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Sample records for application detecting point

  1. Full On-Device Stay Points Detection in Smartphones for Location-Based Mobile Applications

    Directory of Open Access Journals (Sweden)

    Rafael Pérez-Torres

    2016-10-01

    Full Text Available The tracking of frequently visited places, also known as stay points, is a critical feature in location-aware mobile applications as a way to adapt the information and services provided to smartphones users according to their moving patterns. Location based applications usually employ the GPS receiver along with Wi-Fi hot-spots and cellular cell tower mechanisms for estimating user location. Typically, fine-grained GPS location data are collected by the smartphone and transferred to dedicated servers for trajectory analysis and stay points detection. Such Mobile Cloud Computing approach has been successfully employed for extending smartphone’s battery lifetime by exchanging computation costs, assuming that on-device stay points detection is prohibitive. In this article, we propose and validate the feasibility of having an alternative event-driven mechanism for stay points detection that is executed fully on-device, and that provides higher energy savings by avoiding communication costs. Our solution is encapsulated in a sensing middleware for Android smartphones, where a stream of GPS location updates is collected in the background, supporting duty cycling schemes, and incrementally analyzed following an event-driven paradigm for stay points detection. To evaluate the performance of the proposed middleware, real world experiments were conducted under different stress levels, validating its power efficiency when compared against a Mobile Cloud Computing oriented solution.

  2. Full On-Device Stay Points Detection in Smartphones for Location-Based Mobile Applications.

    Science.gov (United States)

    Pérez-Torres, Rafael; Torres-Huitzil, César; Galeana-Zapién, Hiram

    2016-10-13

    The tracking of frequently visited places, also known as stay points, is a critical feature in location-aware mobile applications as a way to adapt the information and services provided to smartphones users according to their moving patterns. Location based applications usually employ the GPS receiver along with Wi-Fi hot-spots and cellular cell tower mechanisms for estimating user location. Typically, fine-grained GPS location data are collected by the smartphone and transferred to dedicated servers for trajectory analysis and stay points detection. Such Mobile Cloud Computing approach has been successfully employed for extending smartphone's battery lifetime by exchanging computation costs, assuming that on-device stay points detection is prohibitive. In this article, we propose and validate the feasibility of having an alternative event-driven mechanism for stay points detection that is executed fully on-device, and that provides higher energy savings by avoiding communication costs. Our solution is encapsulated in a sensing middleware for Android smartphones, where a stream of GPS location updates is collected in the background, supporting duty cycling schemes, and incrementally analyzed following an event-driven paradigm for stay points detection. To evaluate the performance of the proposed middleware, real world experiments were conducted under different stress levels, validating its power efficiency when compared against a Mobile Cloud Computing oriented solution.

  3. Detecting determinism from point processes.

    Science.gov (United States)

    Andrzejak, Ralph G; Mormann, Florian; Kreuz, Thomas

    2014-12-01

    The detection of a nonrandom structure from experimental data can be crucial for the classification, understanding, and interpretation of the generating process. We here introduce a rank-based nonlinear predictability score to detect determinism from point process data. Thanks to its modular nature, this approach can be adapted to whatever signature in the data one considers indicative of deterministic structure. After validating our approach using point process signals from deterministic and stochastic model dynamics, we show an application to neuronal spike trains recorded in the brain of an epilepsy patient. While we illustrate our approach in the context of temporal point processes, it can be readily applied to spatial point processes as well.

  4. Detecting corner points from digital curves

    International Nuclear Information System (INIS)

    Sarfraz, M.

    2011-01-01

    Corners in digital images give important clues for shape representation, recognition, and analysis. Since dominant information regarding shape is usually available at the corners, they provide important features for various real life applications in the disciplines like computer vision, pattern recognition, computer graphics. Corners are the robust features in the sense that they provide important information regarding objects under translation, rotation and scale change. They are also important from the view point of understanding human perception of objects. They play crucial role in decomposing or describing the digital curves. They are also used in scale space theory, image representation, stereo vision, motion tracking, image matching, building mosaics and font designing systems. If the corner points are identified properly, a shape can be represented in an efficient and compact way with sufficient accuracy. Corner detection schemes, based on their applications, can be broadly divided into two categories: binary (suitable for binary images) and gray level (suitable for gray level images). Corner detection approaches for binary images usually involve segmenting the image into regions and extracting boundaries from those regions that contain them. The techniques for gray level images can be categorized into two classes: (a) Template based and (b) gradient based. The template based techniques utilize correlation between a sub-image and a template of a given angle. A corner point is selected by finding the maximum of the correlation output. Gradient based techniques require computing curvature of an edge that passes through a neighborhood in a gray level image. Many corner detection algorithms have been proposed in the literature which can be broadly divided into two parts. One is to detect corner points from grayscale images and other relates to boundary based corner detection. This contribution mainly deals with techniques adopted for later approach

  5. Interest point detection for hyperspectral imagery

    Science.gov (United States)

    Dorado-Muñoz, Leidy P.; Vélez-Reyes, Miguel; Roysam, Badrinath; Mukherjee, Amit

    2009-05-01

    This paper presents an algorithm for automated extraction of interest points (IPs)in multispectral and hyperspectral images. Interest points are features of the image that capture information from its neighbours and they are distinctive and stable under transformations such as translation and rotation. Interest-point operators for monochromatic images were proposed more than a decade ago and have since been studied extensively. IPs have been applied to diverse problems in computer vision, including image matching, recognition, registration, 3D reconstruction, change detection, and content-based image retrieval. Interest points are helpful in data reduction, and reduce the computational burden of various algorithms (like registration, object detection, 3D reconstruction etc) by replacing an exhaustive search over the entire image domain by a probe into a concise set of highly informative points. An interest operator seeks out points in an image that are structurally distinct, invariant to imaging conditions, stable under geometric transformation, and interpretable which are good candidates for interest points. Our approach extends ideas from Lowe's keypoint operator that uses local extrema of Difference of Gaussian (DoG) operator at multiple scales to detect interest point in gray level images. The proposed approach extends Lowe's method by direct conversion of scalar operations such as scale-space generation, and extreme point detection into operations that take the vector nature of the image into consideration. Experimental results with RGB and hyperspectral images which demonstrate the potential of the method for this application and the potential improvements of a fully vectorial approach over band-by-band approaches described in the literature.

  6. Algorithms for Collision Detection Between a Point and a Moving Polygon, with Applications to Aircraft Weather Avoidance

    Science.gov (United States)

    Narkawicz, Anthony; Hagen, George

    2016-01-01

    This paper proposes mathematical definitions of functions that can be used to detect future collisions between a point and a moving polygon. The intended application is weather avoidance, where the given point represents an aircraft and bounding polygons are chosen to model regions with bad weather. Other applications could possibly include avoiding other moving obstacles. The motivation for the functions presented here is safety, and therefore they have been proved to be mathematically correct. The functions are being developed for inclusion in NASA's Stratway software tool, which allows low-fidelity air traffic management concepts to be easily prototyped and quickly tested.

  7. Few molecule SERS detection using nanolens based plasmonic nanostructure: application to point mutation detection

    KAUST Repository

    Das, Gobind

    2016-10-27

    Advancements in nanotechnology fabrication techniques allow the possibility to design and fabricate a device with a minimum gap (<10 nm) between the composing nanostructures in order to obtain better control over the creation and spatial definition of plasmonic hot-spots. The present study is intended to show the fabrication of nanolens and their application to single/few molecules detection. Theoretical simulations were performed on different designs of real structures, including comparison of rough and smooth surfaces. Various molecules (rhodamine 6G, benzenethiol and BRCA1/BRCT peptides) were examined in this regard. Single molecule detection was possible for synthetic peptides, with a possible application in early detection of diseases. © The Royal Society of Chemistry.

  8. Few molecule SERS detection using nanolens based plasmonic nanostructure: application to point mutation detection

    KAUST Repository

    Das, Gobind; Alrasheed, Salma; Coluccio, Maria Laura; Gentile, Francesco; Nicastri, Annalisa; Candeloro, Patrizio; Cuda, Giovanni; Perozziello, Gerardo; Di Fabrizio, Enzo M.

    2016-01-01

    Advancements in nanotechnology fabrication techniques allow the possibility to design and fabricate a device with a minimum gap (<10 nm) between the composing nanostructures in order to obtain better control over the creation and spatial definition of plasmonic hot-spots. The present study is intended to show the fabrication of nanolens and their application to single/few molecules detection. Theoretical simulations were performed on different designs of real structures, including comparison of rough and smooth surfaces. Various molecules (rhodamine 6G, benzenethiol and BRCA1/BRCT peptides) were examined in this regard. Single molecule detection was possible for synthetic peptides, with a possible application in early detection of diseases. © The Royal Society of Chemistry.

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

    Science.gov (United States)

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

    2015-03-01

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

  10. Comparison of methods for accurate end-point detection of potentiometric titrations

    Science.gov (United States)

    Villela, R. L. A.; Borges, P. P.; Vyskočil, L.

    2015-01-01

    Detection of the end point in potentiometric titrations has wide application on experiments that demand very low measurement uncertainties mainly for certifying reference materials. Simulations of experimental coulometric titration data and consequential error analysis of the end-point values were conducted using a programming code. These simulations revealed that the Levenberg-Marquardt method is in general more accurate than the traditional second derivative technique used currently as end-point detection for potentiometric titrations. Performance of the methods will be compared and presented in this paper.

  11. Comparison of methods for accurate end-point detection of potentiometric titrations

    International Nuclear Information System (INIS)

    Villela, R L A; Borges, P P; Vyskočil, L

    2015-01-01

    Detection of the end point in potentiometric titrations has wide application on experiments that demand very low measurement uncertainties mainly for certifying reference materials. Simulations of experimental coulometric titration data and consequential error analysis of the end-point values were conducted using a programming code. These simulations revealed that the Levenberg-Marquardt method is in general more accurate than the traditional second derivative technique used currently as end-point detection for potentiometric titrations. Performance of the methods will be compared and presented in this paper

  12. Advanced DNA-Based Point-of-Care Diagnostic Methods for Plant Diseases Detection

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    Han Yih Lau

    2017-12-01

    Full Text Available Diagnostic technologies for the detection of plant pathogens with point-of-care capability and high multiplexing ability are an essential tool in the fight to reduce the large agricultural production losses caused by plant diseases. The main desirable characteristics for such diagnostic assays are high specificity, sensitivity, reproducibility, quickness, cost efficiency and high-throughput multiplex detection capability. This article describes and discusses various DNA-based point-of care diagnostic methods for applications in plant disease detection. Polymerase chain reaction (PCR is the most common DNA amplification technology used for detecting various plant and animal pathogens. However, subsequent to PCR based assays, several types of nucleic acid amplification technologies have been developed to achieve higher sensitivity, rapid detection as well as suitable for field applications such as loop-mediated isothermal amplification, helicase-dependent amplification, rolling circle amplification, recombinase polymerase amplification, and molecular inversion probe. The principle behind these technologies has been thoroughly discussed in several review papers; herein we emphasize the application of these technologies to detect plant pathogens by outlining the advantages and disadvantages of each technology in detail.

  13. Adaptive Ridge Point Refinement for Seeds Detection in X-Ray Coronary Angiogram

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    Ruoxiu Xiao

    2015-01-01

    Full Text Available Seed point is prerequired condition for tracking based method for extracting centerline or vascular structures from the angiogram. In this paper, a novel seed point detection method for coronary artery segmentation is proposed. Vessels on the image are first enhanced according to the distribution of Hessian eigenvalue in multiscale space; consequently, centerlines of tubular vessels are also enhanced. Ridge point is extracted as candidate seed point, which is then refined according to its mathematical definition. The theoretical feasibility of this method is also proven. Finally, all the detected ridge points are checked using a self-adaptive threshold to improve the robustness of results. Clinical angiograms are used to evaluate the performance of the proposed algorithm, and the results show that the proposed algorithm can detect a large set of true seed points located on most branches of vessels. Compared with traditional seed point detection algorithms, the proposed method can detect a larger number of seed points with higher precision. Considering that the proposed method can achieve accurate seed detection without any human interaction, it can be utilized for several clinical applications, such as vessel segmentation, centerline extraction, and topological identification.

  14. Application of random-point processes to the detection of radiation sources

    International Nuclear Information System (INIS)

    Woods, J.W.

    1978-01-01

    In this report the mathematical theory of random-point processes is reviewed and it is shown how use of the theory can obtain optimal solutions to the problem of detecting radiation sources. As noted, the theory also applies to image processing in low-light-level or low-count-rate situations. Paralleling Snyder's work, the theory is extended to the multichannel case of a continuous, two-dimensional (2-D), energy-time space. This extension essentially involves showing that the data are doubly stochastic Poisson (DSP) point processes in energy as well as time. Further, a new 2-D recursive formulation is presented for the radiation-detection problem with large computational savings over nonrecursive techniques when the number of channels is large (greater than or equal to 30). Finally, some adaptive strategies for on-line ''learning'' of unknown, time-varying signal and background-intensity parameters and statistics are present and discussed. These adaptive procedures apply when a complete statistical description is not available a priori

  15. Advances in Candida detection platforms for clinical and point-of-care applications

    Science.gov (United States)

    Safavieh, Mohammadali; Coarsey, Chad; Esiobu, Nwadiuto; Memic, Adnan; Vyas, Jatin Mahesh; Shafiee, Hadi; Asghar, Waseem

    2016-01-01

    Invasive candidiasis remains one of the most serious community and healthcare-acquired infections worldwide. Conventional Candida detection methods based on blood and plate culture are time-consuming and require at least 2–4 days to identify various Candida species. Despite considerable advances for candidiasis detection, the development of simple, compact and portable point-of-care diagnostics for rapid and precise testing that automatically performs cell lysis, nucleic acid extraction, purification and detection still remains a challenge. Here, we systematically review most prominent conventional and nonconventional techniques for the detection of various Candida species, including Candida staining, blood culture, serological testing and nucleic acid-based analysis. We also discuss the most advanced lab on a chip devices for candida detection. PMID:27093473

  16. Detecting change-points in extremes

    KAUST Repository

    Dupuis, D. J.

    2015-01-01

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

  17. Ghost imaging with bucket detection and point detection

    Science.gov (United States)

    Zhang, De-Jian; Yin, Rao; Wang, Tong-Biao; Liao, Qing-Hua; Li, Hong-Guo; Liao, Qinghong; Liu, Jiang-Tao

    2018-04-01

    We experimentally investigate ghost imaging with bucket detection and point detection in which three types of illuminating sources are applied: (a) pseudo-thermal light source; (b) amplitude modulated true thermal light source; (c) amplitude modulated laser source. Experimental results show that the quality of ghost images reconstructed with true thermal light or laser beam is insensitive to the usage of bucket or point detector, however, the quality of ghost images reconstructed with pseudo-thermal light in bucket detector case is better than that in point detector case. Our theoretical analysis shows that the reason for this is due to the first order transverse coherence of the illuminating source.

  18. Induced Temporal Signatures for Point-Source Detection

    International Nuclear Information System (INIS)

    Stephens, Daniel L.; Runkle, Robert C.; Carlson, Deborah K.; Peurrung, Anthony J.; Seifert, Allen; Wyatt, Cory R.

    2005-01-01

    Detection of radioactive point-sized sources is inherently divided into two regimes encompassing stationary and moving detectors. The two cases differ in their treatment of background radiation and its influence on detection sensitivity. In the stationary detector case the statistical fluctuation of the background determines the minimum detectable quantity. In the moving detector case the detector may be subjected to widely and irregularly varying background radiation, as a result of geographical and environmental variation. This significant systematic variation, in conjunction with the statistical variation of the background, requires a conservative threshold to be selected to yield the same false-positive rate as the stationary detection case. This results in lost detection sensitivity for real sources. This work focuses on a simple and practical modification of the detector geometry that increase point-source recognition via a distinctive temporal signature. A key part of this effort is the integrated development of both detector geometries that induce a highly distinctive signature for point sources and the development of statistical algorithms able to optimize detection of this signature amidst varying background. The identification of temporal signatures for point sources has been demonstrated and compared with the canonical method showing good results. This work demonstrates that temporal signatures are efficient at increasing point-source discrimination in a moving detector system

  19. Robust Spacecraft Component Detection in Point Clouds

    Directory of Open Access Journals (Sweden)

    Quanmao Wei

    2018-03-01

    Full Text Available Automatic component detection of spacecraft can assist in on-orbit operation and space situational awareness. Spacecraft are generally composed of solar panels and cuboidal or cylindrical modules. These components can be simply represented by geometric primitives like plane, cuboid and cylinder. Based on this prior, we propose a robust automatic detection scheme to automatically detect such basic components of spacecraft in three-dimensional (3D point clouds. In the proposed scheme, cylinders are first detected in the iteration of the energy-based geometric model fitting and cylinder parameter estimation. Then, planes are detected by Hough transform and further described as bounded patches with their minimum bounding rectangles. Finally, the cuboids are detected with pair-wise geometry relations from the detected patches. After successive detection of cylinders, planar patches and cuboids, a mid-level geometry representation of the spacecraft can be delivered. We tested the proposed component detection scheme on spacecraft 3D point clouds synthesized by computer-aided design (CAD models and those recovered by image-based reconstruction, respectively. Experimental results illustrate that the proposed scheme can detect the basic geometric components effectively and has fine robustness against noise and point distribution density.

  20. Robust Spacecraft Component Detection in Point Clouds.

    Science.gov (United States)

    Wei, Quanmao; Jiang, Zhiguo; Zhang, Haopeng

    2018-03-21

    Automatic component detection of spacecraft can assist in on-orbit operation and space situational awareness. Spacecraft are generally composed of solar panels and cuboidal or cylindrical modules. These components can be simply represented by geometric primitives like plane, cuboid and cylinder. Based on this prior, we propose a robust automatic detection scheme to automatically detect such basic components of spacecraft in three-dimensional (3D) point clouds. In the proposed scheme, cylinders are first detected in the iteration of the energy-based geometric model fitting and cylinder parameter estimation. Then, planes are detected by Hough transform and further described as bounded patches with their minimum bounding rectangles. Finally, the cuboids are detected with pair-wise geometry relations from the detected patches. After successive detection of cylinders, planar patches and cuboids, a mid-level geometry representation of the spacecraft can be delivered. We tested the proposed component detection scheme on spacecraft 3D point clouds synthesized by computer-aided design (CAD) models and those recovered by image-based reconstruction, respectively. Experimental results illustrate that the proposed scheme can detect the basic geometric components effectively and has fine robustness against noise and point distribution density.

  1. Optimizing Probability of Detection Point Estimate Demonstration

    Science.gov (United States)

    Koshti, Ajay M.

    2017-01-01

    Probability of detection (POD) analysis is used in assessing reliably detectable flaw size in nondestructive evaluation (NDE). MIL-HDBK-18231and associated mh18232POD software gives most common methods of POD analysis. Real flaws such as cracks and crack-like flaws are desired to be detected using these NDE methods. A reliably detectable crack size is required for safe life analysis of fracture critical parts. The paper provides discussion on optimizing probability of detection (POD) demonstration experiments using Point Estimate Method. POD Point estimate method is used by NASA for qualifying special NDE procedures. The point estimate method uses binomial distribution for probability density. Normally, a set of 29 flaws of same size within some tolerance are used in the demonstration. The optimization is performed to provide acceptable value for probability of passing demonstration (PPD) and achieving acceptable value for probability of false (POF) calls while keeping the flaw sizes in the set as small as possible.

  2. Exploring Permission-Induced Risk in Android Applications for Malicious Application Detection

    KAUST Repository

    Wang, Wei; Wang, Xing; Feng, Dawei; Liu, Jiqiang; Han, Zhen; Zhang, Xiangliang

    2014-01-01

    Android has been a major target of malicious applications (malapps). How to detect and keep the malapps out of the app markets is an ongoing challenge. One of the central design points of Android security mechanism is permission control

  3. Fast Change Point Detection for Electricity Market Analysis

    Energy Technology Data Exchange (ETDEWEB)

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

    2013-08-25

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

  4. Detecting change-points in extremes

    KAUST Repository

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

    2015-01-01

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

  5. Indoor Navigation from Point Clouds: 3d Modelling and Obstacle Detection

    Science.gov (United States)

    Díaz-Vilariño, L.; Boguslawski, P.; Khoshelham, K.; Lorenzo, H.; Mahdjoubi, L.

