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Sample records for accurate change detection

  1. Obtaining Accurate Change Detection Results from High-Resolution Satellite Sensors

    NASA Technical Reports Server (NTRS)

    Bryant, N.; Bunch, W.; Fretz, R.; Kim, P.; Logan, T.; Smyth, M.; Zobrist, A.

    2012-01-01

    Multi-date acquisitions of high-resolution imaging satellites (e.g. GeoEye and WorldView), can display local changes of current economic interest. However, their large data volume precludes effective manual analysis, requiring image co-registration followed by image-to-image change detection, preferably with minimal analyst attention. We have recently developed an automatic change detection procedure that minimizes false-positives. The processing steps include: (a) Conversion of both the pre- and post- images to reflectance values (this step is of critical importance when different sensors are involved); reflectance values can be either top-of-atmosphere units or have full aerosol optical depth calibration applied using bi-directional reflectance knowledge. (b) Panchromatic band image-to-image co-registration, using an orthorectified base reference image (e.g. Digital Orthophoto Quadrangle) and a digital elevation model; this step can be improved if a stereo-pair of images have been acquired on one of the image dates. (c) Pan-sharpening of the multispectral data to assure recognition of change objects at the highest resolution. (d) Characterization of multispectral data in the post-image ( i.e. the background) using unsupervised cluster analysis. (e) Band ratio selection in the post-image to separate surface materials of interest from the background. (f) Preparing a pre-to-post change image. (g) Identifying locations where change has occurred involving materials of interest.

  2. Accurate glucose detection in a small etalon

    NASA Astrophysics Data System (ADS)

    Martini, Joerg; Kuebler, Sebastian; Recht, Michael; Torres, Francisco; Roe, Jeffrey; Kiesel, Peter; Bruce, Richard

    2010-02-01

    We are developing a continuous glucose monitor for subcutaneous long-term implantation. This detector contains a double chamber Fabry-Perot-etalon that measures the differential refractive index (RI) between a reference and a measurement chamber at 850 nm. The etalon chambers have wavelength dependent transmission maxima which dependent linearly on the RI of their contents. An RI difference of ▵n=1.5.10-6 changes the spectral position of a transmission maximum by 1pm in our measurement. By sweeping the wavelength of a single-mode Vertical-Cavity-Surface-Emitting-Laser (VCSEL) linearly in time and detecting the maximum transmission peaks of the etalon we are able to measure the RI of a liquid. We have demonstrated accuracy of ▵n=+/-3.5.10-6 over a ▵n-range of 0 to 1.75.10-4 and an accuracy of 2% over a ▵nrange of 1.75.10-4 to 9.8.10-4. The accuracy is primarily limited by the reference measurement. The RI difference between the etalon chambers is made specific to glucose by the competitive, reversible release of Concanavalin A (ConA) from an immobilized dextran matrix. The matrix and ConA bound to it, is positioned outside the optical detection path. ConA is released from the matrix by reacting with glucose and diffuses into the optical path to change the RI in the etalon. Factors such as temperature affect the RI in measurement and detection chamber equally but do not affect the differential measurement. A typical standard deviation in RI is +/-1.4.10-6 over the range 32°C to 42°C. The detector enables an accurate glucose specific concentration measurement.

  3. 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.

    PubMed

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

    2013-10-10

    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.

  4. High Frequency QRS ECG Accurately Detects Cardiomyopathy

    NASA Technical Reports Server (NTRS)

    Schlegel, Todd T.; Arenare, Brian; Poulin, Gregory; Moser, Daniel R.; Delgado, Reynolds

    2005-01-01

    High frequency (HF, 150-250 Hz) analysis over the entire QRS interval of the ECG is more sensitive than conventional ECG for detecting myocardial ischemia. However, the accuracy of HF QRS ECG for detecting cardiomyopathy is unknown. We obtained simultaneous resting conventional and HF QRS 12-lead ECGs in 66 patients with cardiomyopathy (EF = 23.2 plus or minus 6.l%, mean plus or minus SD) and in 66 age- and gender-matched healthy controls using PC-based ECG software recently developed at NASA. The single most accurate ECG parameter for detecting cardiomyopathy was an HF QRS morphological score that takes into consideration the total number and severity of reduced amplitude zones (RAZs) present plus the clustering of RAZs together in contiguous leads. This RAZ score had an area under the receiver operator curve (ROC) of 0.91, and was 88% sensitive, 82% specific and 85% accurate for identifying cardiomyopathy at optimum score cut-off of 140 points. Although conventional ECG parameters such as the QRS and QTc intervals were also significantly longer in patients than controls (P less than 0.001, BBBs excluded), these conventional parameters were less accurate (area under the ROC = 0.77 and 0.77, respectively) than HF QRS morphological parameters for identifying underlying cardiomyopathy. The total amplitude of the HF QRS complexes, as measured by summed root mean square voltages (RMSVs), also differed between patients and controls (33.8 plus or minus 11.5 vs. 41.5 plus or minus 13.6 mV, respectively, P less than 0.003), but this parameter was even less accurate in distinguishing the two groups (area under ROC = 0.67) than the HF QRS morphologic and conventional ECG parameters. Diagnostic accuracy was optimal (86%) when the RAZ score from the HF QRS ECG and the QTc interval from the conventional ECG were used simultaneously with cut-offs of greater than or equal to 40 points and greater than or equal to 445 ms, respectively. In conclusion 12-lead HF QRS ECG employing

  5. Accurate detection of differential RNA processing

    PubMed Central

    Drewe, Philipp; Stegle, Oliver; Hartmann, Lisa; Kahles, André; Bohnert, Regina; Wachter, Andreas; Borgwardt, Karsten; Rätsch, Gunnar

    2013-01-01

    Deep transcriptome sequencing (RNA-Seq) has become a vital tool for studying the state of cells in the context of varying environments, genotypes and other factors. RNA-Seq profiling data enable identification of novel isoforms, quantification of known isoforms and detection of changes in transcriptional or RNA-processing activity. Existing approaches to detect differential isoform abundance between samples either require a complete isoform annotation or fall short in providing statistically robust and calibrated significance estimates. Here, we propose a suite of statistical tests to address these open needs: a parametric test that uses known isoform annotations to detect changes in relative isoform abundance and a non-parametric test that detects differential read coverages and can be applied when isoform annotations are not available. Both methods account for the discrete nature of read counts and the inherent biological variability. We demonstrate that these tests compare favorably to previous methods, both in terms of accuracy and statistical calibrations. We use these techniques to analyze RNA-Seq libraries from Arabidopsis thaliana and Drosophila melanogaster. The identified differential RNA processing events were consistent with RT–qPCR measurements and previous studies. The proposed toolkit is available from http://bioweb.me/rdiff and enables in-depth analyses of transcriptomes, with or without available isoform annotation. PMID:23585274

  6. Detecting Unidentified Changes

    PubMed Central

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

    2014-01-01

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

  7. Accurately Detecting Students' Lies regarding Relational Aggression by Correctional Instructions

    ERIC Educational Resources Information Center

    Dickhauser, Oliver; Reinhard, Marc-Andre; Marksteiner, Tamara

    2012-01-01

    This study investigates the effect of correctional instructions when detecting lies about relational aggression. Based on models from the field of social psychology, we predict that correctional instruction will lead to a less pronounced lie bias and to more accurate lie detection. Seventy-five teachers received videotapes of students' true denial…

  8. A fast and accurate FPGA based QRS detection system.

    PubMed

    Shukla, Ashish; Macchiarulo, Luca

    2008-01-01

    An accurate Field Programmable Gate Array (FPGA) based ECG Analysis system is described in this paper. The design, based on a popular software based QRS detection algorithm, calculates the threshold value for the next peak detection cycle, from the median of eight previously detected peaks. The hardware design has accuracy in excess of 96% in detecting the beats correctly when tested with a subset of five 30 minute data records obtained from the MIT-BIH Arrhythmia database. The design, implemented using a proprietary design tool (System Generator), is an extension of our previous work and uses 76% resources available in a small-sized FPGA device (Xilinx Spartan xc3s500), has a higher detection accuracy as compared to our previous design and takes almost half the analysis time in comparison to software based approach.

  9. Building dynamic population graph for accurate correspondence detection.

    PubMed

    Du, Shaoyi; Guo, Yanrong; Sanroma, Gerard; Ni, Dong; Wu, Guorong; Shen, Dinggang

    2015-12-01

    In medical imaging studies, there is an increasing trend for discovering the intrinsic anatomical difference across individual subjects in a dataset, such as hand images for skeletal bone age estimation. Pair-wise matching is often used to detect correspondences between each individual subject and a pre-selected model image with manually-placed landmarks. However, the large anatomical variability across individual subjects can easily compromise such pair-wise matching step. In this paper, we present a new framework to simultaneously detect correspondences among a population of individual subjects, by propagating all manually-placed landmarks from a small set of model images through a dynamically constructed image graph. Specifically, we first establish graph links between models and individual subjects according to pair-wise shape similarity (called as forward step). Next, we detect correspondences for the individual subjects with direct links to any of model images, which is achieved by a new multi-model correspondence detection approach based on our recently-published sparse point matching method. To correct those inaccurate correspondences, we further apply an error detection mechanism to automatically detect wrong correspondences and then update the image graph accordingly (called as backward step). After that, all subject images with detected correspondences are included into the set of model images, and the above two steps of graph expansion and error correction are repeated until accurate correspondences for all subject images are established. Evaluations on real hand X-ray images demonstrate that our proposed method using a dynamic graph construction approach can achieve much higher accuracy and robustness, when compared with the state-of-the-art pair-wise correspondence detection methods as well as a similar method but using static population graph.

  10. Accurate colon residue detection algorithm with partial volume segmentation

    NASA Astrophysics Data System (ADS)

    Li, Xiang; Liang, Zhengrong; Zhang, PengPeng; Kutcher, Gerald J.

    2004-05-01

    Colon cancer is the second leading cause of cancer-related death in the United States. Earlier detection and removal of polyps can dramatically reduce the chance of developing malignant tumor. Due to some limitations of optical colonoscopy used in clinic, many researchers have developed virtual colonoscopy as an alternative technique, in which accurate colon segmentation is crucial. However, partial volume effect and existence of residue make it very challenging. The electronic colon cleaning technique proposed by Chen et al is a very attractive method, which is also kind of hard segmentation method. As mentioned in their paper, some artifacts were produced, which might affect the accurate colon reconstruction. In our paper, instead of labeling each voxel with a unique label or tissue type, the percentage of different tissues within each voxel, which we call a mixture, was considered in establishing a maximum a posterior probability (MAP) image-segmentation framework. A Markov random field (MRF) model was developed to reflect the spatial information for the tissue mixtures. The spatial information based on hard segmentation was used to determine which tissue types are in the specific voxel. Parameters of each tissue class were estimated by the expectation-maximization (EM) algorithm during the MAP tissue-mixture segmentation. Real CT experimental results demonstrated that the partial volume effects between four tissue types have been precisely detected. Meanwhile, the residue has been electronically removed and very smooth and clean interface along the colon wall has been obtained.

  11. Do Canadian collegiate hockey players accurately perceive body composition changes after unmonitored training and diet?

    PubMed

    Prokop, Neal W; Duncan, Lindsay R; Andersen, Ross E

    2015-10-01

    Collegiate athletes often use nutritional programs and supplements to elicit body composition changes in muscle or fat. It is unknown if athletes can accurately perceive their fluctuations in body composition, yet their understanding may help them make more accurate interpretations regarding the success of potential nutrition or exercise regimens. The purpose of this study was to investigate if collegiate hockey players could accurately perceive a change in body composition during a 3-month period within their regular season, in which no predetermined nutritional or exercise program was provided. Twenty-four male Canadian collegiate hockey players completed preseason and midseason body composition assessments using dual-energy X-ray absorptiometry. Immediately before the midseason scan, players attempted to accurately match their perceived fluctuation in composition, with predetermined categorical ranges of relative body composition and strength. Two-thirds of players and one-half of players accurately perceived changes in arm-lean and arm-fat tissue, respectively. Approximately two-thirds of players did not accurately perceive gains or losses of lean or fat tissue within their leg and overall body. Although some athletes partially detected changes in the lean and fat tissue of particular regions, the vast majority of players cannot detect the type, or amount of tissue gained and lost across the overall body. Body composition assessments, rather than an athlete's perceptions, should be used to help interpret the success of a sport nutrition or exercise program. Athletes should be aware that physiologic adaptations might take place unnoticed, which could affect the acceptance and adherence of nutrition or exercise interventions.

  12. Accurate feature detection and estimation using nonlinear and multiresolution analysis

    NASA Astrophysics Data System (ADS)

    Rudin, Leonid; Osher, Stanley

    1994-11-01

    A program for feature detection and estimation using nonlinear and multiscale analysis was completed. The state-of-the-art edge detection was combined with multiscale restoration (as suggested by the first author) and robust results in the presence of noise were obtained. Successful applications to numerous images of interest to DOD were made. Also, a new market in the criminal justice field was developed, based in part, on this work.

  13. An accurate fuzzy edge detection method using wavelet details subimages

    NASA Astrophysics Data System (ADS)

    Sedaghat, Nafiseh; Pourreza, Hamidreza

    2010-02-01

    Edge detection is a basic and important subject in computer vision and image processing. An edge detector is defined as a mathematical operator of small spatial extent that responds in some way to these discontinuities, usually classifying every image pixel as either belonging to an edge or not. Many researchers have been spent attempting to develop effective edge detection algorithms. Despite this extensive research, the task of finding the edges that correspond to true physical boundaries remains a difficult problem.Edge detection algorithms based on the application of human knowledge show their flexibility and suggest that the use of human knowledge is a reasonable alternative. In this paper we propose a fuzzy inference system with two inputs: gradient and wavelet details. First input is calculated by Sobel operator and the second is calculated by wavelet transform of input image and then reconstruction of image only with details subimages by inverse wavelet transform. There are many fuzzy edge detection methods, but none of them utilize wavelet transform as it is used in this paper. For evaluating our method, we detect edges of images with different brightness characteristics and compare results with canny edge detector. The results show the high performance of our method in finding true edges.

  14. SAR change detection MTI

    NASA Astrophysics Data System (ADS)

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

    2006-05-01

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

  15. Instrument accurately measures small temperature changes on test surface

    NASA Technical Reports Server (NTRS)

    Harvey, W. D.; Miller, H. B.

    1966-01-01

    Calorimeter apparatus accurately measures very small temperature rises on a test surface subjected to aerodynamic heating. A continuous thin sheet of a sensing material is attached to a base support plate through which a series of holes of known diameter have been drilled for attaching thermocouples to the material.

  16. How Accurate Are We in Detecting Biceps Tendinopathy?

    PubMed

    Carr, Ryan M; Shishani, Yousef; Gobezie, Reuben

    2016-01-01

    Biceps tendon pain is frequently called biceps "tendinitis," or inflammation of the biceps tendon. Histologic analysis of biceps tendon biopsies demonstrates changes in tenocyte size, ground substance, collagen organization, and vascularity observed with many different tendinopathies. There are distinct symptoms of biceps tendinopathy and a few provocative maneuvers can help make the diagnosis. Imaging studies (eg, MRI) can show changes in signal sequence or tears. However, MRI has a low sensitivity and frequently results in missed or misdiagnosed biceps pathology. Clinical decision making is best guided by a strong clinical suspicion based on patient history, physical examination, and MRI.

  17. Change Detection: Training and Transfer

    PubMed Central

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

    2013-01-01

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

  18. Accurate detection of blood vessels improves the detection of exudates in color fundus images.

    PubMed

    Youssef, Doaa; Solouma, Nahed H

    2012-12-01

    Exudates are one of the earliest and most prevalent symptoms of diseases leading to blindness such as diabetic retinopathy and macular degeneration. Certain areas of the retina with such conditions are to be photocoagulated by laser to stop the disease progress and prevent blindness. Outlining these areas is dependent on outlining the lesions and the anatomic structures of the retina. In this paper, we provide a new method for the detection of blood vessels that improves the detection of exudates in fundus photographs. The method starts with an edge detection algorithm which results in a over segmented image. Then the new feature-based algorithm can be used to accurately detect the blood vessels. This algorithm considers the characteristics of a retinal blood vessel such as its width range, intensities and orientations for the purpose of selective segmentation. Because of its bulb shape and its color similarity with exudates, the optic disc can be detected using the common Hough transform technique. The extracted blood vessel tree and optic disc could be subtracted from the over segmented image to get an initial estimate of exudates. The final estimation of exudates can then be obtained by morphological reconstruction based on the appearance of exudates. This method is shown to be promising since it increases the sensitivity and specificity of exudates detection to 80% and 100% respectively.

  19. PATHOME: an algorithm for accurately detecting differentially expressed subpathways

    PubMed Central

    Nam, S; Chang, H R; Kim, K-T; Kook, M-C; Hong, D; Kwon, C H; Jung, H R; Park, H S; Powis, G; Liang, H; Park, T; Kim, Y H

    2014-01-01

    The translation of high-throughput gene expression data into biologically meaningful information remains a bottleneck. We developed a novel computational algorithm, PATHOME, for detecting differentially expressed biological pathways. This algorithm employs straightforward statistical tests to evaluate the significance of differential expression patterns along subpathways. Applying it to gene expression data sets of gastric cancer (GC), we compared its performance with those of other leading programs. Based on a literature-driven reference set, PATHOME showed greater consistency in identifying known cancer-related pathways. For the WNT pathway uniquely identified by PATHOME, we validated its involvement in gastric carcinogenesis through experimental perturbation of both cell lines and animal models. We identified HNF4α-WNT5A regulation in the cross-talk between the AMPK metabolic pathway and the WNT signaling pathway, and further identified WNT5A as a potential therapeutic target for GC. We have demonstrated PATHOME to be a powerful tool, with improved sensitivity for identifying disease-related dysregulated pathways. PMID:24681952

  20. Electrophysiological correlates of change detection.

    PubMed

    Eimer, Martin; Mazza, Veronica

    2005-05-01

    To identify electrophysiological correlates of change detection, event-related brain potentials (ERPs) were recorded while participants monitored displays containing four faces in order to detect a face identity change across successive displays. Successful change detection was mirrored by an N2pc component at posterior electrodes contralateral to the side of a change, suggesting close links between conscious change detection and attention. ERPs on undetected-change trials differed from detected-change and no-change trials. We suggest that short-latency ERP differences between these trial types reflect trial-by-trial fluctuations in advance task preparation, whereas differences in the P3 time range are due to variations in the duration of perceptual and decision-related processing. Overall, these findings demonstrate that ERPs are a useful tool for dissociating processes underlying change blindness and change detection.

  1. Accurate Detection of Dysmorphic Nuclei Using Dynamic Programming and Supervised Classification.

    PubMed

    Verschuuren, Marlies; De Vylder, Jonas; Catrysse, Hannes; Robijns, Joke; Philips, Wilfried; De Vos, Winnok H

    2017-01-01

    A vast array of pathologies is typified by the presence of nuclei with an abnormal morphology. Dysmorphic nuclear phenotypes feature dramatic size changes or foldings, but also entail much subtler deviations such as nuclear protrusions called blebs. Due to their unpredictable size, shape and intensity, dysmorphic nuclei are often not accurately detected in standard image analysis routines. To enable accurate detection of dysmorphic nuclei in confocal and widefield fluorescence microscopy images, we have developed an automated segmentation algorithm, called Blebbed Nuclei Detector (BleND), which relies on two-pass thresholding for initial nuclear contour detection, and an optimal path finding algorithm, based on dynamic programming, for refining these contours. Using a robust error metric, we show that our method matches manual segmentation in terms of precision and outperforms state-of-the-art nuclear segmentation methods. Its high performance allowed for building and integrating a robust classifier that recognizes dysmorphic nuclei with an accuracy above 95%. The combined segmentation-classification routine is bound to facilitate nucleus-based diagnostics and enable real-time recognition of dysmorphic nuclei in intelligent microscopy workflows.

  2. Accurate Detection of Dysmorphic Nuclei Using Dynamic Programming and Supervised Classification

    PubMed Central

    Verschuuren, Marlies; De Vylder, Jonas; Catrysse, Hannes; Robijns, Joke; Philips, Wilfried

    2017-01-01

    A vast array of pathologies is typified by the presence of nuclei with an abnormal morphology. Dysmorphic nuclear phenotypes feature dramatic size changes or foldings, but also entail much subtler deviations such as nuclear protrusions called blebs. Due to their unpredictable size, shape and intensity, dysmorphic nuclei are often not accurately detected in standard image analysis routines. To enable accurate detection of dysmorphic nuclei in confocal and widefield fluorescence microscopy images, we have developed an automated segmentation algorithm, called Blebbed Nuclei Detector (BleND), which relies on two-pass thresholding for initial nuclear contour detection, and an optimal path finding algorithm, based on dynamic programming, for refining these contours. Using a robust error metric, we show that our method matches manual segmentation in terms of precision and outperforms state-of-the-art nuclear segmentation methods. Its high performance allowed for building and integrating a robust classifier that recognizes dysmorphic nuclei with an accuracy above 95%. The combined segmentation-classification routine is bound to facilitate nucleus-based diagnostics and enable real-time recognition of dysmorphic nuclei in intelligent microscopy workflows. PMID:28125723

  3. Change in BMI Accurately Predicted by Social Exposure to Acquaintances

    PubMed Central

    Oloritun, Rahman O.; Ouarda, Taha B. M. J.; Moturu, Sai; Madan, Anmol; Pentland, Alex (Sandy); Khayal, Inas

    2013-01-01

    Research has mostly focused on obesity and not on processes of BMI change more generally, although these may be key factors that lead to obesity. Studies have suggested that obesity is affected by social ties. However these studies used survey based data collection techniques that may be biased toward select only close friends and relatives. In this study, mobile phone sensing techniques were used to routinely capture social interaction data in an undergraduate dorm. By automating the capture of social interaction data, the limitations of self-reported social exposure data are avoided. This study attempts to understand and develop a model that best describes the change in BMI using social interaction data. We evaluated a cohort of 42 college students in a co-located university dorm, automatically captured via mobile phones and survey based health-related information. We determined the most predictive variables for change in BMI using the least absolute shrinkage and selection operator (LASSO) method. The selected variables, with gender, healthy diet category, and ability to manage stress, were used to build multiple linear regression models that estimate the effect of exposure and individual factors on change in BMI. We identified the best model using Akaike Information Criterion (AIC) and R2. This study found a model that explains 68% (p<0.0001) of the variation in change in BMI. The model combined social interaction data, especially from acquaintances, and personal health-related information to explain change in BMI. This is the first study taking into account both interactions with different levels of social interaction and personal health-related information. Social interactions with acquaintances accounted for more than half the variation in change in BMI. This suggests the importance of not only individual health information but also the significance of social interactions with people we are exposed to, even people we may not consider as close friends. PMID

  4. FAS 33: accurately recording effects of changing prices.

    PubMed

    Sage, L G

    1987-02-01

    FAS 33 addresses the problem of distortion in conventional historical cost financial statements because of changing prices. It requires 1300 business enterprises to report selected changing price data on a supplementary basis. It has been demonstrated that it is also feasible and beneficial for hospitals to present price disclosures as supplementary information to their financial statements. The possible application of FAS 33 is supported on the basis that the accounting and reporting methods of healthcare institutions are similar to the accounting and reporting practices of profit-seeking entities.

  5. Accurate measurement of mean sea level changes by altimetric satellites

    NASA Technical Reports Server (NTRS)

    Born, G. H.; Tapley, B. D.; Ries, J. C.; Stewart, R. H.

    1986-01-01

    A technique for monitoring changes in global mean sea levels using altimeter data from a well-tracked satellite is examined. The usefulness of this technique is evaluated by analyzing Seasat altimeter data obtained during July-September 1978. The effects of orbit errors, geoid errors, sampling intervals, tides, and atmosphere refraction on the calculation of the mean sea level are investigated. The data reveal that the stability of an altimeter can be determined with an accuracy of + or - 7 cm using globally averaged sea surface height measurements. The application of this procedure to the US/French Ocean Topography Experiment is discussed.

  6. Change detection in satellite images

    NASA Astrophysics Data System (ADS)

    Thonnessen, U.; Hofele, G.; Middelmann, W.

    2005-05-01

    Change detection plays an important role in different military areas as strategic reconnaissance, verification of armament and disarmament control and damage assessment. It is the process of identifying differences in the state of an object or phenomenon by observing it at different times. The availability of spaceborne reconnaissance systems with high spatial resolution, multi spectral capabilities, and short revisit times offer new perspectives for change detection. Before performing any kind of change detection it is necessary to separate changes of interest from changes caused by differences in data acquisition parameters. In these cases it is necessary to perform a pre-processing to correct the data or to normalize it. Image registration and, corresponding to this task, the ortho-rectification of the image data is a further prerequisite for change detection. If feasible, a 1-to-1 geometric correspondence should be aspired for. Change detection on an iconic level with a succeeding interpretation of the changes by the observer is often proposed; nevertheless an automatic knowledge-based analysis delivering the interpretation of the changes on a semantic level should be the aim of the future. We present first results of change detection on a structural level concerning urban areas. After pre-processing, the images are segmented in areas of interest and structural analysis is applied to these regions to extract descriptions of urban infrastructure like buildings, roads and tanks of refineries. These descriptions are matched to detect changes and similarities.

  7. Distributed Pedestrian Detection Alerts Based on Data Fusion with Accurate Localization

    PubMed Central

    García, Fernando; Jiménez, Felipe; Anaya, José Javier; Armingol, José María; Naranjo, José Eugenio; de la Escalera, Arturo

    2013-01-01

    Among Advanced Driver Assistance Systems (ADAS) pedestrian detection is a common issue due to the vulnerability of pedestrians in the event of accidents. In the present work, a novel approach for pedestrian detection based on data fusion is presented. Data fusion helps to overcome the limitations inherent to each detection system (computer vision and laser scanner) and provides accurate and trustable tracking of any pedestrian movement. The application is complemented by an efficient communication protocol, able to alert vehicles in the surroundings by a fast and reliable communication. The combination of a powerful location, based on a GPS with inertial measurement, and accurate obstacle localization based on data fusion has allowed locating the detected pedestrians with high accuracy. Tests proved the viability of the detection system and the efficiency of the communication, even at long distances. By the use of the alert communication, dangerous situations such as occlusions or misdetections can be avoided. PMID:24008284

  8. Distributed pedestrian detection alerts based on data fusion with accurate localization.

    PubMed

    García, Fernando; Jiménez, Felipe; Anaya, José Javier; Armingol, José María; Naranjo, José Eugenio; de la Escalera, Arturo

    2013-09-04

    Among Advanced Driver Assistance Systems (ADAS) pedestrian detection is a common issue due to the vulnerability of pedestrians in the event of accidents. In the present work, a novel approach for pedestrian detection based on data fusion is presented. Data fusion helps to overcome the limitations inherent to each detection system (computer vision and laser scanner) and provides accurate and trustable tracking of any pedestrian movement. The application is complemented by an efficient communication protocol, able to alert vehicles in the surroundings by a fast and reliable communication. The combination of a powerful location, based on a GPS with inertial measurement, and accurate obstacle localization based on data fusion has allowed locating the detected pedestrians with high accuracy. Tests proved the viability of the detection system and the efficiency of the communication, even at long distances. By the use of the alert communication, dangerous situations such as occlusions or misdetections can be avoided.

  9. Breaking Snake Camouflage: Humans Detect Snakes More Accurately than Other Animals under Less Discernible Visual Conditions.

    PubMed

    Kawai, Nobuyuki; He, Hongshen

    2016-01-01

    Humans and non-human primates are extremely sensitive to snakes as exemplified by their ability to detect pictures of snakes more quickly than those of other animals. These findings are consistent with the Snake Detection Theory, which hypothesizes that as predators, snakes were a major source of evolutionary selection that favored expansion of the visual system of primates for rapid snake detection. Many snakes use camouflage to conceal themselves from both prey and their own predators, making it very challenging to detect them. If snakes have acted as a selective pressure on primate visual systems, they should be more easily detected than other animals under difficult visual conditions. Here we tested whether humans discerned images of snakes more accurately than those of non-threatening animals (e.g., birds, cats, or fish) under conditions of less perceptual information by presenting a series of degraded images with the Random Image Structure Evolution technique (interpolation of random noise). We find that participants recognize mosaic images of snakes, which were regarded as functionally equivalent to camouflage, more accurately than those of other animals under dissolved conditions. The present study supports the Snake Detection Theory by showing that humans have a visual system that accurately recognizes snakes under less discernible visual conditions.

  10. Breaking Snake Camouflage: Humans Detect Snakes More Accurately than Other Animals under Less Discernible Visual Conditions

    PubMed Central

    He, Hongshen

    2016-01-01

    Humans and non-human primates are extremely sensitive to snakes as exemplified by their ability to detect pictures of snakes more quickly than those of other animals. These findings are consistent with the Snake Detection Theory, which hypothesizes that as predators, snakes were a major source of evolutionary selection that favored expansion of the visual system of primates for rapid snake detection. Many snakes use camouflage to conceal themselves from both prey and their own predators, making it very challenging to detect them. If snakes have acted as a selective pressure on primate visual systems, they should be more easily detected than other animals under difficult visual conditions. Here we tested whether humans discerned images of snakes more accurately than those of non-threatening animals (e.g., birds, cats, or fish) under conditions of less perceptual information by presenting a series of degraded images with the Random Image Structure Evolution technique (interpolation of random noise). We find that participants recognize mosaic images of snakes, which were regarded as functionally equivalent to camouflage, more accurately than those of other animals under dissolved conditions. The present study supports the Snake Detection Theory by showing that humans have a visual system that accurately recognizes snakes under less discernible visual conditions. PMID:27783686

  11. Accurate means of detecting and characterizing abnormal patterns of ventricular activation by phase image analysis

    SciTech Connect

    Botvinick, E.H.; Frais, M.A.; Shosa, D.W.; O'Connell, J.W.; Pacheco-Alvarez, J.A.; Scheinman, M.; Hattner, R.S.; Morady, F.; Faulkner, D.B.

    1982-08-01

    The ability of scintigraphic phase image analysis to characterize patterns of abnormal ventricular activation was investigated. The pattern of phase distribution and sequential phase changes over both right and left ventricular regions of interest were evaluated in 16 patients with normal electrical activation and wall motion and compared with those in 8 patients with an artificial pacemaker and 4 patients with sinus rhythm with the Wolff-Parkinson-White syndrome and delta waves. Normally, the site of earliest phase angle was seen at the base of the interventricular septum, with sequential change affecting the body of the septum and the cardiac apex and then spreading laterally to involve the body of both ventricles. The site of earliest phase angle was located at the apex of the right ventricle in seven patients with a right ventricular endocardial pacemaker and on the lateral left ventricular wall in one patient with a left ventricular epicardial pacemaker. In each case the site corresponded exactly to the position of the pacing electrode as seen on posteroanterior and left lateral chest X-ray films, and sequential phase changes spread from the initial focus to affect both ventricles. In each of the patients with the Wolff-Parkinson-White syndrome, the site of earliest ventricular phase angle was located, and it corresponded exactly to the site of the bypass tract as determined by endocardial mapping. In this way, four bypass pathways, two posterior left paraseptal, one left lateral and one right lateral, were correctly localized scintigraphically. On the basis of the sequence of mechanical contraction, phase image analysis provides an accurate noninvasive method of detecting abnormal foci of ventricular activation.

  12. Accurate band-to-band registration of AOTF imaging spectrometer using motion detection technology

    NASA Astrophysics Data System (ADS)

    Zhou, Pengwei; Zhao, Huijie; Jin, Shangzhong; Li, Ningchuan

    2016-05-01

    This paper concerns the problem of platform vibration induced band-to-band misregistration with acousto-optic imaging spectrometer in spaceborne application. Registrating images of different bands formed at different time or different position is difficult, especially for hyperspectral images form acousto-optic tunable filter (AOTF) imaging spectrometer. In this study, a motion detection method is presented using the polychromatic undiffracted beam of AOTF. The factors affecting motion detect accuracy are analyzed theoretically, and calculations show that optical distortion is an easily overlooked factor to achieve accurate band-to-band registration. Hence, a reflective dual-path optical system has been proposed for the first time, with reduction of distortion and chromatic aberration, indicating the potential of higher registration accuracy. Consequently, a spectra restoration experiment using additional motion detect channel is presented for the first time, which shows the accurate spectral image registration capability of this technique.

  13. Accurate lithography hotspot detection based on PCA-SVM classifier with hierarchical data clustering

    NASA Astrophysics Data System (ADS)

    Gao, Jhih-Rong; Yu, Bei; Pan, David Z.

    2014-03-01

    As technology nodes continues shrinking, layout patterns become more sensitive to lithography processes, resulting in lithography hotspots that need to be identified and eliminated during physical verification. In this paper, we propose an accurate hotspot detection approach based on PCA (principle component analysis)-SVM (sup- port vector machine) classifier. Several techniques, including hierarchical data clustering, data balancing, and multi-level training, are provided to enhance performance of the proposed approach. Our approach is accurate and more efficient than conventional time-consuming lithography simulation; in the meanwhile, provides high flexibility to adapt to new lithography processes and rules.

  14. Accurate derivation of heart rate variability signal for detection of sleep disordered breathing in children.

    PubMed

    Chatlapalli, S; Nazeran, H; Melarkod, V; Krishnam, R; Estrada, E; Pamula, Y; Cabrera, S

    2004-01-01

    The electrocardiogram (ECG) signal is used extensively as a low cost diagnostic tool to provide information concerning the heart's state of health. Accurate determination of the QRS complex, in particular, reliable detection of the R wave peak, is essential in computer based ECG analysis. ECG data from Physionet's Sleep-Apnea database were used to develop, test, and validate a robust heart rate variability (HRV) signal derivation algorithm. The HRV signal was derived from pre-processed ECG signals by developing an enhanced Hilbert transform (EHT) algorithm with built-in missing beat detection capability for reliable QRS detection. The performance of the EHT algorithm was then compared against that of a popular Hilbert transform-based (HT) QRS detection algorithm. Autoregressive (AR) modeling of the HRV power spectrum for both EHT- and HT-derived HRV signals was achieved and different parameters from their power spectra as well as approximate entropy were derived for comparison. Poincare plots were then used as a visualization tool to highlight the detection of the missing beats in the EHT method After validation of the EHT algorithm on ECG data from the Physionet, the algorithm was further tested and validated on a dataset obtained from children undergoing polysomnography for detection of sleep disordered breathing (SDB). Sensitive measures of accurate HRV signals were then derived to be used in detecting and diagnosing sleep disordered breathing in children. All signal processing algorithms were implemented in MATLAB. We present a description of the EHT algorithm and analyze pilot data for eight children undergoing nocturnal polysomnography. The pilot data demonstrated that the EHT method provides an accurate way of deriving the HRV signal and plays an important role in extraction of reliable measures to distinguish between periods of normal and sleep disordered breathing (SDB) in children.

  15. Robust and Accurate Anomaly Detection in ECG Artifacts Using Time Series Motif Discovery

    PubMed Central

    Sivaraks, Haemwaan

    2015-01-01

    Electrocardiogram (ECG) anomaly detection is an important technique for detecting dissimilar heartbeats which helps identify abnormal ECGs before the diagnosis process. Currently available ECG anomaly detection methods, ranging from academic research to commercial ECG machines, still suffer from a high false alarm rate because these methods are not able to differentiate ECG artifacts from real ECG signal, especially, in ECG artifacts that are similar to ECG signals in terms of shape and/or frequency. The problem leads to high vigilance for physicians and misinterpretation risk for nonspecialists. Therefore, this work proposes a novel anomaly detection technique that is highly robust and accurate in the presence of ECG artifacts which can effectively reduce the false alarm rate. Expert knowledge from cardiologists and motif discovery technique is utilized in our design. In addition, every step of the algorithm conforms to the interpretation of cardiologists. Our method can be utilized to both single-lead ECGs and multilead ECGs. Our experiment results on real ECG datasets are interpreted and evaluated by cardiologists. Our proposed algorithm can mostly achieve 100% of accuracy on detection (AoD), sensitivity, specificity, and positive predictive value with 0% false alarm rate. The results demonstrate that our proposed method is highly accurate and robust to artifacts, compared with competitive anomaly detection methods. PMID:25688284

  16. Robust and accurate anomaly detection in ECG artifacts using time series motif discovery.

    PubMed

    Sivaraks, Haemwaan; Ratanamahatana, Chotirat Ann

    2015-01-01

    Electrocardiogram (ECG) anomaly detection is an important technique for detecting dissimilar heartbeats which helps identify abnormal ECGs before the diagnosis process. Currently available ECG anomaly detection methods, ranging from academic research to commercial ECG machines, still suffer from a high false alarm rate because these methods are not able to differentiate ECG artifacts from real ECG signal, especially, in ECG artifacts that are similar to ECG signals in terms of shape and/or frequency. The problem leads to high vigilance for physicians and misinterpretation risk for nonspecialists. Therefore, this work proposes a novel anomaly detection technique that is highly robust and accurate in the presence of ECG artifacts which can effectively reduce the false alarm rate. Expert knowledge from cardiologists and motif discovery technique is utilized in our design. In addition, every step of the algorithm conforms to the interpretation of cardiologists. Our method can be utilized to both single-lead ECGs and multilead ECGs. Our experiment results on real ECG datasets are interpreted and evaluated by cardiologists. Our proposed algorithm can mostly achieve 100% of accuracy on detection (AoD), sensitivity, specificity, and positive predictive value with 0% false alarm rate. The results demonstrate that our proposed method is highly accurate and robust to artifacts, compared with competitive anomaly detection methods.

  17. An accurate assay for HCV based on real-time fluorescence detection of isothermal RNA amplification.

    PubMed

    Wu, Xuping; Wang, Jianfang; Song, Jinyun; Li, Jiayan; Yang, Yongfeng

    2016-09-01

    Hepatitis C virus (HCV) is one of the common reasons of liver fibrosis and hepatocellular carcinoma (HCC). Early, rapid and accurate HCV RNA detection is important to prevent and control liver disease. A simultaneous amplification and testing (SAT) assay, which is based on isothermal amplification of RNA and real-time fluorescence detection, was designed to optimize routine HCV RNA detection. In this study, HCV RNA and an internal control (IC) were amplified and analyzed simultaneously by SAT assay and detection of fluorescence using routine real-time PCR equipment. The assay detected as few as 10 copies of HCV RNA transcripts. We tested 705 serum samples with SAT, among which 96.4% (680/705) showed consistent results compared with routine real-time PCR. About 92% (23/25) discordant samples were confirmed to be same results as SAT-HCV by using a second real-time PCR. The sensitivity and specificity of SAT-HCV assay were 99.6% (461/463) and 100% (242/242), respectively. In conclusion, the SAT assay is an accurate test with a high specificity and sensitivity which may increase the detection rate of HCV. It is therefore a promising tool to diagnose HCV infection.

  18. Accurate Automatic Detection of Densely Distributed Cell Nuclei in 3D Space

    PubMed Central

    Tokunaga, Terumasa; Kanamori, Manami; Teramoto, Takayuki; Jang, Moon Sun; Kuge, Sayuri; Ishihara, Takeshi; Yoshida, Ryo; Iino, Yuichi

    2016-01-01

    To measure the activity of neurons using whole-brain activity imaging, precise detection of each neuron or its nucleus is required. In the head region of the nematode C. elegans, the neuronal cell bodies are distributed densely in three-dimensional (3D) space. However, no existing computational methods of image analysis can separate them with sufficient accuracy. Here we propose a highly accurate segmentation method based on the curvatures of the iso-intensity surfaces. To obtain accurate positions of nuclei, we also developed a new procedure for least squares fitting with a Gaussian mixture model. Combining these methods enables accurate detection of densely distributed cell nuclei in a 3D space. The proposed method was implemented as a graphical user interface program that allows visualization and correction of the results of automatic detection. Additionally, the proposed method was applied to time-lapse 3D calcium imaging data, and most of the nuclei in the images were successfully tracked and measured. PMID:27271939

  19. Highly accurate moving object detection in variable bit rate video-based traffic monitoring systems.

    PubMed

    Huang, Shih-Chia; Chen, Bo-Hao

    2013-12-01

    Automated motion detection, which segments moving objects from video streams, is the key technology of intelligent transportation systems for traffic management. Traffic surveillance systems use video communication over real-world networks with limited bandwidth, which frequently suffers because of either network congestion or unstable bandwidth. Evidence supporting these problems abounds in publications about wireless video communication. Thus, to effectively perform the arduous task of motion detection over a network with unstable bandwidth, a process by which bit-rate is allocated to match the available network bandwidth is necessitated. This process is accomplished by the rate control scheme. This paper presents a new motion detection approach that is based on the cerebellar-model-articulation-controller (CMAC) through artificial neural networks to completely and accurately detect moving objects in both high and low bit-rate video streams. The proposed approach is consisted of a probabilistic background generation (PBG) module and a moving object detection (MOD) module. To ensure that the properties of variable bit-rate video streams are accommodated, the proposed PBG module effectively produces a probabilistic background model through an unsupervised learning process over variable bit-rate video streams. Next, the MOD module, which is based on the CMAC network, completely and accurately detects moving objects in both low and high bit-rate video streams by implementing two procedures: 1) a block selection procedure and 2) an object detection procedure. The detection results show that our proposed approach is capable of performing with higher efficacy when compared with the results produced by other state-of-the-art approaches in variable bit-rate video streams over real-world limited bandwidth networks. Both qualitative and quantitative evaluations support this claim; for instance, the proposed approach achieves Similarity and F1 accuracy rates that are 76

  20. Land-cover change detection

    USGS Publications Warehouse

    Chen, Xuexia; Giri, Chandra; Vogelmann, James

    2012-01-01

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

  1. Automatic identification and accurate temporal detection of inhalations in asthma inhaler recordings.

    PubMed

    Holmes, Martin S; Le Menn, Marine; D'Arcy, Shona; Rapcan, Viliam; MacHale, Elaine; Costello, Richard W; Reilly, Richard B

    2012-01-01

    Asthma is chronic airways disease characterized by recurrent attacks of breathlessness and wheezing. Adherence to medication regimes is a common failing for asthmatic patients and there exists a requirement to monitor such patients' adherence. The detection of inhalations from recordings of inhaler use can provide empirical evidence about patients' adherence to their asthma medication regime. Manually listening to recordings of inhaler use is a tedious and time consuming process and thus an algorithm which can automatically and accurately carry out this task would be of great value. This study employs a recording device attached to a commonly used dry powder inhaler to record the acoustic signals of patients taking their prescribed medication. An algorithm was developed to automatically detect and accurately demarcate inhalations from the acoustic signals. This algorithm was tested on a dataset of 255 separate recordings of inhaler use in real world environments. The dataset was obtained from 12 asthma outpatients who attended a respiratory clinic over a three month period. Evaluation of the algorithm on this dataset achieved sensitivity of 95%, specificity of 94% and an accuracy of 89% in detecting inhalations compared to manual inhalation detection.

  2. SAR Object Change Detection Study.

    DTIC Science & Technology

    1980-03-01

    based techniques when applied to Synthetic Aperature Radar (SAR imagery. DOUGLA 3. PRASKA, 2LT, USAF Project Engineer viii Section 1 INTRODUCTION AND...to assess the applicability of three region-based change-detection methods to synthetic aperture radar imagery. I/ Ac .0ion For K:CTAB [ ft i . i...Section 2, the algorithms developed were applied to synthetic -aperture radar image data furnished by RADC. Some preprocessing of all images was required

  3. Detecting changes during pregnancy with Raman spectroscopy

    NASA Astrophysics Data System (ADS)

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

    2010-02-01

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

  4. Urban change detection procedures using Landsat digital data

    NASA Technical Reports Server (NTRS)

    Jensen, J. R.; Toll, D. L.

    1982-01-01

    Landsat multispectral scanner data was applied to an urban change detection problem in Denver, CO. A dichotomous key yielding ten stages of residential development at the urban fringe was developed. This heuristic model allowed one to identify certain stages of development which are difficult to detect when performing digital change detection using Landsat data. The stages of development were evaluated in terms of their spectral and derived textural characteristics. Landsat band 5 (0.6-0.7 micron) and texture data produced change detection maps which were approximately 81 percent accurate. Results indicated that the stage of development and the spectral/textural features affect the change in the spectral values used for change detection. These preliminary findings will hopefully prove valuable for improved change detection at the urban fringe.

  5. Continuous digital ECG analysis over accurate R-peak detection using adaptive wavelet technique.

    PubMed

    Gopalakrishnan Nair, T R; Geetha, A P; Asharani, M

    2013-10-01

    Worldwide, health care segment is under a severe challenge to achieve more accurate and intelligent biomedical systems in order to assist healthcare professionals with more accurate and consistent data as well as reliability. The role of ECG in healthcare is one of the paramount importances and it has got a multitude of abnormal relations and anomalies which characterizes intricate cardiovascular performance image. Until the recent past, ECG instruments and analysis played the role of providing the PQRST signal as raw observational output either on paper or on a console or in a file having many diagnostic clues embedded in the signal left to the expert cardiologist to look out for characteristic intervals and to detect the cardiovascular abnormality. Methods and practises are required more and more, to automate this process of cardiac expertise using knowledge engineering and an intelligent systems approach. This paper presents one of the challenging R-peak detections to classify diagnosis and estimate cardio disorders in a fully automated signal processing sequence. This study used an adaptive wavelet approach to generate an appropriate wavelet for R-signal identification under noise, baseband wandering and temporal variations of R-positions. This study designed an adaptive wavelet and successfully detected R- peak variations under various ECG signal conditions. The result and analysis of this method and the ways to use it for further purposes are presented here.

  6. Methodological Guidelines for Accurate Detection of Viruses in Wild Plant Species.

    PubMed

    Lacroix, Christelle; Renner, Kurra; Cole, Ellen; Seabloom, Eric W; Borer, Elizabeth T; Malmstrom, Carolyn M

    2016-01-15

    Ecological understanding of disease risk, emergence, and dynamics and of the efficacy of control strategies relies heavily on efficient tools for microorganism identification and characterization. Misdetection, such as the misclassification of infected hosts as healthy, can strongly bias estimates of disease prevalence and lead to inaccurate conclusions. In natural plant ecosystems, interest in assessing microbial dynamics is increasing exponentially, but guidelines for detection of microorganisms in wild plants remain limited, particularly so for plant viruses. To address this gap, we explored issues and solutions associated with virus detection by serological and molecular methods in noncrop plant species as applied to the globally important Barley yellow dwarf virus PAV (Luteoviridae), which infects wild native plants as well as crops. With enzyme-linked immunosorbent assays (ELISA), we demonstrate how virus detection in a perennial wild plant species may be much greater in stems than in leaves, although leaves are most commonly sampled, and may also vary among tillers within an individual, thereby highlighting the importance of designing effective sampling strategies. With reverse transcription-PCR (RT-PCR), we demonstrate how inhibitors in tissues of perennial wild hosts can suppress virus detection but can be overcome with methods and products that improve isolation and amplification of nucleic acids. These examples demonstrate the paramount importance of testing and validating survey designs and virus detection methods for noncrop plant communities to ensure accurate ecological surveys and reliable assumptions about virus dynamics in wild hosts.

  7. Accurate detection and quantitation of heteroplasmic mitochondrial point mutations by pyrosequencing.

    PubMed

    White, Helen E; Durston, Victoria J; Seller, Anneke; Fratter, Carl; Harvey, John F; Cross, Nicholas C P

    2005-01-01

    Disease-causing mutations in mitochondrial DNA (mtDNA) are typically heteroplasmic and therefore interpretation of genetic tests for mitochondrial disorders can be problematic. Detection of low level heteroplasmy is technically demanding and it is often difficult to discriminate between the absence of a mutation or the failure of a technique to detect the mutation in a particular tissue. The reliable measurement of heteroplasmy in different tissues may help identify individuals who are at risk of developing specific complications and allow improved prognostic advice for patients and family members. We have evaluated Pyrosequencing technology for the detection and estimation of heteroplasmy for six mitochondrial point mutations associated with the following diseases: Leber's hereditary optical neuropathy (LHON), G3460A, G11778A, and T14484C; mitochondrial encephalopathy with lactic acidosis and stroke-like episodes (MELAS), A3243G; myoclonus epilepsy with ragged red fibers (MERRF), A8344G, and neurogenic muscle weakness, ataxia, and retinitis pigmentosa (NARP)/Leighs: T8993G/C. Results obtained from the Pyrosequencing assays for 50 patients with presumptive mitochondrial disease were compared to those obtained using the commonly used diagnostic technique of polymerase chain reaction (PCR) and restriction enzyme digestion. The Pyrosequencing assays provided accurate genotyping and quantitative determination of mutational load with a sensitivity and specificity of 100%. The MELAS A3243G mutation was detected reliably at a level of 1% heteroplasmy. We conclude that Pyrosequencing is a rapid and robust method for detecting heteroplasmic mitochondrial point mutations.

