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Sample records for change detection method

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

    Science.gov (United States)

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

    2010-01-05

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

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

    Directory of Open Access Journals (Sweden)

    Yanhui Wang

    2018-01-01

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

  3. One new method for road data shape change detection

    Science.gov (United States)

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

    2009-10-01

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

  4. Updating National Topographic Data Base Using Change Detection Methods

    Science.gov (United States)

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

    2016-06-01

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

  5. UPDATING NATIONAL TOPOGRAPHIC DATA BASE USING CHANGE DETECTION METHODS

    Directory of Open Access Journals (Sweden)

    E. Keinan

    2016-06-01

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

  6. Detecting anthropogenic climate change with an optimal fingerprint method

    International Nuclear Information System (INIS)

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

    1994-01-01

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

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

    Science.gov (United States)

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

    2016-06-01

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

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

    Directory of Open Access Journals (Sweden)

    C. H. Yang

    2016-06-01

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

  9. Linear and kernel methods for multivariate change detection

    DEFF Research Database (Denmark)

    Canty, Morton J.; Nielsen, Allan Aasbjerg

    2012-01-01

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

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

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg; Canty, Morton J.

    2010-01-01

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

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

    Science.gov (United States)

    Liu, Siqi; Wright, Adam; Hauskrecht, Milos

    2017-06-01

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

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

    Science.gov (United States)

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

    2014-03-01

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

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

    International Nuclear Information System (INIS)

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

    2014-01-01

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

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

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg; Canty, Morton John

    2011-01-01

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

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

    International Nuclear Information System (INIS)

    Riano M, Orlando

    2002-01-01

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

  16. Changing change detection

    DEFF Research Database (Denmark)

    Kyllingsbæk, Søren; Bundesen, Claus

    2009-01-01

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

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

    Science.gov (United States)

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

    2018-04-01

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

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

    International Nuclear Information System (INIS)

    McGinley, P.H.

    2000-01-01

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

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

    Science.gov (United States)

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

    2015-01-01

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

  20. The Regularized Iteratively Reweighted MAD Method for Change Detection in Multi- and Hyperspectral Data

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg

    2007-01-01

    This paper describes new extensions to the previously published multivariate alteration detection (MAD) method for change detection in bi-temporal, multi- and hypervariate data such as remote sensing imagery. Much like boosting methods often applied in data mining work, the iteratively reweighted...... to observations that show little change, i.e., for which the sum of squared, standardized MAD variates is small, and small weights are assigned to observations for which the sum is large. Like the original MAD method, the iterative extension is invariant to linear (affine) transformations of the original...... an agricultural region in Kenya, and hyperspectral airborne HyMap data from a small rural area in southeastern Germany are given. The latter case demonstrates the need for regularization....

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

    Science.gov (United States)

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

    2013-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Bin Hou

    2016-08-01

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

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

    Science.gov (United States)

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

    2017-06-01

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

  4. Comparison of feature extraction methods within a spatio-temporal land cover change detection framework

    CSIR Research Space (South Africa)

    Kleynhans, W

    2011-07-01

    Full Text Available OF FEATURE EXTRACTION METHODS WITHIN A SPATIO-TEMPORAL LAND COVER CHANGE DETECTION FRAMEWORK ??W. Kleynhans,, ??B.P. Salmon, ?J.C. Olivier, ?K.J. Wessels, ?F. van den Bergh ? Electrical, Electronic and Computer Engi- neering University of Pretoria, South... Bergh, and K. Steenkamp, ?Improving land cover class separation using an extended Kalman filter on MODIS NDVI time series data,? IEEE Geoscience and Remote Sensing Letters, vol. 7, no. 2, pp. 381?385, Apr. 2010. ...

  5. Statistical methods for change-point detection in surface temperature records

    Science.gov (United States)

    Pintar, A. L.; Possolo, A.; Zhang, N. F.

    2013-09-01

    We describe several statistical methods to detect possible change-points in a time series of values of surface temperature measured at a meteorological station, and to assess the statistical significance of such changes, taking into account the natural variability of the measured values, and the autocorrelations between them. These methods serve to determine whether the record may suffer from biases unrelated to the climate signal, hence whether there may be a need for adjustments as considered by M. J. Menne and C. N. Williams (2009) "Homogenization of Temperature Series via Pairwise Comparisons", Journal of Climate 22 (7), 1700-1717. We also review methods to characterize patterns of seasonality (seasonal decomposition using monthly medians or robust local regression), and explain the role they play in the imputation of missing values, and in enabling robust decompositions of the measured values into a seasonal component, a possible climate signal, and a station-specific remainder. The methods for change-point detection that we describe include statistical process control, wavelet multi-resolution analysis, adaptive weights smoothing, and a Bayesian procedure, all of which are applicable to single station records.

  6. Advancing Research Methods to Detect Impact of Climate Change on Health in Grand'Anse, Haiti

    Science.gov (United States)

    Barnhart, S.; Coq, R. N.; Frederic, R.; DeRiel, E.; Camara, H.; Barnhart, K. R.

    2013-12-01

    Haiti is considered particularly vulnerable to the effects of climate change, but directly linking climate change to health effects is limited by the lack of robust data and the multiple determinants of health. Worsening storms and rising temperatures in this rugged country with high poverty is likely to adversely affect economic activity, population growth and other determinants of health. For the past two years, the Univ. of Washington has supported the public hospital in the department of Grand'Anse. Grand'Anse, a relatively contained region in SW Haiti with an area of 11,912 km2, is predominantly rural with a population of 350,000 and is bounded to the south by peaks up to 2,347 m. Grand'Anse would serve as an excellent site to assess the interface between climate change and health. The Demographic and Health Survey (DHS) shows health status is low relative to other countries. Estimates of climate change for Jeremie, the largest city in Grand'Anse, predict the mean monthly temperature will increase from 26.1 to 27.3 oC while mean monthly rainfall will decrease from 80.5 to 73.5 mm over the next 60 years. The potential impact of these changes ranges from threatening food security to greater mortality. Use of available secondary data such as indicators of climate change and DHS health status are not likely to offer sufficient resolution to detect positive or negative impacts of climate change on health. How might a mixed methods approach incorporating secondary data and quantitative and qualitative survey data on climate, economic activity, health and determinants of health address the hypothesis: Climate change does not adversely affect health? For example, in Haiti most women deliver at home. Maternal mortality is high at 350 deaths/100,000 deliveries. This compares to deliveries in facilities where the median rate is less than 100/100,000. Thus, maternal mortality is closely linked to access to health care in this rugged mountainous country. Climate change

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

    Science.gov (United States)

    2015-06-01

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

  8. Object-Based Change Detection in Urban Areas: The Effects of Segmentation Strategy, Scale, and Feature Space on Unsupervised Methods

    Directory of Open Access Journals (Sweden)

    Lei Ma

    2016-09-01

    Full Text Available Object-based change detection (OBCD has recently been receiving increasing attention as a result of rapid improvements in the resolution of remote sensing data. However, some OBCD issues relating to the segmentation of high-resolution images remain to be explored. For example, segmentation units derived using different segmentation strategies, segmentation scales, feature space, and change detection methods have rarely been assessed. In this study, we have tested four common unsupervised change detection methods using different segmentation strategies and a series of segmentation scale parameters on two WorldView-2 images of urban areas. We have also evaluated the effect of adding extra textural and Normalized Difference Vegetation Index (NDVI information instead of using only spectral information. Our results indicated that change detection methods performed better at a medium scale than at a fine scale where close to the pixel size. Multivariate Alteration Detection (MAD always outperformed the other methods tested, at the same confidence level. The overall accuracy appeared to benefit from using a two-date segmentation strategy rather than single-date segmentation. Adding textural and NDVI information appeared to reduce detection accuracy, but the magnitude of this reduction was not consistent across the different unsupervised methods and segmentation strategies. We conclude that a two-date segmentation strategy is useful for change detection in high-resolution imagery, but that the optimization of thresholds is critical for unsupervised change detection methods. Advanced methods need be explored that can take advantage of additional textural or other parameters.

  9. Change Detection in Social Networks

    National Research Council Canada - National Science Library

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

    2008-01-01

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

  10. Comparison of four machine learning methods for object-oriented change detection in high-resolution satellite imagery

    Science.gov (United States)

    Bai, Ting; Sun, Kaimin; Deng, Shiquan; Chen, Yan

    2018-03-01

    High resolution image change detection is one of the key technologies of remote sensing application, which is of great significance for resource survey, environmental monitoring, fine agriculture, military mapping and battlefield environment detection. In this paper, for high-resolution satellite imagery, Random Forest (RF), Support Vector Machine (SVM), Deep belief network (DBN), and Adaboost models were established to verify the possibility of different machine learning applications in change detection. In order to compare detection accuracy of four machine learning Method, we applied these four machine learning methods for two high-resolution images. The results shows that SVM has higher overall accuracy at small samples compared to RF, Adaboost, and DBN for binary and from-to change detection. With the increase in the number of samples, RF has higher overall accuracy compared to Adaboost, SVM and DBN.

  11. An Unsupervised kNN Method to Systematically Detect Changes in Protein Localization in High-Throughput Microscopy Images.

    Directory of Open Access Journals (Sweden)

    Alex Xijie Lu

    Full Text Available Despite the importance of characterizing genes that exhibit subcellular localization changes between conditions in proteome-wide imaging experiments, many recent studies still rely upon manual evaluation to assess the results of high-throughput imaging experiments. We describe and demonstrate an unsupervised k-nearest neighbours method for the detection of localization changes. Compared to previous classification-based supervised change detection methods, our method is much simpler and faster, and operates directly on the feature space to overcome limitations in needing to manually curate training sets that may not generalize well between screens. In addition, the output of our method is flexible in its utility, generating both a quantitatively ranked list of localization changes that permit user-defined cut-offs, and a vector for each gene describing feature-wise direction and magnitude of localization changes. We demonstrate that our method is effective at the detection of localization changes using the Δrpd3 perturbation in Saccharomyces cerevisiae, where we capture 71.4% of previously known changes within the top 10% of ranked genes, and find at least four new localization changes within the top 1% of ranked genes. The results of our analysis indicate that simple unsupervised methods may be able to identify localization changes in images without laborious manual image labelling steps.

  12. An Unsupervised kNN Method to Systematically Detect Changes in Protein Localization in High-Throughput Microscopy Images.

    Science.gov (United States)

    Lu, Alex Xijie; Moses, Alan M

    2016-01-01

    Despite the importance of characterizing genes that exhibit subcellular localization changes between conditions in proteome-wide imaging experiments, many recent studies still rely upon manual evaluation to assess the results of high-throughput imaging experiments. We describe and demonstrate an unsupervised k-nearest neighbours method for the detection of localization changes. Compared to previous classification-based supervised change detection methods, our method is much simpler and faster, and operates directly on the feature space to overcome limitations in needing to manually curate training sets that may not generalize well between screens. In addition, the output of our method is flexible in its utility, generating both a quantitatively ranked list of localization changes that permit user-defined cut-offs, and a vector for each gene describing feature-wise direction and magnitude of localization changes. We demonstrate that our method is effective at the detection of localization changes using the Δrpd3 perturbation in Saccharomyces cerevisiae, where we capture 71.4% of previously known changes within the top 10% of ranked genes, and find at least four new localization changes within the top 1% of ranked genes. The results of our analysis indicate that simple unsupervised methods may be able to identify localization changes in images without laborious manual image labelling steps.

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

    Directory of Open Access Journals (Sweden)

    Jerzy Stojek

    2010-06-01

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

  14. SWCD: a sliding window and self-regulated learning-based background updating method for change detection in videos

    Science.gov (United States)

    Işık, Şahin; Özkan, Kemal; Günal, Serkan; Gerek, Ömer Nezih

    2018-03-01

    Change detection with background subtraction process remains to be an unresolved issue and attracts research interest due to challenges encountered on static and dynamic scenes. The key challenge is about how to update dynamically changing backgrounds from frames with an adaptive and self-regulated feedback mechanism. In order to achieve this, we present an effective change detection algorithm for pixelwise changes. A sliding window approach combined with dynamic control of update parameters is introduced for updating background frames, which we called sliding window-based change detection. Comprehensive experiments on related test videos show that the integrated algorithm yields good objective and subjective performance by overcoming illumination variations, camera jitters, and intermittent object motions. It is argued that the obtained method makes a fair alternative in most types of foreground extraction scenarios; unlike case-specific methods, which normally fail for their nonconsidered scenarios.

  15. Improving features used for hyper-temporal land cover change detection by reducing the uncertainty in the feature extraction method

    CSIR Research Space (South Africa)

    Salmon, BP

    2017-07-01

    Full Text Available the effect which the length of a temporal sliding window has on the success of detecting land cover change. It is shown using a short Fourier transform as a feature extraction method provides meaningful robust input to a machine learning method. In theory...

  16. Social Network Change Detection

    National Research Council Canada - National Science Library

    McCulloh, Ian A; Carley, Kathleen M

    2008-01-01

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

  17. Rapid detection of new and expanding human settlements in the Limpopo province of South Africa using a spatio-temporal change detection method

    Science.gov (United States)

    Kleynhans, W.; Salmon, B. P.; Wessels, K. J.; Olivier, J. C.

    2015-08-01

    Recent development has identified the benefits of using hyper-temporal satellite time series data for land cover change detection and classification in South Africa. In particular, the monitoring of human settlement expansion in the Limpopo province is of relevance as it is the one of the most pervasive forms of land-cover change in this province which covers an area of roughly 125 000 km2. In this paper, a spatio-temporal autocorrelation change detection (STACD) method is developed to improve the performance of a pixel based temporal Autocorrelation change detection (TACD) method previously proposed. The objective is to apply the algorithm to large areas to detect the conversion of natural vegetation to settlement which is then validated by an operator using additional data (such as high resolution imagery). Importantly, as the objective of the method is to indicate areas of potential change to operators for further analysis, a low false alarm rate is required while achieving an acceptable probability of detection. Results indicate that detection accuracies of 70% of new settlement instances are achievable at a false alarm rate of less than 1% with the STACD method, an improvement of up to 17% compared to the original TACD formulation.

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

    International Nuclear Information System (INIS)

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

    2014-01-01

    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

  19. Detecting a clinically meaningful change in tic severity in Tourette syndrome: a comparison of three methods.

    Science.gov (United States)

    Jeon, Sangchoon; Walkup, John T; Woods, Douglas W; Peterson, Alan; Piacentini, John; Wilhelm, Sabine; Katsovich, Lily; McGuire, Joseph F; Dziura, James; Scahill, Lawrence

    2013-11-01

    To compare three statistical strategies for classifying positive treatment response based on a dimensional measure (Yale Global Tic Severity Scale [YGTSS]) and a categorical measure (Clinical Global Impression-Improvement [CGI-I] scale). Subjects (N=232; 69.4% male; ages 9-69years) with Tourette syndrome or chronic tic disorder participated in one of two 10-week, randomized controlled trials comparing behavioral treatment to supportive therapy. The YGTSS and CGI-I were rated by clinicians blind to treatment assignment. We examined the percent reduction in the YGTSS-Total Tic Score (TTS) against Much Improved or Very Much Improved on the CGI-I, computed a signal detection analysis (SDA) and built a mixture model to classify dimensional response based on the change in the YGTSS-TTS. A 25% decrease on the YGTSS-TTS predicted positive response on the CGI-I during the trial. The SDA showed that a 25% reduction in the YGTSS-TTS provided optimal sensitivity (87%) and specificity (84%) for predicting positive response. Using a mixture model without consideration of the CGI-I, the dimensional response was defined by 23% (or greater) reduction on the YGTSS-TTS. The odds ratio (OR) of positive response (OR=5.68, 95% CI=[2.99, 10.78]) on the CGI-I for behavioral intervention was greater than the dimensional response (OR=2.86, 95% CI=[1.65, 4.99]). A 25% reduction on the YGTSS-TTS is highly predictive of positive response by all three analytic methods. For trained raters, however, tic severity alone does not drive the classification of positive response. Clinicaltrials.gov identifiers: NCT00218777; NCT00231985. © 2013.

  20. Multivariate methods for the detection of greenhouse-gas-induced climate change

    International Nuclear Information System (INIS)

    Santer, B.D.; Wigley, T.M.L.; Jones, P.D.; Schlesinger, M.E.

    1990-01-01

    This investigation considers whether observed changes in surface air temperature are consistent with GCM equilibrium response predictions for a doubling of atmospheric CO 2 . The model considered is a version of the Oregon State University (OSU) atmospheric general circulation model (AGCM). The study consists of three stages. In the first stage the authors examine the spatial structure of changes in the annual mean and annual cycle for surface air temperature, mean sea-level pressure (SLP) and precipitation rate. Signal-to-noise (S/N) ratios or equivalent test statistics are then computed (using the 1 x CO 2 and 2 x CO 2 data) in order to identify variables most useful for detection purposes. Changes in both means and variances are considered as possible detection parameters. The highest S/N ratios are obtained for annual-mean and winter surface air temperature, and the lowest S/N ratios are obtained for SLP. There are significant increases in the temporal and spatial variability of precipitation, and significant decreases in the temporal and spatial variability of surface air temperature

  1. Metode za otkrivanje promjena kod daljinskih istraživanja : Methods for change detection in remote sensing

    Directory of Open Access Journals (Sweden)

    Admir Mulahusić

    2011-03-01

    Full Text Available U ovom radu predstavljeni su različiti načini identifikovanja promjena kod daljinskih istraživanja. Različiti autori su predstavljali različite metode otkrivanja promjena na površini zemlje. Otkrivanje promjena je, između ostalog, veoma važno zbog praćenja promjena, kao i procjene promjena i međusobnih odnosa prirodnih i vještačkih objekata. Sve to vodi ka boljem razumijevanju potencijalnih uzroka promjena. : In this paper, the different ways to identify changes in remote sensing are given. Various authors have presented different methods of detecting changes on the Earth's surface. Detection of changes, among other things, are very important for tracking changes, as well as assessment and evaluation of changes and interrelations of natural and artificial objects. All this leads to better understanding of potential causes of change.

  2. A simple and effective radiometric correction method to improve landscape change detection across sensors and across time

    Science.gov (United States)

    Chen, X.; Vierling, Lee; Deering, D.

    2005-01-01

    Satellite data offer unrivaled utility in monitoring and quantifying large scale land cover change over time. Radiometric consistency among collocated multi-temporal imagery is difficult to maintain, however, due to variations in sensor characteristics, atmospheric conditions, solar angle, and sensor view angle that can obscure surface change detection. To detect accurate landscape change using multi-temporal images, we developed a variation of the pseudoinvariant feature (PIF) normalization scheme: the temporally invariant cluster (TIC) method. Image data were acquired on June 9, 1990 (Landsat 4), June 20, 2000 (Landsat 7), and August 26, 2001 (Landsat 7) to analyze boreal forests near the Siberian city of Krasnoyarsk using the normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), and reduced simple ratio (RSR). The temporally invariant cluster (TIC) centers were identified via a point density map of collocated pixel VIs from the base image and the target image, and a normalization regression line was created to intersect all TIC centers. Target image VI values were then recalculated using the regression function so that these two images could be compared using the resulting common radiometric scale. We found that EVI was very indicative of vegetation structure because of its sensitivity to shadowing effects and could thus be used to separate conifer forests from deciduous forests and grass/crop lands. Conversely, because NDVI reduced the radiometric influence of shadow, it did not allow for distinctions among these vegetation types. After normalization, correlations of NDVI and EVI with forest leaf area index (LAI) field measurements combined for 2000 and 2001 were significantly improved; the r 2 values in these regressions rose from 0.49 to 0.69 and from 0.46 to 0.61, respectively. An EVI "cancellation effect" where EVI was positively related to understory greenness but negatively related to forest canopy coverage was evident across a

  3. Supervised / unsupervised change detection

    OpenAIRE

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

    2014-01-01

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

  4. Remote sensing change detection methods to track deforestation and growth in threatened rainforests in Madre de Dios, Peru

    Science.gov (United States)

    Shermeyer, Jacob S.; Haack, Barry N.

    2015-01-01

    Two forestry-change detection methods are described, compared, and contrasted for estimating deforestation and growth in threatened forests in southern Peru from 2000 to 2010. The methods used in this study rely on freely available data, including atmospherically corrected Landsat 5 Thematic Mapper and Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation continuous fields (VCF). The two methods include a conventional supervised signature extraction method and a unique self-calibrating method called MODIS VCF guided forest/nonforest (FNF) masking. The process chain for each of these methods includes a threshold classification of MODIS VCF, training data or signature extraction, signature evaluation, k-nearest neighbor classification, analyst-guided reclassification, and postclassification image differencing to generate forest change maps. Comparisons of all methods were based on an accuracy assessment using 500 validation pixels. Results of this accuracy assessment indicate that FNF masking had a 5% higher overall accuracy and was superior to conventional supervised classification when estimating forest change. Both methods succeeded in classifying persistently forested and nonforested areas, and both had limitations when classifying forest change.

  5. Automatic change detection in RapidEye data using the combined MAD and kernel MAF methods

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg; Hecheltjen, Antje; Thonfeld, Frank

    2010-01-01

    The IR-MAD components show changes for a large part of the entire subset. Especially phenological changes in the agricultural fields surrounding the open pit are predominant. As opposed to this, kMAF components focus more on changes in the open-cast mine (and changes due to the two clouds...... and their shadows, not visible in the zoom). Ground data were available from bucket-wheel excavators on the extraction side (to the northwest in the open pit) in terms of elevation data for both dates. No ground data were available for changes due to backfill (southeastern part of the open pit) or changes due...

  6. Detection of Anomalies and Changes of Rainfall in the Yellow River Basin, China, through Two Graphical Methods

    Directory of Open Access Journals (Sweden)

    Hao Wu

    2017-12-01

    Full Text Available This study aims to reveal rainfall anomalies and changes over the Yellow River Basin due to the fragile ecosystem and rainfall-related disasters. Common trend analyses relate to overall trends in mean values. Therefore, we used two graphical methods: the quantile perturbation method (QPM was used to investigate anomalies over time in extreme rainfall, and the partial trend method (PTM was used to analyze rainfall changes at different intensities. A nonparametric bootstrap procedure is proposed in order to identify significant PTM indices. The QPM indicated prevailing positive anomalies in extreme daily rainfall 50 years ago and in the middle reaches during the 1970s and 1980s. The PTM detected significant decreases in annual rainfall mainly in the latter half of the middle reaches, two-thirds of which occurred in high and heavy rainfall. Most stations in the middle and lower reaches showed significant decreases in rainy days. Daily rainfall intensity had a significant increase at 13 stations, where rainy days were generally decreasing. The combined effect of these opposing changes explains the prevailing absence of change in annual rainfall, and the observed decreases in annual rainfall can be attributed to the decreasing number of rainy days. The changes in rainy days and rainfall intensity were dominated by the wet season and dry season, respectively.

  7. Combining the Pixel-based and Object-based Methods for Building Change Detection Using High-resolution Remote Sensing Images

    Directory of Open Access Journals (Sweden)

    ZHANG Zhiqiang

    2018-01-01

    Full Text Available Timely and accurate change detection of buildings provides important information for urban planning and management.Accompanying with the rapid development of satellite remote sensing technology,detecting building changes from high-resolution remote sensing images have received wide attention.Given that pixel-based methods of change detection often lead to low accuracy while object-based methods are complicated for uses,this research proposes a method that combines pixel-based and object-based methods for detecting building changes from high-resolution remote sensing images.First,based on the multiple features extracted from the high-resolution images,a random forest classifier is applied to detect changed building at the pixel level.Then,a segmentation method is applied to segement the post-phase remote sensing image and to get post-phase image objects.Finally,both changed building at the pixel level and post-phase image objects are fused to recognize the changed building objects.Multi-temporal QuickBird images are used as experiment data for building change detection with high-resolution remote sensing images,the results indicate that the proposed method could reduce the influence of environmental difference,such as light intensity and view angle,on building change detection,and effectively improve the accuracies of building change detection.

  8. DETECTION OF CHANGES OF THE SYSTEM TECHNICAL STATE USING STOCHASTIC SUBSPACE OBSERVATION METHOD

    Directory of Open Access Journals (Sweden)

    Andrzej Puchalski

    2014-03-01

    Full Text Available System diagnostics based on vibroacoustics signals, carried out by means of stochastic subspace methods was undertaken in the hereby paper. Subspace methods are the ones based on numerical linear algebra tools. The considered solutions belong to diagnostic methods according to data, leading to the generation of residuals allowing failure recognition of elements and assemblies in machines and devices. The algorithm of diagnostics according to the subspace observation method was applied – in the paper – for the estimation of the valve system of the spark ignition engine.

  9. On Radar Resolution in Coherent Change Detection.

    Energy Technology Data Exchange (ETDEWEB)

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

    2015-11-01

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

  10. HMCan-diff: a method to detect changes in histone modifications in cells with different genetic characteristics

    KAUST Repository

    Ashoor, Haitham

    2016-12-19

    Comparing histone modification profiles between cancer and normal states, or across different tumor samples, can provide insights into understanding cancer initiation, progression and response to therapy. ChIP-seq histone modification data of cancer samples are distorted by copy number variation innate to any cancer cell. We present HMCan-diff, the first method designed to analyze ChIP-seq data to detect changes in histone modifications between two cancer samples of different genetic backgrounds, or between a cancer sample and a normal control. HMCan-diff explicitly corrects for copy number bias, and for other biases in the ChIP-seq data, which significantly improves prediction accuracy compared to methods that do not consider such corrections. On in silico simulated ChIP-seq data generated using genomes with differences in copy number profiles, HMCan-diff shows a much better performance compared to other methods that have no correction for copy number bias. Additionally, we benchmarked HMCan-diff on four experimental datasets, characterizing two histone marks in two different scenarios. We correlated changes in histone modifications between a cancer and a normal control sample with changes in gene expression. On all experimental datasets, HMCan-diff demonstrated better performance compared to the other methods.

  11. An Unsupervised Method of Change Detection in Multi-Temporal PolSAR Data Using a Test Statistic and an Improved K&I Algorithm

    Directory of Open Access Journals (Sweden)

    Jinqi Zhao

    2017-12-01

    Full Text Available In recent years, multi-temporal imagery from spaceborne sensors has provided a fast and practical means for surveying and assessing changes in terrain surfaces. Owing to the all-weather imaging capability, polarimetric synthetic aperture radar (PolSAR has become a key tool for change detection. Change detection methods include both unsupervised and supervised methods. Supervised change detection, which needs some human intervention, is generally ineffective and impractical. Due to this limitation, unsupervised methods are widely used in change detection. The traditional unsupervised methods only use a part of the polarization information, and the required thresholding algorithms are independent of the multi-temporal data, which results in the change detection map being ineffective and inaccurate. To solve these problems, a novel method of change detection using a test statistic based on the likelihood ratio test and the improved Kittler and Illingworth (K&I minimum-error thresholding algorithm is introduced in this paper. The test statistic is used to generate the comparison image (CI of the multi-temporal PolSAR images, and improved K&I using a generalized Gaussian model simulates the distribution of the CI. As a result of these advantages, we can obtain the change detection map using an optimum threshold. The efficiency of the proposed method is demonstrated by the use of multi-temporal PolSAR images acquired by RADARSAT-2 over Wuhan, China. The experimental results show that the proposed method is effective and highly accurate.

  12. A new method to detect significant basal body temperature changes during a woman's menstrual cycle.

    Science.gov (United States)

    Freundl, Günter; Frank-Herrmann, Petra; Brown, Simon; Blackwell, Leonard

    2014-10-01

    To compare the results of a computer programme based on the Trigg's tracking system (TTS) identification of the basal body temperature (BBT) shift day from daily records of BBT values (TTS transition day), with the BBT shift day identified from the same records using the Sensiplan(®) symptothermal method of natural family planning. A computer programme was written to display the daily BBT readings for 364 menstrual cycles from 51 women aged 24 to 35 years, obtained from the German Natural Family Planning (NFP) database. The TTS transition day so identified from each record was then compared with the BBT shift day estimated from the same record by the Sensiplan(®) method. Total agreement between the methods was obtained for 81% (294/364) of the cycles and 18% (67) cycles differed by ± 1 day. For the 364 pairs of values distributed among 51 women the medians of the differences between the TTS transition day and Sensiplan(®) initial day of the BBT rise (shift day) were not significantly different (χ(2) = 65.28, df = 50, p = 0.07205). The advantages of the tracking signal algorithm are that in many cases it was possible to identify the BBT shift day on that very day - rather than only some days later - and to estimate the probability that a transition had occurred from the different values of the tracking signal.

  13. What lies beneath: detecting sub-canopy changes in savanna woodlands using a three-dimensional classification method

    CSIR Research Space (South Africa)

    Fisher, JT

    2015-07-01

    Full Text Available structural diversity. A 3D classification approach was successful in detecting fine-scale, short-term changes between land uses, and can thus be used as amonitoring tool for savannawoody vegetation structure....

  14. Change detection by the IR-MAD and kernel MAF methods in Landsat TM data covering a Swedish forest region

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg; Olsson, Håkan

    2010-01-01

    Change over time between two 512 by 512 (25 m by 25 m pixels) multispectral Landsat Thematic Mapper images dated 6 June 1986 and 27 June 1988 respectively covering a forested region in northern Sweden, is here detected by means of the iteratively reweighted multivariate alteration detection (IR-M...

  15. Leak detection method

    International Nuclear Information System (INIS)

    1978-01-01

    This invention provides a method for removing nuclear fuel elements from a fabrication building while at the same time testing the fuel elements for leaks without releasing contaminants from the fabrication building or from the fuel elements. The vacuum source used, leak detecting mechanism and fuel element fabrication building are specified to withstand environmental hazards. (UK)

  16. CARAT: A novel method for allelic detection of DNA copy number changes using high density oligonucleotide arrays

    Directory of Open Access Journals (Sweden)

    Ishikawa Shumpei

    2006-02-01

    Full Text Available Abstract Background DNA copy number alterations are one of the main characteristics of the cancer cell karyotype and can contribute to the complex phenotype of these cells. These alterations can lead to gains in cellular oncogenes as well as losses in tumor suppressor genes and can span small intervals as well as involve entire chromosomes. The ability to accurately detect these changes is central to understanding how they impact the biology of the cell. Results We describe a novel algorithm called CARAT (Copy Number Analysis with Regression And Tree that uses probe intensity information to infer copy number in an allele-specific manner from high density DNA oligonuceotide arrays designed to genotype over 100, 000 SNPs. Total and allele-specific copy number estimations using CARAT are independently evaluated for a subset of SNPs using quantitative PCR and allelic TaqMan reactions with several human breast cancer cell lines. The sensitivity and specificity of the algorithm are characterized using DNA samples containing differing numbers of X chromosomes as well as a test set of normal individuals. Results from the algorithm show a high degree of agreement with results from independent verification methods. Conclusion Overall, CARAT automatically detects regions with copy number variations and assigns a significance score to each alteration as well as generating allele-specific output. When coupled with SNP genotype calls from the same array, CARAT provides additional detail into the structure of genome wide alterations that can contribute to allelic imbalance.

  17. An Unsupervised Change Detection Method Using Time-Series of PolSAR Images from Radarsat-2 and GaoFen-3.

    Science.gov (United States)

    Liu, Wensong; Yang, Jie; Zhao, Jinqi; Shi, Hongtao; Yang, Le

    2018-02-12

    The traditional unsupervised change detection methods based on the pixel level can only detect the changes between two different times with same sensor, and the results are easily affected by speckle noise. In this paper, a novel method is proposed to detect change based on time-series data from different sensors. Firstly, the overall difference image of the time-series PolSAR is calculated by omnibus test statistics, and difference images between any two images in different times are acquired by R j test statistics. Secondly, the difference images are segmented with a Generalized Statistical Region Merging (GSRM) algorithm which can suppress the effect of speckle noise. Generalized Gaussian Mixture Model (GGMM) is then used to obtain the time-series change detection maps in the final step of the proposed method. To verify the effectiveness of the proposed method, we carried out the experiment of change detection using time-series PolSAR images acquired by Radarsat-2 and Gaofen-3 over the city of Wuhan, in China. Results show that the proposed method can not only detect the time-series change from different sensors, but it can also better suppress the influence of speckle noise and improve the overall accuracy and Kappa coefficient.

  18. Multi- and hyperspectral remote sensing change detection with generalized difference images by the IR-MAD method

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg; Canty, Morton J.

    2005-01-01

    -based method for determining thresholds for differentiating between change and no-change in the difference images, and for estimating the variance of the no-change observations. This variance is used to establish a single change/no-change image based on the general multivariate difference image. The resulting....../no-change image can be used to establish both change regions and to extract observations based on which a fully automated orthogonal regression analysis based normalization of the multivariate data between the two points in time can be developed. Also, regularization issues typically important in connection...

  19. Remote detection device and detection method therefor

    International Nuclear Information System (INIS)

    Kogure, Sumio; Yoshida, Yoji; Matsuo, Takashiro; Takehara, Hidetoshi; Kojima, Shinsaku.

    1997-01-01

    The present invention provides a non-destructive detection device for collectively, efficiently and effectively conducting maintenance and detection for confirming the integrity of a nuclear reactor by way of a shielding member for shielding radiation rays generated from an objective portion to be detected. Namely, devices for direct visual detection using an under water TV camera as a sensor, an eddy current detection using a coil as a sensor and each magnetic powder flow detection are integrated and applied collectively. Specifically, the visual detection by using the TV camera and the eddy current flaw detection are adopted together. The flaw detection with magnetic powder is applied as a means for confirming the results of the two kinds of detections by other method. With such procedures, detection techniques using respective specific theories are combined thereby enabling to enhance the accuracy for the evaluation of the detection. (I.S.)

  20. Microbial Contamination Detection in Water Resources: Interest of Current Optical Methods, Trends and Needs in the Context of Climate Change

    Directory of Open Access Journals (Sweden)

    Aude-Valérie Jung

    2014-04-01

    Full Text Available Microbial pollution in aquatic environments is one of the crucial issues with regard to the sanitary state of water bodies used for drinking water supply, recreational activities and harvesting seafood due to a potential contamination by pathogenic bacteria, protozoa or viruses. To address this risk, microbial contamination monitoring is usually assessed by turbidity measurements performed at drinking water plants. Some recent studies have shown significant correlations of microbial contamination with the risk of endemic gastroenteresis. However the relevance of turbidimetry may be limited since the presence of colloids in water creates interferences with the nephelometric response. Thus there is a need for a more relevant, simple and fast indicator for microbial contamination detection in water, especially in the perspective of climate change with the increase of heavy rainfall events. This review focuses on the one hand on sources, fate and behavior of microorganisms in water and factors influencing pathogens’ presence, transportation and mobilization, and on the second hand, on the existing optical methods used for monitoring microbiological risks. Finally, this paper proposes new ways of research.

  1. Updating the 2001 National Land Cover Database Impervious Surface Products to 2006 using Landsat imagery change detection methods

    Science.gov (United States)

    Xian, George; Homer, Collin G.

    2010-01-01

    A prototype method was developed to update the U.S. Geological Survey (USGS) National Land Cover Database (NLCD) 2001 to a nominal date of 2006. NLCD 2001 is widely used as a baseline for national land cover and impervious cover conditions. To enable the updating of this database in an optimal manner, methods are designed to be accomplished by individual Landsat scene. Using conservative change thresholds based on land cover classes, areas of change and no-change were segregated from change vectors calculated from normalized Landsat scenes from 2001 and 2006. By sampling from NLCD 2001 impervious surface in unchanged areas, impervious surface predictions were estimated for changed areas within an urban extent defined by a companion land cover classification. Methods were developed and tested for national application across six study sites containing a variety of urban impervious surface. Results show the vast majority of impervious surface change associated with urban development was captured, with overall RMSE from 6.86 to 13.12% for these areas. Changes of urban development density were also evaluated by characterizing the categories of change by percentile for impervious surface. This prototype method provides a relatively low cost, flexible approach to generate updated impervious surface using NLCD 2001 as the baseline.

