research shows that the guided clustering classification process can be automated while maintaining highly accurate results. Three different evaluation methods were used. (Evaluation 1) Appraised the consistency of 25 classifications produced from the automated system. The classifications differed from one another by only two to four percent. (Evaluation 2) Compared accuracies produced by the automated system to classification accuracies generated following a manual guided clustering protocol. Results: The automated system produced higher overall accuracies in 50 percent of the tests and was comparable for all but one of the remaining tests. (Evaluation 3) Assessed the time and effort required to produce accurate classifications. Results: The automated system produced classifications in less time and with less effort than the manual 'protocol' method. (Objective 3) Built a flexible, interactive software tool to aid in producing binary change masks. (Objective 4) Reduced by automation the amount of training data needed to classify the second image of a two-time-period change detection project. Locations of the training sites in 'unchanged' areas employed to classify the first image were used to identify sites where spectral information was automatically extracted from the second image. Results: The automatically generated training data produces classification accuracies

  16. 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

  17. 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

  18. 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.

  19. 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

  20. 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.

  1. 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.

  2. 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.

  3. Detecting inaudible vocal organ changes through glottal inverse filtering.

    PubMed

    Geneid, Ahmed; Rönkkö, Marjo; Voutilainen, Risto; Airaksinen, Liisa; Toskala, Elina; Alku, Paavo; Vilkman, Erkki

    2012-03-01

    The aim of this study was to investigate if there were objective quantities extracted from the speech pressure waveforms that underlay inaudible changes in the symptoms of the vocal organ. This was done through analyzing 180 voice samples obtained from nine subjects (five females and four males) before and after exposure to a placebo substance (lactose) and an organic dust substance. Acoustical analysis of the voice samples was achieved by using glottal inverse filtering. Results showed that the values of primary open quotient and primary speed quotient changed significantly (P<0.05) as did the amplitude quotient (P<0.01). Exposure to lactose resulted in significant changes of secondary open quotient (P<0.05) but opposite to effects found for exposure to organic dust. Modeling of the vocal tract into cross-sectional planes revealed that the immediate plane above the vocal folds correlates inversely with the feeling that voice is tense, or feeling the need to make an effort when speaking in addition having a feeling of shortness of breath or the need to gasp for air. Such results may point to acoustically detected subclinical changes in the vocal organ that the subject him/herself feels while they remain perceptually undetected by others.

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  5. 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

  6. 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

  7. 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.

  8. Advances in nucleic acid-based detection methods.

    PubMed Central

    Wolcott, M J

    1992-01-01

    Laboratory techniques based on nucleic acid methods have increased in popularity over the last decade with clinical microbiologists and other laboratory scientists who are concerned with the diagnosis of infectious agents. This increase in popularity is a result primarily of advances made in nucleic acid amplification and detection techniques. Polymerase chain reaction, the original nucleic acid amplification technique, changed the way many people viewed and used nucleic acid techniques in clinical settings. After the potential of polymerase chain reaction became apparent, other methods of nucleic acid amplification and detection were developed. These alternative nucleic acid amplification methods may become serious contenders for application to routine laboratory analyses. This review presents some background information on nucleic acid analyses that might be used in clinical and anatomical laboratories and describes some recent advances in the amplification and detection of nucleic acids. PMID:1423216

  9. [Review of change detection methods using multi-temporal remotely sensed images].

    PubMed

    Yin, Shou-Jing; Wu, Chuan-Qing; Wang, Qiao; Ma, Wan-Dong; Zhu, Li; Yao, Yan-Juan; Wang, Xue-Lei; Wu, Di

    2013-12-01

    With the development of platforms and sensors, continuous repetition of remote sensing observation of the earth surface has been realized, and a mass of multi-source, multi-scale, multi-resolution remote sensing data has been accumulated. Those images have detailedly recorded the changing process of ground objects on the earth, which makes the long term global change research, such as change detection, based on remote sensing become possible, and greatly push forward the research on image processing and application. Although plenty of successful research has been reported, there are still enormous challenges in multi-temporal imagery change detection. A relatively complete mature theoretical system has not formed, and there is still a lack of systematic summary of research progress. Firstly, the current progress in change detection methods using multi-temporal remotely sensed imagery has been reviewed in this paper. Then, the methods are classified into three categories and summarized according to the type and amount of the input data, single-phase post-classification comparison, two-phase comparison, and time series analysis. After that, the possible existing problems in the current development of multi-temporal change detection are analyzed, and the development trend is discussed finally.