  8. Methodological Guidelines for Accurate Detection of Viruses in Wild Plant Species

    PubMed Central

    Renner, Kurra; Cole, Ellen; Seabloom, Eric W.; Borer, Elizabeth T.; Malmstrom, Carolyn M.

    2016-01-01

    Ecological understanding of disease risk, emergence, and dynamics and of the efficacy of control strategies relies heavily on efficient tools for microorganism identification and characterization. Misdetection, such as the misclassification of infected hosts as healthy, can strongly bias estimates of disease prevalence and lead to inaccurate conclusions. In natural plant ecosystems, interest in assessing microbial dynamics is increasing exponentially, but guidelines for detection of microorganisms in wild plants remain limited, particularly so for plant viruses. To address this gap, we explored issues and solutions associated with virus detection by serological and molecular methods in noncrop plant species as applied to the globally important Barley yellow dwarf virus PAV (Luteoviridae), which infects wild native plants as well as crops. With enzyme-linked immunosorbent assays (ELISA), we demonstrate how virus detection in a perennial wild plant species may be much greater in stems than in leaves, although leaves are most commonly sampled, and may also vary among tillers within an individual, thereby highlighting the importance of designing effective sampling strategies. With reverse transcription-PCR (RT-PCR), we demonstrate how inhibitors in tissues of perennial wild hosts can suppress virus detection but can be overcome with methods and products that improve isolation and amplification of nucleic acids. These examples demonstrate the paramount importance of testing and validating survey designs and virus detection methods for noncrop plant communities to ensure accurate ecological surveys and reliable assumptions about virus dynamics in wild hosts. PMID:26773088

  9. On Radar Resolution in Coherent Change Detection.

    SciTech Connect

    Bickel, Douglas L.

    2015-11-01

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

  10. A simplified and accurate detection of the genetically modified wheat MON71800 with one calibrator plasmid.

    PubMed

    Kim, Jae-Hwan; Park, Saet-Byul; Roh, Hyo-Jeong; Park, Sunghoon; Shin, Min-Ki; Moon, Gui Im; Hong, Jin-Hwan; Kim, Hae-Yeong

    2015-06-01

    With the increasing number of genetically modified (GM) events, unauthorized GMO releases into the food market have increased dramatically, and many countries have developed detection tools for them. This study described the qualitative and quantitative detection methods of unauthorized the GM wheat MON71800 with a reference plasmid (pGEM-M71800). The wheat acetyl-CoA carboxylase (acc) gene was used as the endogenous gene. The plasmid pGEM-M71800, which contains both the acc gene and the event-specific target MON71800, was constructed as a positive control for the qualitative and quantitative analyses. The limit of detection in the qualitative PCR assay was approximately 10 copies. In the quantitative PCR assay, the standard deviation and relative standard deviation repeatability values ranged from 0.06 to 0.25 and from 0.23% to 1.12%, respectively. This study supplies a powerful and very simple but accurate detection strategy for unauthorized GM wheat MON71800 that utilizes a single calibrator plasmid.

  11. Land Cover Change Detection Using Saliency Andwavelet Transformation

    NASA Astrophysics Data System (ADS)

    Zhang, Haopeng; Jiang, Zhiguo; Cheng, Yan

    2016-06-01

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

  12. A highly accurate wireless digital sun sensor based on profile detecting and detector multiplexing technologies

    NASA Astrophysics Data System (ADS)

    Wei, Minsong; Xing, Fei; You, Zheng

    2017-01-01

    The advancing growth of micro- and nano-satellites requires miniaturized sun sensors which could be conveniently applied in the attitude determination subsystem. In this work, a profile detecting technology based high accurate wireless digital sun sensor was proposed, which could transform a two-dimensional image into two-linear profile output so that it can realize a high update rate under a very low power consumption. A multiple spots recovery approach with an asymmetric mask pattern design principle was introduced to fit the multiplexing image detector method for accuracy improvement of the sun sensor within a large Field of View (FOV). A FOV determination principle based on the concept of FOV region was also proposed to facilitate both sub-FOV analysis and the whole FOV determination. A RF MCU, together with solar cells, was utilized to achieve the wireless and self-powered functionality. The prototype of the sun sensor is approximately 10 times lower in size and weight compared with the conventional digital sun sensor (DSS). Test results indicated that the accuracy of the prototype was 0.01° within a cone FOV of 100°. Such an autonomous DSS could be equipped flexibly on a micro- or nano-satellite, especially for highly accurate remote sensing applications.

  13. Joint iris boundary detection and fit: a real-time method for accurate pupil tracking.

    PubMed

    Barbosa, Marconi; James, Andrew C

    2014-08-01

    A range of applications in visual science rely on accurate tracking of the human pupil's movement and contraction in response to light. While the literature for independent contour detection and fitting of the iris-pupil boundary is vast, a joint approach, in which it is assumed that the pupil has a given geometric shape has been largely overlooked. We present here a global method for simultaneously finding and fitting of an elliptic or circular contour against a dark interior, which produces consistently accurate results even under non-ideal recording conditions, such as reflections near and over the boundary, droopy eye lids, or the sudden formation of tears. The specific form of the proposed optimization problem allows us to write down closed analytic formulae for the gradient and the Hessian of the objective function. Moreover, both the objective function and its derivatives can be cast into vectorized form, making the proposed algorithm significantly faster than its closest relative in the literature. We compare methods in multiple ways, both analytically and numerically, using real iris images as well as idealizations of the iris for which the ground truth boundary is precisely known. The method proposed here is illustrated under challenging recording conditions and it is shown to be robust.

  14. Joint iris boundary detection and fit: a real-time method for accurate pupil tracking

    PubMed Central

    Barbosa, Marconi; James, Andrew C.

    2014-01-01

    A range of applications in visual science rely on accurate tracking of the human pupil’s movement and contraction in response to light. While the literature for independent contour detection and fitting of the iris-pupil boundary is vast, a joint approach, in which it is assumed that the pupil has a given geometric shape has been largely overlooked. We present here a global method for simultaneously finding and fitting of an elliptic or circular contour against a dark interior, which produces consistently accurate results even under non-ideal recording conditions, such as reflections near and over the boundary, droopy eye lids, or the sudden formation of tears. The specific form of the proposed optimization problem allows us to write down closed analytic formulae for the gradient and the Hessian of the objective function. Moreover, both the objective function and its derivatives can be cast into vectorized form, making the proposed algorithm significantly faster than its closest relative in the literature. We compare methods in multiple ways, both analytically and numerically, using real iris images as well as idealizations of the iris for which the ground truth boundary is precisely known. The method proposed here is illustrated under challenging recording conditions and it is shown to be robust. PMID:25136477

  15. Accurate Monitoring and Fault Detection in Wind Measuring Devices through Wireless Sensor Networks

    PubMed Central

    Khan, Komal Saifullah; Tariq, Muhammad

    2014-01-01

    Many wind energy projects report poor performance as low as 60% of the predicted performance. The reason for this is poor resource assessment and the use of new untested technologies and systems in remote locations. Predictions about the potential of an area for wind energy projects (through simulated models) may vary from the actual potential of the area. Hence, introducing accurate site assessment techniques will lead to accurate predictions of energy production from a particular area. We solve this problem by installing a Wireless Sensor Network (WSN) to periodically analyze the data from anemometers installed in that area. After comparative analysis of the acquired data, the anemometers transmit their readings through a WSN to the sink node for analysis. The sink node uses an iterative algorithm which sequentially detects any faulty anemometer and passes the details of the fault to the central system or main station. We apply the proposed technique in simulation as well as in practical implementation and study its accuracy by comparing the simulation results with experimental results to analyze the variation in the results obtained from both simulation model and implemented model. Simulation results show that the algorithm indicates faulty anemometers with high accuracy and low false alarm rate when as many as 25% of the anemometers become faulty. Experimental analysis shows that anemometers incorporating this solution are better assessed and performance level of implemented projects is increased above 86% of the simulated models. PMID:25421739

  16. Accurate monitoring and fault detection in wind measuring devices through wireless sensor networks.

    PubMed

    Khan, Komal Saifullah; Tariq, Muhammad

    2014-11-24

    Many wind energy projects report poor performance as low as 60% of the predicted performance. The reason for this is poor resource assessment and the use of new untested technologies and systems in remote locations. Predictions about the potential of an area for wind energy projects (through simulated models) may vary from the actual potential of the area. Hence, introducing accurate site assessment techniques will lead to accurate predictions of energy production from a particular area. We solve this problem by installing a Wireless Sensor Network (WSN) to periodically analyze the data from anemometers installed in that area. After comparative analysis of the acquired data, the anemometers transmit their readings through a WSN to the sink node for analysis. The sink node uses an iterative algorithm which sequentially detects any faulty anemometer and passes the details of the fault to the central system or main station. We apply the proposed technique in simulation as well as in practical implementation and study its accuracy by comparing the simulation results with experimental results to analyze the variation in the results obtained from both simulation model and implemented model. Simulation results show that the algorithm indicates faulty anemometers with high accuracy and low false alarm rate when as many as 25% of the anemometers become faulty. Experimental analysis shows that anemometers incorporating this solution are better assessed and performance level of implemented projects is increased above 86% of the simulated models.

  17. ROM Plus®: accurate point-of-care detection of ruptured fetal membranes

    PubMed Central

    McQuivey, Ross W; Block, Jon E

    2016-01-01

    Accurate and timely diagnosis of rupture of fetal membranes is imperative to inform and guide gestational age-specific interventions to optimize perinatal outcomes and reduce the risk of serious complications, including preterm delivery and infections. The ROM Plus is a rapid, point-of-care, qualitative immunochromatographic diagnostic test that uses a unique monoclonal/polyclonal antibody approach to detect two different proteins found in amniotic fluid at high concentrations: alpha-fetoprotein and insulin-like growth factor binding protein-1. Clinical study results have uniformly demonstrated high diagnostic accuracy and performance characteristics with this point-of-care test that exceeds conventional clinical testing with external laboratory evaluation. The description, indications for use, procedural steps, and laboratory and clinical characterization of this assay are presented in this article. PMID:27274316

  18. ROM Plus(®): accurate point-of-care detection of ruptured fetal membranes.

    PubMed

    McQuivey, Ross W; Block, Jon E

    2016-01-01

    Accurate and timely diagnosis of rupture of fetal membranes is imperative to inform and guide gestational age-specific interventions to optimize perinatal outcomes and reduce the risk of serious complications, including preterm delivery and infections. The ROM Plus is a rapid, point-of-care, qualitative immunochromatographic diagnostic test that uses a unique monoclonal/polyclonal antibody approach to detect two different proteins found in amniotic fluid at high concentrations: alpha-fetoprotein and insulin-like growth factor binding protein-1. Clinical study results have uniformly demonstrated high diagnostic accuracy and performance characteristics with this point-of-care test that exceeds conventional clinical testing with external laboratory evaluation. The description, indications for use, procedural steps, and laboratory and clinical characterization of this assay are presented in this article.

  19. Medical Image Watermarking Technique for Accurate Tamper Detection in ROI and Exact Recovery of ROI.

    PubMed

    Eswaraiah, R; Sreenivasa Reddy, E

    2014-01-01

    In telemedicine while transferring medical images tampers may be introduced. Before making any diagnostic decisions, the integrity of region of interest (ROI) of the received medical image must be verified to avoid misdiagnosis. In this paper, we propose a novel fragile block based medical image watermarking technique to avoid embedding distortion inside ROI, verify integrity of ROI, detect accurately the tampered blocks inside ROI, and recover the original ROI with zero loss. In this proposed method, the medical image is segmented into three sets of pixels: ROI pixels, region of noninterest (RONI) pixels, and border pixels. Then, authentication data and information of ROI are embedded in border pixels. Recovery data of ROI is embedded into RONI. Results of experiments conducted on a number of medical images reveal that the proposed method produces high quality watermarked medical images, identifies the presence of tampers inside ROI with 100% accuracy, and recovers the original ROI without any loss.

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

    PubMed

    Gerhard, Holly E; Maloney, Laurence T

    2010-07-16

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

  1. 3D change detection - Approaches and applications

    NASA Astrophysics Data System (ADS)

    Qin, Rongjun; Tian, Jiaojiao; Reinartz, Peter

    2016-12-01

    Due to the unprecedented technology development of sensors, platforms and algorithms for 3D data acquisition and generation, 3D spaceborne, airborne and close-range data, in the form of image based, Light Detection and Ranging (LiDAR) based point clouds, Digital Elevation Models (DEM) and 3D city models, become more accessible than ever before. Change detection (CD) or time-series data analysis in 3D has gained great attention due to its capability of providing volumetric dynamics to facilitate more applications and provide more accurate results. The state-of-the-art CD reviews aim to provide a comprehensive synthesis and to simplify the taxonomy of the traditional remote sensing CD techniques, which mainly sit within the boundary of 2D image/spectrum analysis, largely ignoring the particularities of 3D aspects of the data. The inclusion of 3D data for change detection (termed 3D CD), not only provides a source with different modality for analysis, but also transcends the border of traditional top-view 2D pixel/object-based analysis to highly detailed, oblique view or voxel-based geometric analysis. This paper reviews the recent developments and applications of 3D CD using remote sensing and close-range data, in support of both academia and industry researchers who seek for solutions in detecting and analyzing 3D dynamics of various objects of interest. We first describe the general considerations of 3D CD problems in different processing stages and identify CD types based on the information used, being the geometric comparison and geometric-spectral analysis. We then summarize relevant works and practices in urban, environment, ecology and civil applications, etc. Given the broad spectrum of applications and different types of 3D data, we discuss important issues in 3D CD methods. Finally, we present concluding remarks in algorithmic aspects of 3D CD.

  2. Experiments in Coherent Change Detection for Synthetic Aperture Sonar

    DTIC Science & Technology

    2010-06-01

    over time. ACD techniques, long used in airborne radar applications, are just beginning to be applied to sidescan sonar . In Coherent Change Detection...accurate geo- registration), the complexity of the propagation environment, and the radiometric inconsistencies of conventional sidescan sonars ...will follow suit. As conventional sidescan sonars exhibit resolution that degrades with range and are typically limited to creation of backscatter

  3. An accurate heart beat detection method in the EKG recorded in fMRI system.

    PubMed

    Oh, Sung Suk; Chung, Jun-Young; Yoon, Hyo Woon; Park, HyunWook

    2007-01-01

    The simultaneous recording of functional magnetic resonance imaging (fMRI) and electroencephalogram (EEG) provides an efficient signal for the high spatiotemporal brain mapping because each modality provides complementary information. The peak detection in the EEG signal measured in the MR scanner is necessary for removal of the ballistocardiac artifact. Especially, it would be affected by the quality of the EKG signal and the variation of the heart beat rate. Therefore, we propose the peak detection method using a K-teager energy operator (K-TEO) as well as further refinement processes in order to detect precise peaks. We applied this technique to the analysis of simulation waves with random noise and abrupt heat beat changes.

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

    PubMed Central

    Hammer, Rubi; Cooke, Gillian E.; Stein, Mark A.; Booth, James R.

    2015-01-01

    Finding neurobiological markers for neurodevelopmental disorders, such as attention deficit and hyperactivity disorder (ADHD), is a major objective of clinicians and neuroscientists. We examined if functional Magnetic Resonance Imaging (fMRI) data from a few distinct visuospatial working memory (VSWM) tasks enables accurately detecting cases with ADHD. We tested 20 boys with ADHD combined type and 20 typically developed (TD) boys in four VSWM tasks that differed in feedback availability (feedback, no-feedback) and reward size (large, small). We used a multimodal analysis based on brain activity in 16 regions of interest, significantly activated or deactivated in the four VSWM tasks (based on the entire participants' sample). Dimensionality of the data was reduced into 10 principal components that were used as the input variables to a logistic regression classifier. fMRI data from the four VSWM tasks enabled a classification accuracy of 92.5%, with high predicted ADHD probability values for most clinical cases, and low predicted ADHD probabilities for most TDs. This accuracy level was higher than those achieved by using the fMRI data of any single task, or the respective behavioral data. This indicates that task-based fMRI data acquired while participants perform a few distinct VSWM tasks enables improved detection of clinical cases. PMID:26509111

  5. COSMOS: accurate detection of somatic structural variations through asymmetric comparison between tumor and normal samples.

    PubMed

    Yamagata, Koichi; Yamanishi, Ayako; Kokubu, Chikara; Takeda, Junji; Sese, Jun

    2016-05-05

    An important challenge in cancer genomics is precise detection of structural variations (SVs) by high-throughput short-read sequencing, which is hampered by the high false discovery rates of existing analysis tools. Here, we propose an accurate SV detection method named COSMOS, which compares the statistics of the mapped read pairs in tumor samples with isogenic normal control samples in a distinct asymmetric manner. COSMOS also prioritizes the candidate SVs using strand-specific read-depth information. Performance tests on modeled tumor genomes revealed that COSMOS outperformed existing methods in terms of F-measure. We also applied COSMOS to an experimental mouse cell-based model, in which SVs were induced by genome engineering and gamma-ray irradiation, followed by polymerase chain reaction-based confirmation. The precision of COSMOS was 84.5%, while the next best existing method was 70.4%. Moreover, the sensitivity of COSMOS was the highest, indicating that COSMOS has great potential for cancer genome analysis.

  6. COSMOS: accurate detection of somatic structural variations through asymmetric comparison between tumor and normal samples

    PubMed Central

    Yamagata, Koichi; Yamanishi, Ayako; Kokubu, Chikara; Takeda, Junji; Sese, Jun

    2016-01-01

    An important challenge in cancer genomics is precise detection of structural variations (SVs) by high-throughput short-read sequencing, which is hampered by the high false discovery rates of existing analysis tools. Here, we propose an accurate SV detection method named COSMOS, which compares the statistics of the mapped read pairs in tumor samples with isogenic normal control samples in a distinct asymmetric manner. COSMOS also prioritizes the candidate SVs using strand-specific read-depth information. Performance tests on modeled tumor genomes revealed that COSMOS outperformed existing methods in terms of F-measure. We also applied COSMOS to an experimental mouse cell-based model, in which SVs were induced by genome engineering and gamma-ray irradiation, followed by polymerase chain reaction-based confirmation. The precision of COSMOS was 84.5%, while the next best existing method was 70.4%. Moreover, the sensitivity of COSMOS was the highest, indicating that COSMOS has great potential for cancer genome analysis. PMID:26833260

  7. Can phenological models predict tree phenology accurately under climate change conditions?

    NASA Astrophysics Data System (ADS)

    Chuine, Isabelle; Bonhomme, Marc; Legave, Jean Michel; García de Cortázar-Atauri, Inaki; Charrier, Guillaume; Lacointe, André; Améglio, Thierry

    2014-05-01

    The onset of the growing season of trees has been globally earlier by 2.3 days/decade during the last 50 years because of global warming and this trend is predicted to continue according to climate forecast. The effect of temperature on plant phenology is however not linear because temperature has a dual effect on bud development. On one hand, low temperatures are necessary to break bud dormancy, and on the other hand higher temperatures are necessary to promote bud cells growth afterwards. Increasing phenological changes in temperate woody species have strong impacts on forest trees distribution and productivity, as well as crops cultivation areas. Accurate predictions of trees phenology are therefore a prerequisite to understand and foresee the impacts of climate change on forests and agrosystems. Different process-based models have been developed in the last two decades to predict the date of budburst or flowering of woody species. They are two main families: (1) one-phase models which consider only the ecodormancy phase and make the assumption that endodormancy is always broken before adequate climatic conditions for cell growth occur; and (2) two-phase models which consider both the endodormancy and ecodormancy phases and predict a date of dormancy break which varies from year to year. So far, one-phase models have been able to predict accurately tree bud break and flowering under historical climate. However, because they do not consider what happens prior to ecodormancy, and especially the possible negative effect of winter temperature warming on dormancy break, it seems unlikely that they can provide accurate predictions in future climate conditions. It is indeed well known that a lack of low temperature results in abnormal pattern of bud break and development in temperate fruit trees. An accurate modelling of the dormancy break date has thus become a major issue in phenology modelling. Two-phases phenological models predict that global warming should delay

  8. Possibility of detecting anisotropic expansion of the universe by very accurate astrometry measurements.

    PubMed

    Quercellini, Claudia; Quartin, Miguel; Amendola, Luca

    2009-04-17

    Refined astrometry measurements allow us to detect large-scale deviations from isotropy through real-time observations of changes in the angular separation between sources at cosmic distances. This "cosmic parallax" effect is a powerful consistency test of the Friedmann-Robertson-Walker metric and may set independent constraints on cosmic anisotropy. We apply this novel general test to Lemaitre-Tolman-Bondi cosmologies with off-center observers and show that future satellite missions such as Gaia might achieve accuracies that would put limits on the off-center distance which are competitive with cosmic microwave background dipole constraints.

  9. Three-dimensional accurate detection of lung emphysema in rats using ultra-short and zero echo time MRI.

    PubMed

    Bianchi, Andrea; Tibiletti, Marta; Kjørstad, Åsmund; Birk, Gerald; Schad, Lothar R; Stierstorfer, Birgit; Rasche, Volker; Stiller, Detlef

    2015-11-01

    Emphysema is a life-threatening pathology that causes irreversible destruction of alveolar walls. In vivo imaging techniques play a fundamental role in the early non-invasive pre-clinical and clinical detection and longitudinal follow-up of this pathology. In the present study, we aimed to evaluate the feasibility of using high resolution radial three-dimensional (3D) zero echo time (ZTE) and 3D ultra-short echo time (UTE) MRI to accurately detect lung pathomorphological changes in a rodent model of emphysema.Porcine pancreas elastase (PPE) was intratracheally administered to the rats to produce the emphysematous changes. 3D ZTE MRI, low and high definition 3D UTE MRI and micro-computed tomography images were acquired 4 weeks after the PPE challenge. Signal-to-noise ratios (SNRs) were measured in PPE-treated and control rats. T2* values were computed from low definition 3D UTE MRI. Histomorphometric measurements were made after euthanizing the animals. Both ZTE and UTE MR images showed a significant decrease in the SNR measured in PPE-treated lungs compared with controls, due to the pathomorphological changes taking place in the challenged lungs. A significant decrease in T2* values in PPE-challenged animals compared with controls was measured using UTE MRI. Histomorphometric measurements showed a significant increase in the mean linear intercept in PPE-treated lungs. UTE yielded significantly higher SNR compared with ZTE (14% and 30% higher in PPE-treated and non-PPE-treated lungs, respectively).This study showed that optimized 3D radial UTE and ZTE MRI can provide lung images of excellent quality, with high isotropic spatial resolution (400 µm) and SNR in parenchymal tissue (>25) and negligible motion artifacts in freely breathing animals. These techniques were shown to be useful non-invasive instruments to accurately and reliably detect the pathomorphological alterations taking place in emphysematous lungs, without incurring the risks of cumulative radiation

  10. Anxiety, conscious awareness and change detection.

    PubMed

    Gregory, Sally M; Lambert, Anthony

    2012-03-01

    Attentional scanning was studied in anxious and non-anxious participants, using a modified change detection paradigm. Participants detected changes in pairs of emotional scenes separated by two task irrelevant slides, which contained an emotionally valenced scene (the 'distractor scene') and a visual mask. In agreement with attentional control theory, change detection latencies were slower overall for anxious participants. Change detection in anxious, but not non-anxious, participants was influenced by the emotional valence and exposure duration of distractor scenes. When negative distractor scenes were presented at subliminal exposure durations, anxious participants detected changes more rapidly than when supraliminal negative scenes or subliminal positive scenes were presented. We propose that for anxious participants, subliminal presentation of emotionally negative distractor scenes stimulated attention into a dynamic state in the absence of attentional engagement. Presentation of the same scenes at longer exposure times was accompanied by conscious awareness, attentional engagement, and slower change detection.

  11. Accurate tracking of tumor volume change during radiotherapy by CT-CBCT registration with intensity correction

    NASA Astrophysics Data System (ADS)

    Park, Seyoun; Robinson, Adam; Quon, Harry; Kiess, Ana P.; Shen, Colette; Wong, John; Plishker, William; Shekhar, Raj; Lee, Junghoon

    2016-03-01

    In this paper, we propose a CT-CBCT registration method to accurately predict the tumor volume change based on daily cone-beam CTs (CBCTs) during radiotherapy. CBCT is commonly used to reduce patient setup error during radiotherapy, but its poor image quality impedes accurate monitoring of anatomical changes. Although physician's contours drawn on the planning CT can be automatically propagated to daily CBCTs by deformable image registration (DIR), artifacts in CBCT often cause undesirable errors. To improve the accuracy of the registration-based segmentation, we developed a DIR method that iteratively corrects CBCT intensities by local histogram matching. Three popular DIR algorithms (B-spline, demons, and optical flow) with the intensity correction were implemented on a graphics processing unit for efficient computation. We evaluated their performances on six head and neck (HN) cancer cases. For each case, four trained scientists manually contoured the nodal gross tumor volume (GTV) on the planning CT and every other fraction CBCTs to which the propagated GTV contours by DIR were compared. The performance was also compared with commercial image registration software based on conventional mutual information (MI), VelocityAI (Varian Medical Systems Inc.). The volume differences (mean±std in cc) between the average of the manual segmentations and automatic segmentations are 3.70+/-2.30 (B-spline), 1.25+/-1.78 (demons), 0.93+/-1.14 (optical flow), and 4.39+/-3.86 (VelocityAI). The proposed method significantly reduced the estimation error by 9% (B-spline), 38% (demons), and 51% (optical flow) over the results using VelocityAI. Although demonstrated only on HN nodal GTVs, the results imply that the proposed method can produce improved segmentation of other critical structures over conventional methods.

  12. MIDAS robust trend estimator for accurate GPS station velocities without step detection.

    PubMed

    Blewitt, Geoffrey; Kreemer, Corné; Hammond, William C; Gazeaux, Julien

    2016-03-01

    Automatic estimation of velocities from GPS coordinate time series is becoming required to cope with the exponentially increasing flood of available data, but problems detectable to the human eye are often overlooked. This motivates us to find an automatic and accurate estimator of trend that is resistant to common problems such as step discontinuities, outliers, seasonality, skewness, and heteroscedasticity. Developed here, Median Interannual Difference Adjusted for Skewness (MIDAS) is a variant of the Theil-Sen median trend estimator, for which the ordinary version is the median of slopes vij  = (xj-xi )/(tj-ti ) computed between all data pairs i > j. For normally distributed data, Theil-Sen and least squares trend estimates are statistically identical, but unlike least squares, Theil-Sen is resistant to undetected data problems. To mitigate both seasonality and step discontinuities, MIDAS selects data pairs separated by 1 year. This condition is relaxed for time series with gaps so that all data are used. Slopes from data pairs spanning a step function produce one-sided outliers that can bias the median. To reduce bias, MIDAS removes outliers and recomputes the median. MIDAS also computes a robust and realistic estimate of trend uncertainty. Statistical tests using GPS data in the rigid North American plate interior show ±0.23 mm/yr root-mean-square (RMS) accuracy in horizontal velocity. In blind tests using synthetic data, MIDAS velocities have an RMS accuracy of ±0.33 mm/yr horizontal, ±1.1 mm/yr up, with a 5th percentile range smaller than all 20 automatic estimators tested. Considering its general nature, MIDAS has the potential for broader application in the geosciences.

  13. MIDAS robust trend estimator for accurate GPS station velocities without step detection

    NASA Astrophysics Data System (ADS)

    Blewitt, Geoffrey; Kreemer, Corné; Hammond, William C.; Gazeaux, Julien

    2016-03-01

    Automatic estimation of velocities from GPS coordinate time series is becoming required to cope with the exponentially increasing flood of available data, but problems detectable to the human eye are often overlooked. This motivates us to find an automatic and accurate estimator of trend that is resistant to common problems such as step discontinuities, outliers, seasonality, skewness, and heteroscedasticity. Developed here, Median Interannual Difference Adjusted for Skewness (MIDAS) is a variant of the Theil-Sen median trend estimator, for which the ordinary version is the median of slopes vij = (xj-xi)/(tj-ti) computed between all data pairs i > j. For normally distributed data, Theil-Sen and least squares trend estimates are statistically identical, but unlike least squares, Theil-Sen is resistant to undetected data problems. To mitigate both seasonality and step discontinuities, MIDAS selects data pairs separated by 1 year. This condition is relaxed for time series with gaps so that all data are used. Slopes from data pairs spanning a step function produce one-sided outliers that can bias the median. To reduce bias, MIDAS removes outliers and recomputes the median. MIDAS also computes a robust and realistic estimate of trend uncertainty. Statistical tests using GPS data in the rigid North American plate interior show ±0.23 mm/yr root-mean-square (RMS) accuracy in horizontal velocity. In blind tests using synthetic data, MIDAS velocities have an RMS accuracy of ±0.33 mm/yr horizontal, ±1.1 mm/yr up, with a 5th percentile range smaller than all 20 automatic estimators tested. Considering its general nature, MIDAS has the potential for broader application in the geosciences.

  14. MIDAS robust trend estimator for accurate GPS station velocities without step detection

    PubMed Central

    Kreemer, Corné; Hammond, William C.; Gazeaux, Julien

    2016-01-01

    Abstract Automatic estimation of velocities from GPS coordinate time series is becoming required to cope with the exponentially increasing flood of available data, but problems detectable to the human eye are often overlooked. This motivates us to find an automatic and accurate estimator of trend that is resistant to common problems such as step discontinuities, outliers, seasonality, skewness, and heteroscedasticity. Developed here, Median Interannual Difference Adjusted for Skewness (MIDAS) is a variant of the Theil‐Sen median trend estimator, for which the ordinary version is the median of slopes vij = (xj–xi)/(tj–ti) computed between all data pairs i > j. For normally distributed data, Theil‐Sen and least squares trend estimates are statistically identical, but unlike least squares, Theil‐Sen is resistant to undetected data problems. To mitigate both seasonality and step discontinuities, MIDAS selects data pairs separated by 1 year. This condition is relaxed for time series with gaps so that all data are used. Slopes from data pairs spanning a step function produce one‐sided outliers that can bias the median. To reduce bias, MIDAS removes outliers and recomputes the median. MIDAS also computes a robust and realistic estimate of trend uncertainty. Statistical tests using GPS data in the rigid North American plate interior show ±0.23 mm/yr root‐mean‐square (RMS) accuracy in horizontal velocity. In blind tests using synthetic data, MIDAS velocities have an RMS accuracy of ±0.33 mm/yr horizontal, ±1.1 mm/yr up, with a 5th percentile range smaller than all 20 automatic estimators tested. Considering its general nature, MIDAS has the potential for broader application in the geosciences. PMID:27668140

  15. Anomalous change detection in imagery

    DOEpatents

    Theiler, James P.; Perkins, Simon J.

    2011-05-31

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

  16. Accurate, multi-kb reads resolve complex populations and detect rare microorganisms

    PubMed Central

    Sharon, Itai; Kertesz, Michael; Hug, Laura A.; Pushkarev, Dmitry; Blauwkamp, Timothy A.; Castelle, Cindy J.; Amirebrahimi, Mojgan; Thomas, Brian C.; Burstein, David; Tringe, Susannah G.; Williams, Kenneth H.

    2015-01-01

    Accurate evaluation of microbial communities is essential for understanding global biogeochemical processes and can guide bioremediation and medical treatments. Metagenomics is most commonly used to analyze microbial diversity and metabolic potential, but assemblies of the short reads generated by current sequencing platforms may fail to recover heterogeneous strain populations and rare organisms. Here we used short (150-bp) and long (multi-kb) synthetic reads to evaluate strain heterogeneity and study microorganisms at low abundance in complex microbial communities from terrestrial sediments. The long-read data revealed multiple (probably dozens of) closely related species and strains from previously undescribed Deltaproteobacteria and Aminicenantes (candidate phylum OP8). Notably, these are the most abundant organisms in the communities, yet short-read assemblies achieved only partial genome coverage, mostly in the form of short scaffolds (N50 = ∼2200 bp). Genome architecture and metabolic potential for these lineages were reconstructed using a new synteny-based method. Analysis of long-read data also revealed thousands of species whose abundances were <0.1% in all samples. Most of the organisms in this “long tail” of rare organisms belong to phyla that are also represented by abundant organisms. Genes encoding glycosyl hydrolases are significantly more abundant than expected in rare genomes, suggesting that rare species may augment the capability for carbon turnover and confer resilience to changing environmental conditions. Overall, the study showed that a diversity of closely related strains and rare organisms account for a major portion of the communities. These are probably common features of many microbial communities and can be effectively studied using a combination of long and short reads. PMID:25665577

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

    NASA Astrophysics Data System (ADS)

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

    2016-08-01

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

  18. Image Change Detection via Ensemble Learning

    SciTech Connect

    Martin, Benjamin W; Vatsavai, Raju

    2013-01-01

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

  19. A fast and accurate method for detection of IBD shared haplotypes in genome-wide SNP data.

    PubMed

    Bjelland, Douglas W; Lingala, Uday; Patel, Piyush S; Jones, Matt; Keller, Matthew C

    2017-02-08

    Identical by descent (IBD) segments are used to understand a number of fundamental issues in genetics. IBD segments are typically detected using long stretches of identical alleles between haplotypes in phased, whole-genome SNP data. Phase or SNP call errors in genomic data can degrade accuracy of IBD detection and lead to false-positive/negative calls and to under/overextension of true IBD segments. Furthermore, the number of comparisons increases quadratically with sample size, requiring high computational efficiency. We developed a new IBD segment detection program, FISHR (Find IBD Shared Haplotypes Rapidly), in an attempt to accurately detect IBD segments and to better estimate their endpoints using an algorithm that is fast enough to be deployed on very large whole-genome SNP data sets. We compared the performance of FISHR to three leading IBD segment detection programs: GERMLINE, refined IBD, and HaploScore. Using simulated and real genomic sequence data, we show that FISHR is slightly more accurate than all programs at detecting long (>3 cm) IBD segments but slightly less accurate than refined IBD at detecting short (~1 cm) IBD segments. More centrally, FISHR outperforms all programs in determining the true endpoints of IBD segments, which is crucial for several applications of IBD information. FISHR takes two to three times longer than GERMLINE to run, whereas both GERMLINE and FISHR were orders of magnitude faster than refined IBD and HaploScore. Overall, FISHR provides accurate IBD detection in unrelated individuals and is computationally efficient enough to be utilized on large SNP data sets >60 000 individuals.European Journal of Human Genetics advance online publication, 8 February 2017; doi:10.1038/ejhg.2017.6.

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

    PubMed Central

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

    2016-01-01

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

  1. Detecting Concentration Changes with Cooperative Receptors

    NASA Astrophysics Data System (ADS)

    Bo, Stefano; Celani, Antonio

    2016-03-01

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

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

    PubMed

    Aswani, Shankar; Lauer, Matthew

    2014-06-01

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

  3. Detecting Children's Lies: Are Parents Accurate Judges of Their Own Children's Lies?

    ERIC Educational Resources Information Center

    Talwar, Victoria; Renaud, Sarah-Jane; Conway, Lauryn

    2015-01-01

    The current study investigated whether parents are accurate judges of their own children's lie-telling behavior. Participants included 250 mother-child dyads. Children were between three and 11 years of age. A temptation resistance paradigm was used to elicit a minor transgressive behavior from the children involving peeking at a forbidden toy and…

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

    PubMed

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

    2003-01-01

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

  5. Detectability of onsets versus offsets in the change detection paradigm.

    PubMed

    Cole, Geoff G; Kentridge, Robert W; Gellatly, Angus R H; Heywood, Charles A

    2003-01-01

    The human visual system is particularly sensitive to abrupt onset of new objects that appear in the visual field. Onsets have been shown to capture attention even when other transients simultaneously occur. This has led some authors to argue for the special role that object onset plays in attentional capture. However, evidence from the change detection paradigm appears contradictory to such findings. Studies of change blindness demonstrate that the onset of new objects can often go unnoticed. Assessing the relative detectability of onsets compared with other visual transients in a change detection procedure may help resolve this contradiction. We report the results of four experiments investigating the efficacy with which onsets capture attention compared with offsets. In Experiment 1, we employed a standard flicker procedure and assessed whether participants were more likely to detect the change following a frame containing an onset or following a frame containing an offset. In Experiment 2, we employed the one-shot method and investigated whether participants detected more onsets or offsets. Experiment 3 used the same method but assessed whether onsets would be detected more rapidly than offsets. In Experiment 4, we investigated whether the effect obtained in Experiments 1-3 using simple shapes would replicate when images of real-world objects were used. Results showed that onsets were less susceptible to change blindness than were offsets. We argue that the preservation of information is greater in onsets than in offsets.

  6. Accurate Mass Assignment of Native Protein Complexes Detected by Electrospray Mass Spectrometry

    PubMed Central

    Liepold, Lars O.; Oltrogge, Luke M.; Suci, Peter; Douglas, Trevor; Young, Mark J.

    2009-01-01

    Correct charge state assignment is crucial to assigning an accurate mass to supramolecular complexes analyzed by electrospray mass spectrometry. Conventional charge state assignment techniques fall short of reliably and unambiguously predicting the correct charge state for many supramolecular complexes. We provide an explanation of the shortcomings of the conventional techniques and have developed a robust charge state assignment method that is applicable to all spectra. PMID:19103497

  7. Change Detection Experiments Using Low Cost UAVs

    NASA Technical Reports Server (NTRS)

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

    2005-01-01

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

  8. Change Point Detection in Correlation Networks

    PubMed Central

    Barnett, Ian; Onnela, Jukka-Pekka

    2016-01-01

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

  9. Change Point Detection in Correlation Networks

    NASA Astrophysics Data System (ADS)

    Barnett, Ian; Onnela, Jukka-Pekka

    2016-01-01

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

  10. Molecular Detection of Foodborne Pathogens: A Rapid and Accurate Answer to Food Safety.

    PubMed

    Mangal, Manisha; Bansal, Sangita; Sharma, Satish K; Gupta, Ram K

    2016-07-03

    Food safety is a global health concern. For the prevention and recognition of problems related to health and safety, detection of foodborne pathogen is of utmost importance at all levels of food production chain. For several decades, a lot of research has been targeted at the development of rapid methodology as reducing the time needed to complete pathogen detection tests has been the primary goal of food microbiologists. With the result, food microbiology laboratories now have a wide array of detection methods and automated technologies such as enzyme immunoassay, polymerase chain reaction, and microarrays, which can cut test times considerably. Nucleic acid amplification strategies and advances in amplicon detection methodologies have been the key factors in the progress of molecular microbiology. A comprehensive literature survey has been carried out to give an overview in the field of foodborne pathogen detection. In this paper, we describe the conventional methods, as well as recent developments in food pathogen detection, identification, and quantification, with a major emphasis on molecular detection methods.

  11. Towards Accurate Node-Based Detection of P2P Botnets

    PubMed Central

    2014-01-01

    Botnets are a serious security threat to the current Internet infrastructure. In this paper, we propose a novel direction for P2P botnet detection called node-based detection. This approach focuses on the network characteristics of individual nodes. Based on our model, we examine node's flows and extract the useful features over a given time period. We have tested our approach on real-life data sets and achieved detection rates of 99-100% and low false positives rates of 0–2%. Comparison with other similar approaches on the same data sets shows that our approach outperforms the existing approaches. PMID:25089287

  12. Sensor for detecting changes in magnetic fields

    DOEpatents

    Praeg, W.F.

    1980-02-26

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

  13. Sensor for detecting changes in magnetic fields

    DOEpatents

    Praeg, Walter F.

    1981-01-01

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

  14. Parallax mitigation for hyperspectral change detection

    NASA Astrophysics Data System (ADS)

    Vongsy, Karmon; Eismann, Michael T.; Mendenhall, Michael J.; Velten, Vincent J.

    2014-06-01

    A pixel-level Generalized Likelihood Ratio Test (GLRT) statistic for hyperspectral change detection is developed to mitigate false change caused by image parallax. Change detection, in general, represents the difficult problem of discriminating significant changes opposed to insignificant changes caused by radiometric calibration, image registration issues, and varying view geometries. We assume that the images have been registered, and each pixel pair provides a measurement from the same spatial region in the scene. Although advanced image registration methods exist that can reduce mis-registration to subpixel levels; residual spatial mis-registration can still be incorrectly detected as significant changes. Similarly, changes in sensor viewing geometry can lead to parallax error in an urban cluttered scene where height structures, such as buildings, appear to move. Our algorithm looks to the inherent relationship between the image views and the theory of stereo vision to perform parallax mitigation leading to a search result in the assumed parallax direction. Mitigation of the parallax-induced false alarms is demonstrated using hyperspectral data in the experimental analysis. The algorithm is examined and compared to the existing chronochrome anomalous change detection algorithm to assess performance.

  15. Simple but accurate GCM-free approach for quantifying anthropogenic climate change

    NASA Astrophysics Data System (ADS)

    Lovejoy, S.

    2014-12-01

    We are so used to analysing the climate with the help of giant computer models (GCM's) that it is easy to get the impression that they are indispensable. Yet anthropogenic warming is so large (roughly 0.9oC) that it turns out that it is straightforward to quantify it with more empirically based methodologies that can be readily understood by the layperson. The key is to use the CO2 forcing as a linear surrogate for all the anthropogenic effects from 1880 to the present (implicitly including all effects due to Greenhouse Gases, aerosols and land use changes). To a good approximation, double the economic activity, double the effects. The relationship between the forcing and global mean temperature is extremely linear as can be seen graphically and understood without fancy statistics, [Lovejoy, 2014a] (see the attached figure and http://www.physics.mcgill.ca/~gang/Lovejoy.htm). To an excellent approximation, the deviations from the linear forcing - temperature relation can be interpreted as the natural variability. For example, this direct - yet accurate approach makes it graphically obvious that the "pause" or "hiatus" in the warming since 1998 is simply a natural cooling event that has roughly offset the anthropogenic warming [Lovejoy, 2014b]. Rather than trying to prove that the warming is anthropogenic, with a little extra work (and some nonlinear geophysics theory and pre-industrial multiproxies) we can disprove the competing theory that it is natural. This approach leads to the estimate that the probability of the industrial scale warming being a giant natural fluctuation is ≈0.1%: it can be dismissed. This destroys the last climate skeptic argument - that the models are wrong and the warming is natural. It finally allows for a closure of the debate. In this talk we argue that this new, direct, simple, intuitive approach provides an indispensable tool for communicating - and convincing - the public of both the reality and the amplitude of anthropogenic warming

  16. Evaluation of experimental UAV video change detection

    NASA Astrophysics Data System (ADS)

    Bartelsen, J.; Saur, G.; Teutsch, C.

    2016-10-01

    During the last ten years, the availability of images acquired from unmanned aerial vehicles (UAVs) has been continuously increasing due to the improvements and economic success of flight and sensor systems. From our point of view, reliable and automatic image-based change detection may contribute to overcoming several challenging problems in military reconnaissance, civil security, and disaster management. Changes within a scene can be caused by functional activities, i.e., footprints or skid marks, excavations, or humidity penetration; these might be recognizable in aerial images, but are almost overlooked when change detection is executed manually. With respect to the circumstances, these kinds of changes may be an indication of sabotage, terroristic activity, or threatening natural disasters. Although image-based change detection is possible from both ground and aerial perspectives, in this paper we primarily address the latter. We have applied an extended approach to change detection as described by Saur and Kr uger,1 and Saur et al.2 and have built upon the ideas of Saur and Bartelsen.3 The commercial simulation environment Virtual Battle Space 3 (VBS3) is used to simulate aerial "before" and "after" image acquisition concerning flight path, weather conditions and objects within the scene and to obtain synthetic videos. Video frames, which depict the same part of the scene, including "before" and "after" changes and not necessarily from the same perspective, are registered pixel-wise against each other by a photogrammetric concept, which is based on a homography. The pixel-wise registration is used to apply an automatic difference analysis, which, to a limited extent, is able to suppress typical errors caused by imprecise frame registration, sensor noise, vegetation and especially parallax effects. The primary concern of this paper is to seriously evaluate the possibilities and limitations of our current approach for image-based change detection with respect

  17. The impact of misregistration on change detection

    NASA Technical Reports Server (NTRS)

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

    1992-01-01

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

  18. Automated change detection for synthetic aperture sonar

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

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

  19. Hydrogen sulfide detection based on reflection: from a poison test approach of ancient China to single-cell accurate localization.

    PubMed

    Kong, Hao; Ma, Zhuoran; Wang, Song; Gong, Xiaoyun; Zhang, Sichun; Zhang, Xinrong

    2014-08-05

    With the inspiration of an ancient Chinese poison test approach, we report a rapid hydrogen sulfide detection strategy in specific areas of live cells using silver needles with good spatial resolution of 2 × 2 μm(2). Besides the accurate-localization ability, this reflection-based strategy also has attractive merits of convenience and robust response when free pretreatment and short detection time are concerned. The success of endogenous H2S level evaluation in cellular cytoplasm and nuclear of human A549 cells promises the application potential of our strategy in scientific research and medical diagnosis.