  2. A new relative radiometric consistency processing method for change detection based on wavelet transform and a low-pass filter

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    The research purpose of this paper is to show the limitations of the existing radiometric normalization approaches and their disadvantages in change detection of artificial objects by comparing the existing approaches,on the basis of which a preprocessing approach to radiometric consistency,based on wavelet transform and a spatial low-pass filter,has been devised.This approach first separates the high frequency information and low frequency information by wavelet transform.Then,the processing of relative radiometric consistency based on a low-pass filter is conducted on the low frequency parts.After processing,an inverse wavelet transform is conducted to obtain the results image.The experimental results show that this approach can substantially reduce the influence on change detection of linear or nonlinear radiometric differences in multi-temporal images.

  3. Failed fuel detection method

    International Nuclear Information System (INIS)

    Utamura, Motoaki; Urata, Megumu.

    1976-01-01

    Object: To detect failed fuel element in a reactor with high precision by measuring the radioactivity concentrations for more than one nuclides of fission products ( 131 I and 132 I, for example) contained in each sample of coolant in fuel channel. Method: The radioactivity concentrations in the sampled coolant are obtained from gamma spectra measured by a pulse height analyser after suitable cooling periods according to the half-lives of the fission products to be measured. The first measurement for 132 I is made in two hours after sampling, and the second for 131 I is started one day after the sampling. Fuel element corresponding to the high radioactivity concentrations for both 131 I and 132 I is expected with certainty to have failed

  4. Updating the 2001 National Land Cover Database land cover classification to 2006 by using Landsat imagery change detection methods

    Science.gov (United States)

    Xian, George; Homer, Collin G.; Fry, Joyce

    2009-01-01

    The recent release of the U.S. Geological Survey (USGS) National Land Cover Database (NLCD) 2001, which represents the nation's land cover status based on a nominal date of 2001, is widely used as a baseline for national land cover conditions. To enable the updating of this land cover information in a consistent and continuous manner, a prototype method was developed to update land cover by an individual Landsat path and row. This method updates NLCD 2001 to a nominal date of 2006 by using both Landsat imagery and data from NLCD 2001 as the baseline. Pairs of Landsat scenes in the same season in 2001 and 2006 were acquired according to satellite paths and rows and normalized to allow calculation of change vectors between the two dates. Conservative thresholds based on Anderson Level I land cover classes were used to segregate the change vectors and determine areas of change and no-change. Once change areas had been identified, land cover classifications at the full NLCD resolution for 2006 areas of change were completed by sampling from NLCD 2001 in unchanged areas. Methods were developed and tested across five Landsat path/row study sites that contain several metropolitan areas including Seattle, Washington; San Diego, California; Sioux Falls, South Dakota; Jackson, Mississippi; and Manchester, New Hampshire. Results from the five study areas show that the vast majority of land cover change was captured and updated with overall land cover classification accuracies of 78.32%, 87.5%, 88.57%, 78.36%, and 83.33% for these areas. The method optimizes mapping efficiency and has the potential to provide users a flexible method to generate updated land cover at national and regional scales by using NLCD 2001 as the baseline.

  5. Detecting change-points in extremes

    KAUST Repository

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

    2015-01-01

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

  6. Adaptive filtering and change detection

    CERN Document Server

    Gustafsson, Fredrik

    2003-01-01

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

  7. Climate change and precipitation: Detecting changes Climate change and precipitation: Detecting changes

    International Nuclear Information System (INIS)

    Van Boxel, John H

    2001-01-01

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

  8. DNA Comet Assay and Changes in Microflora Load as Screening Methods to Detect Irradiated Food in Egypt

    International Nuclear Information System (INIS)

    Hammad, A.A.; Abo El Nour, S.A.; Ibrahim, H.M.; Osman, M.E.; Abo El- Nasr, A.

    2014-01-01

    In the present study the microgel electrophoresis of single cells (DNA Comet Assay), and changes in microflora load were applied to detect irradiation treatment of strawberries and fresh-deboned chicken produced in Egypt. Strawberry samples were irradiated at 1.0, 2.0, 3.0 and 4.0 kGy, stored at 4 degree C±1 and analyzed at 0 and 7 days post.-irradiation. Fresh- deboned chicken meat samples were exposed to 2.0, 3.0, 4.0 and 5.0 kGy, stored at 4 degree C±1 and analyzed at 0, 7, 14 and 21 days post-irradiation. After electrophoresis performance, the accridine orange stain slides were seen under fluorescent microscope and the DNA comets were evaluated by photographic and image analysis. Changes in microflora load of irradiated samples were also evaluated. In all irradiated samples, the DNA fragments stretched or migrated out of the cells towards the anode of the agrose gel and appeared as a “comets” with tail. Whereas, DNA comets of all non-irradiated samples were almost intact, round without tail or had very short tail. Values of DNA % in tails and the tail length increased with increasing irradiation dose and storage times. The DNA comet assay could successfully be used to detect radiation treatment of strawberry and deboned-chicken meat samples up to 7 and 21 days post-irradiation, respectively. The absence of gram-negative bacteria and enterobacteriaceae group as well as the very low count of fungi (mostly yeasts) might be considered another evidence of radiation treatment of strawberries and fresh-deboned chicken.

  9. Detecting change-points in extremes

    KAUST Repository

    Dupuis, D. J.

    2015-01-01

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

  10. Adaptively detecting changes in Autonomic Grid Computing

    KAUST Repository

    Zhang, Xiangliang

    2010-10-01

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

  11. Crack detecting method

    International Nuclear Information System (INIS)

    Narita, Michiko; Aida, Shigekazu

    1998-01-01

    A penetration liquid or a slow drying penetration liquid prepared by mixing a penetration liquid and a slow drying liquid is filled to the inside of an artificial crack formed to a member to be detected such as of boiler power generation facilities and nuclear power facilities. A developing liquid is applied to the periphery of the artificial crack on the surface of a member to be detected. As the slow-drying liquid, an oil having a viscosity of 56 is preferably used. Loads are applied repeatedly to the member to be detected, and when a crack is caused to the artificial crack, the permeation liquid penetrates into the crack. The penetration liquid penetrated into the crack is developed by the developing liquid previously coated to the periphery of the artificial crack of the surface of the member to be detected. When a crack is caused, since the crack is developed clearly even if it is a small opening, the crack can be recognized visually reliably. (I.N.)

  12. Nonlinear Multiantenna Detection Methods

    Directory of Open Access Journals (Sweden)

    Chen Sheng

    2004-01-01

    Full Text Available A nonlinear detection technique designed for multiple-antenna assisted receivers employed in space-division multiple-access systems is investigated. We derive the optimal solution of the nonlinear spatial-processing assisted receiver for binary phase shift keying signalling, which we refer to as the Bayesian detector. It is shown that this optimal Bayesian receiver significantly outperforms the standard linear beamforming assisted receiver in terms of a reduced bit error rate, at the expense of an increased complexity, while the achievable system capacity is substantially enhanced with the advent of employing nonlinear detection. Specifically, when the spatial separation expressed in terms of the angle of arrival between the desired and interfering signals is below a certain threshold, a linear beamformer would fail to separate them, while a nonlinear detection assisted receiver is still capable of performing adequately. The adaptive implementation of the optimal Bayesian detector can be realized using a radial basis function network. Two techniques are presented for constructing block-data-based adaptive nonlinear multiple-antenna assisted receivers. One of them is based on the relevance vector machine invoked for classification, while the other on the orthogonal forward selection procedure combined with the Fisher ratio class-separability measure. A recursive sample-by-sample adaptation procedure is also proposed for training nonlinear detectors based on an amalgam of enhanced -means clustering techniques and the recursive least squares algorithm.

  13. A colorimetric method for highly sensitive and accurate detection of iodide by finding the critical color in a color change process using silver triangular nanoplates

    Energy Technology Data Exchange (ETDEWEB)

    Yang, Xiu-Hua; Ling, Jian, E-mail: lingjian@ynu.edu.cn; Peng, Jun; Cao, Qiu-E., E-mail: qecao@ynu.edu.cn; Ding, Zhong-Tao; Bian, Long-Chun

    2013-10-10

    Graphical abstract: -- Highlights: •Demonstrated a new colorimetric strategy for iodide detection by silver nanoplates. •The colorimetric strategy is to find the critical color in a color change process. •The colorimetric strategy is more accurate and sensitive than common colorimetry. •Discovered a new morphological transformation phenomenon of silver nanoplates. -- Abstract: In this contribution, we demonstrated a novel colorimetric method for highly sensitive and accurate detection of iodide using citrate-stabilized silver triangular nanoplates (silver TNPs). Very lower concentration of iodide can induce an appreciable color change of silver TNPs solution from blue to yellow by fusing of silver TNPs to nanoparticles, as confirmed by UV–vis absorption spectroscopy and transmission electron microscopy (TEM). The principle of this colorimetric assay is not an ordinary colorimetry, but a new colorimetric strategy by finding the critical color in a color change process. With this strategy, 0.1 μM of iodide can be recognized within 30 min by naked-eyes observation, and lower concentration of iodide down to 8.8 nM can be detected using a spectrophotometer. Furthermore, this high sensitive colorimetric assay has good accuracy, stability and reproducibility comparing with other ordinary colorimetry. We believe this new colorimetric method will open up a fresh insight of simple, rapid and reliable detection of iodide and can find its future application in the biochemical analysis or clinical diagnosis.

  14. A colorimetric method for highly sensitive and accurate detection of iodide by finding the critical color in a color change process using silver triangular nanoplates

    International Nuclear Information System (INIS)

    Yang, Xiu-Hua; Ling, Jian; Peng, Jun; Cao, Qiu-E.; Ding, Zhong-Tao; Bian, Long-Chun

    2013-01-01

    Graphical abstract: -- Highlights: •Demonstrated a new colorimetric strategy for iodide detection by silver nanoplates. •The colorimetric strategy is to find the critical color in a color change process. •The colorimetric strategy is more accurate and sensitive than common colorimetry. •Discovered a new morphological transformation phenomenon of silver nanoplates. -- Abstract: In this contribution, we demonstrated a novel colorimetric method for highly sensitive and accurate detection of iodide using citrate-stabilized silver triangular nanoplates (silver TNPs). Very lower concentration of iodide can induce an appreciable color change of silver TNPs solution from blue to yellow by fusing of silver TNPs to nanoparticles, as confirmed by UV–vis absorption spectroscopy and transmission electron microscopy (TEM). The principle of this colorimetric assay is not an ordinary colorimetry, but a new colorimetric strategy by finding the critical color in a color change process. With this strategy, 0.1 μM of iodide can be recognized within 30 min by naked-eyes observation, and lower concentration of iodide down to 8.8 nM can be detected using a spectrophotometer. Furthermore, this high sensitive colorimetric assay has good accuracy, stability and reproducibility comparing with other ordinary colorimetry. We believe this new colorimetric method will open up a fresh insight of simple, rapid and reliable detection of iodide and can find its future application in the biochemical analysis or clinical diagnosis

  15. Is air-displacement plethysmography a reliable method of detecting ongoing changes in percent body fat within obese children involved in a weight management program?

    DEFF Research Database (Denmark)

    Ewane, Cecile; McConkey, Stacy A; Kreiter, Clarence D

    2010-01-01

    (percent body fat) over time. The gold standard method, hydrodensitometry, has severe limitations for the pediatric population. OBJECTIVE: This study examines the reliability of air-displacement plethysmography (ADP) in detecting percent body fat changes within obese children over time. METHODS: Percent...... body fat by ADP, weight, and body mass index (BMI) were measured for eight obese children aged 5-12 years enrolled in a weight management program over a 12-month period. These measurements were taken at initial evaluation, 1.5 months, 3 months, 6 months, and 12 months to monitor the progress...... of the subjects and detect any changes in these measures over time. Statistical analysis was used to determine the reliability of the data collected. RESULTS: The reliability estimate for percent body fat by ADP was 0.78. This was much lower than the reliability of BMI, 0.98, and weight measurements, 0...

  16. Multisensor Fusion for Change Detection

    Science.gov (United States)

    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. Non-invasive method to detect the changes of glucose concentration in whole blood using photometric technique.

    Science.gov (United States)

    Rajan, Shiny Amala Priya; Towe, Bruce C

    2014-01-01

    A non-invasive method is developed to monitor rapid changes in blood glucose levels in diabetic patients. The system depends on an optical cell built with a LED that emits light of wavelength 535nm, which is a peak absorbance of hemoglobin. As the glucose concentration in blood decreases, its osmolarity also decreases and the Red Blood Cells (RBCs) swell and decrease the path length absorption coefficient. Decreasing absorption coefficient increases the transmission of light through the whole blood. The system was tested with a constructed optical cell that held whole blood in a capillary tube. As expected the light transmitted to the photodiode increases with decreasing glucose concentration. The average response time of the system was between 30-40 seconds.

  18. A Voltage Quality Detection Method

    DEFF Research Database (Denmark)

    Chen, Zhe; Wei, Mu

    2008-01-01

    This paper presents a voltage quality detection method based on a phase-locked loop (PLL) technique. The technique can detect the voltage magnitude and phase angle of each individual phase under both normal and fault power system conditions. The proposed method has the potential to evaluate various...

  19. 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.

    Science.gov (United States)

    Roush, W.; Munroe, Jeffrey 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.

  20. Detection methods for irradiated food

    International Nuclear Information System (INIS)

    Stevenson, M.H.

    1993-01-01

    The plenary lecture gives a brief historical review of the development of methods for the detection of food irradiation and defines the demands on such methods. The methods described in detail are as follows: 1) Physical methods: As examples of luminescence methods, thermoluminescence and chermoluminescence are mentioned; ESR spectroscopy is discussed in detail by means of individual examples (crustaceans, frutis and vegetables, spieces and herbs, nuts). 2) Chemical methods: Examples given for these are methods that make use of alterations in lipids through radiation (formation of long-chain hydrocarbons, formation of 2-alkyl butanones), respectively radiation-induced alterations in the DNA. 3) Microbiological methods. An extensive bibliography is appended. (VHE) [de

  1. Land-cover change detection

    Science.gov (United States)

    Chen, Xuexia; Giri, Chandra; Vogelmann, James

    2012-01-01

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

  2. A comparison of change detection measurements using object-based and pixel-based classification methods on western juniper dominated woodlands in eastern Oregon

    Directory of Open Access Journals (Sweden)

    Ryan G. Howell

    2017-03-01

    Full Text Available Encroachment of pinyon (Pinus spp and juniper (Juniperus spp. woodlands in western North America is considered detrimental due to its effects on ecohydrology, plant community structure, and soil stability. Management plans at the federal, state, and private level often include juniper removal for improving habitat of sensitive species and maintaining sustainable ecosystem processes. Remote sensing has become a useful tool in determining changes in juniper woodland structure because of its uses in comparing archived historic imagery with newly available multispectral images to provide information on changes that are no longer detectable by field measurements. Change in western juniper (J. occidentalis cover was detected following juniper removal treatments between 1995 and 2011 using panchromatic 1-meter NAIP and 4-band 1-meter NAIP imagery, respectively. Image classification was conducted using remotely sensed images taken at the Roaring Springs Ranch in southeastern Oregon. Feature Analyst for ArcGIS (object-based extraction and a supervised classification with ENVI 5.2 (pixel-based extraction were used to delineate juniper canopy cover. Image classification accuracy was calculated using an Accuracy Assessment and Kappa Statistic. Both methods showed approximately a 76% decrease in western juniper cover, although differing in total canopy cover area, with object-based classification being more accurate. Classification results for the 2011 imagery were much more accurate (0.99 Kappa statistic because of its low juniper density and the presence of an infrared band. The development of methods for detecting change in juniper cover can lead to more accurate and efficient data acquisition and subsequently improved land management and monitoring practices. These data can subsequently be used to assess and quantify juniper invasion and succession, potential ecological impacts, and plant community resilience.

  3. Rapid Change Detection Algorithm for Disaster Management

    Science.gov (United States)

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

    2012-07-01

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

  4. Metode za otkrivanje promjena kod daljinskih istraživanja : Methods for change detection in remote sensing

    OpenAIRE

    Admir Mulahusić; Nedim Tuno

    2011-01-01

    U ovom radu predstavljeni su različiti načini identifikovanja promjena kod daljinskih istraživanja. Različiti autori su predstavljali različite metode otkrivanja promjena na površini zemlje. Otkrivanje promjena je, između ostalog, veoma važno zbog praćenja promjena, kao i procjene promjena i međusobnih odnosa prirodnih i vještačkih objekata. Sve to vodi ka boljem razumijevanju potencijalnih uzroka promjena. : In this paper, the different ways to identify changes in remote sensing are given. V...

  5. Spices, irradiation and detection methods

    International Nuclear Information System (INIS)

    Sjoeberg, A.M.; Manninen, M.

    1991-01-01

    This paper is about microbiological aspects of spices and microbiological methods to detect irradiated food. The proposed method is a combination of the Direct Epifluorescence Filter Technique (DEFT) and the Aerobic Plate Count (APC). The evidence for irradiation of spices is based on the demonstration of a higher DEFT count than the APC. The principle was first tested in our earlier investigation in the detection of irradiation of whole spices. The combined DEFT+APC procedure was found to give a fairly reliable indication of whether or not a whole spice sample had been irradiated. The results are given (8 figs, 22 refs)

  6. Investigation of environmental change on the Tega Lake based on lake sediment analysis. Pt. 2. Dating of sediment by the lead-210/cesium-137 method and environmental change detected by the diatom assemblage analysis

    International Nuclear Information System (INIS)

    Hamada, Takaomi

    1998-01-01

    Sediment collected in the Tega Lake was dated by lead-210/cesium-137 method and environmental change in the Tega Lake was investigated by analysis of diatom remain assemblages in the sediment. Dating of the lead-210/cesium-137 method proved that the surface 30 cm-thickness of sediment in the Tega Lake was deposited during the recent 50 years. Diatom remain assemblage change in the Hon-Tega Lake sediment started in the early half of 1960's and the changes is characterized decrease of Fragilaria construens, that does not prefer to inhabit eutrophic water, and increase of Cyclotella meneghiniana that prefers to inhabit eutrophic water. This diatom assemblage change indicates that the Tega Lake was eutrophicated, and probably suggests water pollution in the Tega Lake. It is detected that influence of residential development around the Tega Lake and reclaiming by drainage on the Tega Lake. (author)

  7. Detection methods for irradiated foods

    International Nuclear Information System (INIS)

    Dyakova, A.; Tsvetkova, E.; Nikolova, R.

    2005-01-01

    In connection with the ongoing world application of irradiation as a technology in Food industry for increasing food safety, it became a need for methods of identification of irradiation. It was required to control international trade of irradiated foods, because of the certain that legally imposed food laws are not violated; supervise correct labeling; avoid multiple irradiation. Physical, chemical and biological methods for detection of irradiated foods as well principle that are based, are introducing in this summary

  8. Adjunct methods for caries detection

    DEFF Research Database (Denmark)

    Twetman, Svante; Axelsson, Susanna Bihari; Dahlén, Gunnar

    2012-01-01

    Abstract Objective. To assess the diagnostic accuracy of adjunct methods used to detect and quantify dental caries. Study design. A systematic literature search for relevant papers was conducted with pre-determined inclusion and exclusion criteria. Abstracts and full text articles were assessed...

  9. Method of detecting failed fuels

    International Nuclear Information System (INIS)

    Ishizaki, Hideaki; Suzumura, Takeshi.

    1982-01-01

    Purpose: To enable the settlement of the temperature of an adequate filling high temperature pure water by detecting the outlet temperature of a high temperature pure water filling tube to a fuel assembly to control the heating of the pure water and detecting the failed fuel due to the sampling of the pure water. Method: A temperature sensor is provided at a water tube connected to a sipping cap for filling high temperature pure water to detect the temperature of the high temperature pure water at the outlet of the tube, and the temperature is confirmed by a temperature indicator. A heater is controlled on the basis of this confirmation, an adequate high temperature pure water is filled in the fuel assembly, and the pure water is replaced with coolant. Then, it is sampled to settle the adequate temperature of the high temperature coolant used for detecting the failure of the fuel assembly. As a result, the sipping effect does not decrease, and the failed fuel can be precisely detected. (Yoshihara, H.)

  10. Detection methods of irradiated foodstuffs

    Energy Technology Data Exchange (ETDEWEB)

    Ponta, C C; Cutrubinis, M; Georgescu, R [IRASM Center, Horia Hulubei National Institute for Physics and Nuclear Engineering, PO Box MG-6, RO-077125 Magurele-Bucharest (Romania); Mihai, R [Life and Environmental Physics Department, Horia Hulubei National Institute for Physics and Nuclear Engineering, PO Box MG-6, RO-077125 Magurele-Bucharest (Romania); Secu, M [National Institute of Materials Physics, Bucharest (Romania)

    2005-07-01

    food is marketed as irradiated or if irradiated goods are sold without the appropriate labeling, then detection tests should be able to prove the authenticity of the product. For the moment in Romania there is not any food control laboratory able to detect irradiated foodstuffs. The Technological Irradiation Department coordinates and co finances a research project aimed to establish the first Laboratory of Irradiated Foodstuffs Detection. The detection methods studied in this project are the ESR methods (for cellulose EN 1787/2000, bone EN 1786/1996 and crystalline sugar EN 13708/2003), the TL method (EN 1788/2001), the PSL method (EN 13751/2002) and the DNA Comet Assay method (EN 13784/2001). The above detection methods will be applied on various foodstuffs such: garlic, onion, potatoes, rice, beans, wheat, maize, pistachio, sunflower seeds, raisins, figs, strawberries, chicken, beef, fish, pepper, paprika, thyme, laurel and mushrooms. As an example of the application of a detection method there are presented the ESR spectra of irradiated and nonirradiated paprika acquired according to ESR detection method for irradiated foodstuffs containing cellulose. First of all it can be noticed that the intensity of the signal of cellulose is much higher for the irradiated sample than that for the nonirradiated one and second that appear two radiation specific signals symmetrical to the cellulose signal. These two radiation specific signals prove the irradiation treatment of paprika. (author)

  11. Detection of chromosomal changes in chronic lymphocytic leukemia using classical cytogenetic methods and FISH: application of rich mitogen mixtures for lymphocyte cultures.

    Science.gov (United States)

    Koczkodaj, Dorota; Popek, Sylwia; Zmorzyński, Szymon; Wąsik-Szczepanek, Ewa; Filip, Agata A

    2016-04-01

    One of the research methods of prognostic value in chronic lymphocytic leukemia (CLL) is cytogenetic analysis. This method requires the presence of appropriate B-cell mitogens in cultures in order to obtain a high mitotic index. The aim of our research was to determine the most effective methods of in vitro B-cell stimulation to maximize the number of metaphases from peripheral blood cells of patients with CLL for classical cytogenetic examination, and then to correlate the results with those obtained using fluorescence in situ hybridization (FISH). The study group involved 50 consecutive patients with CLL. Cell cultures were maintained with the basic composition of culture medium and addition of respective stimulators. We used the following stimulators: Pokeweed Mitogen (PWM), 12-O-tetradecanoylphorbol 13-acetate (TPA), ionophore, lipopolysaccharide (LPS), and CpG-oligonucleotide DSP30. We received the highest mitotic index when using the mixture of PWM+TPA+I+DSP30. With classical cytogenetic tests using banding techniques, numerical and structural aberrations of chromosomes were detected in 46 patients, and no change was found in only four patients. Test results clearly confirmed the legitimacy of using cell cultures enriched with the mixture of cell stimulators and combining classical cytogenetic techniques with the FISH technique in later patient diagnosing. Copyright © 2016 American Federation for Medical Research.

  12. Higuchi’s Method applied to detection of changes in timbre of digital sound synthesis of string instruments with the functional transformation method

    Science.gov (United States)

    Kanjanapen, Manorth; Kunsombat, Cherdsak; Chiangga, Surasak

    2017-09-01

    The functional transformation method (FTM) is a powerful tool for detailed investigation of digital sound synthesis by the physical modeling method, the resulting sound or measured vibrational characteristics at discretized points on real instruments directly solves the underlying physical effect of partial differential equation (PDE). In this paper, we present the Higuchi’s method to examine the difference between the timbre of tone and estimate fractal dimension of musical signals which contains information about their geometrical structure that synthesizes by FTM. With the Higuchi’s method we obtain the whole process is not complicated, fast processing, with the ease of analysis without expertise in the physics or virtuoso musicians and the easiest way for the common people can judge that sounds similarly presented.

  13. Method of detecting irradiated pepper

    International Nuclear Information System (INIS)

    Doumaru, Takaaki; Furuta, Masakazu; Katayama, Tadashi; Toratani, Hirokazu; Takeda, Atsuhiko

    1989-01-01

    Spices represented by pepper are generally contaminated by microorganisms, and for using them as foodstuffs, some sterilizing treatment is indispensable. However, heating is not suitable to spices, accordingly ethylene oxide gas sterilization has been inevitably carried out, but its carcinogenic property is a problem. Food irradiation is the technology for killing microorganisms and noxious insects which cause the rotting and spoiling of foods and preventing the germination, which is an energy-conserving method without the fear of residual chemicals, therefore, it is most suitable to the sterilization of spices. In the irradiation of lower than 10 kGy, the toxicity test is not required for any food, and the irradiation of spices is permitted in 20 countries. However, in order to establish the international distribution organization for irradiated foods, the PR to consumers and the development of the means of detecting irradiation are the important subjects. The authors used pepper, and examined whether the hydrogen generated by irradiation remains in seeds and it can be detected or not. The experimental method and the results are reported. From the samples without irradiation, hydrogen was scarcely detected. The quantity of hydrogen generated was proportional to dose. The measuring instrument is only a gas chromatograph. (K.I.)

  14. Unsupervised Condition Change Detection In Large Diesel Engines

    DEFF Research Database (Denmark)

    Pontoppidan, Niels Henrik; Larsen, Jan

    2003-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Knol Dirk L

    2006-08-01

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

  16. Adaptively detecting changes in Autonomic Grid Computing

    KAUST Repository

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

    2010-01-01

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

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

    Science.gov (United States)

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

    2018-04-01

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

  18. Analytical detection methods for irradiated foods

    International Nuclear Information System (INIS)

    1991-03-01

    The present publication is a review of scientific literature on the analytical identification of foods treated with ionizing radiation and the quantitative determination of absorbed dose of radiation. Because of the extremely low level of chemical changes resulting from irradiation or because of the lack of specificity to irradiation of any chemical changes, a few methods of quantitative determination of absorbed dose have shown promise until now. On the other hand, the present review has identified several possible methods, which could be used, following further research and testing, for the identification of irradiated foods. An IAEA Co-ordinated Research Programme on Analytical Detection Methods for Irradiation Treatment of Food ('ADMIT'), established in 1990, is currently investigating many of the methods cited in the present document. Refs and tab

  19. Method to detect biological particles

    International Nuclear Information System (INIS)

    Giaever, I.

    1976-01-01

    A medical-diagnostic method to detect immunological as well as other specific reactions is described. According to the invention, first reactive particles (e.g. antibodies) are adsorbed on the surface of a solid, non-reactive substrate. The coated substrate is subjected to a solution which one assumes to contain the second biological particles (e.g. antigens) which are specific to the first and form complexes with these. A preferential radioactive labelling (e.g. with iodine 125) of the second biological particle is then directly or indirectly carried out. Clearage follows labelling in order to separate the second biological particles from the first ones. A specific splitting agent can selectively break the bond of both types of particle. The splitting agent solution is finally separated off and its content is investigated for the presence of labelling. (VJ) [de

  20. Detecting significant changes in protein abundance

    Directory of Open Access Journals (Sweden)

    Kai Kammers

    2015-06-01

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

  1. Animal magnetocardiography using superconducting quantum interference device gradiometers assisted with magnetic nanoparticle injection: A sensitive method for early detecting electromagnetic changes induced by hypercholesterolemia

    Science.gov (United States)

    Wu, C. C.; Hong, B. F.; Wu, B. H.; Yang, S. Y.; Horng, H. E.; Yang, H. C.; Tseng, W. Y. Isaac; Tseng, W. K.; Liu, Y. B.; Lin, L. C.; Lu, L. S.; Lee, Y. H.

    2007-01-01

    In this work, the authors used a superconducting quantum interference device (SQUID) magnetocardiography (MCG) system consisted of 64-channel low-transition-temperature SQUID gradiometers to detect the MCG signals of hepercholesterolemic rabbits. In addition, the MCG signals were recorded before and after the injection of magnetic nanoparticles into the rabbits' ear veins to investigate the effects of magnetic nanoparticles on the MCG signals. These MCG data were compared to those of normal rabbits to reveal the feasibility for early detection of the electromagnetic changes induced by hypercholesterolemia using MCG with the assistance of magnetic nanoparticle injection.

  2. Regularisation in multi- and hyperspectral remote sensing change detection

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg

    2005-01-01

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

  3. Detection of radiation-induced changes in electrochemical properties of austenitic stainless steels using miniaturized specimens and the single-loop electrochemical potentiokinetic reactivation method

    International Nuclear Information System (INIS)

    Inazumi, T.; Bell, G.E.C.; Kenik, E.A.; Kiuchi, K.

    1993-01-01

    Single-loop electrochemical potentiokinetic reactivation testing of miniaturized (TEM) specimens can provide reliable data comparable to data obtained with larger specimens. Significant changes in electrochemical properties (increased reactivation current and Flade potential) were detected for PCA and type 316 stainless steels irradiated at 200--420 degrees C up to 7--9 dpa. Irradiations in the FFTF Materials Open Test Assembly and in the Oak Ridge Research Reactor are reported on. 45 figs., 5 tabs., 52 refs

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

    Directory of Open Access Journals (Sweden)

    Haobo Lyu

    2016-06-01

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

  5. Distance Measurement Methods for Improved Insider Threat Detection

    Directory of Open Access Journals (Sweden)

    Owen Lo

    2018-01-01

    Full Text Available Insider threats are a considerable problem within cyber security and it is often difficult to detect these threats using signature detection. Increasing machine learning can provide a solution, but these methods often fail to take into account changes of behaviour of users. This work builds on a published method of detecting insider threats and applies Hidden Markov method on a CERT data set (CERT r4.2 and analyses a number of distance vector methods (Damerau–Levenshtein Distance, Cosine Distance, and Jaccard Distance in order to detect changes of behaviour, which are shown to have success in determining different insider threats.

  6. Molecular methods for the detection of mutations.

    Science.gov (United States)

    Monteiro, C; Marcelino, L A; Conde, A R; Saraiva, C; Giphart-Gassler, M; De Nooij-van Dalen, A G; Van Buuren-van Seggelen, V; Van der Keur, M; May, C A; Cole, J; Lehmann, A R; Steinsgrimsdottir, H; Beare, D; Capulas, E; Armour, J A

    2000-01-01

    We report the results of a collaborative study aimed at developing reliable, direct assays for mutation in human cells. The project used common lymphoblastoid cell lines, both with and without mutagen treatment, as a shared resource to validate the development of new molecular methods for the detection of low-level mutations in the presence of a large excess of normal alleles. As the "gold standard, " hprt mutation frequencies were also measured on the same samples. The methods under development included i) the restriction site mutation (RSM) assay, in which mutations lead to the destruction of a restriction site; ii) minisatellite length-change mutation, in which mutations lead to alleles containing new numbers of tandem repeat units; iii) loss of heterozygosity for HLA epitopes, in which antibodies can be used to direct selection for mutant cells; iv) multiple fluorescence-based long linker arm nucleotides assay (mf-LLA) technology, for the detection of substitutional mutations; v) detection of alterations in the TP53 locus using a (CA) array as the target for the screening; and vi) PCR analysis of lymphocytes for the presence of the BCL2 t(14:18) translocation. The relative merits of these molecular methods are discussed, and a comparison made with more "traditional" methods.

  7. Particle detection systems and methods

    Science.gov (United States)

    Morris, Christopher L.; Makela, Mark F.

    2010-05-11

    Techniques, apparatus and systems for detecting particles such as muons and neutrons. In one implementation, a particle detection system employs a plurality of drift cells, which can be for example sealed gas-filled drift tubes, arranged on sides of a volume to be scanned to track incoming and outgoing charged particles, such as cosmic ray-produced muons. The drift cells can include a neutron sensitive medium to enable concurrent counting of neutrons. The system can selectively detect devices or materials, such as iron, lead, gold, uranium, plutonium, and/or tungsten, occupying the volume from multiple scattering of the charged particles passing through the volume and can concurrently detect any unshielded neutron sources occupying the volume from neutrons emitted therefrom. If necessary, the drift cells can be used to also detect gamma rays. The system can be employed to inspect occupied vehicles at border crossings for nuclear threat objects.

  8. Detection of food irradiation - two analytical methods

    International Nuclear Information System (INIS)

    1994-01-01

    This publication summarizes the activities of Nordic countries in the field of detection of irradiated food. The National Food Agency of Denmark has coordinated the project. The two analytical methods investigated were: the gas-chromatographic determination of the hydrocarbon/lipid ratio in irradiated chicken meat, and a bioassay based on microelectrophoresis of DNA from single cells. Also a method for determination of o-tyrosine in the irradiated and non-irradiated chicken meat has been tested. The first method based on radiolytical changes in fatty acids, contained in chicken meat, has been tested and compared in the four Nordic countries. Four major hydrocarbons (C16:2, C16:3, C17:1 and C17:2) have been determined and reasonable agreement was observed between the dose level and hydrocarbons concentration. Results of a bioassay, where strand breaks of DNA are demonstrated by microelectrophoresis of single cells, prove a correlation between the dose levels and the pattern of DNA fragments migration. The hydrocarbon method can be applied to detect other irradiated, fat-containing foods, while the DNA method can be used for some animal and some vegetable foods as well.Both methods allow to determine the fact of food irradiation beyond any doubt, thus making them suitable for food control analysis. The detailed determination protocols are given. (EG)

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

    Science.gov (United States)

    Aswani, Shankar; Lauer, Matthew

    2014-06-01

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

  10. Analysis and detection of climate change

    International Nuclear Information System (INIS)

    Thejll, P.; Stendel, M.

    2001-01-01

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

  11. Comparison of Methods for Oscillation Detection

    DEFF Research Database (Denmark)

    Odgaard, Peter Fogh; Trangbæk, Klaus

    2006-01-01

    This paper compares a selection of methods for detecting oscillations in control loops. The methods are tested on measurement data from a coal-fired power plant, where some oscillations are occurring. Emphasis is put on being able to detect oscillations without having a system model and without...... using process knowledge. The tested methods show potential for detecting the oscillations, however, transient components in the signals cause false detections as well, motivating usage of models in order to remove the expected signals behavior....

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

    CSIR Research Space (South Africa)

    Salmon, BP

    2011-06-01

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

  13. Interpreting the change detection error matrix

    NARCIS (Netherlands)

    Oort, van P.A.J.

    2007-01-01

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

  14. DIAGNOSTIC METHODS IN BREAST CANCER DETECTION

    Directory of Open Access Journals (Sweden)

    Kristijana Hertl

    2018-02-01

    Full Text Available Background. In the world as well as in Slovenia, breast cancer is the most frequent female cancer. Due to its high incidence, it appears to be a serious health and economic problem. Content. Among other, tumour size at diagnosis, is an important prognostic factors of the course of the disease. The probability of axillary lymph node involvement as well as distant metastases is greater in larger tumours. This is the reason that encouraged the development of various diagnostic methods for early detection of small, clinically non-palpable breast tumours. Mammography, however, remains the »golden standard« of early breast cancer detection. It is the basic diagnostic method applied in all symptomatic women over 35 years of age and in asymptomatic women over 40 years of age. Ultrasonography (US, additional projections, magnetic resonance imaging (MRI and ductography are regarded as complementary diagnostic breast imaging techniques in addition to mammography. The detected changes in the breast can be further confirmed by US-, MR-guided or stereotactic biopsy. If necessary, surgical biopsy and the excision of a tissue sample, after wire or isotope localisation of the nonpalpable lesion, can be performed. Conclusions. Any of the above mentioned diagnostic methods has advantages as well as drawbacks and only detailed knowledge and understanding of each of them may assure the best option.