    2016-06-01

    In the recent years, indoor modelling and navigation has become a research of interest because many stakeholders require navigation assistance in various application scenarios. The navigational assistance for blind or wheelchair people, building crisis management such as fire protection, augmented reality for gaming, tourism or training emergency assistance units are just some of the direct applications of indoor modelling and navigation. Navigational information is traditionally extracted from 2D drawings or layouts. Real state of indoors, including opening position and geometry for both windows and doors, and the presence of obstacles is commonly ignored. In this work, a real indoor-path planning methodology based on 3D point clouds is developed. The value and originality of the approach consist on considering point clouds not only for reconstructing semantically-rich 3D indoor models, but also for detecting potential obstacles in the route planning and using these for readapting the routes according to the real state of the indoor depictured by the laser scanner.

  6. INDOOR NAVIGATION FROM POINT CLOUDS: 3D MODELLING AND OBSTACLE DETECTION

    Directory of Open Access Journals (Sweden)

    L. Díaz-Vilariño

    2016-06-01

    Full Text Available In the recent years, indoor modelling and navigation has become a research of interest because many stakeholders require navigation assistance in various application scenarios. The navigational assistance for blind or wheelchair people, building crisis management such as fire protection, augmented reality for gaming, tourism or training emergency assistance units are just some of the direct applications of indoor modelling and navigation. Navigational information is traditionally extracted from 2D drawings or layouts. Real state of indoors, including opening position and geometry for both windows and doors, and the presence of obstacles is commonly ignored. In this work, a real indoor-path planning methodology based on 3D point clouds is developed. The value and originality of the approach consist on considering point clouds not only for reconstructing semantically-rich 3D indoor models, but also for detecting potential obstacles in the route planning and using these for readapting the routes according to the real state of the indoor depictured by the laser scanner.

  7. Point Cluster Analysis Using a 3D Voronoi Diagram with Applications in Point Cloud Segmentation

    Directory of Open Access Journals (Sweden)

    Shen Ying

    2015-08-01

    Full Text Available Three-dimensional (3D point analysis and visualization is one of the most effective methods of point cluster detection and segmentation in geospatial datasets. However, serious scattering and clotting characteristics interfere with the visual detection of 3D point clusters. To overcome this problem, this study proposes the use of 3D Voronoi diagrams to analyze and visualize 3D points instead of the original data item. The proposed algorithm computes the cluster of 3D points by applying a set of 3D Voronoi cells to describe and quantify 3D points. The decompositions of point cloud of 3D models are guided by the 3D Voronoi cell parameters. The parameter values are mapped from the Voronoi cells to 3D points to show the spatial pattern and relationships; thus, a 3D point cluster pattern can be highlighted and easily recognized. To capture different cluster patterns, continuous progressive clusters and segmentations are tested. The 3D spatial relationship is shown to facilitate cluster detection. Furthermore, the generated segmentations of real 3D data cases are exploited to demonstrate the feasibility of our approach in detecting different spatial clusters for continuous point cloud segmentation.

  8. Nanoparticle Detection of Urinary Markers for Point-of-Care Diagnosis of Kidney Injury.

    Directory of Open Access Journals (Sweden)

    Hyun Jung Chung

    Full Text Available The high incidence of acute and chronic kidney injury due to various environmental factors such as heavy metals or chemicals has been a major problem in developing countries. However, the diagnosis of kidney injury in these areas can be more challenging due to the lack of highly sensitive and specific techniques that can be applied in point-of-care settings. To address this, we have developed a technique called 'micro-urine nanoparticle detection (μUNPD', that allows the detection of trace amounts of molecular markers in urine. Specifically, this technique utilizes an automated on-chip assay followed by detection with a hand-held device for the read-out. Using the μUNPD technology, the kidney injury markers KIM-1 and Cystatin C were detected down to concentrations of 0.1 ng/ml and 20 ng/ml respectively, which meets the cut-off range required to identify patients with acute or chronic kidney injury. Thus, we show that the μUNPD technology enables point of care and non-invasive detection of kidney injury, and has potential for applications in diagnosing kidney injury with high sensitivity in resource-limited settings.

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

    Science.gov (United States)

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

    2013-09-01

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

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

    Directory of Open Access Journals (Sweden)

    Nathan Gold

    2018-01-01

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

  11. Supervised Outlier Detection in Large-Scale Mvs Point Clouds for 3d City Modeling Applications

    Science.gov (United States)

    Stucker, C.; Richard, A.; Wegner, J. D.; Schindler, K.

    2018-05-01

    We propose to use a discriminative classifier for outlier detection in large-scale point clouds of cities generated via multi-view stereo (MVS) from densely acquired images. What makes outlier removal hard are varying distributions of inliers and outliers across a scene. Heuristic outlier removal using a specific feature that encodes point distribution often delivers unsatisfying results. Although most outliers can be identified correctly (high recall), many inliers are erroneously removed (low precision), too. This aggravates object 3D reconstruction due to missing data. We thus propose to discriminatively learn class-specific distributions directly from the data to achieve high precision. We apply a standard Random Forest classifier that infers a binary label (inlier or outlier) for each 3D point in the raw, unfiltered point cloud and test two approaches for training. In the first, non-semantic approach, features are extracted without considering the semantic interpretation of the 3D points. The trained model approximates the average distribution of inliers and outliers across all semantic classes. Second, semantic interpretation is incorporated into the learning process, i.e. we train separate inlieroutlier classifiers per semantic class (building facades, roof, ground, vegetation, fields, and water). Performance of learned filtering is evaluated on several large SfM point clouds of cities. We find that results confirm our underlying assumption that discriminatively learning inlier-outlier distributions does improve precision over global heuristics by up to ≍ 12 percent points. Moreover, semantically informed filtering that models class-specific distributions further improves precision by up to ≍ 10 percent points, being able to remove very isolated building, roof, and water points while preserving inliers on building facades and vegetation.

  12. Distance-based microfluidic quantitative detection methods for point-of-care testing.

    Science.gov (United States)

    Tian, Tian; Li, Jiuxing; Song, Yanling; Zhou, Leiji; Zhu, Zhi; Yang, Chaoyong James

    2016-04-07

    Equipment-free devices with quantitative readout are of great significance to point-of-care testing (POCT), which provides real-time readout to users and is especially important in low-resource settings. Among various equipment-free approaches, distance-based visual quantitative detection methods rely on reading the visual signal length for corresponding target concentrations, thus eliminating the need for sophisticated instruments. The distance-based methods are low-cost, user-friendly and can be integrated into portable analytical devices. Moreover, such methods enable quantitative detection of various targets by the naked eye. In this review, we first introduce the concept and history of distance-based visual quantitative detection methods. Then, we summarize the main methods for translation of molecular signals to distance-based readout and discuss different microfluidic platforms (glass, PDMS, paper and thread) in terms of applications in biomedical diagnostics, food safety monitoring, and environmental analysis. Finally, the potential and future perspectives are discussed.

  13. The computation of fixed points and applications

    CERN Document Server

    Todd, Michael J

    1976-01-01

    Fixed-point algorithms have diverse applications in economics, optimization, game theory and the numerical solution of boundary-value problems. Since Scarf's pioneering work [56,57] on obtaining approximate fixed points of continuous mappings, a great deal of research has been done in extending the applicability and improving the efficiency of fixed-point methods. Much of this work is available only in research papers, although Scarf's book [58] gives a remarkably clear exposition of the power of fixed-point methods. However, the algorithms described by Scarf have been super~eded by the more sophisticated restart and homotopy techniques of Merrill [~8,~9] and Eaves and Saigal [1~,16]. To understand the more efficient algorithms one must become familiar with the notions of triangulation and simplicial approxi- tion, whereas Scarf stresses the concept of primitive set. These notes are intended to introduce to a wider audience the most recent fixed-point methods and their applications. Our approach is therefore ...

  14. Laser desorption mass spectrometry for point mutation detection

    Energy Technology Data Exchange (ETDEWEB)

    Taranenko, N.I.; Chung, C.N.; Zhu, Y.F. [Oak Ridge National Lab., TN (United States)] [and others

    1996-12-31

    A point mutation can be associated with the pathogenesis of inherited or acquired diseases. Laser desorption mass spectrometry coupled with allele specific polymerase chain reaction (PCR) was first used for point mutation detection. G551D is one of several mutations of the cystic fibrosis transmembrane conductance regulator (CFTR) gene present in 1-3% of the mutant CFTR alleles in most European populations. In this work, two different approaches were pursued to detect G551D point mutation in the cystic fibrosis gene. The strategy is to amplify the desired region of DNA template by PCR using two primers that overlap one base at the site of the point mutation and which vary in size. If the two primers based on the normal sequence match the target DNA sequence, a normal PCR product will be produced. However, if the alternately sized primers that match the mutant sequence recognize the target DNA, an abnormal PCR product will be produced. Thus, the mass spectrometer can be used to identify patients that are homozygous normal, heterozygous for a mutation or homozygous abnormal at a mutation site. Another approach to identify similar mutations is the use of sequence specific restriction enzymes which respond to changes in the DNA sequence. Mass spectrometry is used to detect the length of the restriction fragments by digestion of a PCR generated target fragment. 21 refs., 10 figs., 2 tabs.

  15. A multi points ultrasonic detection method for material flow of belt conveyor

    Science.gov (United States)

    Zhang, Li; He, Rongjun

    2018-03-01

    For big detection error of single point ultrasonic ranging technology used in material flow detection of belt conveyor when coal distributes unevenly or is large, a material flow detection method of belt conveyor is designed based on multi points ultrasonic counter ranging technology. The method can calculate approximate sectional area of material by locating multi points on surfaces of material and belt, in order to get material flow according to running speed of belt conveyor. The test results show that the method has smaller detection error than single point ultrasonic ranging technology under the condition of big coal with uneven distribution.

  16. A new methodology for automatic detection of reference points in 3D cephalometry: A pilot study.

    Science.gov (United States)

    Ed-Dhahraouy, Mohammed; Riri, Hicham; Ezzahmouly, Manal; Bourzgui, Farid; El Moutaoukkil, Abdelmajid

    2018-04-05

    The aim of this study was to develop a new method for an automatic detection of reference points in 3D cephalometry to overcome the limits of 2D cephalometric analyses. A specific application was designed using the C++ language for automatic and manual identification of 21 (reference) points on the craniofacial structures. Our algorithm is based on the implementation of an anatomical and geometrical network adapted to the craniofacial structure. This network was constructed based on the anatomical knowledge of the 3D cephalometric (reference) points. The proposed algorithm was tested on five CBCT images. The proposed approach for the automatic 3D cephalometric identification was able to detect 21 points with a mean error of 2.32mm. In this pilot study, we propose an automated methodology for the identification of the 3D cephalometric (reference) points. A larger sample will be implemented in the future to assess the method validity and reliability. Copyright © 2018 CEO. Published by Elsevier Masson SAS. All rights reserved.

  17. Jump point detection for real estate investment success

    Science.gov (United States)

    Hui, Eddie C. M.; Yu, Carisa K. W.; Ip, Wai-Cheung

    2010-03-01

    In the literature, studies on real estate market were mainly concentrating on the relation between property price and some key factors. The trend of the real estate market is a major concern. It is believed that changes in trend are signified by some jump points in the property price series. Identifying such jump points reveals important findings that enable policy-makers to look forward. However, not all jump points are observable from the plot of the series. This paper looks into the trend and introduces a new approach to the framework for real estate investment success. The main purpose of this paper is to detect jump points in the time series of some housing price indices and stock price index in Hong Kong by applying the wavelet analysis. The detected jump points reflect to some significant political issues and economic collapse. Moreover, the relations among properties of different classes and between stocks and properties are examined. It can be shown from the empirical result that a lead-lag effect happened between the prices of large-size property and those of small/medium-size property. However, there is no apparent relation or consistent lead in terms of change point measure between property price and stock price. This may be due to the fact that globalization effect has more impact on the stock price than the property price.

  18. An angle-based subspace anomaly detection approach to high-dimensional data: With an application to industrial fault detection

    International Nuclear Information System (INIS)

    Zhang, Liangwei; Lin, Jing; Karim, Ramin

    2015-01-01

    The accuracy of traditional anomaly detection techniques implemented on full-dimensional spaces degrades significantly as dimensionality increases, thereby hampering many real-world applications. This work proposes an approach to selecting meaningful feature subspace and conducting anomaly detection in the corresponding subspace projection. The aim is to maintain the detection accuracy in high-dimensional circumstances. The suggested approach assesses the angle between all pairs of two lines for one specific anomaly candidate: the first line is connected by the relevant data point and the center of its adjacent points; the other line is one of the axis-parallel lines. Those dimensions which have a relatively small angle with the first line are then chosen to constitute the axis-parallel subspace for the candidate. Next, a normalized Mahalanobis distance is introduced to measure the local outlier-ness of an object in the subspace projection. To comprehensively compare the proposed algorithm with several existing anomaly detection techniques, we constructed artificial datasets with various high-dimensional settings and found the algorithm displayed superior accuracy. A further experiment on an industrial dataset demonstrated the applicability of the proposed algorithm in fault detection tasks and highlighted another of its merits, namely, to provide preliminary interpretation of abnormality through feature ordering in relevant subspaces. - Highlights: • An anomaly detection approach for high-dimensional reliability data is proposed. • The approach selects relevant subspaces by assessing vectorial angles. • The novel ABSAD approach displays superior accuracy over other alternatives. • Numerical illustration approves its efficacy in fault detection applications

  19. Laser desorption mass spectrometry for point mutation detection

    Energy Technology Data Exchange (ETDEWEB)

    Taranenko, N.I.; Chung, C.N.; Zhu, Y.F. [Oak Ridge National Lab., TN (United States)] [and others

    1996-10-01

    A point mutation can be associated with the pathogenesis of inherited or acquired diseases. Laser desorption mass spectrometry coupled with allele specific polymerase chain reaction (PCR) was first used for point mutation detection. G551D is one of several mutations of the cystic fibrosis transmembrane conductance regulator (CFTR) gene present in 1-3% of the mutant CFTR alleles in most European populations. In this work, two different approaches were pursued to detect G551D point mutation in the cystic fibrosis gene. The strategy is to amplify the desired region of DNA template by PCR using two primers that overlap one base at the site of the point mutation and which vary in size. If the two primers based on the normal sequence match the target DNA sequence, a normal PCR product will be produced. However, if the alternately sized primers that match the mutant sequence recognize the target DNA, an abnormal PCR product will be produced. Thus, the mass spectrometer can be used to identify patients that are homozygous normal, heterozygous for a mutation or homozygous abnormal at a mutation site. Another approach to identify similar mutations is the use of sequence specific restriction enzymes which respond to changes in the DNA sequence. Mass spectrometry is used to detect the length of the restriction fragments generated by digestion of a PCR generated target fragment. 21 refs., 10 figs., 2 tabs.

  20. A MARKED POINT PROCESS MODEL FOR VEHICLE DETECTION IN AERIAL LIDAR POINT CLOUDS

    Directory of Open Access Journals (Sweden)

    A. Börcs

    2012-07-01

    Full Text Available In this paper we present an automated method for vehicle detection in LiDAR point clouds of crowded urban areas collected from an aerial platform. We assume that the input cloud is unordered, but it contains additional intensity and return number information which are jointly exploited by the proposed solution. Firstly, the 3-D point set is segmented into ground, vehicle, building roof, vegetation and clutter classes. Then the points with the corresponding class labels and intensity values are projected to the ground plane, where the optimal vehicle configuration is described by a Marked Point Process (MPP model of 2-D rectangles. Finally, the Multiple Birth and Death algorithm is utilized to find the configuration with the highest confidence.

  1. Distribution majorization of corner points by reinforcement learning for moving object detection

    Science.gov (United States)

    Wu, Hao; Yu, Hao; Zhou, Dongxiang; Cheng, Yongqiang

    2018-04-01

    Corner points play an important role in moving object detection, especially in the case of free-moving camera. Corner points provide more accurate information than other pixels and reduce the computation which is unnecessary. Previous works only use intensity information to locate the corner points, however, the information that former and the last frames provided also can be used. We utilize the information to focus on more valuable area and ignore the invaluable area. The proposed algorithm is based on reinforcement learning, which regards the detection of corner points as a Markov process. In the Markov model, the video to be detected is regarded as environment, the selections of blocks for one corner point are regarded as actions and the performance of detection is regarded as state. Corner points are assigned to be the blocks which are seperated from original whole image. Experimentally, we select a conventional method which uses marching and Random Sample Consensus algorithm to obtain objects as the main framework and utilize our algorithm to improve the result. The comparison between the conventional method and the same one with our algorithm show that our algorithm reduce 70% of the false detection.

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

    Directory of Open Access Journals (Sweden)

    A. Schlichting

    2016-06-01

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

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

    Science.gov (United States)

    Schlichting, A.; Brenner, C.

    2016-06-01

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

  4. Error Mitigation of Point-to-Point Communication for Fault-Tolerant Computing

    Science.gov (United States)

    Akamine, Robert L.; Hodson, Robert F.; LaMeres, Brock J.; Ray, Robert E.

    2011-01-01

    Fault tolerant systems require the ability to detect and recover from physical damage caused by the hardware s environment, faulty connectors, and system degradation over time. This ability applies to military, space, and industrial computing applications. The integrity of Point-to-Point (P2P) communication, between two microcontrollers for example, is an essential part of fault tolerant computing systems. In this paper, different methods of fault detection and recovery are presented and analyzed.

  5. Accurate modeling and maximum power point detection of ...

    African Journals Online (AJOL)

    Accurate modeling and maximum power point detection of photovoltaic ... Determination of MPP enables the PV system to deliver maximum available power. ..... adaptive artificial neural network: Proposition for a new sizing procedure.

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

    DEFF Research Database (Denmark)

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

    2014-01-01

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

  7. History and Point in Time in Enterprise Applications

    Directory of Open Access Journals (Sweden)

    Constantin Gelu APOSTOL

    2006-01-01

    Full Text Available First part points out the main differences between temporal and non-temporal databases. In the second part, based on identification of the three main categories of time involved in database applications: user-defined time, valid time and transaction time, some relevant solutions for their implementation are discussed, mainly from the point of view of database organization and data access level of enterprise applications. The final part is dedicated to the influences of historical data in the business logic and presentation levels of enterprise applications and in application services, as security, workflow, reporting.

  8. When Dijkstra Meets Vanishing Point: A Stereo Vision Approach for Road Detection.

    Science.gov (United States)

    Zhang, Yigong; Su, Yingna; Yang, Jian; Ponce, Jean; Kong, Hui

    2018-05-01

    In this paper, we propose a vanishing-point constrained Dijkstra road model for road detection in a stereo-vision paradigm. First, the stereo-camera is used to generate the u- and v-disparity maps of road image, from which the horizon can be extracted. With the horizon and ground region constraints, we can robustly locate the vanishing point of road region. Second, a weighted graph is constructed using all pixels of the image, and the detected vanishing point is treated as the source node of the graph. By computing a vanishing-point constrained Dijkstra minimum-cost map, where both disparity and gradient of gray image are used to calculate cost between two neighbor pixels, the problem of detecting road borders in image is transformed into that of finding two shortest paths that originate from the vanishing point to two pixels in the last row of image. The proposed approach has been implemented and tested over 2600 grayscale images of different road scenes in the KITTI data set. The experimental results demonstrate that this training-free approach can detect horizon, vanishing point, and road regions very accurately and robustly. It can achieve promising performance.

  9. Detection of BCG bacteria using a magnetoresistive biosensor: A step towards a fully electronic platform for tuberculosis point-of-care detection.