  10. 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

  11. 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.

  12. 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.

  13. 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

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

    PubMed

    Hou, Bin; Wang, Yunhong; Liu, Qingjie

    2016-08-27

    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.

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

    PubMed Central

    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

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

    PubMed

    Aoyama, Atsushi; Haruyama, Tomohiro; Kuriki, Shinya

    2013-09-01

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

  17. 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.…

  18. 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

  19. 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.

  20. [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

  1. 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.

  2. 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

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

    PubMed

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

    2003-01-01

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

  4. A New Intrusion Detection Method Based on Antibody Concentration

    NASA Astrophysics Data System (ADS)

    Zeng, Jie; Li, Tao; Li, Guiyang; Li, Haibo

    Antibody is one kind of protein that fights against the harmful antigen in human immune system. In modern medical examination, the health status of a human body can be diagnosed by detecting the intrusion intensity of a specific antigen and the concentration indicator of corresponding antibody from human body’s serum. In this paper, inspired by the principle of antigen-antibody reactions, we present a New Intrusion Detection Method Based on Antibody Concentration (NIDMBAC) to reduce false alarm rate without affecting detection rate. In our proposed method, the basic definitions of self, nonself, antigen and detector in the intrusion detection domain are given. Then, according to the antigen intrusion intensity, the change of antibody number is recorded from the process of clone proliferation for detectors based on the antigen classified recognition. Finally, building upon the above works, a probabilistic calculation method for the intrusion alarm production, which is based on the correlation between the antigen intrusion intensity and the antibody concen-tration, is proposed. Our theoretical analysis and experimental results show that our proposed method has a better performance than traditional methods.

  5. 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.

  6. 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

  7. 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

  8. 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.

  9. Reproducibility and quantitation of amplicon sequencing-based detection.

    PubMed

    Zhou, Jizhong; Wu, Liyou; Deng, Ye; Zhi, Xiaoyang; Jiang, Yi-Huei; Tu, Qichao; Xie, Jianping; Van Nostrand, Joy D; He, Zhili; Yang, Yunfeng

    2011-08-01

    To determine the reproducibility and quantitation of the amplicon sequencing-based detection approach for analyzing microbial community structure, a total of 24 microbial communities from a long-term global change experimental site were examined. Genomic DNA obtained from each community was used to amplify 16S rRNA genes with two or three barcode tags as technical replicates in the presence of a small quantity (0.1% wt/wt) of genomic DNA from Shewanella oneidensis MR-1 as the control. The technical reproducibility of the amplicon sequencing-based detection approach is quite low, with an average operational taxonomic unit (OTU) overlap of 17.2%±2.3% between two technical replicates, and 8.2%±2.3% among three technical replicates, which is most likely due to problems associated with random sampling processes. Such variations in technical replicates could have substantial effects on estimating β-diversity but less on α-diversity. A high variation was also observed in the control across different samples (for example, 66.7-fold for the forward primer), suggesting that the amplicon sequencing-based detection approach could not be quantitative. In addition, various strategies were examined to improve the comparability of amplicon sequencing data, such as increasing biological replicates, and removing singleton sequences and less-representative OTUs across biological replicates. Finally, as expected, various statistical analyses with preprocessed experimental data revealed clear differences in the composition and structure of microbial communities between warming and non-warming, or between clipping and non-clipping. Taken together, these results suggest that amplicon sequencing-based detection is useful in analyzing microbial community structure even though it is not reproducible and quantitative. However, great caution should be taken in experimental design and data interpretation when the amplicon sequencing-based detection approach is used for quantitative

  10. Enzymatic amplification detection of DNA based on "molecular beacon" biosensors.

    PubMed

    Mao, Xun; Jiang, Jianhui; Xu, Xiangmin; Chu, Xia; Luo, Yan; Shen, Guoli; Yu, Ruqin

    2008-05-15

    We described a novel electrochemical DNA biosensor based on molecular beacon (MB) probe and enzymatic amplification protocol. The MB modified with a thiol at its 5' end and a biotin at its 3' end was immobilized on the gold electrode through mixed self-assembly process. Hybridization events between MB and target DNA cause the conformational change of the MB, triggering the attached biotin group on the electrode surface. Following the specific interaction between the conformation-triggered biotin and streptavidin-horseradish peroxidase (HRP), subsequent quantification of DNA was realized by electrochemical detection of enzymatic product in the presence of substrate. The detection limit is obtained as low as 0.1nM. The presented DNA biosensor has good selectivity, being able to differentiate between a complementary target DNA sequence and one containing G-G single-base mismatches.