  15. Detecting land cover change using a sliding window temporal autocorrelation approach

    CSIR Research Space (South Africa)

    Kleynhans, W

    2012-07-01

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

  16. Cancer Detection and Diagnosis Methods - Annual Plan

    Science.gov (United States)

    Early cancer detection is a proven life-saving strategy. Learn about the research opportunities NCI supports, including liquid biopsies and other less-invasive methods, for detecting early cancers and precancerous growths.

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

    Science.gov (United States)

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

    2017-10-01

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

  18. Detection methods for irradiated mites and insects

    International Nuclear Information System (INIS)

    Ignatowicz, S.

    1999-01-01

    Results of the study on the following tests for separation of irradiated pests from untreated ones are reported: (a) test for identification of irradiated mites (Acaridae) based on lack of fecundity of treated females; (b) test for identification of irradiated beetles based on their locomotor activity; (c) test for identification of irradiated pests based on electron spin resonance (ESR) signal derived from treated insects; (d) test for identification of irradiated pests based on changes in the midgut induced by gamma radiation; and (e) test for identification of irradiated pests based on the alterations in total proteins of treated adults. Of these detection methods, only the test based on the pathological changes induced by irradiation in the insect midgut may identify consistently either irradiated larvae or adults. This test is simple and convenient when a rapid processing technique for dehydrating and embedding the midgut is used. (author)

  19. A Review of the Detection Methods for Climate Regime Shifts

    Directory of Open Access Journals (Sweden)

    Qunqun Liu

    2016-01-01

    Full Text Available An abrupt climate change means that the climate system shifts from a steady state to another steady state. Study on the phenomenon and theory of the abrupt climate change is a new research field of modern climatology, and it is of great significance for the prediction of future climate change. The climate regime shift is one of the most common forms of abrupt climate change, which mainly refers to the statistical significant changes on the variable of climate system at one time scale. These detection methods can be roughly divided into five categories based on different types of abrupt changes, namely, abrupt mean value change, abrupt variance change, abrupt frequency change, abrupt probability density change, and the multivariable analysis. The main research progress of abrupt climate change detection methods is reviewed. What is more, some actual applications of those methods in observational data are provided. With the development of nonlinear science, many new methods have been presented for detecting an abrupt dynamic change in recent years, which is useful supplement for the abrupt change detection methods.

  20. A Simple and Robust Method for Semi-Quantitative Detection of Human Papillomavirus Nucleic Acids (HPV Helps Oncological Clinicians to Assess the Severeness of HPV Cellular Changing

    Directory of Open Access Journals (Sweden)

    Florian Heirler

    2011-01-01

    Full Text Available A simple and robust method for the detection of nucleic acids of human papilloma virus (HPV has been developed. The assay exploits the excellent sensitivity and specificity of “nested” polymerase chain reaction (nPCR that is designed in the original single tube configuration to effectively prevent the carry-over contamination. This approach theoretically covers the amplification of all cancer developing genotypes currently known. The nPCR, paired with very simple nucleic acids isolation steps, is a real alternative to the standard method. This manuscript shows its capacity for routine use under clinical conditions. It is shown that the strategy is at least as sensitive as the standard two tube nPCR and the data are acceptably reproducible.

  1. Sensor for detecting changes in magnetic fields

    Science.gov (United States)

    Praeg, Walter F.

    1981-01-01

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

  2. Rapid methods for detection of bacteria

    DEFF Research Database (Denmark)

    Corfitzen, Charlotte B.; Andersen, B.Ø.; Miller, M.

    2006-01-01

    Traditional methods for detection of bacteria in drinking water e.g. Heterotrophic Plate Counts (HPC) or Most Probable Number (MNP) take 48-72 hours to give the result. New rapid methods for detection of bacteria are needed to protect the consumers against contaminations. Two rapid methods...

  3. A comparison of moving object detection methods for real-time moving object detection

    Science.gov (United States)

    Roshan, Aditya; Zhang, Yun

    2014-06-01

    Moving object detection has a wide variety of applications from traffic monitoring, site monitoring, automatic theft identification, face detection to military surveillance. Many methods have been developed across the globe for moving object detection, but it is very difficult to find one which can work globally in all situations and with different types of videos. The purpose of this paper is to evaluate existing moving object detection methods which can be implemented in software on a desktop or laptop, for real time object detection. There are several moving object detection methods noted in the literature, but few of them are suitable for real time moving object detection. Most of the methods which provide for real time movement are further limited by the number of objects and the scene complexity. This paper evaluates the four most commonly used moving object detection methods as background subtraction technique, Gaussian mixture model, wavelet based and optical flow based methods. The work is based on evaluation of these four moving object detection methods using two (2) different sets of cameras and two (2) different scenes. The moving object detection methods have been implemented using MatLab and results are compared based on completeness of detected objects, noise, light change sensitivity, processing time etc. After comparison, it is observed that optical flow based method took least processing time and successfully detected boundary of moving objects which also implies that it can be implemented for real-time moving object detection.

  4. Leak detection by vibrational diagnostic methods

    International Nuclear Information System (INIS)

    Siklossy, P.

    1983-01-01

    The possibilities and methods of leak detection due to mechanical failures in nuclear power plants are reviewed on the basis of the literature. Great importance is attributed to vibrational diagnostic methods for their adventageous characteristics which enable them to become final leak detecting methods. The problems of noise analysis, e.g. leak detection by impact sound measurements, probe characteristics, gain problems, probe selection, off-line analysis and correlation functions, types of leak noises etc. are summarized. Leak detection based on noise analysis can be installed additionally to power plants. Its maintenance and testing is simple. On the other hand, it requires special training and measuring methods. (Sz.J.)

  5. Detection of food irradiation with luminescence methods

    International Nuclear Information System (INIS)

    Anderle, H.

    1997-06-01

    Food irradiation is applied as method for the preservation of foods, the prevention of food spoilage and the inhibition of food-borne pathogens. Doses exceeding 10 kGy (10 kJ/kg) are not recommended by the WHO. The different legislation requires methods for the detection and the closimetry of irradiated foods. Among the physical methods based on the radiation-induced changes in inorganic, nonhygroscopic crystalline solids are thermoluminescence (TL), photostimulated luminescence (PSL) and lyoluminescence (LL) measurement. The luminescence methods were tested on natural minerals. Pure quartz, feldspars, calcite, aragonite and dolomite of known origin were irradiated, read out and analyzed to determine the influence of luminescence-activators and deactivators. Carbonate minerals show an orange-red TL easily detectable by blue-sensitive photomultiplier tubes. TIL-inactive carbonate samples may be identified by a lyoluminescence method using the reaction of trapped irradiation-generated charge carriers with the solvent during crystal-lattice breakup. The fine-ground mineral is dissolved in an alkaline complexing agent/chemiluminescence sensitizer/chemiluminescence catalyst (EDTA/luminol/hemin) reagent mixture. The TL and PSL of quartz is too weak to contribute a significant part for the corresponding signals in polymineral dust. Alkali and soda feldspar show intense TL and PSL. The temperature maxima in the TL glow curves allow a clear distinction. PSL does not give this additional information, it suffers from bleaching by ambient light and requires light-protection. Grain disinfestated with low irradiation doses (500 Gy) may not identified by both TL and PSL measurement. The natural TL of feldspar particles may be overlap with the irradiation-induced TL of other minerals. As a routine method, irradiated spices are identified with TL measurement. The dust particles have to be enriched by heavy-liquid flotation and centrifugation. The PSL method allows a clear

  6. Saliency predicts change detection in pictures of natural scenes.

    Science.gov (United States)

    Wright, Michael J

    2005-01-01

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

  7. Video change detection for fixed wing UAVs

    Science.gov (United States)

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

    2017-10-01

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

  8. Land cover change detection in West Jilin using ETM+ images

    Institute of Scientific and Technical Information of China (English)

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

    2004-01-01

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

  9. Adaptive 4d Psi-Based Change Detection

    Science.gov (United States)

    Yang, Chia-Hsiang; Soergel, Uwe

    2018-04-01

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

  10. Electromagnetic Methods of Lightning Detection

    Science.gov (United States)

    Rakov, V. A.

    2013-11-01

    Both cloud-to-ground and cloud lightning discharges involve a number of processes that produce electromagnetic field signatures in different regions of the spectrum. Salient characteristics of measured wideband electric and magnetic fields generated by various lightning processes at distances ranging from tens to a few hundreds of kilometers (when at least the initial part of the signal is essentially radiation while being not influenced by ionospheric reflections) are reviewed. An overview of the various lightning locating techniques, including magnetic direction finding, time-of-arrival technique, and interferometry, is given. Lightning location on global scale, when radio-frequency electromagnetic signals are dominated by ionospheric reflections, is also considered. Lightning locating system performance characteristics, including flash and stroke detection efficiencies, percentage of misclassified events, location accuracy, and peak current estimation errors, are discussed. Both cloud and cloud-to-ground flashes are considered. Representative examples of modern lightning locating systems are reviewed. Besides general characterization of each system, the available information on its performance characteristics is given with emphasis on those based on formal ground-truth studies published in the peer-reviewed literature.

  11. Material detection method and device

    International Nuclear Information System (INIS)

    Shigenaka, Naoto; Fujimori, Haruo; Ono, Shigeki; Fuse, Motomasa; Uchida, Shunsuke.

    1994-01-01

    A specimen A sampled from an objective member for integrity evaluation, as well as a virgin specimen B having the same composition as the member are prepared. Ion injection, for example, is performed to the specimens A and B under the same condition to form deposits derived from ions, and the shape of the deposits of the specimens A and B are compared. The deposits formed on the crystal grain boundary has a convex shape, and a relative value for the energy of crystal grain boundary can be determined based on the aspect ratio. In addition, since the energy of the crystal grain boundary is in proportion to the grain boundary corrosion rate, the relative value for the grain boundary corrosion rate can be evaluated by measuring the shape of the deposits formed in the crystal grain boundary. If the grain boundary corrosion rate of the virgin specimen is previously measured, the change of the grain boundary corrosion rate can quantitatively be evaluated. A crack propagating rate of the reactor material upon evaluation of integrity, which has been difficult so far, can be determined, thereby enabling to forecast the remaining life time of the material at high accuracy. (N.H.)

  12. A Hybrid Change Detection Approach for Damage Detection and Recovery Monitoring

    Science.gov (United States)

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

    2014-05-01

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

  13. Application of bimodal distribution to the detection of changes in uranium concentration in drinking water collected by random daytime sampling method from a large water supply zone.

    Science.gov (United States)

    Garboś, Sławomir; Święcicka, Dorota

    2015-11-01

    The random daytime (RDT) sampling method was used for the first time in the assessment of average weekly exposure to uranium through drinking water in a large water supply zone. Data set of uranium concentrations determined in 106 RDT samples collected in three runs from the water supply zone in Wroclaw (Poland), cannot be simply described by normal or log-normal distributions. Therefore, a numerical method designed for the detection and calculation of bimodal distribution was applied. The extracted two distributions containing data from the summer season of 2011 and the winter season of 2012 (nI=72) and from the summer season of 2013 (nII=34) allowed to estimate means of U concentrations in drinking water: 0.947 μg/L and 1.23 μg/L, respectively. As the removal efficiency of uranium during applied treatment process is negligible, the effect of increase in uranium concentration can be explained by higher U concentration in the surface-infiltration water used for the production of drinking water. During the summer season of 2013, heavy rains were observed in Lower Silesia region, causing floods over the territory of the entire region. Fluctuations in uranium concentrations in surface-infiltration water can be attributed to releases of uranium from specific sources - migration from phosphate fertilizers and leaching from mineral deposits. Thus, exposure to uranium through drinking water may increase during extreme rainfall events. The average chronic weekly intakes of uranium through drinking water, estimated on the basis of central values of the extracted normal distributions, accounted for 3.2% and 4.1% of tolerable weekly intake. Copyright © 2015 Elsevier Ltd. All rights reserved.

  14. Automated Change Detection for Synthetic Aperture Sonar

    Science.gov (United States)

    2014-01-01

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

  15. Detection and Attribution of Anthropogenic Climate Change Impacts

    Science.gov (United States)

    Rosenzweig, Cynthia; Neofotis, Peter

    2013-01-01

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

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

    Directory of Open Access Journals (Sweden)

    S. Makuti

    2018-05-01

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

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

    Science.gov (United States)

    Yokoi, Kentaro

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

  18. Improved GLR method to instrument failure detection

    International Nuclear Information System (INIS)

    Jeong, Hak Yeoung; Chang, Soon Heung

    1985-01-01

    The generalized likehood radio(GLR) method performs statistical tests on the innovations sequence of a Kalman-Buchy filter state estimator for system failure detection and its identification. However, the major drawback of the convensional GLR is to hypothesize particular failure type in each case. In this paper, a method to solve this drawback is proposed. The improved GLR method is applied to a PWR pressurizer and gives successful results in detection and identification of any failure. Furthmore, some benefit on the processing time per each cycle of failure detection and its identification can be accompanied. (Author)

  19. GMDD: a database of GMO detection methods.

    Science.gov (United States)

    Dong, Wei; Yang, Litao; Shen, Kailin; Kim, Banghyun; Kleter, Gijs A; Marvin, Hans J P; Guo, Rong; Liang, Wanqi; Zhang, Dabing

    2008-06-04

    Since more than one hundred events of genetically modified organisms (GMOs) have been developed and approved for commercialization in global area, the GMO analysis methods are essential for the enforcement of GMO labelling regulations. Protein and nucleic acid-based detection techniques have been developed and utilized for GMOs identification and quantification. However, the information for harmonization and standardization of GMO analysis methods at global level is needed. GMO Detection method Database (GMDD) has collected almost all the previous developed and reported GMOs detection methods, which have been grouped by different strategies (screen-, gene-, construct-, and event-specific), and also provide a user-friendly search service of the detection methods by GMO event name, exogenous gene, or protein information, etc. In this database, users can obtain the sequences of exogenous integration, which will facilitate PCR primers and probes design. Also the information on endogenous genes, certified reference materials, reference molecules, and the validation status of developed methods is included in this database. Furthermore, registered users can also submit new detection methods and sequences to this database, and the newly submitted information will be released soon after being checked. GMDD contains comprehensive information of GMO detection methods. The database will make the GMOs analysis much easier.

  20. Total least squares for anomalous change detection

    Science.gov (United States)

    Theiler, James; Matsekh, Anna M.

    2010-04-01

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

  1. CHANGE DETECTION VIA SELECTIVE GUIDED CONTRASTING FILTERS

    Directory of Open Access Journals (Sweden)

    Y. V. Vizilter

    2017-05-01

    Full Text Available Change detection scheme based on guided contrasting was previously proposed. Guided contrasting filter takes two images (test and sample as input and forms the output as filtered version of test image. Such filter preserves the similar details and smooths the non-similar details of test image with respect to sample image. Due to this the difference between test image and its filtered version (difference map could be a basis for robust change detection. Guided contrasting is performed in two steps: at the first step some smoothing operator (SO is applied for elimination of test image details; at the second step all matched details are restored with local contrast proportional to the value of some local similarity coefficient (LSC. The guided contrasting filter was proposed based on local average smoothing as SO and local linear correlation as LSC. In this paper we propose and implement new set of selective guided contrasting filters based on different combinations of various SO and thresholded LSC. Linear average and Gaussian smoothing, nonlinear median filtering, morphological opening and closing are considered as SO. Local linear correlation coefficient, morphological correlation coefficient (MCC, mutual information, mean square MCC and geometrical correlation coefficients are applied as LSC. Thresholding of LSC allows operating with non-normalized LSC and enhancing the selective properties of guided contrasting filters: details are either totally recovered or not recovered at all after the smoothing. These different guided contrasting filters are tested as a part of previously proposed change detection pipeline, which contains following stages: guided contrasting filtering on image pyramid, calculation of difference map, binarization, extraction of change proposals and testing change proposals using local MCC. Experiments on real and simulated image bases demonstrate the applicability of all proposed selective guided contrasting filters. All

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

    Directory of Open Access Journals (Sweden)

    P. Duncan

    2012-08-01

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

  3. Convolutional neural network features based change detection in satellite images

    Science.gov (United States)

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

    2016-07-01

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

  4. GC ‘Multi-Analyte’ Detection Method

    Energy Technology Data Exchange (ETDEWEB)

    Dudar, E. [Plant Protection & Soil Conservation Service of Budapest, Budapest (Hungary)

    2009-07-15

    Elaborated methodologies for GC multi-analyte detection are presented, comprising the steps of method development, chromatographic conditions and procedures including the determination of relative retention times and summary results tables. (author)

  5. Automated Change Detection for Validation and Update of Geodata

    DEFF Research Database (Denmark)

    Olsen, Brian Pilemann; Knudsen, Thomas

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

  6. Detecting and Attributing Health Burdens to Climate Change.

    Science.gov (United States)

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

    2017-08-07

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

  7. Detection of cardiac activity changes from human speech

    Science.gov (United States)

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

    2015-05-01

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

  8. Detecting changes during pregnancy with Raman spectroscopy

    Science.gov (United States)

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

    2010-02-01

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

  9. A comparison of three time-domain anomaly detection methods

    Energy Technology Data Exchange (ETDEWEB)

    Schoonewelle, H.; Hagen, T.H.J.J. van der; Hoogenboom, J.E. [Delft University of Technology (Netherlands). Interfaculty Reactor Institute

    1996-01-01

    Three anomaly detection methods based on a comparison of signal values with predictions from an autoregressive model are presented. These methods are: the extremes method, the {chi}{sup 2} method and the sequential probability ratio test. The methods are used to detect a change of the standard deviation of the residual noise obtained from applying an autoregressive model. They are fast and can be used in on-line applications. For each method some important anomaly detection parameters are determined by calculation or simulation. These parameters are: the false alarm rate, the average time to alarm and - being of minor importance -the alarm failure rate. Each method is optimized with respect to the average time to alarm for a given value of the false alarm rate. The methods are compared with each other, resulting in the sequential probability ratio test being clearly superior. (author).

  10. A comparison of three time-domain anomaly detection methods

    International Nuclear Information System (INIS)

    Schoonewelle, H.; Hagen, T.H.J.J. van der; Hoogenboom, J.E.

    1996-01-01

    Three anomaly detection methods based on a comparison of signal values with predictions from an autoregressive model are presented. These methods are: the extremes method, the χ 2 method and the sequential probability ratio test. The methods are used to detect a change of the standard deviation of the residual noise obtained from applying an autoregressive model. They are fast and can be used in on-line applications. For each method some important anomaly detection parameters are determined by calculation or simulation. These parameters are: the false alarm rate, the average time to alarm and - being of minor importance -the alarm failure rate. Each method is optimized with respect to the average time to alarm for a given value of the false alarm rate. The methods are compared with each other, resulting in the sequential probability ratio test being clearly superior. (author)

  11. Transistor-based particle detection systems and methods

    Science.gov (United States)

    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.

  12. Comprehensive methods for earlier detection and monitoring of forest decline

    Science.gov (United States)

    Jennifer Pontius; Richard Hallett

    2014-01-01

    Forested ecosystems are threatened by invasive pests, pathogens, and unusual climatic events brought about by climate change. Earlier detection of incipient forest health problems and a quantitatively rigorous assessment method is increasingly important. Here, we describe a method that is adaptable across tree species and stress agents and practical for use in the...

  13. Automated baseline change detection phase I. Final report

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1995-12-01

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

  14. Automated baseline change detection phase I. Final report

    International Nuclear Information System (INIS)

    1995-12-01

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

  15. Brain correlates of automatic visual change detection.

    Science.gov (United States)

    Cléry, H; Andersson, F; Fonlupt, P; Gomot, M

    2013-07-15

    A number of studies support the presence of visual automatic detection of change, but little is known about the brain generators involved in such processing and about the modulation of brain activity according to the salience of the stimulus. The study presented here was designed to locate the brain activity elicited by unattended visual deviant and novel stimuli using fMRI. Seventeen adult participants were presented with a passive visual oddball sequence while performing a concurrent visual task. Variations in BOLD signal were observed in the modality-specific sensory cortex, but also in non-specific areas involved in preattentional processing of changing events. A degree-of-deviance effect was observed, since novel stimuli elicited more activity in the sensory occipital regions and at the medial frontal site than small changes. These findings could be compared to those obtained in the auditory modality and might suggest a "general" change detection process operating in several sensory modalities. Copyright © 2013 Elsevier Inc. All rights reserved.

  16. Removing Parallax-Induced False Changes in Change Detection

    Science.gov (United States)

    2014-03-27

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

  17. Consumer behaviour in district heating systems. Detecting changes

    Energy Technology Data Exchange (ETDEWEB)

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

    2002-10-01

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

  18. Detecting Change-Point via Saddlepoint Approximations

    Institute of Scientific and Technical Information of China (English)

    Zhaoyuan LI; Maozai TIAN

    2017-01-01

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

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

    Science.gov (United States)

    Beer, N. Reginald; Paglieroni, David W.

    2015-07-21

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

  20. Using adversary text to detect adversary phase changes.

    Energy Technology Data Exchange (ETDEWEB)

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

    2009-05-01

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

  1. Detecting change in stochastic sound sequences.

    Directory of Open Access Journals (Sweden)

    Benjamin Skerritt-Davis

    2018-05-01

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

  2. Lake Chapala change detection using time series

    Science.gov (United States)

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

    2008-10-01

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

  3. Nationwide Hybrid Change Detection of Buildings

    Science.gov (United States)

    Hron, V.; Halounova, L.

    2016-06-01

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

  4. A Bayesian method for detecting stellar flares

    Science.gov (United States)

    Pitkin, M.; Williams, D.; Fletcher, L.; Grant, S. D. T.

    2014-12-01

    We present a Bayesian-odds-ratio-based algorithm for detecting stellar flares in light-curve data. We assume flares are described by a model in which there is a rapid rise with a half-Gaussian profile, followed by an exponential decay. Our signal model also contains a polynomial background model required to fit underlying light-curve variations in the data, which could otherwise partially mimic a flare. We characterize the false alarm probability and efficiency of this method under the assumption that any unmodelled noise in the data is Gaussian, and compare it with a simpler thresholding method based on that used in Walkowicz et al. We find our method has a significant increase in detection efficiency for low signal-to-noise ratio (S/N) flares. For a conservative false alarm probability our method can detect 95 per cent of flares with S/N less than 20, as compared to S/N of 25 for the simpler method. We also test how well the assumption of Gaussian noise holds by applying the method to a selection of `quiet' Kepler stars. As an example we have applied our method to a selection of stars in Kepler Quarter 1 data. The method finds 687 flaring stars with a total of 1873 flares after vetos have been applied. For these flares we have made preliminary characterizations of their durations and and S/N.

  5. Novel methods for detecting buried explosive devices

    Energy Technology Data Exchange (ETDEWEB)

    Kercel, S.W.; Burlage, R.S.; Patek, D.R.; Smith, C.M. [Oak Ridge National Lab., TN (United States); Hibbs, A.D.; Rayner, T.J. [Quantum Magnetics, Inc., San Diego, CA (United States)

    1997-04-01

    Oak Ridge National Laboratory (ORNL) and Quantum Magnetics, Inc. (QM) are exploring novel landmine detection technologies. Technologies considered here include bioreporter bacteria, swept acoustic resonance, nuclear quadrupole resonance (NQR), and semiotic data fusion. Bioreporter bacteria look promising for third-world humanitarian applications; they are inexpensive, and deployment does not require high-tech methods. Swept acoustic resonance may be a useful adjunct to magnetometers in humanitarian demining. For military demining, NQR is a promising method for detecting explosive substances; of 50,000 substances that have been tested, none has an NQR signature that can be mistaken for RDX or TNT. For both military and commercial demining, sensor fusion entails two daunting tasks, identifying fusible features in both present-day and emerging technologies, and devising a fusion algorithm that runs in real-time on cheap hardware. Preliminary research in these areas is encouraging. A bioreporter bacterium for TNT detection is under development. Investigation has just started in swept acoustic resonance as an approach to a cheap mine detector for humanitarian use. Real-time wavelet processing appears to be a key to extending NQR bomb detection into mine detection, including TNT-based mines. Recent discoveries in semiotics may be the breakthrough that will lead to a robust fused detection scheme.

  6. ESA ice sheet CCI: derivation of the optimal method for surface elevation change detection of the Greenland ice sheet – round robin results

    DEFF Research Database (Denmark)

    Fredenslund Levinsen, Joanna; Khvorostovsky, Kirill; Ticconi, F.

    2015-01-01

    from the European Space Agency’s Environmental Satellite (ENVISAT), European Remote Sensing (ERS)-1 and -2, CryoSat-2, and, in the longer term, Sentinel-3 satellites. In order to find the best-performing method, an intercomparison exercise has been carried out in which the scientific community......) laser altimetry over the Jakobshavn Isbræ drainage basin. The submissions were validated against airborne laser-scanner data, and intercomparisons were carried out to analyse the potential of the applied methods and to find whether the two altimeters were capable of resolving the same signal...

  7. Fuel rod failure detection method and system

    International Nuclear Information System (INIS)

    Assmann, H.; Janson, W.; Stehle, H.; Wahode, P.

    1975-01-01

    The inventor claims a method for the detection of a defective fuel rod cladding tube or of inleaked water in the cladding tube of a fuel rod in the fuel assembly of a pressurized-water reactor. The fuel assembly is not disassembled but examined as a whole. In the examination, the cladding tube is heated near one of its two end plugs, e.g. with an attached high-frequency inductor. The water contained in the cladding tube evaporates, and steam bubbles or a condensate are detected by the ultrasonic impulse-echo method. It is also possible to measure the delay of the temperature rise at the end plug or to determine the cooling energy required to keep the end plug temperature stable and thus to detect water ingression. (DG/AK) [de

  8. A method for detecting hydrophobic patches protein

    NARCIS (Netherlands)

    Lijnzaad, P.; Berendsen, H.J.C.; Argos, P.

    1996-01-01

    A method for the detection of hydrophobic patches on the surfaces of protein tertiary structures is presented, it delineates explicit contiguous pieces of surface of arbitrary size and shape that consist solely of carbon and sulphur atoms using a dot representation of the solvent-accessible surface,

  9. Radioimmunoassay method for detection of gonorrhea antibodies

    International Nuclear Information System (INIS)

    1975-01-01

    A novel radioimmunoassay for the detection of gonorrhea antibodies in serum is described. A radionuclide is bound to gonorrhea antigens produced by a growth culture. In the presence of gonorrhea antibodies in the serum, an antigen-antibody conjugate is formed, the concentration of which can be measured with conventional radiometric methods. The radioimmunoassay is highly specific

  10. GMDD: a database of GMO detection methods

    NARCIS (Netherlands)

    Dong, W.; Yang, L.; Shen, K.; Kim, B.; Kleter, G.A.; Marvin, H.J.P.; Guo, R.; Liang, W.; Zhang, D.

    2008-01-01

    Since more than one hundred events of genetically modified organisms (GMOs) have been developed and approved for commercialization in global area, the GMO analysis methods are essential for the enforcement of GMO labelling regulations. Protein and nucleic acid-based detection techniques have been

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

    Science.gov (United States)

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

    2010-08-01

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

  12. Towards a Framework for Change Detection in Data Sets

    Science.gov (United States)

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

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

  13. Graph-based structural change detection for rotating machinery monitoring

    Science.gov (United States)

    Lu, Guoliang; Liu, Jie; Yan, Peng

    2018-01-01

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

  14. Change Detection with Polarimetric SAR Imagery for Nuclear Verification

    International Nuclear Information System (INIS)

    Canty, M.

    2015-01-01

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

  15. NATIONWIDE HYBRID CHANGE DETECTION OF BUILDINGS

    Directory of Open Access Journals (Sweden)

    V. Hron

    2016-06-01

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

  16. Bayesian Methods for Radiation Detection and Dosimetry

    CERN Document Server

    Groer, Peter G

    2002-01-01

    We performed work in three areas: radiation detection, external and internal radiation dosimetry. In radiation detection we developed Bayesian techniques to estimate the net activity of high and low activity radioactive samples. These techniques have the advantage that the remaining uncertainty about the net activity is described by probability densities. Graphs of the densities show the uncertainty in pictorial form. Figure 1 below demonstrates this point. We applied stochastic processes for a method to obtain Bayesian estimates of 222Rn-daughter products from observed counting rates. In external radiation dosimetry we studied and developed Bayesian methods to estimate radiation doses to an individual with radiation induced chromosome aberrations. We analyzed chromosome aberrations after exposure to gammas and neutrons and developed a method for dose-estimation after criticality accidents. The research in internal radiation dosimetry focused on parameter estimation for compartmental models from observed comp...

  17. Metagenomic Detection Methods in Biopreparedness Outbreak Scenarios

    DEFF Research Database (Denmark)

    Karlsson, Oskar Erik; Hansen, Trine; Knutsson, Rickard

    2013-01-01

    In the field of diagnostic microbiology, rapid molecular methods are critically important for detecting pathogens. With rapid and accurate detection, preventive measures can be put in place early, thereby preventing loss of life and further spread of a disease. From a preparedness perspective...... of a clinical sample, creating a metagenome, in a single week of laboratory work. As new technologies emerge, their dissemination and capacity building must be facilitated, and criteria for use, as well as guidelines on how to report results, must be established. This article focuses on the use of metagenomics...

  18. Detectable perfusion changes in MAG3 studies

    International Nuclear Information System (INIS)

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

    1998-01-01

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

  19. Detection method of internal leakage from valve using acoustic method

    International Nuclear Information System (INIS)

    Kumagai, Hiromichi; Kitajima, Akira; Suzuki, Akio.

    1990-01-01

    The objective of this study is to estimate the feasibility of the acoustic method for the internal leakage from the valves in power plants. From the experimental results, it was suggested that the acoustic method for the monitoring of leakage was feasible. When the background levels are higher than the acoustic signals from leakage, we can detect the leakage analyzing the spectrum of the remainders which take the background noise from the acoustic signals. (author)

  20. A novel method for detection of apoptosis

    International Nuclear Information System (INIS)

    Zagariya, Alexander M.

    2012-01-01

    There are two different Angiotensin II (ANG II) peptides in nature: Human type (ANG II) and Bovine type (ANG II*). These eight amino acid peptides differ only at position 5 where Valine is replaced by Isoleucine in the Bovine type. They are present in all species studied so far. These amino acids are different by only one atom of carbon. This difference is so small, that it will allow any of ANG II, Bovine or Human antibodies to interact with all species and create a universal method for apoptosis detection. ANG II concentrations are found at substantially higher levels in apoptotic, compared to non-apoptotic, tissues. ANG II accumulation can lead to DNA damage, mutations, carcinogenesis and cell death. We demonstrate that Bovine antiserum can be used for universal detection of apoptosis. In 2010, the worldwide market for apoptosis detection reached the $20 billion mark and significantly increases each year. Most commercially available methods are related to Annexin V and TUNNEL. Our new method based on ANG II is more widely known to physicians and scientists compared to previously used methods. Our approach offers a novel alternative for assessing apoptosis activity with enhanced sensitivity, at a lower cost and ease of use.

  1. Hough transform methods used for object detection

    International Nuclear Information System (INIS)

    Qussay A Salih; Abdul Rahman Ramli; Md Mahmud Hassan Prakash

    2001-01-01

    The Hough transform (HT) is a robust parameter estimator of multi-dimensional features in images. The HT is an established technique which evidences a shape by mapping image edge points into a parameter space. The HT is technique which is used to isolate curves of a give shape in an image. The classical HT requires that the curve be specified in some parametric from and, hence is most commonly used in the detection of regular curves. The HT has been generalized so that it is capable of detecting arbitrary curved shapes. The main advantage of this transform technique is that it is very tolerant of gaps in the actual object boundaries the classical HT for the detection of line , we will indicate how it can be applied to the detection of arbitrary shapes. Sometimes the straight line HT is efficient enough to detect features such as artificial curves. The HT is an established technique for extracting geometric shapes based on the duality definition of the points on a curve and their parameters. This technique has been developed for extracting simple geometric shapes such as lines, circles and ellipses as well as arbitrary shapes. The HT provides robustness against discontinuous or missing features, points or edges are mapped into a partitioned parameter of Hough space as individual votes where peaks denote the feature of interest represented in a non-analytically tabular form. The main drawback of the HT technique is the computational requirement which has an exponential growth of memory space and processing time as the number of parameters used to represent a primitive increases. For this reason most of the research on the HT has focused on reducing the computational burden for extracting of arbitrary shapes under more general transformations include a overview of describing the methods for the detection image processing programs are frequently required to detect and particle classification in an industrial setting, a standard algorithms for this detection lines

  2. Detecting and Understanding Changing Arctic Carbon Emissions

    Science.gov (United States)

    Bruhwiler, L.

    2017-12-01

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

  3. Recent and innovative methods for detection of bacteremia and fungemia

    International Nuclear Information System (INIS)

    Reller, L.B.

    1983-01-01

    Advances continue to be made in methods for more reliable or more rapid means of detecting bacteremia and fungemia. The importance of blood sample volume and broth dilution has been established in controlled studies. New technology includes the use of resins that remove antimicrobials from blood samples, detection of radioactivity from organisms given radiolabeled substrate, use of dyes that stain microbial DNA and RNA, use of slides coated with growth media, and lysis-centrifugation for trapping microorganisms. Technology now being considered includes counterimmunoelectrophoresis, head-space gas chromatography, electrical impedance, microcalorimetry, and the use of lasers to detect pH changes and turbidity

  4. Research and Design of Rootkit Detection Method

    Science.gov (United States)

    Liu, Leian; Yin, Zuanxing; Shen, Yuli; Lin, Haitao; Wang, Hongjiang

    Rootkit is one of the most important issues of network communication systems, which is related to the security and privacy of Internet users. Because of the existence of the back door of the operating system, a hacker can use rootkit to attack and invade other people's computers and thus he can capture passwords and message traffic to and from these computers easily. With the development of the rootkit technology, its applications are more and more extensive and it becomes increasingly difficult to detect it. In addition, for various reasons such as trade secrets, being difficult to be developed, and so on, the rootkit detection technology information and effective tools are still relatively scarce. In this paper, based on the in-depth analysis of the rootkit detection technology, a new kind of the rootkit detection structure is designed and a new method (software), X-Anti, is proposed. Test results show that software designed based on structure proposed is much more efficient than any other rootkit detection software.

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

    DEFF Research Database (Denmark)

    Willersrud, Anders; Blanke, Mogens; Imsland, Lars

    2015-01-01

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

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

    Science.gov (United States)

    Paglieroni, David W.; Beer, Reginald N.

    2016-01-19

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

  7. Detection method of a failed fuel

    International Nuclear Information System (INIS)

    Urata, Megumu; Uchida, Shunsuke; Utamura, Motoaki.

    1976-01-01

    Object: To divide a tank arrangement into a heating tank for the exclusive use of heating and a mixing tank for the exclusive use of mixing to thereby minimize the purifying amount of reactor water pumped from the interior of reactor and to considerably minimize the capacity of a purifier. Structure: In a detection method of a failed fuel comprising stopping a flow of coolant within fuel assemblies arranged in the coolant in a reactor container, sampling said coolant within the fuel assemblies, and detecting a radioactivity level of sampling liquid, the improvement of the method comprising the steps of heating a part of said coolant removed from the interior of said reactor container, mixing said heated coolant into the remainder of said removed coolant, pouring said mixed liquid into said fuel assemblies, and after a lapse of given time, sampling the liquid poured into said fuel assemblies. (Kawakami, Y.)