    Science.gov (United States)

    Barroso, Teresa G; Martins, Rui C; Fernandes, Elisabete; Cardoso, Susana; Rivas, José; Freitas, Paulo P

    2018-02-15

    Tuberculosis is one of the major public health concerns. This highly contagious disease affects more than 10.4 million people, being a leading cause of morbidity by infection. Tuberculosis is diagnosed at the point-of-care by the Ziehl-Neelsen sputum smear microscopy test. Ziehl-Neelsen is laborious, prone to human error and infection risk, with a limit of detection of 10 4 cells/mL. In resource-poor nations, a more practical test, with lower detection limit, is paramount. This work uses a magnetoresistive biosensor to detect BCG bacteria for tuberculosis diagnosis. Herein we report: i) nanoparticle assembly method and specificity for tuberculosis detection; ii) demonstration of proportionality between BCG cell concentration and magnetoresistive voltage signal; iii) application of multiplicative signal correction for systematic effects removal; iv) investigation of calibration effectiveness using chemometrics methods; and v) comparison with state-of-the-art point-of-care tuberculosis biosensors. Results present a clear correspondence between voltage signal and cell concentration. Multiplicative signal correction removes baseline shifts within and between biochip sensors, allowing accurate and precise voltage signal between different biochips. The corrected signal was used for multivariate regression models, which significantly decreased the calibration standard error from 0.50 to 0.03log 10 (cells/mL). Results show that Ziehl-Neelsen detection limits and below are achievable with the magnetoresistive biochip, when pre-processing and chemometrics are used. Copyright © 2017 Elsevier B.V. All rights reserved.

  10. Flexible low-cost cardiovascular risk marker biosensor for point-of-care applications

    KAUST Repository

    Sivashankar, Shilpa

    2015-10-22

    The detection and quantification of protein on a laser written flexible substrate for point-of-care applications are described. A unique way of etching gold on polyethylene terephthalate (PET) substrate is demonstrated by reducing the damage that may be caused on PET sheets otherwise. On the basis of the quantity of the C-reactive protein (CRP) present in the sample, the risk of cardiac disease can be assessed. This hsCRP test is incorporated to detect the presence of CRP on a PET laser patterned biosensor. Concentrations of 1, 2, and 10 mg/l were chosen to assess the risk of cardiac diseases as per the limits set by the American Heart Association.

  11. Automatic Detection and Positioning of Ground Control Points Using TerraSAR-X Multiaspect Acquisitions

    Science.gov (United States)

    Montazeri, Sina; Gisinger, Christoph; Eineder, Michael; Zhu, Xiao xiang

    2018-05-01

    Geodetic stereo Synthetic Aperture Radar (SAR) is capable of absolute three-dimensional localization of natural Persistent Scatterer (PS)s which allows for Ground Control Point (GCP) generation using only SAR data. The prerequisite for the method to achieve high precision results is the correct detection of common scatterers in SAR images acquired from different viewing geometries. In this contribution, we describe three strategies for automatic detection of identical targets in SAR images of urban areas taken from different orbit tracks. Moreover, a complete work-flow for automatic generation of large number of GCPs using SAR data is presented and its applicability is shown by exploiting TerraSAR-X (TS-X) high resolution spotlight images over the city of Oulu, Finland and a test site in Berlin, Germany.

  12. Application of change-point problem to the detection of plant patches.

    Science.gov (United States)

    López, I; Gámez, M; Garay, J; Standovár, T; Varga, Z

    2010-03-01

    In ecology, if the considered area or space is large, the spatial distribution of individuals of a given plant species is never homogeneous; plants form different patches. The homogeneity change in space or in time (in particular, the related change-point problem) is an important research subject in mathematical statistics. In the paper, for a given data system along a straight line, two areas are considered, where the data of each area come from different discrete distributions, with unknown parameters. In the paper a method is presented for the estimation of the distribution change-point between both areas and an estimate is given for the distributions separated by the obtained change-point. The solution of this problem will be based on the maximum likelihood method. Furthermore, based on an adaptation of the well-known bootstrap resampling, a method for the estimation of the so-called change-interval is also given. The latter approach is very general, since it not only applies in the case of the maximum-likelihood estimation of the change-point, but it can be also used starting from any other change-point estimation known in the ecological literature. The proposed model is validated against typical ecological situations, providing at the same time a verification of the applied algorithms.

  13. Detecting quantum critical points using bipartite fluctuations.

    Science.gov (United States)

    Rachel, Stephan; Laflorencie, Nicolas; Song, H Francis; Le Hur, Karyn

    2012-03-16

    We show that the concept of bipartite fluctuations F provides a very efficient tool to detect quantum phase transitions in strongly correlated systems. Using state-of-the-art numerical techniques complemented with analytical arguments, we investigate paradigmatic examples for both quantum spins and bosons. As compared to the von Neumann entanglement entropy, we observe that F allows us to find quantum critical points with much better accuracy in one dimension. We further demonstrate that F can be successfully applied to the detection of quantum criticality in higher dimensions with no prior knowledge of the universality class of the transition. Promising approaches to experimentally access fluctuations are discussed for quantum antiferromagnets and cold gases.

  14. Method and apparatus for continuously detecting and monitoring the hydrocarbon dew-point of gas

    Energy Technology Data Exchange (ETDEWEB)

    Boyle, G.J.; Pritchard, F.R.

    1987-08-04

    This patent describes a method and apparatus for continuously detecting and monitoring the hydrocarbon dew-point of a gas. A gas sample is supplied to a dew-point detector and the temperature of a portion of the sample gas stream to be investigated is lowered progressively prior to detection until the dew-point is reached. The presence of condensate within the flowing gas is detected and subsequently the supply gas sample is heated to above the dew-point. The procedure of cooling and heating the gas stream continuously in a cyclical manner is repeated.

  15. Label-free detection of DNA hybridization and single point mutations in a nano-gap biosensor

    International Nuclear Information System (INIS)

    Zaffino, R L; Mir, M; Samitier, J

    2014-01-01

    We describe a conductance-based biosensor that exploits DNA-mediated long-range electron transport for the label-free and direct electrical detection of DNA hybridization. This biosensor platform comprises an array of vertical nano-gap biosensors made of gold and fabricated through standard photolithography combined with focused ion beam lithography. The nano-gap walls are covalently modified with short, anti-symmetric thiolated DNA probes, which are terminated by 19 bases complementary to both the ends of a target DNA strand. The nano-gaps are separated by a distance of 50nm, which was adjusted to fit the length of the DNA target plus the DNA probes. The hybridization of the target DNA closes the gap circuit in a switch on/off fashion, in such a way that it is readily detected by an increase in the current after nano-gap closure. The nano-biosensor shows high specificity in the discrimination of base-pair mismatching and does not require signal indicators or enhancing molecules. The design of the biosensor platform is applicable for multiplexed detection in a straightforward manner. The platform is well-suited to mass production, point-of-care diagnostics, and wide-scale DNA analysis applications. (paper)

  16. Exploring Permission-Induced Risk in Android Applications for Malicious Application Detection

    KAUST Repository

    Wang, Wei

    2014-10-07

    Android has been a major target of malicious applications (malapps). How to detect and keep the malapps out of the app markets is an ongoing challenge. One of the central design points of Android security mechanism is permission control that restricts the access of apps to core facilities of devices. However, it imparts a significant responsibility to the app developers with regard to accurately specifying the requested permissions and to the users with regard to fully understanding the risk of granting certain combinations of permissions. Android permissions requested by an app depict the app\\'s behavioral patterns. In order to help understanding Android permissions, in this paper, we explore the permission-induced risk in Android apps on three levels in a systematic manner. First, we thoroughly analyze the risk of an individual permission and the risk of a group of collaborative permissions. We employ three feature ranking methods, namely, mutual information, correlation coefficient, and T-test to rank Android individual permissions with respect to their risk. We then use sequential forward selection as well as principal component analysis to identify risky permission subsets. Second, we evaluate the usefulness of risky permissions for malapp detection with support vector machine, decision trees, as well as random forest. Third, we in depth analyze the detection results and discuss the feasibility as well as the limitations of malapp detection based on permission requests. We evaluate our methods on a very large official app set consisting of 310 926 benign apps and 4868 real-world malapps and on a third-party app sets. The empirical results show that our malapp detectors built on risky permissions give satisfied performance (a detection rate as 94.62% with a false positive rate as 0.6%), catch the malapps\\' essential patterns on violating permission access regulations, and are universally applicable to unknown malapps (detection rate as 74.03%).

  17. Application of fluorescence spectroscopy and imaging in the detection of a photosensitizer in photodynamic therapy

    Science.gov (United States)

    Zang, Lixin; Zhao, Huimin; Zhang, Zhiguo; Cao, Wenwu

    2017-02-01

    Photodynamic therapy (PDT) is currently an advanced optical technology in medical applications. However, the application of PDT is limited by the detection of photosensitizers. This work focuses on the application of fluorescence spectroscopy and imaging in the detection of an effective photosenzitizer, hematoporphyrin monomethyl ether (HMME). Optical properties of HMME were measured and analyzed based on its absorption and fluorescence spectra. The production mechanism of its fluorescence emission was analyzed. The detection device for HMME based on fluorescence spectroscopy was designed. Ratiometric method was applied to eliminate the influence of intensity change of excitation sources, fluctuates of excitation sources and photo detectors, and background emissions. The detection limit of this device is 6 μg/L, and it was successfully applied to the diagnosis of the metabolism of HMME in the esophageal cancer cells. To overcome the limitation of the point measurement using fluorescence spectroscopy, a two-dimensional (2D) fluorescence imaging system was established. The algorithm of the 2D fluorescence imaging system is deduced according to the fluorescence ratiometric method using bandpass filters. The method of multiple pixel point addition (MPPA) was used to eliminate fluctuates of signals. Using the method of MPPA, SNR was improved by about 30 times. The detection limit of this imaging system is 1.9 μg/L. Our systems can be used in the detection of porphyrins to improve the PDT effect.

  18. Detection of Point Sources on Two-Dimensional Images Based on Peaks

    Directory of Open Access Journals (Sweden)

    R. B. Barreiro

    2005-09-01

    Full Text Available This paper considers the detection of point sources in two-dimensional astronomical images. The detection scheme we propose is based on peak statistics. We discuss the example of the detection of far galaxies in cosmic microwave background experiments throughout the paper, although the method we present is totally general and can be used in many other fields of data analysis. We consider sources with a Gaussian profile—that is, a fair approximation of the profile of a point source convolved with the detector beam in microwave experiments—on a background modeled by a homogeneous and isotropic Gaussian random field characterized by a scale-free power spectrum. Point sources are enhanced with respect to the background by means of linear filters. After filtering, we identify local maxima and apply our detection scheme, a Neyman-Pearson detector that defines our region of acceptance based on the a priori pdf of the sources and the ratio of number densities. We study the different performances of some linear filters that have been used in this context in the literature: the Mexican hat wavelet, the matched filter, and the scale-adaptive filter. We consider as well an extension to two dimensions of the biparametric scale-adaptive filter (BSAF. The BSAF depends on two parameters which are determined by maximizing the number density of real detections while fixing the number density of spurious detections. For our detection criterion the BSAF outperforms the other filters in the interesting case of white noise.

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

    KAUST Repository

    Meng, Rui

    2016-05-15

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

  20. Fault Detection and Diagnosis of Railway Point Machines by Sound Analysis

    Science.gov (United States)

    Lee, Jonguk; Choi, Heesu; Park, Daihee; Chung, Yongwha; Kim, Hee-Young; Yoon, Sukhan

    2016-01-01

    Railway point devices act as actuators that provide different routes to trains by driving switchblades from the current position to the opposite one. Point failure can significantly affect railway operations, with potentially disastrous consequences. Therefore, early detection of anomalies is critical for monitoring and managing the condition of rail infrastructure. We present a data mining solution that utilizes audio data to efficiently detect and diagnose faults in railway condition monitoring systems. The system enables extracting mel-frequency cepstrum coefficients (MFCCs) from audio data with reduced feature dimensions using attribute subset selection, and employs support vector machines (SVMs) for early detection and classification of anomalies. Experimental results show that the system enables cost-effective detection and diagnosis of faults using a cheap microphone, with accuracy exceeding 94.1% whether used alone or in combination with other known methods. PMID:27092509

  1. About Applications of the Fixed Point Theory

    Directory of Open Access Journals (Sweden)

    Bucur Amelia

    2017-06-01

    Full Text Available The fixed point theory is essential to various theoretical and applied fields, such as variational and linear inequalities, the approximation theory, nonlinear analysis, integral and differential equations and inclusions, the dynamic systems theory, mathematics of fractals, mathematical economics (game theory, equilibrium problems, and optimisation problems and mathematical modelling. This paper presents a few benchmarks regarding the applications of the fixed point theory. This paper also debates if the results of the fixed point theory can be applied to the mathematical modelling of quality.

  2. A micro dew point sensor with a thermal detection principle

    Science.gov (United States)

    Kunze, M.; Merz, J.; Hummel, W.-J.; Glosch, H.; Messner, S.; Zengerle, R.

    2012-01-01

    We present a dew point temperature sensor with the thermal detection of condensed water on a thin membrane, fabricated by silicon micromachining. The membrane (600 × 600 × ~1 µm3) is part of a silicon chip and contains a heating element as well as a thermopile for temperature measurement. By dynamically heating the membrane and simultaneously analyzing the transient increase of its temperature it is detected whether condensed water is on the membrane or not. To cool the membrane down, a peltier cooler is used and electronically controlled in a way that the temperature of the membrane is constantly held at a value where condensation of water begins. This temperature is measured and output as dew point temperature. The sensor system works in a wide range of dew point temperatures between 1 K and down to 44 K below air temperature. In experimental investigations it could be proven that the deviation of the measured dew point temperatures compared to reference values is below ±0.2 K in an air temperature range of 22 to 70 °C. At low dew point temperatures of -20 °C (air temperature = 22 °C) the deviation increases to nearly -1 K.

  3. A micro dew point sensor with a thermal detection principle

    International Nuclear Information System (INIS)

    Kunze, M; Merz, J; Glosch, H; Messner, S; Zengerle, R; Hummel, W-J

    2012-01-01

    We present a dew point temperature sensor with the thermal detection of condensed water on a thin membrane, fabricated by silicon micromachining. The membrane (600 × 600 × ∼1 µm 3 ) is part of a silicon chip and contains a heating element as well as a thermopile for temperature measurement. By dynamically heating the membrane and simultaneously analyzing the transient increase of its temperature it is detected whether condensed water is on the membrane or not. To cool the membrane down, a peltier cooler is used and electronically controlled in a way that the temperature of the membrane is constantly held at a value where condensation of water begins. This temperature is measured and output as dew point temperature. The sensor system works in a wide range of dew point temperatures between 1 K and down to 44 K below air temperature. In experimental investigations it could be proven that the deviation of the measured dew point temperatures compared to reference values is below ±0.2 K in an air temperature range of 22 to 70 °C. At low dew point temperatures of −20 °C (air temperature = 22 °C) the deviation increases to nearly −1 K

  4. Automatic 3D Building Detection and Modeling from Airborne LiDAR Point Clouds

    Science.gov (United States)

    Sun, Shaohui

    Urban reconstruction, with an emphasis on man-made structure modeling, is an active research area with broad impact on several potential applications. Urban reconstruction combines photogrammetry, remote sensing, computer vision, and computer graphics. Even though there is a huge volume of work that has been done, many problems still remain unsolved. Automation is one of the key focus areas in this research. In this work, a fast, completely automated method to create 3D watertight building models from airborne LiDAR (Light Detection and Ranging) point clouds is presented. The developed method analyzes the scene content and produces multi-layer rooftops, with complex rigorous boundaries and vertical walls, that connect rooftops to the ground. The graph cuts algorithm is used to separate vegetative elements from the rest of the scene content, which is based on the local analysis about the properties of the local implicit surface patch. The ground terrain and building rooftop footprints are then extracted, utilizing the developed strategy, a two-step hierarchical Euclidean clustering. The method presented here adopts a "divide-and-conquer" scheme. Once the building footprints are segmented from the terrain and vegetative areas, the whole scene is divided into individual pendent processing units which represent potential points on the rooftop. For each individual building region, significant features on the rooftop are further detected using a specifically designed region-growing algorithm with surface smoothness constraints. The principal orientation of each building rooftop feature is calculated using a minimum bounding box fitting technique, and is used to guide the refinement of shapes and boundaries of the rooftop parts. Boundaries for all of these features are refined for the purpose of producing strict description. Once the description of the rooftops is achieved, polygonal mesh models are generated by creating surface patches with outlines defined by detected

  5. Sequential Change-Point Detection via Online Convex Optimization

    Directory of Open Access Journals (Sweden)

    Yang Cao

    2018-02-01

    Full Text Available Sequential change-point detection when the distribution parameters are unknown is a fundamental problem in statistics and machine learning. When the post-change parameters are unknown, we consider a set of detection procedures based on sequential likelihood ratios with non-anticipating estimators constructed using online convex optimization algorithms such as online mirror descent, which provides a more versatile approach to tackling complex situations where recursive maximum likelihood estimators cannot be found. When the underlying distributions belong to a exponential family and the estimators satisfy the logarithm regret property, we show that this approach is nearly second-order asymptotically optimal. This means that the upper bound for the false alarm rate of the algorithm (measured by the average-run-length meets the lower bound asymptotically up to a log-log factor when the threshold tends to infinity. Our proof is achieved by making a connection between sequential change-point and online convex optimization and leveraging the logarithmic regret bound property of online mirror descent algorithm. Numerical and real data examples validate our theory.

  6. Point Count Length and Detection of Forest Neotropical Migrant Birds

    Science.gov (United States)

    Deanna K. Dawson; David R. Smith; Chandler S. Robbins

    1995-01-01

    Comparisons of bird abundances among years or among habitats assume that the rates at which birds are detected and counted are constant within species. We use point count data collected in forests of the Mid-Atlantic states to estimate detection probabilities for Neotropical migrant bird species as a function of count length. For some species, significant differences...

  7. Detection of Dew-Point by substantial Raman Band Frequency Jumps (A new Method)

    DEFF Research Database (Denmark)

    Hansen, Susanne Brunsgaard; Berg, Rolf W.; Stenby, Erling Halfdan

    Detection of Dew-Point by substantial Raman Band Frequency Jumps (A new Method). See poster at http://www.kemi.dtu.dk/~ajo/rolf/jumps.pdf......Detection of Dew-Point by substantial Raman Band Frequency Jumps (A new Method). See poster at http://www.kemi.dtu.dk/~ajo/rolf/jumps.pdf...

  8. Advanced DNA-Based Point-of-Care Diagnostic Methods for Plant Diseases Detection

    OpenAIRE

    Lau, Han Yih; Botella, Jose R.

    2017-01-01

    Diagnostic technologies for the detection of plant pathogens with point-of-care capability and high multiplexing ability are an essential tool in the fight to reduce the large agricultural production losses caused by plant diseases. The main desirable characteristics for such diagnostic assays are high specificity, sensitivity, reproducibility, quickness, cost efficiency and high-throughput multiplex detection capability. This article describes and discusses various DNA-based point-of care di...

  9. Sensitive detection of point mutation by electrochemiluminescence and DNA ligase-based assay

    Science.gov (United States)

    Zhou, Huijuan; Wu, Baoyan

    2008-12-01

    The technology of single-base mutation detection plays an increasingly important role in diagnosis and prognosis of genetic-based diseases. Here we reported a new method for the analysis of point mutations in genomic DNA through the integration of allele-specific oligonucleotide ligation assay (OLA) with magnetic beads-based electrochemiluminescence (ECL) detection scheme. In this assay the tris(bipyridine) ruthenium (TBR) labeled probe and the biotinylated probe are designed to perfectly complementary to the mutant target, thus a ligation can be generated between those two probes by Taq DNA Ligase in the presence of mutant target. If there is an allele mismatch, the ligation does not take place. The ligation products are then captured onto streptavidin-coated paramagnetic beads, and detected by measuring the ECL signal of the TBR label. Results showed that the new method held a low detection limit down to 10 fmol and was successfully applied in the identification of point mutations from ASTC-α-1, PANC-1 and normal cell lines in codon 273 of TP53 oncogene. In summary, this method provides a sensitive, cost-effective and easy operation approach for point mutation detection.

  10. Applications of multiscale change point detections to monthly stream flow and rainfall in Xijiang River in southern China, part I: correlation and variance

    Science.gov (United States)

    Zhu, Yuxiang; Jiang, Jianmin; Huang, Changxing; Chen, Yongqin David; Zhang, Qiang

    2018-04-01

    This article, as part I, introduces three algorithms and applies them to both series of the monthly stream flow and rainfall in Xijiang River, southern China. The three algorithms include (1) normalization of probability distribution, (2) scanning U test for change points in correlation between two time series, and (3) scanning F-test for change points in variances. The normalization algorithm adopts the quantile method to normalize data from a non-normal into the normal probability distribution. The scanning U test and F-test have three common features: grafting the classical statistics onto the wavelet algorithm, adding corrections for independence into each statistic criteria at given confidence respectively, and being almost objective and automatic detection on multiscale time scales. In addition, the coherency analyses between two series are also carried out for changes in variance. The application results show that the changes of the monthly discharge are still controlled by natural precipitation variations in Xijiang's fluvial system. Human activities disturbed the ecological balance perhaps in certain content and in shorter spells but did not violate the natural relationships of correlation and variance changes so far.