  11. 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.

  12. 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.

  13. Damage detection based on acceleration data using artificial immune system

    NASA Astrophysics Data System (ADS)

    Chartier, Sandra; Mita, Akira

    2009-03-01

    Nowadays, Structural Health Monitoring (SHM) is essential in order to prevent damages occurrence in civil structures. This is a particularly important issue as the number of aged structures is increasing. Damage detection algorithms are often based on changes in the modal properties like natural frequencies, modal shapes and modal damping. In this paper, damage detection is completed by using Artificial Immune System (AIS) theory directly on acceleration data. Inspired from the biological immune system, AIS is composed of several models like negative selection which has a great potential for this study. The negative selection process relies on the fact that T-cells, after their maturation, are sensitive to non self cells and can not detect self cells. Acceleration data were provided by using the numerical model of a 3-story frame structure. Damages were introduced, at particular times, by reduction of story's stiffness. Based on these acceleration data, undamaged data (equivalent to self data) and damaged data (equivalent to non self data) can be obtained and represented in the Hamming shape-space with a binary representation. From the undamaged encoded data, detectors (equivalent to T-cells) are derived and are able to detect damaged encoded data really efficiently by using the rcontiguous bits matching rule. Indeed, more than 95% of detection can be reached when efficient combinations of parameters are used. According to the number of detected data, the localization of damages can even be determined by using the differences between story's relative accelerations. Thus, the difference which presents the highest detection rate, generally up to 89%, is directly linked to the location of damage.

  14. 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

  15. 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.

  16. 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.

  17. 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.

  18. Smell Detection Agent Based Optimization Algorithm

    NASA Astrophysics Data System (ADS)

    Vinod Chandra, S. S.

    2016-09-01

    In this paper, a novel nature-inspired optimization algorithm has been employed and the trained behaviour of dogs in detecting smell trails is adapted into computational agents for problem solving. The algorithm involves creation of a surface with smell trails and subsequent iteration of the agents in resolving a path. This algorithm can be applied in different computational constraints that incorporate path-based problems. Implementation of the algorithm can be treated as a shortest path problem for a variety of datasets. The simulated agents have been used to evolve the shortest path between two nodes in a graph. This algorithm is useful to solve NP-hard problems that are related to path discovery. This algorithm is also useful to solve many practical optimization problems. The extensive derivation of the algorithm can be enabled to solve shortest path problems.

  19. 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.

  20. Detecting regional changes in myocardial contraction patterns using MRI

    NASA Astrophysics Data System (ADS)

    Sanchez-Ortiz, Gerardo I.; Chandrashekara, Raghavendra; Rhode, Kawal S.; Razavi, Reza; Hill, Derek L. G.; Rueckert, Daniel

    2004-04-01

    Measuring changes in cardiac motion patterns can assist in diagnosing the onset of arrhythmia and ischaemia and in the follow-up of treatment. This work presents a methodology for measuring such motion changes from MR images. Non-rigid registration is used to track cardiac motion in a sequence of 3D tagged MR images. We use a cylindrical coordinate system to subdivide the myocardium into smaller anatomically meaningful regions and to express motion derived measurements such as displacement and strain for each myocardial region during the cardiac cycle. In the first experiment we have evaluated the proposed methods using synthetic image sequences where the ground truth was available. These images were generated using a cardiac motion simulator for tagged MRI. Normal and abnormal motion fields were produced by modifying parameters in a small region of the myocardium. In the second experiment we have acquired two separate tagged MR image sequences from five healthy volunteers. Both acquisitions have been carried out without moving the volunteer inside the scanner, thus avoiding potential misregistration errors due to subject motion between scans. In addition, one of volunteers was subjected to stress during one of the scans. In the final experiment we acquired tagged MR images from a patient with super-ventricular tachyarrhythmia, before and after radio frequency ablation. The image acquisition and catheter intervention were performed with a combined X-ray and MRI system. Detection results were correct on synthetic data and no region was incorrectly classified as having significant changes in the repetition studies. Significant changes in motion pattern were measured in the stress and ablation studies. Furthermore, results seem to corroborate that the ablation regularised cardiac contraction.

  1. 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.

  2. Personality and attention: Levels of neuroticism and extraversion can predict attentional performance during a change detection task.