  8. Method for detecting a failed fuel

    International Nuclear Information System (INIS)

    Utamura, Motoaki; Urata, Megumu; Uchida, Shunsuke.

    1976-01-01

    Purpose: To provide a method for the detection of failed fuel by pouring hot water, in which pouring speed of liquid to be poured and temperature of the liquid are controlled to prevent the leakage of the liquid. Constitution: The method comprises blocking the top of a fuel assembly arranged in coolant to stop a flow of coolant, pouring a liquid higher in temperature than that of coolant into the fuel assembly, sampling the liquid poured, and measuring the concentration of radioactivity of coolant already subjected to sampling to detect a failed fuel. At this time, controlling is made so that the pouring speed of the poured liquid is set to about 25 l/min, and an increased portion of temperature from the temperature of liquid to the temperature of coolant is set to a level less than about 15 0 C. (Furukawa, Y.)

  9. System and method for anomaly detection

    Science.gov (United States)

    Scherrer, Chad

    2010-06-15

    A system and method for detecting one or more anomalies in a plurality of observations is provided. In one illustrative embodiment, the observations are real-time network observations collected from a stream of network traffic. The method includes performing a discrete decomposition of the observations, and introducing derived variables to increase storage and query efficiencies. A mathematical model, such as a conditional independence model, is then generated from the formatted data. The formatted data is also used to construct frequency tables which maintain an accurate count of specific variable occurrence as indicated by the model generation process. The formatted data is then applied to the mathematical model to generate scored data. The scored data is then analyzed to detect anomalies.

  10. Method and device for detecting radiatons

    International Nuclear Information System (INIS)

    Borel, J.; Goascoz, V.

    1979-01-01

    The method consists in fabricating an MOS transistor comprising a drain region and a source region separated from each other by a bulk region of opposite doping type relative to the first two regions, in delivering the radiation to be detected into the carrier-collection region of the MOS transistor, in leaving the bulk region at a floating potential and in collecting the drain-source current of the transistor

  11. Detection method of internal leakage from valve using acoustic method

    International Nuclear Information System (INIS)

    Kumagai, Horomichi

    1990-01-01

    The purpose of this study is to estimate the availability of acoustic method for detecting the internal leakage of valves at power plants. Experiments have been carried out on the characteristics of acoustic noise caused by the leak simulated flow. From the experimental results, the mechanism of the acoustic noisegenerated from flow, the relation between acoustic intensity and leak flow velocity, and the characteristics of the acoustic frequency spectrum were clarified. The acoustic method was applied to valves at site, and the background noises were measured in abnormal plant conditions. When the background level is higher than the acoustic signal, the difference between the background noise frequency spectrum and the acoustic signal spectrum provide a very useful leak detection method. (author)

  12. Methods for environmental change; an exploratory study

    NARCIS (Netherlands)

    Nell Gottlieb; Robert Panne; Chris Smerecnik; Gerjo Kok

    2012-01-01

    Background: While the interest of health promotion researchers in change methods directed at the target population has a long tradition, interest in change methods directed at the environment is still developing. In this survey, the focus is on methods for environmental change; especially about how

  13. Detecting evolutionary forces in language change.

    Science.gov (United States)

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

    2017-11-09

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

  14. Spectral anomaly methods for aerial detection using KUT nuisance rejection

    International Nuclear Information System (INIS)

    Detwiler, R.S.; Pfund, D.M.; Myjak, M.J.; Kulisek, J.A.; Seifert, C.E.

    2015-01-01

    This work discusses the application and optimization of a spectral anomaly method for the real-time detection of gamma radiation sources from an aerial helicopter platform. Aerial detection presents several key challenges over ground-based detection. For one, larger and more rapid background fluctuations are typical due to higher speeds, larger field of view, and geographically induced background changes. As well, the possible large altitude or stand-off distance variations cause significant steps in background count rate as well as spectral changes due to increased gamma-ray scatter with detection at higher altitudes. The work here details the adaptation and optimization of the PNNL-developed algorithm Nuisance-Rejecting Spectral Comparison Ratios for Anomaly Detection (NSCRAD), a spectral anomaly method previously developed for ground-based applications, for an aerial platform. The algorithm has been optimized for two multi-detector systems; a NaI(Tl)-detector-based system and a CsI detector array. The optimization here details the adaptation of the spectral windows for a particular set of target sources to aerial detection and the tailoring for the specific detectors. As well, the methodology and results for background rejection methods optimized for the aerial gamma-ray detection using Potassium, Uranium and Thorium (KUT) nuisance rejection are shown. Results indicate that use of a realistic KUT nuisance rejection may eliminate metric rises due to background magnitude and spectral steps encountered in aerial detection due to altitude changes and geographically induced steps such as at land–water interfaces

  15. Clinical value of different detection methods in blunt ocular trauma

    Directory of Open Access Journals (Sweden)

    Yang Li

    2018-02-01

    Full Text Available Blunt ocular can cause persistent change of eye structure and function, the method of detection which is closely related to eye injury including B-can ultrasonography, UBM, OCT, FFA, scanning laser polarimetry, fundus autofluorescence, each examination with particular emphasis. This paper aims to review the advantages and disadvantages of different inspection methods in order to provide reference for clinical diagnosis and treatment of blunt ocular trauma.

  16. Waterborne Pathogens: Detection Methods and Challenges

    Directory of Open Access Journals (Sweden)

    Flor Yazmín Ramírez-Castillo

    2015-05-01

    Full Text Available Waterborne pathogens and related diseases are a major public health concern worldwide, not only by the morbidity and mortality that they cause, but by the high cost that represents their prevention and treatment. These diseases are directly related to environmental deterioration and pollution. Despite the continued efforts to maintain water safety, waterborne outbreaks are still reported globally. Proper assessment of pathogens on water and water quality monitoring are key factors for decision-making regarding water distribution systems’ infrastructure, the choice of best water treatment and prevention waterborne outbreaks. Powerful, sensitive and reproducible diagnostic tools are developed to monitor pathogen contamination in water and be able to detect not only cultivable pathogens but also to detect the occurrence of viable but non-culturable microorganisms as well as the presence of pathogens on biofilms. Quantitative microbial risk assessment (QMRA is a helpful tool to evaluate the scenarios for pathogen contamination that involve surveillance, detection methods, analysis and decision-making. This review aims to present a research outlook on waterborne outbreaks that have occurred in recent years. This review also focuses in the main molecular techniques for detection of waterborne pathogens and the use of QMRA approach to protect public health.

  17. Doppler method leak detection for LMFBR steam generators. Pt. 3. Investigation of detection sensitivity and method

    International Nuclear Information System (INIS)

    Kumagai, Hiromichi; Kinoshita, Izumi

    2001-01-01

    To prevent the expansion of tube damage and to maintain structural integrity in the steam generators (SGs) of a fast breeder reactor (FBR), it is necessary to detect precisely and immediately any leakage of water from heat transfer tubes. Therefore, the Doppler method was developed. Previous studies have revealed that, in the SG full-sector model that simulates actual SGs, the Doppler method can detect bubbles of 0.4 l/s within a few seconds. However in consideration of the dissolution rate of hydrogen generated by a sodium-water reaction even from a small water leak, it is necessary to detect smaller leakages of water from the heat transfer tubes. The detection sensitivity of the Doppler method and the influence of background noise were experimentally investigated. In-water experiments were performed using the SG model. The results show that the Doppler method can detect bubbles of 0.01 l/s (equivalent to a water leak rate of about 0.01 g/s) within a few seconds and that the background noise has little effect on water leak detection performance. The Doppler method thus has great potential for the detection of water leakage in SGs. (author)

  18. Novel Methods of Hydrogen Leak Detection

    International Nuclear Information System (INIS)

    Pushpinder S Puri

    2006-01-01

    With the advent of the fuel cell technology and a drive for clean fuel, hydrogen gas is emerging as a leading candidate for the fuel of choice. For hydrogen to become a consumer fuel for automotive and domestic power generation, safety is paramount. It is, therefore, desired to have a method and system for hydrogen leak detection using odorant which can incorporate a uniform concentration of odorant in the hydrogen gas, when odorants are mixed in the hydrogen storage or delivery means. It is also desired to develop methods where the odorant is not added to the bulk hydrogen, keeping it free of the odorization additives. When odorants are not added to the hydrogen gas in the storage or delivery means, methods must be developed to incorporate odorant in the leaking gas so that leaks can be detected by small. Further, when odorants are not added to the stored hydrogen, it may also be desirable to observe leaks by sight by discoloration of the surface of the storage or transportation vessels. A series of novel solutions are proposed which address the issues raised above. These solutions are divided into three categories as follows: 1. Methods incorporating an odorant in the path of hydrogen leak as opposed to adding it to the hydrogen gas. 2. Methods where odorants are generated in-situ by chemical reaction with the leaking hydrogen 3. Methods of dispensing and storing odorants in high pressure hydrogen gas which release odorants to the gas at a uniform and predetermined rates. Use of one or more of the methods described here in conjunction with appropriate engineering solutions will assure the ultimate safety of hydrogen use as a commercial fuel. (authors)

  19. Sensing Methods for Detecting Analog Television Signals

    Science.gov (United States)

    Rahman, Mohammad Azizur; Song, Chunyi; Harada, Hiroshi

    This paper introduces a unified method of spectrum sensing for all existing analog television (TV) signals including NTSC, PAL and SECAM. We propose a correlation based method (CBM) with a single reference signal for sensing any analog TV signals. In addition we also propose an improved energy detection method. The CBM approach has been implemented in a hardware prototype specially designed for participating in Singapore TV white space (WS) test trial conducted by Infocomm Development Authority (IDA) of the Singapore government. Analytical and simulation results of the CBM method will be presented in the paper, as well as hardware testing results for sensing various analog TV signals. Both AWGN and fading channels will be considered. It is shown that the theoretical results closely match with those from simulations. Sensing performance of the hardware prototype will also be presented in fading environment by using a fading simulator. We present performance of the proposed techniques in terms of probability of false alarm, probability of detection, sensing time etc. We also present a comparative study of the various techniques.

  20. Neutron imaging integrated circuit and method for detecting neutrons

    Science.gov (United States)

    Nagarkar, Vivek V.; More, Mitali J.

    2017-12-05

    The present disclosure provides a neutron imaging detector and a method for detecting neutrons. In one example, a method includes providing a neutron imaging detector including plurality of memory cells and a conversion layer on the memory cells, setting one or more of the memory cells to a first charge state, positioning the neutron imaging detector in a neutron environment for a predetermined time period, and reading a state change at one of the memory cells, and measuring a charge state change at one of the plurality of memory cells from the first charge state to a second charge state less than the first charge state, where the charge state change indicates detection of neutrons at said one of the memory cells.

  1. Detection of Hydrological changes of Wujiang River

    Science.gov (United States)

    Dong, L.; Chen, Y.

    2016-12-01

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

  2. Variable threshold method for ECG R-peak detection.

    Science.gov (United States)

    Kew, Hsein-Ping; Jeong, Do-Un

    2011-10-01

    In this paper, a wearable belt-type ECG electrode worn around the chest by measuring the real-time ECG is produced in order to minimize the inconvenient in wearing. ECG signal is detected using a potential instrument system. The measured ECG signal is transmits via an ultra low power consumption wireless data communications unit to personal computer using Zigbee-compatible wireless sensor node. ECG signals carry a lot of clinical information for a cardiologist especially the R-peak detection in ECG. R-peak detection generally uses the threshold value which is fixed. There will be errors in peak detection when the baseline changes due to motion artifacts and signal size changes. Preprocessing process which includes differentiation process and Hilbert transform is used as signal preprocessing algorithm. Thereafter, variable threshold method is used to detect the R-peak which is more accurate and efficient than fixed threshold value method. R-peak detection using MIT-BIH databases and Long Term Real-Time ECG is performed in this research in order to evaluate the performance analysis.

  3. Bayesian Methods for Radiation Detection and Dosimetry

    International Nuclear Information System (INIS)

    Peter G. Groer

    2002-01-01

    We performed work in three areas: radiation detection, external and internal radiation dosimetry. In radiation detection we developed Bayesian techniques to estimate the net activity of high and low activity radioactive samples. These techniques have the advantage that the remaining uncertainty about the net activity is described by probability densities. Graphs of the densities show the uncertainty in pictorial form. Figure 1 below demonstrates this point. We applied stochastic processes for a method to obtain Bayesian estimates of 222Rn-daughter products from observed counting rates. In external radiation dosimetry we studied and developed Bayesian methods to estimate radiation doses to an individual with radiation induced chromosome aberrations. We analyzed chromosome aberrations after exposure to gammas and neutrons and developed a method for dose-estimation after criticality accidents. The research in internal radiation dosimetry focused on parameter estimation for compartmental models from observed compartmental activities. From the estimated probability densities of the model parameters we were able to derive the densities for compartmental activities for a two compartment catenary model at different times. We also calculated the average activities and their standard deviation for a simple two compartment model

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

    CSIR Research Space (South Africa)

    Van Den Bergh, F

    2009-07-01

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

  5. A New Outlier Detection Method for Multidimensional Datasets

    KAUST Repository

    Abdel Messih, Mario A.

    2012-07-01

    This study develops a novel hybrid method for outlier detection (HMOD) that combines the idea of distance based and density based methods. The proposed method has two main advantages over most of the other outlier detection methods. The first advantage is that it works well on both dense and sparse datasets. The second advantage is that, unlike most other outlier detection methods that require careful parameter setting and prior knowledge of the data, HMOD is not very sensitive to small changes in parameter values within certain parameter ranges. The only required parameter to set is the number of nearest neighbors. In addition, we made a fully parallelized implementation of HMOD that made it very efficient in applications. Moreover, we proposed a new way of using the outlier detection for redundancy reduction in datasets where the confidence level that evaluates how accurate the less redundant dataset can be used to represent the original dataset can be specified by users. HMOD is evaluated on synthetic datasets (dense and mixed “dense and sparse”) and a bioinformatics problem of redundancy reduction of dataset of position weight matrices (PWMs) of transcription factor binding sites. In addition, in the process of assessing the performance of our redundancy reduction method, we developed a simple tool that can be used to evaluate the confidence level of reduced dataset representing the original dataset. The evaluation of the results shows that our method can be used in a wide range of problems.

  6. Apparatus and method for detecting explosives

    International Nuclear Information System (INIS)

    Griffith, B.

    1976-01-01

    An apparatus is described for use in situations such as airports to detect explosives hidden in containers (for eg. suitcases). The method involves the evaluation of the quantities of oxygen and nitrogen within the container by neutron activation analysis and the determination of whether these quantities exceed predetermined limits. The equipment includes a small sub-critical lower powered reactor for thermal (0.01 to 0.10 eV) neutron production, a radium beryllium primary source, a deuterium-tritium reactor as a high energy (> 1.06 MeV) neutron source and Geiger counter detector arrays. (UK)

  7. Novel Methods of Hydrogen Leak Detection

    International Nuclear Information System (INIS)

    Pushpinder S Puri

    2006-01-01

    For hydrogen to become a consumer fuel for automotive and domestic power generation, safety is paramount. Today's hydrogen systems are built with inherent safety measures and multiple levels of protection. However, human senses, in particular, the sense of smell, is considered the ultimate safeguards against leaks. Since hydrogen is an odorless gas, use of odorants to detect leaks, as is done in case of natural gas, is obvious solution. The odorants required for hydrogen used in fuel cells have a unique requirement which must be met. This is because almost all of the commercial odorants used in gas leak detection contain sulfur which acts as poison for the catalysts used in hydrogen based fuel cells, most specifically for the PEM (polymer electrolyte membrane or proton exchange membrane) fuel cells. A possible solution to this problem is to use non-sulfur containing odorants. Chemical compounds based on mixtures of acrylic acid and nitrogen compounds have been adopted to achieve a sulfur-free odorization of a gas. It is, therefore, desired to have a method and system for hydrogen leak detection using odorant which can incorporate a uniform concentration of odorant in the hydrogen gas, when odorants are mixed in the hydrogen storage or delivery means. It is also desired to develop methods where the odorant is not added to the bulk hydrogen, keeping it free of the odorization additives. A series of novel solutions are proposed which address the issues raised above. These solutions are divided into three categories as follows: 1. Methods incorporating an odorant in the path of hydrogen leak as opposed to adding it to the hydrogen gas. 2. Methods where odorants are generated in-situ by chemical reaction with the leaking hydrogen 3. Methods of dispensing and storing odorants in high pressure hydrogen gas which release odorants to the gas at a uniform and predetermined rates. Use of one or more of the methods described here in conjunction with appropriate engineering

  8. Early detection of structual changes in random signal

    International Nuclear Information System (INIS)

    Kuroda, Yoshiteru; Yokota, Katsuhiro

    1981-01-01

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

  9. Radiation sensitive area detection device and method

    Science.gov (United States)

    Carter, Daniel C. (Inventor); Hecht, Diana L. (Inventor); Witherow, William K. (Inventor)

    1991-01-01

    A radiation sensitive area detection device for use in conjunction with an X ray, ultraviolet or other radiation source is provided which comprises a phosphor containing film which releases a stored diffraction pattern image in response to incoming light or other electromagnetic wave. A light source such as a helium-neon laser, an optical fiber capable of directing light from the laser source onto the phosphor film and also capable of channelling the fluoresced light from the phosphor film to an integrating sphere which directs the light to a signal processing means including a light receiving means such as a photomultiplier tube. The signal processing means allows translation of the fluoresced light in order to detect the original pattern caused by the diffraction of the radiation by the original sample. The optical fiber is retained directly in front of the phosphor screen by a thin metal holder which moves up and down across the phosphor screen and which features a replaceable pinhole which allows easy adjustment of the resolution of the light projected onto the phosphor film. The device produces near real time images with high spatial resolution and without the distortion that accompanies prior art devices employing photomultiplier tubes. A method is also provided for carrying out radiation area detection using the device of the invention.

  10. OBJECT-ORIENTED CHANGE DETECTION BASED ON MULTI-SCALE APPROACH

    Directory of Open Access Journals (Sweden)

    Y. Jia

    2016-06-01

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

  11. Lagrangian based methods for coherent structure detection

    Energy Technology Data Exchange (ETDEWEB)

    Allshouse, Michael R., E-mail: mallshouse@chaos.utexas.edu [Center for Nonlinear Dynamics and Department of Physics, University of Texas at Austin, Austin, Texas 78712 (United States); Peacock, Thomas, E-mail: tomp@mit.edu [Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139 (United States)

    2015-09-15

    There has been a proliferation in the development of Lagrangian analytical methods for detecting coherent structures in fluid flow transport, yielding a variety of qualitatively different approaches. We present a review of four approaches and demonstrate the utility of these methods via their application to the same sample analytic model, the canonical double-gyre flow, highlighting the pros and cons of each approach. Two of the methods, the geometric and probabilistic approaches, are well established and require velocity field data over the time interval of interest to identify particularly important material lines and surfaces, and influential regions, respectively. The other two approaches, implementing tools from cluster and braid theory, seek coherent structures based on limited trajectory data, attempting to partition the flow transport into distinct regions. All four of these approaches share the common trait that they are objective methods, meaning that their results do not depend on the frame of reference used. For each method, we also present a number of example applications ranging from blood flow and chemical reactions to ocean and atmospheric flows.

  12. Some methods for the detection of fissionable matter; Quelques methodes de detection des corps fissiles

    Energy Technology Data Exchange (ETDEWEB)

    Guery, M [Commissariat a l' Energie Atomique, Saclay (France). Centre d' Etudes Nucleaires

    1967-03-01

    A number of equipments or processes allowing to detect uranium or plutonium in industrial plants, and in particular to measure solution concentrations, are studied here. Each method has its own field of applications and has its own performances, which we have tried to define by calculations and by experiments. The following topics have been treated: {gamma} absorptiometer with an Am source, detection test by neutron multiplication, apparatus for the measurement of the {alpha} activity of a solution, fissionable matter detection by {gamma} emission, fissionable matter detection by neutron emission. (author) [French] On examine ici plusieurs appareils ou procedes qui permettent de detecter l'uranium ou le plutonium dans les installations industrielles, et en particulier de mesurer les concentrations de solutions. Chacune des methodes a son domaine d'application et ses performances, qu'on a tente de definir par le calcul et par des experiences. Les sujets traites sont les suivants: absorptiometre {gamma} a source d'americium, essais de detection par multiplication neutronique, appareil de mesure de l'activite {alpha} d'une solution, detection des matieres fissiles par leur emission {gamma}, detection des matieres fissiles par leur emission neutronique. (auteur)

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

    NARCIS (Netherlands)

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

    2012-01-01

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

  14. Delamination detection using methods of computational intelligence

    Science.gov (United States)

    Ihesiulor, Obinna K.; Shankar, Krishna; Zhang, Zhifang; Ray, Tapabrata

    2012-11-01

    Abstract Reliable delamination prediction scheme is indispensable in order to prevent potential risks of catastrophic failures in composite structures. The existence of delaminations changes the vibration characteristics of composite laminates and hence such indicators can be used to quantify the health characteristics of laminates. An approach for online health monitoring of in-service composite laminates is presented in this paper that relies on methods based on computational intelligence. Typical changes in the observed vibration characteristics (i.e. change in natural frequencies) are considered as inputs to identify the existence, location and magnitude of delaminations. The performance of the proposed approach is demonstrated using numerical models of composite laminates. Since this identification problem essentially involves the solution of an optimization problem, the use of finite element (FE) methods as the underlying tool for analysis turns out to be computationally expensive. A surrogate assisted optimization approach is hence introduced to contain the computational time within affordable limits. An artificial neural network (ANN) model with Bayesian regularization is used as the underlying approximation scheme while an improved rate of convergence is achieved using a memetic algorithm. However, building of ANN surrogate models usually requires large training datasets. K-means clustering is effectively employed to reduce the size of datasets. ANN is also used via inverse modeling to determine the position, size and location of delaminations using changes in measured natural frequencies. The results clearly highlight the efficiency and the robustness of the approach.

  15. Nucleic acid detection system and method for detecting influenza

    Science.gov (United States)

    Cai, Hong; Song, Jian

    2015-03-17

    The invention provides a rapid, sensitive and specific nucleic acid detection system which utilizes isothermal nucleic acid amplification in combination with a lateral flow chromatographic device, or DNA dipstick, for DNA-hybridization detection. The system of the invention requires no complex instrumentation or electronic hardware, and provides a low cost nucleic acid detection system suitable for highly sensitive pathogen detection. Hybridization to single-stranded DNA amplification products using the system of the invention provides a sensitive and specific means by which assays can be multiplexed for the detection of multiple target sequences.

  16. Supersonic wave detection method and supersonic detection device

    International Nuclear Information System (INIS)

    Machida, Koichi; Seto, Takehiro; Ishizaki, Hideaki; Asano, Rin-ichi.

    1996-01-01

    The present invention provides a method of and device for a detection suitable to a channel box which is used while covering a fuel assembly of a BWR type reactor. Namely, a probe for transmitting/receiving supersonic waves scans on the surface of the channel box. A data processing device determines an index showing a selective orientation degree of crystal direction of the channel box based on the signals received by the probe. A judging device compares the determined index with a previously determined allowable range to judge whether the channel box is satisfactory or not based on the result of the comparison. The judgement are on the basis that (1) the bending of the channel box is caused by the difference of elongation of opposed surfaces, (2) the elongation due to irradiation is caused by the selective orientation of crystal direction, and (3) the bending of the channel box can be suppressed within a predetermined range by suppressing the index determined by the measurement of supersonic waves having a correlation with the selective orientation of the crystal direction. As a result, the performance of the channel box capable of enduring high burnup region can be confirmed in a nondestructive manner. (I.S.)

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2009-01-01

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

  18. Orthogonal transformations for change detection, Matlab code

    DEFF Research Database (Denmark)

    2005-01-01

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

  19. Thermoluminescence method for detection of irradiated food

    International Nuclear Information System (INIS)

    Pinnioja, S.

    1998-01-01

    A method of thermoluminescence (TL) analysis was developed for the detection of irradiated foods. The TL method is based on the determination of thermoluminescence of adhering or contaminating minerals separated from foods by wet sieving and treatment with high density liquid. Carbon tetrachloride provided a suitable alternative for foods that form gels with water. Thermoluminescence response of minerals in a first TL measurement is normalised with a second TL measurement of the same mineral sample after calibration irradiation to a dose of 5 kGy. The decision about irradiation is made on the basis of a comparison of the two TL spectra: if the two TL glow curves match in shape and intensity the sample has been irradiated, and if they are clearly different it has not been irradiated. An attractive feature of TL analysis is that the mineral material itself is used for calibration; no reference material is required. Foods of interest in the investigation were herbs, spices, berries and seafood. The presence of minerals in samples is a criterion for application of the method, and appropriate minerals were found in all herbs, spices and berries. The most common minerals in terrestrial food were tecto-silicates - quartz and feldspars - which with their intense and stable thermoluminescence were well suited for the analysis. Mica proved to be useless for detection purposes, whereas carbonate in the form of calcite separated from intestines of seafood was acceptable. Fading of the TL signal is considerable in the low temperature part of the glow curve during a storage of several months after irradiation. However, spices and herbs could easily be identified as irradiated even after two years storage. Conditions for seafood, which is stored in a freezer, are different, and only slight fading was observed after one year. The effect of mineral composition and structure on TL was studied for feldspars. Feldspars originating from subtropical and tropical regions exhibit lower TL

  20. Thermoluminescence method for detection of irradiated food

    Energy Technology Data Exchange (ETDEWEB)

    Pinnioja, S

    1998-12-31

    A method of thermoluminescence (TL) analysis was developed for the detection of irradiated foods. The TL method is based on the determination of thermoluminescence of adhering or contaminating minerals separated from foods by wet sieving and treatment with high density liquid. Carbon tetrachloride provided a suitable alternative for foods that form gels with water. Thermoluminescence response of minerals in a first TL measurement is normalised with a second TL measurement of the same mineral sample after calibration irradiation to a dose of 5 kGy. The decision about irradiation is made on the basis of a comparison of the two TL spectra: if the two TL glow curves match in shape and intensity the sample has been irradiated, and if they are clearly different it has not been irradiated. An attractive feature of TL analysis is that the mineral material itself is used for calibration; no reference material is required. Foods of interest in the investigation were herbs, spices, berries and seafood. The presence of minerals in samples is a criterion for application of the method, and appropriate minerals were found in all herbs, spices and berries. The most common minerals in terrestrial food were tecto-silicates - quartz and feldspars - which with their intense and stable thermoluminescence were well suited for the analysis. Mica proved to be useless for detection purposes, whereas carbonate in the form of calcite separated from intestines of seafood was acceptable. Fading of the TL signal is considerable in the low temperature part of the glow curve during a storage of several months after irradiation. However, spices and herbs could easily be identified as irradiated even after two years storage. Conditions for seafood, which is stored in a freezer, are different, and only slight fading was observed after one year. The effect of mineral composition and structure on TL was studied for feldspars. Feldspars originating from subtropical and tropical regions exhibit lower TL

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2014-09-01

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

  2. Odour detection methods: olfactometry and chemical sensors.

    Science.gov (United States)

    Brattoli, Magda; de Gennaro, Gianluigi; de Pinto, Valentina; Loiotile, Annamaria Demarinis; Lovascio, Sara; Penza, Michele

    2011-01-01

    The complexity of the odours issue arises from the sensory nature of smell. From the evolutionary point of view olfaction is one of the oldest senses, allowing for seeking food, recognizing danger or communication: human olfaction is a protective sense as it allows the detection of potential illnesses or infections by taking into account the odour pleasantness/unpleasantness. Odours are mixtures of light and small molecules that, coming in contact with various human sensory systems, also at very low concentrations in the inhaled air, are able to stimulate an anatomical response: the experienced perception is the odour. Odour assessment is a key point in some industrial production processes (i.e., food, beverages, etc.) and it is acquiring steady importance in unusual technological fields (i.e., indoor air quality); this issue mainly concerns the environmental impact of various industrial activities (i.e., tanneries, refineries, slaughterhouses, distilleries, civil and industrial wastewater treatment plants, landfills and composting plants) as sources of olfactory nuisances, the top air pollution complaint. Although the human olfactory system is still regarded as the most important and effective "analytical instrument" for odour evaluation, the demand for more objective analytical methods, along with the discovery of materials with chemo-electronic properties, has boosted the development of sensor-based machine olfaction potentially imitating the biological system. This review examines the state of the art of both human and instrumental sensing currently used for the detection of odours. The olfactometric techniques employing a panel of trained experts are discussed and the strong and weak points of odour assessment through human detection are highlighted. The main features and the working principles of modern electronic noses (E-Noses) are then described, focusing on their better performances for environmental analysis. Odour emission monitoring carried out through

  3. Odour Detection Methods: Olfactometry and Chemical Sensors

    Directory of Open Access Journals (Sweden)

    Sara Lovascio

    2011-05-01

    Full Text Available The complexity of the odours issue arises from the sensory nature of smell. From the evolutionary point of view olfaction is one of the oldest senses, allowing for seeking food, recognizing danger or communication: human olfaction is a protective sense as it allows the detection of potential illnesses or infections by taking into account the odour pleasantness/unpleasantness. Odours are mixtures of light and small molecules that, coming in contact with various human sensory systems, also at very low concentrations in the inhaled air, are able to stimulate an anatomical response: the experienced perception is the odour. Odour assessment is a key point in some industrial production processes (i.e., food, beverages, etc. and it is acquiring steady importance in unusual technological fields (i.e., indoor air quality; this issue mainly concerns the environmental impact of various industrial activities (i.e., tanneries, refineries, slaughterhouses, distilleries, civil and industrial wastewater treatment plants, landfills and composting plants as sources of olfactory nuisances, the top air pollution complaint. Although the human olfactory system is still regarded as the most important and effective “analytical instrument” for odour evaluation, the demand for more objective analytical methods, along with the discovery of materials with chemo-electronic properties, has boosted the development of sensor-based machine olfaction potentially imitating the biological system. This review examines the state of the art of both human and instrumental sensing currently used for the detection of odours. The olfactometric techniques employing a panel of trained experts are discussed and the strong and weak points of odour assessment through human detection are highlighted. The main features and the working principles of modern electronic noses (E-Noses are then described, focusing on their better performances for environmental analysis. Odour emission monitoring

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

    Science.gov (United States)

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

    2014-08-01

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

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

    KAUST Repository

    Meng, Rui

    2016-05-15

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

  6. SCREENING METHODS FOR THE DETECTION OF CARTELS

    Directory of Open Access Journals (Sweden)

    Mihail BUŞU

    2014-06-01

    Full Text Available During their everyday activities, the economic operators conclude a multitude of agreements in tacit or written form, such as: contracts or conventions. Some of these arrangements are absolutely necessary for the development of their current activities. These are agreements which, by respecting the rules of competition, are able to bring benefits to consumers and to the entire economy, as a whole. On the other hand, the economic operators often conclude agreements which are harmful to the economy as well as to the consumers, violating the competition rules. Some examples in this respect are: operators’ agreements on price fixing, on market or customers sharing. Before investigating the violation of competition rules, the relevant authorities should identify the possibility of the existence of such illegalities. The theoretical models for detecting the cartels do represent a proactive tool concerning the antitrust activity of competition authorities. The present paper furnishes a review of the methods for detecting cartels as well as a part of their practical application.

  7. A Method to Detect AAC Audio Forgery

    Directory of Open Access Journals (Sweden)

    Qingzhong Liu

    2015-08-01

    Full Text Available Advanced Audio Coding (AAC, a standardized lossy compression scheme for digital audio, which was designed to be the successor of the MP3 format, generally achieves better sound quality than MP3 at similar bit rates. While AAC is also the default or standard audio format for many devices and AAC audio files may be presented as important digital evidences, the authentication of the audio files is highly needed but relatively missing. In this paper, we propose a scheme to expose tampered AAC audio streams that are encoded at the same encoding bit-rate. Specifically, we design a shift-recompression based method to retrieve the differential features between the re-encoded audio stream at each shifting and original audio stream, learning classifier is employed to recognize different patterns of differential features of the doctored forgery files and original (untouched audio files. Experimental results show that our approach is very promising and effective to detect the forgery of the same encoding bit-rate on AAC audio streams. Our study also shows that shift recompression-based differential analysis is very effective for detection of the MP3 forgery at the same bit rate.

  8. Method of detecting a fuel element failure

    International Nuclear Information System (INIS)

    Cohen, P.

    1975-01-01

    A method is described for detecting a fuel element failure in a liquid-sodium-cooled fast breeder reactor consisting of equilibrating a sample of the coolant with a molten salt consisting of a mixture of barium iodide and strontium iodide (or other iodides) whereby a large fraction of any radioactive iodine present in the liquid sodium coolant exchanges with the iodine present in the salt; separating the molten salt and sodium; if necessary, equilibrating the molten salt with nonradioactive sodium and separating the molten salt and sodium; and monitoring the molten salt for the presence of iodine, the presence of iodine indicating that the cladding of a fuel element has failed. (U.S.)

  9. Liquid chromatography detection unit, system, and method

    Science.gov (United States)

    Derenzo, Stephen E.; Moses, William W.

    2015-10-27

    An embodiment of a liquid chromatography detection unit includes a fluid channel and a radiation detector. The radiation detector is operable to image a distribution of a radiolabeled compound as the distribution travels along the fluid channel. An embodiment of a liquid chromatography system includes an injector, a separation column, and a radiation detector. The injector is operable to inject a sample that includes a radiolabeled compound into a solvent stream. The position sensitive radiation detector is operable to image a distribution of the radiolabeled compound as the distribution travels along a fluid channel. An embodiment of a method of liquid chromatography includes injecting a sample that comprises radiolabeled compounds into a solvent. The radiolabeled compounds are then separated. A position sensitive radiation detector is employed to image distributions of the radiolabeled compounds as the radiolabeled compounds travel along a fluid channel.

  10. A new ultrasonic signal amplification method for detection of bacteria

    Science.gov (United States)

    Kant Shukla, Shiva; Resa López, Pablo; Sierra Sánchez, Carlos; Urréjola, José; Segura, Luis Elvira

    2012-10-01

    A new method is presented that increases the sensitivity of ultrasound-based techniques for detection of bacteria. The technique was developed for the detection of catalase-positive microorganisms. It uses a bubble trapping medium containing hydrogen peroxide that is mixed with the sample for microbiological evaluation. The enzyme catalase is present in catalase-positive bacteria, which induces a rapid hydrolysis of hydrogen peroxide, forming bubbles which remain in the medium. This reaction results in the amplification of the mechanical changes that the microorganisms produce in the medium. The effect can be detected by means of ultrasonic wave amplitude continuous measurement since the bubbles increase the ultrasonic attenuation significantly. It is shown that microorganism concentrations of the order of 105 cells ml-1 can be detected using this method. This allows an improvement of three orders of magnitude in the ultrasonic detection threshold of microorganisms in conventional culture media, and is competitive with modern rapid microbiological methods. It can also be used for the characterization of the enzymatic activity.