  11. Vanishing points detection using combination of fast Hough transform and deep learning

    Science.gov (United States)

    Sheshkus, Alexander; Ingacheva, Anastasia; Nikolaev, Dmitry

    2018-04-01

    In this paper we propose a novel method for vanishing points detection based on convolutional neural network (CNN) approach and fast Hough transform algorithm. We show how to determine fast Hough transform neural network layer and how to use it in order to increase usability of the neural network approach to the vanishing point detection task. Our algorithm includes CNN with consequence of convolutional and fast Hough transform layers. We are building estimator for distribution of possible vanishing points in the image. This distribution can be used to find candidates of vanishing point. We provide experimental results from tests of suggested method using images collected from videos of road trips. Our approach shows stable result on test images with different projective distortions and noise. Described approach can be effectively implemented for mobile GPU and CPU.

  12. Fragmentation Point Detection of JPEG Images at DHT Using Validator

    Science.gov (United States)

    Mohamad, Kamaruddin Malik; Deris, Mustafa Mat

    File carving is an important, practical technique for data recovery in digital forensics investigation and is particularly useful when filesystem metadata is unavailable or damaged. The research on reassembly of JPEG files with RST markers, fragmented within the scan area have been done before. However, fragmentation within Define Huffman Table (DHT) segment is yet to be resolved. This paper analyzes the fragmentation within the DHT area and list out all the fragmentation possibilities. Two main contributions are made in this paper. Firstly, three fragmentation points within DHT area are listed. Secondly, few novel validators are proposed to detect these fragmentations. The result obtained from tests done on manually fragmented JPEG files, showed that all three fragmentation points within DHT are successfully detected using validators.

  13. Research on point source simulating the γ-ray detection efficiencies of stander source

    International Nuclear Information System (INIS)

    Tian Zining; Jia Mingyan; Shen Maoquan; Yang Xiaoyan; Cheng Zhiwei

    2010-01-01

    For φ 75 mm x 25 mm sample, the full energy peak efficiencies on different heights of sample radius were obtained using the point sources, and the function parameters about the full energy peak efficiencies of point sources based on radius was fixed. The 59.54 keV γ-ray, 661.66 keV γ-ray, 1173.2 keV γ-ray, 1332.5 keV γ-ray detection efficiencies on different height of samples were obtained, based on the full energy peak efficiencies of point sources and its height, and the function parameters about the full energy peak efficiencies of surface sources based on sample height was fixed. The detection efficiency of (75 mm x 25 mm calibration source can be obtained by integrality, the detection efficiencies simulated by point sources are consistent with the results of stander source in 10%. Therefore, the calibration method of stander source can be substituted by the point source simulation method, and it tis feasible when there is no stander source.) (authors)

  14. International Conference on Fixed Point Theory and Applications (Colloque International Theorie Du Point Fixe et Applications)

    Science.gov (United States)

    1989-06-09

    could be used to establish a conjectured minimax for a search game of Baston and Bostock [2]. An application of Theorem 1 is to the problem of getting...Alpern S., Search for point in interval, with high-low feedback, Math. Proc., Cambridge Phil. Soc. 98, (1985), 569-578. [2] Baston V. J. and Bostock F. A

  15. CMOS image sensor for detection of interferon gamma protein interaction as a point-of-care approach.

    Science.gov (United States)

    Marimuthu, Mohana; Kandasamy, Karthikeyan; Ahn, Chang Geun; Sung, Gun Yong; Kim, Min-Gon; Kim, Sanghyo

    2011-09-01

    Complementary metal oxide semiconductor (CMOS)-based image sensors have received increased attention owing to the possibility of incorporating them into portable diagnostic devices. The present research examined the efficiency and sensitivity of a CMOS image sensor for the detection of antigen-antibody interactions involving interferon gamma protein without the aid of expensive instruments. The highest detection sensitivity of about 1 fg/ml primary antibody was achieved simply by a transmission mechanism. When photons are prevented from hitting the sensor surface, a reduction in digital output occurs in which the number of photons hitting the sensor surface is approximately proportional to the digital number. Nanoscale variation in substrate thickness after protein binding can be detected with high sensitivity by the CMOS image sensor. Therefore, this technique can be easily applied to smartphones or any clinical diagnostic devices for the detection of several biological entities, with high impact on the development of point-of-care applications.

  16. LASER POINTER DETECTION BASED ON INTENSITY PROFILE ANALYSIS FOR APPLICATION IN TELECONSULTATION

    Directory of Open Access Journals (Sweden)

    NAIREEN IMTIAZ

    2017-08-01

    Full Text Available Telemedicine is application of electronic communication to deliver medical care remotely. An important aspect of telemedicine is teleconsultation which involves obtaining the professional opinion of a healthcare provider. One of the ways to improve eleconsultation is to equip the remote specialist via control of a laser pointer, located in the consultation area to provide a means of gesture. As such, accurate detection of laser spot is crucial in such systems as they rely on visual feedback, which enables the specialist in a remote site to control and point the laser in the active location using a standard mouse. The main issue in laser spot detection in a natural environment is the distinguishability of a laser point image from other bright regions and glare due to camera saturation. This problem remains unsolved without extensive computing and use of hardware filters. In this paper a hybrid algorithm is described which is aimed to work with natural indoor environment while limiting computation. This algorithm combines thresholding and blob evaluation methods with a novel image intensity profile comparison method based on linear regression. A comparison of the algorithm has been done with existing approaches. The developed algorithm shows a higher accuracy and faster execution time making it an ideal candidate for real time detection applications.

  17. Learning search-driven application development with SharePoint 2013

    CERN Document Server

    Tordgeman, Johnny

    2013-01-01

    A fast paced, practical guide, filled with code examples and demonstrations of enterprise search using SharePoint 2013.This book is written for SharePoint and JavaScript developers who want to get started with SharePoint search and create search-driven applications. The book assumes working knowledge with previous versions of SharePoint and some experience with JavaScript and client side development

  18. Dim point target detection against bright background

    Science.gov (United States)

    Zhang, Yao; Zhang, Qiheng; Xu, Zhiyong; Xu, Junping

    2010-05-01

    For target detection within a large-field cluttered background from a long distance, several difficulties, involving low contrast between target and background, little occupancy, illumination ununiformity caused by vignetting of lens, and system noise, make it a challenging problem. The existing approaches to dim target detection can be roughly divided into two categories: detection before tracking (DBT) and tracking before detection (TBD). The DBT-based scheme has been widely used in practical applications due to its simplicity, but it often requires working in the situation with a higher signal-to-noise ratio (SNR). In contrast, the TBD-based methods can provide impressive detection results even in the cases of very low SNR; unfortunately, the large memory requirement and high computational load prevents these methods from real-time tasks. In this paper, we propose a new method for dim target detection. We address this problem by combining the advantages of the DBT-based scheme in computational efficiency and of the TBD-based in detection capability. Our method first predicts the local background, and then employs the energy accumulation and median filter to remove background clutter. The dim target is finally located by double window filtering together with an improved high order correlation which speeds up the convergence. The proposed method is implemented on a hardware platform and performs suitably in outside experiments.

  19. A voting-based statistical cylinder detection framework applied to fallen tree mapping in terrestrial laser scanning point clouds

    Science.gov (United States)

    Polewski, Przemyslaw; Yao, Wei; Heurich, Marco; Krzystek, Peter; Stilla, Uwe

    2017-07-01

    This paper introduces a statistical framework for detecting cylindrical shapes in dense point clouds. We target the application of mapping fallen trees in datasets obtained through terrestrial laser scanning. This is a challenging task due to the presence of ground vegetation, standing trees, DTM artifacts, as well as the fragmentation of dead trees into non-collinear segments. Our method shares the concept of voting in parameter space with the generalized Hough transform, however two of its significant drawbacks are improved upon. First, the need to generate samples on the shape's surface is eliminated. Instead, pairs of nearby input points lying on the surface cast a vote for the cylinder's parameters based on the intrinsic geometric properties of cylindrical shapes. Second, no discretization of the parameter space is required: the voting is carried out in continuous space by means of constructing a kernel density estimator and obtaining its local maxima, using automatic, data-driven kernel bandwidth selection. Furthermore, we show how the detected cylindrical primitives can be efficiently merged to obtain object-level (entire tree) semantic information using graph-cut segmentation and a tailored dynamic algorithm for eliminating cylinder redundancy. Experiments were performed on 3 plots from the Bavarian Forest National Park, with ground truth obtained through visual inspection of the point clouds. It was found that relative to sample consensus (SAC) cylinder fitting, the proposed voting framework can improve the detection completeness by up to 10 percentage points while maintaining the correctness rate.

  20. Poisson point processes imaging, tracking, and sensing

    CERN Document Server

    Streit, Roy L

    2010-01-01

    This overview of non-homogeneous and multidimensional Poisson point processes and their applications features mathematical tools and applications from emission- and transmission-computed tomography to multiple target tracking and distributed sensor detection.

  1. Radioisotope tracer instrument and its application to the detection of the groundwater parameters

    International Nuclear Information System (INIS)

    Chen Jiansheng

    1988-01-01

    The application of radioisotope tracer technique and probe can result in the detection of groundwater flow direction, flow velocity and vertical currents in one single well. The tracer probe consists of the source injector and the components related with direction detection, location and velocity measurement. The nuclear detector employs a thermoluminescence detector (TLD) and a direct reading ionization chamber (IC) for the detection of flow direction and also employs a new method of photofluorography location for the determination of the probe's northern or southern position in the well, thereby greatly simplifying the design of the direction-detecting probe. The velocity measuring section includes ground receiving instruments and meters for conducting point or whole-borehole measurement. It is also possible to carry out interconnection tests and dispersion tests. With the applications to the ascertaining of the groundwater distribution in the karst region as well as the execution of the dispersion tests related with environmental protection and so on, it has been confirmed that the radioisotope tracer instrument has a broad scope of application and practicability. (author). 5 refs, 6 figs

  2. Laser-induced fluorescence detection platform for point-of-care testing

    Science.gov (United States)

    Berner, Marcel; Hilbig, Urs; Schubert, Markus B.; Gauglitz, Günter

    2017-08-01

    Point-of-care testing (POCT) devices for continuous low-cost monitoring of critical patient parameters require miniaturized and integrated setups for performing quick high-sensitivity analyses, away from central clinical laboratories. This work presents a novel and promising laser-induced fluorescence platform for measurements in direct optical test formats that leads towards such powerful POCT devices based on fluorescence-labeled immunoassays. Ultimate sensitivity of thin film photodetectors, integrated with microfluidics, and a comprehensive optimization of all system components aim at low-level signal detection in the targeted biosensor application. The setup acquires fluorescence signals from the volume of a microfluidic channel. An innovative sandwiching process forms a flow channel in the microfluidic chips by embedding laser-cut double-sided adhesive tapes. The custom fit of amorphous silicon based photodiode arrays to the geometry of the flow channel enables miniaturization, fully adequate for POCT devices. A free-beam laser excitation with line focus provides excellent alignment stability, allows for easy and reliable swapping of the disposable microfluidic chips, and therewith greatly improves the ease of use of the resulting integrated device. As a proof-of-concept of this novel in-volume measurement approach, the limit of detection for the dye DY636-COOH in pure water as a model fluorophore is examined and found to be 26 nmol l-1 .

  3. Evaluation of point-of-care tests for detecting microalbuminuria in ...

    African Journals Online (AJOL)

    Evaluation of point-of-care tests for detecting microalbuminuria in diabetic patients. ... creatinine (modified Jaffe) and albumin-to-creatinine ratio (ACR). Results: Linear regression analysis demonstrated a good correlation for the HemoCue® ...

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

    Science.gov (United States)

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

    2017-06-01

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

  5. Automatic markerless registration of point clouds with semantic-keypoint-based 4-points congruent sets

    Science.gov (United States)

    Ge, Xuming

    2017-08-01

    The coarse registration of point clouds from urban building scenes has become a key topic in applications of terrestrial laser scanning technology. Sampling-based algorithms in the random sample consensus (RANSAC) model have emerged as mainstream solutions to address coarse registration problems. In this paper, we propose a novel combined solution to automatically align two markerless point clouds from building scenes. Firstly, the method segments non-ground points from ground points. Secondly, the proposed method detects feature points from each cross section and then obtains semantic keypoints by connecting feature points with specific rules. Finally, the detected semantic keypoints from two point clouds act as inputs to a modified 4PCS algorithm. Examples are presented and the results compared with those of K-4PCS to demonstrate the main contributions of the proposed method, which are the extension of the original 4PCS to handle heavy datasets and the use of semantic keypoints to improve K-4PCS in relation to registration accuracy and computational efficiency.

  6. Evaluation of null-point detection methods on simulation data

    Science.gov (United States)

    Olshevsky, Vyacheslav; Fu, Huishan; Vaivads, Andris; Khotyaintsev, Yuri; Lapenta, Giovanni; Markidis, Stefano

    2014-05-01

    We model the measurements of artificial spacecraft that resemble the configuration of CLUSTER propagating in the particle-in-cell simulation of turbulent magnetic reconnection. The simulation domain contains multiple isolated X-type null-points, but the majority are O-type null-points. Simulations show that current pinches surrounded by twisted fields, analogous to laboratory pinches, are formed along the sequences of O-type nulls. In the simulation, the magnetic reconnection is mainly driven by the kinking of the pinches, at spatial scales of several ion inertial lentghs. We compute the locations of magnetic null-points and detect their type. When the satellites are separated by the fractions of ion inertial length, as it is for CLUSTER, they are able to locate both the isolated null-points, and the pinches. We apply the method to the real CLUSTER data and speculate how common are pinches in the magnetosphere, and whether they play a dominant role in the dissipation of magnetic energy.

  7. Fixed Points in Grassmannians with Applications to Economic Equilibrium

    DEFF Research Database (Denmark)

    Keiding, Hans

    2017-01-01

    In some applications of equilibrium theory, the fixed point involves not only a state and a value of a parameter in the dual of the state space, but also a particular subspace of the state space. Since the set of all subspaces of a finite-dimensional Euclidean space has a structure which does...... not allow immediate application of fixed point theorems, the problem must be reformulated using a suitable parametrization of subspaces. One such parametrization, the Plücker coordinates, is used here to prove a general equilibrium existence theorem. Applications to economic problems involving hierarchies...... of consumers or incomplete markets with real assets are outlined....

  8. Non-uniqueness of the point of application of the buoyancy force

    International Nuclear Information System (INIS)

    Kliava, Janis; Megel, Jacques

    2010-01-01

    Even though the buoyancy force (also known as the Archimedes force) has always been an important topic of academic studies in physics, its point of application has not been explicitly identified yet. We present a quantitative approach to this problem based on the concept of the hydrostatic energy, considered here for a general shape of the cross-section of a floating body and for an arbitrary angle of heel. We show that the location of the point of application of the buoyancy force essentially depends (i) on the type of motion experienced by the floating body and (ii) on the definition of this point. In a rolling/pitching motion, considerations involving the rotational moment lead to a particular dynamical point of application of the buoyancy force, and for some simple shapes of the floating body this point coincides with the well-known metacentre. On the other hand, from the work-energy relation it follows that in the rolling/pitching motion the energetical point of application of this force is rigidly connected to the centre of buoyancy; in contrast, in a vertical translation this point is rigidly connected to the centre of gravity of the body. Finally, we consider the location of the characteristic points of the floating bodies for some particular shapes of immersed cross-sections. The paper is intended for higher education level physics teachers and students.

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

    Science.gov (United States)

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

    2018-03-01

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

  10. Determining Data Entry Points For Javascript-rich Web applications

    Directory of Open Access Journals (Sweden)

    George Maksimovich Noseevich

    2013-02-01

    Full Text Available The paper is devoted the task of automatic crawling of javascript-rich web applications for data entry points. A new technique is proposed, which combines dynamic and static javascript code analysis. Testing the proposed technique on real world web applications such as Twitter, Youtube and Reddit has confirmed its applicability for analysis of modern web applications.

  11. DETECTION OF SLOPE MOVEMENT BY COMPARING POINT CLOUDS CREATED BY SFM SOFTWARE

    Directory of Open Access Journals (Sweden)

    K. Oda

    2016-06-01

    Full Text Available This paper proposes movement detection method between point clouds created by SFM software, without setting any onsite georeferenced points. SfM software, like Smart3DCaputure, PhotoScan, and Pix4D, are convenient for non-professional operator of photogrammetry, because these systems require simply specification of sequence of photos and output point clouds with colour index which corresponds to the colour of original image pixel where the point is projected. SfM software can execute aerial triangulation and create dense point clouds fully automatically. This is useful when monitoring motion of unstable slopes, or loos rocks in slopes along roads or railroads. Most of existing method, however, uses mesh-based DSM for comparing point clouds before/after movement and it cannot be applied in such cases that part of slopes forms overhangs. And in some cases movement is smaller than precision of ground control points and registering two point clouds with GCP is not appropriate. Change detection method in this paper adopts CCICP (Classification and Combined ICP algorithm for registering point clouds before / after movement. The CCICP algorithm is a type of ICP (Iterative Closest Points which minimizes point-to-plane, and point-to-point distances, simultaneously, and also reject incorrect correspondences based on point classification by PCA (Principle Component Analysis. Precision test shows that CCICP method can register two point clouds up to the 1 pixel size order in original images. Ground control points set in site are useful for initial setting of two point clouds. If there are no GCPs in site of slopes, initial setting is achieved by measuring feature points as ground control points in the point clouds before movement, and creating point clouds after movement with these ground control points. When the motion is rigid transformation, in case that a loose Rock is moving in slope, motion including rotation can be analysed by executing CCICP for a

  12. Design of a Binocular Pupil and Gaze Point Detection System Utilizing High Definition Images

    Directory of Open Access Journals (Sweden)

    Yilmaz Durna

    2017-05-01

    Full Text Available This study proposes a novel binocular pupil and gaze detection system utilizing a remote full high definition (full HD camera and employing LabVIEW. LabVIEW is inherently parallel and has fewer time-consuming algorithms. Many eye tracker applications are monocular and use low resolution cameras due to real-time image processing difficulties. We utilized the computer’s direct access memory channel for rapid data transmission and processed full HD images with LabVIEW. Full HD images make easier determinations of center coordinates/sizes of pupil and corneal reflection. We modified the camera so that the camera sensor passed only infrared (IR images. Glints were taken as reference points for region of interest (ROI area selection of the eye region in the face image. A morphologic filter was applied for erosion of noise, and a weighted average technique was used for center detection. To test system accuracy with 11 participants, we produced a visual stimulus set up to analyze each eye’s movement. Nonlinear mapping function was utilized for gaze estimation. Pupil size, pupil position, glint position and gaze point coordinates were obtained with free natural head movements in our system. This system also works at 2046 × 1086 resolution at 40 frames per second. It is assumed that 280 frames per second for 640 × 480 pixel images is the case. Experimental results show that the average gaze detection error for 11 participants was 0.76° for the left eye, 0.89° for right eye and 0.83° for the mean of two eyes.

  13. The Italian Lightning Detection System of CESI and its applications

    International Nuclear Information System (INIS)

    Iorio, R.