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

    PubMed

    Mathis, Katherine M; Kahan, Todd A

    2014-10-01

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

  1. Accurately measuring sea level change from space: an ESA Climate Change Initiative for MSL closure budget studies

    NASA Astrophysics Data System (ADS)

    Legeais, JeanFrancois; Cazenave, Anny; Ablain, Michael; Larnicol, Gilles; Benveniste, Jerome; Johannessen, Johnny; Timms, Gary; Andersen, Ole; Cipollini, Paolo; Roca, Monica; Rudenko, Sergei; Fernandes, Joana; Balmaseda, Magdalena; Quartly, Graham; Fenoglio-Marc, Luciana; Meyssignac, Benoit; Scharffenberg, Martin

    2016-04-01

    Sea level is a very sensitive index of climate change and variability. Sea level integrates the ocean warming, mountain glaciers and ice sheet melting. Understanding the sea level variability and changes implies an accurate monitoring of the sea level variable at climate scales, in addition to understanding the ocean variability and the exchanges between ocean, land, cryosphere, and atmosphere. That is why Sea Level is one of the Essential Climate Variables (ECV) selected in the frame of the ESA Climate Change Initiative (CCI) program. It aims at providing long-term monitoring of the sea level ECV with regular updates, as required for climate studies. The program is now in its second phase of 3 year (following phase I during 2011-2013). The objectives are firstly to involve the climate research community, to refine their needs and collect their feedbacks on product quality. And secondly to develop, test and select the best algorithms and standards to generate an updated climate time series and to produce and validate the Sea Level ECV product. This will better answer the climate user needs by improving the quality of the Sea Level products and maintain a sustain service for an up-to-date production. This has led to the production of the Sea Level ECV which has benefited from yearly extensions and now covers the period 1993-2014. We will firstly present the main achievements of the ESA CCI Sea Level Project. On the one hand, the major steps required to produce the 22 years climate time series are briefly described: collect and refine the user requirements, development of adapted algorithms for climate applications and specification of the production system. On the other hand, the product characteristics are described as well as the results from product validation, performed by several groups of the ocean and climate modeling community. At last, new altimeter standards have been developed and the best one have been recently selected in order to produce a full

  2. Accurately measuring sea level change from space: an ESA climate change initiative for MSL closure budget studies

    NASA Astrophysics Data System (ADS)

    Legeais, JeanFrancois; Benveniste, Jérôme

    2016-07-01

    Sea level is a very sensitive index of climate change and variability. Sea level integrates the ocean warming, mountain glaciers and ice sheet melting. Understanding the sea level variability and changes implies an accurate monitoring of the sea level variable at climate scales, in addition to understanding the ocean variability and the exchanges between ocean, land, cryosphere, and atmosphere. That is why Sea Level is one of the Essential Climate Variables (ECV) selected in the frame of the ESA Climate Change Initiative (CCI) program. It aims at providing long-term monitoring of the sea level ECV with regular updates, as required for climate studies. The program is now in its second phase of 3 year (following phase I during 2011-2013). The objectives are firstly to involve the climate research community, to refine their needs and collect their feedbacks on product quality. And secondly to develop, test and select the best algorithms and standards to generate an updated climate time series and to produce and validate the Sea Level ECV product. This will better answer the climate user needs by improving the quality of the Sea Level products and maintain a sustain service for an up-to-date production. This has led to the production of a first version of the Sea Level ECV which has benefited from yearly extensions and now covers the period 1993-2014. Within phase II, new altimeter standards have been developed and tested in order to reprocess the dataset with the best standards for climate studies. The reprocessed ECV will be released in summer 2016. We will present the main achievements of the ESA CCI Sea Level Project. On the one hand, the major steps required to produce the 22 years climate time series are briefly described: collect and refine the user requirements, development of adapted algorithms for climate applications and specification of the production system. On the other hand, the product characteristics are described as well as the results from product

  3. Accurate detection and complete tracking of large populations of features in three dimensions.

    PubMed

    Gao, Yongxiang; Kilfoil, Maria L

    2009-03-16

    Localization and tracking of colloidal particles in microscopy images generates the raw data necessary to understand both the dynamics and the mechanical properties of colloidal model systems. Yet, despite the obvious importance of analyzing particle movement in three dimensions (3D), accurate sub-pixel localization of the particles in 3D has received little attention so far. Tracking has been limited by the choice of whether to track all particles in a low-density system, or whether to neglect the most mobile fraction of particles in a dense system. Moreover, assertions are frequently made on the accuracies of methods for locating particles in colloid physics and in biology, and the field of particle locating and tracking can be well-served by quantitative comparison of relative performances. We show that by iterating sub-pixel localization in three dimensions, the centers of particles can be more accurately located in three-dimensions (3D) than with all previous methods by at least half an order of magnitude. In addition, we show that implementing a multi-pass deflation approach, greater fidelity can be achieved in reconstruction of trajectories, once particle positions are known. In general, all future work must defend the accuracy of the particle tracks to be considered reliable. Specifically, other researchers must use the methods presented here (or an alternative whose accuracy can be substantianted) in order for the entire investigation to be considered legitimate, if the basis of the physical argument (in colloids, biology, or any other application) depends on quantitative accuracy of particle positions. We compare our algorithms to other recent and related advances in location/tracking in colloids and in biology, and discuss the relative strengths and weaknesses of all the algorithms in various situations. We carry out performance tests directly comparing the accuracy of our and other 3D methods with simulated data for both location and tracking, and in

  4. Accurate and reproducible detection of proteins in water using an extended-gate type organic transistor biosensor

    NASA Astrophysics Data System (ADS)

    Minamiki, Tsukuru; Minami, Tsuyoshi; Kurita, Ryoji; Niwa, Osamu; Wakida, Shin-ichi; Fukuda, Kenjiro; Kumaki, Daisuke; Tokito, Shizuo

    2014-06-01

    In this Letter, we describe an accurate antibody detection method using a fabricated extended-gate type organic field-effect-transistor (OFET), which can be operated at below 3 V. The protein-sensing portion of the designed device is the gate electrode functionalized with streptavidin. Streptavidin possesses high molecular recognition ability for biotin, which specifically allows for the detection of biotinylated proteins. Here, we attempted to detect biotinylated immunoglobulin G (IgG) and observed a shift of threshold voltage of the OFET upon the addition of the antibody in an aqueous solution with a competing bovine serum albumin interferent. The detection limit for the biotinylated IgG was 8 nM, which indicates the potential utility of the designed device in healthcare applications.

  5. Detecting regional patterns of changing CO2 flux in Alaska

    NASA Astrophysics Data System (ADS)

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

    2016-07-01

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

  6. Detecting regional patterns of changing CO2 flux in Alaska

    PubMed Central

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

    2016-01-01

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

  7. SU-E-J-23: An Accurate Algorithm to Match Imperfectly Matched Images for Lung Tumor Detection Without Markers

    SciTech Connect

    Rozario, T; Bereg, S; Chiu, T; Liu, H; Kearney, V; Jiang, L; Mao, W

    2014-06-01

    Purpose: In order to locate lung tumors on projection images without internal markers, digitally reconstructed radiograph (DRR) is created and compared with projection images. Since lung tumors always move and their locations change on projection images while they are static on DRRs, a special DRR (background DRR) is generated based on modified anatomy from which lung tumors are removed. In addition, global discrepancies exist between DRRs and projections due to their different image originations, scattering, and noises. This adversely affects comparison accuracy. A simple but efficient comparison algorithm is reported. Methods: This method divides global images into a matrix of small tiles and similarities will be evaluated by calculating normalized cross correlation (NCC) between corresponding tiles on projections and DRRs. The tile configuration (tile locations) will be automatically optimized to keep the tumor within a single tile which has bad matching with the corresponding DRR tile. A pixel based linear transformation will be determined by linear interpolations of tile transformation results obtained during tile matching. The DRR will be transformed to the projection image level and subtracted from it. The resulting subtracted image now contains only the tumor. A DRR of the tumor is registered to the subtracted image to locate the tumor. Results: This method has been successfully applied to kV fluoro images (about 1000 images) acquired on a Vero (Brainlab) for dynamic tumor tracking on phantom studies. Radiation opaque markers are implanted and used as ground truth for tumor positions. Although, other organs and bony structures introduce strong signals superimposed on tumors at some angles, this method accurately locates tumors on every projection over 12 gantry angles. The maximum error is less than 2.6 mm while the total average error is 1.0 mm. Conclusion: This algorithm is capable of detecting tumor without markers despite strong background signals.

  8. How Accurately Can Your Wrist Device Recognize Daily Activities and Detect Falls?

    PubMed Central

    Gjoreski, Martin; Gjoreski, Hristijan; Luštrek, Mitja; Gams, Matjaž

    2016-01-01

    Although wearable accelerometers can successfully recognize activities and detect falls, their adoption in real life is low because users do not want to wear additional devices. A possible solution is an accelerometer inside a wrist device/smartwatch. However, wrist placement might perform poorly in terms of accuracy due to frequent random movements of the hand. In this paper we perform a thorough, large-scale evaluation of methods for activity recognition and fall detection on four datasets. On the first two we showed that the left wrist performs better compared to the dominant right one, and also better compared to the elbow and the chest, but worse compared to the ankle, knee and belt. On the third (Opportunity) dataset, our method outperformed the related work, indicating that our feature-preprocessing creates better input data. And finally, on a real-life unlabeled dataset the recognized activities captured the subject’s daily rhythm and activities. Our fall-detection method detected all of the fast falls and minimized the false positives, achieving 85% accuracy on the first dataset. Because the other datasets did not contain fall events, only false positives were evaluated, resulting in 9 for the second, 1 for the third and 15 for the real-life dataset (57 days data). PMID:27258282

  9. How Accurately Can Your Wrist Device Recognize Daily Activities and Detect Falls?

    PubMed

    Gjoreski, Martin; Gjoreski, Hristijan; Luštrek, Mitja; Gams, Matjaž

    2016-06-01

    Although wearable accelerometers can successfully recognize activities and detect falls, their adoption in real life is low because users do not want to wear additional devices. A possible solution is an accelerometer inside a wrist device/smartwatch. However, wrist placement might perform poorly in terms of accuracy due to frequent random movements of the hand. In this paper we perform a thorough, large-scale evaluation of methods for activity recognition and fall detection on four datasets. On the first two we showed that the left wrist performs better compared to the dominant right one, and also better compared to the elbow and the chest, but worse compared to the ankle, knee and belt. On the third (Opportunity) dataset, our method outperformed the related work, indicating that our feature-preprocessing creates better input data. And finally, on a real-life unlabeled dataset the recognized activities captured the subject's daily rhythm and activities. Our fall-detection method detected all of the fast falls and minimized the false positives, achieving 85% accuracy on the first dataset. Because the other datasets did not contain fall events, only false positives were evaluated, resulting in 9 for the second, 1 for the third and 15 for the real-life dataset (57 days data).

  10. NOVELTY DETECTION UNDER CHANGING ENVIRONMENTAL CONDITIONS

    SciTech Connect

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

    2001-04-01

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

  11. RT-PCR is a more accurate diagnostic tool for detection of BCR-ABL rearrangement

    SciTech Connect

    Zehnbauer, B.A.; Allen, A.P.; McGrath, S.D.

    1994-09-01

    Detection of the Philadelphia chromosome (Ph1) or genomic Southern hybridization for clonal gene rearrangement (GSH-R) has provided very specific identification of BCR-ABL gene rearrangement. Reverse transcriptase-polymerase chain reaction (RT-PCR) is diagnostic for patterns of BCR-ABL expression which are undetected by GSH-R and/or Ph1 and provides increased sensitivity both at diagnosis and in detection of minimal residual leukemia. Fifty-three specimens (of 150 tested from 119 consecutive leukemia patients) were RT-PCR positive for BCR-ABL gene expression confirmed by hybridization of PCR products with b{sub 3}a{sub 2}, b{sub 2}a{sub 2}, or e{sub 1}a{sub 2} junction-specific oligonucleotides. In 6 cases of CML with GSH-R{sup {minus}}at diagnosis, RT-PCR provided specific BCR-ABL identification. Deletion of BCR regions, low mitotic index, or e{sub 1}a{sub 2} expression caused failure to detect GSH-R or Ph1 translocation.

  12. Is `Resilience' Maladaptive? Towards an Accurate Lexicon for Climate Change Adaptation

    NASA Astrophysics Data System (ADS)

    Fisichelli, Nicholas A.; Schuurman, Gregor W.; Hoffman, Cat Hawkins

    2016-04-01

    Climate change adaptation is a rapidly evolving field in conservation biology and includes a range of strategies from resisting to actively directing change on the landscape. The term `climate change resilience,' frequently used to characterize adaptation strategies, deserves closer scrutiny because it is ambiguous, often misunderstood, and difficult to apply consistently across disciplines and spatial and temporal scales to support conservation efforts. Current definitions of resilience encompass all aspects of adaptation from resisting and absorbing change to reorganizing and transforming in response to climate change. However, many stakeholders are unfamiliar with this spectrum of definitions and assume the more common meaning of returning to a previous state after a disturbance. Climate change, however, is unrelenting and intensifying, characterized by both directional shifts in baseline conditions and increasing variability in extreme events. This ongoing change means that scientific understanding and management responses must develop concurrently, iteratively, and collaboratively, in a science-management partnership. Divergent concepts of climate change resilience impede cross-jurisdictional adaptation efforts and complicate use of adaptive management frameworks. Climate change adaptation practitioners require clear terminology to articulate management strategies and the inherent tradeoffs involved in adaptation. Language that distinguishes among strategies that seek to resist change, accommodate change, and direct change (i.e., persistence, autonomous change, and directed change) is prerequisite to clear communication about climate change adaptation goals and management intentions in conservation areas.

  13. Is 'Resilience' Maladaptive? Towards an Accurate Lexicon for Climate Change Adaptation.

    PubMed

    Fisichelli, Nicholas A; Schuurman, Gregor W; Hoffman, Cat Hawkins

    2016-04-01

    Climate change adaptation is a rapidly evolving field in conservation biology and includes a range of strategies from resisting to actively directing change on the landscape. The term 'climate change resilience,' frequently used to characterize adaptation strategies, deserves closer scrutiny because it is ambiguous, often misunderstood, and difficult to apply consistently across disciplines and spatial and temporal scales to support conservation efforts. Current definitions of resilience encompass all aspects of adaptation from resisting and absorbing change to reorganizing and transforming in response to climate change. However, many stakeholders are unfamiliar with this spectrum of definitions and assume the more common meaning of returning to a previous state after a disturbance. Climate change, however, is unrelenting and intensifying, characterized by both directional shifts in baseline conditions and increasing variability in extreme events. This ongoing change means that scientific understanding and management responses must develop concurrently, iteratively, and collaboratively, in a science-management partnership. Divergent concepts of climate change resilience impede cross-jurisdictional adaptation efforts and complicate use of adaptive management frameworks. Climate change adaptation practitioners require clear terminology to articulate management strategies and the inherent tradeoffs involved in adaptation. Language that distinguishes among strategies that seek to resist change, accommodate change, and direct change (i.e., persistence, autonomous change, and directed change) is prerequisite to clear communication about climate change adaptation goals and management intentions in conservation areas.

  14. Magnetic resonance elastography is accurate in detecting advanced fibrosis in autoimmune hepatitis

    PubMed Central

    Wang, Jin; Malik, Neera; Yin, Meng; Smyrk, Thomas C; Czaja, Albert J; Ehman, Richard L; Venkatesh, Sudhakar K

    2017-01-01

    AIM To assess the value of magnetic resonance elastography (MRE) in detecting advanced fibrosis/cirrhosis in autoimmune hepatitis (AIH). METHODS In this retrospective study, 36 patients (19 treated and 17 untreated) with histologically confirmed AIH and liver biopsy performed within 3 mo of MRE were identified at a tertiary care referral center. Liver stiffness (LS) with MRE was calculated by a radiologist, and inflammation grade and fibrosis stage in liver biopsy was assessed by a pathologist in a blinded fashion. Two radiologists evaluated morphological features of cirrhosis on conventional magnetic resonance imaging (MRI). Accuracy of MRE was compared to laboratory markers and MRI for detection of advanced fibrosis/cirrhosis. RESULTS Liver fibrosis stages of 0, 1, 2, 3 and 4 were present in 4, 6, 7, 6 and 13 patients respectively. There were no significant differences in distribution of fibrosis stage and inflammation grade between treated and untreated patient groups. LS with MRE demonstrated stronger correlation with liver fibrosis stage in comparison to laboratory markers for chronic liver disease (r = 0.88 vs -0.48-0.70). A trend of decreased mean LS in treated patients compared to untreated patients was observed (3.7 kPa vs 3.84 kPa) but was not statistically significant. MRE had an accuracy/sensitivity/specificity/positive predictive value/negative predictive value of 0.97/90%/100%/100%/90% and 0.98/92.3%/96%/92.3%/96% for detection of advanced fibrosis and cirrhosis, respectively. The performance of MRE was significantly better than laboratory tests for detection of advanced fibrosis (0.97 vs 0.53-0.80, P < 0.01), and cirrhosis (0.98 vs 0.58-0.80, P < 0.01) and better than conventional MRI for diagnosis of cirrhosis (0.98 vs 0.78, P = 0.002). CONCLUSION MRE is a promising modality for detection of advanced fibrosis and cirrhosis in patients with AIH with superior diagnostic accuracy compared to laboratory assessment and MRI. PMID:28223730

  15. Avoiding incidental predation by mammalian herbivores: accurate detection and efficient response in aphids.

    PubMed

    Gish, Moshe; Dafni, Amots; Inbar, Moshe

    2011-09-01

    Mammalian herbivores eat plants that may also provide food and shelter for insects. The direct trophic effect of the browsing and grazing of mammalian herbivory on insects, which is probably prevalent in terrestrial ecosystems, has been mostly neglected by ecologists. We examined how the aphid Uroleucon sonchi L. deals with the danger of incidental predation by mammalian herbivores. We found that most (76%) of the aphids in a colony survive the ingestion of the plant by a feeding herbivore. They do so by sensing the combination of heat and humidity in the herbivore's breath and immediately dropping off the plant in large numbers. Their ability to sense the herbivore's breath or their tendency to drop off the plant weakens as ambient temperature rises. This could indicate a limitation of the aphids' sensory system or an adaptation that enables them to avoid the hostile conditions on a hot ground. Once on the ground, U. sonchi is highly mobile and capable of locating a new host plant by advancing in a pattern that differs significantly from random movement. The accurate and efficient defense mechanism of U. sonchi emphasizes the significance of incidental predation as a danger to plant-dwelling invertebrates.

  16. Avoiding incidental predation by mammalian herbivores: accurate detection and efficient response in aphids

    NASA Astrophysics Data System (ADS)

    Gish, Moshe; Dafni, Amots; Inbar, Moshe

    2011-09-01

    Mammalian herbivores eat plants that may also provide food and shelter for insects. The direct trophic effect of the browsing and grazing of mammalian herbivory on insects, which is probably prevalent in terrestrial ecosystems, has been mostly neglected by ecologists. We examined how the aphid Uroleucon sonchi L. deals with the danger of incidental predation by mammalian herbivores. We found that most (76%) of the aphids in a colony survive the ingestion of the plant by a feeding herbivore. They do so by sensing the combination of heat and humidity in the herbivore's breath and immediately dropping off the plant in large numbers. Their ability to sense the herbivore's breath or their tendency to drop off the plant weakens as ambient temperature rises. This could indicate a limitation of the aphids' sensory system or an adaptation that enables them to avoid the hostile conditions on a hot ground. Once on the ground, U. sonchi is highly mobile and capable of locating a new host plant by advancing in a pattern that differs significantly from random movement. The accurate and efficient defense mechanism of U. sonchi emphasizes the significance of incidental predation as a danger to plant-dwelling invertebrates.

  17. Automatic change detection in spaceborne SAR imagery

    NASA Astrophysics Data System (ADS)

    Corr, Douglas G.; Whitehouse, Simon W.; Mott, David H.; Baldwin, Jim F.

    1996-06-01

    This paper describes a new technique of the automatic detection of change within synthetic aperture radar (SAR) images produced from satellite data. The interpretation of this type of imagery is difficult due to the combined effect of speckle, low resolution and the complexity of the radar signatures. The change detection technique that has been developed overcomes these problems by automatically measuring the degree of change between two images. The principle behind the technique used is that when satellite repeat orbits are at almost the same position in space then unless the scene has changed, the speckle pattern in the image will be unchanged. Comparison of images therefore reveals real change, not change due to fluctuating speckle patterns. The degree of change between two SAR images was measured by using the coherence function. Coherence has been studied for a variety of scene types: agricultural, forestry, domestic housing, small and large scale industrial complexes. Fuzzy set techniques, as well as direct threshold methods, have bee applied to the coherence data to determine places where change has occurred. The method has been validated using local information on building changes due to construction or demolition.

  18. Parametric probability distributions for anomalous change detection

    SciTech Connect

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

    2010-01-01

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

  19. Accurate Detection of Interaural Time Differences by a Population of Slowly Integrating Neurons

    NASA Astrophysics Data System (ADS)

    Vasilkov, Viacheslav A.; Tikidji-Hamburyan, Ruben A.

    2012-03-01

    For localization of a sound source, animals and humans process the microsecond interaural time differences of arriving sound waves. How nervous systems, consisting of elements with time constants of about and more than 1 ms, can reach such high precision is still an open question. In this Letter we present a hypothesis and show theoretical and computational evidence that a rather large population of slowly integrating neurons with inhibitory and excitatory inputs (EI neurons) can detect minute temporal disparities in input signals which are significantly less than any time constant in the system.

  20. Detection of abrupt changes in dynamic systems

    NASA Technical Reports Server (NTRS)

    Willsky, A. S.

    1984-01-01

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

  1. Accurate determination of the diffusion coefficient of proteins by Fourier analysis with whole column imaging detection.

    PubMed

    Zarabadi, Atefeh S; Pawliszyn, Janusz

    2015-02-17

    Analysis in the frequency domain is considered a powerful tool to elicit precise information from spectroscopic signals. In this study, the Fourier transformation technique is employed to determine the diffusion coefficient (D) of a number of proteins in the frequency domain. Analytical approaches are investigated for determination of D from both experimental and data treatment viewpoints. The diffusion process is modeled to calculate diffusion coefficients based on the Fourier transformation solution to Fick's law equation, and its results are compared to time domain results. The simulations characterize optimum spatial and temporal conditions and demonstrate the noise tolerance of the method. The proposed model is validated by its application for the electropherograms from the diffusion path of a set of proteins. Real-time dynamic scanning is conducted to monitor dispersion by employing whole column imaging detection technology in combination with capillary isoelectric focusing (CIEF) and the imaging plug flow (iPF) experiment. These experimental techniques provide different peak shapes, which are utilized to demonstrate the Fourier transformation ability in extracting diffusion coefficients out of irregular shape signals. Experimental results confirmed that the Fourier transformation procedure substantially enhanced the accuracy of the determined values compared to those obtained in the time domain.

  2. Automatic change detection using mobile laser scanning

    NASA Astrophysics Data System (ADS)

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

    2014-10-01

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

  3. Fast and accurate detection of cancer cell using a versatile three-channel plasmonic sensor

    NASA Astrophysics Data System (ADS)

    Hoseinian, M.; Ahmadi, A. R.; Bolorizadeh, M. A.

    2016-09-01

    Surface Plasmon Resonance (SPR) optical fiber sensors can be used as cost-effective small sized biosensors that are relatively simple to operate. Additionally, these instruments are label-free, hence rendering them highly sensitive to biological measurements. In this study, a three-channel microstructure optical fiber plasmonic-based portable biosensor is designed and analyzed using Finite Element Method. The proposed system is capable of determining changes in sample's refractive index with precision of order one thousandth. The biosensor measures three absorption resonance wavelengths of the analytes simultaneously. This property is one of the main advantages of the proposed biosensor since it reduces the error in the measured wavelength and enhances the accuracy of the results up to 10-5 m/RIU by reducing noise. In this paper, Jurkat cell, an indicator cell for leukemia cancer, is considered as the analyte; and its absorption resonance wavelengths as well as sensitivity in each channel are determined.

  4. The Addenbrooke's Cognitive Examination-Revised accurately detects cognitive decline in Huntington's disease.

    PubMed

    Begeti, Faye; Tan, Adrian Y K; Cummins, Gemma A; Collins, Lucy M; Guzman, Natalie Valle; Mason, Sarah L; Barker, Roger A

    2013-11-01

    Cognitive features, which begin before manifestation of the motor features, are an integral part of Huntington's disease and profoundly affect quality of life. A number of neuropsychological batteries have been used to assess this aspect of the condition, many of which are difficult to administer and time consuming, especially in advanced disease. We, therefore, investigated a simple and practical way to monitor cognition using the Addenbrooke's Cognitive Examination-Revised (ACE-R) in 126 manifest Huntington's disease patients, 28 premanifest gene carriers and 21 controls. Using this test, we demonstrated a selective decrease in phonemic, but not semantic, fluency in premanifest participants Cognitive decline in manifest Huntington's disease varied according to disease severity with extensive cognitive decline observed in early-stage Huntington's disease patients, indicating that this would be an optimal stage for interventions designed to halt cognitive decline, and lesser changes in the advanced cases. We next examined cognitive performance in patients prescribed antidopaminergic drugs as these drugs are known to decrease cognition when administered to healthy volunteers. We paradoxically found that these drugs may be beneficial, as early-stage Huntington's disease participants in receipt of them had improved attention and Mini-Mental State Examination scores. In conclusion, this is the first study to test the usefulness of the ACE-R in a Huntington's disease population and demonstrates that this is a brief, inexpensive and practical way to measure global cognitive performance in clinical practice with potential use in clinical trials.

  5. Can a Global Model Accurately Simulate Land-Atmosphere Interactions under Climate Change Conditions?

    NASA Astrophysics Data System (ADS)

    Zhou, C., VI; Wang, K.

    2015-12-01

    Surface air temperature (Ta) is largely determined by surface net radiation (Rn) and its partitioning into latent (LE) and sensible heat fluxes (H). Existing model evaluations of the absolute values of these fluxes are less helpful because the evaluation results are a blending of inconsistent spatial scales, inaccurate model forcing data and inaccurate parameterizations. This study further evaluates the relationship of LE and H with Rn and environmental parameters, including Ta, relative humidity (RH) and wind speed (WS), using ERA-interim reanalysis data at a grid of 0.125°×0.125° with measurements at AmeriFlux sites from 1998 to 2012. The results demonstrate that ERA-Interim can reproduce the absolute values of environmental parameters, radiation and turbulent fluxes rather accurately. The model performs well in simulating the correlation of LE and H to Rn, except for the notable correlation overestimation of H against Rn over high-density vegetation (e.g., deciduous broadleaf forest (DBF), grassland (GRA) and cropland (CRO)). The sensitivity of LE to Rn in the model is similar to the observations, but that of H to Rn is overestimated by 24.2%. In regions with high-density vegetation, the correlation coefficient between H and Ta is overestimated by more than 0.2, whereas that between H and WS is underestimated by more than 0.43. The sensitivity of H to Ta is overestimated by 0.72 Wm-2 °C-1, whereas that of H to WS in the model is underestimated by 16.15 Wm-2/(ms-1) over all of the sites. Considering both LE and H, the model cannot accurately capture the response of the evaporative fraction (EF=LE/(LE+H)) to Rn and the environmental parameters.

  6. Total least squares for anomalous change detection

    SciTech Connect

    Theiler, James P; Matsekh, Anna M

    2010-01-01

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

  7. Evaluation of object level change detection techniques

    NASA Astrophysics Data System (ADS)

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

    2007-04-01

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

  8. Full house of fears: evidence that people high in attachment anxiety are more accurate in detecting deceit.

    PubMed

    Ein-Dor, Tsachi; Perry, Adi

    2014-04-01

    Lying is deep-rooted in our nature, as over 90% of all people lie. Laypeople, however, do only slightly better than chance when detecting lies and deceptions. Recently, attachment anxiety was linked with people's hypervigilance toward threat-related cues. Accordingly, we tested whether attachment anxiety predicts people's ability to detect deceit and to play poker-a game that is based on players' ability to detect cheating. In Study 1, 202 participants watched a series of interpersonal interactions that comprised subtle clues to the honesty or dishonesty of the speakers. In Study 2, 58 participants watched clips in which such cues were absent. Participants were asked to decide whether the main characters were honest or dishonest. In Study 3, we asked 35 semiprofessional poker players to participate in a poker tournament, and then we predicted the amount of money won during the game. Results indicated that attachment anxiety, but not other types of anxiety, predicted more accurate detection of deceitful statements (Studies 1-2) and a greater amount of money won during a game of poker (Study 3). Results are discussed in relation to the possible adaptive functions of certain personality characteristics, such as attachment anxiety, often viewed as undesirable.

  9. Detecting hydrological changes through conceptual model

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

    Natural changes and human modifications in hydrological systems coevolve and interact in a coupled and interlinked way. If, on one hand, climatic changes are stochastic, non-steady, and affect the hydrological systems, on the other hand, human-induced changes due to over-exploitation of soils and water resources modifies the natural landscape, water fluxes and its partitioning. Indeed, the traditional assumption of static systems in hydrological analysis, which has been adopted for long time, fails whenever transient climatic conditions and/or land use changes occur. Time series analysis is a way to explore environmental changes together with societal changes; unfortunately, the not distinguishability between causes restrict the scope of this method. In order to overcome this limitation, it is possible to couple time series analysis with an opportune hydrological model, such as a conceptual hydrological model, which offers a schematization of complex dynamics acting within a basin. Assuming that model parameters represent morphological basin characteristics and that calibration is a way to detect hydrological signature at a specific moment, it is possible to argue that calibrating the model over different time windows could be a method for detecting potential hydrological changes. In order to test the capabilities of a conceptual model in detecting hydrological changes, this work presents different "in silico" experiments. A synthetic-basin is forced with an ensemble of possible future scenarios generated with a stochastic weather generator able to simulate steady and non-steady climatic conditions. The experiments refer to Mediterranean climate, which is characterized by marked seasonality, and consider the outcomes of the IPCC 5th report for describing climate evolution in the next century. In particular, in order to generate future climate change scenarios, a stochastic downscaling in space and time is carried out using realizations of an ensemble of General

  10. Detecting Change in Longitudinal Social Networks

    DTIC Science & Technology

    2011-01-01

    marketing campaigns and media on social behavior. Initial Construct populations, social and knowledge networks, can be hypothetical or real (Carley...patent data bases, phone-networks, email- based-networks, social- media networks and more. Page 6 of 37 Current methods of change detection in...CUSUM C Sta measured fo o be successf Average Bet ct either incre or each socia g increases in the data for fective for ch ork. tistic Over Tim

  11. Automated Change Detection for Synthetic Aperture Sonar

    DTIC Science & Technology

    2014-01-01

    analysis ( CCA ). The method was tested using data collected with a high-frequency SAS in a sandy shallow-water environment. By using precise co...coherent-based change detection results using canonical correlation analysis ( CCA ) described by Azimi-Sadjadi and Srinivasan,18 G-Michael and Tucker15 and...Sternlicht and G-Michael,19 where the preliminary studies were performed on simulated SAR and SAS imagery. The motivation behind CCA comes from recent

  12. Scene change detection based on multimodal integration

    NASA Astrophysics Data System (ADS)

    Zhu, Yingying; Zhou, Dongru

    2003-09-01

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

  13. Muscle spindle responses in man to changes in load during accurate position maintenance.

    PubMed

    Burke, D; Hagbarth, K E; Löfstedt, L

    1978-03-01

    1. Single unit and multi-unit recordings of muscle spindle activity were made from the peroneal nerves of human subjects. While the subjects attempted to maintain a constant ankle joint position, an external load on the receptor-bearing muscle was altered unexpectedly. 2. The spindle discharge produced by a sudden increase in load was of similar strength when the receptor-bearing muscle was relaxed as when it was contracting at the moment of the impact. A motor response at a latency consistent with a spinal reflex mechanism occurred only when the muscle was contracting. It is concluded that the potentiation of the reflex mechanism during contraction was not due primarily to a fusimotor action. 3. Sudden decrease in load produced a pause in spindle discharge followed by a pause in on-going e.m.g. activity at a latency consistent with spinal reflex mechanisms. 4. Slow changes in load produced parallel changes in e.m.g. and spindle discharge. It is suggested that the voluntary effort involved in maintaining joint position in the face of gradually changing loads results in corticospinal activity adjusted in strength to the opposing torque and operating on alpha and gamma motoneurones in parallel.

  14. Accurate Point-of-Care Detection of Ruptured Fetal Membranes: Improved Diagnostic Performance Characteristics with a Monoclonal/Polyclonal Immunoassay

    PubMed Central

    Rogers, Linda C.; Scott, Laurie; Block, Jon E.

    2016-01-01

    OBJECTIVE Accurate and timely diagnosis of rupture of membranes (ROM) is imperative to allow for gestational age-specific interventions. This study compared the diagnostic performance characteristics between two methods used for the detection of ROM as measured in the same patient. METHODS Vaginal secretions were evaluated using the conventional fern test as well as a point-of-care monoclonal/polyclonal immunoassay test (ROM Plus®) in 75 pregnant patients who presented to labor and delivery with complaints of leaking amniotic fluid. Both tests were compared to analytical confirmation of ROM using three external laboratory tests. Diagnostic performance characteristics were calculated including sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy. RESULTS Diagnostic performance characteristics uniformly favored ROM detection using the immunoassay test compared to the fern test: sensitivity (100% vs. 77.8%), specificity (94.8% vs. 79.3%), PPV (75% vs. 36.8%), NPV (100% vs. 95.8%), and accuracy (95.5% vs. 79.1%). CONCLUSIONS The point-of-care immunoassay test provides improved diagnostic accuracy for the detection of ROM compared to fern testing. It has the potential of improving patient management decisions, thereby minimizing serious complications and perinatal morbidity. PMID:27199579

  15. Strategy for Accurate Detection of Escherichia Coli O157:H7 in Ground Pork Using a Lateral Flow Immunoassay.

    PubMed

    Cheng, Song; Chen, Ming-Hui; Zhang, Gang-Gang; Yu, Zhi-Biao; Liu, Dao-Feng; Xiong, Yong-Hua; Wei, Hua; Lai, Wei-Hua

    2017-04-02

    Escherichia coli O157:H7 is known to cause serious diseases including hemorrhagic colitis and hemolytic uremic syndrome. A gold nanoparticle lateral flow immunoassay (Au-LFIA) was used to detect Escherichia coli O157:H7 in ground pork samples. False-positive results were detected using Au-LFIA; a Citrobacterfreundii strain was isolated from the ground pork samples and identified by using CHROmagar(TM) plates, API 20E, and 16S RNA sequencing. Since C.freundii showed cross-reactivity with E. coli O157:H7 when Au-LFIA test strips were used, a novel method combining modified enrichment with a lateral flow immunoassay for accurate and convenient detection of E. coli O157:H7 in ground pork was developed in this study to minimize these false positives. MacConkey broth was optimized for E. coli O157:H7 enrichment and C.freundii inhibition by the addition of 5 mg/L potassium tellurite and 0.10 mg/L cefixime. Using the proposed modified enrichment procedure, the false-positive rate of ground pork samples spiked with 100 CFU/g C.freundii decreased to 5%.

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

    NASA Technical Reports Server (NTRS)

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

    1977-01-01

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

  17. Children with mixed language disorder do not discriminate accurately facial identity when expressions change.

    PubMed

    Robel, Laurence; Vaivre-Douret, Laurence; Neveu, Xavier; Piana, Hélène; Perier, Antoine; Falissard, Bruno; Golse, Bernard

    2008-12-01

    We investigated the recognition of pairs of faces (same or different facial identities and expressions) in two groups of 14 children aged 6-10 years, with either an expressive language disorder (ELD), or a mixed language disorder (MLD), and two groups of 14 matched healthy controls. When looking at their global performances, children with either expressive (ELD) or MLD have few differences from controls in either face or emotional recognition. At contrary, we found that children with MLD, but not those with ELD, take identical faces to be different if their expressions change. Since children with mixed language disorders are socially more impaired than children with ELD, we think that these features may partly underpin the social difficulties of these children.

  18. Nationwide Hybrid Change Detection of Buildings

    NASA Astrophysics Data System (ADS)

    Hron, V.; Halounova, L.

    2016-06-01

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

  19. Detecting ecological change on coral reefs

    NASA Astrophysics Data System (ADS)

    Dustan, P.

    2011-12-01

    Remote sensing offers the potential to observe the response of coral reef ecosystems to environmental perturbations on a geographical scale not previously accessible. However, coral reef environments are optically, spatially, and temporally complex habitats which all present significant challenges for extracting meaningful information. Virtually every member of the reef community possesses some degree of photosynthetic capability. The community thus generates a matrix of fine scale features with bio-optical signatures that blend as the scale of observation increases. Furthermore, to have any validity, the remotely sensed signal must be "calibrated" to the bio-optics of the reef, a difficult and resource intensive process due to a convergence of photosynthetic light harvesting by green, red, and brown algal pigment systems. To make matters more complex, reefs are overlain by a seawater skin with its own set of hydrological optical challenges. Rather than concentrating on classification, my research has attempted to track change by following the variation in geo-referenced pixel brightness over time with a technique termed temporal texture. Environmental periodicities impart a phenology to the variation in brightness and departures from the norm are easily detected as statistical outliers. This opens the door to using current orbiting technology to efficiently examine large areas of sea for change. If hot spots are detected, higher resolution sensors and field studies can be focused as resources permit. While this technique does not identify the type of change, it is sensitive, simple to compute, easy to automate and grounded in ecological niche theory

  20. Immunohistochemical Detection of Changes in Tumor Hypoxia

    SciTech Connect

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

    2009-03-15

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

  1. Lake Chapala change detection using time series

    NASA Astrophysics Data System (ADS)

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

    2008-10-01

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

  2. Accurate Measurement of Brain Changes in Longitudinal MRI Scans using Tensor-Based Morphometry

    PubMed Central

    Hua, Xue; Gutman, Boris; Boyle, Christina; Rajagopalan, Priya; Leow, Alex D.; Yanovsky, Igor; Kumar, Anand R.; Toga, Arthur W.; Jack, Clifford R.; Schuff, Norbert; Alexander, Gene E.; Chen, Kewei; Reiman, Eric M.; Weiner, Michael W.; Thompson, Paul M.

    2011-01-01

    This paper responds to Thompson and Holland (2011), who challenged our tensor-based morphometry (TBM) method for estimating rates of brain changes in serial MRI from 431 subjects scanned every 6 months, for 2 years. Thompson and Holland noted an unexplained jump in our atrophy rate estimates: an offset between 0-6 months that may bias clinical trial power calculations. We identified why this jump occurs and propose a solution. By enforcing inverse-consistency in our TBM method, the offset dropped from 1.4% to 0.28%, giving plausible anatomical trajectories. Transitivity error accounted for the minimal remaining offset. Drug trial sample size estimates with the revised TBM-derived metrics are highly competitive with other methods, though higher than previously reported sample size estimates by a factor of 1.6 to 2.4. Importantly, estimates are far below those given in the critique. To demonstrate a 25% slowing of atrophic rates with 80% power, 62 AD and 129 MCI subjects would be required for a 2-year trial, and 91 AD and 192 MCI subjects for a 1-year trial. PMID:21320612

  3. Accurate Prediction of the Dynamical Changes within the Second PDZ Domain of PTP1e

    PubMed Central

    Cilia, Elisa; Vuister, Geerten W.; Lenaerts, Tom

    2012-01-01

    Experimental NMR relaxation studies have shown that peptide binding induces dynamical changes at the side-chain level throughout the second PDZ domain of PTP1e, identifying as such the collection of residues involved in long-range communication. Even though different computational approaches have identified subsets of residues that were qualitatively comparable, no quantitative analysis of the accuracy of these predictions was thus far determined. Here, we show that our information theoretical method produces quantitatively better results with respect to the experimental data than some of these earlier methods. Moreover, it provides a global network perspective on the effect experienced by the different residues involved in the process. We also show that these predictions are consistent within both the human and mouse variants of this domain. Together, these results improve the understanding of intra-protein communication and allostery in PDZ domains, underlining at the same time the necessity of producing similar data sets for further validation of thses kinds of methods. PMID:23209399

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

    SciTech Connect

    Beer, N. Reginald; Paglieroni, David W.

    2015-07-21

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

  5. BlueDetect: An iBeacon-Enabled Scheme for Accurate and Energy-Efficient Indoor-Outdoor Detection and Seamless Location-Based Service.

    PubMed

    Zou, Han; Jiang, Hao; Luo, Yiwen; Zhu, Jianjie; Lu, Xiaoxuan; Xie, Lihua

    2016-02-22

    The location and contextual status (indoor or outdoor) is fundamental and critical information for upper-layer applications, such as activity recognition and location-based services (LBS) for individuals. In addition, optimizations of building management systems (BMS), such as the pre-cooling or heating process of the air-conditioning system according to the human traffic entering or exiting a building, can utilize the information, as well. The emerging mobile devices, which are equipped with various sensors, become a feasible and flexible platform to perform indoor-outdoor (IO) detection. However, power-hungry sensors, such as GPS and WiFi, should be used with caution due to the constrained battery storage on mobile device. We propose BlueDetect: an accurate, fast response and energy-efficient scheme for IO detection and seamless LBS running on the mobile device based on the emerging low-power iBeacon technology. By leveraging the on-broad Bluetooth module and our proposed algorithms, BlueDetect provides a precise IO detection service that can turn on/off on-board power-hungry sensors smartly and automatically, optimize their performances and reduce the power consumption of mobile devices simultaneously. Moreover, seamless positioning and navigation services can be realized by it, especially in a semi-outdoor environment, which cannot be achieved by GPS or an indoor positioning system (IPS) easily. We prototype BlueDetect on Android mobile devices and evaluate its performance comprehensively. The experimental results have validated the superiority of BlueDetect in terms of IO detection accuracy, localization accuracy and energy consumption.

  6. BlueDetect: An iBeacon-Enabled Scheme for Accurate and Energy-Efficient Indoor-Outdoor Detection and Seamless Location-Based Service

    PubMed Central

    Zou, Han; Jiang, Hao; Luo, Yiwen; Zhu, Jianjie; Lu, Xiaoxuan; Xie, Lihua

    2016-01-01

    The location and contextual status (indoor or outdoor) is fundamental and critical information for upper-layer applications, such as activity recognition and location-based services (LBS) for individuals. In addition, optimizations of building management systems (BMS), such as the pre-cooling or heating process of the air-conditioning system according to the human traffic entering or exiting a building, can utilize the information, as well. The emerging mobile devices, which are equipped with various sensors, become a feasible and flexible platform to perform indoor-outdoor (IO) detection. However, power-hungry sensors, such as GPS and WiFi, should be used with caution due to the constrained battery storage on mobile device. We propose BlueDetect: an accurate, fast response and energy-efficient scheme for IO detection and seamless LBS running on the mobile device based on the emerging low-power iBeacon technology. By leveraging the on-broad Bluetooth module and our proposed algorithms, BlueDetect provides a precise IO detection service that can turn on/off on-board power-hungry sensors smartly and automatically, optimize their performances and reduce the power consumption of mobile devices simultaneously. Moreover, seamless positioning and navigation services can be realized by it, especially in a semi-outdoor environment, which cannot be achieved by GPS or an indoor positioning system (IPS) easily. We prototype BlueDetect on Android mobile devices and evaluate its performance comprehensively. The experimental results have validated the superiority of BlueDetect in terms of IO detection accuracy, localization accuracy and energy consumption. PMID:26907295

  7. CLARREO Cornerstone of the Earth Observing System: Measuring Decadal Change Through Accurate Emitted Infrared and Reflected Solar Spectra and Radio Occultation

    NASA Technical Reports Server (NTRS)

    Sandford, Stephen P.

    2010-01-01

    The Climate Absolute Radiance and Refractivity Observatory (CLARREO) is one of four Tier 1 missions recommended by the recent NRC Decadal Survey report on Earth Science and Applications from Space (NRC, 2007). The CLARREO mission addresses the need to provide accurate, broadly acknowledged climate records that are used to enable validated long-term climate projections that become the foundation for informed decisions on mitigation and adaptation policies that address the effects of climate change on society. The CLARREO mission accomplishes this critical objective through rigorous SI traceable decadal change observations that are sensitive to many of the key uncertainties in climate radiative forcings, responses, and feedbacks that in turn drive uncertainty in current climate model projections. These same uncertainties also lead to uncertainty in attribution of climate change to anthropogenic forcing. For the first time CLARREO will make highly accurate, global, SI-traceable decadal change observations sensitive to the most critical, but least understood, climate forcings, responses, and feedbacks. The CLARREO breakthrough is to achieve the required levels of accuracy and traceability to SI standards for a set of observations sensitive to a wide range of key decadal change variables. The required accuracy levels are determined so that climate trend signals can be detected against a background of naturally occurring variability. Climate system natural variability therefore determines what level of accuracy is overkill, and what level is critical to obtain. In this sense, the CLARREO mission requirements are considered optimal from a science value perspective. The accuracy for decadal change traceability to SI standards includes uncertainties associated with instrument calibration, satellite orbit sampling, and analysis methods. Unlike most space missions, the CLARREO requirements are driven not by the instantaneous accuracy of the measurements, but by accuracy in

  8. Accurate estimation of entropy in very short physiological time series: the problem of atrial fibrillation detection in implanted ventricular devices.

    PubMed

    Lake, Douglas E; Moorman, J Randall

    2011-01-01

    Entropy estimation is useful but difficult in short time series. For example, automated detection of atrial fibrillation (AF) in very short heart beat interval time series would be useful in patients with cardiac implantable electronic devices that record only from the ventricle. Such devices require efficient algorithms, and the clinical situation demands accuracy. Toward these ends, we optimized the sample entropy measure, which reports the probability that short templates will match with others within the series. We developed general methods for the rational selection of the template length m and the tolerance matching r. The major innovation was to allow r to vary so that sufficient matches are found for confident entropy estimation, with conversion of the final probability to a density by dividing by the matching region volume, 2r(m). The optimized sample entropy estimate and the mean heart beat interval each contributed to accurate detection of AF in as few as 12 heartbeats. The final algorithm, called the coefficient of sample entropy (COSEn), was developed using the canonical MIT-BIH database and validated in a new and much larger set of consecutive Holter monitor recordings from the University of Virginia. In patients over the age of 40 yr old, COSEn has high degrees of accuracy in distinguishing AF from normal sinus rhythm in 12-beat calculations performed hourly. The most common errors are atrial or ventricular ectopy, which increase entropy despite sinus rhythm, and atrial flutter, which can have low or high entropy states depending on dynamics of atrioventricular conduction.

  9. Detecting past changes of effective population size

    PubMed Central

    Nikolic, Natacha; Chevalet, Claude

    2014-01-01

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

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

    SciTech Connect

    Paglieroni, David W.

    2016-06-07

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

  11. Automated detection of changes in sequential color ocular fundus images

    NASA Astrophysics Data System (ADS)

    Sakuma, Satoshi; Nakanishi, Tadashi; Takahashi, Yasuko; Fujino, Yuichi; Tsubouchi, Tetsuro; Nakanishi, Norimasa

    1998-06-01

    A recent trend is the automatic screening of color ocular fundus images. The examination of such images is used in the early detection of several adult diseases such as hypertension and diabetes. Since this type of examination is easier than CT, costs less, and has no harmful side effects, it will become a routine medical examination. Normal ocular fundus images are found in more than 90% of all people. To deal with the increasing number of such images, this paper proposes a new approach to process them automatically and accurately. Our approach, based on individual comparison, identifies changes in sequential images: a previously diagnosed normal reference image is compared to a non- diagnosed image.

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

    NASA Astrophysics Data System (ADS)

    Schlichting, A.; Brenner, C.

    2016-06-01

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

  13. Census cities experiment in urban change detection

    NASA Technical Reports Server (NTRS)

    Wray, J. R. (Principal Investigator)

    1973-01-01

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

  14. Towards accurate assessments of CH4 and N2O soil-atmosphere exchange rates with the combination of automated systems and new detection techniques

    NASA Astrophysics Data System (ADS)

    Díaz-Pinés, E.; Wolf, B.; Kiese, R.; Butterbach-Bahl, K.

    2012-04-01

    Soils can be either a source or a sink of CH4 and N2O. Accurate assessment of CH4 and N2O soil-atmosphere exchange processes is necessary in order to estimate the contribution of soil to the global warming potential under current and future conditions. Soil-atmosphere exchange processes of both CH4 and N2O depend on a combination of soil temperature and soil moisture status, as well as on nutrient availability and various microbial processes. The task of measuring CH4 and N2O exchange processes is challenging due to, among other factors: high spatial ("hot spots") and temporal heterogeneity ("hot moments") in the emissions of these species. In addition, accurate determination of CH4 and N2O concentrations is still difficult. So far, this prevents from a full understanding and contributes to a high uncertainty degree in the assessment of CH4 and N2O soil-atmosphere exchange rates across different ecosystems. Aiming at the achievement of a deeper understanding of the role of the soil in the GHG balance, we have combined new laser spectroscopy detection techniques (Quantum Cascade Laser, QCL) with automatic and semi-automatic chamber measurement systems. Therefore, different applications will be presented: A three-month-long field campaign in a poplar plantation in NE Romania allowed us to demonstrate the feasibility of the QCL coupled with automatic chambers to accurately estimate the soil-atmosphere GHG exchange at a high time resolution with a very low detection limit. A new semi-automatic system with relatively low human-maintenance requirements was tested in a poplar plantation in SW Germany. The system is not able to record fine-scale temporal variations of the GHG exchange processes; however, cumulative fluxes obtained with the semi-automatic system were very close to those measured with an automatic system with high temporal resolution. Within a climate change experiment in grassland ecosystems, an application of the QCL in combination with a robotized chamber

  15. A finite rate of innovation algorithm for fast and accurate spike detection from two-photon calcium imaging

    NASA Astrophysics Data System (ADS)

    Oñativia, Jon; Schultz, Simon R.; Dragotti, Pier Luigi

    2013-08-01

    Objective. Inferring the times of sequences of action potentials (APs) (spike trains) from neurophysiological data is a key problem in computational neuroscience. The detection of APs from two-photon imaging of calcium signals offers certain advantages over traditional electrophysiological approaches, as up to thousands of spatially and immunohistochemically defined neurons can be recorded simultaneously. However, due to noise, dye buffering and the limited sampling rates in common microscopy configurations, accurate detection of APs from calcium time series has proved to be a difficult problem. Approach. Here we introduce a novel approach to the problem making use of finite rate of innovation (FRI) theory (Vetterli et al 2002 IEEE Trans. Signal Process. 50 1417-28). For calcium transients well fit by a single exponential, the problem is reduced to reconstructing a stream of decaying exponentials. Signals made of a combination of exponentially decaying functions with different onset times are a subclass of FRI signals, for which much theory has recently been developed by the signal processing community. Main results. We demonstrate for the first time the use of FRI theory to retrieve the timing of APs from calcium transient time series. The final algorithm is fast, non-iterative and parallelizable. Spike inference can be performed in real-time for a population of neurons and does not require any training phase or learning to initialize parameters. Significance. The algorithm has been tested with both real data (obtained by simultaneous electrophysiology and multiphoton imaging of calcium signals in cerebellar Purkinje cell dendrites), and surrogate data, and outperforms several recently proposed methods for spike train inference from calcium imaging data.