  11. A new ultrasonic signal amplification method for detection of bacteria

    International Nuclear Information System (INIS)

    Shukla, Shiva Kant; López, Pablo Resa; Sánchez, Carlos Sierra; Segura, Luis Elvira; Urréjola, José

    2012-01-01

    A new method is presented that increases the sensitivity of ultrasound-based techniques for detection of bacteria. The technique was developed for the detection of catalase-positive microorganisms. It uses a bubble trapping medium containing hydrogen peroxide that is mixed with the sample for microbiological evaluation. The enzyme catalase is present in catalase-positive bacteria, which induces a rapid hydrolysis of hydrogen peroxide, forming bubbles which remain in the medium. This reaction results in the amplification of the mechanical changes that the microorganisms produce in the medium. The effect can be detected by means of ultrasonic wave amplitude continuous measurement since the bubbles increase the ultrasonic attenuation significantly. It is shown that microorganism concentrations of the order of 10 5 cells ml −1 can be detected using this method. This allows an improvement of three orders of magnitude in the ultrasonic detection threshold of microorganisms in conventional culture media, and is competitive with modern rapid microbiological methods. It can also be used for the characterization of the enzymatic activity. (paper)

  12. Epigenetic changes detected in micropropagated hop plants.

    Science.gov (United States)

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

    2009-07-01

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

  13. Activity Level Change Detection for Persistent Surveillance

    National Research Council Canada - National Science Library

    Liu, F; Bush, L. A

    2004-01-01

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

  14. Detecting Holocene changes in thermohaline circulation

    OpenAIRE

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

    2000-01-01

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

  15. Change Detection in Naturalistic Pictures among Children with Autism

    Science.gov (United States)

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

    2009-01-01

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

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

    NARCIS (Netherlands)

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

    2014-01-01

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

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

    Science.gov (United States)

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

    2000-01-01

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

  18. Ultrasonic defect detection method for socket welding joint

    International Nuclear Information System (INIS)

    Tominaga, Masaaki; Matsuo, Toshiyuki; Ueno, Akihiro; Watanabe, Kunimichi; Kawamata, Kunio.

    1995-01-01

    The present invention provides a method of detecting defects over a wide range of a socket weld portion of various kinds of pipelines used, for example, in a nuclear power plant. Namely, an inclined probe is disposed to a jig for detecting defects by ultrasonic waves. This is rotated at least by one turn along the peripheral surface of the material to be detected such as weld tube joints. Defects of weld portion of the material can be detected automatically by using ultrasonic waves during the rotation. The inclined probe for detecting defects by ultrasonic waves comprises a transmission portion having a planar transmittance oscillator disposed to a wedge on the transmission side and a receiving portion comprising a planar receiving oscillator disposed to a wedge on the receiving side. With such a constitution, ultrasonic waves are emitted from the transmission portion to the defect detection portion in the welded portion. If a defect is present, defective echo is reflected to the receiving portion disposed ahead of the probe. Since the defective echo changes depending on the height of the detective portion, the estimation of the height of the defect can be facilitated. (I.S.)

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

    Directory of Open Access Journals (Sweden)

    Sebastian Aleksandrowicz

    2014-06-01

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

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

    Science.gov (United States)

    Hollingworth, Andrew; Henderson, John M

    2004-07-01

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

  1. Two different hematocrit detection methods: Different methods, different results?

    Directory of Open Access Journals (Sweden)

    Schuepbach Reto A

    2010-03-01

    Full Text Available Abstract Background Less is known about the influence of hematocrit detection methodology on transfusion triggers. Therefore, the aim of the present study was to compare two different hematocrit-assessing methods. In a total of 50 critically ill patients hematocrit was analyzed using (1 blood gas analyzer (ABLflex 800 and (2 the central laboratory method (ADVIA® 2120 and compared. Findings Bland-Altman analysis for repeated measurements showed a good correlation with a bias of +1.39% and 2 SD of ± 3.12%. The 24%-hematocrit-group showed a correlation of r2 = 0.87. With a kappa of 0.56, 22.7% of the cases would have been transfused differently. In the-28%-hematocrit group with a similar correlation (r2 = 0.8 and a kappa of 0.58, 21% of the cases would have been transfused differently. Conclusions Despite a good agreement between the two methods used to determine hematocrit in clinical routine, the calculated difference of 1.4% might substantially influence transfusion triggers depending on the employed method.

  2. Ice Sheet Change Detection by Satellite Image Differencing

    Science.gov (United States)

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

    2010-01-01

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

  3. Sensitive change detection for remote sensing monitoring of nuclear treaties

    DEFF Research Database (Denmark)

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

    2005-01-01

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

  4. Methods for environmental change; an exploratory study

    Directory of Open Access Journals (Sweden)

    Kok Gerjo

    2012-11-01

    Full Text Available Abstract Background While the interest of health promotion researchers in change methods directed at the target population has a long tradition, interest in change methods directed at the environment is still developing. In this survey, the focus is on methods for environmental change; especially about how these are composed of methods for individual change (‘Bundling’ and how within one environmental level, organizations, methods differ when directed at the management (‘At’ or applied by the management (‘From’. Methods The first part of this online survey dealt with examining the ‘bundling’ of individual level methods to methods at the environmental level. The question asked was to what extent the use of an environmental level method would involve the use of certain individual level methods. In the second part of the survey the question was whether there are differences between applying methods directed ‘at’ an organization (for instance, by a health promoter versus ‘from’ within an organization itself. All of the 20 respondents are experts in the field of health promotion. Results Methods at the individual level are frequently bundled together as part of a method at a higher ecological level. A number of individual level methods are popular as part of most of the environmental level methods, while others are not chosen very often. Interventions directed at environmental agents often have a strong focus on the motivational part of behavior change. There are different approaches targeting a level or being targeted from a level. The health promoter will use combinations of motivation and facilitation. The manager will use individual level change methods focusing on self-efficacy and skills. Respondents think that any method may be used under the right circumstances, although few endorsed coercive methods. Conclusions Taxonomies of theoretical change methods for environmental change should include combinations of individual

  5. Recent developments in optical detection methods for microchip separations

    NARCIS (Netherlands)

    Götz, S.; Karst, U.

    2007-01-01

    This paper summarizes the features and performances of optical detection systems currently applied in order to monitor separations on microchip devices. Fluorescence detection, which delivers very high sensitivity and selectivity, is still the most widely applied method of detection. Instruments

  6. Kernel principal component analysis for change detection

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg; Morton, J.C.

    2008-01-01

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

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

    Science.gov (United States)

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

    2016-07-01

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

  8. Methods for environmental change; an exploratory study.

    Science.gov (United States)

    Kok, Gerjo; Gottlieb, Nell H; Panne, Robert; Smerecnik, Chris

    2012-11-28

    While the interest of health promotion researchers in change methods directed at the target population has a long tradition, interest in change methods directed at the environment is still developing. In this survey, the focus is on methods for environmental change; especially about how these are composed of methods for individual change ('Bundling') and how within one environmental level, organizations, methods differ when directed at the management ('At') or applied by the management ('From'). The first part of this online survey dealt with examining the 'bundling' of individual level methods to methods at the environmental level. The question asked was to what extent the use of an environmental level method would involve the use of certain individual level methods. In the second part of the survey the question was whether there are differences between applying methods directed 'at' an organization (for instance, by a health promoter) versus 'from' within an organization itself. All of the 20 respondents are experts in the field of health promotion. Methods at the individual level are frequently bundled together as part of a method at a higher ecological level. A number of individual level methods are popular as part of most of the environmental level methods, while others are not chosen very often. Interventions directed at environmental agents often have a strong focus on the motivational part of behavior change.There are different approaches targeting a level or being targeted from a level. The health promoter will use combinations of motivation and facilitation. The manager will use individual level change methods focusing on self-efficacy and skills. Respondents think that any method may be used under the right circumstances, although few endorsed coercive methods. Taxonomies of theoretical change methods for environmental change should include combinations of individual level methods that may be bundled and separate suggestions for methods targeting a level

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

    Science.gov (United States)

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

    2017-12-01

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

  10. A dual-process account of auditory change detection.

    Science.gov (United States)

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

    2010-08-01

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

  11. General survey of detection methods for irradiation foods

    International Nuclear Information System (INIS)

    Yang, J. S.

    1997-01-01

    The development of detection techniques is needed, in order for regulating authorities to determine whether or not a particular food sample has been irradiated, and label it accordingly so that a consumer's free choice can be exercised. The chemical and physical changes brought about in foods by practical doses of irradiation are very small, and therefore very sensitive methods are required. A number of promising approaches have been developed and evaluated. These include chemical, physical and biological methods ranging from the very simple to highly sophisticated techniques. (author)

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

    International Nuclear Information System (INIS)

    Byler, E.

    1997-01-01

    The primary objective of this project is to apply robotic and optical sensor technology to the operational inspection of mixed toxic and radioactive waste stored in barrels, using Automated Baseline Change Detection (ABCD), based on image subtraction. Absolute change detection is based on detecting any visible physical changes, regardless of cause, between a current inspection image of a barrel and an archived baseline image of the same barrel. Thus, in addition to rust, the ABCD system can also detect corrosion, leaks, dents, and bulges. The ABCD approach and method rely on precise camera positioning and repositioning relative to the barrel and on feature recognition in images. The ABCD image processing software was installed on a robotic vehicle developed under a related DOE/FETC contract DE-AC21-92MC29112 Intelligent Mobile Sensor System (IMSS) and integrated with the electronics and software. This vehicle was designed especially to navigate in DOE Waste Storage Facilities. Initial system testing was performed at Fernald in June 1996. After some further development and more extensive integration the prototype integrated system was installed and tested at the Radioactive Waste Management Facility (RWMC) at INEEL beginning in April 1997 through the present (November 1997). The integrated system, composed of ABCD imaging software and IMSS mobility base, is called MISS EVE (Mobile Intelligent Sensor System--Environmental Validation Expert). Evaluation of the integrated system in RWMC Building 628, containing approximately 10,000 drums, demonstrated an easy to use system with the ability to properly navigate through the facility, image all the defined drums, and process the results into a report delivered to the operator on a GUI interface and on hard copy. Further work is needed to make the brassboard system more operationally robust

  13. Detection method for nuclear reactor material

    International Nuclear Information System (INIS)

    Isobe, Yusuke; Hashimoto, Motoyuki.

    1995-01-01

    A fine state of a test piece taken out of a reactor core is analyzed upon periodical inspection, and a new test piece previously reproducing the state described above at the outside of the reactor is disposed to the reactor core upon completion of the periodical inspection. Further, a fine state of the material at a time preceding to the operation time at a certain periodical inspection is forecast, and a test piece reproducing the state at the outside of the reactor is disposed to the reactor core upon the completion of the periodical inspection. Since a test piece previously reproducing the change of the state up to a certain periodical inspection by a method other than irradiation of neutrons is newly disposed, radiation of the test piece is not extremely increased even after an extremely long period of summed up reactor operation time, to provide substantially constant radiation level on every test piece. (T.M.)

  14. Image Processing Methods Usable for Object Detection on the Chessboard

    Directory of Open Access Journals (Sweden)

    Beran Ladislav

    2016-01-01

    Full Text Available Image segmentation and object detection is challenging problem in many research. Although many algorithms for image segmentation have been invented, there is no simple algorithm for image segmentation and object detection. Our research is based on combination of several methods for object detection. The first method suitable for image segmentation and object detection is colour detection. This method is very simply, but there is problem with different colours. For this method it is necessary to have precisely determined colour of segmented object before all calculations. In many cases it is necessary to determine this colour manually. Alternative simply method is method based on background removal. This method is based on difference between reference image and detected image. In this paper several methods suitable for object detection are described. Thisresearch is focused on coloured object detection on chessboard. The results from this research with fusion of neural networks for user-computer game checkers will be applied.

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

    Directory of Open Access Journals (Sweden)

    Pessi eLyyra

    2012-03-01

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

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

    Directory of Open Access Journals (Sweden)

    A. Schlichting

    2016-06-01

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

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

    Science.gov (United States)

    Schlichting, A.; Brenner, C.

    2016-06-01

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

  18. Development of detection methods for irradiated foods

    International Nuclear Information System (INIS)

    Yang, Jae Seung; Nam, Hye Seon; Oh, Kyong Nam; Woo, Si Ho; Kim, Kyeung Eun; Yi, Sang Duk; Park, Jun Young; Kim, Kyong Su; Hwang, Keum Taek

    2000-04-01

    In 1999, we have been studied (1) on the detection of irradiated foods by ESR spectroscopy, by thermoluminescence, and by viscometry for physical measurements, (2) on the detection of hydrocarbons and 2-alkylcyclobutanones derived from fatty foods by GC/MS for chemical measurements, (3) on the screening and detection of irradiated foods by Comet assay and immunochemical (ELISA) technique for biological or biochemical measurements

  19. Development of detection methods for irradiated foods

    Energy Technology Data Exchange (ETDEWEB)

    Yang, Jae Seung; Nam, Hye Seon; Oh, Kyong Nam; Woo, Si Ho; Kim, Kyeung Eun; Yi, Sang Duk; Park, Jun Young; Kim, Kyong Su; Hwang, Keum Taek

    2000-04-01

    In 1999, we have been studied (1) on the detection of irradiated foods by ESR spectroscopy, by thermoluminescence, and by viscometry for physical measurements, (2) on the detection of hydrocarbons and 2-alkylcyclobutanones derived from fatty foods by GC/MS for chemical measurements, (3) on the screening and detection of irradiated foods by Comet assay and immunochemical (ELISA) technique for biological or biochemical measurements.

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

    Science.gov (United States)

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

    2016-04-01

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

  1. Stochastic Change Detection based on an Active Fault Diagnosis Approach

    DEFF Research Database (Denmark)

    Poulsen, Niels Kjølstad; Niemann, Hans Henrik

    2007-01-01

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

  2. Unsupervised Speaker Change Detection for Broadcast News Segmentation

    DEFF Research Database (Denmark)

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

    2006-01-01

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

  3. Detection and monitoring of invasive exotic plants: a comparison of four sampling methods

    Science.gov (United States)

    Cynthia D. Huebner

    2007-01-01

    The ability to detect and monitor exotic invasive plants is likely to vary depending on the sampling method employed. Methods with strong qualitative thoroughness for species detection often lack the intensity necessary to monitor vegetation change. Four sampling methods (systematic plot, stratified-random plot, modified Whittaker, and timed meander) in hemlock and red...

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

    Science.gov (United States)

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

    2017-09-01

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

  5. Alcohol Detection in Exhaled Air by NDIR Method

    Science.gov (United States)

    Fujitsuka, Norio; Yonemura, Masatoshi; Sakakibara, Kiyomi; Taguchi, Toshiyuki; Wakita, Toshihiro

    In recent years, the increase in traffic accidents associated with drunk driving has become a serious social issue. Therefore, there is a need for an in-vehicle system that can detect the fact that the driver is under the influence of alcohol. We thought a method for alcohol detection in the breath of the driver, based on a nondispersive infrared (NDIR) method, is suitable for this system. Since alcohol content in the driver's breath is significantly diluted at the sensor device, it is necessary that the sensor is highly sensitive to detect diluted alcohol. A quantum cascade laser was used to produce highly intense infrared light source. An infrared hollow fiber used in medical treatment was utilized as a gas absorption cell. Since the core of the fiber is hollow, gas is introduced for analyzer. The flexibility of the fiber allowed it to be looped so that 2 m fiber in length could be formed into a compact coil of 29 cm in diameter. It was clarified that the light intensity change of light output from the hollow fiber with ethanol density, and rarefied ethanol as small as 1 ppm in density was detected.

  6. A new fault detection method for computer networks

    International Nuclear Information System (INIS)

    Lu, Lu; Xu, Zhengguo; Wang, Wenhai; Sun, Youxian

    2013-01-01

    Over the past few years, fault detection for computer networks has attracted extensive attentions for its importance in network management. Most existing fault detection methods are based on active probing techniques which can detect the occurrence of faults fast and precisely. But these methods suffer from the limitation of traffic overhead, especially in large scale networks. To relieve traffic overhead induced by active probing based methods, a new fault detection method, whose key is to divide the detection process into multiple stages, is proposed in this paper. During each stage, only a small region of the network is detected by using a small set of probes. Meanwhile, it also ensures that the entire network can be covered after multiple detection stages. This method can guarantee that the traffic used by probes during each detection stage is small sufficiently so that the network can operate without severe disturbance from probes. Several simulation results verify the effectiveness of the proposed method

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

    Directory of Open Access Journals (Sweden)

    Yuan Xu

    2015-01-01

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

  8. Radiation detection device and a radiation detection method

    International Nuclear Information System (INIS)

    Blum, A.

    1975-01-01

    A radiation detection device is described including at least one scintillator in the path of radiation emissions from a distributed radiation source; a plurality of photodetectors for viewing each scintillator; a signal processing means, a storage means, and a data processing means that are interconnected with one another and connected to said photodetectors; and display means connected to the data processing means to locate a plurality of radiation sources in said distributed radiation source and to provide an image of the distributed radiation sources. The storage means includes radiation emission response data and location data from a plurality of known locations for use by the data processing means to derive a more accurate image by comparison of radiation responses from known locations with radiation responses from unknown locations. (auth)

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

    Science.gov (United States)

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

    2014-11-01

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

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

    KAUST Repository

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

    2014-01-01

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

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

    KAUST Repository

    Qahtan, Abdulhakim Ali Ali

    2014-08-01

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

  12. Perspective Effects during Reading: Evidence from Text Change-Detection

    Science.gov (United States)

    Bohan, Jason; Filik, Ruth

    2018-01-01

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

  13. Consumer behavior changing: methods of evaluation

    Directory of Open Access Journals (Sweden)

    Elīna Gaile-Sarkane

    2013-11-01

    Full Text Available The article is devoted to methods of analyses of consumer buying behavior as well as to evaluation of most important factors what influences consumer behavior. This research aims at investigations about the changes in consumer behavior caused by globalization and development of information technologies; it helps to understand the specific factors what should be taken into account in evaluation of consumer behavior. The authors employ well-established quantitative and qualitative methods of research: grouping, analysis, synthesis, expert method, statistic method, etc. Research findings disclosed that there is possibility to introduce new methods for evaluation of changing consumer behavior.

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

    Directory of Open Access Journals (Sweden)

    H. Ru

    2016-06-01

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

  15. Method of detecting a failed fuel

    International Nuclear Information System (INIS)

    Utamura, Motoaki; Urata, Megumi; Uchida, Shunsuke.

    1976-01-01

    Object: To improve detection accuracy of a failed fuel by eliminating a coolant temperature distribution in a fuel assembly. Structure: A failed fuel is detected from contents of nuclear fission products in a coolant by shutting off an upper portion of a fuel assembly provided in the coolant and by sampling the coolant in the fuel assembly. Temperature distribution in the fuel assembly is eliminated, by injecting the higher temperature coolant than that of the coolant inside and outside the fuel assembly when sampling, and thereby replacing the existing coolant in the fuel assembly for the higher temperature coolant. The failed fuel is detected from contents of the fission products existing in the coolant, by sampling the higher temperature coolant of the fuel assembly after a temperature passed. (Moriyama, K.)

  16. Detection and Attribution of Regional Climate Change

    Energy Technology Data Exchange (ETDEWEB)

    Bala, G; Mirin, A

    2007-01-19

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

  17. Method to detect steam generator tube leakage

    International Nuclear Information System (INIS)

    Watabe, Kiyomi

    1994-01-01

    It is important for plant operation to detect minor leakages from the steam generator tube at an early stage, thus, leakage detection has been performed using a condenser air ejector gas monitor and a steam generator blow down monitor, etc. In this study highly-sensitive main steam line monitors have been developed in order to identify leakages in the steam generator more quickly and accurately. The performance of the monitors was verified and the demonstration test at the actual plant was conducted for their intended application to the plants. (author)

  18. An Entropy-Based Network Anomaly Detection Method

    Directory of Open Access Journals (Sweden)

    Przemysław Bereziński

    2015-04-01

    Full Text Available Data mining is an interdisciplinary subfield of computer science involving methods at the intersection of artificial intelligence, machine learning and statistics. One of the data mining tasks is anomaly detection which is the analysis of large quantities of data to identify items, events or observations which do not conform to an expected pattern. Anomaly detection is applicable in a variety of domains, e.g., fraud detection, fault detection, system health monitoring but this article focuses on application of anomaly detection in the field of network intrusion detection.The main goal of the article is to prove that an entropy-based approach is suitable to detect modern botnet-like malware based on anomalous patterns in network. This aim is achieved by realization of the following points: (i preparation of a concept of original entropy-based network anomaly detection method, (ii implementation of the method, (iii preparation of original dataset, (iv evaluation of the method.

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

    DEFF Research Database (Denmark)

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

    2007-01-01

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

  20. Detection methods for centrifugal microfluidic platforms

    DEFF Research Database (Denmark)

    Burger, Robert; Amato, Letizia; Boisen, Anja

    2016-01-01

    Centrifugal microfluidics has attracted much interest from academia as well as industry, since it potentially offers solutions for affordable, user-friendly and portable biosensing. A wide range of so-called fluidic unit operations, e.g. mixing, metering, liquid routing, and particle separation...... for the centrifugal microfluidics platform and cover optical as well as mechanical and electrical detection principles....

  1. Molecular Methods for Detection of Antimicrobial Resistance

    DEFF Research Database (Denmark)

    Anjum, Muna F.; Zankari, Ea; Hasman, Henrik

    2017-01-01

    The increase in bacteria harboring antimicrobial resistance (AMR) is a global problem because there is a paucity of antibiotics available to treat multidrug-resistant bacterial infections in humans and animals. Detection of AMR present in bacteria that may pose a threat to veterinary and public...

  2. Steam generator leak detection using acoustic method

    International Nuclear Information System (INIS)

    Goluchko, V.V.; Sokolov, B.M.; Bulanov, A.N.

    1982-05-01

    The main requirements to meet by a device for leak detection in sodium - water steam generators are determined. The potentialities of instrumentation designed based on the developed requirements have been tested using a model of a 550 kw steam generator [fr

  3. Ultrasound Imaging Methods for Breast Cancer Detection

    NARCIS (Netherlands)

    Ozmen, N.

    2014-01-01

    The main focus of this thesis is on modeling acoustic wavefield propagation and implementing imaging algorithms for breast cancer detection using ultrasound. As a starting point, we use an integral equation formulation, which can be used to solve both the forward and inverse problems. This thesis

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

    Science.gov (United States)

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

    2018-04-01

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

  5. Fast Change Point Detection for Electricity Market Analysis

    Energy Technology Data Exchange (ETDEWEB)

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

    2013-08-25

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

  6. Acoustic change detection algorithm using an FM radio

    Science.gov (United States)

    Goldman, Geoffrey H.; Wolfe, Owen

    2012-06-01

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

  7. Detection of Greenhouse-Gas-Induced Climatic Change

    Energy Technology Data Exchange (ETDEWEB)

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

    1998-05-26

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

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

    Science.gov (United States)

    Morizumi, N.; Kimura, H.

    1986-01-01

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

  9. Anomaly-based Network Intrusion Detection Methods

    Directory of Open Access Journals (Sweden)

    Pavel Nevlud

    2013-01-01

    Full Text Available The article deals with detection of network anomalies. Network anomalies include everything that is quite different from the normal operation. For detection of anomalies were used machine learning systems. Machine learning can be considered as a support or a limited type of artificial intelligence. A machine learning system usually starts with some knowledge and a corresponding knowledge organization so that it can interpret, analyse, and test the knowledge acquired. There are several machine learning techniques available. We tested Decision tree learning and Bayesian networks. The open source data-mining framework WEKA was the tool we used for testing the classify, cluster, association algorithms and for visualization of our results. The WEKA is a collection of machine learning algorithms for data mining tasks.

  10. Standardized Methods for Detection of Poliovirus Antibodies.

    Science.gov (United States)

    Weldon, William C; Oberste, M Steven; Pallansch, Mark A

    2016-01-01

    Testing for neutralizing antibodies against polioviruses has been an established gold standard for assessing individual protection from disease, population immunity, vaccine efficacy studies, and other vaccine clinical trials. Detecting poliovirus specific IgM and IgA in sera and mucosal specimens has been proposed for evaluating the status of population mucosal immunity. More recently, there has been a renewed interest in using dried blood spot cards as a medium for sample collection to enhance surveillance of poliovirus immunity. Here, we describe the modified poliovirus microneutralization assay, poliovirus capture IgM and IgA ELISA assays, and dried blood spot polio serology procedures for the detection of antibodies against poliovirus serotypes 1, 2, and 3.

  11. Methods and systems for detection of radionuclides

    Science.gov (United States)

    Coates, Jr., John T.; DeVol, Timothy A.

    2010-05-25

    Disclosed are materials and systems useful in determining the existence of radionuclides in an aqueous sample. The materials provide the dual function of both extraction and scintillation to the systems. The systems can be both portable and simple to use, and as such can beneficially be utilized to determine presence and optionally concentration of radionuclide contamination in an aqueous sample at any desired location and according to a relatively simple process without the necessity of complicated sample handling techniques. The disclosed systems include a one-step process, providing simultaneous extraction and detection capability, and a two-step process, providing a first extraction step that can be carried out in a remote field location, followed by a second detection step that can be carried out in a different location.

  12. Change detection in polarimetric SAR data over several time points

    DEFF Research Database (Denmark)

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

    2014-01-01

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

  13. Developing methods for detecting radioactive scrap

    International Nuclear Information System (INIS)

    Bellian, J.G.; Johnston, J.G.

    1995-01-01

    During the last 10 years, there have been major developments in radiation detection systems used for catching shielded radioactive sources in scrap metal. The original testing required to determine the extent of the problem and the preliminary designs of the first instruments will be discussed. Present systems available today will be described listing their advantages and disadvantages. In conclusion, the newest developments and state of the art equipment will also be included describing the limits and most appropriate locations for the systems

  14. Development of detection methods for irradiated foods

    International Nuclear Information System (INIS)

    Yang, Jae Seung; Kim, Chong Ki; Lee, Hae Jung; Kim, Kyong Su

    1999-04-01

    To identify irradiated foods, studies have been carried out with electron spin resonance (ESR) spectroscopy on bone containing foods, such as chicken, pork, and beef. The intensity of the signal induced in bones increased linearly with irradiation doses in the range of 1.0 kGy to 5.0 kGy, and it was possible to distinguish between samples given low and high doses of irradiation. The signal stability for 6 weeks made them ideal for the quick and easy identification of irradiated meats. The analysis of DNA damage made on single cells by agarose gel electrophoresis (DNA 'comet assay') can be used to detect irradiated food. All the samples irradiated with over 0.3 kGy were identified to detect post-irradiation by the tail length of their comets. Irradiated samples showed comets with long tails, and the tail length of the comets increased with the dose, while unirradiated samples showed no or very short tails. As a result of the above experiment, the DNA 'comet assay' might be applied to the detection of irradiated grains as a simple, low-cost and rapid screening test. When fats are irradiated, hydrocarbons contained one or two fewer carbon atoms are formed from the parent fatty acids. The major hydrocarbons in irradiated beef, pork and chicken were 1,7-hexadecadiene and 8-heptadecene originating from leic acid. 1,7 hexadecadiene was the highest amount in irradiated beef, pork and chicken. Eight kinds of hydrocarbons were identified from irradiated chicken, among which 1,7-hexadecadiene and 8-heptadecen were detected as major compounds. The concentration of radiation-induced hydrocarbons was relatively constant during 16 weeks

  15. Development of detection methods for irradiated foods

    Energy Technology Data Exchange (ETDEWEB)

    Yang, Jae Seung; Kim, Chong Ki; Lee, Hae Jung [Korea Atomic Energy Research Insitiute, Taejon (Korea, Republic of); Kim, Kyong Su [Chosun University, Kwangju (Korea, Republic of)

    1999-04-01

    To identify irradiated foods, studies have been carried out with electron spin resonance (ESR) spectroscopy on bone containing foods, such as chicken, pork, and beef. The intensity of the signal induced in bones increased linearly with irradiation doses in the range of 1.0 kGy to 5.0 kGy, and it was possible to distinguish between samples given low and high doses of irradiation. The signal stability for 6 weeks made them ideal for the quick and easy identification of irradiated meats. The analysis of DNA damage made on single cells by agarose gel electrophoresis (DNA 'comet assay') can be used to detect irradiated food. All the samples irradiated with over 0.3 kGy were identified to detect post-irradiation by the tail length of their comets. Irradiated samples showed comets with long tails, and the tail length of the comets increased with the dose, while unirradiated samples showed no or very short tails. As a result of the above experiment, the DNA 'comet assay' might be applied to the detection of irradiated grains as a simple, low-cost and rapid screening test. When fats are irradiated, hydrocarbons contained one or two fewer carbon atoms are formed from the parent fatty acids. The major hydrocarbons in irradiated beef, pork and chicken were 1,7-hexadecadiene and 8-heptadecene originating from leic acid. 1,7 hexadecadiene was the highest amount in irradiated beef, pork and chicken. Eight kinds of hydrocarbons were identified from irradiated chicken, among which 1,7-hexadecadiene and 8-heptadecen were detected as major compounds. The concentration of radiation-induced hydrocarbons was relatively constant during 16 weeks.

  16. Blind Methods for Detecting Image Fakery

    Czech Academy of Sciences Publication Activity Database

    Mahdian, Babak; Saic, Stanislav

    2010-01-01

    Roč. 25, č. 4 (2010), s. 18-24 ISSN 0885-8985 R&D Projects: GA ČR GA102/08/0470 Institutional research plan: CEZ:AV0Z10750506 Keywords : Image forensics * Image Fakery * Forgery detection * Authentication Subject RIV: BD - Theory of Information Impact factor: 0.179, year: 2010 http://library.utia.cas.cz/separaty/2010/ZOI/saic-0343316.pdf

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

    Energy Technology Data Exchange (ETDEWEB)

    Simonson, Katherine Mary; Ma, Tian J.

    2009-08-01

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

  18. Method of detecting leakage in nuclear reactor containment vessel

    International Nuclear Information System (INIS)

    Koba, Akitoshi; Goto, Seiichiro.

    1974-01-01

    Object: To permit accurate and prompt detection of leakage of a radioactive substance. Structure: The rate of change of such factors as radiation dose, temperature and pressure in the containment vessel, and each detected rate of change is compared with a reference value. The running cycle of the condensed drain exhausting pump in a drain collecting tank within a predetermined period is detected, and it is also compared with a reference value. These comparisons determine the absence or presence of leakage. (Kamimura, M.)

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

    Science.gov (United States)

    Gong, Maoguo; Yang, Hailun; Zhang, Puzhao

    2017-07-01

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

  20. Volumetric Forest Change Detection Through Vhr Satellite Imagery

    Science.gov (United States)

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

    2016-06-01

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

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

    Science.gov (United States)

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

    1990-01-01

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

  2. HPLC ‘Multi-Analyte’ Detection Method

    Energy Technology Data Exchange (ETDEWEB)

    Dudar, E. [Plant Protection & Soil Conservation Service of Budapest, Budapest (Hungary)

    2009-07-15

    The application of multi-analyte methods for pesticides carrying chromophoric structures by HPLC is described. Details are given on the materials and methods used. Recorded UV spectra of active substances are presented for allowing the verification of purity and the confirmation of substances eluting from the HPLC column. (author)

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

    DEFF Research Database (Denmark)

    Muro, Javier; Canty, Morton; Conradsen, Knut

    2016-01-01

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

  4. Detection of irradiated meats by hydrocarbon method

    International Nuclear Information System (INIS)

    Goto, Michiko; Miyakawa, Hiroyuki; Fujinuma, Kenji; Ozawa, Hideki

    2005-01-01

    Meats, for example, lamb, razorback, wild duck and turkey were irradiated by gamma ray, and the amounts of hydrocarbons formed from fatty acids were measured. Since C 20:0 was found from wild duck and turkey. C 1-18:1 was recommended for internal standard. Good correlation was found between the amount of hydrocarbons and the doses of gamma irradiation. This study shows that such hydrocarbons induced after radiation procedure as C 1,7-16:2 , C 8-17:1 , C 1-14:1 , and C 15:0 may make it possible to detect irradiated lamb, razorback, wild duck and turkey. (author)

  5. Rootkits. Methods of detecting and removing

    International Nuclear Information System (INIS)

    Lagutina, A.M.; Bogdanovich, A.A.; Ivanov, M.A.

    2012-01-01

    The problems connected with the threat of the infection of computer systems by rootkits have been examined, and the methods for providing a guard from this type of malicious software have been analyzed [ru

  6. Knowledge representation methods for early failure detection

    International Nuclear Information System (INIS)

    Scherer, K.P.; Stiller, P.

    1990-01-01

    To supervise technical processes like nuclear power plants, it is very important to detect failure modes in an early stage. In the nuclear research center at Karlsruhe an expert system is developed, embedded in a computer network of autonomous computers, which are used for intelligent prepocessing. Events, process data and actual parameter values are stored in slots of special frames in the knowledge base of the expert system. Both rule based and fact based knowledge representations are employed to generate cause consequence chains of failure states. By on-line surveillance of the reactor process, the slots of the frames are dynamically actualized. Immediately after the evaluation, the inference engine starts in the special domain experts (triggered by metarules from a manager) and detects the correspondend failures or anomaly state. Matching the members of the chain and regarding a catalogue of instructions and messages, what is to do by the operator, future failure states can be estimated and propagation can be prohibited. That means qualitative failure prediction based on cause consequence in the static part of the knowledge base. Also, a time series of physical data can be used to predict on analytical way future process state and to continue such a theoretical propagation with matching the cause consuquence chain

  7. Marine Biotoxins: Occurrence, Toxicity, and Detection Methods

    Science.gov (United States)

    Asakawa, M.

    2017-04-01

    This review summarizes the role of marine organisms as vectors of marine biotoxins, and discusses the need for surveillance to protect public health and ensure the quality of seafood. I Paralytic shellfish poison (PSP) and PSP-bearing organisms-PSP is produced by toxic dinoflagellates species belonging to the genera Alexandrium, Gymnodinium, and Pyrodinium. Traditionally, PSP monitoring programs have only considered filter-feeding molluscs that concentrate these toxic algae, however, increasing attention is now being paid to higher-order predators that carry PSP, such as carnivorous gastropods and crustaceans. II. Tetrodotoxin (TTX) and TTX-bearing organisms - TTX is the most common natural marine toxin that causes food poisonings in Japan, and poses a serious public health risk. TTX was long believed to be present only in pufferfish. However, TTX was detected in the eggs of California newt Taricha torosa in 1964, and since then it has been detected in a wide variety of species belonging to several different phyla. In this study, the main toxic components in the highly toxic ribbon worm Cephalothrix simula and the greater blue-ringed octopus Hapalochlaena lunulata from Japan were purified and analysed.

  8. Polarization sensitive optical coherence tomography detection method

    International Nuclear Information System (INIS)

    Colston, B W; DaSilva, L B; Everett, M J; Featherstone, J D B; Fried, D; Ragadio, J N; Sathyam, U S.

    1999-01-01

    This study demonstrates the potential of polarization sensitive optical coherence tomography (PS-OCT) for non-invasive in vivo detection and characterization of early, incipient caries lesions. PS-OCT generates cross-sectional images of biological tissue while measuring the effect of the tissue on the polarization state of incident light. Clear discrimination between regions of normal and demineralized enamel is first shown in PS-OCT images of bovine enamel blocks containing well-characterized artificial lesions. High-resolution, cross-sectional images of extracted human teeth are then generated that clearly discriminate between the normal and carious regions on both the smooth and occlusal surfaces. Regions of the teeth that appeared to be demineralized in the PS-OCT images were verified using histological thin sections examined under polarized light microscopy. The PS-OCT system discriminates between normal and carious regions by measuring the polarization state of the back-scattered 1310 nm light, which is affected by the state of demineralization of the enamel. Demineralization of enamel increases the scattering coefficient, thus depolarizing the incident light. This study shows that PS-OCT has great potential for the detection, characterization, and monitoring of incipient caries lesions

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

    Science.gov (United States)

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

    2018-03-01

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

  10. Thermal History Devices, Systems For Thermal History Detection, And Methods For Thermal History Detection

    KAUST Repository

    Caraveo Frescas, Jesus Alfonso; Alshareef, Husam N.