    1998-01-01

    Aim of the paper is to give a description of the CESI lightning detection system SIRF. The system allows the real time localization (latitude, longitude) of the striking point of a cloud-to-ground lightning flash. Electrical parameters of the impulsive currents related to the flash strokes are calculated as well. Based on sensors covering the whole Italian territory, SIRF configuration and of the basic calculation criteria for passing from the sensor raw data to the final flash data is given together with the evaluation of the system expected performance parameters (accuracy, detection efficiently, signal/noise ratio). Main uses of lightning data in several fields are then reported, with special reference to electrical applications. Mention is done about the different modalities adopted for data distribution, according to that either real time or passed time applications have to be carried out. In this latter case (e.g. statistics), a huge amount of data archived within the Lightning Data Base of SIRF is available [it

  14. MODIS 250m burned area mapping based on an algorithm using change point detection and Markov random fields.

    Science.gov (United States)

    Mota, Bernardo; Pereira, Jose; Campagnolo, Manuel; Killick, Rebeca

    2013-04-01

    Area burned in tropical savannas of Brazil was mapped using MODIS-AQUA daily 250m resolution imagery by adapting one of the European Space Agency fire_CCI project burned area algorithms, based on change point detection and Markov random fields. The study area covers 1,44 Mkm2 and was performed with data from 2005. The daily 1000 m image quality layer was used for cloud and cloud shadow screening. The algorithm addresses each pixel as a time series and detects changes in the statistical properties of NIR reflectance values, to identify potential burning dates. The first step of the algorithm is robust filtering, to exclude outlier observations, followed by application of the Pruned Exact Linear Time (PELT) change point detection technique. Near-infrared (NIR) spectral reflectance changes between time segments, and post change NIR reflectance values are combined into a fire likelihood score. Change points corresponding to an increase in reflectance are dismissed as potential burn events, as are those occurring outside of a pre-defined fire season. In the last step of the algorithm, monthly burned area probability maps and detection date maps are converted to dichotomous (burned-unburned maps) using Markov random fields, which take into account both spatial and temporal relations in the potential burned area maps. A preliminary assessment of our results is performed by comparison with data from the MODIS 1km active fires and the 500m burned area products, taking into account differences in spatial resolution between the two sensors.

  15. An Instantaneous Low-Cost Point-of-Care Anemia Detection Device

    Directory of Open Access Journals (Sweden)

    Jaime Punter-Villagrasa

    2015-02-01

    Full Text Available We present a small, compact and portable device for point-of-care instantaneous early detection of anemia. The method used is based on direct hematocrit measurement from whole blood samples by means of impedance analysis. This device consists of a custom electronic instrumentation and a plug-and-play disposable sensor. The designed electronics rely on straightforward standards for low power consumption, resulting in a robust and low consumption device making it completely mobile with a long battery life. Another approach could be powering the system based on other solutions like indoor solar cells, or applying energy-harvesting solutions in order to remove the batteries. The sensing system is based on a disposable low-cost label-free three gold electrode commercial sensor for 50 µL blood samples. The device capability for anemia detection has been validated through 24 blood samples, obtained from four hospitalized patients at Hospital Clínic. As a result, the response, effectiveness and robustness of the portable point-of-care device to detect anemia has been proved with an accuracy error of 2.83% and a mean coefficient of variation of 2.57% without any particular case above 5%.

  16. Imaging monitoring techniques applications in the transient gratings detection

    Science.gov (United States)

    Zhao, Qing-ming

    2009-07-01

    Experimental studies of Degenerate four-wave mixing (DFWM) in iodine vapor at atmospheric pressure and 0℃ and 25℃ are reported. The Laser-induced grating (LIG) studies are carried out by generating the thermal grating using a pulsed, narrow bandwidth, dye laser .A new image processing system for detecting forward DFWM spectroscopy on iodine vapor is reported. This system is composed of CCD camera, imaging processing card and the related software. With the help of the detecting system, phase matching can be easily achieved in the optical arrangement by crossing the two pumps and the probe as diagonals linking opposite corners of a rectangular box ,and providing a way to position the PhotoMultiplier Tube (PMT) . Also it is practical to know the effect of the pointing stability on the optical path by monitoring facula changing with the laser beam pointing and disturbs of the environment. Finally the effects of Photostability of dye laser on the ration of signal to noise in DFWM using forward geometries have been investigated in iodine vapor. This system makes it feasible that the potential application of FG-DFWM is used as a diagnostic tool in combustion research and environment monitoring.

  17. Replacement Condition Detection of Railway Point Machines Using an Electric Current Sensor.

    Science.gov (United States)

    Sa, Jaewon; Choi, Younchang; Chung, Yongwha; Kim, Hee-Young; Park, Daihee; Yoon, Sukhan

    2017-01-29

    Detecting replacement conditions of railway point machines is important to simultaneously satisfy the budget-limit and train-safety requirements. In this study, we consider classification of the subtle differences in the aging effect-using electric current shape analysis-for the purpose of replacement condition detection of railway point machines. After analyzing the shapes of after-replacement data and then labeling the shapes of each before-replacement data, we can derive the criteria that can handle the subtle differences between "does-not-need-to-be-replaced" and "needs-to-be-replaced" shapes. On the basis of the experimental results with in-field replacement data, we confirmed that the proposed method could detect the replacement conditions with acceptable accuracy, as well as provide visual interpretability of the criteria used for the time-series classification.

  18. Salient Point Detection in Protrusion Parts of 3D Object Robust to Isometric Variations

    Science.gov (United States)

    Mirloo, Mahsa; Ebrahimnezhad, Hosein

    2018-03-01

    In this paper, a novel method is proposed to detect 3D object salient points robust to isometric variations and stable against scaling and noise. Salient points can be used as the representative points from object protrusion parts in order to improve the object matching and retrieval algorithms. The proposed algorithm is started by determining the first salient point of the model based on the average geodesic distance of several random points. Then, according to the previous salient point, a new point is added to this set of points in each iteration. By adding every salient point, decision function is updated. Hence, a condition is created for selecting the next point in which the iterative point is not extracted from the same protrusion part so that drawing out of a representative point from every protrusion part is guaranteed. This method is stable against model variations with isometric transformations, scaling, and noise with different levels of strength due to using a feature robust to isometric variations and considering the relation between the salient points. In addition, the number of points used in averaging process is decreased in this method, which leads to lower computational complexity in comparison with the other salient point detection algorithms.

  19. Processing Terrain Point Cloud Data

    KAUST Repository

    DeVore, Ronald; Petrova, Guergana; Hielsberg, Matthew; Owens, Luke; Clack, Billy; Sood, Alok

    2013-01-01

    Terrain point cloud data are typically acquired through some form of Light Detection And Ranging sensing. They form a rich resource that is important in a variety of applications including navigation, line of sight, and terrain visualization

  20. STRUCTURE LINE DETECTION FROM LIDAR POINT CLOUDS USING TOPOLOGICAL ELEVATION ANALYSIS

    Directory of Open Access Journals (Sweden)

    C. Y. Lo

    2012-07-01

    Full Text Available Airborne LIDAR point clouds, which have considerable points on object surfaces, are essential to building modeling. In the last two decades, studies have developed different approaches to identify structure lines using two main approaches, data-driven and modeldriven. These studies have shown that automatic modeling processes depend on certain considerations, such as used thresholds, initial value, designed formulas, and predefined cues. Following the development of laser scanning systems, scanning rates have increased and can provide point clouds with higher point density. Therefore, this study proposes using topological elevation analysis (TEA to detect structure lines instead of threshold-dependent concepts and predefined constraints. This analysis contains two parts: data pre-processing and structure line detection. To preserve the original elevation information, a pseudo-grid for generating digital surface models is produced during the first part. The highest point in each grid is set as the elevation value, and its original threedimensional position is preserved. In the second part, using TEA, the structure lines are identified based on the topology of local elevation changes in two directions. Because structure lines can contain certain geometric properties, their locations have small relieves in the radial direction and steep elevation changes in the circular direction. Following the proposed approach, TEA can be used to determine 3D line information without selecting thresholds. For validation, the TEA results are compared with those of the region growing approach. The results indicate that the proposed method can produce structure lines using dense point clouds.

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

    Science.gov (United States)

    Liu, Siqi; Wright, Adam; Hauskrecht, Milos

    2017-06-01

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

  2. Replacement Condition Detection of Railway Point Machines Using an Electric Current Sensor

    Science.gov (United States)

    Sa, Jaewon; Choi, Younchang; Chung, Yongwha; Kim, Hee-Young; Park, Daihee; Yoon, Sukhan

    2017-01-01

    Detecting replacement conditions of railway point machines is important to simultaneously satisfy the budget-limit and train-safety requirements. In this study, we consider classification of the subtle differences in the aging effect—using electric current shape analysis—for the purpose of replacement condition detection of railway point machines. After analyzing the shapes of after-replacement data and then labeling the shapes of each before-replacement data, we can derive the criteria that can handle the subtle differences between “does-not-need-to-be-replaced” and “needs-to-be-replaced” shapes. On the basis of the experimental results with in-field replacement data, we confirmed that the proposed method could detect the replacement conditions with acceptable accuracy, as well as provide visual interpretability of the criteria used for the time-series classification. PMID:28146057

  3. Can Detectability Analysis Improve the Utility of Point Counts for Temperate Forest Raptors?

    Science.gov (United States)

    Temperate forest breeding raptors are poorly represented in typical point count surveys because these birds are cryptic and typically breed at low densities. In recent years, many new methods for estimating detectability during point counts have been developed, including distanc...

  4. Interesting Interest Points

    DEFF Research Database (Denmark)

    Aanæs, Henrik; Dahl, Anders Lindbjerg; Pedersen, Kim Steenstrup

    2012-01-01

    on spatial invariance of interest points under changing acquisition parameters by measuring the spatial recall rate. The scope of this paper is to investigate the performance of a number of existing well-established interest point detection methods. Automatic performance evaluation of interest points is hard......Not all interest points are equally interesting. The most valuable interest points lead to optimal performance of the computer vision method in which they are employed. But a measure of this kind will be dependent on the chosen vision application. We propose a more general performance measure based...... position. The LED illumination provides the option for artificially relighting the scene from a range of light directions. This data set has given us the ability to systematically evaluate the performance of a number of interest point detectors. The highlights of the conclusions are that the fixed scale...

  5. PointFinder: a novel web tool for WGS-based detection of antimicrobial resistance associated with chromosomal point mutations in bacterial pathogens

    DEFF Research Database (Denmark)

    Zankari, Ea; Allesøe, Rosa Lundbye; Joensen, Katrine Grimstrup

    2017-01-01

    enterica, Escherichia coli and Campylobacter jejuni. The web-server ResFinder-2.1 was used to identify acquired antimicrobial resistance genes and two methods, the novel PointFinder (using BLAST) and an in-house method (mapping of raw WGS reads), were used to identify chromosomal point mutations. Results...... or when mapping the reads. Conclusions PointFinder proved, with high concordance between phenotypic and predicted antimicrobial susceptibility, to be a user-friendly web tool for detection of chromosomal point mutations associated with antimicrobial resistance....

  6. An algorithm for leak point detection of underground pipelines

    International Nuclear Information System (INIS)

    Lee, Young Sup; Yoon, Dong Jin

    2004-01-01

    Leak noise is a good source to identify the exact location of a leak point of underground water pipelines. Water leak generates broadband noise from a leak location and can be propagated to both directions of water pipes. However, the necessity of long-range detection of this leak location makes to identify low-frequency acoustic waves rather than high frequency ones. Acoustic wave propagation coupled with surrounding boundaries including cast iron pipes is theoretically analyzed and the wave velocity was confirmed with experiment. The leak locations were identified both by the acoustic emission (AE) method and the cross-correlation method. In a short-range distance, both the AE method and cross-correlation method are effective to detect leak position. However, the detection for a long-range distance required a lower frequency range accelerometers only because higher frequency waves were attenuated very quickly with the increase of propagation paths. Two algorithms for the cross-correlation function were suggested, and a long-range detection has been achieved at real underground water pipelines longer than 300 m.

  7. Unconventional applications of conventional intrusion detection sensors

    International Nuclear Information System (INIS)

    Williams, J.D.; Matter, J.C.

    1983-01-01

    A number of conventional intrusion detection sensors exists for the detection of persons entering buildings, moving within a given volume, and crossing a perimeter isolation zone. Unconventional applications of some of these sensors have recently been investigated. Some of the applications which are discussed include detection on the edges and tops of buildings, detection in storm sewers, detection on steam and other types of large pipes, and detection of unauthorized movement within secure enclosures. The enclosures can be used around complicated control valves, electrical control panels, emergency generators, etc

  8. Comparison of Birds Detected from Roadside and Off-Road Point Counts in the Shenandoah National Park

    Science.gov (United States)

    Cherry M.E. Keller; Mark R. Fuller

    1995-01-01

    Roadside point counts are generally used for large surveys to increase the number of samples. We examined differences in species detected from roadside versus off-road (200-m and 400-m) point counts in the Shenandoah National Park. We also compared the list of species detected in the first 3 minutes to those detected in 10 minutes for potential species biases. Results...

  9. Dew inspired breathing-based detection of genetic point mutation visualized by naked eye

    Science.gov (United States)

    Xie, Liping; Wang, Tongzhou; Huang, Tianqi; Hou, Wei; Huang, Guoliang; Du, Yanan

    2014-09-01

    A novel label-free method based on breathing-induced vapor condensation was developed for detection of genetic point mutation. The dew-inspired detection was realized by integration of target-induced DNA ligation with rolling circle amplification (RCA). The vapor condensation induced by breathing transduced the RCA-amplified variances in DNA contents into visible contrast. The image could be recorded by a cell phone for further or even remote analysis. This green assay offers a naked-eye-reading method potentially applied for point-of-care liver cancer diagnosis in resource-limited regions.

  10. Edge Detection and Feature Line Tracing in 3D-Point Clouds by Analyzing Geometric Properties of Neighborhoods

    Directory of Open Access Journals (Sweden)

    Huan Ni

    2016-09-01

    Full Text Available This paper presents an automated and effective method for detecting 3D edges and tracing feature lines from 3D-point clouds. This method is named Analysis of Geometric Properties of Neighborhoods (AGPN, and it includes two main steps: edge detection and feature line tracing. In the edge detection step, AGPN analyzes geometric properties of each query point’s neighborhood, and then combines RANdom SAmple Consensus (RANSAC and angular gap metric to detect edges. In the feature line tracing step, feature lines are traced by a hybrid method based on region growing and model fitting in the detected edges. Our approach is experimentally validated on complex man-made objects and large-scale urban scenes with millions of points. Comparative studies with state-of-the-art methods demonstrate that our method obtains a promising, reliable, and high performance in detecting edges and tracing feature lines in 3D-point clouds. Moreover, AGPN is insensitive to the point density of the input data.

  11. A Research on Fast Face Feature Points Detection on Smart Mobile Devices

    Directory of Open Access Journals (Sweden)

    Xiaohe Li

    2018-01-01

    Full Text Available We explore how to leverage the performance of face feature points detection on mobile terminals from 3 aspects. First, we optimize the models used in SDM algorithms via PCA and Spectrum Clustering. Second, we propose an evaluation criterion using Linear Discriminative Analysis to choose the best local feature descriptions which plays a critical role in feature points detection. Third, we take advantage of multicore architecture of mobile terminal and parallelize the optimized SDM algorithm to improve the efficiency further. The experiment observations show that our final accomplished GPC-SDM (improved Supervised Descent Method using spectrum clustering, PCA, and GPU acceleration suppresses the memory usage, which is beneficial and efficient to meet the real-time requirements.

  12. Comparing Two Approaches for Point-Like Scatterer Detection

    Directory of Open Access Journals (Sweden)

    Angela Dell’Aversano

    2015-01-01

    Full Text Available Many inverse scattering problems concern the detection and localisation of point-like scatterers which are sparsely enclosed within a prescribed investigation domain. Therefore, it looks like a good option to tackle the problem by applying reconstruction methods that are properly tailored for such a type of scatterers or that naturally enforce sparsity in the reconstructions. Accordingly, in this paper we compare the time reversal-MUSIC and the compressed sensing. The study develops through numerical examples and focuses on the role of noise in data and mutual coupling between the scatterers.

  13. Data-Driven Method for Wind Turbine Yaw Angle Sensor Zero-Point Shifting Fault Detection

    Directory of Open Access Journals (Sweden)

    Yan Pei

    2018-03-01

    Full Text Available Wind turbine yaw control plays an important role in increasing the wind turbine production and also in protecting the wind turbine. Accurate measurement of yaw angle is the basis of an effective wind turbine yaw controller. The accuracy of yaw angle measurement is affected significantly by the problem of zero-point shifting. Hence, it is essential to evaluate the zero-point shifting error on wind turbines on-line in order to improve the reliability of yaw angle measurement in real time. Particularly, qualitative evaluation of the zero-point shifting error could be useful for wind farm operators to realize prompt and cost-effective maintenance on yaw angle sensors. In the aim of qualitatively evaluating the zero-point shifting error, the yaw angle sensor zero-point shifting fault is firstly defined in this paper. A data-driven method is then proposed to detect the zero-point shifting fault based on Supervisory Control and Data Acquisition (SCADA data. The zero-point shifting fault is detected in the proposed method by analyzing the power performance under different yaw angles. The SCADA data are partitioned into different bins according to both wind speed and yaw angle in order to deeply evaluate the power performance. An indicator is proposed in this method for power performance evaluation under each yaw angle. The yaw angle with the largest indicator is considered as the yaw angle measurement error in our work. A zero-point shifting fault would trigger an alarm if the error is larger than a predefined threshold. Case studies from several actual wind farms proved the effectiveness of the proposed method in detecting zero-point shifting fault and also in improving the wind turbine performance. Results of the proposed method could be useful for wind farm operators to realize prompt adjustment if there exists a large error of yaw angle measurement.

  14. Prospects for detecting supersymmetric dark matter at Post-LEP benchmark points

    International Nuclear Information System (INIS)

    Ellis, J.; Matchev, K.T.; Feng, J.L.; Ferstl, A.; Olive, K.A.

    2002-01-01

    A new set of supersymmetric benchmark scenarios has recently been proposed in the context of the constrained MSSM (CMSSM) with universal soft supersymmetry-breaking masses, taking into account the constraints from LEP, b→sγ and g μ -2. These points have previously been used to discuss the physics reaches of different accelerators. In this paper, we discuss the prospects for discovering supersymmetric dark matter in these scenarios. We consider direct detection through spin-independent and spin-dependent nuclear scattering, as well as indirect detection through relic annihilations to neutrinos, photons, and positrons. We find that several of the benchmark scenarios offer good prospects for direct detection via spin-independent nuclear scattering and indirect detection via muons produced by neutrinos from relic annihilations inside the Sun, and some models offer good prospects for detecting photons from relic annihilations in the galactic centre. (orig.)

  15. Detecting change points in VIX and S&P 500: A new approach to dynamic asset allocation

    DEFF Research Database (Denmark)

    Nystrup, Peter; Hansen, Bo William; Madsen, Henrik

    2016-01-01

    to DAA that is based on detection of change points without fitting a model with a fixed number of regimes to the data, without estimating any parameters and without assuming a specific distribution of the data. It is examined whether DAA is most profitable when based on changes in the Chicago Board...... Options Exchange Volatility Index or change points detected in daily returns of the S&P 500 index. In an asset universe consisting of the S&P 500 index and cash, it is shown that a dynamic strategy based on detected change points significantly improves the Sharpe ratio and reduces the drawdown risk when...

  16. Video motion detection for physical security applications

    International Nuclear Information System (INIS)

    Matter, J.C.

    1990-01-01

    Physical security specialists have been attracted to the concept of video motion detection for several years. Claimed potential advantages included additional benefit from existing video surveillance systems, automatic detection, improved performance compared to human observers, and cost-effectiveness. In recent years, significant advances in image-processing dedicated hardware and image analysis algorithms and software have accelerated the successful application of video motion detection systems to a variety of physical security applications. Early video motion detectors (VMDs) were useful for interior applications of volumetric sensing. Success depended on having a relatively well-controlled environment. Attempts to use these systems outdoors frequently resulted in an unacceptable number of nuisance alarms. Currently, Sandia National Laboratories (SNL) is developing several advanced systems that employ image-processing techniques for a broader set of safeguards and security applications. The Target Cueing and Tracking System (TCATS), the Video Imaging System for Detection, Tracking, and Assessment (VISDTA), the Linear Infrared Scanning Array (LISA); the Mobile Intrusion Detection and Assessment System (MIDAS), and the Visual Artificially Intelligent Surveillance (VAIS) systems are described briefly

  17. On a Hopping-Points SVD and Hough Transform-Based Line Detection Algorithm for Robot Localization and Mapping

    Directory of Open Access Journals (Sweden)

    Abhijeet Ravankar

    2016-05-01

    Full Text Available Line detection is an important problem in computer vision, graphics and autonomous robot navigation. Lines detected using a laser range sensor (LRS mounted on a robot can be used as features to build a map of the environment, and later to localize the robot in the map, in a process known as Simultaneous Localization and Mapping (SLAM. We propose an efficient algorithm for line detection from LRS data using a novel hopping-points Singular Value Decomposition (SVD and Hough transform-based algorithm, in which SVD is applied to intermittent LRS points to accelerate the algorithm. A reverse-hop mechanism ensures that the end points of the line segments are accurately extracted. Line segments extracted from the proposed algorithm are used to form a map and, subsequently, LRS data points are matched with the line segments to localize the robot. The proposed algorithm eliminates the drawbacks of point-based matching algorithms like the Iterative Closest Points (ICP algorithm, the performance of which degrades with an increasing number of points. We tested the proposed algorithm for mapping and localization in both simulated and real environments, and found it to detect lines accurately and build maps with good self-localization.