  16. Aptamer-conjugated live human immune cell based biosensors for the accurate detection of C-reactive protein

    PubMed Central

    Hwang, Jangsun; Seo, Youngmin; Jo, Yeonho; Son, Jaewoo; Choi, Jonghoon

    2016-01-01

    C-reactive protein (CRP) is a pentameric protein that is present in the bloodstream during inflammatory events, e.g., liver failure, leukemia, and/or bacterial infection. The level of CRP indicates the progress and prognosis of certain diseases; it is therefore necessary to measure CRP levels in the blood accurately. The normal concentration of CRP is reported to be 1–3 mg/L. Inflammatory events increase the level of CRP by up to 500 times; accordingly, CRP is a biomarker of acute inflammatory disease. In this study, we demonstrated the preparation of DNA aptamer-conjugated peripheral blood mononuclear cells (Apt-PBMCs) that specifically capture human CRP. Live PBMCs functionalized with aptamers could detect different levels of human CRP by producing immune complexes with reporter antibody. The binding behavior of Apt-PBMCs toward highly concentrated CRP sites was also investigated. The immune responses of Apt-PBMCs were evaluated by measuring TNF-alpha secretion after stimulating the PBMCs with lipopolysaccharides. In summary, engineered Apt-PBMCs have potential applications as live cell based biosensors and for in vitro tracing of CRP secretion sites. PMID:27708384

  17. Evaluation of a pan-serotype point-of-care rapid diagnostic assay for accurate detection of acute dengue infection.

    PubMed

    Vivek, Rosario; Ahamed, Syed Fazil; Kotabagi, Shalini; Chandele, Anmol; Khanna, Ira; Khanna, Navin; Nayak, Kaustuv; Dias, Mary; Kaja, Murali-Krishna; Shet, Anita

    2017-03-01

    The catastrophic rise in dengue infections in India and globally has created a need for an accurate, validated low-cost rapid diagnostic test (RDT) for dengue. We prospectively evaluated the diagnostic performance of NS1/IgM RDT (dengue day 1) using 211 samples from a pediatric dengue cohort representing all 4 serotypes in southern India. The dengue-positive panel consisted of 179 dengue real-time polymerase chain reaction (RT-PCR) positive samples from symptomatic children. The dengue-negative panel consisted of 32 samples from dengue-negative febrile children and asymptomatic individuals that were negative for dengue RT-PCR/NS1 enzyme-linked immunosorbent assay/IgM/IgG. NS1/IgM RDT sensitivity was 89.4% and specificity was 93.8%. The NS1/IgM RDT showed high sensitivity throughout the acute phase of illness, in primary and secondary infections, in different severity groups, and detected all 4 dengue serotypes, including coinfections. This NS1/IgM RDT is a useful point-of-care assay for rapid and reliable diagnosis of acute dengue and an excellent surveillance tool in our battle against dengue.

  18. Aptamer-conjugated live human immune cell based biosensors for the accurate detection of C-reactive protein

    NASA Astrophysics Data System (ADS)

    Hwang, Jangsun; Seo, Youngmin; Jo, Yeonho; Son, Jaewoo; Choi, Jonghoon

    2016-10-01

    C-reactive protein (CRP) is a pentameric protein that is present in the bloodstream during inflammatory events, e.g., liver failure, leukemia, and/or bacterial infection. The level of CRP indicates the progress and prognosis of certain diseases; it is therefore necessary to measure CRP levels in the blood accurately. The normal concentration of CRP is reported to be 1–3 mg/L. Inflammatory events increase the level of CRP by up to 500 times; accordingly, CRP is a biomarker of acute inflammatory disease. In this study, we demonstrated the preparation of DNA aptamer-conjugated peripheral blood mononuclear cells (Apt-PBMCs) that specifically capture human CRP. Live PBMCs functionalized with aptamers could detect different levels of human CRP by producing immune complexes with reporter antibody. The binding behavior of Apt-PBMCs toward highly concentrated CRP sites was also investigated. The immune responses of Apt-PBMCs were evaluated by measuring TNF-alpha secretion after stimulating the PBMCs with lipopolysaccharides. In summary, engineered Apt-PBMCs have potential applications as live cell based biosensors and for in vitro tracing of CRP secretion sites.

  19. Fiber-optic immuno-biosensor for rapid and accurate detection of nerve growth factor in human blood.

    PubMed

    Tang, Liang; Cha, Yong-Mei; Li, Hongmei; Chen, Peng-Sheng; Lin, Shien-Fong

    2006-01-01

    An accurate and rapid assay of cardiac nerve growth factor (NGF) levels in blood can provide physicians with critical information regarding myocardial injury and neural remodeling in cardiac tissues to identify patients at risk of impending heart attack, thereby enabling them to receive appropriate lifesaving treatment more quickly. Currently used assay methods, such as enzyme-linked immunosorbent assay (ELISA), are usually time-consuming (hours to days), expensive and technically complicated. In this paper, we described the development and clinical study of a rapid and sensitive method for detection and quantification of NGF in human blood plasma. This method utilizes a fiber-optic, immuno-biosensing system which performs a fluorophore-mediated sandwich immunoassay on the surface of an optical fiber. Physiological concentrations of NGF could be quantified in both buffer and human blood plasma samples within 5 minutes. The NGF concentrations determined by the fiberoptic sensor were comparable to those by the gold standard, ELISA. Preliminary study of NGF assay in cardiac patient plasma samples showed a great potential of the fiber-optic sensor as a rapid diagnostic and prognostic tool in clinical applications.

  20. Accurate Analysis of the Change in Volume, Location, and Shape of Metastatic Cervical Lymph Nodes During Radiotherapy

    SciTech Connect

    Takao, Seishin; Tadano, Shigeru; Taguchi, Hiroshi; Yasuda, Koichi; Onimaru, Rikiya; Ishikawa, Masayori; Bengua, Gerard; Suzuki, Ryusuke; Shirato, Hiroki

    2011-11-01

    Purpose: To establish a method for the accurate acquisition and analysis of the variations in tumor volume, location, and three-dimensional (3D) shape of tumors during radiotherapy in the era of image-guided radiotherapy. Methods and Materials: Finite element models of lymph nodes were developed based on computed tomography (CT) images taken before the start of treatment and every week during the treatment period. A surface geometry map with a volumetric scale was adopted and used for the analysis. Six metastatic cervical lymph nodes, 3.5 to 55.1 cm{sup 3} before treatment, in 6 patients with head and neck carcinomas were analyzed in this study. Three fiducial markers implanted in mouthpieces were used for the fusion of CT images. Changes in the location of the lymph nodes were measured on the basis of these fiducial markers. Results: The surface geometry maps showed convex regions in red and concave regions in blue to ensure that the characteristics of the 3D tumor geometries are simply understood visually. After the irradiation of 66 to 70 Gy in 2 Gy daily doses, the patterns of the colors had not changed significantly, and the maps before and during treatment were strongly correlated (average correlation coefficient was 0.808), suggesting that the tumors shrank uniformly, maintaining the original characteristics of the shapes in all 6 patients. The movement of the gravitational center of the lymph nodes during the treatment period was everywhere less than {+-}5 mm except in 1 patient, in whom the change reached nearly 10 mm. Conclusions: The surface geometry map was useful for an accurate evaluation of the changes in volume and 3D shapes of metastatic lymph nodes. The fusion of the initial and follow-up CT images based on fiducial markers enabled an analysis of changes in the location of the targets. Metastatic cervical lymph nodes in patients were suggested to decrease in size without significant changes in the 3D shape during radiotherapy. The movements of the

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

    SciTech Connect

    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.

  2. Change detection experiments using Gotcha public release SAR data

    NASA Astrophysics Data System (ADS)

    Stojanovic, Ivana; Novak, Les

    2013-05-01

    In this paper we compare coherent change detection performance obtained using the maximum likelihood estimate (MLE) of the SAR image-pair coherence versus using the complex correlation coefficient coherence estimate (CCD). We also compare the non-coherent change detection performance (PD vs. PFA) versus the performance of the coherent change detection algorithms.

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

    PubMed

    Beanland, Vanessa; Filtness, Ashleigh J; Jeans, Rhiannon

    2017-03-01

    The ability to detect changes is crucial for safe driving. Previous research has demonstrated that drivers often experience change blindness, which refers to failed or delayed change detection. The current study explored how susceptibility to change blindness varies as a function of the driving environment, type of object changed, and safety relevance of the change. Twenty-six fully-licenced drivers completed a driving-related change detection task. Changes occurred to seven target objects (road signs, cars, motorcycles, traffic lights, pedestrians, animals, or roadside trees) across two environments (urban or rural). The contextual safety relevance of the change was systematically manipulated within each object category, ranging from high safety relevance (i.e., requiring a response by the driver) to low safety relevance (i.e., requiring no response). When viewing rural scenes, compared with urban scenes, participants were significantly faster and more accurate at detecting changes, and were less susceptible to "looked-but-failed-to-see" errors. Interestingly, safety relevance of the change differentially affected performance in urban and rural environments. In urban scenes, participants were more efficient at detecting changes with higher safety relevance, whereas in rural scenes the effect of safety relevance has marginal to no effect on change detection. Finally, even after accounting for safety relevance, change blindness varied significantly between target types. Overall the results suggest that drivers are less susceptible to change blindness for objects that are likely to change or move (e.g., traffic lights vs. road signs), and for moving objects that pose greater danger (e.g., wild animals vs. pedestrians).

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

    NASA Astrophysics Data System (ADS)

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

    2011-08-01

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

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

    NASA Technical Reports Server (NTRS)

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

    1990-01-01

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

  6. Eye Movements and Display Change Detection during Reading

    ERIC Educational Resources Information Center

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

    2011-01-01

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

  7. Environmental monitoring in peat bog areas by change detection methods

    NASA Astrophysics Data System (ADS)

    Michel, Ulrich; Mildes, Wiebke

    2016-10-01

    Remote sensing image analysis systems and geographic information systems (GIS) show great promise for the integration of a wide variety of spatial information supporting tasks such as urban and regional planning, natural resource management, agricultural studies and topographic or thematic mapping. Current and future remote sensing programs are based on a variety of sensors that will provide timely and repetitive multisensor earth observation on a global scale. GIS offer efficient tools for handling, manipulating, analyzing and presenting spatial data that are required for sensible decision making in various areas. The Environmental Monitoring project may serve as a convincing example of the operational use of integrated GIS/remote sensing technologies. The overall goal of the project is to assess the capabilities of satellite remote sensing for the analysis of land use changes, especially in moor areas. These areas are recognized as areas crucial to the mission of the Department of Environment and, therefore, to be placed under an extended level of protection. It is of critical importance, however, to have accurate and current information about the ecological and economic state of these sensitive areas. In selected pasture and moor areas, methods for multisensor data fusion have being developed and tested. The results of this testing show which techniques are useful for pasture and moor monitoring at an operational level. A hierarchical method is used for extracting bog land classes with respect to the environmental protection goals. A highly accurate classification of the following classes was accomplished: deciduous- and mixed forest, coniferous forest, water, very wet areas, meadowland/farmland with vegetation, meadowland/farmland with partly vegetation, meadowland/ farmland without vegetation, peat quarrying with maximum of 50% vegetation, de- and regeneration stages. In addition, a change detection analysis is performed in comparison with the existing

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

    NASA Technical Reports Server (NTRS)

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

    1977-01-01

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

  9. Toward optimizing patient-specific IMRT QA techniques in the accurate detection of dosimetrically acceptable and unacceptable patient plans

    SciTech Connect

    McKenzie, Elizabeth M.; Balter, Peter A.; Stingo, Francesco C.; Jones, Jimmy; Followill, David S.; Kry, Stephen F.

    2014-12-15

    was no significant difference in the performance of any device between gamma criteria of 2%/2 mm, 3%/3 mm, and 5%/3 mm. Finally, optimal cutoffs (e.g., percent of pixels passing gamma) were determined for each device and while clinical practice commonly uses a threshold of 90% of pixels passing for most cases, these results showed variability in the optimal cutoff among devices. Conclusions: IMRT QA devices have differences in their ability to accurately detect dosimetrically acceptable and unacceptable plans. Field-by-field analysis with a MapCheck device and use of the MapCheck with a MapPhan phantom while delivering at planned rotational gantry angles resulted in a significantly poorer ability to accurately sort acceptable and unacceptable plans compared with the other techniques examined. Patient-specific IMRT QA techniques in general should be thoroughly evaluated for their ability to correctly differentiate acceptable and unacceptable plans. Additionally, optimal agreement thresholds should be identified and used as common clinical thresholds typically worked very poorly to identify unacceptable plans.

  10. Accurate detection for a wide range of mutation and editing sites of microRNAs from small RNA high-throughput sequencing profiles

    PubMed Central

    Zheng, Yun; Ji, Bo; Song, Renhua; Wang, Shengpeng; Li, Ting; Zhang, Xiaotuo; Chen, Kun; Li, Tianqing; Li, Jinyan

    2016-01-01

    Various types of mutation and editing (M/E) events in microRNAs (miRNAs) can change the stabilities of pre-miRNAs and/or complementarities between miRNAs and their targets. Small RNA (sRNA) high-throughput sequencing (HTS) profiles can contain many mutated and edited miRNAs. Systematic detection of miRNA mutation and editing sites from the huge volume of sRNA HTS profiles is computationally difficult, as high sensitivity and low false positive rate (FPR) are both required. We propose a novel method (named MiRME) for an accurate and fast detection of miRNA M/E sites using a progressive sequence alignment approach which refines sensitivity and improves FPR step-by-step. From 70 sRNA HTS profiles with over 1.3 billion reads, MiRME has detected thousands of statistically significant M/E sites, including 3′-editing sites, 57 A-to-I editing sites (of which 32 are novel), as well as some putative non-canonical editing sites. We demonstrated that a few non-canonical editing sites were not resulted from mutations in genome by integrating the analysis of genome HTS profiles of two human cell lines, suggesting the existence of new editing types to further diversify the functions of miRNAs. Compared with six existing studies or methods, MiRME has shown much superior performance for the identification and visualization of the M/E sites of miRNAs from the ever-increasing sRNA HTS profiles. PMID:27229138

  11. High-precision topography measurement through accurate in-focus plane detection with hybrid digital holographic microscope and white light interferometer module.

    PubMed

    Liżewski, Kamil; Tomczewski, Sławomir; Kozacki, Tomasz; Kostencka, Julianna

    2014-04-10

    High-precision topography measurement of micro-objects using interferometric and holographic techniques can be realized provided that the in-focus plane of an imaging system is very accurately determined. Therefore, in this paper we propose an accurate technique for in-focus plane determination, which is based on coherent and incoherent light. The proposed method consists of two major steps. First, a calibration of the imaging system with an amplitude object is performed with a common autofocusing method using coherent illumination, which allows for accurate localization of the in-focus plane position. In the second step, the position of the detected in-focus plane with respect to the imaging system is measured with white light interferometry. The obtained distance is used to accurately adjust a sample with the precision required for the measurement. The experimental validation of the proposed method is given for measurement of high-numerical-aperture microlenses with subwavelength accuracy.

  12. Detecting holocene changes in thermohaline circulation.

    PubMed

    Keigwin, L D; Boyle, E A

    2000-02-15

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

  13. Change Detection in Naturalistic Pictures among Children with Autism

    ERIC Educational Resources Information Center

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

    2009-01-01

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

  14. Epigenetic changes detected in micropropagated hop plants.

    PubMed

    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.

  15. Occupancy change detection system and method

    SciTech Connect

    Bruemmer, David J; Few, Douglas A

    2009-09-01

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

  16. Accurate lithography hotspot detection based on principal component analysis-support vector machine classifier with hierarchical data clustering

    NASA Astrophysics Data System (ADS)

    Yu, Bei; Gao, Jhih-Rong; Ding, Duo; Zeng, Xuan; Pan, David Z.

    2015-01-01

    As technology nodes continue to shrink, layout patterns become more sensitive to lithography processes, resulting in lithography hotspots that need to be identified and eliminated during physical verification. We propose an accurate hotspot detection approach based on principal component analysis-support vector machine classifier. Several techniques, including hierarchical data clustering, data balancing, and multilevel training, are provided to enhance the performance of the proposed approach. Our approach is accurate and more efficient than conventional time-consuming lithography simulation and provides a high flexibility for adapting to new lithography processes and rules.

  17. Change Detection Module for New Orleans City of USA Using

    NASA Astrophysics Data System (ADS)

    Singh, Dharmendra

    accuracy. The New Orleans city of USA is taken as study area because this is reported that this city is shrinking. RADARSAT SLC (Single look complex) images acquired from January 2002 to March 2007 were obtained for the study area. Image pairs with perpendicular baselines less than 100 km are chosen. Selection of suitable image pairs is crucial since baseline distance between them affects the altitude ambiguity in resultant change detection map. Coherence is computed for the image pairs. If the coherence is greater than 0.25, such image pairs are considered for further analysis. Three pass differential InSAR is used for the analysis of change detection. Images 1 and 2 of the study area with lesser temporal span (minimum of 24 day interval) is chosen to make a digital elevation model and then images 1 and 3 of the same area with one year of temporal span is chosen to make an interferogram. The topographic phase estimated with images 1 and 2 is then subtracted to make a differential interferogram showing change from image 2 to 3. Image pairs with approximately one month temporal span, are considered for generating interferogram. Changes occurred in every one year is measured by subtracting topographic phase of the year corresponding to master image, from interferogram. From the change detection map obtained from both methods show that areas of larger changes are identified near Lake Borgne, and in the boundaries of Mississippi river. Lake Borgne is reported to be identified as an area of major land subsidence as found by other studies also. On comparing our result with this interferometric study, it is found that both are showing some common regions with high changes near water bodies. Surface deformation can be monitored quantitatively in the scale of mm with the help of temporal analysis of D-InSAR.

  18. A Dual-Process Account of Auditory Change Detection

    ERIC Educational Resources Information Center

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

    2010-01-01

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

  19. Load and Rate of Change of Load Detection System.

    DTIC Science & Technology

    The present invention relates to a system for detecting and recording the level and rate of change of landing loads in the struts of aircraft landing...to a minimum pressure to record the level and rate of change of pressure detected by the sensor.

  20. Comparing Several Algorithms for Change Detection of Wetland

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

    As "the kidneys of the landscape" and "ecological supermarkets", wetland plays an important role in ecological equilibrium and environmental protection.Therefore, it is of great significance to understand the dynamic changes of the wetland. Nowadays, many index and many methods have been used in dynamic Monitoring of Wetland. However, there are no single method and no single index are adapted to detect dynamic change of wetland all over the world. In this paper, three digital change detection algorithms are applied to 2005 and 2010 Landsat Thematic Mapper (TM) images of a portion of the Northeast China to detect wetland dynamic between the two dates. The change vector analysis method (CVA) uses 6 bands of TM images to detect wetland dynamic. The tassled cap transformation is used to create three change images (change in brightness, greenness, and wetness). A new method--- Comprehensive Change Detection Method (CCDM) is introduced to detect forest dynamic change. The CCDM integrates spectral-based change detection algorithms including a Multi-Index Integrated Change Analysis (MIICA) model and a novel change model called Zone, which extracts change information from two Landsat image pairs. The MIICA model is the core module of the change detection strategy and uses four spectral indices (differenced Normalized Burn Ratio (dNBR), differenced Normalized Difference Vegetation Index (dNDVI), the Change Vector (CV) and a new index called the Relative Change Vector Maximum (RCVMAX)) to obtain the changes that occurred between two image dates. The CCDM also includes a knowledge-based system, which uses critical information on historical and current land cover conditions and trends and the likelihood of land cover change, to combine the changes from MIICA and Zone. Related test proved that CCDM method is simple, easy to operate, widely applicable, and capable of capturing a variety of natural and anthropogenic disturbances potentially associated with land cover changes on

  1. Change Detection in Rough Time Series

    DTIC Science & Technology

    2014-09-01

    support models. While at DSTO he has worked on applications for modelling strategic decisions, intelligence analysis, and decision support systems ...changing nature of expected droughts into the future thus indicates increasing stress on the MDB river and lake system such that pre-existing irrigation ...or inaccurate sensor data, subjective ratings of vague variables, imperfect intelligence reports, algorithmic derived measures indicating degrees

  2. A portable analog lock-in amplifier for accurate phase measurement and application in high-precision optical oxygen concentration detection

    NASA Astrophysics Data System (ADS)

    Chen, Xi; Chang, Jun; Wang, Fupeng; Wang, Zongliang; Wei, Wei; Liu, Yuanyuan; Qin, Zengguang

    2017-03-01

    A portable analog lock-in amplifier capable of accurate phase detection is proposed in this paper. The proposed lock-in amplifier, which uses the dual-channel orthometric signals as the references to build the xy coordinate system, can detect the relative phase between the input and x-axis based on trigonometric function. The sensitivity of the phase measurement reaches 0.014 degree, and a detection precision of 0.1 degree is achieved. At the same time, the performance of the lock-in amplifier is verified in the high precision optical oxygen concentration detection. Experimental results reveal that the portable analog lock-in amplifier is accurate for phase detection applications. In the oxygen sensing experiments, 0.058% oxygen concentration resulted in 0.1 degree phase shift detected by the lock-in amplifier precisely. In addition, the lock-in amplifier is small and economical compared with the commercial lock-in equipments, so it can be easily integrated in many portable devices for industrial applications.

  3. A portable analog lock-in amplifier for accurate phase measurement and application in high-precision optical oxygen concentration detection

    NASA Astrophysics Data System (ADS)

    Chen, Xi; Chang, Jun; Wang, Fupeng; Wang, Zongliang; Wei, Wei; Liu, Yuanyuan; Qin, Zengguang

    2016-10-01

    A portable analog lock-in amplifier capable of accurate phase detection is proposed in this paper. The proposed lock-in amplifier, which uses the dual-channel orthometric signals as the references to build the xy coordinate system, can detect the relative phase between the input and x-axis based on trigonometric function. The sensitivity of the phase measurement reaches 0.014 degree, and a detection precision of 0.1 degree is achieved. At the same time, the performance of the lock-in amplifier is verified in the high precision optical oxygen concentration detection. Experimental results reveal that the portable analog lock-in amplifier is accurate for phase detection applications. In the oxygen sensing experiments, 0.058% oxygen concentration resulted in 0.1 degree phase shift detected by the lock-in amplifier precisely. In addition, the lock-in amplifier is small and economical compared with the commercial lock-in equipments, so it can be easily integrated in many portable devices for industrial applications.

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

    PubMed

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

    2014-05-01

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

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

    PubMed Central

    Kim, Jongmin; Khetarpal, Ishan; Murray, Richard M.

    2014-01-01

    Biological organisms use their sensory systems to detect changes in their environment. The ability of sensory systems to adapt to static inputs allows wide dynamic range as well as sensitivity to input changes including fold-change detection, a response that depends only on fold changes in input, and not on absolute changes. This input scale invariance underlies an important strategy for search that depends solely on the spatial profile of the input. Synthetic efforts to reproduce the architecture and response of cellular circuits provide an important step to foster understanding at the molecular level. We report the bottom-up assembly of biochemical systems that show exact adaptation and fold-change detection. Using a malachite green aptamer as the output, a synthetic transcriptional circuit with the connectivity of an incoherent feed-forward loop motif exhibits pulse generation and exact adaptation. A simple mathematical model was used to assess the amplitude and duration of pulse response as well as the parameter regimes required for fold-change detection. Upon parameter tuning, this synthetic circuit exhibits fold-change detection for four successive rounds of two-fold input changes. The experimental realization of fold-change detection circuit highlights the programmability of transcriptional switches and the ability to obtain predictive dynamical systems in a cell-free environment for technological applications. PMID:24728988

  6. An automatic method for fast and accurate liver segmentation in CT images using a shape detection level set method

    NASA Astrophysics Data System (ADS)

    Lee, Jeongjin; Kim, Namkug; Lee, Ho; Seo, Joon Beom; Won, Hyung Jin; Shin, Yong Moon; Shin, Yeong Gil

    2007-03-01

    Automatic liver segmentation is still a challenging task due to the ambiguity of liver boundary and the complex context of nearby organs. In this paper, we propose a faster and more accurate way of liver segmentation in CT images with an enhanced level set method. The speed image for level-set propagation is smoothly generated by increasing number of iterations in anisotropic diffusion filtering. This prevents the level-set propagation from stopping in front of local minima, which prevails in liver CT images due to irregular intensity distributions of the interior liver region. The curvature term of shape modeling level-set method captures well the shape variations of the liver along the slice. Finally, rolling ball algorithm is applied for including enhanced vessels near the liver boundary. Our approach are tested and compared to manual segmentation results of eight CT scans with 5mm slice distance using the average distance and volume error. The average distance error between corresponding liver boundaries is 1.58 mm and the average volume error is 2.2%. The average processing time for the segmentation of each slice is 5.2 seconds, which is much faster than the conventional ones. Accurate and fast result of our method will expedite the next stage of liver volume quantification for liver transplantations.

  7. One new method for road data shape change detection

    NASA Astrophysics Data System (ADS)

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

    2009-10-01

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

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

    NASA Astrophysics Data System (ADS)

    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.

  9. Improved change detection with local co-registration adjustments

    SciTech Connect

    Wohlberg, Brendt E; Theiler, James P

    2009-01-01

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

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

    ERIC Educational Resources Information Center

    Yang, Cheng-Ta

    2011-01-01

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

  11. Rapid and highly accurate detection of Drosophila suzukii, spotted wing Drosophila (Diptera: Drosophilidae) by loop-mediated isothermal amplification assays

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Drosophila suzukii, the spotted wing drosophila (SWD), is currently a major pest that causes severe economic losses to thin-skinned, small fruit growers in North America and Europe. The monitoring and early detection of SWD in the field is of the utmost importance for its proper management. Althou...

  12. Are the Original and Second Edition of the California Verbal Learning Test Equally Accurate in Detecting Malingering?

    ERIC Educational Resources Information Center

    Greve, Kevin W.; Curtis, Kelly L.; Bianchini, Kevin J.; Ord, Jonathan S.

    2009-01-01

    This two-part study sought to determine the equivalence of the California Verbal Learning Tests (CVLT-1 and CVLT-2) in the detection of malingering in traumatic brain injury (TBI) and chronic pain. Part 1 compared a variety of scores from the two versions in carefully matched patient groups. Part 2 used criterion groups (known-groups) methodology…

  13. Detecting data and schema changes in scientific documents

    SciTech Connect

    Adiwijaya, I; Critchlow, T; Musick, R

    1999-06-08

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

  14. Detection and Attribution of Regional Climate Change

    SciTech Connect

    Bala, G; Mirin, A

    2007-01-19

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

  15. Accurate method for measurement of pipe wall thickness using a circumferential guided wave generated and detected by a pair of noncontact transducers

    NASA Astrophysics Data System (ADS)

    Nishino, H.; Taniguchi, Y.; Yoshida, K.

    2012-05-01

    A noncontact method of an accurate estimation of a pipe wall thickness using a circumferential (C-) Lamb wave is presented. The C-Lamb waves circling along the circumference of pipes are transmitted and received by the critical angle method using a pair of noncontact air-coupled ultrasonic transducers. For the accurate estimation of a pipe wall thickness, the accurate measurement of the angular wave number that changes minutely owing to the thickness must be achieved. To achieve the accurate measurement, a large number of tone-burst cycles are used so as to superpose the C-Lamb wave on itself along its circumferential orbit. In this setting, the amplitude of the superposed region changes considerably with the angular wave number, from which the wall thickness can be estimated. This paper presents the principle of the method and experimental verifications. As results of the experimental verifications, it was confirmed that the maximum error between the estimates and the theoretical model was less than 10 micrometers.

  16. Attending to faces: change detection, familiarization, and inversion effects.

    PubMed

    Barton, Jason J S; Deepak, Shaunak; Malik, Numaan

    2003-01-01

    We tested detection of changes to eye position, eye color (brightness), mouth position, and mouth color in frontal views of faces. Two faces were presented sequentially for 555 ms each, with a blank screen of 120 ms separating the two. Faces were presented either both upright or both inverted. Measures of detection (d') were calculated for several different degrees of change for each of the four dimensions of change. We first compared results to an earlier experiment that used an oddity design, in which subjects indicated which of three simultaneously viewed and otherwise identical faces had been altered on one of these four dimensions. Subjects in both of these experiments were partially cued, in that they knew the four possible types of changes that could occur on a given trial. The change-detection results correlated well with the oddity data. They confirmed that face inversion had little effect upon detection of changes in eye color, a moderate effect upon detection of eye-position or mouth-color changes, and caused a drastic reduction in the detection of mouth-position changes. An experiment in which uncued and fully cued subjects were compared showed that cueing significantly improved detection of feature color changes, but there was little difference between upright and inverted faces. Full cueing eliminated all effects of inversion. Compared to partial cueing, changes in mouth color were poorly detected by uncued subjects. Last, a change in the frequency of the base (unaltered) face in an experiment from 75% to 40% showed that increased short-term familiarity decreased the detection of eye changes and increased the detection of mouth changes, regardless of face orientation and the type of change made (color or position). We conclude that uncued subjects encode the spatial relations of features more than the colors of features, that mouth color in particular is not considered a relevant dimension for encoding, and that familiarization redistributes attention

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

    NASA Astrophysics Data System (ADS)

    Tanaka, Hirokazu; Katura, Takusige

    2011-08-01

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

  18. Questioning the Specificity of ASRS-v1.1 to Accurately Detect ADHD in Substance Abusing Populations

    ERIC Educational Resources Information Center

    Chiasson, Jean-Pierre; Stavro, Katherine; Rizkallah, Elie; Lapierre, Luc; Dussault, Maxime; Legault, Louis; Potvin, Stephane

    2012-01-01

    Objective: To assess the specificity of the Adult ADHD Self-Report Scale (ASRS-v1.1) in detecting ADHD among individuals with substance use disorders (SUDs). Method: A chart review of 183 SUD patients was conducted. Patients were screened for ADHD with the ASRS-v1.1 and were later assessed by a psychiatrist specialized in ADHD. Results: Among SUD…

  19. Robust Detection of Dynamical Change in Scalp EEG

    SciTech Connect

    Gailey, P.C.; Hively, L.M.; Protopopescu, V.A.

    1999-06-28

    We present a robust, model-independent technique for measuring changes in the dynamics underlying nonlinear time-serial data. We define indicators of dynamical change by comparing distribution functions on the attractor via L{sub 1}-distance and X{sup 2} statistics. We apply the measures to scalp EEG data with the objective of capturing the transition between non-seizure and epileptic brain activity in a timely, accurate, and non-invasive manner. We find a clear superiority of the new metrics in comparison to traditional nonlinear measures as discriminators of dynamical change.

  20. The Detection of the Methylated Wif-1 Gene Is More Accurate than a Fecal Occult Blood Test for Colorectal Cancer Screening

    PubMed Central

    Baumgaertner, Isabelle; Delchier, Jean-Charles; Tournigand, Christophe; Furet, Jean-Pierre; Carrau, Jean-Pierre; Canoui-Poitrine, Florence; Sobhani, Iradj

    2014-01-01

    Background The clinical benefit of guaiac fecal occult blood tests (FOBT) is now well established for colorectal cancer screening. Growing evidence has demonstrated that epigenetic modifications and fecal microbiota changes, also known as dysbiosis, are associated with CRC pathogenesis and might be used as surrogate markers of CRC. Patients and Methods We performed a cross-sectional study that included all consecutive subjects that were referred (from 2003 to 2007) for screening colonoscopies. Prior to colonoscopy, effluents (fresh stools, sera-S and urine-U) were harvested and FOBTs performed. Methylation levels were measured in stools, S and U for 3 genes (Wif1, ALX-4, and Vimentin) selected from a panel of 63 genes; Kras mutations and seven dominant and subdominant bacterial populations in stools were quantified. Calibration was assessed with the Hosmer-Lemeshow chi-square, and discrimination was determined by calculating the C-statistic (Area Under Curve) and Net Reclassification Improvement index. Results There were 247 individuals (mean age 60.8±12.4 years, 52% of males) in the study group, and 90 (36%) of these individuals were patients with advanced polyps or invasive adenocarcinomas. A multivariate model adjusted for age and FOBT led to a C-statistic of 0.83 [0.77–0.88]. After supplementary sequential (one-by-one) adjustment, Wif-1 methylation (S or U) and fecal microbiota dysbiosis led to increases of the C-statistic to 0.90 [0.84–0.94] (p = 0.02) and 0.81 [0.74–0.86] (p = 0.49), respectively. When adjusted jointly for FOBT and Wif-1 methylation or fecal microbiota dysbiosis, the increase of the C-statistic was even more significant (0.91 and 0.85, p<0.001 and p = 0.10, respectively). Conclusion The detection of methylated Wif-1 in either S or U has a higher performance accuracy compared to guaiac FOBT for advanced colorectal neoplasia screening. Conversely, fecal microbiota dysbiosis detection was not more accurate. Blood and urine

  1. Spatial Temporal Land Use Change Detection Using Google Earth Data

    NASA Astrophysics Data System (ADS)

    Wibowo, Adi; Osman Salleh, Khairulmaini; Sitanala Frans, F. Th. R.; Mulyo Semedi, Jarot

    2016-11-01

    Land use as representation of human activities had different type. Human activity needs land for home, food, school, work, and leisure. Land use changed depends on human activity in the world within spatial and temporal term. This study aims to identify land use change using Google Earth data spatially and temporally. To answer the aim of this research, Google Earth data within five-year used for the analysis. This technique use for detection and mapping the land use change. The result saw the spatial-temporal land use change each year. This result addressed very importance of Google Earth Data as spatial temporal land use detection for land use mapping.

  2. Acoustic change detection algorithm using an FM radio

    NASA Astrophysics Data System (ADS)

    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.

  3. Fast Change Point Detection for Electricity Market Analysis

    SciTech Connect

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

    2013-08-25

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

  4. Detection of Greenhouse-Gas-Induced Climatic Change

    SciTech Connect

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

    1998-05-26

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

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

    PubMed

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

    2010-08-01

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

  6. Full automatic fiducial marker detection on coil arrays for accurate instrumentation placement during MRI guided breast interventions

    NASA Astrophysics Data System (ADS)

    Filippatos, Konstantinos; Boehler, Tobias; Geisler, Benjamin; Zachmann, Harald; Twellmann, Thorsten

    2010-02-01

    With its high sensitivity, dynamic contrast-enhanced MR imaging (DCE-MRI) of the breast is today one of the first-line tools for early detection and diagnosis of breast cancer, particularly in the dense breast of young women. However, many relevant findings are very small or occult on targeted ultrasound images or mammography, so that MRI guided biopsy is the only option for a precise histological work-up [1]. State-of-the-art software tools for computer-aided diagnosis of breast cancer in DCE-MRI data offer also means for image-based planning of biopsy interventions. One step in the MRI guided biopsy workflow is the alignment of the patient position with the preoperative MR images. In these images, the location and orientation of the coil localization unit can be inferred from a number of fiducial markers, which for this purpose have to be manually or semi-automatically detected by the user. In this study, we propose a method for precise, full-automatic localization of fiducial markers, on which basis a virtual localization unit can be subsequently placed in the image volume for the purpose of determining the parameters for needle navigation. The method is based on adaptive thresholding for separating breast tissue from background followed by rigid registration of marker templates. In an evaluation of 25 clinical cases comprising 4 different commercial coil array models and 3 different MR imaging protocols, the method yielded a sensitivity of 0.96 at a false positive rate of 0.44 markers per case. The mean distance deviation between detected fiducial centers and ground truth information that was appointed from a radiologist was 0.94mm.

  7. A SAR ATR algorithm based on coherent change detection

    SciTech Connect

    Harmony, D.W.

    2000-12-01

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

  8. A Generalizable Hierarchical Bayesian Model for Persistent SAR Change Detection

    DTIC Science & Technology

    2012-04-01

    6] K. Ranney and M. Soumekh, “Signal subspace change detection in averaged multilook sar imagery,” Geoscience and Remote Sensing, IEEE Transactions on...A Generalizable Hierarchical Bayesian Model for Persistent SAR Change Detection Gregory E. Newstadta, Edmund G. Zelniob, and Alfred O. Hero IIIa...Base, OH, 45433, USA ABSTRACT This paper proposes a hierarchical Bayesian model for multiple-pass, multiple antenna synthetic aperture radar ( SAR

  9. Diffusion Geometry Based Nonlinear Methods for Hyperspectral Change Detection

    DTIC Science & Technology

    2010-05-12

    Schaum and A. Stocker, “Hyperspectral change detection and supervised matched filtering based on covariance equalization,” Proceedings of the SPIE, vol...5425, pp. 77- 90 (2004). 10. A. Schaum and A. Stocker, “Linear chromodynamics models for hyperspectral target detection,” Proceedings of the IEEE...Aerospace Conference (February 2003). 11. A. Schaum and A. Stocker, “Linear chromodynamics models for hyperspectral target detection

  10. An Optimized Method for Accurate Fetal Sex Prediction and Sex Chromosome Aneuploidy Detection in Non-Invasive Prenatal Testing

    PubMed Central

    Li, Haibo; Ding, Jie; Wen, Ping; Zhang, Qin; Xiang, Jingjing; Li, Qiong; Xuan, Liming; Kong, Lingyin; Mao, Yan; Zhu, Yijun; Shen, Jingjing; Liang, Bo; Li, Hong

    2016-01-01

    Massively parallel sequencing (MPS) combined with bioinformatic analysis has been widely applied to detect fetal chromosomal aneuploidies such as trisomy 21, 18, 13 and sex chromosome aneuploidies (SCAs) by sequencing cell-free fetal DNA (cffDNA) from maternal plasma, so-called non-invasive prenatal testing (NIPT). However, many technical challenges, such as dependency on correct fetal sex prediction, large variations of chromosome Y measurement and high sensitivity to random reads mapping, may result in higher false negative rate (FNR) and false positive rate (FPR) in fetal sex prediction as well as in SCAs detection. Here, we developed an optimized method to improve the accuracy of the current method by filtering out randomly mapped reads in six specific regions of the Y chromosome. The method reduces the FNR and FPR of fetal sex prediction from nearly 1% to 0.01% and 0.06%, respectively and works robustly under conditions of low fetal DNA concentration (1%) in testing and simulation of 92 samples. The optimized method was further confirmed by large scale testing (1590 samples), suggesting that it is reliable and robust enough for clinical testing. PMID:27441628

  11. Establishment of an accurate and fast detection method using molecular beacons in loop-mediated isothermal amplification assay

    PubMed Central

    Liu, Wei; Huang, Simo; Liu, Ningwei; Dong, Derong; Yang, Zhan; Tang, Yue; Ma, Wen; He, Xiaoming; Ao, Da; Xu, Yaqing; Zou, Dayang; Huang, Liuyu

    2017-01-01

    This study established a constant-temperature fluorescence quantitative detection method, combining loop-mediated isothermal amplification (LAMP) with molecular beacons. The advantages of LAMP are its convenience and efficiency, as it does not require a thermocycler and results are easily visualized by the naked eye. However, a major disadvantage of current LAMP techniques is the use of indirect evaluation methods (e.g., electrophoresis, SYBR Green I dye, precipitation, hydroxynaphthol blue dye, the turbidimetric method, calcein/Mn2+ dye, and the composite probe method), which cannot distinguish between the desired products and products of nonspecific amplification, thereby leading to false positives. Use of molecular beacons avoids this problem because molecular beacons produce fluorescence signals only when binding to target DNA, thus acting as a direct indicator of amplification products. Our analyses determined the optimal conditions for molecular beacons as an evaluation tool in LAMP: beacon length of 25–45 bp, beacon concentration of 0.6–1 pmol/μL, and reaction temperature of 60–65 °C. In conclusion, we validated a novel molecular beacon loop-mediated isothermal amplification method (MB-LAMP), realizing the direct detection of LAMP product. PMID:28059137

  12. You Seem Certain but You Were Wrong Before: Developmental Change in Preschoolers’ Relative Trust in Accurate versus Confident Speakers

    PubMed Central

    Brosseau-Liard, Patricia; Cassels, Tracy; Birch, Susan

    2014-01-01

    The present study tested how preschoolers weigh two important cues to a person’s credibility, namely prior accuracy and confidence, when deciding what to learn and believe. Four- and 5-year-olds (N = 96) preferred to believe information provided by a confident rather than hesitant individual; however, when confidence conflicted with accuracy, preschoolers increasingly favored information from the previously accurate but hesitant individual as they aged. These findings reveal an important developmental progression in how children use others’ confidence and prior accuracy to shape what they learn and provide a window into children’s developing social cognition, scepticism, and critical thinking. PMID:25254553

  13. DNA extraction techniques compared for accurate detection of genetically modified organisms (GMOs) in maize food and feed products.

    PubMed

    Turkec, Aydin; Kazan, Hande; Karacanli, Burçin; Lucas, Stuart J

    2015-08-01

    In this paper, DNA extraction methods have been evaluated to detect the presence of genetically modified organisms (GMOs) in maize food and feed products commercialised in Turkey. All the extraction methods tested performed well for the majority of maize foods and feed products analysed. However, the highest DNA content was achieved by the Wizard, Genespin or the CTAB method, all of which produced optimal DNA yield and purity for different maize food and feed products. The samples were then screened for the presence of GM elements, along with certified reference materials. Of the food and feed samples, 8 % tested positive for the presence of one GM element (NOS terminator), of which half (4 % of the total) also contained a second element (the Cauliflower Mosaic Virus 35S promoter). The results obtained herein clearly demonstrate the presence of GM maize in the Turkish market, and that the Foodproof GMO Screening Kit provides reliable screening of maize food and feed products.

  14. Nanoarray of polycyclic aromatic hydrocarbons and carbon nanotubes for accurate and predictive detection in real-world environmental humidity.

    PubMed

    Zilberman, Yael; Ionescu, Radu; Feng, Xinliang; Müllen, Klaus; Haick, Hossam

    2011-08-23

    In the present work, we introduce a cross-reactive array of synthetically designed polycyclic aromatic hydrocarbons (PAH) and single-walled carbon nanotube (SWCNT) bilayers and demonstrate the huge potential of the array in discriminating between polar and nonpolar volatile organic compounds (VOCs), as well as between the different VOCs from each subgroup. Using appropriate combinations of PAH/SWCNT sensors, we demonstrate that high sensitivity and accuracy values can be obtained for discriminating polar and nonpolar VOCs in samples with variable humidity levels (5-80% RH). The same array of sensors exhibited self-learning capabilities that facilitated exchanging information about environmental properties under observation. The results presented here could lead to the development of a cost-effective, lightweight, low-power, and non-invasive tool for a widespread detection of VOCs in real-world environmental, security, food, health, and other applications.

  15. Change detection from very high resolution satellite time series with variable off-nadir angle

    NASA Astrophysics Data System (ADS)

    Barazzetti, Luigi; Brumana, Raffaella; Cuca, Branka; Previtali, Mattia

    2015-06-01

    Very high resolution (VHR) satellite images have the potential for revealing changes occurred overtime with a superior level of detail. However, their use for metric purposes requires accurate geo-localization with ancillary DEMs and GCPs to achieve sub-pixel terrain correction, in order to obtain images useful for mapping applications. Change detection with a time series of VHS images is not a simple task because images acquired with different off-nadir angles have a lack of pixel-to-pixel image correspondence, even after accurate geo-correction. This paper presents a procedure for automatic change detection able to deal with variable off-nadir angles. The case study concerns the identification of damaged buildings from pre- and post-event images acquired on the historic center of L'Aquila (Italy), which was struck by an earthquake in April 2009. The developed procedure is a multi-step approach where (i) classes are assigned to both images via object-based classification, (ii) an initial alignment is provided with an automated tile-based rubber sheeting interpolation on the extracted layers, and (iii) change detection is carried out removing residual mis-registration issues resulting in elongated features close to building edges. The method is fully automated except for some thresholds that can be interactively set to improve the visualization of the damaged buildings. The experimental results proved that damages can be automatically found without additional information, such as digital surface models, SAR data, or thematic vector layers.

  16. A New Metric for Detecting Change in Slowly Evolving Brain Tumors: Validation in Meningioma Patients

    PubMed Central

    Pohl, Kilian M.; Konukoglu, Ender; Novellas, Sebastian; Ayache, Nicholas; Fedorov, Andriy; Talos, Ion-Florin; Golby, Alexandra; Wells, William M.; Kikinis, Ron; Black, Peter M.

    2011-01-01

    Background Change detection is a critical component in the diagnosis and monitoring of many slowly evolving pathologies. Objective This article describes a semi-automatic monitoring approach using longitudinal medical images. We test the method on brain scans of meningioma patients, which experts found difficult to monitor as the tumor evolution is very slow and may be obscured by artifacts related to image acquisition. Methods We describe a semi-automatic procedure targeted towards identifying difficult-to-detect changes in brain tumor imaging. The tool combines input from a medical expert with state-of-the-art technology. The software is easy to calibrate and, in less than five minutes, returns the total volume of tumor change in mm3. We test the method on post-gadolinium, T1-weighted Magnetic Resonance Images of ten meningioma patients and compare our results to experts’ findings. We also perform benchmark testing with synthetic data. Results Our experiments indicated that experts’ visual inspections are not sensitive enough to detect subtle growth. Measurements based on experts’ manual segmentations were highly accurate but also labor intensive. The accuracy of our approach was comparable to the experts’ results. However, our approach required far less user input and generated more consistent measurements. Conclusion The sensitivity of experts’ visual inspection is often too low to detect subtle growth of meningiomas from longitudinal scans. Measurements based on experts’ segmentation are highly accurate but generally too labor intensive for standard clinical settings. We described an alternative metric that provides accurate and robust measurements of subtle tumor changes while requiring a minimal amount of user input. PMID:21206318

  17. Signal detection using change point analysis in postmarket surveillance†

    PubMed Central

    Xu, Zhiheng; Kass-Hout, Taha; Anderson-Smits, Colin; Gray, Gerry

    2015-01-01

    Purpose Signal detection methods have been used extensively in postmarket surveillance to identify elevated risks of adverse events associated with medical products (drugs, vaccines, and devices). However, current popular disproportionality methods ignore useful information such as trends when the data are aggregated over time for signal detection. Methods In this paper, we applied change point analysis (CPA) to trend analysis of medical products in a spontaneous adverse event reporting system. CPA was used to detect the time point at which statistical properties of a sequence of observations change over time. Two CPA approaches, change in mean and change in variance, were demonstrated by an example using neurostimulator adverse event dataset. Results Two significant change points associated with upward trends were detected in June 2008 (n = 20, p < 0.001) and May 2011 (n = 51, p = 0.003). Further investigation confirmed battery issues and expansion of the indication for use could be possible causes for the occurrence of these change points. Two time points showed extremely low number of loss of therapy events, two cases in October 2009 and three in November 2009, which could be the result of reporting issues such as underreporting. Conclusion As a complimentary tool to current signal detection efforts at FDA, CPA can be used to detect changes in the association between medical products and adverse events over time. Detecting these changes could be critical for public health regulation, adverse events surveillance, product recalls, and regulators’ understanding of the connection between adverse events and other events regarding regulated products. © 2015 The Authors. Pharmacoepidemiology and Drug Safety published by John Wiley & Sons, Ltd. PMID:25903221

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

    NASA Astrophysics Data System (ADS)

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

    2009-09-01

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

  19. A Hopfield neural network for image change detection.

    PubMed

    Pajares, Gonzalo

    2006-09-01

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

  20. Automated baseline change detection phase I. Final report

    SciTech Connect

    1995-12-01

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

  1. Detection and Attribution of Anthropogenic Climate Change Impacts

    NASA Technical Reports Server (NTRS)

    Rosenzweig, Cynthia; Neofotis, Peter

    2013-01-01

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

  2. New Method for Accurate Calibration of Micro-Channel Plate based Detection Systems and its use in the Fast Plasma Investigation of NASA's Magnetospheric MultiScale Mission

    NASA Astrophysics Data System (ADS)

    Gliese, U.; Avanov, L. A.; Barrie, A.; Kujawski, J. T.; Mariano, A. J.; Tucker, C. J.; Chornay, D. J.; Cao, N. T.; Zeuch, M.; Pollock, C. J.; Jacques, A. D.