    2015-01-01

    Embodiments of the present disclosure include nanowire field-effect transistors, systems for temperature history detection, methods for thermal history detection, a matrix of field effect transistors, and the like.

  11. Thermal History Devices, Systems For Thermal History Detection, And Methods For Thermal History Detection

    KAUST Repository

    Caraveo Frescas, Jesus Alfonso

    2015-05-28

    Embodiments of the present disclosure include nanowire field-effect transistors, systems for temperature history detection, methods for thermal history detection, a matrix of field effect transistors, and the like.

  12. Development and Establishment of Detection Method of Irradiated Foods

    International Nuclear Information System (INIS)

    Byun, Myung Woo; Lee, Ju Woon; Kim, Dong Ho; Jo, Cheo Run; Kim, Jang Ho; Kim, Kyong Su

    2004-12-01

    The present project was related to the development and establishment of the detection techniques for the safety management of gamma-irradiated food and particularly conducted for the establishment of standard detection method for gamma-irradiated dried spices and raw materials, dried meat and fish powder for processed foods, bean paste powder, red pepper paste powder, soy sauce powder, and starch for flavoring ingredients described in 3, 6, 7 section of Korean Food Standard. Since the approvement of gamma-irradiated food items will be enlarged due to the international tendency for gamma-irradiated food, it was concluded that the establishment of detailed detection methods for each food group is not efficient for the enactment and enforcement of related regulations. For this reason, in order to establish the standard detection method, a detection system for gamma-irradiated food suitable for domestic operation was studied using comparative analysis of domestic and foreign research data classified by items and methods and European Standard as a reference. According to the comparative analyses of domestic and foreign research data and regulations of detection for gamma-irradiated food, it was concluded to be desirable that the optimal detection method should be decided after principal detection tests such as physical, chemical, and biological detection methods are established as standard methods and that the specific descriptions such as pre-treatment of raw materials, test methods, and the evaluation of results should be separately prescribed

  13. Development and Establishment of Detection Method of Irradiated Foods

    Energy Technology Data Exchange (ETDEWEB)

    Byun, Myung Woo; Lee, Ju Woon; Kim, Dong Ho; Jo, Cheo Run; Kim, Jang Ho; Kim, Kyong Su

    2004-12-15

    The present project was related to the development and establishment of the detection techniques for the safety management of gamma-irradiated food and particularly conducted for the establishment of standard detection method for gamma-irradiated dried spices and raw materials, dried meat and fish powder for processed foods, bean paste powder, red pepper paste powder, soy sauce powder, and starch for flavoring ingredients described in 3, 6, 7 section of Korean Food Standard. Since the approvement of gamma-irradiated food items will be enlarged due to the international tendency for gamma-irradiated food, it was concluded that the establishment of detailed detection methods for each food group is not efficient for the enactment and enforcement of related regulations. For this reason, in order to establish the standard detection method, a detection system for gamma-irradiated food suitable for domestic operation was studied using comparative analysis of domestic and foreign research data classified by items and methods and European Standard as a reference. According to the comparative analyses of domestic and foreign research data and regulations of detection for gamma-irradiated food, it was concluded to be desirable that the optimal detection method should be decided after principal detection tests such as physical, chemical, and biological detection methods are established as standard methods and that the specific descriptions such as pre-treatment of raw materials, test methods, and the evaluation of results should be separately prescribed.

  14. Development of detection methods for irradiated foods - Detection method for radiolytic products of irradiated foods

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Kyong Su; Kim, Sun Min; Park, Eun Ryong; Lee, Hae Jung; Kim, Eun Ah; Jo, Jung Ok [Chosun University, Kwangju (Korea)

    1999-04-01

    Meat (beef, pork, chicken) and nut (sesame, perilla, black sesame, peanut) were irradiated with /sup 60/Co gamma-ray. A process to detect radiation-induced hydrocarbons and 2-alkylcyclobutanones includes the extraction of fat from meat and nut, separation of hydrocarbons and 2-alkylcyclobutanones with a florisil column and identification of GC/MS methods. Concentrations of the produced hydrocarbons and 2-alkylcyclobutanones tended to increase linearly with the dose levels of irradiation in beef, pork and chicken, while concentrations of radiation-induced hydrocarbons were different individually at the same dose level. In meat, hydrocarbons and 2-alkylcyclobutanones originated from oleic acid were found in a large amount. The concentrations of radiation-induced hydrocarbons were relatively constant during 16 weeks. In nut, hydrocarbons originated from oleic acid and linoleic acid were the major compounds whereas results of perilla was similar to meat. Radiation-induced hydrocarbons were increased linearly with the irradiation dose and remarkably detected at 0.5 kGy and over. 44 refs., 30 figs., 14 tabs. (Author)

  15. A method of failed fuel detection

    International Nuclear Information System (INIS)

    Uchida, Shunsuke; Utamura, Motoaki; Urata, Megumu.

    1976-01-01

    Object: To keep the coolant fed to a fuel assembly at a level below the temperature of existing coolant to detect a failed fuel with high accuracy without using a heater. Structure: When a coolant in a coolant pool disposed at the upper part of a reactor container is fed by a coolant feed system into a fuel assembly through a cap to fill therewith and exchange while forming a boundary layer between said coolant and the existing coolant, the temperature distribution of the feed coolant is heated by fuel rods so that the upper part is low whereas the lower part is high. Then, the lower coolant is upwardly moved by the agitating action and fission products leaked through a failed opening at the lower part of the fuel assembly and easily extracted by the sampling system. (Yoshino, Y.)

  16. Distributed gas detection system and method

    Science.gov (United States)

    Challener, William Albert; Palit, Sabarni; Karp, Jason Harris; Kasten, Ansas Matthias; Choudhury, Niloy

    2017-11-21

    A distributed gas detection system includes one or more hollow core fibers disposed in different locations, one or more solid core fibers optically coupled with the one or more hollow core fibers and configured to receive light of one or more wavelengths from a light source, and an interrogator device configured to receive at least some of the light propagating through the one or more solid core fibers and the one or more hollow core fibers. The interrogator device is configured to identify a location of a presence of a gas-of-interest by examining absorption of at least one of the wavelengths of the light at least one of the hollow core fibers.

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

    Science.gov (United States)

    Bu, Li; Alippi, Cesare; Zhao, Dongbin

    2018-02-01

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

  18. Hardware accelerator design for change detection in smart camera

    Science.gov (United States)

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

    2011-10-01

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

  19. Short-term change detection for UAV video

    Science.gov (United States)

    Saur, Günter; Krüger, Wolfgang

    2012-11-01

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

  20. Theoretical and numerical investigations into the SPRT method for anomaly detection

    Energy Technology Data Exchange (ETDEWEB)

    Schoonewelle, H.; Hagen, T.H.J.J. van der; Hoogenboom, J.E. [Interuniversitair Reactor Inst., Delft (Netherlands)

    1995-11-01

    The sequential probability ratio test developed by Wald is a powerful method of testing an alternative hypothesis against a null hypothesis. This makes the method applicable for anomaly detection. In this paper the method is used to detect a change of the standard deviation of a Gaussian distributed white noise signal. The false alarm probability, the alarm failure probability and the average time to alarm of the method, which are important parameters for anomaly detection, are determined by simulation and compared with theoretical results. Each of the three parameters is presented in dependence of the other two and the ratio of the standard deviation of the anomalous signal and that of the normal signal. Results show that the method is very well suited for anomaly detection. It can detect for example a 50% change in standard deviation within 1 second with a false alarm and alarm failure rate of less than once per month. (author).

  1. Theoretical and numerical investigations into the SPRT method for anomaly detection

    International Nuclear Information System (INIS)

    Schoonewelle, H.; Hagen, T.H.J.J. van der; Hoogenboom, J.E.

    1995-01-01

    The sequential probability ratio test developed by Wald is a powerful method of testing an alternative hypothesis against a null hypothesis. This makes the method applicable for anomaly detection. In this paper the method is used to detect a change of the standard deviation of a Gaussian distributed white noise signal. The false alarm probability, the alarm failure probability and the average time to alarm of the method, which are important parameters for anomaly detection, are determined by simulation and compared with theoretical results. Each of the three parameters is presented in dependence of the other two and the ratio of the standard deviation of the anomalous signal and that of the normal signal. Results show that the method is very well suited for anomaly detection. It can detect for example a 50% change in standard deviation within 1 second with a false alarm and alarm failure rate of less than once per month. (author)

  2. METHODS FOR DETECTING BACTERIA USING POLYMER MATERIALS

    NARCIS (Netherlands)

    Van Grinsven Bart Robert, Nicolaas; Cleij, Thomas

    2017-01-01

    A method for characterizing bacteria includes passing a liquid containing an analyte comprising a first bacteria and a second bacteria over and in contact with a polymer material on a substrate. The polymer material is formulated to bind to the first bacteria, and the first bacteria binds to the

  3. Method of Pentest Synthesis and Vulnerability Detection

    OpenAIRE

    Hahanova Irina Vitalyevna

    2012-01-01

    The structural method for penetration test generation and vulnerability simulation for infrastructure of telecommunication hardwaresoftware information cybernetic systems (CS), focused to protect against unauthorized access the services defined in the system specification by means of penetrating through legal interfaces of component interaction, which have vulnerabilities, is proposed. A protection service infrastructure is created with cybersystem and maintains it during the life cycle, serv...

  4. Method of Detecting Coliform Bacteria from Reflected Light

    Science.gov (United States)

    Vincent, Robert K. (Inventor)

    2014-01-01

    The present invention relates to a method of detecting coliform bacteria in water from reflected light, and also includes devices for the measurement, calculation and transmission of data relating to that method.

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

    Science.gov (United States)

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

    2017-10-01

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

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

    Directory of Open Access Journals (Sweden)

    Shaiyan Keshvari

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

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

    Science.gov (United States)

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

    2018-04-01

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

  8. Localized surface plasmon resonance mercury detection system and methods

    Science.gov (United States)

    James, Jay; Lucas, Donald; Crosby, Jeffrey Scott; Koshland, Catherine P.

    2016-03-22

    A mercury detection system that includes a flow cell having a mercury sensor, a light source and a light detector is provided. The mercury sensor includes a transparent substrate and a submonolayer of mercury absorbing nanoparticles, e.g., gold nanoparticles, on a surface of the substrate. Methods of determining whether mercury is present in a sample using the mercury sensors are also provided. The subject mercury detection systems and methods find use in a variety of different applications, including mercury detecting applications.

  9. A review on automated pavement distress detection methods

    NARCIS (Netherlands)

    Coenen, Tom B.J.; Golroo, Amir

    2017-01-01

    In recent years, extensive research has been conducted on pavement distress detection. A large part of these studies applied automated methods to capture different distresses. In this paper, a literature review on the distresses and related detection methods are presented. This review also includes

  10. Recent developments in analytical detection methods for radiation processed foods

    International Nuclear Information System (INIS)

    Wu Jilan

    1993-01-01

    A short summary of the programmes of 'ADMIT' (FAO/IAEA) and the developments in analytical detection methods for radiation processed foods has been given. It is suggested that for promoting the commercialization of radiation processed foods and controlling its quality, one must pay more attention to the study of analytical detection methods of irradiated food

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

    Directory of Open Access Journals (Sweden)

    Omar E. Mora

    2018-01-01

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

  12. Imaging methods for detection of infectious foci

    International Nuclear Information System (INIS)

    Couret, I.; Rossi, M.; Weinemann, P.; Moretti, J.L.

    1993-01-01

    Several tracers can be used for imaging infection. None is a worthwhile agent for all infectious foci, but each one has preferential applications, depending on its uptake mechanism by the infectious and/or inflammatory focus. Autologous leucocytes labeled in vitro with indium-111 (In-111) or with technetium-99-hexamethylpropyleneamine oxime (Tc-99m HMPAO) were applied with success in the detection of peripheral bone infection, focal vascular graft infection and inflammatory bowel disease. Labeling with In-111 is of interest in chronic bone infection, while labeling with Tc-99m HMPAO gets the advantage of a better dosimetry and imaging. The interest of in vivo labeled leucocytes with a Tc-99m labeled monoclonal antigranulocyte antibody anti-NCA 95 (BW 250/183) was proved in the same principal type of infectious foci than in vitro labeled leucocytes. Sites of chronic infection in the spine and the pelvis, whether active or healed, appear as photopenic defects on both in vitro labeled leucocytes and Tc-99m monoclonal antigranulocyte antibody (BW 250/183) scintigraphies. With gallium-67 results showed a high sensitivity with a low specificity. This tracer demonstrated good performance to delineate foci of infectious spondylitis. In-111 and Tc-99m labeled polyclonal human immunoglobulin (HIG) was applied with success in the assessment of various infectious foci, particularly in chronic sepsis. As labeled leucocytes, labeled HIG showed cold defects in infectious sepsis of the spine. Research in nuclear medicine is very active in the development of more specific tracers of infection, mainly involved in Tc-99m or In-111 labeled chemotactic peptides, antigranulocyte antibody fragments, antibiotic derivatives and interleukins. (authors). 70 refs

  13. Method for detecting trace impurities in gases

    Science.gov (United States)

    Freund, S.M.; Maier, W.B. II; Holland, R.F.; Beattie, W.H.

    A technique for considerably improving the sensitivity and specificity of infrared spectrometry as applied to quantitative determination of trace impurities in various carrier or solvent gases is presented. A gas to be examined for impurities is liquefied and infrared absorption spectra of the liquid are obtained. Spectral simplification and number densities of impurities in the optical path are substantially higher than are obtainable in similar gas-phase analyses. Carbon dioxide impurity (approx. 2 ppM) present in commercial Xe and ppM levels of Freon 12 and vinyl chloride added to liquefied air are used to illustrate the method.

  14. Track detection methods of radium measurements

    International Nuclear Information System (INIS)

    Somogyi, G.

    1986-06-01

    The principles of tack formation and processing including the description of etching and etch-track evaluation for the preferably used plastic track detectors are discussed. Measuring methods to determine 226 Ra activity based either on the mapping of alpha-decaying elements in the complete U-Ra series by alpha-radiography, or on the measurement of uranium alone by neutron induced fissionography, or on the alpha-decay measurement of 222 Rn, the first daughter element of radium, and finally on the measurement of alpha-tracks originating from radium itself, which is separated from its parent nuclides are described in detail. (V.N.)

  15. Detection of greenhouse-gas-induced climatic change

    International Nuclear Information System (INIS)

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

    1992-01-01

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

  16. Vapor generation methods for explosives detection research

    Energy Technology Data Exchange (ETDEWEB)

    Grate, Jay W.; Ewing, Robert G.; Atkinson, David A.

    2012-12-01

    The generation of calibrated vapor samples of explosives compounds remains a challenge due to the low vapor pressures of the explosives, adsorption of explosives on container and tubing walls, and the requirement to manage (typically) multiple temperature zones as the vapor is generated, diluted, and delivered. Methods that have been described to generate vapors can be classified as continuous or pulsed flow vapor generators. Vapor sources for continuous flow generators are typically explosives compounds supported on a solid support, or compounds contained in a permeation or diffusion device. Sources are held at elevated isothermal temperatures. Similar sources can be used for pulsed vapor generators; however, pulsed systems may also use injection of solutions onto heated surfaces with generation of both solvent and explosives vapors, transient peaks from a gas chromatograph, or vapors generated by s programmed thermal desorption. This article reviews vapor generator approaches with emphasis on the method of generating the vapors and on practical aspects of vapor dilution and handling. In addition, a gas chromatographic system with two ovens that is configurable with up to four heating ropes is proposed that could serve as a single integrated platform for explosives vapor generation and device testing. Issues related to standards, calibration, and safety are also discussed.

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

    Science.gov (United States)

    Saur, Günter; Krüger, Wolfgang; Schumann, Arne

    2014-03-01

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

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

    Science.gov (United States)

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

    2017-12-01

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

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

    Science.gov (United States)

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

    2016-11-01

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

  20. System and Method for Multi-Wavelength Optical Signal Detection

    Science.gov (United States)

    McGlone, Thomas D. (Inventor)

    2017-01-01

    The system and method for multi-wavelength optical signal detection enables the detection of optical signal levels significantly below those processed at the discrete circuit level by the use of mixed-signal processing methods implemented with integrated circuit technologies. The present invention is configured to detect and process small signals, which enables the reduction of the optical power required to stimulate detection networks, and lowers the required laser power to make specific measurements. The present invention provides an adaptation of active pixel networks combined with mixed-signal processing methods to provide an integer representation of the received signal as an output. The present invention also provides multi-wavelength laser detection circuits for use in various systems, such as a differential absorption light detection and ranging system.

  1. Reliably detectable flaw size for NDE methods that use calibration

    Science.gov (United States)

    Koshti, Ajay M.

    2017-04-01

    Probability of detection (POD) analysis is used in assessing reliably detectable flaw size in nondestructive evaluation (NDE). MIL-HDBK-1823 and associated mh18232 POD software gives most common methods of POD analysis. In this paper, POD analysis is applied to an NDE method, such as eddy current testing, where calibration is used. NDE calibration standards have known size artificial flaws such as electro-discharge machined (EDM) notches and flat bottom hole (FBH) reflectors which are used to set instrument sensitivity for detection of real flaws. Real flaws such as cracks and crack-like flaws are desired to be detected using these NDE methods. A reliably detectable crack size is required for safe life analysis of fracture critical parts. Therefore, it is important to correlate signal responses from real flaws with signal responses form artificial flaws used in calibration process to determine reliably detectable flaw size.

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

    CSIR Research Space (South Africa)

    Kleynhans, W

    2011-05-01

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

  3. Signal anomaly detection using modified CUSUM [cumulative sum] method

    International Nuclear Information System (INIS)

    Morgenstern, V.; Upadhyaya, B.R.; Benedetti, M.

    1988-01-01

    An important aspect of detection of anomalies in signals is the identification of changes in signal behavior caused by noise, jumps, changes in band-width, sudden pulses and signal bias. A methodology is developed to identify, isolate and characterize these anomalies using a modification of the cumulative sum (CUSUM) approach. The new algorithm performs anomaly detection at three levels and is implemented on a general purpose computer. 7 refs., 4 figs

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

    Directory of Open Access Journals (Sweden)

    Nathan Gold

    2018-01-01

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

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

    Science.gov (United States)

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

    2010-12-01

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

  6. Landsat change detection can aid in water quality monitoring

    Science.gov (United States)

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

    1977-01-01

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

  7. Steam leak detection method in pipeline using histogram analysis

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Se Oh; Jeon, Hyeong Seop; Son, Ki Sung; Chae, Gyung Sun [Saean Engineering Corp, Seoul (Korea, Republic of); Park, Jong Won [Dept. of Information Communications Engineering, Chungnam NationalUnversity, Daejeon (Korea, Republic of)

    2015-10-15

    Leak detection in a pipeline usually involves acoustic emission sensors such as contact type sensors. These contact type sensors pose difficulties for installation and cannot operate in areas having high temperature and radiation. Therefore, recently, many researchers have studied the leak detection phenomenon by using a camera. Leak detection by using a camera has the advantages of long distance monitoring and wide area surveillance. However, the conventional leak detection method by using difference images often mistakes the vibration of a structure for a leak. In this paper, we propose a method for steam leakage detection by using the moving average of difference images and histogram analysis. The proposed method can separate the leakage and the vibration of a structure. The working performance of the proposed method is verified by comparing with experimental results.

  8. Anterior prefrontal involvement in implicit contextual change detection

    Directory of Open Access Journals (Sweden)

    Stefan Pollmann

    2009-10-01

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

  9. Systems and Methods for Automated Water Detection Using Visible Sensors

    Science.gov (United States)

    Rankin, Arturo L. (Inventor); Matthies, Larry H. (Inventor); Bellutta, Paolo (Inventor)

    2016-01-01

    Systems and methods are disclosed that include automated machine vision that can utilize images of scenes captured by a 3D imaging system configured to image light within the visible light spectrum to detect water. One embodiment includes autonomously detecting water bodies within a scene including capturing at least one 3D image of a scene using a sensor system configured to detect visible light and to measure distance from points within the scene to the sensor system, and detecting water within the scene using a processor configured to detect regions within each of the at least one 3D images that possess at least one characteristic indicative of the presence of water.

  10. Rapid radiometric method for detection of Salmonella in foods

    International Nuclear Information System (INIS)

    Stewart, B.J.; Eyles, M.J.; Murrell, W.G.

    1980-01-01

    A radiometric method for the detection of Salmonella in foods has been developed which is based on Salmonella poly H agglutinating serum preventing Salmonella from producing 14CO2 from [14C] dulcitol. The method will detect the presence or absence of Salmonella in a product within 30 h compared to 4 to 5 days by routine culture methods. The method has been evaluated against a routine culture method using 58 samples of food. The overall agreement was 91%. Five samples negative for Salmonella by the routine method were positive by the radiometric method. These may have been false positives. However, the routine method may have failed to detect Salmonella due to the presence of large numbers of lactose-fermenting bacteria which hindered isolation of Salmonella colonies on the selective agar plates

  11. Stroller running: Energetic and kinematic changes across pushing methods.

    Science.gov (United States)

    Alcantara, Ryan S; Wall-Scheffler, Cara M

    2017-01-01

    Running with a stroller provides an opportunity for parents to exercise near their child and counteract health declines experienced during early parenthood. Understanding biomechanical and physiological changes that occur when stroller running is needed to evaluate its health impact, yet the effects of stroller running have not been clearly presented. Here, three commonly used stroller pushing methods were investigated to detect potential changes in energetic cost and lower-limb kinematics. Sixteen individuals (M/F: 10/6) ran at self-selected speeds for 800m under three stroller conditions (2-Hands, 1-Hand, and Push/Chase) and an independent running control. A significant decrease in speed (p = 0.001) and stride length (ppushing method had a significant effect on speed (p = 0.001) and stride length (ppushing technique influences stroller running speed and kinematics. These findings suggest specific fitness effects may be achieved through the implementation of different pushing methods.

  12. [Optimized application of nested PCR method for detection of malaria].

    Science.gov (United States)

    Yao-Guang, Z; Li, J; Zhen-Yu, W; Li, C

    2017-04-28

    Objective To optimize the application of the nested PCR method for the detection of malaria according to the working practice, so as to improve the efficiency of malaria detection. Methods Premixing solution of PCR, internal primers for further amplification and new designed primers that aimed at two Plasmodium ovale subspecies were employed to optimize the reaction system, reaction condition and specific primers of P . ovale on basis of routine nested PCR. Then the specificity and the sensitivity of the optimized method were analyzed. The positive blood samples and examination samples of malaria were detected by the routine nested PCR and the optimized method simultaneously, and the detection results were compared and analyzed. Results The optimized method showed good specificity, and its sensitivity could reach the pg to fg level. The two methods were used to detect the same positive malarial blood samples simultaneously, the results indicated that the PCR products of the two methods had no significant difference, but the non-specific amplification reduced obviously and the detection rates of P . ovale subspecies improved, as well as the total specificity also increased through the use of the optimized method. The actual detection results of 111 cases of malarial blood samples showed that the sensitivity and specificity of the routine nested PCR were 94.57% and 86.96%, respectively, and those of the optimized method were both 93.48%, and there was no statistically significant difference between the two methods in the sensitivity ( P > 0.05), but there was a statistically significant difference between the two methods in the specificity ( P PCR can improve the specificity without reducing the sensitivity on the basis of the routine nested PCR, it also can save the cost and increase the efficiency of malaria detection as less experiment links.

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

    Science.gov (United States)

    Herbranson, Walter T; Jeffers, Jacob S

    2017-07-01

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

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

    Science.gov (United States)

    Pessoa, Luiz; Ungerleider, Leslie G

    2004-05-01

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

  15. Systems and methods for neutron detection using scintillator nano-materials

    Science.gov (United States)

    Letant, Sonia Edith; Wang, Tzu-Fang

    2016-03-08

    In one embodiment, a neutron detector includes a three dimensional matrix, having nanocomposite materials and a substantially transparent film material for suspending the nanocomposite materials, a detector coupled to the three dimensional matrix adapted for detecting a change in the nanocomposite materials, and an analyzer coupled to the detector adapted for analyzing the change detected by the detector. In another embodiment, a method for detecting neutrons includes receiving radiation from a source, converting neutrons in the radiation into alpha particles using converter material, converting the alpha particles into photons using quantum dot emitters, detecting the photons, and analyzing the photons to determine neutrons in the radiation.

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

    Science.gov (United States)

    Wilford, Miko M; Wells, Gary L

    2010-11-01

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

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

    Science.gov (United States)

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

    2017-11-01

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

  18. Comparative study on 4 quantitative detection methods of apoptosis induced by radiation

    International Nuclear Information System (INIS)

    Yang Yepeng; Chen Guanying; Zhou Mei; Shen Qinjian; Shen Lei; Zhu Yingbao

    2004-01-01

    Objective: To reveal the capability of 4 apoptosis-detecting methods to discriminate between apoptosis and necrosis and show their respective advantages and shortcomings through comparison of detected results and analysis of detection mechanism. Methods: Four methods, PI staining-flow cytometric detection (P-F method), TUNEL labeling-flow cytometric detection (T-F method), annexing V-FITC/PI vital staining-flow cytometric detection (A-F method) and Hoechst/PI vital staining-fluorescence microscopic observation (H-O method), were used to determine apoptosis and necrosis in human breast cancer MCF-7 cell line induced by γ-rays. Hydroxycamptothecine and sodium azide were used to induce positive controls of apoptosis and necrosis respectively. Results: All 4 methods showed good time-dependent and dose dependent respondence to apoptosis induced by γ-rays and hydroxycamptothecine. Apoptotic cell ratios and curve slopes obtained from P-F method were minimum and, on the contrary, those from T-F method were maximum among these 4 methods. With A-F method and H-O method, two sets of data, apoptosis and necrosis, could be gained respectively and the data gained from these two methods were close to equal. A-F method and H-O method could distinguish necrosis induced by sodium azide from apoptosis while P-F method and T-F method presented false increase of apoptosis. Conclusions: P-F method and T-F method can not discriminate between apoptosis and necrosis. P-F method is less sensitive but more simple, convenient and economical than T-F method. A-F method and H-O method can distinguish necrosis from apoptosis. A-F method is more costly but more quick and reliable than H-O method. H-O method is economical, practical and morphological changes of cells and nucleus can be observed simultaneously with it. (authors)

  19. Rubella virus detection by ELISA method in exposed radiation workers

    International Nuclear Information System (INIS)

    Wu Jianmei; Zhu Bo; Zhu Youming; Shao Jinhui; Wu Weiping; Han Jinxiang

    2005-01-01

    Objective: A rapid diagnosis method was developed to detect Rubella virus infection in radiation workers. Methods: Modified ELISA method was used to detect the level of lgG and lgM antibodies in 514 in Jinan district. Results: 90.47% of 514 cases was shown to be resistant against Rubella virus; 6.42% were sensitive type; 0.78% belonged to be reinfected. Conclusion: Detection of Rubella virus in exposed radiation workers was imperative, and vaccine against Rubella virus was also needed to eliminate the infection risk. (authors)

  20. Change detection of medical images using dictionary learning techniques and PCA

    Science.gov (United States)

    Nika, Varvara; Babyn, Paul; Zhu, Hongmei

    2014-03-01

    Automatic change detection methods for identifying the changes of serial MR images taken at different times are of great interest to radiologists. The majority of existing change detection methods in medical imaging, and those of brain images in particular, include many preprocessing steps and rely mostly on statistical analysis of MRI scans. Although most methods utilize registration software, tissue classification remains a difficult and overwhelming task. Recently, dictionary learning techniques are used in many areas of image processing, such as image surveillance, face recognition, remote sensing, and medical imaging. In this paper we present the Eigen-Block Change Detection algorithm (EigenBlockCD). It performs local registration and identifies the changes between consecutive MR images of the brain. Blocks of pixels from baseline scan are used to train local dictionaries that are then used to detect changes in the follow-up scan. We use PCA to reduce the dimensionality of the local dictionaries and the redundancy of data. Choosing the appropriate distance measure significantly affects the performance of our algorithm. We examine the differences between L1 and L2 norms as two possible similarity measures in the EigenBlockCD. We show the advantages of L2 norm over L1 norm theoretically and numerically. We also demonstrate the performance of the EigenBlockCD algorithm for detecting changes of MR images and compare our results with those provided in recent literature. Experimental results with both simulated and real MRI scans show that the EigenBlockCD outperforms the previous methods. It detects clinical changes while ignoring the changes due to patient's position and other acquisition artifacts.

  1. Novel method for detecting weak magnetic fields at low frequencies

    Science.gov (United States)

    González-Martínez, S.; Castillo-Torres, J.; Mendoza-Santos, J. C.; Zamorano-Ulloa, R.

    2005-06-01

    A low-level-intensity magnetic field detection system has been designed and developed based on the amplification-selection process of signals. This configuration is also very sensitive to magnetic field changes produced by harmonic-like electrical currents transported in finite-length wires. Experimental and theoretical results of magnetic fields detection as low as 10-9T at 120Hz are also presented with an accuracy of around 13%. The assembled equipment is designed to measure an electromotive force induced in a free-magnetic-core coil in order to recover signals which are previously selected, despite the fact that their intensities are much lower than the environment electromagnetic radiation. The prototype has a signal-to-noise ratio of 60dB. This system also presents the advantage for using it as a portable unit of measurement. The concept and prototype may be applied, for example, as a nondestructive method to analyze any corrosion formation in metallic oil pipelines which are subjected to cathodic protection.

  2. TMTI Task 1.6 Genetic Engineering Methods and Detection

    Energy Technology Data Exchange (ETDEWEB)

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

    2009-12-04

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

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

    International Nuclear Information System (INIS)

    Yun, Hae-Bum; Masri, Sami F

    2009-01-01

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

  4. Dim target detection method based on salient graph fusion

    Science.gov (United States)

    Hu, Ruo-lan; Shen, Yi-yan; Jiang, Jun

    2018-02-01

    Dim target detection is one key problem in digital image processing field. With development of multi-spectrum imaging sensor, it becomes a trend to improve the performance of dim target detection by fusing the information from different spectral images. In this paper, one dim target detection method based on salient graph fusion was proposed. In the method, Gabor filter with multi-direction and contrast filter with multi-scale were combined to construct salient graph from digital image. And then, the maximum salience fusion strategy was designed to fuse the salient graph from different spectral images. Top-hat filter was used to detect dim target from the fusion salient graph. Experimental results show that proposal method improved the probability of target detection and reduced the probability of false alarm on clutter background images.

  5. A Novel Unscheduled Islanding Detection Method for Microgrid

    Directory of Open Access Journals (Sweden)

    Li Hui

    2018-01-01

    Full Text Available Microgrid with its intelligent and flexible control characteristics conform to the trend of sustainable development of electricity, and when the microgrid in the unplanned island state, the successful detection of the island is a prerequisite, energy storage inverter as the key equipment in the microgrid system, island protection is one of the necessary functions. In this paper, an improved islanding detection method based on active frequency drift and q-axis reactive power perturbation is proposed. The method has the advantages of faster detection speed and minor influence on power quality, which makes the energy storage inverter with better output power quality when it works on grid-connected state, and can be detected the islanding state quickly from grid-connected mode to islanded mode. Finally, the validity and superiority of the improved island detection method are verified by simulation experiments.

  6. Change of time methods in quantitative finance

    CERN Document Server

    Swishchuk, Anatoliy

    2016-01-01

    This book is devoted to the history of Change of Time Methods (CTM), the connections of CTM to stochastic volatilities and finance, fundamental aspects of the theory of CTM, basic concepts, and its properties. An emphasis is given on many applications of CTM in financial and energy markets, and the presented numerical examples are based on real data. The change of time method is applied to derive the well-known Black-Scholes formula for European call options, and to derive an explicit option pricing formula for a European call option for a mean-reverting model for commodity prices. Explicit formulas are also derived for variance and volatility swaps for financial markets with a stochastic volatility following a classical and delayed Heston model. The CTM is applied to price financial and energy derivatives for one-factor and multi-factor alpha-stable Levy-based models. Readers should have a basic knowledge of probability and statistics, and some familiarity with stochastic processes, such as Brownian motion, ...

  7. Blind spot detection & passive lane change assist systems

    NARCIS (Netherlands)

    Surovtcev, I.

    2015-01-01

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

  8. Efficient Incorporation of Markov Random Fields in Change Detection

    DEFF Research Database (Denmark)

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

    2009-01-01

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

  9. Real-time change detection in data streams with FPGAs

    International Nuclear Information System (INIS)

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

    2014-01-01

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

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

    Science.gov (United States)

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

    2010-06-01

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

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

    NARCIS (Netherlands)

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

    2007-01-01

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

  12. Scientific Uncertainties in Climate Change Detection and Attribution Studies

    Science.gov (United States)

    Santer, B. D.

    2017-12-01

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

  13. Fast Detection Method in Cooperative Cognitive Radio Networks

    Directory of Open Access Journals (Sweden)

    Zhengyi Li

    2010-01-01

    Full Text Available Cognitive Radio (CR technology improves the utilization of spectrum highly via opportunistic spectrum sharing, which requests fast detection as the spectrum utilization is dynamic. Taking into consideration the characteristic of wireless channels, we propose a fast detection scheme for a cooperative cognitive radio network, which consists of multiple CRs and a central control office. Specifically, each CR makes individual detection decision using the sequential probability ratio test combined with Neyman Pearson detection with respect to a specific observation window length. The proposed method upper bounds the detection delay. In addition, a weighted K out of N fusion rule is also proposed for the central control office to reach fast global decision based on the information collected from CRs, with more weights assigned for CRs with good channel conditions. Simulation results show that the proposed scheme can achieve fast detection while maintaining the detection accuracy.

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

    Science.gov (United States)

    Busch, Niko A

    2013-07-03

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

  15. Current status of the EPR method to detect irradiated food

    International Nuclear Information System (INIS)

    Desrosiers, M.F.