  18. Full distributed fiber optical sensor for intrusion detection in application to buried pipelines

    Science.gov (United States)

    Gao, Jianzhong; Jiang, Zhuangde; Zhao, Yulong; Zhu, Li; Zhao, Guoxian

    2005-11-01

    Based on the microbend effect of optical fiber, a distributed sensor for real-time continuous monitoring of intrusion in application to buried pipelines is proposed. The sensing element is a long cable with a special structure made up of an elastic polymer wire, an optical fiber, and a metal wire. The damage point is located with an embedded optical time domain reflectometry (OTDR) instrument. The intrusion types can be indicated by the amplitude of output voltage. Experimental results show that the detection system can alarm adequately under abnormal load and can locate the intrusion point within 22.4 m for distance of 3.023 km.

  19. A volumetric meter chip for point-of-care quantitative detection of bovine catalase for food safety control

    International Nuclear Information System (INIS)

    Cui, Xingye; Hu, Jie; Choi, Jane Ru; Huang, Yalin; Wang, Xuemin; Lu, Tian Jian; Xu, Feng

    2016-01-01

    A volumetric meter chip was developed for quantitative point-of-care (POC) analysis of bovine catalase, a bioindicator of bovine mastitis, in milk samples. The meter chip displays multiplexed quantitative results by presenting the distance of ink bar advancement that is detectable by the naked eye. The meter chip comprises a poly(methyl methacrylate) (PMMA) layer, a double-sided adhesive (DSA) layer and a glass slide layer fabricated by the laser-etching method, which is typically simple, rapid (∼3 min per chip), and cost effective (∼$0.2 per chip). Specially designed “U shape” reaction cells are covered by an adhesive tape that serves as an on-off switch, enabling the simple operation of the assay. As a proof of concept, we employed the developed meter chip for the quantification of bovine catalase in raw milk samples to detect catalase concentrations as low as 20 μg/mL. The meter chip has great potential to detect various target analytes for a wide range of POC applications. - Highlights: • The meter chip is a standalone point-of-care diagnostic tool with visible readouts of quantification results. • A fast and low cost fabrication protocol (~3 min and ~$0.2 per chip) of meter chip was proposed. • The chip may hold the potential for rapid scaning of bovine mastitis in cattle farms for food safety control.

  20. A volumetric meter chip for point-of-care quantitative detection of bovine catalase for food safety control

    Energy Technology Data Exchange (ETDEWEB)

    Cui, Xingye; Hu, Jie; Choi, Jane Ru; Huang, Yalin; Wang, Xuemin [The Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi' an Jiaotong University, Xi' an, 710049 (China); Bioinspired Engineering and Biomechanics Center (BEBC), Xi' an Jiaotong University, Xi' an, 710049 (China); Lu, Tian Jian, E-mail: tjlu@mail.xjtu.edu.cn [Bioinspired Engineering and Biomechanics Center (BEBC), Xi' an Jiaotong University, Xi' an, 710049 (China); Xu, Feng, E-mail: fengxu@mail.xjtu.edu.cn [The Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi' an Jiaotong University, Xi' an, 710049 (China); Bioinspired Engineering and Biomechanics Center (BEBC), Xi' an Jiaotong University, Xi' an, 710049 (China)

    2016-09-07

    A volumetric meter chip was developed for quantitative point-of-care (POC) analysis of bovine catalase, a bioindicator of bovine mastitis, in milk samples. The meter chip displays multiplexed quantitative results by presenting the distance of ink bar advancement that is detectable by the naked eye. The meter chip comprises a poly(methyl methacrylate) (PMMA) layer, a double-sided adhesive (DSA) layer and a glass slide layer fabricated by the laser-etching method, which is typically simple, rapid (∼3 min per chip), and cost effective (∼$0.2 per chip). Specially designed “U shape” reaction cells are covered by an adhesive tape that serves as an on-off switch, enabling the simple operation of the assay. As a proof of concept, we employed the developed meter chip for the quantification of bovine catalase in raw milk samples to detect catalase concentrations as low as 20 μg/mL. The meter chip has great potential to detect various target analytes for a wide range of POC applications. - Highlights: • The meter chip is a standalone point-of-care diagnostic tool with visible readouts of quantification results. • A fast and low cost fabrication protocol (~3 min and ~$0.2 per chip) of meter chip was proposed. • The chip may hold the potential for rapid scaning of bovine mastitis in cattle farms for food safety control.

  1. First principles calculation of point defects and mobility degradation in bulk AlSb for radiation detection application

    International Nuclear Information System (INIS)

    Lordi, V; Aberg, D; Erhart, P; Wu, K J

    2007-01-01

    The development of high resolution, room temperature semiconductor radiation detectors requires the introduction of materials with increased carrier mobility-lifetime (μτ) product, while having a band gap in the 1.4-2.2 eV range. AlSb is a promising material for this application. However, systematic improvements in the material quality are necessary to achieve an adequate μτ product. We are using a combination of simulation and experiment to develop a fundamental understanding of the factors which affect detector material quality. First principles calculations are used to study the microscopic mechanisms of mobility degradation from point defects and to calculate the intrinsic limit of mobility from phonon scattering. We use density functional theory (DFT) to calculate the formation energies of native and impurity point defects, to determine their equilibrium concentrations as a function of temperature and charge state. Perturbation theory via the Born approximation is coupled with Boltzmann transport theory to calculate the contribution toward mobility degradation of each type of point defect, using DFT-computed carrier scattering rates. A comparison is made to measured carrier concentrations and mobilities from AlSb crystals grown in our lab. We find our predictions in good quantitative agreement with experiment, allowing optimized annealing conditions to be deduced. A major result is the determination of oxygen impurity as a severe mobility killer, despite the ability of oxygen to compensation dope AlSb and reduce the net carrier concentration. In this case, increased resistivity is not a good indicator of improved material performance, due to the concomitant sharp reduction in μτ

  2. Data mining approach to web application intrusions detection

    Science.gov (United States)

    Kalicki, Arkadiusz

    2011-10-01

    Web applications became most popular medium in the Internet. Popularity, easiness of web application script languages and frameworks together with careless development results in high number of web application vulnerabilities and high number of attacks performed. There are several types of attacks possible because of improper input validation: SQL injection Cross-site scripting, Cross-Site Request Forgery (CSRF), web spam in blogs and others. In order to secure web applications intrusion detection (IDS) and intrusion prevention systems (IPS) are being used. Intrusion detection systems are divided in two groups: misuse detection (traditional IDS) and anomaly detection. This paper presents data mining based algorithm for anomaly detection. The principle of this method is the comparison of the incoming HTTP traffic with a previously built profile that contains a representation of the "normal" or expected web application usage sequence patterns. The frequent sequence patterns are found with GSP algorithm. Previously presented detection method was rewritten and improved. Some tests show that the software catches malicious requests, especially long attack sequences, results quite good with medium length sequences, for short length sequences must be complemented with other methods.

  3. Modelling and design of a capacitive touch sensor for urinary tract infection detection at the point-of-care.

    Science.gov (United States)

    Barbosa, Cátia; Dong, Tao

    2014-01-01

    Due to great use of touchscreens in mobile telephones and other electronic devices, there has been great evolution in this technology. Its wide applicability makes the touch sensor technology suitable for detection of specific components in urine, responsible for urinary tract infection (UTI). Integration of a touch sensor in a disposable probe tip to be used in UTI detection represents a powerful tool to develop new point-of-care testing (POCT) devices. The simplified structure of an electrodes array touch screen was simulated using the software COMSOL Multiphysics to prove that capacitive based touch screens can be used for detection of UTI. Besides we assumed presence of E.coli, one of the major causes of UTI urine. Results show that global capacitance increases if an E.coli sphere is present near the active electrodes, remaining approximately constant when further apart electrodes are excited. The output simulated voltage varies according to the capacitance value, decreasing when the capacitance is increased.

  4. Colorimetric detection for paper-based biosensing applications

    Science.gov (United States)

    Brink, C.; Joubert, T.-H.

    2016-02-01

    Research on affordable point-of-care health diagnostics is rapidly advancing1. Colorimetric biosensor applications are typically qualitative, but recently the focus has been shifted to quantitative measurements2,3. Although numerous qualitative point-of-care (POC) health diagnostic devices are available, the challenge exists of developing a quantitative colorimetric array reader system that complies with the ASSURED (Affordable, Sensitive, Specific, User-friendly, Rapid and Robust, Equipment-free, Deliverable to end-users) principles of the World Health Organization4. This paper presents a battery powered 8-bit tonal resolution colorimetric sensor circuit for paper microfluidic assays using low cost photo-detection circuitry and a low-power LED light source. A colorimetric 3×3-pixel array reader was developed for rural environments where resources and personnel are limited. The device sports an ultralow-power E-ink paper display. The colorimetric device includes integrated GPS functionality and EEPROM memory to log measurements with geo-tags for possible analysis of regional trends. The device competes with colour intensity measurement techniques using smartphone cameras, but proves to be a cheaper solution, compensating for the typical performance variations between cameras of different brands of smartphones. Inexpensive methods for quantifying bacterial assays have been shown using desktop scanners, which are not portable, and cameras, which suffer severely from changes in ambient light in different environments. Promising colorimetric detection results have been demonstrated using devices such as video cameras5, digital colour analysers6, flatbed scanners7 or custom portable readers8. The major drawback of most of these methods is the need for specialized instrumentation and for image analysis on a computer.

  5. Detection and Control of Spin-Orbit Interactions in a GaAs Hole Quantum Point Contact

    Science.gov (United States)

    Srinivasan, A.; Miserev, D. S.; Hudson, K. L.; Klochan, O.; Muraki, K.; Hirayama, Y.; Reuter, D.; Wieck, A. D.; Sushkov, O. P.; Hamilton, A. R.

    2017-04-01

    We investigate the relationship between the Zeeman interaction and the inversion-asymmetry-induced spin-orbit interactions (Rashba and Dresselhaus SOIs) in GaAs hole quantum point contacts. The presence of a strong SOI results in the crossing and anticrossing of adjacent spin-split hole subbands in a magnetic field. We demonstrate theoretically and experimentally that the anticrossing energy gap depends on the interplay between the SOI terms and the highly anisotropic hole g tensor and that this interplay can be tuned by selecting the crystal axis along which the current and magnetic field are aligned. Our results constitute the independent detection and control of the Dresselhaus and Rashba SOIs in hole systems, which could be of importance for spintronics and quantum information applications.

  6. Optimal Design of Fixed-Point and Floating-Point Arithmetic Units for Scientific Applications

    OpenAIRE

    Pongyupinpanich, Surapong

    2012-01-01

    The challenge in designing a floating-point arithmetic co-processor/processor for scientific and engineering applications is to improve the performance, efficiency, and computational accuracy of the arithmetic unit. The arithmetic unit should efficiently support several mathematical functions corresponding to scientific and engineering computation demands. Moreover, the computations should be performed as fast as possible with a high degree of accuracy. Thus, this thesis proposes algorithm, d...

  7. A volumetric meter chip for point-of-care quantitative detection of bovine catalase for food safety control.

    Science.gov (United States)

    Cui, Xingye; Hu, Jie; Choi, Jane Ru; Huang, Yalin; Wang, Xuemin; Lu, Tian Jian; Xu, Feng

    2016-09-07

    A volumetric meter chip was developed for quantitative point-of-care (POC) analysis of bovine catalase, a bioindicator of bovine mastitis, in milk samples. The meter chip displays multiplexed quantitative results by presenting the distance of ink bar advancement that is detectable by the naked eye. The meter chip comprises a poly(methyl methacrylate) (PMMA) layer, a double-sided adhesive (DSA) layer and a glass slide layer fabricated by the laser-etching method, which is typically simple, rapid (∼3 min per chip), and cost effective (∼$0.2 per chip). Specially designed "U shape" reaction cells are covered by an adhesive tape that serves as an on-off switch, enabling the simple operation of the assay. As a proof of concept, we employed the developed meter chip for the quantification of bovine catalase in raw milk samples to detect catalase concentrations as low as 20 μg/mL. The meter chip has great potential to detect various target analytes for a wide range of POC applications. Copyright © 2016 Elsevier B.V. All rights reserved.

  8. Detection of oscillatory components in noise signals and its application to fast detection of sodium boiling in LMFBR's

    International Nuclear Information System (INIS)

    Ehrhardt, J.

    1975-09-01

    In general, the surveillance of technical plants is performed by observating the mean value of measured signals. In this method not all information included in these signals is used. On the other hand - for example in a reactor - disturbances are possible which generate small oscillatory components in the measured signals. In general, these oscillatory components do not influence the mean value of the signals and consequently do not activate the conventional control system; however they can be found by analysis of the signal's noise component. For the detection of these oscillatory signals the observation of the frequency spectra of the noise signals is particularly advantageous because they produce peaks at the oscillation frequencies. In this paper a new detection system for the fast detection of suddenly appearing peaks in the frequency spectra of noise signals is presented. The prototype of a compact detection unit was developed which continuously computes the power spectral density (PSD) of noise signals and simultaneously supervises the PSD for peaks in the relevant frequency range. The detection method is not affected by the frequency dependance of the PSD and is applicable to any noise signal. General criteria were developed to enable the determination of the optimal detection system and its sensitivity. The upper limits of false alarm rate and detection time were taken into account. The detection criteria are applicable to all noise signals with approximately normally distributed amplitudes. Theoretical results were confirmed in a number of experiments; special experimental and theoretical parameter studies were done for the optimal detection of sodium boiling in LMFBR's. Computations based on these results showed that local and integral sodium boiling can be detected in a wide core range of SNR 300 by observing fluctuations of the neutron flux. In this connection it is important to point out that no additional core instrumentation is necessary because the

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

    Science.gov (United States)

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

    2016-11-01

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

  10. Application of Data Cubes for Improving Detection of Water Cycle Extreme Events

    Science.gov (United States)

    Albayrak, Arif; Teng, William

    2015-01-01

    As part of an ongoing NASA-funded project to remove a longstanding barrier to accessing NASA data (i.e., accessing archived time-step array data as point-time series), for the hydrology and other point-time series-oriented communities, "data cubes" are created from which time series files (aka "data rods") are generated on-the-fly and made available as Web services from the Goddard Earth Sciences Data and Information Services Center (GES DISC). Data cubes are data as archived rearranged into spatio-temporal matrices, which allow for easy access to the data, both spatially and temporally. A data cube is a specific case of the general optimal strategy of reorganizing data to match the desired means of access. The gain from such reorganization is greater the larger the data set. As a use case of our project, we are leveraging existing software to explore the application of the data cubes concept to machine learning, for the purpose of detecting water cycle extreme events, a specific case of anomaly detection, requiring time series data. We investigate the use of support vector machines (SVM) for anomaly classification. We show an example of detection of water cycle extreme events, using data from the Tropical Rainfall Measuring Mission (TRMM).

  11. Integrated optical detection of autonomous capillary microfluidic immunoassays:a hand-held point-of-care prototype.

    Science.gov (United States)

    Novo, P; Chu, V; Conde, J P

    2014-07-15

    The miniaturization of biosensors using microfluidics has potential in enabling the development of point-of-care devices, with the added advantages of reduced time and cost of analysis with limits-of-detection comparable to those obtained through traditional laboratory techniques. Interfacing microfluidic devices with the external world can be difficult especially in aspects involving fluid handling and the need for simple sample insertion that avoids special equipment or trained personnel. In this work we present a point-of-care prototype system by integrating capillary microfluidics with a microfabricated photodiode array and electronic instrumentation into a hand-held unit. The capillary microfluidic device is capable of autonomous and sequential fluid flow, including control of the average fluid velocity at any given point of the analysis. To demonstrate the functionality of the prototype, a model chemiluminescence ELISA was performed. The performance of the integrated optical detection in the point-of-care prototype is equal to that obtained with traditional bench-top instrumentation. The photodiode signals were acquired, displayed and processed by a simple graphical user interface using a computer connected to the microcontroller through USB. The prototype performed integrated chemiluminescence ELISA detection in about 15 min with a limit-of-detection of ≈2 nM with an antibody-antigen affinity constant of ≈2×10(7) M(-1). Copyright © 2014 Elsevier B.V. All rights reserved.

  12. AIRBORNE LIGHT DETECTION AND RANGING (LIDAR DERIVED DEFORMATION FROM THE MW 6.0 24 AUGUST, 2014 SOUTH NAPA EARTHQUAKE ESTIMATED BY TWO AND THREE DIMENSIONAL POINT CLOUD CHANGE DETECTION TECHNIQUES

    Directory of Open Access Journals (Sweden)

    A. W. Lyda

    2016-06-01

    Full Text Available Remote sensing via LiDAR (Light Detection And Ranging has proven extremely useful in both Earth science and hazard related studies. Surveys taken before and after an earthquake for example, can provide decimeter-level, 3D near-field estimates of land deformation that offer better spatial coverage of the near field rupture zone than other geodetic methods (e.g., InSAR, GNSS, or alignment array. In this study, we compare and contrast estimates of deformation obtained from different pre and post-event airborne laser scanning (ALS data sets of the 2014 South Napa Earthquake using two change detection algorithms, Iterative Control Point (ICP and Particle Image Velocimetry (PIV. The ICP algorithm is a closest point based registration algorithm that can iteratively acquire three dimensional deformations from airborne LiDAR data sets. By employing a newly proposed partition scheme, “moving window,” to handle the large spatial scale point cloud over the earthquake rupture area, the ICP process applies a rigid registration of data sets within an overlapped window to enhance the change detection results of the local, spatially varying surface deformation near-fault. The other algorithm, PIV, is a well-established, two dimensional image co-registration and correlation technique developed in fluid mechanics research and later applied to geotechnical studies. Adapted here for an earthquake with little vertical movement, the 3D point cloud is interpolated into a 2D DTM image and horizontal deformation is determined by assessing the cross-correlation of interrogation areas within the images to find the most likely deformation between two areas. Both the PIV process and the ICP algorithm are further benefited by a presented, novel use of urban geodetic markers. Analogous to the persistent scatterer technique employed with differential radar observations, this new LiDAR application exploits a classified point cloud dataset to assist the change detection

  13. Detection of precursory deformation using a TLS. Application to spatial prediction of rockfalls.

    Science.gov (United States)

    Abellán, Antonio; Vilaplana, Joan Manuel; Calvet, Jaume; Rodriguez, Xavier

    2010-05-01

    Different applications on the use of Terrestrial Laser Scanner (TLS) on rock slopes are undergoing rapid development, mainly in the characterization of 3D discontinuities and the monitoring of rock slopes. The emphasis of this research is on detection of precursory deformation and its application to spatial prediction of rockfalls. The pilot study area corresponds to the main scarp of an old slide located at Puigcercós (Catalonia, Spain). 3D temporal variations of the terrain were analyzed by comparing sequential TLS datasets. Five areas characterized by centimetric precursory deformations were detected in the study area. Of these deformations, (a) growing deformation across three areas culminated in a rockfall occurrence; and (b) another growing deformation across two areas was detected, making a subsequent rockfall likely. The areas with precursory deformations detected in Puigcercós showed the following characteristics: (a) a sub-vertical fracture delimiting the moving part from the rest of the slope; (b) an increase in the horizontal displacement upwards, typical of a toppling failure mechanism (Muller 1968; Goodman and Bray, 1976). In addition, decimetric-scale rockfalls were observed in the upper part of the moving areas, which is consistent with the observations of Rosser et al., (2007). TLS ILRIS 3D technical characteristics are as follows: high accuracy (7.2 mm at a range of 50 meters), high angular resolution (e.g. 1 point every few cm), fast data acquisition: 2,500 points/second; broad coverage; high maximum range on natural slopes: ~600m. The single point distances between the surface of reference and the successive data point clouds were computed using a conventional methodology (data vs. reference comparison). The direction of comparison was defined as the normal vector of the rock face at its central part. We focused in the study of the small scale displacements towards the origin of coordinates, which reflect the pre-failure deformation on part of

  14. Discussions in symposium 'neutron dosimetry in neutron fields - from detection techniques to medical applications'

    International Nuclear Information System (INIS)

    Tanimura, Y.; Sato, T.; Kumada, H.; Terunuma, T.; Sakae, T.; Harano, H.; Matsumoto, T.; Suzuki, T.; Matsufuji, N.