    2013-12-01

    The Fast Plasma Investigation (FPI) of the NASA Magnetospheric MultiScale (MMS) mission employs 16 Dual Electron Spectrometers (DESs) and 16 Dual Ion Spectrometers (DISs) with 4 of each type on each of 4 spacecraft to enable fast (30ms for electrons; 150ms for ions) and spatially differentiated measurements of full the 3D particle velocity distributions. This approach presents a new and challenging aspect to the calibration and operation of these instruments on ground and in flight. The response uniformity and reliability of their calibration and the approach to handling any temporal evolution of these calibrated characteristics all assume enhanced importance in this application, where we attempt to understand the meaning of particle distributions within the ion and electron diffusion regions. Traditionally, the micro-channel plate (MCP) based detection systems for electrostatic particle spectrometers have been calibrated by setting a fixed detection threshold and, subsequently, measuring a detection system count rate plateau curve to determine the MCP voltage that ensures the count rate has reached a constant value independent of further variation in the MCP voltage. This is achieved when most of the MCP pulse height distribution (PHD) is located at higher values (larger pulses) than the detection amplifier threshold. This method is adequate in single-channel detection systems and in multi-channel detection systems with very low crosstalk between channels. However, in dense multi-channel systems, it can be inadequate. Furthermore, it fails to fully and individually characterize each of the fundamental parameters of the detection system. We present a new detection system calibration method that enables accurate and repeatable measurement and calibration of MCP gain, MCP efficiency, signal loss due to variation in gain and efficiency, crosstalk from effects both above and below the MCP, noise margin, and stability margin in one single measurement. The fundamental

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

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

    PubMed

    Ninomiya, Yoshiyuki; Yoshimoto, Atsushi

    2008-03-01

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

  5. Change point detection of the Persian Gulf sea surface temperature

    NASA Astrophysics Data System (ADS)

    Shirvani, A.

    2017-01-01

    In this study, the Student's t parametric and Mann-Whitney nonparametric change point models (CPMs) were applied to detect change point in the annual Persian Gulf sea surface temperature anomalies (PGSSTA) time series for the period 1951-2013. The PGSSTA time series, which were serially correlated, were transformed to produce an uncorrelated pre-whitened time series. The pre-whitened PGSSTA time series were utilized as the input file of change point models. Both the applied parametric and nonparametric CPMs estimated the change point in the PGSSTA in 1992. The PGSSTA follow the normal distribution up to 1992 and thereafter, but with a different mean value after year 1992. The estimated slope of linear trend in PGSSTA time series for the period 1951-1992 was negative; however, that was positive after the detected change point. Unlike the PGSSTA, the applied CPMs suggested no change point in the Niño3.4SSTA time series.

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

    NASA Astrophysics Data System (ADS)

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

    2016-05-01

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

  7. Hardware accelerator design for change detection in smart camera

    NASA Astrophysics Data System (ADS)

    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.

  8. Bivariate gamma distributions for image registration and change detection.

    PubMed

    Chatelain, Florent; Tourneret, Jean-Yves; Inglada, Jordi; Ferrari, André

    2007-07-01

    This paper evaluates the potential interest of using bivariate gamma distributions for image registration and change detection. The first part of this paper studies estimators for the parameters of bivariate gamma distributions based on the maximum likelihood principle and the method of moments. The performance of both methods are compared in terms of estimated mean square errors and theoretical asymptotic variances. The mutual information is a classical similarity measure which can be used for image registration or change detection. The second part of the paper studies some properties of the mutual information for bivariate Gamma distributions. Image registration and change detection techniques based on bivariate gamma distributions are finally investigated. Simulation results conducted on synthetic and real data are very encouraging. Bivariate gamma distributions are good candidates allowing us to develop new image registration algorithms and new change detectors.

  9. Change detection inflates confidence on a subsequent recognition task.

    PubMed

    Fitzgerald, Ryan J; Oriet, Chris; Price, Heather L

    2011-11-01

    A face viewed under good encoding conditions is more likely to be remembered than a face viewed under poor encoding conditions. In four experiments we investigated how encoding conditions affected confidence in recognising faces from line-ups. Participants performed a change detection task followed by a recognition task and then rated how confident they were in their recognition accuracy. In the first two experiments the same faces were repeated across trials. In the final two experiments novel faces were used on each trial. Target-present and target-absent line-ups were utilised. In each experiment participants had greater recognition confidence after change detection than after change blindness. The finding that change detection inflates confidence, even for inaccurate recognitions, indicates recognition certainty can be a product of perceived encoding conditions rather than authentic memory strength.

  10. Coherent Change Detection: Theoretical Description and Experimental Results

    DTIC Science & Technology

    2006-08-01

    multilook polarimetric and interferometric SAR imagery,” IEEE Transactions on Geoscience and Remote Sensing, vol. 32, no. 5, pp. 1017–1027, 1994. 50. J. W...scene changes using repeat pass Synthetic Aperture Radar ( SAR ) imagery. As SAR is a coherent imaging system two forms of change detection may be...changes to the sub-resolution cell scattering structure that may be undetectable using inco- herent techniques. The repeat pass SAR imagery however, must

  11. Geometric change detection in urban environments using images.

    PubMed

    Taneja, Aparna; Ballan, Luca; Pollefeys, Marc

    2015-11-01

    We propose a method to detect changes in the geometry of a city using panoramic images captured by a car driving around the city. The proposed method can be used to significantly optimize the process of updating the 3D model of an urban environment that is changing over time, by restricting this process to only those areas where changes are detected. With this application in mind, we designed our algorithm to specifically detect only structural changes in the environment, ignoring any changes in its appearance, and ignoring also all the changes which are not relevant for update purposes such as cars, people etc. The approach also accounts for the challenges involved in a large scale application of change detection, such as inaccuracies in the input geometry, errors in the geo-location data of the images as well as the limited amount of information due to sparse imagery. We evaluated our approach on a small scale setup using high resolution, densely captured images and a large scale setup covering an entire city using instead the more realistic scenario of low resolution, sparsely captured images. A quantitative evaluation was also conducted for the large scale setup consisting of 14,000 images.

  12. Can Impacts of Climate Change and Agricultural Adaptation Strategies Be Accurately Quantified if Crop Models Are Annually Re-Initialized?

    PubMed

    Basso, Bruno; Hyndman, David W; Kendall, Anthony D; Grace, Peter R; Robertson, G Philip

    2015-01-01

    Estimates of climate change impacts on global food production are generally based on statistical or process-based models. Process-based models can provide robust predictions of agricultural yield responses to changing climate and management. However, applications of these models often suffer from bias due to the common practice of re-initializing soil conditions to the same state for each year of the forecast period. If simulations neglect to include year-to-year changes in initial soil conditions and water content related to agronomic management, adaptation and mitigation strategies designed to maintain stable yields under climate change cannot be properly evaluated. We apply a process-based crop system model that avoids re-initialization bias to demonstrate the importance of simulating both year-to-year and cumulative changes in pre-season soil carbon, nutrient, and water availability. Results are contrasted with simulations using annual re-initialization, and differences are striking. We then demonstrate the potential for the most likely adaptation strategy to offset climate change impacts on yields using continuous simulations through the end of the 21st century. Simulations that annually re-initialize pre-season soil carbon and water contents introduce an inappropriate yield bias that obscures the potential for agricultural management to ameliorate the deleterious effects of rising temperatures and greater rainfall variability.

  13. Can Impacts of Climate Change and Agricultural Adaptation Strategies Be Accurately Quantified if Crop Models Are Annually Re-Initialized?

    PubMed Central

    Basso, Bruno; Hyndman, David W.; Kendall, Anthony D.; Grace, Peter R.; Robertson, G. Philip

    2015-01-01

    Estimates of climate change impacts on global food production are generally based on statistical or process-based models. Process-based models can provide robust predictions of agricultural yield responses to changing climate and management. However, applications of these models often suffer from bias due to the common practice of re-initializing soil conditions to the same state for each year of the forecast period. If simulations neglect to include year-to-year changes in initial soil conditions and water content related to agronomic management, adaptation and mitigation strategies designed to maintain stable yields under climate change cannot be properly evaluated. We apply a process-based crop system model that avoids re-initialization bias to demonstrate the importance of simulating both year-to-year and cumulative changes in pre-season soil carbon, nutrient, and water availability. Results are contrasted with simulations using annual re-initialization, and differences are striking. We then demonstrate the potential for the most likely adaptation strategy to offset climate change impacts on yields using continuous simulations through the end of the 21st century. Simulations that annually re-initialize pre-season soil carbon and water contents introduce an inappropriate yield bias that obscures the potential for agricultural management to ameliorate the deleterious effects of rising temperatures and greater rainfall variability. PMID:26043188

  14. Accurate classification of 29 objects detected in the 39 month Palermo Swift/BAT hard X-ray catalogue

    NASA Astrophysics Data System (ADS)

    Parisi, P.; Masetti, N.; Jiménez-Bailón, E.; Chavushyan, V.; Palazzi, E.; Landi, R.; Malizia, A.; Bassani, L.; Bazzano, A.; Bird, A. J.; Charles, P. A.; Galaz, G.; Mason, E.; McBride, V. A.; Minniti, D.; Morelli, L.; Schiavone, F.; Ubertini, P.

    2012-09-01

    Through an optical campaign performed at four telescopes located in the northern and the southern hemispheres, plus archival data from two on-line sky surveys, we obtained optical spectroscopy for 29 counterparts of unclassified or poorly studied hard X-ray emitting objects detected with Swift /Burst Alert Telescope (BAT) and listed in the 39 month Palermo catalogue. All these objects also have observations taken with Swift /X-ray Telescope (XRT) or XMM-European Photon Imaging Camera (EPIC) which not only allow us to pinpoint their optical counterpart, but also study their X-ray spectral properties (column density, power law photon index, and F2-10 keV flux). We find that 28 sources in our sample are active galactic nuclei (AGNs); 7 are classified as type 1, while 21 are of type 2; the remaining object is a Galactic cataclysmic variable. Among our type 1 AGNs, we find 5 objects of intermediate Seyfert type (1.2-1.9) and one narrow-line Seyfert 1 galaxy; for 4 out of 7 sources, we are able to estimate the central black hole mass. Three of the type 2 AGNs of our sample display optical features typical of low-ionization nuclear emission-line regions (LINER) and one is a likely Compton thick AGN. All galaxies classified in this work are relatively nearby objects since their redshifts lie in the range 0.008-0.075; the only Galactic object found lies at an estimated distance of 90 pc. We also investigate the optical versus X-ray emission ratio of the galaxies of our sample to test the AGN unified model. For these galaxies, we also compare the X-ray absorption (caused by gas) with the optical reddening (caused by dust): we find that for most of our sources, specifically those of type 1.9-2.0 the former is higher than the latter confirming early results of Maiolino and collaborators; this is possibly due to the properties of dust in the circumnuclear obscuring torus of the AGN. Based on observations obtained from the following observatories: the Astronomical Observatory of

  15. Compact and cost-effective temperature-insensitive bio-sensor based on long-period fiber gratings for accurate detection of E. coli bacteria in water.

    PubMed

    Dandapat, Krishnendu; Tripathi, Saurabh Mani; Chinifooroshan, Yasser; Bock, Wojtek J; Mikulic, Predrag

    2016-09-15

    We propose and demonstrate a novel temperature-insensitive bio-sensor for accurate and quantitative detection of Escherichia coli (E. coli) bacteria in water. Surface sensitivity is maximized by operating the long-period fiber grating (LPFG) closest to its turnaround wavelength, and the temperature insensitivity is achieved by selectively exciting a pair of cladding modes with opposite dispersion characteristics. Our sensor shows a nominal temperature sensitivity of ∼1.25  pm/°C, which can be further reduced by properly adjusting the LPFG lengths, while maintaining a high refractive index sensitivity of 1929 nm/RIU. The overall length of the sensor is ∼3.6  cm, making it ideally suitable for bio-sensing applications. As an example, we also show the sensor's capability for reliable, quantitative detection of E. coli bacteria in water over a temperature fluctuation of room temperature to 40°C.

  16. Change detection monitoring of Khoramabad Region(IRAN) via remote sensing

    NASA Astrophysics Data System (ADS)

    Matinfar, Hamid Reza

    2010-05-01

    The importance of accurate and timely information describing the nature and extent of land resources and changes over time is increasing, especially in rapidly growing metropolitan areas. Change detection is a technique in remote sensing for detecting the changes which have occurred in the existing phenomena over two or more periods of time in a particular area. In this paper, Khoramabad a city in Lorestan province of Iran, was examined in a case study via three techniques of remote sensing: (1) NDVI comparison, (2) Principle Component Analysis, and (3) the Post Classification. To carry out these three techniques, TM and ETM+ data obtained from Landsat Satellite within the years 1991 to 2002was used to monitor environmental changes especially the physical development of the area and its devastating effects on the green space. In this research, one of the capabilities of Thematic Mapper of Landsat Satellite is presented which is oriented towards determining land use changes and methodology in comparison to the change detection techniques via the standard method.. The result presented here indicates that the farming land area decreased between 1991 and 2002 by 14% from 4975 to 3672 ha. Also the urban and non arable land area increased from 5376 to 6678 ha. We may conclude any land use/land cover change must be permitted by land management expert

  17. Detecting changes in dynamic and complex acoustic environments

    PubMed Central

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

    2017-01-01

    Natural sounds such as wind or rain, are characterized by the statistical occurrence of their constituents. Despite their complexity, listeners readily detect changes in these contexts. We here address the neural basis of statistical decision-making using a combination of psychophysics, EEG and modelling. In a texture-based, change-detection paradigm, human performance and reaction times improved with longer pre-change exposure, consistent with improved estimation of baseline statistics. Change-locked and decision-related EEG responses were found in a centro-parietal scalp location, whose slope depended on change size, consistent with sensory evidence accumulation. The potential's amplitude scaled with the duration of pre-change exposure, suggesting a time-dependent decision threshold. Auditory cortex-related potentials showed no response to the change. A dual timescale, statistical estimation model accounted for subjects' performance. Furthermore, a decision-augmented auditory cortex model accounted for performance and reaction times, suggesting that the primary cortical representation requires little post-processing to enable change-detection in complex acoustic environments. DOI: http://dx.doi.org/10.7554/eLife.24910.001 PMID:28262095

  18. Towards a Framework for Change Detection in Data Sets

    NASA Astrophysics Data System (ADS)

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

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

  19. Detecting changes in dynamic and complex acoustic environments.

    PubMed

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

    2017-03-06

    Natural sounds such as wind or rain, are characterized by the statistical occurrence of their constituents. Despite their complexity, listeners readily detect changes in these contexts. We here address the neural basis of statistical decision-making using a combination of psychophysics, EEG and modelling. In a texture-based, change-detection paradigm, human performance and reaction times improved with longer pre-change exposure, consistent with improved estimation of baseline statistics. Change-locked and decision-related EEG responses were found in a centro-parietal scalp location, whose slope depended on change size, consistent with sensory evidence accumulation. The potential's amplitude scaled with the duration of pre-change exposure, suggesting a time-dependent decision threshold. Auditory cortex-related potentials showed no response to the change. A dual timescale, statistical estimation model accounted for subjects' performance. Furthermore, a decision-augmented auditory cortex model accounted for performance and reaction times, suggesting that the primary cortical representation requires little post-processing to enable change-detection in complex acoustic environments.

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

    SciTech Connect

    Usynin, A; Ramsey, C

    2014-06-01

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

  1. Region Based Forest Change Detection from CARTOSAT-1 Stereo Imagery

    NASA Astrophysics Data System (ADS)

    Tian, J.; Leitloff, J.; Krauß, T.; Reinartz, P.

    2011-09-01

    Tree height is a fundamental parameter for describing the forest situation and changes. The latest development of automatic Digital Surface Model (DSM) generation techniques allows new approaches of forest change detection from satellite stereo imagery. This paper shows how DSMs can support the change detection in forest area. A novel region based forest change detection method is proposed using single-channel CARTOSAT-1 stereo imagery. In the first step, DSMs from two dates are generated based on automatic matching technology. After co-registration and normalising by using LiDAR data, the mean-shift segmentation is applied to the original pan images, and the images of both dates are classified to forest and non-forest areas by analysing their histograms and height differences. In the second step, a rough forest change detection map is generated based on the comparison of the two forest map. Then the GLCM texture from the nDSM and the Cartosat-1 images of the resulting regions are analyzed and compared, the real changes are extracted by SVM based classification.

  2. Structural Change Can Be Detected in Advanced-Glaucoma Eyes

    PubMed Central

    Belghith, Akram; Medeiros, Felipe A.; Bowd, Christopher; Liebmann, Jeffrey M.; Girkin, Christopher A.; Weinreb, Robert N.; Zangwill, Linda M.

    2016-01-01

    Purpose To compare spectral-domain optical coherence tomography (SD-OCT) standard structural measures and a new three-dimensional (3D) volume optic nerve head (ONH) change detection method for detecting change over time in severely advanced-glaucoma (open-angle glaucoma [OAG]) patients. Methods Thirty-five eyes of 35 patients with very advanced glaucoma (defined as a visual field mean deviation < −21 dB) and 46 eyes of 30 healthy subjects to estimate aging changes were included. Circumpapillary retinal fiber layer thickness (cpRNFL), minimum rim width (MRW), and macular retinal ganglion cell–inner plexiform layer (GCIPL) thicknesses were measured using the San Diego Automated Layer Segmentation Algorithm (SALSA). Progression was defined as structural loss faster than 95th percentile of healthy eyes. Three-dimensional volume ONH change was estimated using the Bayesian-kernel detection scheme (BKDS), which does not require extensive retinal layer segmentation. Results The number of progressing glaucoma eyes identified was highest for 3D volume BKDS (13, 37%), followed by GCPIL (11, 31%), cpRNFL (4, 11%), and MRW (2, 6%). In advanced-OAG eyes, only the mean rate of GCIPL change reached statistical significance, −0.18 μm/y (P = 0.02); the mean rates of cpRNFL and MRW change were not statistically different from zero. In healthy eyes, the mean rates of cpRNFL, MRW, and GCIPL change were significantly different from zero. (all P < 0.001). Conclusions Ganglion cell–inner plexiform layer and 3D volume BKDS show promise for identifying change in severely advanced glaucoma. These results suggest that structural change can be detected in very advanced disease. Longer follow-up is needed to determine whether changes identified are false positives or true progression. PMID:27454660

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

    NASA Astrophysics Data System (ADS)

    Saur, Günter; Krüger, Wolfgang; Schumann, Arne

    2014-03-01

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

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

    SciTech Connect

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

    2016-01-11

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

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

    DOE PAGES

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

    2016-01-11

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

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

    SciTech Connect

    Sorensen, K.W.

    1995-03-01

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

  8. Reconstruction of interrupted SAR imagery for persistent surveillance change detection

    NASA Astrophysics Data System (ADS)

    Stojanovic, Ivana; Karl, W. C.; Novak, Les

    2012-05-01

    In this paper we apply a sparse signal recovery technique for synthetic aperture radar (SAR) image formation from interrupted phase history data. Timeline constraints imposed on multi-function modern radars result in interrupted SAR data collection, which in turn leads to corrupted imagery that degrades reliable change detection. In this paper we extrapolate the missing data by applying the basis pursuit denoising algorithm (BPDN) in the image formation step, effectively, modeling the SAR scene as sparse. We investigate the effects of regular and random interruptions on the SAR point spread function (PSF), as well as on the quality of both coherent (CCD) and non-coherent (NCCD) change detection. We contrast the sparse reconstruction to the matched filter (MF) method, implemented via Fourier processing with missing data set to zero. To illustrate the capabilities of the gap-filling sparse reconstruction algorithm, we evaluate change detection performance using a pair of images from the GOTCHA data set.

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

    NASA Technical Reports Server (NTRS)

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

    1977-01-01

    Procedures for detecting changes in Landsat multispectral scanning imagery of coastal zone environments are discussed. Four detection procedures are examined: a comparison of independently produced spectral classifications; a classification of a multispectral difference data set; a single analysis of a multidate data set; and a maximum likelihood classification using multistage decision logic. The relatively complex maximum likelihood classification technique was found to yield results closest to those obtained with the comparison of independently produced spectral classifications, the chosen standard.

  10. Investigation on automatic change detection using pixel-changes and DSM-changes with ALOS-PRISM triplet images

    NASA Astrophysics Data System (ADS)

    Sasagawa, A.; Baltsavias, E.; Kocaman Aksakal, S.; Wegner, J. D.

    2013-10-01

    A new algorithm for automatic change detection is presented. It detects a pixel-change and DSM-change from two orthoimages and two DSMs, then it extracts the polygons in elevation-changed areas. Pixel-change is detected by using least squares fitting technique. This method can extract the visible changed areas between two orthoimages, while DSM-change is detected by difference DSM. From these two changes, polygons in elevation-changed areas are extracted using the longest matched line selection techniques. This method can automatically detect not only visible changed areas such as vegetated areas, new road construction areas and so on, but also elevation-changed areas such as new building construction, land improvement areas and so on with footprint polygon extraction. We have tested our method using the two sets of ALOS-PRISM triplet images observed over a testfield in Tsukuba, Japan. We confirmed that this method has an effect finding changed areas. Also we compared the number of extracted polygons between manual operation and our automatic method.

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

    NASA Astrophysics Data System (ADS)

    Mishra, B.; Susaki, J.

    2014-09-01

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

  12. Using adversary text to detect adversary phase changes.

    SciTech Connect

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

    2009-05-01

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

  13. Landsat change detection can aid in water quality monitoring

    NASA Technical Reports Server (NTRS)

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

    1977-01-01

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

  14. Tonicity balance, and not electrolyte-free water calculations, more accurately guides therapy for acute changes in natremia.

    PubMed

    Carlotti, A P; Bohn, D; Mallie, J P; Halperin, M L

    2001-05-01

    The usual way to decide why hyponatremia or hypernatremia has developed and to plan goals for its therapy is to analyze events in electrolyte-free water (EFW) terms. We shall demonstrate that an EFW balance does not supply this information. Rather, one must calculate mass balances for water and sodium plus potassium separately (a tonicity balance) to understand the basis for the change in natremia and the proper goals for its therapy. These points are illustrated with a clinical example.

  15. Dissolve Detection Using Intensity Change Information of Edge Pixels

    NASA Astrophysics Data System (ADS)

    Kwon, Chul-Hyun; Han, Doo-Jin; Kim, Hyun-Sool; Lee, Myung-Ho; Park, Sang-Hui

    Shot transition detection is a core technology in video browsing, indexing systems and information retrieval. In this paper we propose a dissolve detection algorithm using the characteristics of edge in MPEG compressed video. Using the intensity change information of edge pixels obtained by Sobel edge detector, we detect the location of a dissolve and its precise duration. We also present a new reliable method to eliminate the false dissolves. The proposed algorithm is tested in various types of videos, and the experimental results show that the proposed algorithm is effective and robust.

  16. Optimal Parameter Exploration for Online Change-Point Detection in Activity Monitoring Using Genetic Algorithms

    PubMed Central

    Khan, Naveed; McClean, Sally; Zhang, Shuai; Nugent, Chris

    2016-01-01

    In recent years, smart phones with inbuilt sensors have become popular devices to facilitate activity recognition. The sensors capture a large amount of data, containing meaningful events, in a short period of time. The change points in this data are used to specify transitions to distinct events and can be used in various scenarios such as identifying change in a patient’s vital signs in the medical domain or requesting activity labels for generating real-world labeled activity datasets. Our work focuses on change-point detection to identify a transition from one activity to another. Within this paper, we extend our previous work on multivariate exponentially weighted moving average (MEWMA) algorithm by using a genetic algorithm (GA) to identify the optimal set of parameters for online change-point detection. The proposed technique finds the maximum accuracy and F_measure by optimizing the different parameters of the MEWMA, which subsequently identifies the exact location of the change point from an existing activity to a new one. Optimal parameter selection facilitates an algorithm to detect accurate change points and minimize false alarms. Results have been evaluated based on two real datasets of accelerometer data collected from a set of different activities from two users, with a high degree of accuracy from 99.4% to 99.8% and F_measure of up to 66.7%. PMID:27792177

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

    NASA Astrophysics Data System (ADS)

    Akbari, Hamed; Kosugi, Yukio; Kojima, Kazuyuki

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

  18. Climate Change Detection and Attribution of Infrared Spectrum Measurements

    NASA Technical Reports Server (NTRS)

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

    2012-01-01

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

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

    NASA Astrophysics Data System (ADS)

    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.

  20. Detection of cardiac activity changes from human speech

    NASA Astrophysics Data System (ADS)

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

    2015-05-01

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

  1. An Integrated Tool to Study MHC Region: Accurate SNV Detection and HLA Genes Typing in Human MHC Region Using Targeted High-Throughput Sequencing

    PubMed Central

    Liu, Xiao; Xu, Yinyin; Liang, Dequan; Gao, Peng; Sun, Yepeng; Gifford, Benjamin; D’Ascenzo, Mark; Liu, Xiaomin; Tellier, Laurent C. A. M.; Yang, Fang; Tong, Xin; Chen, Dan; Zheng, Jing; Li, Weiyang; Richmond, Todd; Xu, Xun; Wang, Jun; Li, Yingrui

    2013-01-01

    The major histocompatibility complex (MHC) is one of the most variable and gene-dense regions of the human genome. Most studies of the MHC, and associated regions, focus on minor variants and HLA typing, many of which have been demonstrated to be associated with human disease susceptibility and metabolic pathways. However, the detection of variants in the MHC region, and diagnostic HLA typing, still lacks a coherent, standardized, cost effective and high coverage protocol of clinical quality and reliability. In this paper, we presented such a method for the accurate detection of minor variants and HLA types in the human MHC region, using high-throughput, high-coverage sequencing of target regions. A probe set was designed to template upon the 8 annotated human MHC haplotypes, and to encompass the 5 megabases (Mb) of the extended MHC region. We deployed our probes upon three, genetically diverse human samples for probe set evaluation, and sequencing data show that ∼97% of the MHC region, and over 99% of the genes in MHC region, are covered with sufficient depth and good evenness. 98% of genotypes called by this capture sequencing prove consistent with established HapMap genotypes. We have concurrently developed a one-step pipeline for calling any HLA type referenced in the IMGT/HLA database from this target capture sequencing data, which shows over 96% typing accuracy when deployed at 4 digital resolution. This cost-effective and highly accurate approach for variant detection and HLA typing in the MHC region may lend further insight into immune-mediated diseases studies, and may find clinical utility in transplantation medicine research. This one-step pipeline is released for general evaluation and use by the scientific community. PMID:23894464

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  3. Detecting human influence in observed changes in precipitation

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

  4. SAR image change detection using watershed and spectral clustering

    NASA Astrophysics Data System (ADS)

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

    2011-12-01

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

  5. Remote sensing of debris-covered glaciers: Change detection and analysis using multiple sensors

    NASA Astrophysics Data System (ADS)

    Ahn, Y.; Huh, K.; Mark, B. G.; La Frenierre, J.; Gulley, J. D.; Park, K.

    2013-12-01

    Debris-cover can insulate glaciers and hinder surface melting, but also challenges accurate assessment of change detection and subsequent risk evaluation of outburst floods from moraine-dammed supra-glacial lakes that endanger downstream inhabitants. These events have been predicted to increase frequency along with the coverage of debris as warming accelerates. Enhanced monitoring capability from optical air and space-borne sensors has improved the detection of changes in surface-derived characteristics such as areal and volumetric fluctuations as well as glacier velocity over debris-covered glaciers, improving the accuracy of geometric and temporal resolutions in hydrological analysis. In this study we present case studies from Nepal, Peru and Ecuador focusing on: 1) time series of debris-coverage and moraine-dammed lakes; and 2) the relationship of remotely sensed observable quantities from different sensors such as aerial photographs, ASTER, Landsat imagery and Airborne/Terrestrial Laser Scanner.

  6. Detecting Changes in Terrain Using Unmanned Aerial Vehicles

    NASA Technical Reports Server (NTRS)

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

    2005-01-01

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

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

    PubMed

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

    2013-03-13

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

  8. Environmental Change Detection Using Multi-Temporal SAR Imagery

    NASA Astrophysics Data System (ADS)

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

    2013-04-01

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

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

    SciTech Connect

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

    2009-01-01

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

  10. Signal subspace change detection in averaged multi-look SAR imagery

    NASA Astrophysics Data System (ADS)

    Ranney, Kenneth; Soumekh, Mehrdad

    2005-05-01

    Modern Synthetic Aperture Radar (SAR) signal processing algorithms could retrieve accurate and subtle information regarding a scene that is being interrogated by an airborne radar system. An important reconnaissance problem that is being studied via the use of SAR systems and their sophisticated signal processing methods involves detecting changes in an imaged scene. In these problems, the user interrogates a scene with a SAR system at two different time points (e.g. different days); the resultant two SAR databases that we refer to as reference and test data, are used to determine where targets have entered or left the imaged scene between the two data acquisitions. For instance, X band SAR systems have the potential to become a potent tool to determine whether mines have been recently placed in an area. This paper describes an algorithm for detecting changes in averaged multi-look SAR imagery. Averaged multi-look SAR images are preferable to full aperture SAR reconstructions when the imaging algorithm is approximation based (e.g. polar format processing), or motion data are not accurate over a long full aperture. We study the application of a SAR detection method, known as Signal Subspace Processing, that is based on the principles of 2D adaptive filtering. We identify the change detection problem as a binary hypothesis-testing problem, and identify an error signal and its normalized version to determine whether i) there is no change in the imaged scene; or ii) a target has been added to the imaged scene. A statistical analysis of the error signal is provided to show its properties and merits. Results are provided for data collected by an X band SAR platform and processed to form non-coherently look-averaged SAR images.

  11. A versatile ratiometric nanosensing approach for sensitive and accurate detection of Hg(2+) and biological thiols based on new fluorescent carbon quantum dots.

    PubMed

    Fu, Huili; Ji, Zhongyin; Chen, Xuejie; Cheng, Anwei; Liu, Shucheng; Gong, Peiwei; Li, Guoliang; Chen, Guang; Sun, Zhiwei; Zhao, Xianen; Cheng, Feng; You, Jinmao

    2017-03-01

    Herein, we first reported a facile synthesis method for fabrication of highly photoluminescent carbon quantum dots (CQDs) using sodium alginate as the carbon source and histidine as both the nitrogen source and functional monomer by one-pot hydrothermal synthesis. The as-prepared CQDs gave a high quantum yield of 32%. By employing the new CQDs and rhodamine B (RhB), we demonstrated a simple, facile, sensitive, and accurate ratiometric sensor for detection of Hg(2+) and biological thiols. The photoluminescence of CQDs in the ratiometric sensor can be selectively and intensively suppressed by Hg(2+) due to strong electrostatic interaction between the surface functional groups of the CQDs and Hg(2+). When glutathione (GSH) was introduced into the "Turn Off" CQDs-RhB-Hg(2+) sensing system, the fluorescence of the CQDs can be recovered rapidly due to the stronger affinity between thiol and Hg(2+), while the fluorescence of the RhB remained constant in this sensing process. Based on the above principle, the ratiometric strategy for detecting Hg(2+) and GSH can be achieved readily, and gives satisfactory limit of detections (LODs) of 30 and 20 nM for Hg(2+) and GSH, respectively. The dual-emission fluorescent CQDs-RhB sensor does not need the complicated molecular design and the synthesis of dual-emission fluorophores. Meanwhile, the feasibility of the proposed method for analysis of water samples, food samples, and biological samples (plasma from mice oxidative stress study) was investigated. The developed ratiometric nanosensor is proven to be facile, with less sample consumption, rapid, lost cost, highly sensitive, and very selective for Hg(2+) and biological thiol detection, which offers a new approach for environmental, food, and biological analysis. Graphical abstract Ratiometric nanosensing approach detection of Hg(2+) and biological thiols.

  12. Detecting forest canopy change due to insect activity using Landsat MSS

    NASA Technical Reports Server (NTRS)

    Nelson, R. F.

    1983-01-01

    Multitemporal Landsat multispectral scanner data were analyzed to test various computer-aided analysis techniques for detecting significant forest canopy alteration. Three data transformations - differencing, ratioing, and a vegetative index difference - were tested to determine which best delineated gypsy moth defoliation. Response surface analyses were conducted to determine optimal threshold levels for the individual transformed bands and band combinations. Results indicate that, of the three transformations investigated, a vegetative index difference (VID) transformation most accurately delineates forest canopy change. Band 5 (0.6 to 0.7 micron ratioed data did nearly as well. However, other single bands and band combinations did not improve upon the band 5 ratio and VID results.

  13. Robust Detection of Examinees with Aberrant Answer Changes

    ERIC Educational Resources Information Center

    Belov, Dmitry I.

    2015-01-01

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

  14. Automated Change Detection Using Synthetic Aperture Sonar Imagery

    DTIC Science & Technology

    2010-06-01

    using shadow outlining, scene matching using control-point matching, and visualization capabilities. This system was developed for sidescan sonar ...surveys using instrumentation such as the high-frequency Marine Sonic Technology sidescan sonar . In this paper, the authors describe modifications to...the sidescan -based system required to perform change detection using Synthetic Aperture Sonar (SAS) bottom imagery. Index Terms—Acoustic signal

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    USGS Publications Warehouse

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

    1997-01-01

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

  17. Helicopter Based Magnetic Detection Of Wells At The Teapot Dome (Naval Petroleum Reserve No. 3 Oilfield: Rapid And Accurate Geophysical Algorithms For Locating Wells

    NASA Astrophysics Data System (ADS)

    Harbert, W.; Hammack, R.; Veloski, G.; Hodge, G.

    2011-12-01

    In this study Airborne magnetic data was collected by Fugro Airborne Surveys from a helicopter platform (Figure 1) using the Midas II system over the 39 km2 NPR3 (Naval Petroleum Reserve No. 3) oilfield in east-central Wyoming. The Midas II system employs two Scintrex CS-2 cesium vapor magnetometers on opposite ends of a transversely mounted, 13.4-m long horizontal boom located amidships (Fig. 1). Each magnetic sensor had an in-flight sensitivity of 0.01 nT. Real time compensation of the magnetic data for magnetic noise induced by maneuvering of the aircraft was accomplished using two fluxgate magnetometers mounted just inboard of the cesium sensors. The total area surveyed was 40.5 km2 (NPR3) near Casper, Wyoming. The purpose of the survey was to accurately locate wells that had been drilled there during more than 90 years of continuous oilfield operation. The survey was conducted at low altitude and with closely spaced flight lines to improve the detection of wells with weak magnetic response and to increase the resolution of closely spaced wells. The survey was in preparation for a planned CO2 flood to enhance oil recovery, which requires a complete well inventory with accurate locations for all existing wells. The magnetic survey was intended to locate wells that are missing from the well database and to provide accurate locations for all wells. The well location method used combined an input dataset (for example, leveled total magnetic field reduced to the pole), combined with first and second horizontal spatial derivatives of this input dataset, which were then analyzed using focal statistics and finally combined using a fuzzy combination operation. Analytic signal and the Shi and Butt (2004) ZS attribute were also analyzed using this algorithm. A parameter could be adjusted to determine sensitivity. Depending on the input dataset 88% to 100% of the wells were located, with typical values being 95% to 99% for the NPR3 field site.

  18. Detection and quantitation of trace phenolphthalein (in pharmaceutical preparations and in forensic exhibits) by liquid chromatography-tandem mass spectrometry, a sensitive and accurate method.

    PubMed

    Sharma, Kakali; Sharma, Shiba P; Lahiri, Sujit C

    2013-01-01

    Phenolphthalein, an acid-base indicator and laxative, is important as a constituent of widely used weight-reducing multicomponent food formulations. Phenolphthalein is an useful reagent in forensic science for the identification of blood stains of suspected victims and for apprehending erring officials accepting bribes in graft or trap cases. The pink-colored alkaline hand washes originating from the phenolphthalein-smeared notes can easily be determined spectrophotometrically. But in many cases, colored solution turns colorless with time, which renders the genuineness of bribe cases doubtful to the judiciary. No method is known till now for the detection and identification of phenolphthalein in colorless forensic exhibits with positive proof. Liquid chromatography-tandem mass spectrometry had been found to be most sensitive, accurate method capable of detection and quantitation of trace phenolphthalein in commercial formulations and colorless forensic exhibits with positive proof. The detection limit of phenolphthalein was found to be 1.66 pg/L or ng/mL, and the calibration curve shows good linearity (r(2) = 0.9974).

  19. Land-use/land-cover change detection using change-vector analysis in posterior probability space

    NASA Astrophysics Data System (ADS)

    Chen, Xuehong; Chen, Jin; Shen, Miaogen; Yang, Wei

    2008-10-01

    Land use/land cover change is an important field in global environmental change research. Remote sensing is a valuable data source from which land use/land cover change information can be extracted efficiently. A number of techniques for accomplishing change detection using satellite imagery have been formulated, applied, and evaluated, which can be generally grouped into two types. (1) Those based on spectral classification of the input data such as post-classification comparison and direct two-date classification; and (2) those based on radiometric change between different acquisition dates. The shortage of type 1 is cumulative error in image classification of an individual date. However, radiometric change approaches has a strict requirement for reliable image radiometry. In light of the above mentioned drawbacks of those two types of change detection methods, this paper presents a new method named change vector analysis in posterior probability space (CVAPS). Change-vector analysis (CVA) is one of the most successful radiometric change-based approaches. CVAPS approach incorporates post-classification comparison method and CVA approach, which is expected to inherit the advantages of two traditional methods and avoid their defects at the same time. CVAPS includes the following four steps. (1) Images in different periods are classified by certain classifier which can provide posterior probability output. Then, the posterior probability can be treated as a vector, the dimension of which is equal to the number of classes. (2) A procedure similar with CVA is employed. Compared with traditional CVA, new method analyzes the change vector in posterior probability space instead of spectral feature space. (3) A semiautomatic method, named Double-Window Flexible Pace Search (DFPS), is employed to determine the threshold of change magnitude. (4) Change category is discriminated by cosines of the change vectors. CVAPS approach was applied and validated by a case study of

  20. Groundwater storage change detection using micro-gravimetric technology

    NASA Astrophysics Data System (ADS)

    El-Diasty, Mohammed

    2016-06-01

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

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

    PubMed Central

    Last, Michael; Shumway, Robert

    2007-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Ye, Su; Chen, Dongmei; Yu, Jie

    2016-04-01

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

  3. Aircraft MSS data registration and vegetation classification of wetland change detection

    USGS Publications Warehouse

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

    1988-01-01

    Portions of the Savannah River floodplain swamp were evaluated for vegetation change using high resolution (5a??6 m) aircraft multispectral scanner (MSS) data. Image distortion from aircraft movement prevented precise image-to-image registration in some areas. However, when small scenes were used (200-250 ha), a first-order linear transformation provided registration accuracies of less than or equal to one pixel. A larger area was registered using a piecewise linear method. Five major wetland classes were identified and evaluated for change. Phenological differences and the variable distribution of vegetation limited wetland type discrimination. Using unsupervised methods and ground-collected vegetation data, overall classification accuracies ranged from 84 per cent to 87 per cent for each scene. Results suggest that high-resolution aircraft MSS data can be precisely registered, if small areas are used, and that wetland vegetation change can be accurately detected and monitored.

  4. Discriminative genre-independent audio-visual scene change detection

    NASA Astrophysics Data System (ADS)

    Wilson, Kevin W.; Divakaran, Ajay

    2009-01-01

    We present a technique for genre-independent scene-change detection using audio and video features in a discriminative support vector machine (SVM) framework. This work builds on our previous work by adding a video feature based on the MPEG-7 "scalable color" descriptor. Adding this feature improves our detection rate over all genres by 5% to 15% for a fixed false positive rate of 10%. We also find that the genres that benefit the most are those with which the previous audio-only was least effective.

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

    NASA Astrophysics Data System (ADS)

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

    2015-11-01

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

  6. Panel-based Genetic Diagnostic Testing for Inherited Eye Diseases is Highly Accurate and Reproducible and More Sensitive for Variant Detection Than Exome Sequencing

    PubMed Central

    Bujakowska, Kinga M.; Sousa, Maria E.; Fonseca-Kelly, Zoë D.; Taub, Daniel G.; Janessian, Maria; Wang, Dan Yi; Au, Elizabeth D.; Sims, Katherine B.; Sweetser, David A.; Fulton, Anne B.; Liu, Qin; Wiggs, Janey L.; Gai, Xiaowu; Pierce, Eric A.

    2015-01-01

    Purpose Next-generation sequencing (NGS) based methods are being adopted broadly for genetic diagnostic testing, but the performance characteristics of these techniques have not been fully defined with regard to test accuracy and reproducibility. Methods We developed a targeted enrichment and NGS approach for genetic diagnostic testing of patients with inherited eye disorders, including inherited retinal degenerations, optic atrophy and glaucoma. In preparation for providing this Genetic Eye Disease (GEDi) test on a CLIA-certified basis, we performed experiments to measure the sensitivity, specificity, reproducibility as well as the clinical sensitivity of the test. Results The GEDi test is highly reproducible and accurate, with sensitivity and specificity for single nucleotide variant detection of 97.9% and 100%, respectively. The sensitivity for variant detection was notably better than the 88.3% achieved by whole exome sequencing (WES) using the same metrics, due to better coverage of targeted genes in the GEDi test compared to commercially available exome capture sets. Prospective testing of 192 patients with IRDs indicated that the clinical sensitivity of the GEDi test is high, with a diagnostic rate of 51%. Conclusion The data suggest that based on quantified performance metrics, selective targeted enrichment is preferable to WES for genetic diagnostic testing. PMID:25412400

  7. Accurate mass determination, quantification and determination of detection limits in liquid chromatography-high-resolution time-of-flight mass spectrometry: challenges and practical solutions.

    PubMed

    Vergeynst, Leendert; Van Langenhove, Herman; Joos, Pieter; Demeestere, Kristof

    2013-07-30

    Uniform guidelines for the data processing and validation of qualitative and quantitative multi-residue analysis using full-spectrum high-resolution mass spectrometry are scarce. Through systematic research, optimal mass accuracy and sensitivity are obtained after refining the post-processing of the HRMS data. For qualitative analysis, transforming the raw profile spectra to centroid spectra is recommended resulting in a 2.3 fold improved precision on the accurate mass determination of spectrum peaks. However, processing centroid data for quantitative purposes could lead to signal interruption when too narrow mass windows are applied for the construction of extracted ion chromatograms. Therefore, peak integration on the raw profile data is recommended. An optimal width of the mass window of 50 ppm, which is a trade-off between sensitivity and selectivity, was obtained for a TOF instrument providing a resolving power of 20,000 at full width at half maximum (FWHM). For the validation of HRMS analytical methods, widespread concepts such as the signal-to-noise ratios for the determination of decision limits and detection capabilities have shown to be not always applicable because in some cases almost no noise can be detected anymore. A statistical methodology providing a reliable alternative is extended and applied.

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

    PubMed Central

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

    2016-01-01

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

  9. A structural framework for anomalous change detection and characterization

    SciTech Connect

    Prasad, Lakshman; Theiler, James P

    2009-01-01

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

  10. Refractive index change detection based on porous silicon microarray

    NASA Astrophysics Data System (ADS)

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

    2016-05-01

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

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

    NASA Technical Reports Server (NTRS)

    Bell, T. L.

    1986-01-01

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

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

    NASA Technical Reports Server (NTRS)

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

    1983-01-01

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

  13. Changes of protein stiffness during folding detect protein folding intermediates.

    PubMed

    Małek, Katarzyna E; Szoszkiewicz, Robert

    2014-01-01

    Single-molecule force-quench atomic force microscopy (FQ-AFM) is used to detect folding intermediates of a simple protein by detecting changes of molecular stiffness of the protein during its folding process. Those stiffness changes are obtained from shape and peaks of an autocorrelation of fluctuations in end-to-end length of the folding molecule. The results are supported by predictions of the equipartition theorem and agree with existing Langevin dynamics simulations of a simplified model of a protein folding. In the light of the Langevin simulations the experimental data probe an ensemble of random-coiled collapsed states of the protein, which are present both in the force-quench and thermal-quench folding pathways.

  14. Sensitive, accurate and rapid detection of trace aliphatic amines in environmental samples with ultrasonic-assisted derivatization microextraction using a new fluorescent reagent for high performance liquid chromatography.

    PubMed

    Chen, Guang; Liu, Jianjun; Liu, Mengge; Li, Guoliang; Sun, Zhiwei; Zhang, Shijuan; Song, Cuihua; Wang, Hua; Suo, Yourui; You, Jinmao

    2014-07-25

    A new fluorescent reagent, 1-(1H-imidazol-1-yl)-2-(2-phenyl-1H-phenanthro[9,10-d]imidazol-1-yl)ethanone (IPPIE), is synthesized, and a simple pretreatment based on ultrasonic-assisted derivatization microextraction (UDME) with IPPIE is proposed for the selective derivatization of 12 aliphatic amines (C1: methylamine-C12: dodecylamine) in complex matrix samples (irrigation water, river water, waste water, cultivated soil, riverbank soil and riverbed soil). Under the optimal experimental conditions (solvent: ACN-HCl, catalyst: none, molar ratio: 4.3, time: 8 min and temperature: 80°C), micro amount of sample (40 μL; 5mg) can be pretreated in only 10 min, with no preconcentration, evaporation or other additional manual operations required. The interfering substances (aromatic amines, aliphatic alcohols and phenols) get the derivatization yields of <5%, causing insignificant matrix effects (<4%). IPPIE-analyte derivatives are separated by high performance liquid chromatography (HPLC) and quantified by fluorescence detection (FD). The very low instrumental detection limits (IDL: 0.66-4.02 ng/L) and method detection limits (MDL: 0.04-0.33 ng/g; 5.96-45.61 ng/L) are achieved. Analytes are further identified from adjacent peaks by on-line ion trap mass spectrometry (MS), thereby avoiding additional operations for impurities. With this UDME-HPLC-FD-MS method, the accuracy (-0.73-2.12%), precision (intra-day: 0.87-3.39%; inter-day: 0.16-4.12%), recovery (97.01-104.10%) and sensitivity were significantly improved. Successful applications in environmental samples demonstrate the superiority of this method in the sensitive, accurate and rapid determination of trace aliphatic amines in micro amount of complex samples.

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

    PubMed

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

    2014-08-01

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

  16. Rapid and accurate measurement of left ventricular function with a new second-harmonic fast-rotating transducer and semi-automated border detection.

    PubMed

    Krenning, Boudewijn J; Voormolen, Marco M; van Geuns, Robert-Jan; Vletter, W B; Lancée, Charles T; de Jong, Nico; Ten Cate, Folkert J; van der Steen, Anton F W; Roelandt, Jos R T C

    2006-07-01

    Measurement of left ventricular (LV) volume and function are the most common clinical referral questions to the echocardiography laboratory. A fast, practical, and accurate method would offer important advantages to obtain this important information. To validate a new practical method for rapid measurement of LV volume and function. We developed a continuous fast-rotating transducer, with second-harmonic capabilities, for three-dimensional echocardiography (3DE). Fifteen cardiac patients underwent both 3DE and magnetic resonance imaging (reference method) on the same day. 3DE image acquisition was performed during a 10-second breath-hold with a frame rate of 100 frames/sec and a rotational speed of 6 rotations/sec. The individual images were postprocessed with Matlab software using multibeat data fusion. Subsequently, with these images, 12 datasets per cardiac cycle were reconstructed, each comprising seven equidistant cross-sectional images for analysis in the new TomTec 4DLV analysis software, which uses a semi-automated border detection (ABD) algorithm. The ABD requires an average analysis time of 15 minutes per patient. A strong correlation was found between LV end-diastolic volume (r = 0.99; y = 0.95x - 1.14 ml; SEE = 6.5 ml), LV end-systolic volume (r = 0.96; y = 0.89x + 7.91 ml; SEE = 7.0 ml), and LV ejection fraction (r = 0.93; y = 0.69x + 13.36; SEE = 2.4%). Inter- and intraobserver agreement for all measurements was good. The fast-rotating transducer with new ABD software is a dedicated tool for rapid and accurate analysis of LV volume and function.