    1996-01-01

    This review gives a brief outline of the principles of the EPR detection method for irradiated foods by food type. For each food type, the scope, limitations and status of the method are given. The extensive reference list aims to include all which define the method, as well as some rarely cited works of historical importance. (author)

  16. Comparative analysis of methods for detecting interacting loci.

    Science.gov (United States)

    Chen, Li; Yu, Guoqiang; Langefeld, Carl D; Miller, David J; Guy, Richard T; Raghuram, Jayaram; Yuan, Xiguo; Herrington, David M; Wang, Yue

    2011-07-05

    Interactions among genetic loci are believed to play an important role in disease risk. While many methods have been proposed for detecting such interactions, their relative performance remains largely unclear, mainly because different data sources, detection performance criteria, and experimental protocols were used in the papers introducing these methods and in subsequent studies. Moreover, there have been very few studies strictly focused on comparison of existing methods. Given the importance of detecting gene-gene and gene-environment interactions, a rigorous, comprehensive comparison of performance and limitations of available interaction detection methods is warranted. We report a comparison of eight representative methods, of which seven were specifically designed to detect interactions among single nucleotide polymorphisms (SNPs), with the last a popular main-effect testing method used as a baseline for performance evaluation. The selected methods, multifactor dimensionality reduction (MDR), full interaction model (FIM), information gain (IG), Bayesian epistasis association mapping (BEAM), SNP harvester (SH), maximum entropy conditional probability modeling (MECPM), logistic regression with an interaction term (LRIT), and logistic regression (LR) were compared on a large number of simulated data sets, each, consistent with complex disease models, embedding multiple sets of interacting SNPs, under different interaction models. The assessment criteria included several relevant detection power measures, family-wise type I error rate, and computational complexity. There are several important results from this study. First, while some SNPs in interactions with strong effects are successfully detected, most of the methods miss many interacting SNPs at an acceptable rate of false positives. In this study, the best-performing method was MECPM. Second, the statistical significance assessment criteria, used by some of the methods to control the type I error rate

  17. Comparative analysis of methods for detecting interacting loci

    Directory of Open Access Journals (Sweden)

    Yuan Xiguo

    2011-07-01

    Full Text Available Abstract Background Interactions among genetic loci are believed to play an important role in disease risk. While many methods have been proposed for detecting such interactions, their relative performance remains largely unclear, mainly because different data sources, detection performance criteria, and experimental protocols were used in the papers introducing these methods and in subsequent studies. Moreover, there have been very few studies strictly focused on comparison of existing methods. Given the importance of detecting gene-gene and gene-environment interactions, a rigorous, comprehensive comparison of performance and limitations of available interaction detection methods is warranted. Results We report a comparison of eight representative methods, of which seven were specifically designed to detect interactions among single nucleotide polymorphisms (SNPs, with the last a popular main-effect testing method used as a baseline for performance evaluation. The selected methods, multifactor dimensionality reduction (MDR, full interaction model (FIM, information gain (IG, Bayesian epistasis association mapping (BEAM, SNP harvester (SH, maximum entropy conditional probability modeling (MECPM, logistic regression with an interaction term (LRIT, and logistic regression (LR were compared on a large number of simulated data sets, each, consistent with complex disease models, embedding multiple sets of interacting SNPs, under different interaction models. The assessment criteria included several relevant detection power measures, family-wise type I error rate, and computational complexity. There are several important results from this study. First, while some SNPs in interactions with strong effects are successfully detected, most of the methods miss many interacting SNPs at an acceptable rate of false positives. In this study, the best-performing method was MECPM. Second, the statistical significance assessment criteria, used by some of the

  18. Method for the detection of Salmonella enterica serovar Enteritidis

    Science.gov (United States)

    Agron, Peter G.; Andersen, Gary L.; Walker, Richard L.

    2008-10-28

    Described herein is the identification of a novel Salmonella enterica serovar Enteritidis locus that serves as a marker for DNA-based identification of this bacterium. In addition, three primer pairs derived from this locus that may be used in a nucleotide detection method to detect the presence of the bacterium are also disclosed herein.

  19. DNA based methods used for characterization and detection of food ...

    African Journals Online (AJOL)

    Detection of food borne pathogen is of outmost importance in the food industries and related agencies. For the last few decades conventional methods were used to detect food borne pathogens based on phenotypic characters. At the advent of complementary base pairing and amplification of DNA, the diagnosis of food ...

  20. DNA based methods used for characterization and detection of food ...

    African Journals Online (AJOL)

    STORAGESEVER

    2009-05-04

    May 4, 2009 ... selective medium followed by plating in differential agar medium ... result. Biochemical and immunological methods for the detection require substantial amount of pure culture whereas .... biotin (chemiluminescent) probes are detected visually. It ..... are also gathering special attention due to their covalent.

  1. Molecular techniques: An overview of methods for the detection of ...

    African Journals Online (AJOL)

    Several DNA molecular markers are now available for use in surveillance and investigation of food-borne outbreaks that were previously difficult to detect. The results from several sources of literature indicate substantially different degrees of sensitivities between conventional detection methods and molecular-based ...

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

    Science.gov (United States)

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

    2018-03-01

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

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

    Science.gov (United States)

    Osorio, Ivan; Manly, B F J

    2015-08-01

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

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

    Directory of Open Access Journals (Sweden)

    Komeil Rokni

    2014-05-01

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

  5. Region-Based Building Rooftop Extraction and Change Detection

    Science.gov (United States)

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

    2017-09-01

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

  6. REGION-BASED BUILDING ROOFTOP EXTRACTION AND CHANGE DETECTION

    Directory of Open Access Journals (Sweden)

    J. Tian

    2017-09-01

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

  7. Concrete deterioration: detection by ultrasonic pulse velocity method

    International Nuclear Information System (INIS)

    Sutan, N.M.; Jaafar, M.S.; Hamdan, S.

    2003-01-01

    Tests were performed to evaluate the feasibility of using Ultrasonic Pulse Velocity Method (UPVM) in detecting defect and determining its depth during the early age concrete. Five reinforced concrete (RC) slabs of grade 30, 40 and 50 specimens at day 3, 7,14 and 28 with a fabricated void at a known location were used. The results obtained were compared to determine the accuracy of the method hence the effectiveness of the method with different strength and as the concrete matures. This method detects defects in specimens during the early age The accuracy varies with concrete strength and as the concrete mature. The test results indicate the method can be used to assess the in-situ properties of concrete or for quality control on site. The method showed better accuracy with stronger concrete detects defects with the accuracy ranging from 55.75-99.62% from day 3-28 (full strength) respectively. (author)

  8. A PCA-Based Change Detection Framework for Multidimensional Data Streams

    KAUST Repository

    Qahtan, Abdulhakim Ali Ali

    2015-08-10

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

  9. Novel inversion method for land mine imaging and detection

    Science.gov (United States)

    Sindoni, Orazio I.; Cohoon, David K.

    2000-08-01

    We have developed, using both partial differential equation approaches and integral equation formulations, a precise method to invert acoustic or electromagnetic scattering data from macroscopic concealed objects. Our approach makes use of the ideas associated with our exact solution of partial differential equations as described in our paper where we were able to collapse the number of equations by elimination of transcendentals therefore preserving the absolute mathematical precision inherent in the partial differential equation formulation. Our mathematical method, as a consequence, has not encountered the traditional loss of precision when inverting the scattered data. The unrestricted wavelength range allows us to penetrate any material which may surround the object and differentiate between the object and the media. For this reason we have applied our inversion scheme to landmine detection as we can penetrate and differentiate under both wet and dry conditions. Also, we are able to account, under certain conditions, for dielectric nonlinearities of material in the concealed object. Therefore, we are able to build in density dependent false colors a 3D grid representative of both the media and of the embedded object including the internal structure of the object. We have surveyed the literature on the subject of recovery of physical location of concealed objects and we have found that most of the present applications such as land mine detection, and we have found that most of the present applications have shortcomings due to the physical changes that are present in the surrounding media or the discontinuities of physical properties of the media. For all the above reasons we believe that we may have the most versatile and mathematically precise approach to the solution of this problem.

  10. Thermoelectric SQUID method for the detection of segregations

    Science.gov (United States)

    Hinken, Johann H.; Tavrin, Yury

    2000-05-01

    Aero engine turbine discs are most critical parts. Material inhomogeneities can cause disc fractures during the flight with fatal air disasters. Nondestructive testing (NDT) of the discs in various machining steps is necessary and performed as well as possible. Conventional NDT methods, however, like eddy current testing and ultrasonic testing have unacceptable limits. For example, subsurface segregations often cannot be detected directly but only indirectly in such cases when cracks already have developed from them. This may be too late. A new NDT method, which we call the Thermoelectric SQUID Method, has been developed. It allows for the detection of metallic inclusions within non-ferromagnetic metallic base material. This paper describes the results of a feasibility study on aero engine turbine discs made from Inconel® 718. These contained segregations that had been detected before by anodic etching. With the Thermoelectric SQUID Method, these segregations were detected again, and further segregations below the surfaces have been found, which had not been detected before. For this new NDT method the disc material is quasi-transparent. The Thermoelectric SQUID Method is also useful to detect distributed and localized inhomogeneities in pure metals like niobium sheets for particle accelerators.

  11. Detection of irradiated food - methods and routine applications

    International Nuclear Information System (INIS)

    Schreiber, G.A.; Helle, N.; Boegl, K.W.

    1993-01-01

    Irradiation of food for the purposes of extension of shelf life, control of microbial load, reduction of pathogenic microorganisms and disinfection is regarded by many consumers with suspicion. One reason is the lack of methods within food-controlling laboratories which can detect irradiation treatment and which are applied to control correct labelling. This review describes the potential of various methods to reveal irradiation treatment. Special emphasis is given to the three most successful methods, thermoluminescence, electron spin resonance spectroscopy and detection of volatiles. The possibilities and limitations of applying the methods in routine control are discussed. (author)

  12. Dynamic baseline detection method for power data network service

    Science.gov (United States)

    Chen, Wei

    2017-08-01

    This paper proposes a dynamic baseline Traffic detection Method which is based on the historical traffic data for the Power data network. The method uses Cisco's NetFlow acquisition tool to collect the original historical traffic data from network element at fixed intervals. This method uses three dimensions information including the communication port, time, traffic (number of bytes or number of packets) t. By filtering, removing the deviation value, calculating the dynamic baseline value, comparing the actual value with the baseline value, the method can detect whether the current network traffic is abnormal.

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

    Science.gov (United States)

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

    2018-04-01

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

  14. Evaluation of primary coolant leaks and assessment of detection methods

    International Nuclear Information System (INIS)

    Cassette, P.; Giroux, C.; Roche, H.; Seveon, J.J.

    1984-11-01

    A review of French PWR situation concerning primary coolant leaks is presented, including a description of operating technical specifications, of the collecting system of primary coolant leakage into the containment and of the detection methods. It is mainly based on a compilation over three years, 1981 to 1983, of almost all occurred leaks, their natures, causes, consequences and methods used for their detection. By analysing these data it is possible to evaluate the efficiency of the primary coolant leak detection system and the problems raised by the compliance with the criteria defined in the operating technical specifications

  15. Evaluation of primary coolant leaks and assessment of detection methods

    International Nuclear Information System (INIS)

    Cassette, P.; Giroux, C.; Roche, H.; Seveon, J.J.

    1986-01-01

    A review of the French PWR situation concerning primary coolant leaks is presented, including a description of operating technical specifications, of the collecting system of primary coolant leakage into the containment and of the detection methods. It is mainly based on a compilation over three years, 1981 to 1983, of almost all actual leaks, their natures, causes, consequences and methods used for their detection. By analysing these data it is possible to evaluate the efficiency of the primary coolant leak detection system and the problems raised by compliance with the criteria defined in the operating technical specifications

  16. Detection of irradiated foods by the DEFT/APC method

    International Nuclear Information System (INIS)

    Yuecel, P. K.; Koeseoglu, T.; Halkman, H. B. D.

    2009-01-01

    Irradiation technology is used to prevent the spoilage losses and to improve the hygienic quality of foods. Appropriate techniques for the detection of irradiated foods are needed to guarantee the proper consumer information and to facilitate the trade of irradiated foods. The characteristics of the microbial population of irradiated foods have been used for developing detection methods for irradiated foods. This microbiological method is based on the comparison of an aerobic plate count (APC) with a count obtained with the direct epifluorescent filter technique (DEFT) for the detection of irradiation of foodstuffs.

  17. Advances in Methods for Assessing Longitudinal Change

    Science.gov (United States)

    Grimm, Kevin J.; Mazza, Gina L.; Mazzocco, Michèle M. M.

    2016-01-01

    Educational research aims to understand how and why students change over time. With its emphasis on within-person change, latent change score models provide educational researchers with a more general and flexible framework for testing nuanced hypotheses regarding within-person change and between-person differences in within-person change. Models…

  18. Detecting Android Malwares with High-Efficient Hybrid Analyzing Methods

    Directory of Open Access Journals (Sweden)

    Yu Liu

    2018-01-01

    Full Text Available In order to tackle the security issues caused by malwares of Android OS, we proposed a high-efficient hybrid-detecting scheme for Android malwares. Our scheme employed different analyzing methods (static and dynamic methods to construct a flexible detecting scheme. In this paper, we proposed some detecting techniques such as Com+ feature based on traditional Permission and API call features to improve the performance of static detection. The collapsing issue of traditional function call graph-based malware detection was also avoided, as we adopted feature selection and clustering method to unify function call graph features of various dimensions into same dimension. In order to verify the performance of our scheme, we built an open-access malware dataset in our experiments. The experimental results showed that the suggested scheme achieved high malware-detecting accuracy, and the scheme could be used to establish Android malware-detecting cloud services, which can automatically adopt high-efficiency analyzing methods according to the properties of the Android applications.

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

    DEFF Research Database (Denmark)

    Willersrud, Anders; Imsland, Lars; Blanke, Mogens

    2015-01-01

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

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

    Science.gov (United States)

    Conci, Markus; Müller, Hermann J

    2014-01-01

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

  1. Global scene layout modulates contextual learning in change detection

    Directory of Open Access Journals (Sweden)

    Markus eConci

    2014-02-01

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

  2. 3D change detection at street level using mobile laser scanning point clouds and terrestrial images

    Science.gov (United States)

    Qin, Rongjun; Gruen, Armin

    2014-04-01

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

  3. A statistical method (cross-validation) for bone loss region detection after spaceflight

    Science.gov (United States)

    Zhao, Qian; Li, Wenjun; Li, Caixia; Chu, Philip W.; Kornak, John; Lang, Thomas F.

    2010-01-01

    Astronauts experience bone loss after the long spaceflight missions. Identifying specific regions that undergo the greatest losses (e.g. the proximal femur) could reveal information about the processes of bone loss in disuse and disease. Methods for detecting such regions, however, remains an open problem. This paper focuses on statistical methods to detect such regions. We perform statistical parametric mapping to get t-maps of changes in images, and propose a new cross-validation method to select an optimum suprathreshold for forming clusters of pixels. Once these candidate clusters are formed, we use permutation testing of longitudinal labels to derive significant changes. PMID:20632144

  4. Musical Tone Law Method for the Structural Damage Detection

    Directory of Open Access Journals (Sweden)

    Weisong Yang

    2017-01-01

    Full Text Available Damage detection tests of inclined cables, steel pipes, spherical shells, and an actual cable-stayed bridge were conducted based on the proposed musical tone law method. The results show that the musical tone law method could be used in the damage detection of isotropic material structures with simple shape, like cables, pipes, plates, and shells. Having distinct spectral lines like a comb with a certain interval distribution rule is the main characteristic of the music tone law. Damage detection baseline could be established by quantizing the fitting relationship between modal orders and the corresponding frequency values. The main advantage of this method is that it could be used in the structural damage detection without vibration information of an intact structure as a reference.

  5. Support system and method for detecting neurodegenerative disorder

    DEFF Research Database (Denmark)

    2013-01-01

    The present invention relates to a system and a method for detection of abnormal motor activity during REM sleep, and further to systems and method for assisting in detecting neurodegenerative disorders such as Parkinson's. One embodiment relates to a method for detection of abnormal motor activity...... during REM sleep comprising the steps of: performing polysomnographic recordings of a sleeping subject, thereby obtaining one or more electromyography (EMG) derivations, preferably surface EMG recordings, and one or more EEG derivations, and/or one or more electrooculargraphy (EOG) derivations, detecting...... one or more REM sleep stages, preferably based on the one or more EEG and/or EOG derivations, determining the level of muscle activity during the one or more REM sleep stages based on the one or more EMG derivations, wherein a subject having an increased level of muscle activity during REM sleep...

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

    Science.gov (United States)

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

    2016-01-01

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

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

    Science.gov (United States)

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

    2016-01-01

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

  8. Lipid droplet detection by the cavity perturbation method

    Energy Technology Data Exchange (ETDEWEB)

    Blakey, R T; Mason, A; Al-Shamma' a, A I [School of Built Environment, Liverpool John Moores University, Liverpool L3 3AF (United Kingdom); Rolph, C E [School of Pharmacy and Biomedical Sciences, University of Central Lancashire, Preston PR1 2HE (United Kingdom); Bond, G, E-mail: r.t.blakey@2010.ljmu.ac.uk [School of Forensic and Investigative Sciences, University of Central Lancashire, Preston PR1 2HE (United Kingdom)

    2011-08-17

    There are currently no point-of-care diagnosis strategies available to indicate the presence of neoplasmic growth. This research aims to develop a novel diagnostic strategy based on detecting TAG accumulation in cells. This element of the research is a preliminary experiment to prove the concept of detecting TAG lipid droplets in YEPD media. It was found that a change in mono-unsaturated concentration can be detected by the frequency shift in a resonant cavity. The dielectric constant of TAG vegetable oils was calculated at 2.34-2.39. It was also found that concentrations of lipid droplet can be differentiated up to 5% (v/v).

  9. Research on pipeline leak detection method based on pressure and dynamic pressure

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Likun; Xiong, Min; Zhao, Jinyun; Wang, Hongchao; Xu, Bin; Yu, DongLiang; Sun, Yi; Cai, Yongjun [RnD center of PetroChina Pipeline Company, Langfang, Hebei, (China)

    2010-07-01

    Pipeline leakages are very frequent and need to be detected as fast as possible to avoid safety and environment issues. Many leakage detection processes have been developed. Acoustic wave methods based on static pressure and dynamic pressure are both used for pipeline leakage detection. This study investigated a new pipeline leak detection method based on joint pressure and dynamic pressure. A dynamic pressure transmitter was designed based on a piezoelectric dynamic pressure sensor. The study showed that the dynamic pressure signal should be used for pipeline leak detection with a quick-change in pipeline internal pressure, while the static pressure signal provides better results with a slow-change of pipeline internal pressure. The in-field results showed that the location error of dynamic pressure is reduced to 80 m with a leakage ratio of 0.6 % pipeline throughput.

  10. A method for detecting fungal contaminants in wall cavities.

    Science.gov (United States)

    Spurgeon, Joe C

    2003-01-01

    This article describes a practical method for detecting the presence of both fungal spores and culturable fungi in wall cavities. Culturable fungi were collected in 25 mm cassettes containing 0.8 microm mixed cellulose ester filters using aggressive sampling conditions. Both culturable fungi and fungal spores were collected in modified slotted-disk cassettes. The sample volume was 4 L. The filters were examined microscopically and dilution plated onto multiple culture media. Collecting airborne samples in filter cassettes was an effective method for assessing wall cavities for fungal contaminants, especially because this method allowed the sample to be analyzed by both microscopy and culture media. Assessment criteria were developed that allowed the sample results to be used to classify wall cavities as either uncontaminated or contaminated. As a criterion, wall cavities with concentrations of culturable fungi below the limit of detection (LOD) were classified as uncontaminated, whereas those cavities with detectable concentrations of culturable fungi were classified as contaminated. A total of 150 wall cavities was sampled as part of a field project. The concentrations of culturable fungi were below the LOD in 34% of the samples, whereas Aspergillus and/or Penicillium were the only fungal genera detected in 69% of the samples in which culturable fungi were detected. Spore counting resulted in the detection of Stachybotrys-like spores in 25% of the samples that were analyzed, whereas Stachybotrys chartarum colonies were only detected on 2% of malt extract agar plates and on 6% of corn meal agar plates.

  11. Automatic change detection to facial expressions in adolescents

    DEFF Research Database (Denmark)

    Liu, Tongran; Xiao, Tong; Jiannong, Shi

    2016-01-01

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

  12. Soybean allergen detection methods--a comparison study

    DEFF Research Database (Denmark)

    Pedersen, M. Højgaard; Holzhauser, T.; Bisson, C.

    2008-01-01

    Soybean containing products are widely consumed, thus reliable methods for detection of soy in foods are needed in order to make appropriate risk assessment studies to adequately protect soy allergic patients. Six methods were compared using eight food products with a declared content of soy...

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

    Science.gov (United States)

    Nika, Varvara; Babyn, Paul; Zhu, Hongmei

    2014-07-01

    Automatic change detection methods for identifying the changes of serial MR images taken at different times are of great interest to radiologists. The majority of existing change detection methods in medical imaging, and those of brain images in particular, include many preprocessing steps and rely mostly on statistical analysis of magnetic resonance imaging (MRI) scans. Although most methods utilize registration software, tissue classification remains a difficult and overwhelming task. Recently, dictionary learning techniques are being used in many areas of image processing, such as image surveillance, face recognition, remote sensing, and medical imaging. We present an improved version of the EigenBlockCD algorithm, named the EigenBlockCD-2. The EigenBlockCD-2 algorithm performs an initial global registration and identifies the changes between serial MR images of the brain. Blocks of pixels from a baseline scan are used to train local dictionaries to detect changes in the follow-up scan. We use PCA to reduce the dimensionality of the local dictionaries and the redundancy of data. Choosing the appropriate distance measure significantly affects the performance of our algorithm. We examine the differences between [Formula: see text] and [Formula: see text] norms as two possible similarity measures in the improved EigenBlockCD-2 algorithm. We show the advantages of the [Formula: see text] norm over the [Formula: see text] norm both theoretically and numerically. We also demonstrate the performance of the new EigenBlockCD-2 algorithm for detecting changes of MR images and compare our results with those provided in the recent literature. Experimental results with both simulated and real MRI scans show that our improved EigenBlockCD-2 algorithm outperforms the previous methods. It detects clinical changes while ignoring the changes due to the patient's position and other acquisition artifacts.

  14. Segment-based change detection for polarimetric SAR data

    DEFF Research Database (Denmark)

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

    2006-01-01

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

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

    Directory of Open Access Journals (Sweden)

    M. Ehlers

    2012-08-01

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

  16. Methods for detection of GMOs in food and feed.

    Science.gov (United States)

    Marmiroli, Nelson; Maestri, Elena; Gullì, Mariolina; Malcevschi, Alessio; Peano, Clelia; Bordoni, Roberta; De Bellis, Gianluca

    2008-10-01

    This paper reviews aspects relevant to detection and quantification of genetically modified (GM) material within the feed/food chain. The GM crop regulatory framework at the international level is evaluated with reference to traceability and labelling. Current analytical methods for the detection, identification, and quantification of transgenic DNA in food and feed are reviewed. These methods include quantitative real-time PCR, multiplex PCR, and multiplex real-time PCR. Particular attention is paid to methods able to identify multiple GM events in a single reaction and to the development of microdevices and microsensors, though they have not been fully validated for application.

  17. A structural framework for anomalous change detection and characterization

    Energy Technology Data Exchange (ETDEWEB)

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

    2009-01-01

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

  18. Happy Face Superiority Effect in Change Detection Paradigm

    Directory of Open Access Journals (Sweden)

    Domagoj Švegar

    2013-09-01

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

  19. Distance Based Method for Outlier Detection of Body Sensor Networks

    Directory of Open Access Journals (Sweden)

    Haibin Zhang

    2016-01-01

    Full Text Available We propose a distance based method for the outlier detection of body sensor networks. Firstly, we use a Kernel Density Estimation (KDE to calculate the probability of the distance to k nearest neighbors for diagnosed data. If the probability is less than a threshold, and the distance of this data to its left and right neighbors is greater than a pre-defined value, the diagnosed data is decided as an outlier. Further, we formalize a sliding window based method to improve the outlier detection performance. Finally, to estimate the KDE by training sensor readings with errors, we introduce a Hidden Markov Model (HMM based method to estimate the most probable ground truth values which have the maximum probability to produce the training data. Simulation results show that the proposed method possesses a good detection accuracy with a low false alarm rate.

  20. Method of detecting genetic deletions identified with chromosomal abnormalities

    Energy Technology Data Exchange (ETDEWEB)

    Gray, Joe W; Pinkel, Daniel; Tkachuk, Douglas

    2013-11-26

    Methods and compositions for staining based upon nucleic acid sequence that employ nucleic acid probes are provided. Said methods produce staining patterns that can be tailored for specific cytogenetic analyzes. Said probes are appropriate for in situ hybridization and stain both interphase and metaphase chromosomal material with reliable signals. The nucleic acids probes are typically of a complexity greater tha 50 kb, the complexity depending upon the cytogenetic application. Methods and reagents are provided for the detection of genetic rearrangements. Probes and test kits are provided for use in detecting genetic rearrangements, particlularly for use in tumor cytogenetics, in the detection of disease related loci, specifically cancer, such as chronic myelogenous leukemia (CML) and for biological dosimetry. Methods and reagents are described for cytogenetic research, for the differentiation of cytogenetically similar ut genetically different diseases, and for many prognostic and diagnostic applications.

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

    Science.gov (United States)

    Johnson, P; Moriarty, J; Peskir, G

    2017-08-13

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

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

    Science.gov (United States)

    2014-05-09

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

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

    OpenAIRE

    Stephen Bunmi Ogungbenro; Tobi Eniolu Morakinyo

    2014-01-01

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

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

    Science.gov (United States)

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

    2017-10-01

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

  5. LANDSAT-8 OPERATIONAL LAND IMAGER CHANGE DETECTION ANALYSIS

    Directory of Open Access Journals (Sweden)

    W. Pervez

    2017-05-01

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

  6. COMPARISON OF FOUR METHODS TO DETECT ADVERSE EVENTS IN HOSPITAL

    Directory of Open Access Journals (Sweden)

    Inge Dhamanti

    2015-09-01

    Full Text Available AbstrakDeteksi terjadinya kejadian yang tidak diharapkan (KTD telah menjadi salah satu tantangan dalam keselamatan pasien oleh karena itu metode untuk mendeteksi terjadinya KTD sangatlah penting untuk meningkatkan keselamatan pasien. Tujuan dari artikel ini adalah untuk membandingkan kelebihan dan kekurangan dari beberapa metode untuk mendeteksi terjadinya KTD di rumah sakit, meliputi review rekam medis, pelaporan insiden secara mandiri, teknologi informasi, dan pelaporan oleh pasien. Studi ini merupakan kajian literatur untuk membandingkan dan menganalisa metode terbaik untuk mendeteksi KTD yang dapat diimplementasikan oleh rumah sakit. Semua dari empat metode telah terbukti mampu untuk mendeteksi terjadinya KTD di rumah sakit, tetapi masing-masing metode mempunyai kelebihan dan kekurangan yang perlu diatasi. Tidak ada satu metode terbaik yang akan memberikan hasil terbaik untuk mendeteksi KTD di rumah sakit. Sehingga untuk mendeteksi lebih banyak KTD yang seharusnya dapat dicegah, atau KTD yang telah terjadi, rumah sakit seharusnya mengkombinasikan lebih dari satu metode untuk mendeteksi, karena masing-masing metode mempunyai sensitivitas berbeda-beda.AbstractDetecting adverse events has become one of the challenges in patient safety thus methods to detect adverse events become critical for improving patient safety. The purpose of this paper is to compare the strengths and weaknesses of several methods of identifying adverse events in hospital, including medical records reviews, self-reported incidents, information technology, and patient self-reports. This study is a literature review to compared and analyzed to determine the best method implemented by the hospital. All of four methods have been proved in their ability in detecting adverse events in hospitals, but each method had strengths and limitations to be overcome. There is no ‘best’ single method that will give the best results for adverse events detection in hospital. Thus to

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

    Directory of Open Access Journals (Sweden)

    CHEN Liyan

    2018-03-01

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

  8. Detection of forced oscillations in power systems with multichannel methods

    Energy Technology Data Exchange (ETDEWEB)

    Follum, James D. [Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)

    2015-09-30

    The increasing availability of high fidelity, geographically dispersed measurements in power systems improves the ability of researchers and engineers to study dynamic behaviors in the grid. One such behavior that is garnering increased attention is the presence of forced oscillations. Power system engineers are interested in forced oscillations because they are often symptomatic of the malfunction or misoperation of equipment. Though the resulting oscillation is not always large in amplitude, the root cause may be serious. In this report, multi-channel forced oscillation detection methods are developed. These methods leverage previously developed detection approaches based on the periodogram and spectral-coherence. Making use of geographically distributed channels of data is shown to improved detection performance and shorten the delay before an oscillation can be detected in the online environment. Results from simulated and measured power system data are presented.

  9. Method of Multiobject Detecting and Tracking Based on DM643

    Directory of Open Access Journals (Sweden)

    Yitao Liang

    2014-01-01

    Full Text Available The technology of moving objects detection has become an important research subject for its extensive application prospect. In this paper, it is presented that interframe difference algorithm and background difference algorithm are combined to update the background. The algorithm can deal with the flaw of background difference algorithm. The mathematical morphology method is employed to denoise the image, which may be helpful to improve the accuracy of the detection. The Pyramid algorithm is used to compress each frame data of video sequence. Then, the detecting and tracking of moving objects are tested on the hardware platform (DM643 and the software frame (RF5. The running speed is about 3 times faster than before. The result shows that the accuracy demanded by the detection is met. This method can provide a useful reference for similar application.

  10. A high-throughput multiplex method adapted for GMO detection.

    Science.gov (United States)

    Chaouachi, Maher; Chupeau, Gaëlle; Berard, Aurélie; McKhann, Heather; Romaniuk, Marcel; Giancola, Sandra; Laval, Valérie; Bertheau, Yves; Brunel, Dominique

    2008-12-24

    A high-throughput multiplex assay for the detection of genetically modified organisms (GMO) was developed on the basis of the existing SNPlex method designed for SNP genotyping. This SNPlex assay allows the simultaneous detection of up to 48 short DNA sequences (approximately 70 bp; "signature sequences") from taxa endogenous reference genes, from GMO constructions, screening targets, construct-specific, and event-specific targets, and finally from donor organisms. This assay avoids certain shortcomings of multiplex PCR-based methods already in widespread use for GMO detection. The assay demonstrated high specificity and sensitivity. The results suggest that this assay is reliable, flexible, and cost- and time-effective for high-throughput GMO detection.

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

    Directory of Open Access Journals (Sweden)

    Borgert Jörn

    2011-06-01

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

  12. Techniques for land use change detection using Landsat imagery

    Science.gov (United States)

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

    1977-01-01

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

  13. INCREMENTAL PRINCIPAL COMPONENT ANALYSIS BASED OUTLIER DETECTION METHODS FOR SPATIOTEMPORAL DATA STREAMS

    Directory of Open Access Journals (Sweden)

    A. Bhushan

    2015-07-01

    Full Text Available In this paper, we address outliers in spatiotemporal data streams obtained from sensors placed across geographically distributed locations. Outliers may appear in such sensor data due to various reasons such as instrumental error and environmental change. Real-time detection of these outliers is essential to prevent propagation of errors in subsequent analyses and results. Incremental Principal Component Analysis (IPCA is one possible approach for detecting outliers in such type of spatiotemporal data streams. IPCA has been widely used in many real-time applications such as credit card fraud detection, pattern recognition, and image analysis. However, the suitability of applying IPCA for outlier detection in spatiotemporal data streams is unknown and needs to be investigated. To fill this research gap, this paper contributes by presenting two new IPCA-based outlier detection methods and performing a comparative analysis with the existing IPCA-based outlier detection methods to assess their suitability for spatiotemporal sensor data streams.

  14. Effects of Feature Extraction and Classification Methods on Cyberbully Detection

    OpenAIRE

    ÖZEL, Selma Ayşe; SARAÇ, Esra

    2016-01-01

    Cyberbullying is defined as an aggressive, intentional action against a defenseless person by using the Internet, or other electronic contents. Researchers have found that many of the bullying cases have tragically ended in suicides; hence automatic detection of cyberbullying has become important. In this study we show the effects of feature extraction, feature selection, and classification methods that are used, on the performance of automatic detection of cyberbullying. To perform the exper...

  15. Tumor specific glycoproteins and method for detecting tumorigenic cancers

    International Nuclear Information System (INIS)

    Davidson, E.A.; Bolmer, S.D.

    1981-01-01

    The detection of tumour specific glycoproteins (TSGP) in human sera often indicates the presence of a malignant tumour in a patient. The distinguishing characteristics of TSGP isolated from the blood sera of cancer patients are described in detail together with methods of TSGP isolation and purification. Details are also given of radioimmunoassay techniques capable of detecting very low levels of serum TSGP with high specificity. (U.K.)

  16. Method for radar detection of persons wearing wires

    OpenAIRE

    Fox, William P.

    2014-01-01

    8,730,098 B1 Methods are described for radar detection of persons wearing wires using radar spectra data including the vertical polarization (VV) radar cross section and the horizontal polarization (HH) radar cross section for a person. In one embodiment, the ratio of the vertical polarization (VV) radar cross section to the horizontal polarization (HH) radar cross section for a person is compared to a detection threshold to determine whether the person is wearing wire...

  17. Isotopic method of leaks detection in oil pipelines

    International Nuclear Information System (INIS)

    Listwam, W.; Mottl, J.

    1974-01-01

    Isotopic method of leaks detection in oil pipelines of diameter 200-800 mm is described. Tracer is injected into pipeline in the form of CH 3 Br 82 . After few hours one or two detectors are passed through pipeline to detect leaks. Detector set consists of scintillation radiometer with Na I/Tl crystal, electronic blecks with one-channel analyzer, recorder and storage batteries. Detector set is built on integrated circuits. (Z.M.)

  18. Steam leak detection in advance reactors via acoustics method

    International Nuclear Information System (INIS)

    Singh, Raj Kumar; Rao, A. Rama

    2011-01-01

    Highlights: → Steam leak detection system is developed to detect any leak inside the reactor vault. → The technique uses leak noise frequency spectrum for leak detection. → Testing of system and method to locate the leak is also developed and discussed in present paper. - Abstract: Prediction of LOCA (loss of coolant activity) plays very important role in safety of nuclear reactor. Coolant is responsible for heat transfer from fuel bundles. Loss of coolant is an accidental situation which requires immediate shut down of reactor. Fall in system pressure during LOCA is the trip parameter used for initiating automatic reactor shut down. However, in primary heat transport system operating in two phase regimes, detection of small break LOCA is not simple. Due to very slow leak rates, time for the fall of pressure is significantly slow. From reactor safety point of view, it is extremely important to find reliable and effective alternative for detecting slow pressure drop in case of small break LOCA. One such technique is the acoustic signal caused by LOCA in small breaks. In boiling water reactors whose primary heat transport is to be driven by natural circulation, small break LOCA detection is important. For prompt action on post small break LOCA, steam leak detection system is developed to detect any leak inside the reactor vault. The detection technique is reliable and plays a very important role in ensuring safety of the reactor. Methodology developed for steam leak detection is discussed in present paper. The methods to locate the leak is also developed and discussed in present paper which is based on analysis of the signal.

  19. Microlensing of unresolved stars as a brown dwarf detection method

    CERN Document Server

    Bouquet, Alain; Melchior, Anne-Laure; Giraud-Heraud, Yannick; Baillon, Paul

    1993-01-01

    We describe a project of brown dwarf detection in the dark halo of a galaxy using the microlensing effect. We argue that monitoring pixels instead of stars could provide an enhancement in the number of detectable events. We estimate the detection efficiency with a Monte-Carlo simulation. We expect a ten-fold increase with respect to current experiments. To assess the feasibility of this method we have determined the photometric precision of a pixel by comparing several pictures of a same field in the LMC. To be published in the Proceeding of the workshop 'The dark side of the universe...', Roma, Juin 1993,

  20. Radiometric method for the rapid detection of Leptospira organisms

    International Nuclear Information System (INIS)

    Manca, N.; Verardi, R.; Colombrita, D.; Ravizzola, G.; Savoldi, E.; Turano, A.

    1986-01-01

    A rapid and sensitive radiometric method for detection of Leptospira interrogans serovar pomona and Leptospira interrogans serovar copenhageni is described. Stuart's medium and Middlebrook TB (12A) medium supplemented with bovine serum albumin, catalase, and casein hydrolysate and labeled with 14 C-fatty acids were used. The radioactivity was measured in a BACTEC 460. With this system, Leptospira organisms were detected in human blood in 2 to 5 days, a notably shorter time period than that required for the majority of detection techniques

  1. Radiometric method for the rapid detection of Leptospira organisms

    Energy Technology Data Exchange (ETDEWEB)

    Manca, N.; Verardi, R.; Colombrita, D.; Ravizzola, G.; Savoldi, E.; Turano, A.

    1986-02-01

    A rapid and sensitive radiometric method for detection of Leptospira interrogans serovar pomona and Leptospira interrogans serovar copenhageni is described. Stuart's medium and Middlebrook TB (12A) medium supplemented with bovine serum albumin, catalase, and casein hydrolysate and labeled with /sup 14/C-fatty acids were used. The radioactivity was measured in a BACTEC 460. With this system, Leptospira organisms were detected in human blood in 2 to 5 days, a notably shorter time period than that required for the majority of detection techniques.