    2008-01-01

    Recently the traceability system (JCSS) of neutron standard based on the Japanese law 'Measurement Act' has been instituted. In addition, importance of the neutron dose evaluation has been increasing in not only the neutron capture medical treatment but also the proton or heavy particle therapy. Against such a background, a symposium 'Neutron dosimetry in neutron fields - From detection techniques to medical applications-' was held on March 29, 2008 and recent topics on the measuring instruments and their calibration, the traceability system, the simulation technique and the medical applications were introduced. This article summarizes the key points in the discussion at the symposium. (author)

  15. Sign Detection Theory and Its Applications.

    Science.gov (United States)

    Heine, M. H.

    1984-01-01

    Offers characterization of sign-transmission which is more general than conventional signal-transmission theory. Concepts and terminology, formal description of individual communications process, reconciliation with classical signal-detection theory, applications of sign-detection formalism to information retrieval on MEDLINE database, and a…

  16. Osmotic actuation for microfluidic components in point-of-care applications

    KAUST Repository

    Chen, Yu-Chih

    2013-01-01

    We present a novel design of micropumps and valves driven by osmotic force for point-of-care applications. Although there have been significant progresses in microfluidic components and control devices such as fluidic diodes, switches, resonators and digital-to-analog converters, the ultimate power source still depends on bulky off-chip components, which are expensive and cannot be easily miniaturized. For point-of-care applications, it is critical to integrate all the components in a compact size at low cost. In this work, we report two key active components actuated by osmotic mechanism for total integrated microfluidic system. For the proof of concept, we have demonstrated valve actuation, which can maintain stable ON/OFF switching operations under 125 kPa back pressure. We have also implemented an osmotic pump, which can pump a high flow rate over 30 μL/min for longer than 30 minutes. The experimental data demonstrates the possibility and potential of applying osmotic actuation in point-of-care disposable microfluidics. © 2013 IEEE.

  17. Temperature Modulation with Specified Detection Point on Metal Oxide Semiconductor Gas Sensors for E-Nose Application

    Directory of Open Access Journals (Sweden)

    Arief SUDARMAJI

    2015-03-01

    Full Text Available Temperature modulation technique, some called dynamic measurement mode, on Metal-Oxide Semiconductor (MOS/MOX gas sensor has been widely observed and employed in many fields. We present its development, a Specified Detection Point (SDP on modulated sensing element of MOS sensor is applied which associated to its temperature modulation, temperature modulation-SDP so-named. We configured the rectangular modulation signal for MOS gas sensors (TGSs and FISs using PSOC CY8C28445-24PVXI (Programmable System on Chip which also functioned as acquisition unit and interface to a computer. Initial responses and selectivity evaluations were performed using statistical tool and Principal Component Analysis (PCA to differ sample gases (Toluene, Ethanol and Ammonia on dynamic chamber measurement under various frequencies (0.25 Hz, 1 Hz, 4 Hz and duty-cycles (25 %, 50 %, 75 %. We found that at lower frequency the response waveform of the sensors becomes more sloping and distinct, and selected modulations successfully increased the selectivity either on singular or array sensors rather than static temperature measurement.

  18. Program computes single-point failures in critical system designs

    Science.gov (United States)

    Brown, W. R.

    1967-01-01

    Computer program analyzes the designs of critical systems that will either prove the design is free of single-point failures or detect each member of the population of single-point failures inherent in a system design. This program should find application in the checkout of redundant circuits and digital systems.

  19. A miniaturised image based fluorescence detection system for point-of-care-testing of cocaine abuse

    Science.gov (United States)

    Walczak, Rafał; Krüger, Jan; Moynihan, Shane

    2015-08-01

    In this paper, we describe a miniaturised image-based fluorescence detection system and demonstrate its viability as a highly sensitive tool for point-of-care-analysis of drugs of abuse in human sweat with a focus on monitor individuals for drugs of abuse. Investigations of miniaturised and low power optoelectronic configurations and methodologies for real-time image analysis were successfully carried out. The miniaturised fluorescence detection system was validated against a reference detection system under controlled laboratory conditions by analysing spiked sweat samples in dip stick and then strip with sample pad. As a result of the validation studies, a 1 ng mL-1 limit of detection of cocaine in sweat and full agreement of test results with the reference detection system can be reported. Results of the investigations open the way towards a detection system that integrates a hand-held fluorescence reader and a wearable skinpatch, and which can collect and in situ analyse sweat for the presence of cocaine at any point for up to tenths hours.

  20. Detection of gaseous heavy water leakage points in CANDU 6 pressurized heavy water reactors

    International Nuclear Information System (INIS)

    Park, T-K.; Jung, S-H.

    1996-01-01

    During reactor operation, the heavy water filled primary coolant system in a CANDU 6 Pressurized Heavy Water (PHWR) may leak through routine operations of the plant via components, mechanical joints, and during inadvertent operations etc. Early detection of leak points is therefore important to maintain plant safety and economy. There are many independent systems to monitor and recover heavy water leakage in a CANDU 6 PHWR. Methodology for early detection based on operating experience from these systems, is investigated in this paper. In addition, the four symptoms of D 2 O leakage, the associated process for clarifying and verifying the leakage, and the probable points of leakage are discussed. (author)

  1. People Detection Based on Spatial Mapping of Friendliness and Floor Boundary Points for a Mobile Navigation Robot

    Directory of Open Access Journals (Sweden)

    Tsuyoshi Tasaki

    2011-01-01

    Full Text Available Navigation robots must single out partners requiring navigation and move in the cluttered environment where people walk around. Developing such robots requires two different people detections: detecting partners and detecting all moving people around the robots. For detecting partners, we design divided spaces based on the spatial relationships and sensing ranges. Mapping the friendliness of each divided space based on the stimulus from the multiple sensors to detect people calling robots positively, robots detect partners on the highest friendliness space. For detecting moving people, we regard objects’ floor boundary points in an omnidirectional image as obstacles. We classify obstacles as moving people by comparing movement of each point with robot movement using odometry data, dynamically changing thresholds to detect. Our robot detected 95.0% of partners while it stands by and interacts with people and detected 85.0% of moving people while robot moves, which was four times higher than previous methods did.

  2. KNOWLEDGE-BASED OBJECT DETECTION IN LASER SCANNING POINT CLOUDS

    Directory of Open Access Journals (Sweden)

    F. Boochs

    2012-07-01

    Full Text Available Object identification and object processing in 3D point clouds have always posed challenges in terms of effectiveness and efficiency. In practice, this process is highly dependent on human interpretation of the scene represented by the point cloud data, as well as the set of modeling tools available for use. Such modeling algorithms are data-driven and concentrate on specific features of the objects, being accessible to numerical models. We present an approach that brings the human expert knowledge about the scene, the objects inside, and their representation by the data and the behavior of algorithms to the machine. This “understanding” enables the machine to assist human interpretation of the scene inside the point cloud. Furthermore, it allows the machine to understand possibilities and limitations of algorithms and to take this into account within the processing chain. This not only assists the researchers in defining optimal processing steps, but also provides suggestions when certain changes or new details emerge from the point cloud. Our approach benefits from the advancement in knowledge technologies within the Semantic Web framework. This advancement has provided a strong base for applications based on knowledge management. In the article we will present and describe the knowledge technologies used for our approach such as Web Ontology Language (OWL, used for formulating the knowledge base and the Semantic Web Rule Language (SWRL with 3D processing and topologic built-ins, aiming to combine geometrical analysis of 3D point clouds, and specialists’ knowledge of the scene and algorithmic processing.

  3. Knowledge-Based Object Detection in Laser Scanning Point Clouds

    Science.gov (United States)

    Boochs, F.; Karmacharya, A.; Marbs, A.

    2012-07-01

    Object identification and object processing in 3D point clouds have always posed challenges in terms of effectiveness and efficiency. In practice, this process is highly dependent on human interpretation of the scene represented by the point cloud data, as well as the set of modeling tools available for use. Such modeling algorithms are data-driven and concentrate on specific features of the objects, being accessible to numerical models. We present an approach that brings the human expert knowledge about the scene, the objects inside, and their representation by the data and the behavior of algorithms to the machine. This "understanding" enables the machine to assist human interpretation of the scene inside the point cloud. Furthermore, it allows the machine to understand possibilities and limitations of algorithms and to take this into account within the processing chain. This not only assists the researchers in defining optimal processing steps, but also provides suggestions when certain changes or new details emerge from the point cloud. Our approach benefits from the advancement in knowledge technologies within the Semantic Web framework. This advancement has provided a strong base for applications based on knowledge management. In the article we will present and describe the knowledge technologies used for our approach such as Web Ontology Language (OWL), used for formulating the knowledge base and the Semantic Web Rule Language (SWRL) with 3D processing and topologic built-ins, aiming to combine geometrical analysis of 3D point clouds, and specialists' knowledge of the scene and algorithmic processing.

  4. End point detection in ion milling processes by sputter-induced optical emission spectroscopy

    International Nuclear Information System (INIS)

    Lu, C.; Dorian, M.; Tabei, M.; Elsea, A.

    1984-01-01

    The characteristic optical emission from the sputtered material during ion milling processes can provide an unambiguous indication of the presence of the specific etched species. By monitoring the intensity of a representative emission line, the etching process can be precisely terminated at an interface. Enhancement of the etching end point is possible by using a dual-channel photodetection system operating in a ratio or difference mode. The installation of the optical detection system to an existing etching chamber has been greatly facilitated by the use of optical fibers. Using a commercial ion milling system, experimental data for a number of etching processes have been obtained. The result demonstrates that sputter-induced optical emission spectroscopy offers many advantages over other techniques in detecting the etching end point of ion milling processes

  5. Glue detection based on teaching points constraint and tracking model of pixel convolution

    Science.gov (United States)

    Geng, Lei; Ma, Xiao; Xiao, Zhitao; Wang, Wen

    2018-01-01

    On-line glue detection based on machine version is significant for rust protection and strengthening in car production. Shadow stripes caused by reflect light and unevenness of inside front cover of car reduce the accuracy of glue detection. In this paper, we propose an effective algorithm to distinguish the edges of the glue and shadow stripes. Teaching points are utilized to calculate slope between the two adjacent points. Then a tracking model based on pixel convolution along motion direction is designed to segment several local rectangular regions using distance. The distance is the height of rectangular region. The pixel convolution along the motion direction is proposed to extract edges of gules in local rectangular region. A dataset with different illumination and complexity shape stripes are used to evaluate proposed method, which include 500 thousand images captured from the camera of glue gun machine. Experimental results demonstrate that the proposed method can detect the edges of glue accurately. The shadow stripes are distinguished and removed effectively. Our method achieves the 99.9% accuracies for the image dataset.

  6. INTERSECTION DETECTION BASED ON QUALITATIVE SPATIAL REASONING ON STOPPING POINT CLUSTERS

    Directory of Open Access Journals (Sweden)

    S. Zourlidou

    2016-06-01

    Full Text Available The purpose of this research is to propose and test a method for detecting intersections by analysing collectively acquired trajectories of moving vehicles. Instead of solely relying on the geometric features of the trajectories, such as heading changes, which may indicate turning points and consequently intersections, we extract semantic features of the trajectories in form of sequences of stops and moves. Under this spatiotemporal prism, the extracted semantic information which indicates where vehicles stop can reveal important locations, such as junctions. The advantage of the proposed approach in comparison with existing turning-points oriented approaches is that it can detect intersections even when not all the crossing road segments are sampled and therefore no turning points are observed in the trajectories. The challenge with this approach is that first of all, not all vehicles stop at the same location – thus, the stop-location is blurred along the direction of the road; this, secondly, leads to the effect that nearby junctions can induce similar stop-locations. As a first step, a density-based clustering is applied on the layer of stop observations and clusters of stop events are found. Representative points of the clusters are determined (one per cluster and in a last step the existence of an intersection is clarified based on spatial relational cluster reasoning, with which less informative geospatial clusters, in terms of whether a junction exists and where its centre lies, are transformed in more informative ones. Relational reasoning criteria, based on the relative orientation of the clusters with their adjacent ones are discussed for making sense of the relation that connects them, and finally for forming groups of stop events that belong to the same junction.

  7. Point-of-care detection and real-time monitoring of intravenously delivered drugs via tubing with an integrated SERS sensor.

    Science.gov (United States)

    Wu, Hsin-Yu; Cunningham, Brian T

    2014-05-21

    We demonstrate an approach for detection, identification, and kinetic monitoring of drugs flowing within tubing, through the use of a plasmonic nanodome array (PNA) surface. The PNA structures are fabricated using a low-cost nanoreplica molding process upon a flexible plastic substrate that is subsequently integrated with a flow cell that connects in series with ordinary intravenous (IV) drug delivery tubing. To investigate the potential clinical applications for point-of-care detection and real-time monitoring, we perform SERS detection of ten pharmaceutical compounds (hydrocodone, levorphanol, morphine, oxycodone, methadone, phenobarbital, dopamine, diltiazem, promethazine, and mitoxantrone). We demonstrate dose-dependent SERS signal magnitude, resulting in detection limits (ng ml(-1)) well below typical administered dosages (mg ml(-1)). Further, we show that the detected drugs are not permanently attached to the PNA surface, and thus our approach is capable of performing continuous monitoring of drug delivery as materials flow through IV tubing that is connected in series with the sensor. Finally, we demonstrate the potential co-detection of multiple drugs when they are mixed together, and show excellent reproducibility and stability of SERS measurements for periods extending at least five days. The capabilities reported here demonstrate the potential to use PNA SERS surfaces for enhancing the safety of IV drug delivery.

  8. 3D change detection at street level using mobile laser scanning point clouds and terrestrial images

    Science.gov (United States)

    Qin, Rongjun; Gruen, Armin

    2014-04-01

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

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

    Science.gov (United States)

    Suhaila, Jamaludin; Yusop, Zulkifli

    2017-06-01

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

  10. Evolvable Smartphone-Based Platforms for Point-of-Care In-Vitro Diagnostics Applications

    Science.gov (United States)

    Patou, François; AlZahra’a Alatraktchi, Fatima; Kjægaard, Claus; Dimaki, Maria; Madsen, Jan; Svendsen, Winnie E.

    2016-01-01

    The association of smart mobile devices and lab-on-chip technologies offers unprecedented opportunities for the emergence of direct-to-consumer in vitro medical diagnostics applications. Despite their clear transformative potential, obstacles remain to the large-scale disruption and long-lasting success of these systems in the consumer market. For instance, the increasing level of complexity of instrumented lab-on-chip devices, coupled to the sporadic nature of point-of-care testing, threatens the viability of a business model mainly relying on disposable/consumable lab-on-chips. We argued recently that system evolvability, defined as the design characteristic that facilitates more manageable transitions between system generations via the modification of an inherited design, can help remedy these limitations. In this paper, we discuss how platform-based design can constitute a formal entry point to the design and implementation of evolvable smart device/lab-on-chip systems. We present both a hardware/software design framework and the implementation details of a platform prototype enabling at this stage the interfacing of several lab-on-chip variants relying on current- or impedance-based biosensors. Our findings suggest that several change-enabling mechanisms implemented in the higher abstraction software layers of the system can promote evolvability, together with the design of change-absorbing hardware/software interfaces. Our platform architecture is based on a mobile software application programming interface coupled to a modular hardware accessory. It allows the specification of lab-on-chip operation and post-analytic functions at the mobile software layer. We demonstrate its potential by operating a simple lab-on-chip to carry out the detection of dopamine using various electroanalytical methods. PMID:27598208

  11. Evolvable Smartphone-Based Platforms for Point-of-Care In-Vitro Diagnostics Applications.

    Science.gov (United States)

    Patou, François; AlZahra'a Alatraktchi, Fatima; Kjægaard, Claus; Dimaki, Maria; Madsen, Jan; Svendsen, Winnie E

    2016-09-03

    The association of smart mobile devices and lab-on-chip technologies offers unprecedented opportunities for the emergence of direct-to-consumer in vitro medical diagnostics applications. Despite their clear transformative potential, obstacles remain to the large-scale disruption and long-lasting success of these systems in the consumer market. For instance, the increasing level of complexity of instrumented lab-on-chip devices, coupled to the sporadic nature of point-of-care testing, threatens the viability of a business model mainly relying on disposable/consumable lab-on-chips. We argued recently that system evolvability, defined as the design characteristic that facilitates more manageable transitions between system generations via the modification of an inherited design, can help remedy these limitations. In this paper, we discuss how platform-based design can constitute a formal entry point to the design and implementation of evolvable smart device/lab-on-chip systems. We present both a hardware/software design framework and the implementation details of a platform prototype enabling at this stage the interfacing of several lab-on-chip variants relying on current- or impedance-based biosensors. Our findings suggest that several change-enabling mechanisms implemented in the higher abstraction software layers of the system can promote evolvability, together with the design of change-absorbing hardware/software interfaces. Our platform architecture is based on a mobile software application programming interface coupled to a modular hardware accessory. It allows the specification of lab-on-chip operation and post-analytic functions at the mobile software layer. We demonstrate its potential by operating a simple lab-on-chip to carry out the detection of dopamine using various electroanalytical methods.

  12. Evolvable Smartphone-Based Platforms for Point-of-Care In-Vitro Diagnostics Applications

    Directory of Open Access Journals (Sweden)

    François Patou

    2016-09-01

    Full Text Available The association of smart mobile devices and lab-on-chip technologies offers unprecedented opportunities for the emergence of direct-to-consumer in vitro medical diagnostics applications. Despite their clear transformative potential, obstacles remain to the large-scale disruption and long-lasting success of these systems in the consumer market. For instance, the increasing level of complexity of instrumented lab-on-chip devices, coupled to the sporadic nature of point-of-care testing, threatens the viability of a business model mainly relying on disposable/consumable lab-on-chips. We argued recently that system evolvability, defined as the design characteristic that facilitates more manageable transitions between system generations via the modification of an inherited design, can help remedy these limitations. In this paper, we discuss how platform-based design can constitute a formal entry point to the design and implementation of evolvable smart device/lab-on-chip systems. We present both a hardware/software design framework and the implementation details of a platform prototype enabling at this stage the interfacing of several lab-on-chip variants relying on current- or impedance-based biosensors. Our findings suggest that several change-enabling mechanisms implemented in the higher abstraction software layers of the system can promote evolvability, together with the design of change-absorbing hardware/software interfaces. Our platform architecture is based on a mobile software application programming interface coupled to a modular hardware accessory. It allows the specification of lab-on-chip operation and post-analytic functions at the mobile software layer. We demonstrate its potential by operating a simple lab-on-chip to carry out the detection of dopamine using various electroanalytical methods.

  13. Infrared interference patterns for new capabilities in laser end point detection

    International Nuclear Information System (INIS)

    Heason, D J; Spencer, A G

    2003-01-01

    Standard laser interferometry is used in dry etch fabrication of semiconductor and MEMS devices to measure etch depth, rate and to detect the process end point. However, many wafer materials, such as silicon are absorbing at probing wavelengths in the visible, severely limiting the amount of information that can be obtained using this technique. At infrared (IR) wavelengths around 1500 nm and above, silicon is highly transparent. In this paper we describe an instrument that can be used to monitor etch depth throughout a thru-wafer etch. The provision of this information could eliminate the requirement of an 'etch stop' layer and improve the performance of fabricated devices. We have added a further new capability by using tuneable lasers to scan through wavelengths in the near IR to generate an interference pattern. Fitting a theoretical curve to this interference pattern gives in situ measurement of film thickness. Whereas conventional interferometry would only allow etch depth to be monitored in real time, we can use a pre-etch thickness measurement to terminate the etch on a remaining thickness of film material. This paper discusses the capabilities of, and the opportunities offered by, this new technique and gives examples of applications in MEMS and waveguides

  14. Fast and Robust Segmentation and Classification for Change Detection in Urban Point Clouds

    Science.gov (United States)

    Roynard, X.; Deschaud, J.-E.; Goulette, F.