  17. Multiscale object-oriented change detection over urban areas

    NASA Astrophysics Data System (ADS)

    Wang, Jianmei; Li, Deren

    2006-10-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

  19. Topographic Change Detection Using Full-Waveform Imaging Lidar

    NASA Technical Reports Server (NTRS)

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

    2001-01-01

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

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

    SciTech Connect

    Wohlberg, Brendt E; Theiler, James P

    2009-01-01

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

  1. Object-based rapid change detection for disaster management

    NASA Astrophysics Data System (ADS)

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

    2011-11-01

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

  2. Vegetation change detection in the Savannah River swamp

    SciTech Connect

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

    1986-01-01

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

  3. A method for detecting changes in long time series

    SciTech Connect

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

    1995-09-01

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

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

    NASA Astrophysics Data System (ADS)

    Maeno, Yoshiharu

    2016-09-01

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

  5. Action change detection in video using a bilateral spatial-temporal constraint

    NASA Astrophysics Data System (ADS)

    Tian, Jing; Chen, Li

    2016-08-01

    Action change detection in video aims to detect action discontinuity in video. The silhouettes-based features are desirable for action change detection. This paper studies the problem of silhouette-quality assessment. For that, a non-reference approach without the need for ground truth is proposed in this paper to evaluate the quality of silhouettes, by exploiting both the boundary contrast of the silhouettes in the spatial domain and the consistency of the silhouettes in the temporal domain. This is in contrast to that either only spatial information or only temporal information of silhouettes is exploited in conventional approaches. Experiments are conducted using artificially generated degraded silhouettes to show that the proposed approach outperforms conventional approaches to achieve more accurate quality assessment. Furthermore, experiments are performed to show that the proposed approach is able to improve the accuracy performance of conventional action change approaches in two human action video data-sets. The average runtime of the proposed approach for Weizmann action video data-set is 0.08 second for one frame using Matlab programming language. It is computationally efficient and potential to real-time implementations.

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

    SciTech Connect

    Byler, E.

    1997-10-31

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

  7. Multi-driver attribution of detected hydrological change

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-09-01

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

  9. Foot-to-foot bioelectrical impedance accurately tracks direction of adiposity change in overweight and obese 7- to 13-year-old children.

    PubMed

    Kasvis, Popi; Cohen, Tamara R; Loiselle, Sarah-Ève; Kim, Nicolas; Hazell, Tom J; Vanstone, Catherine A; Rodd, Celia; Plourde, Hugues; Weiler, Hope A

    2015-03-01

    Body composition measurements are valuable when evaluating pediatric obesity interventions. We hypothesized that foot-to-foot bioelectrical impedance analysis (BIA) will accurately track the direction of adiposity change, but not magnitude, in part due to differences in fat patterning. The purposes of this study were to examine the accuracy of body composition measurements of overweight and obese children over time using dual-energy x-ray absorptiometry (DXA) and BIA and to determine if BIA accuracy was affected by fat patterning. Eighty-nine overweight or obese children (48 girls, 41 boys, age 7-13 years) participating in a randomized controlled trial providing a family-centered, lifestyle intervention, underwent DXA and BIA measurements every 3 months. Bland-Altman plots showed a poor level of agreement between devices for baseline percent body fat (%BF; mean, 0.398%; +2SD, 8.685%; -2SD, -7.889%). There was overall agreement between DXA and BIA in the direction of change over time for %BF (difference between visits 3 and 1: DXA -0.8 ± 0.5%, BIA -0.7 ± 0.5%; P = 1.000) and fat mass (FM; difference between visits 3 and 1: DXA 0.7 ± 0.5 kg, BIA 0.6 ± 0.5 kg; P = 1.000). Bioelectrical impedance analysis measurements of %BF and FM at baseline were significantly different in those with android and gynoid fat (%BF: 35.9% ± 1.4%, 32.2% ± 1.4%, P < .003; FM: 20.1 ± 0.8 kg, 18.4 ± 0.8, P < .013). Bioelectrical impedance analysis accurately reports the direction of change in FM and FFM in overweight and obese children; inaccuracy in the magnitude of BIA measurements may be a result of fat patterning differences.

  10. Effects of spatial configurations on visual change detection: an account of bias changes.

    PubMed

    Boduroglu, Aysecan; Shah, Priti

    2009-12-01

    In order to determine whether people encode spatial configuration information when encoding visual displays, in four experiments, we investigated whether changes in task-irrelevant spatial configuration information would influence color change detection accuracy. In a change detection task, when objects in the test display were presented in new random locations, rather than identical or different locations preserving the overall configuration, participants were more likely to report that the colors had changed. This consistent bias across four experiments suggested that people encode task-irrelevant spatial configuration along with object information. Experiment 4 also demonstrated that only a low-false-alarm group of participants effectively bound spatial configuration information to object information, suggesting that these types of binding processes are open to strategic influences.

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

    PubMed

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

    2016-01-01

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

  12. Development and validation of a high-performance liquid chromatography-fluorescence detection method for the accurate quantification of colistin in human plasma.

    PubMed

    Chepyala, Divyabharathi; Tsai, I-Lin; Sun, Hsin-Yun; Lin, Shu-Wen; Kuo, Ching-Hua

    2015-02-01

    Recently, colistin has become one of the most important drugs for treating infections caused by multidrug-resistant Gram-negative bacteria. Therapeutic drug monitoring is recommended to ensure the safety and efficacy of colistin and to improve clinical outcomes. This study developed an accurate and sensitive high-performance liquid chromatography-fluorescence detection (HPLC-FLD) method for the quantification of colistin in human plasma. The sample preparation included protein precipitation using trichloroacetic acid (TCA) and methanol, followed by in-solid phase extraction (In-SPE) derivatization with 9-fluorenylmethyl chloroformate (FMOC-Cl). A Poroshell 120 EC-C18 2.1×100mm (2.7μm) column was used in the HPLC method with a mobile phase composed of acetonitrile (ACN), tetrahydrofuran (THF), and deionized (DI) water (82%, 2%, 16% (v/v), respectively). Polymyxin B1 was used as the internal standard. The total analysis time was 22min under optimal separation conditions. The HPLC-FLD method was validated over a therapeutic range of 0.3-6.0μgmL(-1). The intra-day and inter-day precisions for colistin A and colistin B were below 9.9% and 4.5% relative standard deviations, respectively. The accuracy test results were between 100.2 and 118.4%. The extraction recoveries were between 81.6 and 94.1%. The method was linear over the test range, with a 0.9991 coefficient of determination. The limit of detection was 0.1μgmL(-1). The validated HPLC-FLD method was successfully applied to quantify the colistin concentrations in 2 patient samples for therapeutic drug monitoring.

  13. Performance of a Micro-Strip Gas Chamber for event wise, high rate thermal neutron detection with accurate 2D position determination

    NASA Astrophysics Data System (ADS)

    Mindur, B.; Alimov, S.; Fiutowski, T.; Schulz, C.; Wilpert, T.

    2014-12-01

    A two-dimensional (2D) position sensitive detector for neutron scattering applications based on low-pressure gas amplification and micro-strip technology was built and tested with an innovative readout electronics and data acquisition system. This detector contains a thin solid neutron converter and was developed for time- and thus wavelength-resolved neutron detection in single-event counting mode, which improves the image contrast in comparison with integrating detectors. The prototype detector of a Micro-Strip Gas Chamber (MSGC) was built with a solid natGd/CsI thermal neutron converter for spatial resolutions of about 100 μm and counting rates up to 107 neutrons/s. For attaining very high spatial resolutions and counting rates via micro-strip readout with centre-of-gravity evaluation of the signal amplitude distributions, a fast, channel-wise, self-triggering ASIC was developed. The front-end chips (MSGCROCs), which are very first signal processing components, are read out into powerful ADC-FPGA boards for on-line data processing and thereafter via Gigabit Ethernet link into the data receiving PC. The workstation PC is controlled by a modular, high performance dedicated software suite. Such a fast and accurate system is crucial for efficient radiography/tomography, diffraction or imaging applications based on high flux thermal neutron beam. In this paper a brief description of the detector concept with its operation principles, readout electronics requirements and design together with the signals processing stages performed in hardware and software are presented. In more detail the neutron test beam conditions and measurement results are reported. The focus of this paper is on the system integration, two dimensional spatial resolution, the time resolution of the readout system and the imaging capabilities of the overall setup. The detection efficiency of the detector prototype is estimated as well.

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

    NASA Astrophysics Data System (ADS)

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

    2015-09-01

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

  15. Fault Diagnostics Using Statistical Change Detection in the Bispectral Domain

    NASA Astrophysics Data System (ADS)

    Eugene Parker, B.; Ware, H. A.; Wipf, D. P.; Tompkins, W. R.; Clark, B. R.; Larson, E. C.; Vincent Poor, H.

    2000-07-01

    It is widely accepted that structural defects in rotating machinery components (e.g. bearings and gears) can be detected through monitoring of vibration and/or sound emissions. Traditional diagnostic vibration analysis attempts to match spectral lines with a priori -known defect frequencies that are characteristic of the affected machinery components. Emphasis herein is on use of bispectral-based statistical change detection algorithms for machinery health monitoring. The bispectrum, a third-order statistic, helps identify pairs of phase-related spectral components, which is useful for fault detection and isolation. In particular, the bispectrum helps sort through the clutter of usual (second-order) vibration spectra to extract useful information associated with the health of particular components. Seeded and non-seeded helicopter gearbox fault results (CH-46E and CH-47D, respectively) show that bispectral algorithms can detect faults at the level of an individual component (i.e. bearings or gears). Fault isolation is implicit with detection based on characteristic a priori -known defect frequencies. Important attributes of the bispectral SCD approach include: (1) it does not require a priori training data as is needed for traditional pattern-classifier-based approaches (and thereby avoids the significant time and cost investments necessary to obtain such data); (2) being based on higher-order moment-based energy detection, it makes no assumptions about the statistical model of the bispectral sequences that are generated; (3) it is operating-regime independent (i.e. works across different operating conditions, flight regimes, torque levels, etc., without knowledge of same); (4) it can be used to isolate faults to the level of specific machinery components (e.g. bearings and gears); and (5) it can be implemented using relatively inexpensive computer hardware, since only low-frequency vibrations need to be processed. The bispectral SCD algorithm thus represents a

  16. Extensive Peptide Fractionation and y1 Ion-Based Interference Detection Method for Enabling Accurate Quantification by Isobaric Labeling and Mass Spectrometry.

    PubMed

    Niu, Mingming; Cho, Ji-Hoon; Kodali, Kiran; Pagala, Vishwajeeth; High, Anthony A; Wang, Hong; Wu, Zhiping; Li, Yuxin; Bi, Wenjian; Zhang, Hui; Wang, Xusheng; Zou, Wei; Peng, Junmin

    2017-02-22

    Isobaric labeling quantification by mass spectrometry (MS) has emerged as a powerful technology for multiplexed large-scale protein profiling, but measurement accuracy in complex mixtures is confounded by the interference from coisolated ions, resulting in ratio compression. Here we report that the ratio compression can be essentially resolved by the combination of pre-MS peptide fractionation, MS2-based interference detection, and post-MS computational interference correction. To recapitulate the complexity of biological samples, we pooled tandem mass tag (TMT)-labeled Escherichia coli peptides at 1:3:10 ratios and added in ∼20-fold more rat peptides as background, followed by the analysis of two-dimensional liquid chromatography (LC)-MS/MS. Systematic investigation shows that quantitative interference was impacted by LC fractionation depth, MS isolation window, and peptide loading amount. Exhaustive fractionation (320 × 4 h) can nearly eliminate the interference and achieve results comparable to the MS3-based method. Importantly, the interference in MS2 scans can be estimated by the intensity of contaminated y1 product ions, and we thus developed an algorithm to correct reporter ion ratios of tryptic peptides. Our data indicate that intermediate fractionation (40 × 2 h) and y1 ion-based correction allow accurate and deep TMT profiling of more than 10 000 proteins, which represents a straightforward and affordable strategy in isobaric labeling proteomics.

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

    USGS Publications Warehouse

    Milazzo, Valerie A.

    1984-01-01

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

  18. Vibration-based monitoring to detect mass changes in satellites

    NASA Astrophysics Data System (ADS)

    Maji, Arup; Vernon, Breck

    2012-04-01

    Vibration-based structural health monitoring could be a useful form of determining the health and safety of space structures. A particular concern is the possibility of a foreign object that attaches itself to a satellite in orbit for adverse reasons. A frequency response analysis was used to determine the changes in mass and moment of inertia of the space structure based on a change in the natural frequencies of the structure or components of the structure. Feasibility studies were first conducted on a 7 in x 19 in aluminum plate with various boundary conditions. Effect of environmental conditions on the frequency response was determined. The baseline frequency response for the plate was then used as the basis for detection of the addition, and possibly the location, of added masses on the plate. The test results were compared to both analytical solutions and finite element models created in SAP2000. The testing was subsequently expanded to aluminum alloy satellite panels and a mock satellite with dummy payloads. Statistical analysis was conducted on variations of frequency due to added mass and thermal changes to determine the threshold of added mass that can be detected.

  19. Automatic detection of unattended changes in room acoustics.

    PubMed

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

    2015-01-01

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

  20. Change and Anomaly Detection in Real-Time GPS Data

    NASA Astrophysics Data System (ADS)

    Granat, R.; Pierce, M.; Gao, X.; Bock, Y.

    2008-12-01

    The California Real-Time Network (CRTN) is currently generating real-time GPS position data at a rate of 1-2Hz at over 80 locations. The CRTN data presents the possibility of studying dynamical solid earth processes in a way that complements existing seismic networks. To realize this possibility we have developed a prototype system for detecting changes and anomalies in the real-time data. Through this system, we can can correlate changes in multiple stations in order to detect signals with geographical extent. Our approach involves developing a statistical model for each GPS station in the network, and then using those models to segment the time series into a number of discrete states described by the model. We use a hidden Markov model (HMM) to describe the behavior of each station; fitting the model to the data requires neither labeled training examples nor a priori information about the system. As such, HMMs are well suited to this problem domain, in which the data remains largely uncharacterized. There are two main components to our approach. The first is the model fitting algorithm, regularized deterministic annealing expectation- maximization (RDAEM), which provides robust, high-quality results. The second is a web service infrastructure that connects the data to the statistical modeling analysis and allows us to easily present the results of that analysis through a web portal interface. This web service approach facilitates the automatic updating of station models to keep pace with dynamical changes in the data. Our web portal interface is critical to the process of interpreting the data. A Google Maps interface allows users to visually interpret state changes not only on individual stations but across the entire network. Users can drill down from the map interface to inspect detailed results for individual stations, download the time series data, and inspect fitted models. Alternatively, users can use the web portal look at the evolution of changes on the

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

    PubMed

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

    2014-07-01

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

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

    NASA Technical Reports Server (NTRS)

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

    2010-01-01

    Increases in the circulation of the stratosphere appear to be a robust result of climate change in chemistry-climate models over decadal time scales. To date observations have yet to show a significant change in this circulation. It is important for the design of future observational missions to identify suitable atmospheric constituents and to determine the accuracy and length of record needed to identify a significant trend that can be attributed to circulation change. First, we determine what atmospheric variables can be used as proxies for stratospheric circulation changes. A few examples are changes in tropical lower stratospheric ozone, phase lag of the water vapor tape recorder, CO2, and SF6. Then, using both the Goddard Earth Observing System Chemistry-Climate Model (GEOS CCM) and observations from satellites and balloon soundings, we calculate the number of years needed to detect a significant trend, taking into account observational uncertainty. Model simulations will be evaluated to see how well they represent observed variability. In addition, the impacts of autocorrelation among the output or data and gaps in the observational record will be discussed.

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

    NASA Astrophysics Data System (ADS)

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

    2016-07-01

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

  4. A novel technique for unsupervised change detection in multitemporal SAR Images

    NASA Astrophysics Data System (ADS)

    Bazi, Y.; Bruzzone, L.; Melgani, F.

    The detection of changes that occur on the Earth surface by using multitemporal remote sensing images is one of the most important applications of the remote sensing technology. This depends on the fact that the knowledge of the dynamics of either natural resources or man-made structures is a valuable source of information in decision-making. In this context, optical remote sensing sensors have been used for addressing change-detection applications for many years. Unlike the optical sensors, images acquired by synthetic aperture radar (SAR) have been less exploited in the context of change detection. This is explained by the fact that SAR images suffer from the presence of the speckle noise that renders their analysis complex. However, the use of SAR sensors in change detection is attractive from the operational view-point, since they present the advantage to be independent on atmospheric and sunlight conditions. In the context of multitemporal SAR image analysis, the problem of change detection has been addressed with focus on different aspects, which include the choice of the comparison operator, the image despeckling and the optimal threshold selection. Despite some interesting works have been proposed in the literature, the main problem still open with SAR data is the lack of accurate and reliable methods capable to perform unsupervised change detection in a completely automatic way. In this paper, we propose to face the aforementioned issue by developing an automatic and unsupervised change-detection method specifically oriented to the analysis of multitemporal single-channel single-polarization SAR images. Such a method is based on three main steps: 1) controlled pre-processing based on adaptive filtering (despeckling); 2) comparison of a pair of multitemporal images according to a log-ratio operator; 3) automatic analysis of the log-ratio image. The first step aims at reducing the speckle noise in a controlled way in order to maximize the discrimination

  5. Rapid and Accurate Detection of Mycobacterium tuberculosis in Sputum Samples by Cepheid Xpert MTB/RIF Assay—A Clinical Validation Study

    PubMed Central

    Rachow, Andrea; Zumla, Alimuddin; Heinrich, Norbert; Rojas-Ponce, Gabriel; Mtafya, Bariki; Reither, Klaus; Ntinginya, Elias N.; O'Grady, Justin; Huggett, Jim; Dheda, Keertan; Boehme, Catharina; Perkins, Mark; Saathoff, Elmar; Hoelscher, Michael

    2011-01-01

    Background A crucial impediment to global tuberculosis control is the lack of an accurate, rapid diagnostic test for detection of patients with active TB. A new, rapid diagnostic method, (Cepheid) Xpert MTB/RIF Assay, is an automated sample preparation and real-time PCR instrument, which was shown to have good potential as an alternative to current reference standard sputum microscopy and culture. Methods We performed a clinical validation study on diagnostic accuracy of the Xpert MTB/RIF Assay in a TB and HIV endemic setting. Sputum samples from 292 consecutively enrolled adults from Mbeya, Tanzania, with suspected TB were subject to analysis by the Xpert MTB/RIF Assay. The diagnostic performance of Xpert MTB/RIF Assay was compared to standard sputum smear microscopy and culture. Confirmed Mycobacterium tuberculosis in a positive culture was used as a reference standard for TB diagnosis. Results Xpert MTB/RIF Assay achieved 88.4% (95%CI = 78.4% to 94.9%) sensitivity among patients with a positive culture and 99% (95%CI = 94.7% to 100.0%) specificity in patients who had no TB. HIV status did not affect test performance in 172 HIV-infected patients (58.9% of all participants). Seven additional cases (9.1% of 77) were detected by Xpert MTB/RIF Assay among the group of patients with clinical TB who were culture negative. Within 45 sputum samples which grew non-tuberculous mycobacteria the assay's specificity was 97.8% (95%CI = 88.2% to 99.9%). Conclusions The Xpert MTB/RIF Assay is a highly sensitive, specific and rapid method for diagnosing TB which has potential to complement the current reference standard of TB diagnostics and increase its overall sensitivity. Its usefulness in detecting sputum smear and culture negative patients needs further study. Further evaluation in high burden TB and HIV areas under programmatic health care settings to ascertain applicability, cost-effectiveness, robustness and local acceptance are required. PMID:21738575

  6. Competitive SWIFT cluster templates enhance detection of aging changes

    PubMed Central

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

    2015-01-01

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

  7. Competitive SWIFT cluster templates enhance detection of aging changes.

    PubMed

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

    2016-01-01

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

  8. GPU based detection of topological changes in Voronoi diagrams

    NASA Astrophysics Data System (ADS)

    Bernaschi, M.; Lulli, M.; Sbragaglia, M.

    2017-04-01

    The Voronoi diagrams are an important tool having theoretical and practical applications in a large number of fields. We present a new procedure, implemented as a set of CUDA kernels, which detects, in a general and efficient way, topological changes in case of dynamic Voronoi diagrams whose generating points move in time. The solution that we provide has been originally developed to identify plastic events during simulations of soft-glassy materials based on a lattice Boltzmann model with frustrated-short range attractive and mid/long-range repulsive-interactions. Along with the description of our approach, we present also some preliminary physics results.

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

    DOEpatents

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

    2010-01-05

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

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

    NASA Astrophysics Data System (ADS)

    Sofina, N.; Ehlers, M.

    2012-08-01

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

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

    SciTech Connect

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

    2014-09-01

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

  12. Evaluating the forced oscillation technique in the detection of early smoking-induced respiratory changes

    PubMed Central

    Faria, Alvaro CD; Lopes, Agnaldo J; Jansen, José M; Melo, Pedro L

    2009-01-01

    Background Early detection of the effects of smoking is of the utmost importance in the prevention of chronic obstructive pulmonary disease (COPD). The forced oscillation technique (FOT) is easy to perform since it requires only tidal breathing and offers a detailed approach to investigate the mechanical properties of the respiratory system. The FOT was recently suggested as an attractive alternative for diagnosing initial obstruction in COPD, which may be helpful in detecting COPD in its initial phases. Thus, the purpose of this study was twofold: (1) to evaluate the ability of FOT to detect early smoking-induced respiratory alterations; and (2) to compare the sensitivity of FOT with spirometry in a sample of low tobacco-dose subjects. Methods Results from a group of 28 smokers with a tobacco consumption of 11.2 ± 7.3 pack-years were compared with a control group formed by 28 healthy subjects using receiver operating characteristic (ROC) curves and a questionnaire as a gold standard. The early adverse effects of smoking were adequately detected by the absolute value of the respiratory impedance (Z4Hz), the intercept resistance (R0), and the respiratory system dynamic compliance (Crs, dyn). Z4Hz was the most accurate parameter (Se = 75%, Sp = 75%), followed by R0 and Crs, dyn. The performances of the FOT parameters in the detection of the early effects of smoking were higher than that of spirometry (p < 0.05). Conclusion This study shows that FOT can be used to detect early smoking-induced respiratory changes while these pathologic changes are still potentially reversible. These findings support the use of FOT as a versatile clinical diagnostic tool in aiding COPD prevention and treatment. PMID:19781078

  13. Electrical detection of C-reactive protein using a single free-standing, thermally controlled piezoresistive microcantilever for highly reproducible and accurate measurements.

    PubMed

    Yen, Yi-Kuang; Lai, Yu-Cheng; Hong, Wei-Ting; Pheanpanitporn, Yotsapoom; Chen, Chuin-Shan; Huang, Long-Sun

    2013-07-29

    This study demonstrates a novel method for electrical detection of C-reactive protein (CRP) as a means of identifying an infection in the body, or as a cardiovascular disease risk assay. The method uses a single free-standing, thermally controlled piezoresistive microcantilever biosensor. In a commonly used sensing arrangement of conventional dual cantilevers in the Wheatstone bridge circuit, reference and gold-coated sensing cantilevers that inherently have heterogeneous surface materials and different multilayer structures may yield independent responses to the liquid environmental changes of chemical substances, flow field and temperature, leading to unwanted signal disturbance for biosensing targets. In this study, the single free-standing microcantilever for biosensing applications is employed to resolve the dual-beam problem of individual responses in chemical solutions and, in a thermally controlled system, to maintain its sensor performance due to the sensitive temperature effect. With this type of single temperature-controlled microcantilever sensor, the electrical detection of various CRP concentrations from 1 µg/mL to 200 µg/mL was performed, which covers the clinically relevant range. Induced surface stresses were measured at between 0.25 N/m and 3.4 N/m with high reproducibility. Moreover, the binding affinity (KD) of CRP and anti-CRP interaction was found to be 18.83 ± 2.99 µg/mL, which agreed with results in previous reported studies. This biosensing technique thus proves valuable in detecting inflammation, and in cardiovascular disease risk assays.

  14. Detection of concealed ground targets in CARABAS SAR images using change detection

    NASA Astrophysics Data System (ADS)

    Ulander, Lars M.; Froelind, Per-Olov; Gustavsson, Anders; Hellsten, Hans; Larsson, Bjoern

    1999-08-01

    The paper describes a new method to detect man-made objects hidden under foliage or camouflage. The method is based on change detection and thus multiple revisits of the same area. It uses SAR image data provided by the low-frequency and ultra-wideband CARABAS SAR system which operate in the 20 - 90 MHz frequency range. Experimental results show a drastic reduction in false-alarm rate compared to methods based on single-pass SAR images. Small- to medium-sized trucks are consistently detected with a false-alarm rate of the order of 0.1 - 1 per km2. This level of false-alarm rate is quite sufficient for most military or civilian applications of interest.

  15. Onboard Data Processor for Change-Detection Radar Imaging

    NASA Technical Reports Server (NTRS)

    Lou, Yunling; Muellerschoen, Ronald J.; Chien, Steve A.; Saatchi, Sasan S.; Clark, Duane

    2008-01-01

    A computer system denoted a change-detection onboard processor (CDOP) is being developed as a means of processing the digitized output of a synthetic-aperture radar (SAR) apparatus aboard an aircraft or spacecraft to generate images showing changes that have occurred in the terrain below between repeat passes of the aircraft or spacecraft over the terrain. When fully developed, the CDOP is intended to be capable of generating SAR images and/or SAR differential interferograms in nearly real time. The CDOP is expected to be especially useful for understanding some large-scale natural phenomena and/or mitigating natural hazards: For example, it could be used for near-real-time observation of surface changes caused by floods, landslides, forest fires, volcanic eruptions, earthquakes, glaciers, and sea ice movements. It could also be used to observe such longer-term surface changes as those associated with growth of vegetation (relevant to estimation of wildfire fuel loads). The CDOP is, essentially, an interferometric SAR processor designed to operate aboard a radar platform.

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  17. Correlation based efficient face recognition and color change detection

    NASA Astrophysics Data System (ADS)

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

    2013-01-01

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

  18. Illumination robust change detection with CMOS imaging sensors

    NASA Astrophysics Data System (ADS)

    Rengarajan, Vijay; Gupta, Sheetal B.; Rajagopalan, A. N.; Seetharaman, Guna

    2015-05-01

    Change detection between two images in the presence of degradations is an important problem in the computer vision community, more so for the aerial scenario which is particularly challenging. Cameras mounted on moving platforms such as aircrafts or drones are subject to general six-dimensional motion as the motion is not restricted to a single plane. With CMOS cameras increasingly in vogue due to their low power consumption, the inevitability of rolling-shutter (RS) effect adds to the challenge. This is caused by sequential exposure of rows in CMOS cameras unlike conventional global shutter cameras where all pixels are exposed simultaneously. The RS effect is particularly pronounced in aerial imaging since each row of the imaging sensor is likely to experience a different motion. For fast-moving platforms, the problem is further compounded since the rows are also affected by motion blur. Moreover, since the two images are shot at different times, illumination differences are common. In this paper, we propose a unified computational framework that elegantly exploits the scarcity constraint to deal with the problem of change detection in images degraded by RS effect, motion blur as well as non-global illumination differences. We formulate an optimization problem where each row of the distorted image is approximated as a weighted sum of the corresponding rows in warped versions of the reference image due to camera motion within the exposure period to account for geometric as well as photometric differences. The method has been validated on both synthetic and real data.

  19. Detecting and isolating abrupt changes in linear switching systems

    NASA Astrophysics Data System (ADS)

    Nazari, Sohail; Zhao, Qing; Huang, Biao

    2015-04-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  1. Volumetric Forest Change Detection Through Vhr Satellite Imagery

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

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

    PubMed

    Aoyama, Atsushi; Haruyama, Tomohiro; Kuriki, Shinya

    2013-09-01

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

  3. Continuous change detection and classification of land cover using all available Landsat data

    NASA Astrophysics Data System (ADS)

    Zhu, Zhe

    Land cover mapping and monitoring has been widely recognized as important for understanding global change and in particular, human contributions. This research emphasizes the use of the time domain for mapping land cover and changes in land cover using satellite images. Unlike most prior methods that compare pairs or sets of images for identifying change, this research compares observations with model predictions. Moreover, instead of classifying satellite images directly, it uses coefficients from time series models as inputs for land cover mapping. The methods developed are capable of detecting many kinds of land cover change as they occur and providing land cover maps for any given time at high temporal frequency. One key processing step of the satellite images is the elimination of "noisy" observations due to clouds, cloud shadows, and snow. I developed a new algorithm called Fmask that processes each Landsat scene individually using an object-based method. For a globally distributed set of reference data, the overall cloud detection accuracy is 96%. A second step further improves cloud detection by using temporal information. The first application of the new methods based on time series analysis found change in forests in an area in Georgia and South Carolina. After the difference between observed and predicted reflectance exceeds a threshold three consecutive times a site is identified as forest disturbance. Accuracy assessment reveals that both the producers and users accuracies are higher than 95% in the spatial domain and approximately 94% in the temporal domain. The second application of this new approach extends the algorithm to include identification of a wide variety of land cover changes as well as land cover mapping. In this approach, the entire archive of Landsat imagery is analyzed to produce a comprehensive land cover history of the Boston region. The results are accurate for detecting change, with producers accuracy of 98% and users accuracies of

  4. Detection of Deforestation and Land Conversion in Rondonia, Brazil Using Change Detection Techniques

    NASA Technical Reports Server (NTRS)

    Guild, Liane S.; Cohen, Warren B,; Kauffman, J. Boone; Peterson, David L. (Technical Monitor)

    2001-01-01

    Fires associated with tropical deforestation, land conversion, and land use greatly contribute to emissions as well as the depletion of carbon and nutrient pools. The objective of this research was to compare change detection techniques for identifying deforestation and cattle pasture formation during a period of early colonization and agricultural expansion in the vicinity of Jamari, Rond6nia. Multi-date Landsat Thematic Mapper (TM) data between 1984 and 1992 was examined in a 94 370-ha area of active deforestation to map land cover change. The Tasseled Cap (TC) transformation was used to enhance the contrast between forest, cleared areas, and regrowth. TC images were stacked into a composite multi-date TC and used in a principal components (PC) transformation to identify change components. In addition, consecutive TC image pairs were differenced and stacked into a composite multi-date differenced image. A maximum likelihood classification of each image composite was compared for identification of land cover change. The multi-date TC composite classification had the best accuracy of 78.1% (kappa). By 1984, only 5% of the study area had been cleared, but by 1992, 11% of the area had been deforested, primarily for pasture and 7% lost due to hydroelectric dam flooding. Finally, discrimination of pasture versus cultivation was improved due to the ability to detect land under sustained clearing opened to land exhibiting regrowth with infrequent clearing.

  5. Optimal use of land surface temperature data to detect changes in tropical forest cover

    NASA Astrophysics Data System (ADS)

    van Leeuwen, Thijs T.; Frank, Andrew J.; Jin, Yufang; Smyth, Padhraic; Goulden, Michael L.; van der Werf, Guido R.; Randerson, James T.

    2011-06-01

    Rapid and accurate assessment of global forest cover change is needed to focus conservation efforts and to better understand how deforestation is contributing to the buildup of atmospheric CO2. Here we examined different ways to use land surface temperature (LST) to detect changes in tropical forest cover. In our analysis we used monthly 0.05° × 0.05° Terra Moderate Resolution Imaging Spectroradiometer (MODIS) observations of LST and Program for the Estimation of Deforestation in the Brazilian Amazon (PRODES) estimates of forest cover change. We also compared MODIS LST observations with an independent estimate of forest cover loss derived from MODIS and Landsat observations. Our study domain of approximately 10° × 10° included the Brazilian state of Mato Grosso. For optimal use of LST data to detect changes in tropical forest cover in our study area, we found that using data sampled during the end of the dry season (˜1-2 months after minimum monthly precipitation) had the greatest predictive skill. During this part of the year, precipitation was low, surface humidity was at a minimum, and the difference between day and night LST was the largest. We used this information to develop a simple temporal sampling algorithm appropriate for use in pantropical deforestation classifiers. Combined with the normalized difference vegetation index, a logistic regression model using day-night LST did moderately well at predicting forest cover change. Annual changes in day-night LST decreased during 2006-2009 relative to 2001-2005 in many regions within the Amazon, providing independent confirmation of lower deforestation levels during the latter part of this decade as reported by PRODES.

  6. Optimal Regulatory Circuit Topologies for Fold-Change Detection.

    PubMed

    Adler, Miri; Szekely, Pablo; Mayo, Avi; Alon, Uri

    2017-02-22

    Evolution repeatedly converges on only a few regulatory circuit designs that achieve a given function. This simplicity helps us understand biological networks. However, why so few circuits are rediscovered by evolution is unclear. We address this question for the case of fold-change detection (FCD): a response to relative changes of input rather than absolute changes. Two types of FCD circuits recur in biological systems-the incoherent feedforward and non-linear integral-feedback loops. We performed an analytical screen of all three-node circuits in a class comprising ∼500,000 topologies. We find that FCD is rare, but still there are hundreds of FCD topologies. The two experimentally observed circuits are among the very few minimal circuits that optimally trade off speed, noise resistance, and response amplitude. This suggests a way to understand why evolution converges on only few topologies for a given function and provides FCD designs for synthetic construction and future discovery.

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

    SciTech Connect

    Simonson, Katherine Mary; Ma, Tian J.

    2009-08-01

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

  8. Effect of projective viewpoint in detecting temporal density changes

    NASA Astrophysics Data System (ADS)

    Raundahl, Jakob; Nielsen, Mads; Olsen, Ole F.; Bagger, Yu Z.

    2004-05-01

    An important question in mammographic image analysis is the importance of the projected view of the breast. Can temporal changes in density be detected equally well using either one of the commonly available views Medio-Lateral (ML) and Cranio-Caudal (CC) or a combination of the two? Two sets of mammograms of 50 patients in a double-blind, placebo controlled hormone replacement therapy (HRT) experiment were used. One set of ML and CC view from 1999 and one from 2001. HRT increases density which means that the degree of separation of the populations (one group receiving HRT and the other placebo) can be used as a measure of how much density change information is carried in a particular view or combination of views. Earlier results have shown a high correlation between CC and ML views leading to the conclusion that only one of them is needed for density assessment purposes. A similar high correlation coefficient was observed in this study (0.85), while the correlation between changes was a bit lower (0.71). Using both views to separate the patients receiving hormones from the ones receiving placebo increased the area under corresponding ROC curves from 0.76 +/- 0.04 to 0.79 +/- 0.04.

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

    USGS Publications Warehouse

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

    2009-01-01

    This article applies formal detection and attribution techniques to investigate the nature of observed shifts in the timing of streamflow in the western United States. Previous studies have shown that the snow hydrology of the western United States has changed in the second half of the twentieth century. Such changes manifest themselves in the form of more rain and less snow, in reductions in the snow water contents, and in earlier snowmelt and associated advances in streamflow "center" timing (the day in the "water-year" on average when half the water-year flow at a point has passed). However, with one exception over a more limited domain, no other study has attempted to formally attribute these changes to anthropogenic increases of greenhouse gases in the atmosphere. Using the observations together with a set of global climate model simulations and a hydrologic model (applied to three major hydrological regions of the western United States_the California region, the upper Colorado River basin, and the Columbia River basin), it is found that the observed trends toward earlier "center" timing of snowmelt-driven streamflows in the western United States since 1950 are detectably different from natural variability (significant at the p < 0.05 level). Furthermore, the nonnatural parts of these changes can be attributed confidently to climate changes induced by anthropogenic greenhouse gases, aerosols, ozone, and land use. The signal from the Columbia dominates the analysis, and it is the only basin that showed a detectable signal when the analysis was performed on individual basins. It should be noted that although climate change is an important signal, other climatic processes have also contributed to the hydrologic variability of large basins in the western United States. ?? 2009 American Meteorological Society.

  10. Orthorectified High Resolution Multispectral Imagery for Application to Change Detection and Analysis

    NASA Technical Reports Server (NTRS)

    Benkelman, Cody A.

    1997-01-01

    The project team has outlined several technical objectives which will allow the companies to improve on their current capabilities. These include modifications to the imaging system, enabling it to operate more cost effectively and with greater ease of use, automation of the post-processing software to mosaic and orthorectify the image scenes collected, and the addition of radiometric calibration to greatly aid in the ability to perform accurate change detection. Business objectives include fine tuning of the market plan plus specification of future product requirements, expansion of sales activities (including identification of necessary additional resources required to meet stated revenue objectives), development of a product distribution plan, and implementation of a world wide sales effort.

  11. Detection of short-term changes in vegetation cover by use of LANDSAT imagery. [Arizona

    NASA Technical Reports Server (NTRS)

    Turner, R. M. (Principal Investigator); Wiseman, F. M.

    1975-01-01

    The author has identified the following significant results. By using a constant band 6 to band 5 radiance ratio of 1.25, the changing pattern of areas of relatively dense vegetation cover was detected for the semiarid region in the vicinity of Tucson, Arizona. Electronically produced binary thematic masks were used to map areas with dense vegetation. The foliar cover threshold represented by the ratio was not accurately determined but field measurements show that the threshold lies in the range of 10 to 25 percent foliage cover. Montana evergreen forests with constant dense cover were correctly shown to exceed the threshold on all dates. The summer active grassland exceeded the threshold in the summer unless rainfall was insufficient. Desert areas exceeded the threshold during the spring of 1973 following heavy rains; the same areas during the rainless spring of 1974 did not exceed threshold. Irrigated fields, parks, golf courses, and riparian communities were among the habitats most frequently surpassing the threshold.

  12. Image animation for theme enhancement and change detection. [LANDSAT 1

    NASA Technical Reports Server (NTRS)

    Evans, W. E.

    1976-01-01

    Animated displays are useful in enhancing subtle temporally related changes in scenes viewed by satellites capable of providing repetitive coverage. The detectability of fixed features is also improved through the help of the powerful visual integration process. To expedite the process of assembling and displaying well-registered, time-lapse sequences and to provide means for making quantitative measurements of radiances, displacements, and areas, an electronic satellite image analysis console was constructed. During the LANDSAT-1 program, this equipment was applied to the needs of a number of earth resource investigators with interests principally related to dynamic hydrology. The measurement of the areal extent of snow cover within defined drainage basins is discussed as a representative applications example.

  13. Change Detection of Mobile LIDAR Data Using Cloud Computing

    NASA Astrophysics Data System (ADS)

    Liu, Kun; Boehm, Jan; Alis, Christian

    2016-06-01

    Change detection has long been a challenging problem although a lot of research has been conducted in different fields such as remote sensing and photogrammetry, computer vision, and robotics. In this paper, we blend voxel grid and Apache Spark together to propose an efficient method to address the problem in the context of big data. Voxel grid is a regular geometry representation consisting of the voxels with the same size, which fairly suites parallel computation. Apache Spark is a popular distributed parallel computing platform which allows fault tolerance and memory cache. These features can significantly enhance the performance of Apache Spark and results in an efficient and robust implementation. In our experiments, both synthetic and real point cloud data are employed to demonstrate the quality of our method.

  14. Tapping into the Hexagon spy imagery database: A new automated pipeline for geomorphic change detection

    NASA Astrophysics Data System (ADS)

    Maurer, Joshua; Rupper, Summer

    2015-10-01

    Declassified historical imagery from the Hexagon spy satellite database has near-global coverage, yet remains a largely untapped resource for geomorphic change studies. Unavailable satellite ephemeris data make DEM (digital elevation model) extraction difficult in terms of time and accuracy. A new fully-automated pipeline for DEM extraction and image orthorectification is presented which yields accurate results and greatly increases efficiency over traditional photogrammetric methods, making the Hexagon image database much more appealing and accessible. A 1980 Hexagon DEM is extracted and geomorphic change computed for the Thistle Creek Landslide region in the Wasatch Range of North America to demonstrate an application of the new method. Surface elevation changes resulting from the landslide show an average elevation decrease of 14.4 ± 4.3 m in the source area, an increase of 17.6 ± 4.7 m in the deposition area, and a decrease of 30.2 ± 5.1 m resulting from a new roadcut. Two additional applications of the method include volume estimates of material excavated during the Mount St. Helens volcanic eruption and the volume of net ice loss over a 34-year period for glaciers in the Bhutanese Himalayas. These results show the value of Hexagon imagery in detecting and quantifying historical geomorphic change, especially in regions where other data sources are limited.

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

    EPA Science Inventory

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

  16. Updating National Topographic Data Base Using Change Detection Methods

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

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

    PubMed

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

    2015-05-01

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

  18. DSM generation using multiple radar data for relief change detection in North Peloponnese

    NASA Astrophysics Data System (ADS)

    Nikolakopoulos, Konstantinos G.; Kyriou, Aggeliki; Sabatakakis, Nikolaos; Anastassopoulos, Vassilis

    2016-08-01

    Interferometry constitutes a technique of acquisition height information with a range of applications, such as Digital Surface Model (DSM) generation in order to monitoring the Earth's surface. This work is focused on interferometric DSM creation utilizing radar data of Sentinel-1 and TerraSAR-X missions, covering the wider area of Northern Peloponnese. This area is characterized of loose geological formations and intense active tectonics resulting in continuous and intense relief changes. In this context, the accuracy and the update of the DSMs is essential in order to detect and map any terrain change. The selection of Sentinel-1 and TerraSAR-X images was based on the fact that both missions provide timely, with short revisiting period and satisfactory spatial resolution data. In particular, two ranges of radar data from both missions were submitted in interferometric process aimed at DSM creation. The produced DSMs were compared both visually and statistically to a very accurate reference DSM produced from airphotos by the Greek Cadastral. Furthermore, in order to estimate the accuracy of the DSMs and detect variations of terrain's surface, points of known elevation have been used. 2D RMSE, correlation and the percentile value were computed and the results are presented.

  19. An ensemble classification approach for improved Land use/cover change detection

    NASA Astrophysics Data System (ADS)

    Chellasamy, M.; Ferré, T. P. A.; Humlekrog Greve, M.; Larsen, R.; Chinnasamy, U.

    2014-11-01

    Change Detection (CD) methods based on post-classification comparison approaches are claimed to provide potentially reliable results. They are considered to be most obvious quantitative method in the analysis of Land Use Land Cover (LULC) changes which provides from - to change information. But, the performance of post-classification comparison approaches highly depends on the accuracy of classification of individual images used for comparison. Hence, we present a classification approach that produce accurate classified results which aids to obtain improved change detection results. Machine learning is a part of broader framework in change detection, where neural networks have drawn much attention. Neural network algorithms adaptively estimate continuous functions from input data without mathematical representation of output dependence on input. A common practice for classification is to use Multi-Layer-Perceptron (MLP) neural network with backpropogation learning algorithm for prediction. To increase the ability of learning and prediction, multiple inputs (spectral, texture, topography, and multi-temporal information) are generally stacked to incorporate diversity of information. On the other hand literatures claims backpropagation algorithm to exhibit weak and unstable learning in use of multiple inputs, while dealing with complex datasets characterized by mixed uncertainty levels. To address the problem of learning complex information, we propose an ensemble classification technique that incorporates multiple inputs for classification unlike traditional stacking of multiple input data. In this paper, we present an Endorsement Theory based ensemble classification that integrates multiple information, in terms of prediction probabilities, to produce final classification results. Three different input datasets are used in this study: spectral, texture and indices, from SPOT-4 multispectral imagery captured on 1998 and 2003. Each SPOT image is classified

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

    NASA Astrophysics Data System (ADS)

    Sidiropoulos, Panagiotis; Muller, Jan-Peter

    2016-10-01

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

  1. Detection of impervious surface change with multitemporal Landsat images in an urban-rural frontier

    PubMed Central

    Lu, Dengsheng; Moran, Emilio; Hetrick, Scott

    2011-01-01

    Mapping and monitoring impervious surface dynamic change in a complex urban-rural frontier with medium or coarse spatial resolution images is a challenge due to the mixed pixel problem and the spectral confusion between impervious surfaces and other non-vegetation land covers. This research selected Lucas do Rio Verde County in Mato Grosso State, Brazil as a case study to improve impervious surface estimation performance by the integrated use of Landsat and QuickBird images and to monitor impervious surface change by analyzing the normalized multitemporal Landsat-derived fractional impervious surfaces. This research demonstrates the importance of two step calibrations. The first step is to calibrate the Landsat-derived fraction impervious surface values through the established regression model based on the QuickBird-derived impervious surface image in 2008. The second step is to conduct the normalization between the calibrated 2008 impervious surface image with other dates of impervious surface images. This research indicates that the per-pixel based method overestimates the impervious surface area in the urban-rural frontier by 50-60%. In order to accurately estimate impervious surface area, it is necessary to map the fractional impervious surface image and further calibrate the estimates with high spatial resolution images. Also normalization of the multitemporal fractional impervious surface images is needed to reduce the impacts from different environmental conditions, in order to effectively detect the impervious surface dynamic change in a complex urban-rural frontier. The procedure developed in this paper for mapping and monitoring impervious surface area is especially valuable in urban-rural frontiers where multitemporal Landsat images are difficult to be used for accurately extracting impervious surface features based on traditional per-pixel based classification methods as they cannot effectively handle the mixed pixel problem. PMID:21552379

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

    NASA Astrophysics Data System (ADS)

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

    2017-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2013-07-01

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

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

    NASA Technical Reports Server (NTRS)

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

    2009-01-01

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

  5. Regional changes in extravascular lung water detected by positron emission tomography

    SciTech Connect

    Schuster, D.P.; Marklin, G.F.; Mintun, M.A.

    1986-04-01

    Regional measurements of extravascular lung water (rEVLW) were made with positron emission tomography (PET) and 15O-labeled radionuclides. The label used to measure the total lung water (TLW) content fully equilibrated with TLW prior to scanning in both dogs with normal and low cardiac outputs, and nearly so in areas of lung made edematous by oleic acid injury (the TLW values used were 97% of maximum values). Regional EVLW measurements made by PET (EVLW-PET) and gravimetric techniques in both normal and edematous lung were closely correlated (r = 0.93), and EVLW-PET increased from an average of 0.20 to 0.37 mlH/sub 2/O/ml lung (P less than 0.05) after regional lung injury. PET measurements of regional blood volume always decreased (from an average of 0.12 to 0.09 ml blood/ml lung (P less than 0.05)) after cardiac output was lowered by hemorrhage in a separate set of animals. Total EVLW (by thermodye indicator dilution) did not change. Likewise, regional EVLW remained constant in areas below the left atrium but decreased in areas above the left atrium. We conclude that PET measurements are accurate, noninvasive, and reproducible and that regional changes may be detected even when measurements of total EVLW by other methods may fail to change significantly.

  6. Representational pseudoneglect for detecting changes to Rey-Osterrieth figures.

    PubMed

    Aniulis, Ellie; Churches, Owen; Thomas, Nicole A; Nicholls, Michael E R

    2016-11-01

    When dividing attention between the left and right sides of physical space, most individuals pay slightly more attention to the left side. This phenomenon, known as pseudoneglect, may also occur for the left and right sides of mental representations of stimuli. Representational pseudoneglect has been shown for the recall of real-world scenes and for simple, briefly presented stimuli. The current study sought to investigate the effect of exposure duration and complexity using adaptations of the Rey-Osterrieth figures. Undergraduates (n = 97) were shown a stimulus for 20 s and asked to remember it. Participants were then shown a probe and indicated whether it was the same or different. Results showed that, irrespective of whether an element was added or subtracted, changes on the left side of the remembered image were better detected. These results are consistent with representational pseudoneglect and demonstrate that this effect occurs for complex stimuli when presented for an extended period of time. Representation neglect is therefore unlikely to be the result of an initial saccade to the left-but could be related to the formation or recall of the representation.

  7. Geomorphological change detection of fluvial processes of lower Siret channel using LIDAR data

    NASA Astrophysics Data System (ADS)

    Niculita, Mihai; Obreja, Florin; Boca, Bogdan

    2015-04-01

    :121-134. Lague D., Brodu N., Leroux J., 2013. Accurate 3D comparison of complex topography with terrestrial laser scanner: application to the Rangitikei canyon (N-Z), ISPRS journal of Photogrammmetry and Remote Sensing, 80:10-26. James L.A., Hodgson M.E., Ghoshal S., Latiolais M.M., 2012. Geomorphic change detection using historic maps and DEM differencing: the temporal dimension of geospatial analysis. Geomorphology, 137:181-198. Nedelcu G., Borcan M., Branescu E., Petre C., Teleanu B., Preda A., Murafa R., 2011. Exceptional floods from the years 2008 and 2010 in Siret river basin, Proceedings of the Annual Scientific Conference of National Romanian Institute of Hydrology and Water Administration, 1-3 November 2011. (in Romanian) Olariu P., Obreja F., Obreja I., 2009. Some aspects regarding the sediment transit from Trotus catchment and lower sector of Siret river during the exceptional floods from 1991 and 2005, Annals of Stefan cel Mare University of Suceava, XVIII:93-104.(in Romanian) Serbu M., Obreja F., Olariu P., 2009. The 2008 floods from upper Siret catchment. Causes, effects, evaluation, Hidrotechnics, 54(12):1-38. (in Romanian) Wheaton J.M., Brasington J., Darby S., Sear D., 2009. Accounting for uncertainty in DEMs from repeat topographic surveys: improved sediment budgets. Earth Surface Processes and Landforms, 35(2):136-156.