  2. Radiation detection and measurement concepts, methods and devices

    CERN Document Server

    McGregor, Douglas

    2019-01-01

    This text on radiation detection and measurement is a response to numerous requests expressed by students at various universities, in which the most popularly used books do not provide adequate background material, nor explain matters in understandable terms. This work provides a modern overview of radiation detection devices and radiation measurement methods. The topics selected in the book have been selected on the basis of the author’s many years of experience designing radiation detectors and teaching radiation detection and measurement in a classroom environment.

  3. Methods and Algorithms for Detecting Objects in Video Files

    Directory of Open Access Journals (Sweden)

    Nguyen The Cuong

    2018-01-01

    Full Text Available Video files are files that store motion pictures and sounds like in real life. In today's world, the need for automated processing of information in video files is increasing. Automated processing of information has a wide range of application including office/home surveillance cameras, traffic control, sports applications, remote object detection, and others. In particular, detection and tracking of object movement in video file plays an important role. This article describes the methods of detecting objects in video files. Today, this problem in the field of computer vision is being studied worldwide.

  4. Safety assessment and detection methods of genetically modified organisms.

    Science.gov (United States)

    Xu, Rong; Zheng, Zhe; Jiao, Guanglian

    2014-01-01

    Genetically modified organisms (GMOs), are gaining importance in agriculture as well as the production of food and feed. Along with the development of GMOs, health and food safety concerns have been raised. These concerns for these new GMOs make it necessary to set up strict system on food safety assessment of GMOs. The food safety assessment of GMOs, current development status of safety and precise transgenic technologies and GMOs detection have been discussed in this review. The recent patents about GMOs and their detection methods are also reviewed. This review can provide elementary introduction on how to assess and detect GMOs.

  5. Method for detecting resin leakage in LWR coolant

    International Nuclear Information System (INIS)

    Girard, J.E.

    1988-05-01

    Resin leakage from condensate polishing units can result in steam generator corrosion. This report describes the development of a resin leakage detection method based in analyzing the organic breakdown products released from resin on heating. The breakdown products are analyzed using high performance liquid chromatography (HPLC) with fluorescence detection. Some of the organic products formed have been identified. A design for a resin monitoring unit, suitable for incorporation into the IONTRAC system, is presented. Theoretically, detection of ppB levels of resin by processing about one liter of water, is possible

  6. Fuel failure detection and location methods in CAGRs

    International Nuclear Information System (INIS)

    Harris, A.M.

    1982-06-01

    The release of fission products from AGR fuel failures and the way in which the signals from such failures must be detected against the background signal from uranium contamination of the fuel is considered. Theoretical assessments of failure detection are used to show the limitations of the existing Electrostatic Wire Precipitator Burst Can Detection system (BCD) and how its operating parameters can be optimised. Two promising alternative methods, the 'split count' technique and the use of iodine measurements, are described. The results of a detailed study of the mechanical and electronic performance of the present BCD trolleys are given. The limited experience of detection and location of two fuel failures in CAGR using conventional and alternative methods is reviewed. The larger failure was detected and located using the conventional BCD equipment with a high confidence level. It is shown that smaller failures may not be easy to detect and locate using the current BCD equipment, and the second smaller failure probably remained in the reactor for about a year before it was discharged. The split count technique used with modified BCD equipment was able to detect the smaller failure after careful inspection of the data. (author)

  7. Machine Learning Methods for Attack Detection in the Smart Grid.

    Science.gov (United States)

    Ozay, Mete; Esnaola, Inaki; Yarman Vural, Fatos Tunay; Kulkarni, Sanjeev R; Poor, H Vincent

    2016-08-01

    Attack detection problems in the smart grid are posed as statistical learning problems for different attack scenarios in which the measurements are observed in batch or online settings. In this approach, machine learning algorithms are used to classify measurements as being either secure or attacked. An attack detection framework is provided to exploit any available prior knowledge about the system and surmount constraints arising from the sparse structure of the problem in the proposed approach. Well-known batch and online learning algorithms (supervised and semisupervised) are employed with decision- and feature-level fusion to model the attack detection problem. The relationships between statistical and geometric properties of attack vectors employed in the attack scenarios and learning algorithms are analyzed to detect unobservable attacks using statistical learning methods. The proposed algorithms are examined on various IEEE test systems. Experimental analyses show that machine learning algorithms can detect attacks with performances higher than attack detection algorithms that employ state vector estimation methods in the proposed attack detection framework.

  8. Detection of oral HPV infection - Comparison of two different specimen collection methods and two HPV detection methods.

    Science.gov (United States)

    de Souza, Marjorie M A; Hartel, Gunter; Whiteman, David C; Antonsson, Annika

    2018-04-01

    Very little is known about the natural history of oral HPV infection. Several different methods exist to collect oral specimens and detect HPV, but their respective performance characteristics are unknown. We compared two different methods for oral specimen collection (oral saline rinse and commercial saliva kit) from 96 individuals and then analyzed the samples for HPV by two different PCR detection methods (single GP5+/6+ PCR and nested MY09/11 and GP5+/6+ PCR). For the oral rinse samples, the oral HPV prevalence was 10.4% (GP+ PCR; 10% repeatability) vs 11.5% (nested PCR method; 100% repeatability). For the commercial saliva kit samples, the prevalences were 3.1% vs 16.7% with the GP+ PCR vs the nested PCR method (repeatability 100% for both detection methods). Overall the agreement was fair or poor between samples and methods (kappa 0.06-0.36). Standardizing methods of oral sample collection and HPV detection would ensure comparability between future oral HPV studies. Copyright © 2017 Elsevier Inc. All rights reserved.

  9. Detection methods for legionellae. Possibilities and limitations of detection methods; Niet alle detectiemethoden geschikt voor legionellagroei. Mogelijkheden en beperkingen detectiemethoden

    Energy Technology Data Exchange (ETDEWEB)

    Scheffer, W.

    2011-06-15

    This article provides an overview of existing and new methods for detecting legionella in water. It offers insight in the characteristics and applications of existing and new detection methods. However, it is impossible to assess the value of alternative methods at the moment. That will require additional research. [Dutch] Een overzicht is gemaakt van bestaande en nieuwe methoden om legionella in water aan te tonen. Daarmee wordt inzicht verkregen in de kenmerken en toepassingsmogelijkheden van bestaande en nieuwe detectiemethoden. De waarde van alternatieve methoden in een installatie kan echter nog niet worden beoordeeld. Daarvoor is nader onderzoek nodig.

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

    Science.gov (United States)

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

    2017-09-01

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

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

    Directory of Open Access Journals (Sweden)

    S. Li

    2017-09-01

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

  12. Effects of Feature Extraction and Classification Methods on Cyberbully Detection

    Directory of Open Access Journals (Sweden)

    Esra SARAÇ

    2016-12-01

    Full Text Available Cyberbullying is defined as an aggressive, intentional action against a defenseless person by using the Internet, or other electronic contents. Researchers have found that many of the bullying cases have tragically ended in suicides; hence automatic detection of cyberbullying has become important. In this study we show the effects of feature extraction, feature selection, and classification methods that are used, on the performance of automatic detection of cyberbullying. To perform the experiments FormSpring.me dataset is used and the effects of preprocessing methods; several classifiers like C4.5, Naïve Bayes, kNN, and SVM; and information gain and chi square feature selection methods are investigated. Experimental results indicate that the best classification results are obtained when alphabetic tokenization, no stemming, and no stopwords removal are applied. Using feature selection also improves cyberbully detection performance. When classifiers are compared, C4.5 performs the best for the used dataset.

  13. High sensitive quench detection method using an integrated test wire

    International Nuclear Information System (INIS)

    Fevrier, A.; Tavergnier, J.P.; Nithart, H.; Kiblaire, M.; Duchateau, J.L.

    1981-01-01

    A high sensitive quench detection method which works even in the presence of an external perturbing magnetic field is reported. The quench signal is obtained from the difference in voltages at the superconducting winding terminals and at the terminals at a secondary winding strongly coupled to the primary. The secondary winding could consist of a ''zero-current strand'' of the superconducting cable not connected to one of the winding terminals or an integrated normal test wire inside the superconducting cable. Experimental results on quench detection obtained by this method are described. It is shown that the integrated test wire method leads to efficient and sensitive quench detection, especially in the presence of an external perturbing magnetic field

  14. Fault detection of gearbox using time-frequency method

    Science.gov (United States)

    Widodo, A.; Satrijo, Dj.; Prahasto, T.; Haryanto, I.

    2017-04-01

    This research deals with fault detection and diagnosis of gearbox by using vibration signature. In this work, fault detection and diagnosis are approached by employing time-frequency method, and then the results are compared with cepstrum analysis. Experimental work has been conducted for data acquisition of vibration signal thru self-designed gearbox test rig. This test-rig is able to demonstrate normal and faulty gearbox i.e., wears and tooth breakage. Three accelerometers were used for vibration signal acquisition from gearbox, and optical tachometer was used for shaft rotation speed measurement. The results show that frequency domain analysis using fast-fourier transform was less sensitive to wears and tooth breakage condition. However, the method of short-time fourier transform was able to monitor the faults in gearbox. Wavelet Transform (WT) method also showed good performance in gearbox fault detection using vibration signal after employing time synchronous averaging (TSA).

  15. A divisive spectral method for network community detection

    International Nuclear Information System (INIS)

    Cheng, Jianjun; Li, Longjie; Yao, Yukai; Chen, Xiaoyun; Leng, Mingwei; Lu, Weiguo

    2016-01-01

    Community detection is a fundamental problem in the domain of complex network analysis. It has received great attention, and many community detection methods have been proposed in the last decade. In this paper, we propose a divisive spectral method for identifying community structures from networks which utilizes a sparsification operation to pre-process the networks first, and then uses a repeated bisection spectral algorithm to partition the networks into communities. The sparsification operation makes the community boundaries clearer and sharper, so that the repeated spectral bisection algorithm extract high-quality community structures accurately from the sparsified networks. Experiments show that the combination of network sparsification and a spectral bisection algorithm is highly successful, the proposed method is more effective in detecting community structures from networks than the others. (paper: interdisciplinary statistical mechanics)

  16. Method for predicting peptide detection in mass spectrometry

    Science.gov (United States)

    Kangas, Lars [West Richland, WA; Smith, Richard D [Richland, WA; Petritis, Konstantinos [Richland, WA

    2010-07-13

    A method of predicting whether a peptide present in a biological sample will be detected by analysis with a mass spectrometer. The method uses at least one mass spectrometer to perform repeated analysis of a sample containing peptides from proteins with known amino acids. The method then generates a data set of peptides identified as contained within the sample by the repeated analysis. The method then calculates the probability that a specific peptide in the data set was detected in the repeated analysis. The method then creates a plurality of vectors, where each vector has a plurality of dimensions, and each dimension represents a property of one or more of the amino acids present in each peptide and adjacent peptides in the data set. Using these vectors, the method then generates an algorithm from the plurality of vectors and the calculated probabilities that specific peptides in the data set were detected in the repeated analysis. The algorithm is thus capable of calculating the probability that a hypothetical peptide represented as a vector will be detected by a mass spectrometry based proteomic platform, given that the peptide is present in a sample introduced into a mass spectrometer.

  17. Environmental risk comparisons with internal methods of UST leak detection

    International Nuclear Information System (INIS)

    Durgin, P.B.

    1993-01-01

    The past five years have seen a variety of advances in how leaks can be detected from within underground storage tanks. Any leak-detection approach employed within a storage tanks must be conducted at specific time intervals and meet certain leak-rate criteria according to federal and state regulations. Nevertheless, the potential environmental consequences of leak detection approaches differ widely. Internal, volumetric UST monitoring techniques have developed over time including: (1) inventory control with stick measurements, (2) precision tank testing, (3) automatic tank gauging (ATG), (4) statistical inventory reconciliation (SIR), and (5) statistical techniques with automatic tank gauging. An ATG focuses on the advantage of precise data but measured for only a brief period. On the other hand, stick data has less precision but when combined with SIR over extended periods it too can detect low leak rates. Graphs demonstrate the comparable amounts of fuel than can leak out of a tank before being detected by these techniques. The results indicate that annual tank testing has the greatest potential for large volumes of fuel leaking without detection while new statistical approaches with an ATG have the least potential. The environmental implications of the volumes of fuel leaked prior to detection are site specific. For example, if storage tank is surrounded by a high water table and in a sole-source aquifer even small leaks may cause problems. The user must also consider regulatory risks. The level of environmental and regulatory risk should influence selection of the UST leak detection method

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

    Science.gov (United States)

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

    2016-04-01

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

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

    DEFF Research Database (Denmark)

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

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

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

    Science.gov (United States)

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

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

    CSIR Research Space (South Africa)

    Ndimba, R

    2015-09-01

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

  2. AN UNSUPERVISED CHANGE DETECTION BASED ON TEST STATISTIC AND KI FROM MULTI-TEMPORAL AND FULL POLARIMETRIC SAR IMAGES

    Directory of Open Access Journals (Sweden)

    J. Q. Zhao

    2016-06-01

    Full Text Available 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.

  3. A novel visual saliency detection method for infrared video sequences

    Science.gov (United States)

    Wang, Xin; Zhang, Yuzhen; Ning, Chen

    2017-12-01

    Infrared video applications such as target detection and recognition, moving target tracking, and so forth can benefit a lot from visual saliency detection, which is essentially a method to automatically localize the ;important; content in videos. In this paper, a novel visual saliency detection method for infrared video sequences is proposed. Specifically, for infrared video saliency detection, both the spatial saliency and temporal saliency are considered. For spatial saliency, we adopt a mutual consistency-guided spatial cues combination-based method to capture the regions with obvious luminance contrast and contour features. For temporal saliency, a multi-frame symmetric difference approach is proposed to discriminate salient moving regions of interest from background motions. Then, the spatial saliency and temporal saliency are combined to compute the spatiotemporal saliency using an adaptive fusion strategy. Besides, to highlight the spatiotemporal salient regions uniformly, a multi-scale fusion approach is embedded into the spatiotemporal saliency model. Finally, a Gestalt theory-inspired optimization algorithm is designed to further improve the reliability of the final saliency map. Experimental results demonstrate that our method outperforms many state-of-the-art saliency detection approaches for infrared videos under various backgrounds.

  4. Detecting long-term growth trends using tree rings: a critical evaluation of methods.

    Science.gov (United States)

    Peters, Richard L; Groenendijk, Peter; Vlam, Mart; Zuidema, Pieter A

    2015-05-01

    Tree-ring analysis is often used to assess long-term trends in tree growth. A variety of growth-trend detection methods (GDMs) exist to disentangle age/size trends in growth from long-term growth changes. However, these detrending methods strongly differ in approach, with possible implications for their output. Here, we critically evaluate the consistency, sensitivity, reliability and accuracy of four most widely used GDMs: conservative detrending (CD) applies mathematical functions to correct for decreasing ring widths with age; basal area correction (BAC) transforms diameter into basal area growth; regional curve standardization (RCS) detrends individual tree-ring series using average age/size trends; and size class isolation (SCI) calculates growth trends within separate size classes. First, we evaluated whether these GDMs produce consistent results applied to an empirical tree-ring data set of Melia azedarach, a tropical tree species from Thailand. Three GDMs yielded similar results - a growth decline over time - but the widely used CD method did not detect any change. Second, we assessed the sensitivity (probability of correct growth-trend detection), reliability (100% minus probability of detecting false trends) and accuracy (whether the strength of imposed trends is correctly detected) of these GDMs, by applying them to simulated growth trajectories with different imposed trends: no trend, strong trends (-6% and +6% change per decade) and weak trends (-2%, +2%). All methods except CD, showed high sensitivity, reliability and accuracy to detect strong imposed trends. However, these were considerably lower in the weak or no-trend scenarios. BAC showed good sensitivity and accuracy, but low reliability, indicating uncertainty of trend detection using this method. Our study reveals that the choice of GDM influences results of growth-trend studies. We recommend applying multiple methods when analysing trends and encourage performing sensitivity and reliability

  5. Study on UPF Harmonic Current Detection Method Based on DSP

    Energy Technology Data Exchange (ETDEWEB)

    Zhao, H J [Northwestern Polytechnical University, Xi' an 710072 (China); Pang, Y F [Xi' an University of Technology, Xi' an 710048 (China); Qiu, Z M [Xi' an University of Technology, Xi' an 710048 (China); Chen, M [Northwestern Polytechnical University, Xi' an 710072 (China)

    2006-10-15

    Unity power factor (UPF) harmonic current detection method applied to active power filter (APF) is presented in this paper. The intention of this method is to make nonlinear loads and active power filter in parallel to be an equivalent resistance. So after compensation, source current is sinusoidal, and has the same shape of source voltage. Meanwhile, there is no harmonic in source current, and the power factor becomes one. The mathematic model of proposed method and the optimum project for equivalent low pass filter in measurement are presented. Finally, the proposed detection method applied to a shunt active power filter experimental prototype based on DSP TMS320F2812 is developed. Simulation and experiment results indicate the method is simple and easy to implement, and can obtain the real-time calculation of harmonic current exactly.

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

    Energy Technology Data Exchange (ETDEWEB)

    Chandola, Varun [ORNL; Vatsavai, Raju [ORNL

    2011-01-01

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

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

    OpenAIRE

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

    2010-01-01

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

  8. Preface to the Focus Issue: Chaos Detection Methods and Predictability

    International Nuclear Information System (INIS)

    Gottwald, Georg A.; Skokos, Charalampos

    2014-01-01

    This Focus Issue presents a collection of papers originating from the workshop Methods of Chaos Detection and Predictability: Theory and Applications held at the Max Planck Institute for the Physics of Complex Systems in Dresden, June 17–21, 2013. The main aim of this interdisciplinary workshop was to review comprehensively the theory and numerical implementation of the existing methods of chaos detection and predictability, as well as to report recent applications of these techniques to different scientific fields. The collection of twelve papers in this Focus Issue represents the wide range of applications, spanning mathematics, physics, astronomy, particle accelerator physics, meteorology and medical research. This Preface surveys the papers of this Issue

  9. Preface to the Focus Issue: chaos detection methods and predictability.

    Science.gov (United States)

    Gottwald, Georg A; Skokos, Charalampos

    2014-06-01

    This Focus Issue presents a collection of papers originating from the workshop Methods of Chaos Detection and Predictability: Theory and Applications held at the Max Planck Institute for the Physics of Complex Systems in Dresden, June 17-21, 2013. The main aim of this interdisciplinary workshop was to review comprehensively the theory and numerical implementation of the existing methods of chaos detection and predictability, as well as to report recent applications of these techniques to different scientific fields. The collection of twelve papers in this Focus Issue represents the wide range of applications, spanning mathematics, physics, astronomy, particle accelerator physics, meteorology and medical research. This Preface surveys the papers of this Issue.

  10. Limited scleroderma and early detection of visceral changes

    International Nuclear Information System (INIS)

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

    1989-01-01

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

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

    Science.gov (United States)

    Ajadi, Olaniyi A.

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

  12. Review of candidate methods for detecting incipient defects due to aging of installed cables in nuclear power plants

    International Nuclear Information System (INIS)

    Martzloff, F.D.

    1988-01-01

    Several types of test methods have been proposed for detecting incipient defects due to aging in cable insulation systems, none offering certainty of detecting all possible types of defects. Some methods apply direct detection of a defect in the cable; other methods detect changes in electrical or non-electrical parameters from which inference can be drawn on the integrity of the cable. The paper summarizes the first year of a program conducted at the National Bureau of Standards to assess the potential of success for in situ detection of incipient defects by the most promising of these methods

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

    Science.gov (United States)

    He, K.; Zhu, W. D.

    2011-07-01

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

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

    International Nuclear Information System (INIS)

    He, K; Zhu, W D

    2011-01-01

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

  15. A current detection based on an extension of the Prony's method

    Energy Technology Data Exchange (ETDEWEB)

    Deng, C.; Xia, X.; Gong, F. [Changsha Univ. of Science and Technology, Changsha (China). College of Electrical Engineering

    2009-07-01

    The Prony method for spectrum estimation was combined with an adaptive frequency tracking and current frequency demultiplication method as a harmonic detection system. An injective active power filter was used for effective harmonic wave management. The automated system includes a digital signal processor and a high-speed interfacing device. An algorithm was developed to consider the slow voltage changes in the power grid as well as potential mutations in current harmonics. Widrow-Hoff's LMS algorithm was used to develop rolling steps for the filter. The method was used to detect harmonic waves with a sampling frequency of 400 Hz. Results of the study showed that the detection method can be used in real time to detect fundamental and first harmonics in electric power grids. 10 refs., 2 tabs., 1 fig.

  16. Novel Method For Low-Rate Ddos Attack Detection

    Science.gov (United States)

    Chistokhodova, A. A.; Sidorov, I. D.

    2018-05-01

    The relevance of the work is associated with an increasing number of advanced types of DDoS attacks, in particular, low-rate HTTP-flood. Last year, the power and complexity of such attacks increased significantly. The article is devoted to the analysis of DDoS attacks detecting methods and their modifications with the purpose of increasing the accuracy of DDoS attack detection. The article details low-rate attacks features in comparison with conventional DDoS attacks. During the analysis, significant shortcomings of the available method for detecting low-rate DDoS attacks were found. Thus, the result of the study is an informal description of a new method for detecting low-rate denial-of-service attacks. The architecture of the stand for approbation of the method is developed. At the current stage of the study, it is possible to improve the efficiency of an already existing method by using a classifier with memory, as well as additional information.

  17. An Examination of Three Spatial Event Cluster Detection Methods

    Directory of Open Access Journals (Sweden)

    Hensley H. Mariathas

    2015-03-01

    Full Text Available In spatial disease surveillance, geographic areas with large numbers of disease cases are to be identified, so that targeted investigations can be pursued. Geographic areas with high disease rates are called disease clusters and statistical cluster detection tests are used to identify geographic areas with higher disease rates than expected by chance alone. In some situations, disease-related events rather than individuals are of interest for geographical surveillance, and methods to detect clusters of disease-related events are called event cluster detection methods. In this paper, we examine three distributional assumptions for the events in cluster detection: compound Poisson, approximate normal and multiple hypergeometric (exact. The methods differ on the choice of distributional assumption for the potentially multiple correlated events per individual. The methods are illustrated on emergency department (ED presentations by children and youth (age < 18 years because of substance use in the province of Alberta, Canada, during 1 April 2007, to 31 March 2008. Simulation studies are conducted to investigate Type I error and the power of the clustering methods.

  18. Recent developments in optical detection methods for microchip separations.

    Science.gov (United States)

    Götz, Sebastian; Karst, Uwe

    2007-01-01

    This paper summarizes the features and performances of optical detection systems currently applied in order to monitor separations on microchip devices. Fluorescence detection, which delivers very high sensitivity and selectivity, is still the most widely applied method of detection. Instruments utilizing laser-induced fluorescence (LIF) and lamp-based fluorescence along with recent applications of light-emitting diodes (LED) as excitation sources are also covered in this paper. Since chemiluminescence detection can be achieved using extremely simple devices which no longer require light sources and optical components for focusing and collimation, interesting approaches based on this technique are presented, too. Although UV/vis absorbance is a detection method that is commonly used in standard desktop electrophoresis and liquid chromatography instruments, it has not yet reached the same level of popularity for microchip applications. Current applications of UV/vis absorbance detection to microchip separations and innovative approaches that increase sensitivity are described. This article, which contains 85 references, focuses on developments and applications published within the last three years, points out exciting new approaches, and provides future perspectives on this field.

  19. Sequential Change-Point Detection via Online Convex Optimization

    Directory of Open Access Journals (Sweden)

    Yang Cao

    2018-02-01

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

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

    Science.gov (United States)

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

    2018-03-01

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

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

    DEFF Research Database (Denmark)

    Willersrud, Anders; Blanke, Mogens; Imsland, Lars

    2015-01-01

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

  2. Sunglass detection method for automation of video surveillance system

    Science.gov (United States)

    Sikandar, Tasriva; Samsudin, Wan Nur Azhani W.; Hawari Ghazali, Kamarul; Mohd, Izzeldin I.; Fazle Rabbi, Mohammad

    2018-04-01

    Wearing sunglass to hide face from surveillance camera is a common activity in criminal incidences. Therefore, sunglass detection from surveillance video has become a demanding issue in automation of security systems. In this paper we propose an image processing method to detect sunglass from surveillance images. Specifically, a unique feature using facial height and width has been employed to identify the covered region of the face. The presence of covered area by sunglass is evaluated using facial height-width ratio. Threshold value of covered area percentage is used to classify the glass wearing face. Two different types of glasses have been considered i.e. eye glass and sunglass. The results of this study demonstrate that the proposed method is able to detect sunglasses in two different illumination conditions such as, room illumination as well as in the presence of sunlight. In addition, due to the multi-level checking in facial region, this method has 100% accuracy of detecting sunglass. However, in an exceptional case where fabric surrounding the face has similar color as skin, the correct detection rate was found 93.33% for eye glass.

  3. An Automata Based Intrusion Detection Method for Internet of Things

    Directory of Open Access Journals (Sweden)

    Yulong Fu

    2017-01-01

    Full Text Available Internet of Things (IoT transforms network communication to Machine-to-Machine (M2M basis and provides open access and new services to citizens and companies. It extends the border of Internet and will be developed as one part of the future 5G networks. However, as the resources of IoT’s front devices are constrained, many security mechanisms are hard to be implemented to protect the IoT networks. Intrusion detection system (IDS is an efficient technique that can be used to detect the attackers when cryptography is broken, and it can be used to enforce the security of IoT networks. In this article, we analyzed the intrusion detection requirements of IoT networks and then proposed a uniform intrusion detection method for the vast heterogeneous IoT networks based on an automata model. The proposed method can detect and report the possible IoT attacks with three types: jam-attack, false-attack, and reply-attack automatically. We also design an experiment to verify the proposed IDS method and examine the attack of RADIUS application.

  4. Plutonium, its occurrence in environment and methods of detection

    Energy Technology Data Exchange (ETDEWEB)

    Petr, I [Ceske Vysoke Uceni Technicke, Prague (Czechoslovakia). Fakulta Jaderna a Fysikalne Inzenyrska

    1977-12-01

    A brief survey is given of the physical properties of plutonium nuclides, their toxicity, values of maximum permissible annual intake, and their occurrence in the environment, and of their determination in water, soil, air and biological objects. The principles are stated of the individual methods of plutonium determination, i.e., the method of radiochemical analysis with subsequent detection or alpha spectrometry, the method of filter sampling of air with subsequent alpha spectrometry, coincidence alpha-beta spectrometry or radiochemical analysis, and the use of X and gamma spectrometry. A comparison of the different methods is presented.

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

    Directory of Open Access Journals (Sweden)

    Timo Melkas

    2012-10-01

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

  6. Performance evaluation of sea surface simulation methods for target detection

    Science.gov (United States)

    Xia, Renjie; Wu, Xin; Yang, Chen; Han, Yiping; Zhang, Jianqi

    2017-11-01

    With the fast development of sea surface target detection by optoelectronic sensors, machine learning has been adopted to improve the detection performance. Many features can be learned from training images by machines automatically. However, field images of sea surface target are not sufficient as training data. 3D scene simulation is a promising method to address this problem. For ocean scene simulation, sea surface height field generation is the key point to achieve high fidelity. In this paper, two spectra-based height field generation methods are evaluated. Comparison between the linear superposition and linear filter method is made quantitatively with a statistical model. 3D ocean scene simulating results show the different features between the methods, which can give reference for synthesizing sea surface target images with different ocean conditions.

  7. A Prognostic Method for Fault Detection in Wind Turbine Drivetrains

    DEFF Research Database (Denmark)

    Nejada, Amir R.; Odgaard, Peter Fogh; Gao, Zhen

    2014-01-01

    In this paper, a prognostic method is presented for fault detection in gears and bearings in wind turbine drivetrains. This method is based on angular velocity measurements from the gearbox input shaft and the output to the generator, using two additional angular velocity sensors on the intermedi......In this paper, a prognostic method is presented for fault detection in gears and bearings in wind turbine drivetrains. This method is based on angular velocity measurements from the gearbox input shaft and the output to the generator, using two additional angular velocity sensors...... bearing faults in three locations: the high-speed shaft stage, the planetary stage and the intermediate-speed shaft stage. Simulations of the faulty and fault-free cases are performed on a gearbox model implemented in multibody dynamic simulation software. The global loads on the gearbox are obtained from...

  8. Detection methods for irradiated foods: current status. Proceedings

    International Nuclear Information System (INIS)

    McMurray, C.H.; Gray, R.; Stewart, E.M.; Pearce, J.; Queen's Univ., Belfast, Northern Ireland

    1996-01-01

    This book contains a scientific record of an international meeting on analytical detection methods for irradiation treatment of food. Apart from encouraging the basic development of detection tests, the meeting also aimed to assess the various test methods critically to determine their suitability for general use by public health laboratories and others concerned with trade in irradiated food. Two sets of criteria have been developed to assess test methods, technical criteria for a qualitative or quantitative test and practical criteria if a method is to be widely applied by food labelling authorities. Agreement has already been achieved for the use of electron spin resonance, thermoluminescence, hydrocarbons, 2-Alkylcyclobutanones, microbiological, viscometry and impedance tests. (UK)

  9. Emergency First Responders' Experience with Colorimetric Detection Methods

    Energy Technology Data Exchange (ETDEWEB)

    Sandra L. Fox; Keith A. Daum; Carla J. Miller; Marnie M. Cortez

    2007-10-01

    Nationwide, first responders from state and federal support teams respond to hazardous materials incidents, industrial chemical spills, and potential weapons of mass destruction (WMD) attacks. Although first responders have sophisticated chemical, biological, radiological, and explosive detectors available for assessment of the incident scene, simple colorimetric detectors have a role in response actions. The large number of colorimetric chemical detection methods available on the market can make the selection of the proper methods difficult. Although each detector has unique aspects to provide qualitative or quantitative data about the unknown chemicals present, not all detectors provide consistent, accurate, and reliable results. Included here, in a consumer-report-style format, we provide “boots on the ground” information directly from first responders about how well colorimetric chemical detection methods meet their needs in the field and how they procure these methods.

  10. Method and means for detecting magnetic deposits in tubular plant

    Energy Technology Data Exchange (ETDEWEB)

    Lord, W

    1981-03-04

    Deposits of magnetite on tubes in a heat exchanger, e.g., a steam generator, are detected by measuring the magnetic reluctance within the tubes. A probe for measuring the reluctance includes a permanent magnet (or a magnetic core and an excitation coil wound on the core) and a magnetic flux detector such as a Hall generator mounted for example on one of the non-magnetic rings. Changes in flux density as the probe is pushed through the tubes are detected by the Hall generator, thus indicating the presence of magnetite deposits. The probe includes a non-magnetic tube for pushing it through the heat exchanger tubes.

  11. COMPARISON OF TWO METHODS FOR THE DETECTION OF LISTERIA MONOCYTOGENES

    Directory of Open Access Journals (Sweden)

    G. Tantillo

    2013-02-01

    Full Text Available The aim of this study was to compare the performance of the conventional methods for detection of Listeria monocytogenes in food using media Oxford and ALOA (Agar Listeria acc. to Ottaviani & Agosti in according to the ISO 11290-1 to a new chromogenic medium “CHROMagar Listeria” standardized in 2005 AFNOR ( CHR – 21/1-12/01. A total of 40 pre-packed ready-to-eat food samples were examined. Using two methods six samples were found positive for Listeria monocytogenes but the medium “CHROMagar Listeria” was more selective in comparison with the others. In conclusion this study has demonstrated that isolation medium able to target specifically the detection of L. monocytogenes such as “CHROMagar Listeria” is highly recommendable because of that detection time is significantly reduced and the analysis cost is less expensive.

  12. A hybrid approach for efficient anomaly detection using metaheuristic methods

    Directory of Open Access Journals (Sweden)

    Tamer F. Ghanem

    2015-07-01

    Full Text Available Network intrusion detection based on anomaly detection techniques has a significant role in protecting networks and systems against harmful activities. Different metaheuristic techniques have been used for anomaly detector generation. Yet, reported literature has not studied the use of the multi-start metaheuristic method for detector generation. This paper proposes a hybrid approach for anomaly detection in large scale datasets using detectors generated based on multi-start metaheuristic method and genetic algorithms. The proposed approach has taken some inspiration of negative selection-based detector generation. The evaluation of this approach is performed using NSL-KDD dataset which is a modified version of the widely used KDD CUP 99 dataset. The results show its effectiveness in generating a suitable number of detectors with an accuracy of 96.1% compared to other competitors of machine learning algorithms.

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

    Indian Academy of Sciences (India)

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

  14. Suitability of the thermoluminescence method for detection of irradiated foods

    International Nuclear Information System (INIS)

    Pinnioja, S.

    1993-01-01

    Irradiated foods can be detected by thermoluminescence (TL) of contaminating minerals. Altogether about 300 lots of herbs, spices, berries, mushrooms and seafood were studied by the TL method. Irradiated herbs and spices were easily differentiated from unirradiated ones two years after irradiation of a 10 kGy dose. The mineral composition of seafood was variable; and while calcite was suitable for the TL analysis, aragonite and smectite gave unreliable results. Control analyses during two years confirmed the reliability of TL method. (author)

  15. The method for glomerulations detection in histological images of prostate

    Science.gov (United States)

    Zavarzin, A. A.; Pronichev, A. N.; Rodionova, O. V.; Komochkina, E. A.; Prilepskaya, E. A.; Kovylina, M. V.

    2018-01-01

    In the work presented, a method for detecting glomeruli in pictures of histological preparations of the prostate gland is described, the presence of which indicates a malignant neoplasm. Pathological structures at the level of microimages are investigated. The developed method is the result of joint activity of the National Research Nuclear University "MEPhI" and the Moscow State Medical and Stomatological University named after A.I. Evdokimova.

  16. Photostimulated luminescence, fast method of detection of irradiated foodstuffs

    International Nuclear Information System (INIS)

    Guzik, G.P.; Stachowicz, W.

    2005-01-01

    The principle of pulsed photostimulated luminescence (PPSL) method, description of instrumentation and methodology of measurements are presented. The pathway of operational procedure and testing of the PPSL instrument in the Laboratory for Detection of Irradiated Food of the Institute of Nuclear Chemistry and Technology are described. Attention has been paid to the positives of the new method while some limitation of its application have been also discussed. (author)

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

    Science.gov (United States)

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

    2016-01-01

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

  18. Comparison of two detection methods in thin layer chromatographic ...

    African Journals Online (AJOL)

    o-tolidine plus potassium iodide and photosynthesis inhibition detection methods were investigated for the analysis of three triazine herbicides (atrazine, ametryne, simazine) and two urea herbicides (diuron, metobromuron) in a coastal savanna soil using thin layer chromatography to compare the suitability of the two ...

  19. Laboratory methods for diagnosis and detection of drug resistant ...

    African Journals Online (AJOL)

    Data source: Published series of peer reviewed journals and manuals written on laboratory methods that are currently used for diagnosis and detection of drug resistance of Mycobacterium tuberculosis complex were reviewed using the index medicus, pubmed and medline search. Conventional bacteriological microscopy ...

  20. Application of Bayesian Methods for Detecting Fraudulent Behavior on Tests

    Science.gov (United States)

    Sinharay, Sandip

    2018-01-01

    Producers and consumers of test scores are increasingly concerned about fraudulent behavior before and during the test. There exist several statistical or psychometric methods for detecting fraudulent behavior on tests. This paper provides a review of the Bayesian approaches among them. Four hitherto-unpublished real data examples are provided to…