    PubMed

    Hahn, Sowon; Buttaccio, Daniel R; Hahn, Jungwon; Lee, Taehun

    2015-01-01

    The present study demonstrates that levels of extraversion and neuroticism can predict attentional performance during a change detection task. After completing a change detection task built on the flicker paradigm, participants were assessed for personality traits using the Revised Eysenck Personality Questionnaire (EPQ-R). Multiple regression analyses revealed that higher levels of extraversion predict increased change detection accuracies, while higher levels of neuroticism predict decreased change detection accuracies. In addition, neurotic individuals exhibited decreased sensitivity A' and increased fixation dwell times. Hierarchical regression analyses further revealed that eye movement measures mediate the relationship between neuroticism and change detection accuracies. Based on the current results, we propose that neuroticism is associated with decreased attentional control over the visual field, presumably due to decreased attentional disengagement. Extraversion can predict increased attentional performance, but the effect is smaller than the relationship between neuroticism and attention.

  3. Land-cover change detection for the tropics using remote sensing and geographic information systems

    NASA Astrophysics Data System (ADS)

    Read, Jane M.

    1999-12-01

    Changing land-cover in the tropics is a central issue in global change research. This dissertation used Landsat-TM data to examine processes of land-use and land-cover changes for a lowland tropical site in Sarapiqui, Costa Rica. Performances of selected image-processing methods to detect and identify land-cover changes were evaluated. A land-cover time-series from 1960 to 1996 for the site was generated using maps derived from aerial photographs and Landsat-TM classifications. Changes in land-cover from 1986 to 1996 were evaluated using standard landscape indices, and interpreted in terms of their historical context. Dominant changes in the site during this decade included the breakup of extensive cattle ranches for large-scale plantation enterprises and small-scale farming. Colonization processes, improvements in access, and changes in export markets were identified as the major driving forces of change. Evaluation of change-detection methods revealed that postclassification comparison performed significantly better than image differencing algorithms. Image differencing using mid- infrared bonds performed the best of the differencing algorithms tested. Selection of a suitable change-detection method can be aided through examination of the individual bond statistics for the specific area and problem in question. The univariate bond differencing technique has potential for identification of 'hot spots' of change using Landsat-TM data. Spatial pattern-recognition techniques to characterize complexity of Landsat-TM data were evaluated. Fractal dimension calculated using the triangular prism surface area method, and Moran's I index of spatial autocorrelation, clearly distinguished different land-cover types. Shannon's diversity index and the contagion metric were not found to be useful in characterizing the images. The use of fractal dimension, in conjunction with standard non-spatial descriptive band statistics, are seen as having great potential in characterizing

  4. 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

  5. Joint Use of ALOS PALSAR and Landsat TM Images for Urban Change Detection

    NASA Astrophysics Data System (ADS)

    Xu, Jinyan; Zhang, Lu; Liao, Mingsheng; Wang, He

    2013-01-01

    It is an important issue for urban planning to monitor the growth and change information of urban areas using remote sensed images. The joint use of Landsat TM data and ALOS PALSAR quad-polarization data for extracting change information of urban areas is investigated. The potential application and the performance of the two data sets are evaluated. The processes including the extraction of features, the dual-threshold EM change detection based on canonical correlation analysis (CCA) and the detection based on random forest (RF) classification were the major steps. The six bands of Landsat TM data without the thermal band were obtained. The four quad-polarimetric features as R-L circular polarization correlation coefficient, the linear polarization correlation coefficient, the total power (TP) and the cross-polarization isolation (XPI) were extracted from ALOS PALSAR data. And the corresponding differential images were got. The dual-threshold EM change detection and the RF classification were carried out based on these images. Accuracy assessment was done and the results were analyzed and verified.

  6. 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.

  7. Detection of biological thiols based on a colorimetric method*

    PubMed Central

    Xu, Yuan-yuan; Sun, Yang-yang; Zhang, Yu-juan; Lu, Chen-he; Miao, Jin-feng

    2016-01-01

    Biological thiols (biothiols), an important kind of functional biomolecules, such as cysteine (Cys) and glutathione (GSH), play vital roles in maintaining the stability of the intracellular environment. In past decades, studies have demonstrated that metabolic disorder of biothiols is related to many serious disease processes and will lead to extreme damage in human and numerous animals. We carried out a series of experiments to detect biothiols in biosamples, including bovine plasma and cell lysates of seven different cell lines based on a simple colorimetric method. In a typical test, the color of the test solution could gradually change from blue to colorless after the addition of biothiols. Based on the color change displayed, experimental results reveal that the percentage of biothiols in the embryonic fibroblast cell line is significantly higher than those in the other six cell lines, which provides the basis for the following biothiols-related study. PMID:27704750

  8. Analyzing the auditory scene: neurophysiologic evidence of a dissociation between detection of regularity and detection of change.