  8. Using Atmospheric Circulation Patterns to Detect and Attribute Changes in the Risk of Extreme Climate Events

    NASA Astrophysics Data System (ADS)

    Diffenbaugh, N. S.; Horton, D. E.; Singh, D.; Swain, D. L.; Touma, D. E.; Mankin, J. S.

    2015-12-01

    Because of the high cost of extreme events and the growing evidence that global warming is likely to alter the statistical distribution of climate variables, detection and attribution of changes in the probability of extreme climate events has become a pressing topic for the scientific community, elected officials, and the public. While most of the emphasis has thus far focused on analyzing the climate variable of interest (most often temperature or precipitation, but also flooding and drought), there is an emerging emphasis on applying detection and attribution analysis techniques to the underlying physical causes of individual extreme events. This approach is promising in part because the underlying physical causes (such as atmospheric circulation patterns) can in some cases be more accurately represented in climate models than the more proximal climate variable (such as precipitation). In addition, and more scientifically critical, is the fact that the most extreme events result from a rare combination of interacting causes, often referred to as "ingredients". Rare events will therefore always have a strong influence of "natural" variability. Analyzing the underlying physical mechanisms can therefore help to test whether there have been changes in the probability of the constituent conditions of an individual event, or whether the co-occurrence of causal conditions cannot be distinguished from random chance. This presentation will review approaches to applying detection/attribution analysis to the underlying physical causes of extreme events (including both "thermodynamic" and "dynamic" causes), and provide a number of case studies, including the role of frequency of atmospheric circulation patterns in the probability of hot, cold, wet and dry events.

  9. Topographic change detection at select archeological sites in Grand Canyon National Park, Arizona, 2007–2010

    USGS Publications Warehouse

    Collins, Brian D.; Corbett, Skye C.; Fairley, Helen C.; Minasian, Diane L.; Kayen, Robert; Dealy, Timothy P.; Bedford, David R.

    2012-01-01

    Human occupation in Grand Canyon, Arizona, dates from at least 11,000 years before present to the modern era. For most of this period, the only evidence of human occupation in this iconic landscape is provided by archeological sites. Because of the dynamic nature of this environment, many archeological sites are subject to relatively rapid topographic change. Quantifying the extent, magnitude, and cause of such change is important for monitoring and managing these archeological sites. Such quantification is necessary to help inform the continuing debate on whether and how controlled releases from Glen Canyon Dam, located immediately upstream of Grand Canyon National Park, are affecting site erosion rates, artifact transport, and archeological resource preservation along the Colorado River in Grand Canyon. Although long-term topographic change resulting from a variety of natural processes is inherent in the Grand Canyon region, continued erosion of archeological sites threatens both the archeological resources and our future ability to study evidence of past cultural habitation. Thus, this subject is of considerable interest to National Park Service managers and other stakeholders in the Glen Canyon Dam Adaptive Management Program. Understanding the causes and effects of archeological site erosion requires a knowledge of several factors, including the location, timing, and magnitude of the changes occurring in relation to archeological resources, the rates of change, and the relative contribution of potential causes. These potential causes include sediment depletion associated with managed flows from Glen Canyon Dam, site-specific weather and overland flow patterns, visitor impacts, and long-term regional climate change. To obtain this information, highly accurate, spatially specific data are needed from sites undergoing change. Using terrestrial lidar techniques, and building upon three previous surveys of archeological sites performed in 2006 and 2007, we

  10. Development and Validation of a Novel Fusion Algorithm for Continuous, Accurate and Automated R-wave Detection and Calculation of Signal-Derived Metrics

    DTIC Science & Technology

    2013-01-01

    into sub-bands using a filter bank , feature extraction, single-channel detection blocks and decision levels, the adaptation of detection strengths...2004;3:1-9. [10] Afonso VX, Tompkins WJ, Nguyen TQ, et al. ECG beat detection using filter banks . IEEE Trans Biomed Eng 1999;46:192-202. [11] Zong W... systems ; Automatic data processing Abstract Purpose: Previous studies have shown that heart rate complexity may be a useful indicator of patient

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

    PubMed Central

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

    2015-01-01

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

  12. A non-contact method based on multiple signal classification algorithm to reduce the measurement time for accurately heart rate detection.

    PubMed

    Bechet, P; Mitran, R; Munteanu, M

    2013-08-01

    Non-contact methods for the assessment of vital signs are of great interest for specialists due to the benefits obtained in both medical and special applications, such as those for surveillance, monitoring, and search and rescue. This paper investigates the possibility of implementing a digital processing algorithm based on the MUSIC (Multiple Signal Classification) parametric spectral estimation in order to reduce the observation time needed to accurately measure the heart rate. It demonstrates that, by proper dimensioning the signal subspace, the MUSIC algorithm can be optimized in order to accurately assess the heart rate during an 8-28 s time interval. The validation of the processing algorithm performance was achieved by minimizing the mean error of the heart rate after performing simultaneous comparative measurements on several subjects. In order to calculate the error the reference value of heart rate was measured using a classic measurement system through direct contact.

  13. A non-contact method based on multiple signal classification algorithm to reduce the measurement time for accurately heart rate detection

    NASA Astrophysics Data System (ADS)

    Bechet, P.; Mitran, R.; Munteanu, M.

    2013-08-01

    Non-contact methods for the assessment of vital signs are of great interest for specialists due to the benefits obtained in both medical and special applications, such as those for surveillance, monitoring, and search and rescue. This paper investigates the possibility of implementing a digital processing algorithm based on the MUSIC (Multiple Signal Classification) parametric spectral estimation in order to reduce the observation time needed to accurately measure the heart rate. It demonstrates that, by proper dimensioning the signal subspace, the MUSIC algorithm can be optimized in order to accurately assess the heart rate during an 8-28 s time interval. The validation of the processing algorithm performance was achieved by minimizing the mean error of the heart rate after performing simultaneous comparative measurements on several subjects. In order to calculate the error the reference value of heart rate was measured using a classic measurement system through direct contact.

  14. Detection of changes in leaf water content using near- and middle-infrared reflectances

    NASA Technical Reports Server (NTRS)

    Hunt, E. Raymond, Jr.; Rock, Barrett N.

    1989-01-01

    A method to detect plant water stress by remote sensing is proposed using indices of near-IR and mid-IR wavelengths. The ability of the Leaf Water Content Index (LWCI) to determine leaf relative water content (RWC) is tested on species with different leaf morphologies. The way in which the Misture Stress Index (MSI) varies with RWC is studied. On test with several species, it is found that LWCI is equal to RWC, although the reflectances at 1.6 microns for two different RWC must be known to accurately predict unknown RWC. A linear correlation is found between MSI and RWC with each species having a different regression equation. Also, MSI is correlated with log sub 10 Equivalent Water Thickness (EWT) with data for all species falling on the same regression line. It is found that the minimum significant change of RWC that could be detected by appying the linear regression equation of MSI to EWT is 52 percent. Because the natural RWC variation from water stress is about 20 percent for most species, it is concluded that the near-IR and mid-IR reflectances cannot be used to remotely sense water stress.

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

    USGS Publications Warehouse

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

    2008-01-01

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

  16. Topographic Change Detection at Select Archeological Sites in Grand Canyon National Park, Arizona, 2006-2007

    USGS Publications Warehouse

    Collins, Brian D.; Minasian, Diane L.; Kayen, Robert

    2009-01-01

    Topographic change of archeological sites within the Colorado River corridor of Grand Canyon National Park (GCNP) is a subject of interest to National Park Service managers and other stakeholders in the Glen Canyon Dam Adaptive Management Program. Although long-term topographic change resulting from a variety of natural processes is typical in the Grand Canyon region, a continuing debate exists on whether and how controlled releases from Glen Canyon Dam, located immediately upstream of GCNP, are impacting rates of site erosion, artifact transport, and the preservation of archeological resources. Continued erosion of archeological sites threatens both the archeological resources and our future ability to study evidence of past cultural habitation. Understanding the causes and effects of archaeological site erosion requires a knowledge of several factors including the location and magnitude of the changes occurring in relation to archeological resources, the rate of the changes, and the relative contribution of several potential causes, including sediment depletion associated with managed flows from Glen Canyon Dam, site-specific weather patterns, visitor impacts, and long-term climate change. To obtain this information, highly accurate, spatially specific data are needed from sites undergoing change. Using terrestrial lidar data collection techniques and novel TIN- and GRID-based change-detection post-processing methods, we analyzed topographic data for nine archeological sites. The data were collected using three separate data collection efforts spanning 16 months (May 2006 to September 2007). Our results documented positive evidence of erosion, deposition, or both at six of the nine sites investigated during this time interval. In addition, we observed possible signs of change at two of the other sites. Erosion was concentrated in established gully drainages and averaged 12 cm to 17 cm in depth with maximum depths of 50 cm. Deposition was concentrated at specific

  17. Quantification of Forecasting and Change-Point Detection Methods for Predictive Maintenance

    DTIC Science & Technology

    2015-08-19

    Final 3. DATES COVERED (From - To) 22 Jul 2014 – 21 Jul 2015 4. TITLE AND SUBTITLE Quantification of forecasting and change -point...disadvantages of change detection techniques using Singular Spectral Transform (SST) and Autoregressive Integrated Moving Average (ARIMA) applied to equipment...are used to evaluate the capability of detection of both methods for several types of changes . SST was applied to change detection in rotating

  18. Climate Change detection using GPS RO and CMIP5 data

    NASA Astrophysics Data System (ADS)

    Molodtsov, S.; Kirilenko, A.; Olsen, D.

    2013-12-01

    General circulation models' (GCMs) response to the increase of atmospheric concentration of greenhouse gases (GHG) due to anthropogenic emissions is evident under variety of forcing scenarios. However the investigation of the anthropogenic signal in the real climate system is challenging as it requires long term high accuracy global coverage data. GPS Radio Occultation (GPS RO) technique becomes close to meeting all of these requirements, becoming the benchmark for climate data. We implemented the analysis for upper troposphere - lower stratosphere (UTLS) region between 50°N and 50°S latitudes, where the GPS RO data has higher quality. For observations, we used vertical profiles of temperature and/or geopotential heights from 2001-2008 CHAMP and 2006-2011 COSMIC occultation. GCM trends of the response patterns to the external forcings of respective climate variables were extracted from CMIP 5 GCM runs under representative concentration pathways (RCP) 8.5 and historical climate scenarios, for the same period. Natural variability was calculated using CMIP 5 GCM runs under preindustrial control scenario. The GPS RO data was downloaded from CDAAC website, GCM CMIP 5 data was obtained from Earth System Grid web page. We used optimal fingerprinting method which is generalized multivariate regression adjusted for climate change detection studies. Optimal fingerprinting allows estimating of the climate signal separately from natural climate variability. Following this methodology we applied Empirical Orthogonal Functions to filter observed and modeled data in order to decrease impact of natural variability and maximize the signal to noise ratio. Temperature and geopotential height trends in the simulated and observed climate datasets show similar features of warming of the upper troposphere and cooling of the lower stratosphere in the tropics region. Using optimal fingerprinting we found that the anthropogenic signal emerges from natural variability in GPS RO temperature

  19. Electrophysiological Correlates of Automatic Visual Change Detection in School-Age Children

    ERIC Educational Resources Information Center

    Clery, Helen; Roux, Sylvie; Besle, Julien; Giard, Marie-Helene; Bruneau, Nicole; Gomot, Marie

    2012-01-01

    Automatic stimulus-change detection is usually investigated in the auditory modality by studying Mismatch Negativity (MMN). Although the change-detection process occurs in all sensory modalities, little is known about visual deviance detection, particularly regarding the development of this brain function throughout childhood. The aim of the…

  20. Unsupervised detection and analysis of changes in everyday physical activity data.

    PubMed

    Sprint, Gina; Cook, Diane J; Schmitter-Edgecombe, Maureen

    2016-10-01

    Sensor-based time series data can be utilized to monitor changes in human behavior as a person makes a significant lifestyle change, such as progress toward a fitness goal. Recently, wearable sensors have increased in popularity as people aspire to be more conscientious of their physical health. Automatically detecting and tracking behavior changes from wearable sensor-collected physical activity data can provide a valuable monitoring and motivating tool. In this paper, we formalize the problem of unsupervised physical activity change detection and address the problem with our Physical Activity Change Detection (PACD) approach. PACD is a framework that detects changes between time periods, determines significance of the detected changes, and analyzes the nature of the changes. We compare the abilities of three change detection algorithms from the literature and one proposed algorithm to capture different types of changes as part of PACD. We illustrate and evaluate PACD on synthetic data and using Fitbit data collected from older adults who participated in a health intervention study. Results indicate PACD detects several changes in both datasets. The proposed change algorithms and analysis methods are useful data mining techniques for unsupervised, window-based change detection with potential to track users' physical activity and motivate progress toward their health goals.

  1. Hydrography change detection: the usefulness of surface channels derived From LiDAR DEMs for updating mapped hydrography

    USGS Publications Warehouse

    Poppenga, Sandra K.; Gesch, Dean B.; Worstell, Bruce B.

    2013-01-01

    The 1:24,000-scale high-resolution National Hydrography Dataset (NHD) mapped hydrography flow lines require regular updating because land surface conditions that affect surface channel drainage change over time. Historically, NHD flow lines were created by digitizing surface water information from aerial photography and paper maps. Using these same methods to update nationwide NHD flow lines is costly and inefficient; furthermore, these methods result in hydrography that lacks the horizontal and vertical accuracy needed for fully integrated datasets useful for mapping and scientific investigations. Effective methods for improving mapped hydrography employ change detection analysis of surface channels derived from light detection and ranging (LiDAR) digital elevation models (DEMs) and NHD flow lines. In this article, we describe the usefulness of surface channels derived from LiDAR DEMs for hydrography change detection to derive spatially accurate and time-relevant mapped hydrography. The methods employ analyses of horizontal and vertical differences between LiDAR-derived surface channels and NHD flow lines to define candidate locations of hydrography change. These methods alleviate the need to analyze and update the nationwide NHD for time relevant hydrography, and provide an avenue for updating the dataset where change has occurred.

  2. Ability of the Masimo pulse CO-Oximeter to detect changes in hemoglobin.

    PubMed

    Colquhoun, Douglas A; Forkin, Katherine T; Durieux, Marcel E; Thiele, Robert H

    2012-04-01

    The decision to administer blood products is complex and multifactorial. Accurate assessment of the concentration of hemoglobin [Hgb] is a key component of this evaluation. Recently a noninvasive method of continuously measuring hemoglobin (SpHb) has become available with multi-wavelength Pulse CO-Oximetry. The accuracy of this device is well documented, but the trending ability of this monitor has not been previously described. Twenty patients undergoing major thoracic and lumbar spine surgery were recruited. All patients received radial arterial lines. On the contralateral index finger, a R1 25 sensor (Rev E) was applied and connected to a Radical-7 Pulse CO-Oximeter (both Masimo Corp, Irvine, CA). Blood samples were drawn intermittently at the anesthesia provider's discretion and were analyzed by the operating room satellite laboratory CO-Oximeter. The value of Hgb and SpHb at that time point was compared. Trend analysis was performed by the four quadrant plot technique, testing directionality of change, and Critchley's polar plot method testing both directionality and magnitude of the change in values. Eighty-eight samples recorded at times of sufficient signal quality were available for analysis. Four quadrant plot analysis revealed 94% of data within the quadrants associated with the correct direction change, and 90% of data points lay within the analysis bounds proposed by Critchley. Pulse CO-Oximetry offers an acceptable trend monitor in patients undergoing major spine surgery. Future work should explore the ability of this device to detect large changes in hemoglobin, as well as its applicability in additional surgical and non-surgical patient populations.

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

    PubMed

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

    2016-08-01

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

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

    NASA Astrophysics Data System (ADS)

    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 .

  5. Grasp preparation improves change detection for congruent objects.

    PubMed

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

    2008-08-01

    A series of experiments provided converging support for the hypothesis that action preparation biases selective attention to action-congruent object features. When visual transients are masked in so-called change-blindness scenes, viewers are blind to substantial changes between 2 otherwise identical pictures that flick back and forth. The authors report data in which participants planned a grasp prior to the onset of a change-blindness scene in which 1 of 12 objects changed identity. Change blindness was substantially reduced for grasp-congruent objects (e.g., planning a whole-hand grasp reduced change blindness to a changing apple). A series of follow-up experiments ruled out an alternative explanation that this reduction had resulted from a labeling or strategizing of responses and provided converging support that the effect genuinely arose from grasp planning.

  6. A simple, yet accurate method for detecting and quantifying secretions from human minor salivary glands using the iodine-starch reaction.

    PubMed

    Shoji, N; Sasano, T; Inukai, K; Satoh-Kuriwada, S; Iikubo, M; Furuuchi, T; Sakamoto, M

    2003-11-01

    The lack of published information about the minor salivary glands is due in part to the difficulties experienced in collecting and quantifying their secretions. In fact, no method exists for measuring their secretions that is both simple and accurate. This investigation examined the accuracy of our newly developed method (which simply employs the iodine-starch reaction) in 10 healthy non-medicated adults. A strip painted with a solution of iodine in absolute alcohol then with a fine starch powder mixed with castor oil was placed at a designated location on the lower-lip mucosa for 2 min to collect saliva. Black-stained spots of various sizes corresponding to the individual glands could be accurately visualized. After removal of the strip, the total stained area (mm2) was calculated by digitizing the spot areas using a computer system. The correlation coefficient (r) between known volumes of saliva and stain size was 0.995, indicating a close correlation. The correlation coefficient (r) between area values obtained in the first trial in each subject (Y) and the second (X; 10 min later) was 0.963, and the simple regression equation was close to Y=X, indicating good reproducibility. The mean flow rate microl/cm2 per min) obtained by converting mean total area to volume and thence to flow rate was 0.49+/-0.26, in good agreement with published values obtained by others. These results suggest that our newly developed method allows both the distribution and secretion rate of the minor salivary glands to be observed, and that it should be of practical value due to its simplicity, accuracy, and reproducibility.

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

    PubMed

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

    2015-05-01

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

  8. Feasibility of using fluorescence in situ hybridization (FISH) to detect early gene changes in sputum cells from uranium miners

    SciTech Connect

    Neft, R.E.; Rogers, J.L.; Belinsky, S.A.

    1995-12-01

    Epidemiological studies have shown that combined exposure to radon progeny and tobacco smoke produce a greater than additive or synergistic increase in lung cancer risk. Lung cancer results from multiple genetic changes over a long period of time. An early change that occurs in lung cancer is trisomy 7 which is found in 50% of non-small cell lung cancer and in the far margins of resected lung tumors. The 80% mortality associated with lung cancer is in part related to the high proportion of patients who present with an advanced, unresectable tumor. Therefore, early detection of patients at risk for tumor development is critical to improve treatment of this disease. Currently, it is difficult to detect lung cancer early while it is still amendable by surgery. Saccomanno, G. has shown that premalignant cytologic changes in sputum cells collected from uranium miners can be detected by a skilled, highly trained cytopathologist. A more objective alternative for identifying premalignant cells in sputum may be to determine whether an early genetic change such as trisomy 7 is present in these cells. Fluorescence in situ hybridization (FISH) can be used to identify cells with trisomy 7. The results of this investigation indicate that FISH may prove to be an accurate, efficient method to test at-risk individuals for genetic alterations in bronchial epithelial cells from sputum.

  9. Accurate detection of the tumor clone in peripheral T-cell lymphoma biopsies by flow cytometric analysis of TCR-Vβ repertoire.

    PubMed

    Salameire, Dimitri; Solly, Françoise; Fabre, Blandine; Lefebvre, Christine; Chauvet, Martine; Gressin, Rémy; Corront, Bernadette; Ciapa, Agnès; Pernollet, Martine; Plumas, Joël; Macintyre, Elizabeth; Callanan, Mary B; Leroux, Dominique; Jacob, Marie-Christine

    2012-09-01

    Multiparametric flow cytometry has proven to be a powerful method for detection and immunophenotypic characterization of clonal subsets, particularly in lymphoproliferative disorders of the B-cell lineage. Although in theory promising, this approach has not been comparably fulfilled in mature T-cell malignancies. Specifically, the T-cell receptor-Vβ repertoire analysis in blood can provide strong evidence of clonality, particularly when a single expanded Vß family is detected. The purpose of this study was to determine the relevance of this approach when applied to biopsies, at the site of tumor involvement. To this end, 30 peripheral T-cell lymphoma and 94 control biopsies were prospectively studied. Vβ expansions were commonly detected within CD4+ or CD8+ T cells (97% of peripheral T-cell lymphoma and 54% of non-peripheral T-cell lymphoma cases); thus, not differentiating malignant from reactive processes. Interestingly, we demonstrated that using a standardized evaluation, the detection of a high Vβ expansion was closely associated with diagnosis of peripheral T-cell lymphoma, with remarkable specificity (98%) and sensitivity (90%). This approach also identified eight cases of peripheral T-cell lymphoma that were not detectable by other forms of immunophenotyping. Moreover, focusing Vβ expression analysis to T-cell subsets with aberrant immunophenotypes, we demonstrated that the T-cell clone might be heterogeneous with regard to surface CD7 or CD10 expression (4/11 cases), providing indication on 'phenotypic plasticity'. Finally, among the wide variety of Vβ families, the occurrence of a Vβ17 expansion in five cases was striking. To our knowledge, this is the first report demonstrating the power of T-cell receptor-Vβ repertoire analysis by flow cytometry in biopsies as a basis for peripheral T-cell lymphoma diagnosis and precise T-cell clone identification and characterization.

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

    NASA Astrophysics Data System (ADS)

    Pattanayak, Sonali; Nagesh Kumar, Dasika

    2015-04-01

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

  11. Grasp Preparation Improves Change Detection for Congruent Objects

    ERIC Educational Resources Information Center

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

    2008-01-01

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

  12. A Comparison of Techniques for Detecting Abnormal Change in Blogs

    SciTech Connect

    Furuta, Dr. Richard Keith; ShipmanIII, Dr. Frank Major; Bogen, Paul Logasa

    2012-01-01

    Distributed collections are made of metadata entries that contain references to artifacts not controlled by the collection curators. These collections often have limited forms of change; for digital distributed collections, primarily creation and deletion of additional resources. However, there exists a class of digital collection that undergoes additional kinds of change. These collections consist of resources that are distributed across the Internet and brought together via hyperlinking. Resources in these collections can be expected to change as time goes on. Part of the difficulty in maintaining these collections is determining if a changed page is still a valid member of the collection. Others have tried to address this by defining a maximum allowed threshold of change, however, these methods treat change as a potential problem and treat web content as static despite its intrinsic dynamicism. Instead we acknowledge change on the web as a normal part of a web document and determine the difference between what a maintainer expects a page to do and what it actually does. In this work we evaluate options for extractors and analyzers from a suite of techniques against a human-generated ground-truth set of blog changes. The results of this work show a statistically significant improvement over traditional threshold techniques for our collection.

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

    EPA Science Inventory

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

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

    NASA Astrophysics Data System (ADS)

    Jia, Yonghong; Zhou, Mingting; Jinshan, Ye

    2016-06-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

  16. Development of a strand-specific real-time qRT-PCR for the accurate detection and quantitation of West Nile virus RNA.

    PubMed

    Lim, Stephanie M; Koraka, Penelope; Osterhaus, Albert D M E; Martina, Byron E E

    2013-12-01

    Studying the tropism and replication kinetics of West Nile virus (WNV) in different cell types in vitro and in tissues in animal models is important for understanding its pathogenesis. As detection of the negative strand viral RNA is a more reliable indicator of active replication for single-stranded positive-sense RNA viruses, the specificity of qRT-PCR assays currently used for the detection of WNV positive and negative strand RNA was reassessed. It was shown that self- and falsely-primed cDNA was generated during the reverse transcription step in an assay employing unmodified primers and several reverse transcriptases. As a result, a qRT-PCR assay using the thermostable rTth in combination with tagged primers was developed, which greatly improved strand specificity by circumventing the events of self- and false-priming. The reliability of the assay was then addressed in vitro using BV-2 microglia cells as well as in C57/BL6 mice. It was possible to follow the kinetics of positive and negative-strand RNA synthesis both in vitro and in vivo; however, the sensitivity of the assay will need to be optimized in order to detect and quantify negative-strand RNA synthesis in the very early stages of infection. Overall, the strand-specific qRT-PCR assay developed in this study is an effective tool to quantify WNV RNA, reassess viral replication, and study tropism of WNV in the context of WNV pathogenesis.

  17. Change Detection Algorithms for Information Assurance of Computer Networks

    DTIC Science & Technology

    2002-01-01

    LIST OF FIGURES 2.1 Code Red I Infection (source CAIDA ) . . . . . . . . . . . . . . . . . 17 2.2 Number of probes due to the w32.Leave worm...16 Figure 2.1: Code Red I Infection (source CAIDA ) 2.3.2 Detection of an exponential signal in noise The i.i.d. assumption of the observations after

  18. Adversary phase change detection using SOMs and text data.

    SciTech Connect

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

    2010-05-01

    In this work, we developed a self-organizing map (SOM) technique for using web-based text analysis to forecast when a group is undergoing a phase change. By 'phase change', we mean that an organization has fundamentally shifted attitudes or behaviors. For instance, when ice melts into water, the characteristics of the substance change. A formerly peaceful group may suddenly adopt violence, or a violent organization may unexpectedly agree to a ceasefire. SOM techniques were used to analyze text obtained from organization postings on the world-wide web. Results suggest it may be possible to forecast phase changes, and determine if an example of writing can be attributed to a group of interest.

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

    DTIC Science & Technology

    2014-05-09

    Biosurveillance . Health officials want to anticipate (and possibly deter) disease outbreaks. These situations represent significant changes from the...approach to other real-world scenarios. Areas such as image analysis, machine health diagnosis and prognosis, biosurveillance , and quality control

  20. Detecting and visualizing structural changes in groundwater head time series

    NASA Astrophysics Data System (ADS)

    van Geer, Frans

    2013-04-01

    Since the fifties of the past century the dynamic behavior of the groundwater head has been monitored at many locations throughout the Netherlands and elsewhere. The data base of the Geological Survey of the Netherlands contains over 30,000 groundwater time series. For many water management purposes characteristics of the dynamic behavior are required, such as average, median, percentile etc.. These characteristics are estimated from the time series. In principle, the longer the time series, the more reliable the estimate. However, due to natural as well as man induced changes, the characteristics of a long time series are often changing in time as well. For water management it is important to be able to distinguish extreme values as part of the 'normal' pattern from structural changes in the groundwater regime. Whether or not structural changes are present in the time series can't be decided completely objective. Choices have to be made concerning the length of the period and the statistical parameters. Here a method is proposed to visualize the probability of structural changes in the time series using well known basic statistical tests. The visualization method is based on the mean values and standard deviation in a moving window. Apart from several characteristics that are calculated for each period separately, all pairs of two periods are compared and the difference is statistically tested. The results of these well known tests are combined in a visualization to supply to the user comprehensive information to examine structural changes in time series.

  1. Detection of seagrass distribution changes from 1991 to 2006 in xincun bay, hainan, with satellite remote sensing.

    PubMed

    Yang, Dingtian; Yang, Chaoyu

    2009-01-01

    Seagrass distribution is a very important index for costal management and protection. Seagrass distribution changes can be used as indexes to analyze the reasons for the changes. In this paper, in situ hyperspectral observation and satellite images of QuickBird, CBERS (China Brazil Earth Resources Satellite data) and Landsat data were used to retrieve bio-optical models and seagrass (Enhalus acoroides, Thalassia hemperichii) distribution in Xincun Bay, Hainan province, and seagrass distribution changes from 1991 to 2006 were analyzed. Hyperspectral results showed that the spectral bands at 555, 635, 650 and 675 nm are sensitive to leaf area index (LAI). Seagrass detection with QuickBird was more accurate than that with Landsat TM and CBERS; five classes could be classified clearly and used as correction for seagrass remote sensing data from Landsat TM and CBERS. In order to better describe seagrass distribution changes, the seagrass distribution area was divided as three regions: region A connected with region B in 1991, however it separated in 1999 and was wholly separated in 2001; seagrass in region C shrank gradually and could not be detected in 2006. Analysis of the reasons for seagrass reduction indicated it was mainly affected by aquaculture and typhoons and in recent years, by land use changes.

  2. Validation of White-Matter Lesion Change Detection Methods on a Novel Publicly Available MRI Image Database.

    PubMed

    Lesjak, Žiga; Pernuš, Franjo; Likar, Boštjan; Špiclin, Žiga

    2016-10-01

    Changes of white-matter lesions (WMLs) are good predictors of the progression of neurodegenerative diseases like multiple sclerosis (MS). Based on longitudinal magnetic resonance (MR) imaging the changes can be monitored, while the need for their accurate and reliable quantification led to the development of several automated MR image analysis methods. However, an objective comparison of the methods is difficult, because publicly unavailable validation datasets with ground truth and different sets of performance metrics were used. In this study, we acquired longitudinal MR datasets of 20 MS patients, in which brain regions were extracted, spatially aligned and intensity normalized. Two expert raters then delineated and jointly revised the WML changes on subtracted baseline and follow-up MR images to obtain ground truth WML segmentations. The main contribution of this paper is an objective, quantitative and systematic evaluation of two unsupervised and one supervised intensity based change detection method on the publicly available datasets with ground truth segmentations, using common pre- and post-processing steps and common evaluation metrics. Besides, different combinations of the two main steps of the studied change detection methods, i.e. dissimilarity map construction and its segmentation, were tested to identify the best performing combination.

  3. An Accurate and Efficient Algorithm for Detection of Radio Bursts with an Unknown Dispersion Measure, for Single-dish Telescopes and Interferometers

    NASA Astrophysics Data System (ADS)

    Zackay, Barak; Ofek, Eran O.

    2017-01-01

    Astronomical radio signals are subjected to phase dispersion while traveling through the interstellar medium. To optimally detect a short-duration signal within a frequency band, we have to precisely compensate for the unknown pulse dispersion, which is a computationally demanding task. We present the “fast dispersion measure transform” algorithm for optimal detection of such signals. Our algorithm has a low theoretical complexity of 2{N}f{N}t+{N}t{N}{{Δ }}{{log}}2({N}f), where Nf, Nt, and NΔ are the numbers of frequency bins, time bins, and dispersion measure bins, respectively. Unlike previously suggested fast algorithms, our algorithm conserves the sensitivity of brute-force dedispersion. Our tests indicate that this algorithm, running on a standard desktop computer and implemented in a high-level programming language, is already faster than the state-of-the-art dedispersion codes running on graphical processing units (GPUs). We also present a variant of the algorithm that can be efficiently implemented on GPUs. The latter algorithm’s computation and data-transport requirements are similar to those of a two-dimensional fast Fourier transform, indicating that incoherent dedispersion can now be considered a nonissue while planning future surveys. We further present a fast algorithm for sensitive detection of pulses shorter than the dispersive smearing limits of incoherent dedispersion. In typical cases, this algorithm is orders of magnitude faster than enumerating dispersion measures and coherently dedispersing by convolution. We analyze the computational complexity of pulsed signal searches by radio interferometers. We conclude that, using our suggested algorithms, maximally sensitive blind searches for dispersed pulses are feasible using existing facilities. We provide an implementation of these algorithms in Python and MATLAB.

  4. A diagnostic one-step real-time reverse transcription polymerase chain reaction method for accurate detection of influenza virus type A

    PubMed Central

    Behzadi, Mohammad Amin; Alborzi, Abdolvahab

    2016-01-01

    Introduction Influenza A is known as a public health concern worldwide. In this study, a novel one-step real-time reverse transcription polymerase chain reaction (rtRT-PCR) assay was designed and optimized for the detection of influenza A viruses. Material and methods The primers and probe were designed based on the analysis of 90 matrix nucleotide sequence data of influenza type A subtypes from the GenBank database of the National Center for Biotechnology Information (NCBI). The influenza virus A/Tehran/5652/2010 (H1N1 pdm09) was used as a reference. The rtRT-PCR assay was optimized, compared with that of the World Health Organization (WHO), and its analytical sensitivity, specificity and reproducibility were evaluated. In total, 64 nasopharyngeal swabs from patients with influenza-like illness (ILI) and 41 samples without ILI symptoms were tested for the virus, using conventional cell culture, direct immunofluorescence antibody (DFA) methods, and one-step rtRT-PCR with the designed primer set and probe and the WHO’s. Results The optimized assay results were similar to the WHO’s. The optimized assay results were similar to WHO’s, with non-significant differences for 10–103 copies of viral RNA/reaction (p > 0.05). It detected 10 copies of viral RNA/reaction with high reproducibility and no cross reactivity with other respiratory viruses. A specific cytopathic effect was observed in 6/64 (9.37%) of the ILI group using conventional culture and DFA staining methods; however, it was not seen in non-ILI. Also, the results of our assay and the WHO’s were similar to those of viral isolation and DFA staining. Conclusions Given the high specificity, sensitivity and reproducibility of this novel assay, it can serve as a reliable diagnostic tool for the detection of influenza A viruses in clinical specimens and lab experiments. PMID:27904520

  5. Accurate and efficient detection of pulmonary seed embolization in prostate iodine-125 permanent brachytherapy with a collimated gamma scintillation survey meter.

    PubMed

    Chen, Qin-Sheng; Blair, Henry F

    2003-05-01

    Pulmonary seed embolization is frequently observed in permanent prostate brachytherapy. Postoperative chest radiographic examination does not always detect seed embolization. To overcome this deficiency, a low energy gamma scintillation survey meter was converted to a seed-migration detector by adding a cone-shaped single-hole collimation cap to the window end of the scintillation probe. The response functions of the seed-migration detector to iodine-125 (I-125) for different source-to-detector distances in air and in water were measured. The spatial discrimination power of the survey meter, represented by the full width at half maximum measured in water, is typically improved from more than 7 cm to about 3 cm. Seventy-nine patients with I-125 implantation were scanned with the seed-migration detector at the patients' 30-day postevaluation visit. Fifteen patients showed single-seed embolization to the chest region and four patients displayed two-seed embolization. In other words, 24% of the patients present with embolized seeds. The detection accuracy of each patient was validated by a comprehensive investigation procedure. The comprehensive investigation consists of reviewing the patient's treatment history, orally questioning the patient for possible seed loss via the urethra route outside the hospital, examining all available chest radiographs before and after the seed implantation, and counting the seeds on the postevaluation CT scans. In comparison, examinations relying only on the analysis of postoperative chest radiographs yielded a false-positive detection in four patients and a false-negative detection in two patients. Another advantage of the seed-migration detector is that multiple seed-migration scans can be performed without exposing the patient to any additional radiation, for this device is a passive detector. Our clinical implementation also demonstrated that the seed-migration detector is a convenient and cost-effective method. As a result of this

  6. Cardiac elastography: detecting pathological changes in myocardium tissues

    NASA Astrophysics Data System (ADS)

    Konofagou, Elisa E.; Harrigan, Timothy; Solomon, Scott

    2003-05-01

    Estimation of the mechanical properties of the cardiac muscle has been shown to play a crucial role in the detection of cardiovascular disease. Elastography was recently shown feasible on RF cardiac data in vivo. In this paper, the role of elastography in the detection of ischemia/infarct is explored with simulations and in vivo experiments. In finite-element simulations of a portion of the cardiac muscle containing an infarcted region, the cardiac cycle was simulated with successive compressive and tensile strains ranging between -30% and 20%. The incremental elastic modulus was also mapped uisng adaptive methods. We then demonstrated this technique utilizing envelope-detected sonographic data (Hewlett-Packard Sonos 5500) in a patient with a known myocardial infarction. In cine-loop and M-Mode elastograms from both normal and infarcted regions in simulations and experiments, the infarcted region was identifed by the up to one order of magnitude lower incremental axial displacements and strains, and higher modulus. Information on motion, deformation and mechanical property should constitute a unique tool for noninvasive cardiac diagnosis.

  7. Shoreline Delineation and Land Reclamation Change Detection Using Landsat Image

    NASA Astrophysics Data System (ADS)

    Rosli, M. I.; Ahmad, M. A.; Kaamin, M.; Izhar, M. F. N.

    2016-07-01

    This study is conducted on the usage of remote sensing images from several different years in order to analyze the changes of shoreline and land cover of the area. Remote sensing images used in this study are the data captured by the Landsat satellite. The images are projecting the land surface in 30 by 30 meter resolution and it is processed by the ENVI software. ENVI is able to change each digital number of the pixels on the images into specific value according to the applied model for classification in which could be used as an approach in calculating the area different classes based from the images itself. Therefore, using this method, the changes on the coastal area are possible to be determined. Analysis of the shoreline and land reclamation around the coastal area is integrated with the land use changes to determine its impact. The study shows that Batu Pahat area might have undergone land reclamation whereas in Pasir Gudang is experiencing substantial amount of erosion. Besides, the changes of land use in both areas were considered to be rapid and due to the results obtained from this study, the issues may be brought about for the local authority awareness action.

  8. An epigenetic biomarker combination of PCDH17 and POU4F2 detects bladder cancer accurately by methylation analyses of urine sediment DNA in Han Chinese

    PubMed Central

    Li, Qiaoling; An, Dan; Fang, Lu; Lin, Youcheng; Hou, Yong; Xu, Abai; Fu, Yu; Lu, Wei; Chen, Xin; Chen, Mingwei; Zhang, Meng; Jiang, Huiling; Zhang, Chuanxia; Dong, Pei; Li, Chong; Chen, Jun; Yang, Guosheng; Liu, Chunxiao; Cai, Zhiming; Zhou, Fangjian; Wu, Song

    2016-01-01

    To develop a routine and effectual procedure of detecting bladder cancer (BlCa), an optimized combination of epigenetic biomarkers that work synergistically with high sensitivity and specificity is necessary. In this study, methylation levels of seven biomarkers (EOMES, GDF15, NID2, PCDH17, POU4F2, TCF21, and ZNF154) in 148 individuals—which including 58 urothelial cell carcinoma (UCC) patients, 20 infected urinary calculi (IUC) patients, 20 kidney cancer (KC) patients,20 prostate cancer (PC) patients, and 30 healthy volunteers (HV)—were quantified by qMSP using the urine sediment DNA. Receiver operating characteristic (ROC) curves were generated for each biomarker. The combining predictors of possible combinations were calculated through logistic regression model. Subsequently, ROC curves of the three best performing combinations were constructed. Then, we validated the three best performing combinations and POU4F2 in another 72 UCC, 21 IUC, 26 KC and 22 PC, and 23 HV urine samples. The combination of POU4F2/PCDH17 has yielded the highest sensitivity and specificity of 90.00% and 93.96% in all the 312 individuals, showing the capability of detecting BlCa effectively among pathologically varied sample groups. PMID:26700620

  9. Trimodal color-fluorescence-polarization endoscopy aided by a tumor selective molecular probe accurately detects flat lesions in colitis-associated cancer

    PubMed Central

    Charanya, Tauseef; York, Timothy; Bloch, Sharon; Sudlow, Gail; Liang, Kexian; Garcia, Missael; Akers, Walter J.; Rubin, Deborah; Gruev, Viktor; Achilefu, Samuel

    2014-01-01

    Abstract. Colitis-associated cancer (CAC) arises from premalignant flat lesions of the colon, which are difficult to detect with current endoscopic screening approaches. We have developed a complementary fluorescence and polarization reporting strategy that combines the unique biochemical and physical properties of dysplasia and cancer for real-time detection of these lesions. Using azoxymethane-dextran sodium sulfate (AOM-DSS) treated mice, which recapitulates human CAC and dysplasia, we show that an octapeptide labeled with a near-infrared (NIR) fluorescent dye selectively identified all precancerous and cancerous lesions. A new thermoresponsive sol-gel formulation allowed topical application of the molecular probe during endoscopy. This method yielded high contrast-to-noise ratios (CNR) between adenomatous tumors (20.6±1.65) and flat lesions (12.1±1.03) and surrounding uninvolved colon tissue versus CNR of inflamed tissues (1.62±0.41). Incorporation of nanowire-filtered polarization imaging into NIR fluorescence endoscopy shows a high depolarization contrast in both adenomatous tumors and flat lesions in CAC, reflecting compromised structural integrity of these tissues. Together, the real-time polarization imaging provides real-time validation of suspicious colon tissue highlighted by molecular fluorescence endoscopy. PMID:25473883

  10. Trimodal color-fluorescence-polarization endoscopy aided by a tumor selective molecular probe accurately detects flat lesions in colitis-associated cancer

    NASA Astrophysics Data System (ADS)

    Charanya, Tauseef; York, Timothy; Bloch, Sharon; Sudlow, Gail; Liang, Kexian; Garcia, Missael; Akers, Walter J.; Rubin, Deborah; Gruev, Viktor; Achilefu, Samuel

    2014-12-01

    Colitis-associated cancer (CAC) arises from premalignant flat lesions of the colon, which are difficult to detect with current endoscopic screening approaches. We have developed a complementary fluorescence and polarization reporting strategy that combines the unique biochemical and physical properties of dysplasia and cancer for real-time detection of these lesions. Using azoxymethane-dextran sodium sulfate (AOM-DSS) treated mice, which recapitulates human CAC and dysplasia, we show that an octapeptide labeled with a near-infrared (NIR) fluorescent dye selectively identified all precancerous and cancerous lesions. A new thermoresponsive sol-gel formulation allowed topical application of the molecular probe during endoscopy. This method yielded high contrast-to-noise ratios (CNR) between adenomatous tumors (20.6±1.65) and flat lesions (12.1±1.03) and surrounding uninvolved colon tissue versus CNR of inflamed tissues (1.62±0.41). Incorporation of nanowire-filtered polarization imaging into NIR fluorescence endoscopy shows a high depolarization contrast in both adenomatous tumors and flat lesions in CAC, reflecting compromised structural integrity of these tissues. Together, the real-time polarization imaging provides real-time validation of suspicious colon tissue highlighted by molecular fluorescence endoscopy.

  11. Infants detect changes in everyday scenes: the role of scene gist.

    PubMed

    Duh, Shinchieh; Wang, Su-hua

    2014-07-01

    When watching physical events, infants bring to bear prior knowledge about objects and readily detect changes that contradict physical rules. Here we investigate the possibility that scene gist may affect infants, as it affects adults, when detecting changes in everyday scenes. In Experiment 1, 15-month-old infants missed a perceptually salient change that preserved the gist of a generic outdoor scene; the same change was readily detected if infants had insufficient time to process the display and had to rely on perceptual information for change detection. In Experiment 2, 15-month-olds detected a perceptually subtle change that preserved the scene gist but violated the rule of object continuity, suggesting that physical rules may overpower scene gist in infants' change detection. Finally, Experiments 3 and 4 provided converging evidence for the effects of scene gist, showing that 15-month-olds missed a perceptually salient change that preserved the gist and detected a perceptually subtle change that disrupted the gist. Together, these results suggest that prior knowledge, including scene knowledge and physical knowledge, affects the process by which infants maintain their representations of everyday scenes.

  12. 3D change detection in staggered voxels model for robotic sensing and navigation

    NASA Astrophysics Data System (ADS)

    Liu, Ruixu; Hampshire, Brandon; Asari, Vijayan K.

    2016-05-01

    3D scene change detection is a challenging problem in robotic sensing and navigation. There are several unpredictable aspects in performing scene change detection. A change detection method which can support various applications in varying environmental conditions is proposed. Point cloud models are acquired from a RGB-D sensor, which provides the required color and depth information. Change detection is performed on robot view point cloud model. A bilateral filter smooths the surface and fills the holes as well as keeps the edge details on depth image. Registration of the point cloud model is implemented by using Random Sample Consensus (RANSAC) algorithm. It uses surface normal as the previous stage for the ground and wall estimate. After preprocessing the data, we create a point voxel model which defines voxel as surface or free space. Then we create a color model which defines each voxel that has a color by the mean of all points' color value in this voxel. The preliminary change detection is detected by XOR subtract on the point voxel model. Next, the eight neighbors for this center voxel are defined. If they are neither all `changed' voxels nor all `no changed' voxels, a histogram of location and hue channel color is estimated. The experimental evaluations performed to evaluate the capability of our algorithm show promising results for novel change detection that indicate all the changing objects with very limited false alarm rate.

  13. Detecting change in ecological controls down drainage networks

    NASA Astrophysics Data System (ADS)

    Power, M.; Finlay, J.; Goodrich, M.; McNeely, C.; Limm, M.; Hondzo, M.; Foufoula-Georgiou, E.; Dietrich, W.

    2007-12-01

    Ecosystem and food web controls of populations, trophic level biomass, and biogeochemical fluxes change down drainage networks. Field surveys, stable isotope tracers, and mensurative experiments repeated at different sites down along the upper drainages South Fork Eel River (North Coast of California) suggest that there are thresholds in drainage area where controls change on nitrogen loading from biological fixation, carbon sources to different consumer guilds in channel food webs, insect emergence, and bat tracking of this emergence. Between these thresholds, scaling relationships with channel hydraulic geometry may provide useful estimates of biomass distribution patterns of certain organisms that are relatively unaffected by consumer control, like some cyanobacteria. By investigating why controls and scaling relationships change at certain landscape positions under present environmental conditions, we hope to improve our ability to forecast how these transitions may shift with climate, land use, or biotic change, expanding, shrinking, or re-locating landscape domains under particular types of control. These steps seem necessary, but far from sufficient, for the grand challenge of linking local ecological control mechanisms to larger, basin-wide response.

  14. Fast and accurate metrology of multi-layered ceramic materials by an automated boundary detection algorithm developed for optical coherence tomography data

    PubMed Central

    Ekberg, Peter; Su, Rong; Chang, Ernest W.; Yun, Seok Hyun; Mattsson, Lars

    2014-01-01

    Optical coherence tomography (OCT) is useful for materials defect analysis and inspection with the additional possibility of quantitative dimensional metrology. Here, we present an automated image-processing algorithm for OCT analysis of roll-to-roll multilayers in 3D manufacturing of advanced ceramics. It has the advantage of avoiding filtering and preset modeling, and will, thus, introduce a simplification. The algorithm is validated for its capability of measuring the thickness of ceramic layers, extracting the boundaries of embedded features with irregular shapes, and detecting the geometric deformations. The accuracy of the algorithm is very high, and the reliability is better than 1 µm when evaluating with the OCT images using the same gauge block step height reference. The method may be suitable for industrial applications to the rapid inspection of manufactured samples with high accuracy and robustness. PMID:24562018

  15. Fast and accurate metrology of multi-layered ceramic materials by an automated boundary detection algorithm developed for optical coherence tomography data.

    PubMed

    Ekberg, Peter; Su, Rong; Chang, Ernest W; Yun, Seok Hyun; Mattsson, Lars

    2014-02-01

    Optical coherence tomography (OCT) is useful for materials defect analysis and inspection with the additional possibility of quantitative dimensional metrology. Here, we present an automated image-processing algorithm for OCT analysis of roll-to-roll multilayers in 3D manufacturing of advanced ceramics. It has the advantage of avoiding filtering and preset modeling, and will, thus, introduce a simplification. The algorithm is validated for its capability of measuring the thickness of ceramic layers, extracting the boundaries of embedded features with irregular shapes, and detecting the geometric deformations. The accuracy of the algorithm is very high, and the reliability is better than 1 μm when evaluating with the OCT images using the same gauge block step height reference. The method may be suitable for industrial applications to the rapid inspection of manufactured samples with high accuracy and robustness.

  16. A robust and accurate approach to automatic blood vessel detection and segmentation from angiography x-ray images using multistage random forests

    NASA Astrophysics Data System (ADS)

    Gupta, Vipin; Kale, Amit; Sundar, Hari

    2012-03-01

    In this paper we propose a novel approach based on multi-stage random forests to address problems faced by traditional vessel segmentation algorithms on account of image artifacts such as stitches organ shadows etc.. Our approach consists of collecting a very large number of training data consisting of positive and negative examples of valid seed points. The method makes use of a 14x14 window around a putative seed point. For this window three types of feature vectors are computed viz. vesselness, eigenvalue and a novel effective margin feature. A random forest RF is trained for each of the feature vectors. At run time the three RFs are applied in succession to a putative seed point generated by a naiive vessel detection algorithm based on vesselness. Our approach will prune this set of putative seed points to correctly identify true seed points thereby avoiding false positives. We demonstrate the effectiveness of our algorithm on a large dataset of angio images.