    PubMed

    Pannese, Alessia; Herrmann, Christoph S; Sussman, Elyse

    2015-05-01

    Detecting regularity and change in the environment is crucial for survival, as it enables making predictions about the world and informing goal-directed behavior. In the auditory modality, the detection of regularity involves segregating incoming sounds into distinct perceptual objects (stream segregation). The detection of change from this within-stream regularity is associated with the mismatch negativity, a component of auditory event-related brain potentials (ERPs). A central unanswered question is how the detection of regularity and the detection of change are interrelated, and whether attention affects the former, the latter, or both. Here we show that the detection of regularity and the detection of change can be empirically dissociated, and that attention modulates the detection of change without precluding the detection of regularity, and the perceptual organization of the auditory background into distinct streams. By applying frequency spectra analysis on the EEG of subjects engaged in a selective listening task, we found distinct peaks of ERP synchronization, corresponding to the rhythm of the frequency streams, independently of whether the stream was attended or ignored. Our results provide direct neurophysiological evidence of regularity detection in the auditory background, and show that it can occur independently of change detection and in the absence of attention.

  9. 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...

  10. 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.

  11. 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.

  12. Implicit processing of tactile information: evidence from the tactile change detection paradigm.

    PubMed

    Pritchett, David; Gallace, Alberto; Spence, Charles

    2011-09-01

    People can maintain accurate representations of visual changes without necessarily being aware of them. Here, we investigate whether a similar phenomenon (implicit change detection) also exists in touch. In Experiments 1 and 2, participants detected the presence of a change between two consecutively-presented tactile displays. Tactile change blindness was observed, with participants failing to report the presence of tactile change. Critically, however, when participants had to make a forced choice response regarding the number of stimuli presented in the two displays, their performance was significantly better than chance (i.e., implicit change detection was observed). Experiment 3 demonstrated that tactile change detection does not necessarily involve a shift of spatial attention toward the location of change, regardless of whether the change is explicitly detected. We conclude that tactile change detection likely results from comparing representations of the two displays, rather than by directing spatial attention to the location of the change.

  13. Robust detection and classification of longitudinal changes in color retinal fundus images for monitoring diabetic retinopathy.

    PubMed

    Narasimha-Iyer, Harihar; Can, Ali; Roysam, Badrinath; Stewart, Charles V; Tanenbaum, Howard L; Majerovics, Anna; Singh, Hanumant

    2006-06-01

    A fully automated approach is presented for robust detection and classification of changes in longitudinal time-series of color retinal fundus images of diabetic retinopathy. The method is robust to: 1) spatial variations in illumination resulting from instrument limitations and changes both within, and between patient visits; 2) imaging artifacts such as dust particles; 3) outliers in the training data; 4) segmentation and alignment errors. Robustness to illumination variation is achieved by a novel iterative algorithm to estimate the reflectance of the retina exploiting automatically extracted segmentations of the retinal vasculature, optic disk, fovea, and pathologies. Robustness to dust artifacts is achieved by exploiting their spectral characteristics, enabling application to film-based, as well as digital imaging systems. False changes from alignment errors are minimized by subpixel accuracy registration using a 12-parameter transformation that accounts for unknown retinal curvature and camera parameters. Bayesian detection and classification algorithms are used to generate a color-coded output that is readily inspected. A multiobserver validation on 43 image pairs from 22 eyes involving nonproliferative and proliferative diabetic retinopathies, showed a 97% change detection rate, a 3% miss rate, and a 10% false alarm rate. The performance in correctly classifying the changes was 99.3%. A self-consistency metric, and an error factor were developed to measure performance over more than two periods. The average self consistency was 94% and the error factor was 0.06%. Although this study focuses on diabetic changes, the proposed techniques have broader applicability in ophthalmology.

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

    NASA Astrophysics Data System (ADS)

    Sidiropoulos, Panagiotis; Muller, Jan-Peter

    2016-10-01

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

  15. 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.

  16. 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.

  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.

  18. 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

  19. 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.

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