  17. Robust Rapid Change-Point Detection in Multi-Sensor Data Fusion and Behavior Research

    DTIC Science & Technology

    2011-02-25

    Areas Commun., 23, 693–702. [2] Basseville, M. and Nikiforov, I. (1993). Detection of Abrupt Changes : Theory and Applications. Englewood Cliffs...Generalization of Kullback-Leibler’s Inequality and Its Ap - plications to Quantization Effects on Detection . . . . . . . . . . . . . . . . . 51 4.3...sensor network. IEEE Trans. Inform. Theory 53 4191–4209. [31] Veeravalli, V. V. (2001). Decentralized quickest change detection . IEEE Trans. Inform

  18. Multiplexed direct genomic selection (MDiGS): a pooled BAC capture approach for highly accurate CNV and SNP/INDEL detection.

    PubMed

    Alvarado, David M; Yang, Ping; Druley, Todd E; Lovett, Michael; Gurnett, Christina A

    2014-06-01

    Despite declining sequencing costs, few methods are available for cost-effective single-nucleotide polymorphism (SNP), insertion/deletion (INDEL) and copy number variation (CNV) discovery in a single assay. Commercially available methods require a high investment to a specific region and are only cost-effective for large samples. Here, we introduce a novel, flexible approach for multiplexed targeted sequencing and CNV analysis of large genomic regions called multiplexed direct genomic selection (MDiGS). MDiGS combines biotinylated bacterial artificial chromosome (BAC) capture and multiplexed pooled capture for SNP/INDEL and CNV detection of 96 multiplexed samples on a single MiSeq run. MDiGS is advantageous over other methods for CNV detection because pooled sample capture and hybridization to large contiguous BAC baits reduces sample and probe hybridization variability inherent in other methods. We performed MDiGS capture for three chromosomal regions consisting of ∼ 550 kb of coding and non-coding sequence with DNA from 253 patients with congenital lower limb disorders. PITX1 nonsense and HOXC11 S191F missense mutations were identified that segregate in clubfoot families. Using a novel pooled-capture reference strategy, we identified recurrent chromosome chr17q23.1q23.2 duplications and small HOXC 5' cluster deletions (51 kb and 12 kb). Given the current interest in coding and non-coding variants in human disease, MDiGS fulfills a niche for comprehensive and low-cost evaluation of CNVs, coding, and non-coding variants across candidate regions of interest.

  19. A stopping theoretic approach to minimal time detection of system parameter change

    NASA Technical Reports Server (NTRS)

    Mazumdar, Ravi R.

    1986-01-01

    The problem of minimal time detection of abrupt parameter changes in linear stochastic systems considered. The problem is posed as an optimal stopping problem for the detection in change of the induced probability measure. Under the assumption of a prior distribution for the time of change (or disruption) a stopping rule is given which minimizes the average detection delay when there is knowledge of the new measure after the change. When the new induced measure is unknown, a stopping rule is given, based only on the noisy observations and is shown to be better than the a priori knowlege of the disruption time.

  20. Detecting changes of a distant gas source with an array of MOX gas sensors.

    PubMed

    Pashami, Sepideh; Lilienthal, Achim J; Trincavelli, Marco

    2012-11-27

    We address the problem of detecting changes in the activity of a distant gas source from the response of an array of metal oxide (MOX) gas sensors deployed in an open sampling system. The main challenge is the turbulent nature of gas dispersion and the response dynamics of the sensors. We propose a change point detection approach and evaluate it on individual gas sensors in an experimental setup where a gas source changes in intensity, compound, or mixture ratio. We also introduce an efficient sensor selection algorithm and evaluate the change point detection approach with the selected sensor array subsets.

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

    PubMed

    Buijsman, W; Sheinman, M

    2014-02-01

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

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

    NASA Astrophysics Data System (ADS)

    Buijsman, W.; Sheinman, M.

    2014-02-01

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

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

    NASA Astrophysics Data System (ADS)

    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

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  5. Improved Detection System Description and New Method for Accurate Calibration of Micro-Channel Plate Based Instruments and Its Use in the Fast Plasma Investigation on NASA's Magnetospheric MultiScale Mission

    NASA Technical Reports Server (NTRS)

    Gliese, U.; Avanov, L. A.; Barrie, A. C.; Kujawski, J. T.; Mariano, A. J.; Tucker, C. J.; Chornay, D. J.; Cao, N. T.; Gershman, D. J.; Dorelli, J. C.; Zeuch, M. A.; Pollock, C. J.; Jacques, A. D.

    2015-01-01

    system calibration method that enables accurate and repeatable measurement and calibration of MCP gain, MCP efficiency, signal loss due to variation in gain and efficiency, crosstalk from effects both above and below the MCP, noise margin, and stability margin in one single measurement. More precise calibration is highly desirable as the instruments will produce higher quality raw data that will require less post-acquisition data correction using results from in-flight pitch angle distribution measurements and ground calibration measurements. The detection system description and the fundamental concepts of this new calibration method, named threshold scan, will be presented. It will be shown how to derive all the individual detection system parameters and how to choose the optimum detection system operating point. This new method has been successfully applied to achieve a highly accurate calibration of the DESs and DISs of the MMS mission. The practical application of the method will be presented together with the achieved calibration results and their significance. Finally, it will be shown that, with further detailed modeling, this method can be extended for use in flight to achieve and maintain a highly accurate detection system calibration across a large number of instruments during the mission.

  6. Detecting Change Points in Sampling from Multinomial Distributions.

    DTIC Science & Technology

    1980-03-04

    change 4 point E(S j ) = E(E(Sm’ j Jk)) 1 m-1 m= --- Y E( £ X 1 k) m-l l1=1 ( 7 ) m-i kl(kp +(m-k)p,) -ik=l =m(pj +P ) 2 which equals mp under no change...var(Tm j ) 1: i2var Xi+l, j I : (i-l) 2 pij(l-Plj). =l 1=2 This is a rather messy expression which obviously reduces to m m-l)(2m-l)( r cpj (-p...expressions in ( 7 ) and (9) enable us to construct method of moments type estimatorsof pj, p; (and 6, if desired), i.e., -12- m m 2(2m-l)S 6T2J- mm,j

  7. Inverse sequential detection of parameter changes in developing time series

    NASA Technical Reports Server (NTRS)

    Radok, Uwe; Brown, Timothy J.

    1992-01-01

    Progressive values of two probabilities are obtained for parameter estimates derived from an existing set of values and from the same set enlarged by one or more new values, respectively. One probability is that of erroneously preferring the second of these estimates for the existing data ('type 1 error'), while the second probability is that of erroneously accepting their estimates for the enlarged test ('type 2 error'). A more stable combined 'no change' probability which always falls between 0.5 and 0 is derived from the (logarithmic) width of the uncertainty region of an equivalent 'inverted' sequential probability ratio test (SPRT, Wald 1945) in which the error probabilities are calculated rather than prescribed. A parameter change is indicated when the compound probability undergoes a progressive decrease. The test is explicitly formulated and exemplified for Gaussian samples.

  8. Rapid and accurate detection of the CFTR gene mutation 1811+1.6 kbA>G by real-time fluorescence resonance energy transfer PCR.

    PubMed

    Reboul, Marie-Pierre; Higueret, Laurent; Biteau, Nicolas; Iron, Albert

    2005-10-01

    The CFTR gene mutation 1811+1.6 kbA>G has been reported as associated with a severe phenotype of cystic fibrosis with pancreatic insufficiency. This mutation has been identified as a rather common one in the South West of France and in the Iberian Peninsula. Because of the precise geographical origin of the subjects and its frequency, the mutation has to be investigated with accuracy. We have developed an original real-time Fluorescence Resonance Energy Transfer (FRET) PCR assay for genotyping the mutation 1811+1.6 kbA>G. It is based on the amplification of a region spanning the mutation with simultaneous detection of the amplicon by hybridization with a bi-probe followed by a melting curve analysis. The results obtained are identical with those resulting from either restriction fragment length polymorphism analysis or sequencing. The distinction between the wild type and the mutation 1811+1.6 kbA>G is easy because the corresponding melting points shows a difference of 6 or 9.5 degrees C depending on the associated SNP A/T located 16 bp downstream. We demonstrated that a FRET assay showed enough sensitivity to discriminate between two nucleotide polymorphisms (SNPs) in the sequence of the sensor. In conclusion, this method is specific, fast, easy to perform, reproducible, inexpensive as it uses only one bi-probe and well adapted to daily practice.

  9. Information Foraging and Change Detection for Automated Science Exploration

    NASA Technical Reports Server (NTRS)

    Furlong, P. Michael; Dille, Michael

    2016-01-01

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

  10. Accurate classification of 75 counterparts of objects detected in the 54-month Palermo Swift/BAT hard X-ray catalogue

    NASA Astrophysics Data System (ADS)

    Parisi, P.; Masetti, N.; Rojas, A. F.; Jiménez-Bailón, E.; Chavushyan, V.; Palazzi, E.; Bassani, L.; Bazzano, A.; Bird, A. J.; Galaz, G.; Minniti, D.; Morelli, L.; Ubertini, P.

    2014-01-01

    Through an optical campaign performed at four telescopes located in the northern and southern hemispheres, we have obtained optical spectroscopy for 75 counterparts of unclassified or poorly studied hard X-ray emitting objects detected with Swift/BAT and listed in the 54-month Palermo BAT catalogue. All these objects also have observations taken with the Swift/XRT, ROSAT, or Chandra satellites, which allowed us to reduce the high-energy error box and pinpoint the most likely optical counterpart(s). We found that 69 sources in our sample are active galactic nuclei (AGNs) of which, 35 are classified as type 1 (with broad and narrow emission lines), 33 are classified as type 2 (with only narrow emission lines), and one is a high-redshift quasi-stellar object; the remaining 6 objects are galactic cataclysmic variables. Of the type 1 AGNs, 32 are objects of intermediate Seyfert type (1.2-1.9) and one is narrow-line Seyfert 1 galaxy; for 29 of the 35 type 1 AGNs, we have been able to estimate the central black hole mass and the Eddington ratio. Of the type 2 AGNs, two display optical features typical of the low-ionization nuclear emission-line region class, three are classified as transition objects, one is a starburst galaxy, and two are X-ray bright, optically normal galaxies. All galaxies classified in this work are relatively nearby objects (0.006-0.213) except for one at redshift 1.137. Based on observations obtained from the following observatories: Astronomical Observatory of Bologna in Loiano (Italy); Observatorio Astronómico Nacional (San Pedro Mártir, Mexico), Astronomical Observatory of Asiago (Italy), Cerro Tololo Interamerican Observatory (Chile).Tables 2 and 3 and Fig. 2 are available in electronic form at http://www.aanda.orgFITS files are only available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (ftp://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/561/A67

  11. Attentional Modulation of Change Detection ERP Components by Peripheral Retro-Cueing

    PubMed Central

    Pazo-Álvarez, Paula; Roca-Fernández, Adriana; Gutiérrez-Domínguez, Francisco-Javier; Amenedo, Elena

    2017-01-01

    Change detection is essential for visual perception and performance in our environment. However, observers often miss changes that should be easily noticed. A failure in any of the processes involved in conscious detection (encoding the pre-change display, maintenance of that information within working memory, and comparison of the pre and post change displays) can lead to change blindness. Given that unnoticed visual changes in a scene can be easily detected once attention is drawn to them, it has been suggested that attention plays an important role on visual awareness. In the present study, we used behavioral and electrophysiological (ERPs) measures to study whether the manipulation of retrospective spatial attention affects performance and modulates brain activity related to the awareness of a change. To that end, exogenous peripheral cues were presented during the delay period (retro-cues) between the first and the second array using a one-shot change detection task. Awareness of a change was associated with a posterior negative amplitude shift around 228–292 ms (“Visual Awareness Negativity”), which was independent of retrospective spatial attention, as it was elicited to both validly and invalidly cued change trials. Change detection was also associated with a larger positive deflection around 420–580 ms (“Late Positivity”), but only when the peripheral retro-cues correctly predicted the change. Present results confirm that the early and late ERP components related to change detection can be functionally dissociated through manipulations of exogenous retro-cueing using a change blindness paradigm. PMID:28270759

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

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

  13. Image change detection using a SWIR active imaging system

    NASA Astrophysics Data System (ADS)

    Schneider, Armin L.; Monnin, David; Laurenzis, Martin; Christnacher, Frank

    2013-10-01

    We are currently developing a system consisting of a GPS receiver, a three-axis magnetic compass as well as a digital video camera in order to visualize changes occuring along a regularily used itinerary. This is done by comparing actual images with images from the same scene, which have been acquired during a previous measurement. The luminosity of images from two different passages however can be quite different (due to different meteorological conditions). Whereas the global luminosity can be adjusted using non-linear luminosity correction, the treatment of shadows is more di cult. Since meteorological conditions cannot be controlled, we are investigating the possibility of using a Laser Gated Viewing system in the SWIR domain to illuminate the scene. Using appropriate filters for the camera, we are completely independent of natural illumination and in addition, the system can also be used at night.

  14. Change detection in coastal zone environments. [by Landsat MSS data analysis

    NASA Technical Reports Server (NTRS)

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

    1977-01-01

    A study was conducted with the objective to develop and evaluate various change detection techniques based upon computer-aided analysis of Landsat multispectral scanner (MSS) data to monitor coastal zone environments. The study site selected includes a portion of the Matagorda Bay estuarine system located along the Texas Coast. The principal data sources for the study were MSS data collected on November, 27, 1972 and February 25, 1975. The MSS data were processed and a multidata eight-channel data set at a scale of 1:24,000 was obtained. A description is presented of four change detection techniques which were designed and implented for evaluation, taking into account postclassification comparison change detection, delta data change detection, spectral/temporal change classification, and layered spectral/temporal approach. The results of the investigation are discussed.

  15. Conflicting effects of context in change detection and visual search: A dual process account.

    PubMed

    LaPointe, Mitchell R P; Milliken, Bruce

    2017-03-01

    Congruent contexts often facilitate performance in visual search and categorisation tasks using natural scenes. A congruent context is thought to contain predictive information about the types of objects likely to be encountered, as well as their location. However, in change detection tasks, changes embedded in congruent contexts often produce impaired performance relative to incongruent contexts. Using a stimulus set controlled for object perceptual salience, we compare performance across change detection and visual search tasks, as well as a hybrid of these 2 tasks. The results support a dual process account with opposing influences of context congruency on change detection and object identification processes, which contribute differentially to performance in visual search and change detection tasks. (PsycINFO Database Record

  16. Toward Robust Climate Baselining: Objective Assessment of Climate Change Using Widely Distributed Miniaturized Sensors for Accurate World-Wide Geophysical Measurements

    DOE R&D Accomplishments Database

    Teller, E.; Leith, C.; Canavan, G.; Marion, J.; Wood, L.

    2001-11-13

    A gap-free, world-wide, ocean-, atmosphere-, and land surface-spanning geophysical data-set of three decades time-duration containing the full set of geophysical parameters characterizing global weather is the scientific perquisite for defining the climate; the generally-accepted definition in the meteorological community is that climate is the 30-year running-average of weather. Until such a tridecadal climate baseline exists, climate change discussions inevitably will have a semi-speculative, vs. a purely scientific, character, as the baseline against which changes are referenced will at least somewhat uncertain.

  17. An automatic multi-lead electrocardiogram segmentation algorithm based on abrupt change detection.

    PubMed

    Illanes-Manriquez, Alfredo

    2010-01-01

    Automatic detection of electrocardiogram (ECG) waves provides important information for cardiac disease diagnosis. In this paper a new algorithm is proposed for automatic ECG segmentation based on multi-lead ECG processing. Two auxiliary signals are computed from the first and second derivatives of several ECG leads signals. One auxiliary signal is used for R peak detection and the other for ECG waves delimitation. A statistical hypothesis testing is finally applied to one of the auxiliary signals in order to detect abrupt mean changes. Preliminary experimental results show that the detected mean changes instants coincide with the boundaries of the ECG waves.

  18. Optical detection of structural changes in human carotid atherosclerotic plaque

    NASA Astrophysics Data System (ADS)

    Korol, R. M.; Canham, P. B.; Finlay, H. M.; Hammond, R. R.; Quantz, M.; Ferguson, G. G.; Liu, L. Y.; Lucas, A. R.

    2005-08-01

    spectroscopy is an effective method for evaluating ECM (collagen and elastin) associated with vascular remodeling despite the considerable variability in the plaque structure. Consistent regional differences were detected in the carotid specimens.

  19. Lake sediment multi-taxon DNA from North Greenland records early post-glacial appearance of vascular plants and accurately tracks environmental changes

    NASA Astrophysics Data System (ADS)

    Epp, L. S.; Gussarova, G.; Boessenkool, S.; Olsen, J.; Haile, J.; Schrøder-Nielsen, A.; Ludikova, A.; Hassel, K.; Stenøien, H. K.; Funder, S.; Willerslev, E.; Kjær, K.; Brochmann, C.

    2015-06-01

    High Arctic environments are particularly sensitive to climate changes, but retrieval of paleoecological data is challenging due to low productivity and biomass. At the same time, Arctic soils and sediments have proven exceptional for long-term DNA preservation due to their constantly low temperatures. Lake sediments contain DNA paleorecords of the surrounding ecosystems and can be used to retrieve a variety of organismal groups from a single sample. In this study, we analyzed vascular plant, bryophyte, algal (in particular diatom) and copepod DNA retrieved from a sediment core spanning the Holocene, taken from Bliss Lake on the northernmost coast of Greenland. A previous multi-proxy study including microscopic diatom analyses showed that this lake experienced changes between marine and lacustrine conditions. We inferred the same environmental changes from algal DNA preserved in the sediment core. Our DNA record was stratigraphically coherent, with no indication of leaching between layers, and our cross-taxon comparisons were in accordance with previously inferred local ecosystem changes. Authentic ancient plant DNA was retrieved from nearly all layers, both from the marine and the limnic phases, and distinct temporal changes in plant presence were recovered. The plant DNA was mostly in agreement with expected vegetation history, but very early occurrences of vascular plants, including the woody Empetrum nigrum, document terrestrial vegetation very shortly after glacial retreat. Our study shows that multi-taxon metabarcoding of sedimentary ancient DNA from lake cores is a valuable tool both for terrestrial and aquatic paleoecology, even in low-productivity ecosystems such as the High Arctic.

  20. Synergistic use of Active Passive Remote Sensing in Change Detection

    NASA Astrophysics Data System (ADS)

    Lakshmi, V.; Narayan, U.

    2006-05-01

    Retrieval of soil moisture from low frequency (1-18 GHz) satellite radiometers is well established, however satellite radiometers have the problem of moderately coarse spatial resolution limiting their potential applications such as incorporation of soil moisture estimates in agriculture or initializing mesoscale weather models. Radars are capable of much higher spatial resolution than radiometers especially with synthetic aperture processing. However, retrieval of soil moisture using radar backscattering coefficients is difficult due to more complex signal target interaction associated with measured radar backscatter data. An optimal soil moisture retrieval algorithm that combines the higher spatial resolution of radar with higher sensitivity of a radiometer to arrive at high-resolution soil moisture change developed by the authors has been used in this study. We attempt to derive high resolution change in soil moisture estimates by combining lower resolution (25 km) soil moisture product obtained from the Advanced Microwave Scanning Radiometer (AMSR-E, C- band) with high resolution (4 km) radar backscatter obtained from the Precipitation Radar (PR, Ku- band) aboard the Tropical Rainfall Measuring Mission (TRMM). PR was selected over other operational lower frequency radars (e.g. ERS-1, RADARSAT) because of its high revisit rate, which is important for capturing the temporal variability of soil moisture. The analysis is done for a one year time period and by assigning expected minimum and maximum soil moisture values for each pixel within the study area a time series of absolute soil moisture is obtained for each pixel. The soil moisture time series are qualitatively assessed by comparison with the rainfall rate data product obtained from the TRMM mission, as there are no in situ measurements of soil moisture for validation. The study area for this work is in the African Sahel region selected because of low vegetation cover and high soil moisture variability

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

    PubMed

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

    2014-11-01

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

  2. Change Detection of Lake Aba Samuel in Ethiopia

    NASA Astrophysics Data System (ADS)

    Kaczynski, R.; Rylko, A.

    2016-06-01

    Old topographic map published in 1975 elaborated from aerial photographs taken in 1972, Landsat TM data acquired in May 1986 and Landsat ETM+ from June 2002 have been used to assess the changes of the lake Aba Samuel in Ethiopia. First map of the lake has been done in the framework of UNDP project running in 1988-90 in the Ethiopian Mapping Authority. The second classification map has been done as M.Sc. thesis in the MUT in 2015. Supervised classification methods with the use of ground truth data have been used for elaboration of the Landsat TM data. From the year 1972 up to 1986 the area of the lake has decreased by 23%. From 1986 up to 2002 the area of the lake has decreased by 20%. Therefore, after 30 years the lake was smaller by 43%. This have had very bad influence on the lives of the local population. From other recent data in the period from 2002-2015 the lake has practically disappeared and now it is only a small part of the river Akaki. ENVI 5.2 and ERDAS IMAGINE 9.2 have been used for Radiometric Calibration, Quick Atmospheric Correction (QUAC) and supervised classification of Landsat ETM+ data. The Optimum Index Factor shows the best combination of Landsat TM and ETM+ bands for color composite as 1,4,5 in the color filters: B, G, R for the signature development. Methodology and final maps are enclosed in the paper.

  3. Children use object-level category knowledge to detect changes in complex auditory scenes.

    PubMed

    Vanden Bosch der Nederlanden, Christina M; Snyder, Joel S; Hannon, Erin E

    2016-11-01

    Children interact with and learn about all types of sound sources, including dogs, bells, trains, and human beings. Although it is clear that knowledge of semantic categories for everyday sights and sounds develops during childhood, there are very few studies examining how children use this knowledge to make sense of auditory scenes. We used a change deafness paradigm and an object-encoding task to investigate how children (6, 8, and 10 years of age) and adults process auditory scenes composed of everyday sounds (e.g., human voices, animal calls, environmental sounds, and musical instruments). Results indicated that although change deafness was present and robust at all ages, listeners improved at detecting changes with age. All listeners were less sensitive to changes within the same semantic category than to small acoustic changes, suggesting that, regardless of age, listeners relied heavily on semantic category knowledge to detect changes. Furthermore, all listeners showed less change deafness when they correctly encoded change-relevant objects (i.e., when they remembered hearing the changing object during the task). Finally, we found that all listeners were better at encoding human voices and were more sensitive to detecting changes involving the human voice. Despite poorer overall performance compared with adults, children detect changes in complex auditory scenes much like adults, using high-level knowledge about auditory objects to guide processing, with special attention to the human voice. (PsycINFO Database Record

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

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

  5. Detecting Significant Change in Wavefront Error: How long does it take?

    PubMed Central

    Koenig, Darren E.; Applegate, Raymond A.; Marsack, Jason D.; Sarver, Edwin J.; Nguyen, Lan Chi

    2010-01-01

    Purpose Measurement noise in ocular wavefront sensing limits detection of statistically significant change in high-order wavefront error (HO WFE). Consequently, measurement noise is problematic when trying to detect progressive change in HO WFE. Our aim is to 1) determine the necessary amount of time to detect age-related change in HO WFE given measurement variability and HO WFE composition and magnitude and 2) minimize the length of time necessary to detect change. Methods Five subjects with 0.26 to 1.57 micrometers root mean square HO WFE (HO RMS) over a 6 mm pupil were measured 12 times in 10–15 minutes using a custom Shack-Hartmann wavefront sensor. Each individual’s standard deviation of measures was used to calculate the 95% confidence interval around their mean HO RMS. Data previously reported on the rate of change in the HO RMS due to normal aging and pupil diameter was used to calculate time to detect change exceeding this interval given measurement variability. Results Single measurements limit statistical detection to a range of 8 to 30 years. Increasing the number of WFE measurements per visit decreases time to detection (e.g., 7 measurements reduce the range to 3 to 14 years). The number of years to detect a change requires consideration of the subject’s measurement variability, level and distribution of aberrations and age. Uncertainty in locating pupil centre accounts for 39 ± 8% of the total variability. Conclusions The ability to detect change in HO WFE over a short period of time due to normal aging is difficult but possible with current WFE measurement technology. Single measurements of HO WFE become less predictive of true HO WFE with increasing measurement variability. Multiple measurements reduce the variability. Even with proper fixation and instrument alignment, pupil centre location uncertainty in HO WFE measurements is a nontrivial contributor to measurement variability. PMID:19469015

  6. Metabolic changes assessed by MRS accurately reflect brain function during drug-induced epilepsy in mice in contrast to fMRI-based hemodynamic readouts.

    PubMed

    Seuwen, Aline; Schroeter, Aileen; Grandjean, Joanes; Rudin, Markus

    2015-10-15

    Functional proton magnetic resonance spectroscopy (1H-MRS) enables the non-invasive assessment of neural activity by measuring signals arising from endogenous metabolites in a time resolved manner. Proof-of-principle of this approach has been demonstrated in humans and rats; yet functional 1H-MRS has not been applied in mice so far, although it would be of considerable interest given the many genetically engineered models of neurological disorders established in this species only. Mouse 1H-MRS is challenging as the high demands on spatial resolution typically result in long data acquisition times not commensurable with functional studies. Here, we propose an approach based on spectroscopic imaging in combination with the acquisition of the free induction decay to maximize signal intensity. Highly resolved metabolite maps have been recorded from mouse brain with 12 min temporal resolution. This enabled monitoring of metabolic changes following the administration of bicuculline, a GABA-A receptor antagonist. Changes in levels of metabolites involved in energy metabolism (lactate and phosphocreatine) and neurotransmitters (glutamate) were investigated in a region-dependent manner and shown to scale with the bicuculline dose. GABAergic inhibition induced spectral changes characteristic for increased neurotransmitter turnover and oxidative stress. In contrast to metabolic readouts, BOLD and CBV fMRI responses did not scale with the bicuculline dose indicative of the failure of neurovascular coupling. Nevertheless fMRI measurements supported the notion of increased oxidative stress revealed by functional MRS. Hence, the combined analysis of metabolic and hemodynamic changes in response to stimulation provides complementary insight into processes associated with neural activity.

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

    PubMed

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

    2012-01-01

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

  8. Multiple support vector machines for land cover change detection: An application for mapping urban extensions

    NASA Astrophysics Data System (ADS)

    Nemmour, Hassiba; Chibani, Youcef

    The reliability of support vector machines for classifying hyper-spectral images of remote sensing has been proven in various studies. In this paper, we investigate their applicability for land cover change detection. First, SVM-based change detection is presented and performed for mapping urban growth in the Algerian capital. Different performance indicators, as well as a comparison with artificial neural networks, are used to support our experimental analysis. In a second step, a combination framework is proposed to improve change detection accuracy. Two combination rules, namely, Fuzzy Integral and Attractor Dynamics, are implemented and evaluated with respect to individual SVMs. Recognition rates achieved by individual SVMs, compared to neural networks, confirm their efficiency for land cover change detection. Furthermore, the relevance of SVM combination is highlighted.

  9. Enhancing the Detectability of Subtle Changes in Multispectral Imagery Through Real-time Change Magnification

    DTIC Science & Technology

    2015-07-27

    changes (movement or temperature fluctuations) in multiband ( visual , near-, shortwave- and longwave-infrared) imagery while simultaneously reducing...dynamic noise. We successfully applied the adapted algorithm to enhance the visibility of small movements in the Visual , Near-Infrared and Thermal (LWIR...image. 15. SUBJECT TERMS EOARD, Multispectral imagery, Temporal visual changes 16. SECURITY CLASSIFICATION OF: 17

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

    PubMed

    Lauer, Matthew; Aswani, Shankar

    2010-05-01

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

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

    PubMed Central

    Aswani, Shankar

    2010-01-01

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

  12. Utility Change Point Detection in Online Social Media: A Revealed Preference Framework

    NASA Astrophysics Data System (ADS)

    Aprem, Anup; Krishnamurthy, Vikram

    2017-04-01

    This paper deals with change detection of utility maximization behaviour in online social media. Such changes occur due to the effect of marketing, advertising, or changes in ground truth. First, we use the revealed preference framework to detect the unknown time point (change point) at which the utility function changed. We derive necessary and sufficient conditions for detecting the change point. Second, in the presence of noisy measurements, we propose a method to detect the change point and construct a decision test. Also, an optimization criteria is provided to recover the linear perturbation coefficients. Finally, to reduce the computational cost, a dimensionality reduction algorithm using Johnson-Lindenstrauss transform is presented. The results developed are illustrated on two real datasets: Yahoo! Tech Buzz dataset and Youstatanalyzer dataset. By using the results developed in the paper, several useful insights can be gleaned from these data sets. First, the changes in ground truth affecting the utility of the agent can be detected by utility maximization behaviour in online search. Second, the recovered utility functions satisfy the single crossing property indicating strategic substitute behaviour in online search. Third, due to the large number of videos in YouTube, the utility maximization behaviour was verified through the dimensionality reduction algorithm. Finally, using the utility function recovered in the lower dimension, we devise an algorithm to predict total traffic in YouTube.

  13. Application of singular spectrum-based change-point analysis to EMG-onset detection.

    PubMed

    Vaisman, Lev; Zariffa, José; Popovic, Milos R

    2010-08-01

    While many approaches have been proposed to identify the signal onset in EMG recordings, there is no standardized method for performing this task. Here, we propose to use a change-point detection procedure based on singular spectrum analysis to determine the onset of EMG signals. This method is suitable for automated real-time implementation, can be applied directly to the raw signal, and does not require any prior knowledge of the EMG signal's properties. The algorithm proposed by Moskvina and Zhigljavsky (2003) was applied to EMG segments recorded from wrist and trunk muscles. Wrist EMG data was collected from 9 Parkinson's disease patients with and without tremor, while trunk EMG data was collected from 13 healthy able-bodied individuals. Along with the change-point detection analysis, two threshold-based onset detection methods were applied, as well as visual estimates of the EMG onset by trained practitioners. In the case of wrist EMG data without tremor, the change-point analysis showed comparable or superior frequency and quality of detection results, as compared to other automatic detection methods. In the case of wrist EMG data with tremor and trunk EMG data, performance suffered because other changes occurring in these signals caused larger changes in the detection statistic than the changes caused by the initial muscle activation, suggesting that additional criteria are needed to identify the onset from the detection statistic other than its magnitude alone. Once this issue is resolved, change-point detection should provide an effective EMG-onset detection method suitable for automated real-time implementation.

  14. Fusion of UAV photogrammetry and digital optical granulometry for detection of structural changes in floodplains

    NASA Astrophysics Data System (ADS)

    Langhammer, Jakub; Lendzioch, Theodora; Mirijovsky, Jakub

    2016-04-01

    Granulometric analysis represents a traditional, important and for the description of sedimentary material substantial method with various applications in sedimentology, hydrology and geomorphology. However, the conventional granulometric field survey methods are time consuming, laborious, costly and are invasive to the surface being sampled, which can be limiting factor for their applicability in protected areas.. The optical granulometry has recently emerged as an image analysis technique, enabling non-invasive survey, employing semi-automated identification of clasts from calibrated digital imagery, taken on site by conventional high resolution digital camera and calibrated frame. The image processing allows detection and measurement of mixed size natural grains, their sorting and quantitative analysis using standard granulometric approaches. Despite known limitations, the technique today presents reliable tool, significantly easing and speeding the field survey in fluvial geomorphology. However, the nature of such survey has still limitations in spatial coverage of the sites and applicability in research at multitemporal scale. In our study, we are presenting novel approach, based on fusion of two image analysis techniques - optical granulometry and UAV-based photogrammetry, allowing to bridge the gap between the needs of high resolution structural information for granulometric analysis and spatially accurate and data coverage. We have developed and tested a workflow that, using UAV imaging platform enabling to deliver seamless, high resolution and spatially accurate imagery of the study site from which can be derived the granulometric properties of the sedimentary material. We have set up a workflow modeling chain, providing (i) the optimum flight parameters for UAV imagery to balance the two key divergent requirements - imagery resolution and seamless spatial coverage, (ii) the workflow for the processing of UAV acquired imagery by means of the optical

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

    NASA Astrophysics Data System (ADS)

    Zhao, Ping; Yang, Fan; Feng, Xinxi

    2009-10-01

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

  16. Toward Robust Climate Baselining: Objective Assessment of Climate Change Using Widely Distributed Miniaturized Sensors for Accurate World-Wide Geophysical Measurements

    SciTech Connect

    Teller, E; Leith, C; Canavan, G; Marion, J; Wood, L

    2001-11-13

    A gap-free, world-wide, ocean-, atmosphere-, and land surface-spanning geophysical data-set of three decades time-duration containing the full set of geophysical parameters characterizing global weather is the scientific perquisite for defining the climate; the generally-accepted definition in the meteorological community is that climate is the 30-year running-average of weather. Until such a tridecadal climate base line exists, climate change discussions inevitably will have a semi-speculative, vs. a purely scientific, character, as the baseline against which changes are referenced will be at least somewhat uncertain. The contemporary technology base provides ways-and-means for commencing the development of such a meteorological measurement-intensive climate baseline, moreover with a program budget far less than the {approx}$2.5 B/year which the US. currently spends on ''global change'' studies. In particular, the recent advent of satellite-based global telephony enables real-time control of, and data-return from, instrument packages of very modest scale, and Silicon Revolution-based sensor, data-processing and -storage advances permit 'intelligent' data-gathering payloads to be created with 10 gram-scale mass budgets. A geophysical measurement system implemented in such modern technology is a populous constellation 03 long-lived, highly-miniaturized robotic weather stations deployed throughout the weather-generating portions of the Earths atmosphere, throughout its oceans and across its land surfaces. Leveraging the technological advances of the OS, the filly-developed atmospheric weather station of this system has a projected weight of the order of 1 ounce, and contains a satellite telephone, a GPS receiver, a full set of atmospheric sensing instruments and a control computer - and has an operational life of the order of 1 year and a mass-production cost of the order of $20. Such stations are effectively ''intra-atmospheric satellites'' but likely have serial

  17. Visual Salience in the Change Detection Paradigm: The Special Role of Object Onset

    ERIC Educational Resources Information Center

    Cole, Geoff G.; Kentridge, Robert W.; Heywood, Charles A.

    2004-01-01

    The relative efficacy with which appearance of a new object orients visual attention was investigated. At issue is whether the visual system treats onset as being of particular importance or only 1 of a number of stimulus events equally likely to summon attention. Using the 1-shot change detection paradigm, the authors compared detectability of…

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

    PubMed Central

    Rice, Thomas; Quinn, Noreen; Lucey, Brigid

    2016-01-01

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

  19. Damage detection in bridge structures under moving loads with phase trajectory change of multi-type vibration measurements

    NASA Astrophysics Data System (ADS)

    Zhang, Weiwei; Li, Jun; Hao, Hong; Ma, Hongwei

    2017-03-01

    This paper presents a non-model based damage detection approach for bridge structures under moving loads based on the phase trajectory change of multi-type vibration measurements. A brief theoretical background on the vibration of a simply-supported bridge with a crack under moving load is described. The phase trajectories of multi-type dynamic responses are obtained and a damage index is defined as the separated distance between the trajectories of undamaged and damaged structures to indicate the damage location. Numerical studies on a simply-supported beam structure are conducted to investigate the sensitivity and robustness of the proposed approach to accurately identify the damage location. Experimental studies demonstrate that the proposed approach can be used to successfully identify the shear connection failure in a composite bridge model subjected to moving loads.

  20. Towards real-time change detection in videos based on existing 3D models

    NASA Astrophysics Data System (ADS)

    Ruf, Boitumelo; Schuchert, Tobias

    2016-10-01

    Image based change detection is of great importance for security applications, such as surveillance and reconnaissance, in order to find new, modified or removed objects. Such change detection can generally be performed by co-registration and comparison of two or more images. However, existing 3d objects, such as buildings, may lead to parallax artifacts in case of inaccurate or missing 3d information, which may distort the results in the image comparison process, especially when the images are acquired from aerial platforms like small unmanned aerial vehicles (UAVs). Furthermore, considering only intensity information may lead to failures in detection of changes in the 3d structure of objects. To overcome this problem, we present an approach that uses Structure-from-Motion (SfM) to compute depth information, with which a 3d change detection can be performed against an existing 3d model. Our approach is capable of the change detection in real-time. We use the input frames with the corresponding camera poses to compute dense depth maps by an image-based depth estimation algorithm. Additionally we synthesize a second set of depth maps, by rendering the existing 3d model from the same camera poses as those of the image-based depth map. The actual change detection is performed by comparing the two sets of depth maps with each other. Our method is evaluated on synthetic test data with corresponding ground truth as well as on real image test data.

  1. Multipolarimetric SAR image change detection based on multiscale feature-level fusion

    NASA Astrophysics Data System (ADS)

    Sun, X.; Zhang, J.; Zhai, L.

    2015-06-01

    Many methodologies of change detection have been discussed in the literature, but most of them are tested on only optical images or traditional synthetic-aperture radar (SAR) images. Few studies have investigated multipolarimetric SAR image change detection. In this study, we presented a type of multipolarimetric SAR image change detection approach based on nonsubsampled contourlet transform and multiscale feature-level fusion techniques. In this approach, Instead of denoising an image in advance, the nonsubsampled contourlet transform multiscale decomposition was used to reduce the effect of speckle noise by processing only the low-frequency sub-band coefficients of the decomposed image, and the multiscale feature-level fusion technique was employed to integrate the rich information obtained from various polarization images. Because SAR image information is dependent on scale, a multiscale multipolarimetric feature-level fusion strategy is introduced into the change detection to improve change detection precision; this feature-level fusion can not only achieve complementation of information with different polarizations and on different scales, but also has better robustness against noise. Compared with PCA methods, the proposed method constructs better differential images, resulting in higher change detection precision.

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

    NASA Astrophysics Data System (ADS)

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

    2013-05-01

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

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

    USGS Publications Warehouse

    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

  4. A segmentation-based approach to SAR change detection and mapping

    NASA Astrophysics Data System (ADS)

    Garzelli, Andrea; Zoppetti, Claudia

    2016-10-01

    The potentials of SAR sensors in change detection applications have been recently strengthened by the high spatial resolution and the short revisit time provided by the new generation SAR-based missions, such as COSMO- SkyMed, TerraSAR-X, and RadarSat 3. Classical pixel-based change detection methods exploit first-order statistics variations in multitemporal acquisitions. Higher-order statistics may improve the reliability of the results, while plain object-based change detection are rarely applied to SAR images due to the low signal-to-noise ratio which characterizes 1-look VHR SAR image products. The paper presents a hybrid approach considering both a pixel-based selection of likely-changed pixels and a segmentation-driven step based on the assumption that structural changes correspond to some clusters in a multiscale amplitude/texture representation. Experiments on simulated and true SAR image pairs demonstrate the advantages of the proposed approach.

  5. Detecting Evidence of Climate Change in the Forests of the Eastern United States

    USGS Publications Warehouse

    Jones, John W.; Osborne, Jesse D.

    2008-01-01

    Changes in land use or disturbances such as defoliation by insects, disease, or fire all affect the composition and amount of tree canopy in a forest. These changes are easy to detect. Noticing and understanding the complex ways that global or regional-scale climate change combines with these disturbances to affect forest growth patterns and succession is difficult. This is particularly true for regions where changes in climate are not the most extreme, such as the mid-latitude forests of the Eastern United States. If land and water resources are to be managed responsibly, it is important to know how well the impacts of climate change on these forests can be measured in order to provide the best information possible to respond to any future changes. The goal of this study is to test whether climate-induced changes in forests in the Eastern United States can be detected and characterized using satellite imagery.

  6. TREFEX: trend estimation and change detection in the response of MOX gas sensors.

    PubMed

    Pashami, Sepideh; Lilienthal, Achim J; Schaffernicht, Erik; Trincavelli, Marco

    2013-06-04

    Many applications of metal oxide gas sensors can benefit from reliable algorithms to detect significant changes in the sensor response. Significant changes indicate a change in the emission modality of a distant gas source and occur due to a sudden change of concentration or exposure to a different compound. As a consequence of turbulent gas transport and the relatively slow response and recovery times of metal oxide sensors, their response in open sampling configuration exhibits strong fluctuations that interfere with the changes of interest. In this paper we introduce TREFEX, a novel change point detection algorithm, especially designed for metal oxide gas sensors in an open sampling system. TREFEX models the response of MOX sensors as a piecewise exponential signal and considers the junctions between consecutive exponentials as change points. We formulate non-linear trend filtering and change point detection as a parameter-free convex optimization problem for single sensors and sensor arrays. We evaluate the performance of the TREFEX algorithm experimentally for different metal oxide sensors and several gas emission profiles. A comparison with the previously proposed GLR method shows a clearly superior performance of the TREFEX algorithm both in detection performance and in estimating the change time.

  7. Continuous Change Detection and Classification (CCDC) of Land Cover Using All Available Landsat Data

    NASA Astrophysics Data System (ADS)

    Zhu, Z.; Woodcock, C. E.

    2012-12-01

    A new algorithm for Continuous Change Detection and Classification (CCDC) of land cover using all available Landsat data is developed. This new algorithm is capable of detecting many kinds of land cover change as new images are collected and at the same time provide land cover maps for any given time. To better identify land cover change, a two step cloud, cloud shadow, and snow masking algorithm is used for eliminating "noisy" observations. Next, a time series model that has components of seasonality, trend, and break estimates the surface reflectance and temperature. The time series model is updated continuously with newly acquired observations. Due to the high variability in spectral response for different kinds of land cover change, the CCDC algorithm uses a data-driven threshold derived from all seven Landsat bands. When the difference between observed and predicted exceeds the thresholds three consecutive times, a pixel is identified as land cover change. Land cover classification is done after change detection. Coefficients from the time series models and the Root Mean Square Error (RMSE) from model fitting are used as classification inputs for the Random Forest Classifier (RFC). We applied this new algorithm for one Landsat scene (Path 12 Row 31) that includes all of Rhode Island as well as much of Eastern Massachusetts and parts of Connecticut. A total of 532 Landsat images acquired between 1982 and 2011 were processed. During this period, 619,924 pixels were detected to change once (91% of total changed pixels) and 60,199 pixels were detected to change twice (8% of total changed pixels). The most frequent land cover change category is from mixed forest to low density residential which occupies more than 8% of total land cover change pixels.

  8. Land cover changed object detection in remote sensing data with medium spatial resolution

    NASA Astrophysics Data System (ADS)

    Yang, Xiao tong; Liu, Huiping; Gao, Xiaofeng

    2015-06-01

    Land cover change information is crucial to analyse the process and the change patterns of environments and ecological systems. Recent studies have incorporated object-based image analysis for its ability to generate meaningful geographical objects into studies of change detection. In this research, we developed a systematic methodology to realise multi-type land cover changed object detection with medium spatial resolution remote sensing images in Beijing, China. Optimum index factor (OIF) was applied to determine the best change indicators and the chi-square transformation was carried out to determine the change threshold of the 4 classes of changed object. The clustering change vectors in the feature space were proposed to discriminate the change types. According to the accuracy assessment, the overall accuracy of changed/unchanged object detection was approximately 93.9% with an overall kappa of 0.824, and the change type discrimination also achieved an overall accuracy of 81.67%, indicating the effectiveness of the proposed method.

  9. An Evaluation of New High-Resolution Image Collection and Processing Techniques for Estimating Shrub Cover and Detecting Landscape Changes

    SciTech Connect

    Hansen, D.J.; Ostler, W.K.

    2001-05-01

    Research funded by the U.S. Department of Defense (DoD), U.S. Department of Energy (DOE), and the U.S. Environmental Protection Agency as part of the Strategic Environmental Research and Development Program (SERDP) evaluated novel techniques for collecting and processing high-resolution images in the Mojave Desert. Several camera types, lens, films, and digital processing techniques were evaluated on the basis of their ability to correctly estimate canopy cover of shrubs. A high degree of accuracy was obtained with photo scales of 1:1000 to 1:4000 and flatbed scanning rates from films or prints of 300 lines per inch or larger. Smaller scale images were of value in detecting retrospective changes in cover of large shrubs, but failed to detect smaller shrubs. New image-processing software, typically used in light microscopy, forensics, and industrial engineering, make it possible to accurately measure areas for total cover of up to four dominant shrub species in minutes compared to hours or days of field work. Canopy cover and individual shrub parameters such as width, length, circumference, and shape factors can be readily measured yielding size distribution histograms and other statistical data on plant community structure. These novel techniques are being evaluated in a four-year study of military training impacts at Fort Irwin, California. Results will be compared among the new and conventional imagery and processing, including 1-meter (m) pixel IKONOS images. The new processes create georectified color-coded contour maps of shrub cover for use with Geographic Information System (GIS) software. The technique is a valuable new emerging tool to accurately assess vegetation structure and landscape changes due to military or other land-use disturbances.

  10. Using gamma spectrometry indicators to detect and quantify fission products changes in irradiated fuel

    SciTech Connect

    Loubet, L.; Martella, Th.

    2015-07-01

    A new analysis method based on gamma scanning of fission products on irradiated rods is presented. Indicators calculated from this method can be used for the qualitative treatment and comparison of irradiated rods from PWR, SFR or and MTR. Differences in the behavior of fission products (FP) can thus be quantified. Phenomena such as migration or geometrical changes in pellets should thus benefit from these accurate, yet quickly and easily achievable results. (authors)

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

    NASA Astrophysics Data System (ADS)

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

    2016-10-01

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

  12. A robust multi-kernel change detection framework for detecting leaf beetle defoliation using Landsat 7 ETM+ data

    NASA Astrophysics Data System (ADS)

    Anees, Asim; Aryal, Jagannath; O'Reilly, Małgorzata M.; Gale, Timothy J.; Wardlaw, Tim

    2016-12-01

    A robust non-parametric framework, based on multiple Radial Basic Function (RBF) kernels, is proposed in this study, for detecting land/forest cover changes using Landsat 7 ETM+ images. One of the widely used frameworks is to find change vectors (difference image) and use a supervised classifier to differentiate between change and no-change. The Bayesian Classifiers e.g. Maximum Likelihood Classifier (MLC), Naive Bayes (NB), are widely used probabilistic classifiers which assume parametric models, e.g. Gaussian function, for the class conditional distributions. However, their performance can be limited if the data set deviates from the assumed model. The proposed framework exploits the useful properties of Least Squares Probabilistic Classifier (LSPC) formulation i.e. non-parametric and probabilistic nature, to model class posterior probabilities of the difference image using a linear combination of a large number of Gaussian kernels. To this end, a simple technique, based on 10-fold cross-validation is also proposed for tuning model parameters automatically instead of selecting a (possibly) suboptimal combination from pre-specified lists of values. The proposed framework has been tested and compared with Support Vector Machine (SVM) and NB for detection of defoliation, caused by leaf beetles (Paropsisterna spp.) in Eucalyptus nitens and Eucalyptus globulus plantations of two test areas, in Tasmania, Australia, using raw bands and band combination indices of Landsat 7 ETM+. It was observed that due to multi-kernel non-parametric formulation and probabilistic nature, the LSPC outperforms parametric NB with Gaussian assumption in change detection framework, with Overall Accuracy (OA) ranging from 93.6% (κ = 0.87) to 97.4% (κ = 0.94) against 85.3% (κ = 0.69) to 93.4% (κ = 0.85), and is more robust to changing data distributions. Its performance was comparable to SVM, with added advantages of being probabilistic and capable of handling multi-class problems

  13. Detectability of change in winter precipitation within mountain landscapes: Spatial patterns and uncertainty

    NASA Astrophysics Data System (ADS)

    Silverman, N. L.; Maneta, M. P.

    2016-06-01

    Detecting long-term change in seasonal precipitation using ground observations is dependent on the representativity of the point measurement to the surrounding landscape. In mountainous regions, representativity can be poor and lead to large uncertainties in precipitation estimates at high elevations or in areas where observations are sparse. If the uncertainty in the estimate is large compared to the long-term shifts in precipitation, then the change will likely go undetected. In this analysis, we examine the minimum detectable change across mountainous terrain