    2016-06-01

    Change detection is an important issue in city monitoring to analyse street furniture, road works, car parking, etc. For example, parking surveys are needed but are currently a laborious task involving sending operators in the streets to identify the changes in car locations. In this paper, we propose a method that performs a fast and robust segmentation and classification of urban point clouds, that can be used for change detection. We apply this method to detect the cars, as a particular object class, in order to perform parking surveys automatically. A recently proposed method already addresses the need for fast segmentation and classification of urban point clouds, using elevation images. The interest to work on images is that processing is much faster, proven and robust. However there may be a loss of information in complex 3D cases: for example when objects are one above the other, typically a car under a tree or a pedestrian under a balcony. In this paper we propose a method that retain the three-dimensional information while preserving fast computation times and improving segmentation and classification accuracy. It is based on fast region-growing using an octree, for the segmentation, and specific descriptors with Random-Forest for the classification. Experiments have been performed on large urban point clouds acquired by Mobile Laser Scanning. They show that the method is as fast as the state of the art, and that it gives more robust results in the complex 3D cases.

  15. Constructing an optimal decision tree for FAST corner point detection

    KAUST Repository

    Alkhalid, Abdulaziz; Chikalov, Igor; Moshkov, Mikhail

    2011-01-01

    In this paper, we consider a problem that is originated in computer vision: determining an optimal testing strategy for the corner point detection problem that is a part of FAST algorithm [11,12]. The problem can be formulated as building a decision tree with the minimum average depth for a decision table with all discrete attributes. We experimentally compare performance of an exact algorithm based on dynamic programming and several greedy algorithms that differ in the attribute selection criterion. © 2011 Springer-Verlag.

  16. Vehicle parts detection based on Faster - RCNN with location constraints of vehicle parts feature point

    Science.gov (United States)

    Yang, Liqin; Sang, Nong; Gao, Changxin

    2018-03-01

    Vehicle parts detection plays an important role in public transportation safety and mobility. The detection of vehicle parts is to detect the position of each vehicle part. We propose a new approach by combining Faster RCNN and three level cascaded convolutional neural network (DCNN). The output of Faster RCNN is a series of bounding boxes with coordinate information, from which we can locate vehicle parts. DCNN can precisely predict feature point position, which is the center of vehicle part. We design an output strategy by combining these two results. There are two advantages for this. The quality of the bounding boxes are greatly improved, which means vehicle parts feature point position can be located more precise. Meanwhile we preserve the position relationship between vehicle parts and effectively improve the validity and reliability of the result. By using our algorithm, the performance of the vehicle parts detection improve obviously compared with Faster RCNN.

  17. Detecting Change-Point via Saddlepoint Approximations

    Institute of Scientific and Technical Information of China (English)

    Zhaoyuan LI; Maozai TIAN

    2017-01-01

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

  18. Air Conditioning Compressor Air Leak Detection by Image Processing Techniques for Industrial Applications

    Directory of Open Access Journals (Sweden)

    Pookongchai Kritsada

    2015-01-01

    Full Text Available This paper presents method to detect air leakage of an air conditioning compressor using image processing techniques. Quality of air conditioning compressor should not have air leakage. To test an air conditioning compressor leak, air is pumped into a compressor and then submerged into the water tank. If air bubble occurs at surface of the air conditioning compressor, that leakage compressor must be returned for maintenance. In this work a new method to detect leakage and search leakage point with high accuracy, fast, and precise processes was proposed. In a preprocessing procedure to detect the air bubbles, threshold and median filter techniques have been used. Connected component labeling technique is used to detect the air bubbles while blob analysis is searching technique to analyze group of the air bubbles in sequential images. The experiments are tested with proposed algorithm to determine the leakage point of an air conditioning compressor. The location of the leakage point was presented as coordinated point. The results demonstrated that leakage point during process could be accurately detected. The estimation point had error less than 5% compared to the real leakage point.

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

    Science.gov (United States)

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

    2018-03-24

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

  20. Structure and applications of point form relativistic quantum mechanics

    International Nuclear Information System (INIS)

    Klink, W.H.

    2003-01-01

    The framework of point form relativistic quantum mechanics is used to construct mass and current operators for hadronic systems with finite degree of freedom. For the point form all of the interactions are in the four-momentum operator and, since Lorentz transformations are kinematic, the theory is manifestly covariant. In the Bakamjian-Thomas version of the point form the four-momentum operator is written as a product of the four-velocity operator and mass operator, where the mass operator is the sum of free and interacting mass operators. Interacting mass operators can be constructed from vertices, matrix elements of local field operators evaluated at the space-time point zero, where the states are eigenstates of the four-velocity. Applications include the study of the spectra and widths of vector mesons, viewed as bound states of quark-antiquark pairs. Besides mass operators, current operators are needed to compute form factors. Form factors are matrix elements of current operators on mass operator eigenstates and are often calculated with one-body current operators (in the point form this is called the point form spectator approximation); but in a properly relativistic theory there must also be many-body current operators. Minimal currents needed to satisfy current conservation in the presence of hadronic interactions (called dynamically determined currents) are shown to be easily calculated in the point form. (author)

  1. SINGLE TREE DETECTION FROM AIRBORNE LASER SCANNING DATA USING A MARKED POINT PROCESS BASED METHOD

    Directory of Open Access Journals (Sweden)

    J. Zhang

    2013-05-01

    Full Text Available Tree detection and reconstruction is of great interest in large-scale city modelling. In this paper, we present a marked point process model to detect single trees from airborne laser scanning (ALS data. We consider single trees in ALS recovered canopy height model (CHM as a realization of point process of circles. Unlike traditional marked point process, we sample the model in a constraint configuration space by making use of image process techniques. A Gibbs energy is defined on the model, containing a data term which judge the fitness of the model with respect to the data, and prior term which incorporate the prior knowledge of object layouts. We search the optimal configuration through a steepest gradient descent algorithm. The presented hybrid framework was test on three forest plots and experiments show the effectiveness of the proposed method.

  2. Processing Terrain Point Cloud Data

    KAUST Repository

    DeVore, Ronald

    2013-01-10

    Terrain point cloud data are typically acquired through some form of Light Detection And Ranging sensing. They form a rich resource that is important in a variety of applications including navigation, line of sight, and terrain visualization. Processing terrain data has not received the attention of other forms of surface reconstruction or of image processing. The goal of terrain data processing is to convert the point cloud into a succinct representation system that is amenable to the various application demands. The present paper presents a platform for terrain processing built on the following principles: (i) measuring distortion in the Hausdorff metric, which we argue is a good match for the application demands, (ii) a multiscale representation based on tree approximation using local polynomial fitting. The basic elements held in the nodes of the tree can be efficiently encoded, transmitted, visualized, and utilized for the various target applications. Several challenges emerge because of the variable resolution of the data, missing data, occlusions, and noise. Techniques for identifying and handling these challenges are developed. © 2013 Society for Industrial and Applied Mathematics.

  3. Highly sensitive chemiluminescent point mutation detection by circular strand-displacement amplification reaction.

    Science.gov (United States)

    Shi, Chao; Ge, Yujie; Gu, Hongxi; Ma, Cuiping

    2011-08-15

    Single nucleotide polymorphism (SNP) genotyping is attracting extensive attentions owing to its direct connections with human diseases including cancers. Here, we have developed a highly sensitive chemiluminescence biosensor based on circular strand-displacement amplification and the separation by magnetic beads reducing the background signal for point mutation detection at room temperature. This method took advantage of both the T4 DNA ligase recognizing single-base mismatch with high selectivity and the strand-displacement reaction of polymerase to perform signal amplification. The detection limit of this method was 1.3 × 10(-16)M, which showed better sensitivity than that of most of those reported detection methods of SNP. Additionally, the magnetic beads as carrier of immobility was not only to reduce the background signal, but also may have potential apply in high through-put screening of SNP detection in human genome. Copyright © 2011 Elsevier B.V. All rights reserved.

  4. Recent Progress in Technology of Leak detection

    Energy Technology Data Exchange (ETDEWEB)

    Jung, H. K.; Kim, S. H.; Cho, J. W.; Joo, Y. S.; Yang, D. J

    2005-07-15

    It is very important to check for leakage points of fluids and gases on primary pressure boundary of nuclear power plants in order to maintain and manage various structures safely. Even though much investigation has been performed by a number of researchers, there are a lot of problems to detect the leakage under some areas to which people can not approach. In particular, it is certainly necessary to find the leakage point in order to repair and replace the pressure boundaries. In this report, the basic principle and application situations for the development of the leak detection system which can detect micro-leaks are introduced. As the technologies and performances of recent sensors have been improving, the application range of leak detection has been increasing steadily. Therefore the sensor technologies written in this report will be able to contribute to nuclear safety to detect the leakage rate and the leakage point with an on-line monitoring system in the near future.

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

    Science.gov (United States)

    Collins, Patrick; Bahr, Thomas

    2016-04-01

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

  6. Resolution of point sources of light as analyzed by quantum detection theory.

    Science.gov (United States)

    Helstrom, C. W.

    1973-01-01

    The resolvability of point sources of incoherent thermal light is analyzed by quantum detection theory in terms of two hypothesis-testing problems. In the first, the observer must decide whether there are two sources of equal radiant power at given locations, or whether there is only one source of twice the power located midway between them. In the second problem, either one, but not both, of two point sources is radiating, and the observer must decide which it is. The decisions are based on optimum processing of the electromagnetic field at the aperture of an optical instrument. In both problems the density operators of the field under the two hypotheses do not commute. The error probabilities, determined as functions of the separation of the points and the mean number of received photons, characterize the ultimate resolvability of the sources.

  7. FAST AND ROBUST SEGMENTATION AND CLASSIFICATION FOR CHANGE DETECTION IN URBAN POINT CLOUDS

    Directory of Open Access Journals (Sweden)

    X. Roynard

    2016-06-01

    Full Text Available Change detection is an important issue in city monitoring to analyse street furniture, road works, car parking, etc. For example, parking surveys are needed but are currently a laborious task involving sending operators in the streets to identify the changes in car locations. In this paper, we propose a method that performs a fast and robust segmentation and classification of urban point clouds, that can be used for change detection. We apply this method to detect the cars, as a particular object class, in order to perform parking surveys automatically. A recently proposed method already addresses the need for fast segmentation and classification of urban point clouds, using elevation images. The interest to work on images is that processing is much faster, proven and robust. However there may be a loss of information in complex 3D cases: for example when objects are one above the other, typically a car under a tree or a pedestrian under a balcony. In this paper we propose a method that retain the three-dimensional information while preserving fast computation times and improving segmentation and classification accuracy. It is based on fast region-growing using an octree, for the segmentation, and specific descriptors with Random-Forest for the classification. Experiments have been performed on large urban point clouds acquired by Mobile Laser Scanning. They show that the method is as fast as the state of the art, and that it gives more robust results in the complex 3D cases.

  8. Knee point search using cascading top-k sorting with minimized time complexity.

    Science.gov (United States)

    Wang, Zheng; Tseng, Shian-Shyong

    2013-01-01

    Anomaly detection systems and many other applications are frequently confronted with the problem of finding the largest knee point in the sorted curve for a set of unsorted points. This paper proposes an efficient knee point search algorithm with minimized time complexity using the cascading top-k sorting when a priori probability distribution of the knee point is known. First, a top-k sort algorithm is proposed based on a quicksort variation. We divide the knee point search problem into multiple steps. And in each step an optimization problem of the selection number k is solved, where the objective function is defined as the expected time cost. Because the expected time cost in one step is dependent on that of the afterwards steps, we simplify the optimization problem by minimizing the maximum expected time cost. The posterior probability of the largest knee point distribution and the other parameters are updated before solving the optimization problem in each step. An example of source detection of DNS DoS flooding attacks is provided to illustrate the applications of the proposed algorithm.

  9. Context-aware event detection smartphone application for first responders

    Science.gov (United States)

    Boddhu, Sanjay K.; Dave, Rakesh P.; McCartney, Matt; West, James A.; Williams, Robert L.

    2013-05-01

    The rise of social networking platforms like Twitter, Facebook, etc…, have provided seamless sharing of information (as chat, video and other media) among its user community on a global scale. Further, the proliferation of the smartphones and their connectivity networks has powered the ordinary individuals to share and acquire information regarding the events happening in his/her immediate vicinity in a real-time fashion. This human-centric sensed data being generated in "human-as-sensor" approach is tremendously valuable as it delivered mostly with apt annotations and ground truth that would be missing in traditional machine-centric sensors, besides high redundancy factor (same data thru multiple users). Further, when appropriately employed this real-time data can support in detecting localized events like fire, accidents, shooting, etc…, as they unfold and pin-point individuals being affected by those events. This spatiotemporal information, when made available for first responders in the event vicinity (or approaching it) can greatly assist them to make effective decisions to protect property and life in a timely fashion. In this vein, under SATE and YATE programs, the research team at AFRL Tec^Edge Discovery labs had demonstrated the feasibility of developing Smartphone applications, that can provide a augmented reality view of the appropriate detected events in a given geographical location (localized) and also provide an event search capability over a large geographic extent. In its current state, the application thru its backend connectivity utilizes a data (Text & Image) processing framework, which deals with data challenges like; identifying and aggregating important events, analyzing and correlating the events temporally and spatially and building a search enabled event database. Further, the smartphone application with its backend data processing workflow has been successfully field tested with live user generated feeds.

  10. Point-of-care testing: applications of 3D printing.

    Science.gov (United States)

    Chan, Ho Nam; Tan, Ming Jun Andrew; Wu, Hongkai

    2017-08-08

    Point-of-care testing (POCT) devices fulfil a critical need in the modern healthcare ecosystem, enabling the decentralized delivery of imperative clinical strategies in both developed and developing worlds. To achieve diagnostic utility and clinical impact, POCT technologies are immensely dependent on effective translation from academic laboratories out to real-world deployment. However, the current research and development pipeline is highly bottlenecked owing to multiple restraints in material, cost, and complexity of conventionally available fabrication techniques. Recently, 3D printing technology has emerged as a revolutionary, industry-compatible method enabling cost-effective, facile, and rapid manufacturing of objects. This has allowed iterative design-build-test cycles of various things, from microfluidic chips to smartphone interfaces, that are geared towards point-of-care applications. In this review, we focus on highlighting recent works that exploit 3D printing in developing POCT devices, underscoring its utility in all analytical steps. Moreover, we also discuss key advantages of adopting 3D printing in the device development pipeline and identify promising opportunities in 3D printing technology that can benefit global health applications.

  11. A microwave resonance dew-point hygrometer

    Science.gov (United States)

    Underwood, R. J.; Cuccaro, R.; Bell, S.; Gavioso, R. M.; Madonna Ripa, D.; Stevens, M.; de Podesta, M.

    2012-08-01

    We report the first measurements of a quasi-spherical microwave resonator used as a dew-point hygrometer. In conventional dew-point hygrometers, the condensation of water from humid gas flowing over a mirror is detected optically, and the mirror surface is then temperature-controlled to yield a stable condensed layer. In our experiments we flowed moist air from a humidity generator through a quasi-spherical resonator and detected the onset of condensation by measuring the frequency ratio of selected microwave modes. We verified the basic operation of the device over the dew-point range 9.5-13.5 °C by comparison with calibrated chilled-mirror hygrometers. These tests indicate that the microwave method may allow a quantitative estimation of the volume and thickness of the water layer which is condensed on the inner surface of the resonator. The experiments reported here are preliminary due to the limited time available for the work, but show the potential of the method for detecting not only water but a variety of other liquid or solid condensates. The robust all-metal construction should make the device appropriate for use in industrial applications over a wide range of temperatures and pressures.

  12. A microwave resonance dew-point hygrometer

    International Nuclear Information System (INIS)

    Underwood, R J; Bell, S; Stevens, M; De Podesta, M; Cuccaro, R; Gavioso, R M; Ripa, D Madonna

    2012-01-01

    We report the first measurements of a quasi-spherical microwave resonator used as a dew-point hygrometer. In conventional dew-point hygrometers, the condensation of water from humid gas flowing over a mirror is detected optically, and the mirror surface is then temperature-controlled to yield a stable condensed layer. In our experiments we flowed moist air from a humidity generator through a quasi-spherical resonator and detected the onset of condensation by measuring the frequency ratio of selected microwave modes. We verified the basic operation of the device over the dew-point range 9.5–13.5 °C by comparison with calibrated chilled-mirror hygrometers. These tests indicate that the microwave method may allow a quantitative estimation of the volume and thickness of the water layer which is condensed on the inner surface of the resonator. The experiments reported here are preliminary due to the limited time available for the work, but show the potential of the method for detecting not only water but a variety of other liquid or solid condensates. The robust all-metal construction should make the device appropriate for use in industrial applications over a wide range of temperatures and pressures. (paper)

  13. Change Analysis in Structural Laser Scanning Point Clouds: The Baseline Method.

    Science.gov (United States)

    Shen, Yueqian; Lindenbergh, Roderik; Wang, Jinhu

    2016-12-24

    A method is introduced for detecting changes from point clouds that avoids registration. For many applications, changes are detected between two scans of the same scene obtained at different times. Traditionally, these scans are aligned to a common coordinate system having the disadvantage that this registration step introduces additional errors. In addition, registration requires stable targets or features. To avoid these issues, we propose a change detection method based on so-called baselines. Baselines connect feature points within one scan. To analyze changes, baselines connecting corresponding points in two scans are compared. As feature points either targets or virtual points corresponding to some reconstructable feature in the scene are used. The new method is implemented on two scans sampling a masonry laboratory building before and after seismic testing, that resulted in damages in the order of several centimeters. The centres of the bricks of the laboratory building are automatically extracted to serve as virtual points. Baselines connecting virtual points and/or target points are extracted and compared with respect to a suitable structural coordinate system. Changes detected from the baseline analysis are compared to a traditional cloud to cloud change analysis demonstrating the potential of the new method for structural analysis.

  14. Change Analysis in Structural Laser Scanning Point Clouds: The Baseline Method

    Directory of Open Access Journals (Sweden)

    Yueqian Shen

    2016-12-01

    Full Text Available A method is introduced for detecting changes from point clouds that avoids registration. For many applications, changes are detected between two scans of the same scene obtained at different times. Traditionally, these scans are aligned to a common coordinate system having the disadvantage that this registration step introduces additional errors. In addition, registration requires stable targets or features. To avoid these issues, we propose a change detection method based on so-called baselines. Baselines connect feature points within one scan. To analyze changes, baselines connecting corresponding points in two scans are compared. As feature points either targets or virtual points corresponding to some reconstructable feature in the scene are used. The new method is implemented on two scans sampling a masonry laboratory building before and after seismic testing, that resulted in damages in the order of several centimeters. The centres of the bricks of the laboratory building are automatically extracted to serve as virtual points. Baselines connecting virtual points and/or target points are extracted and compared with respect to a suitable structural coordinate system. Changes detected from the baseline analysis are compared to a traditional cloud to cloud change analysis demonstrating the potential of the new method for structural analysis.

  15. A centrifugal microfluidic platform for point-of-care diagnostic applications

    Directory of Open Access Journals (Sweden)

    Suzanne Hugo

    2014-02-01

    Full Text Available Microfluidic systems enable precise control over tiny volumes of fluid in a compact and low-cost form, thus providing the ideal platform on which to develop point-of-care diagnostic solutions. Centrifugal microfluidic systems, also referred to as lab-on-a-disc or lab-on-a-CD systems, provide a particularly attractive solution for the implementation of microfluidic point-of-care diagnostic solutions as a result of their simple and compact instrumentation, as well as their functional diversity. Here we detail the implementation of a centrifugal microfluidic platform the first of its kind in South Africa as a foundation for the development of point-of-care diagnostic applications for which both the need and impact is great. The centrifugal microfluidic platform consists of three main components: a microfluidic disc device similar in size and shape to a CD, a system for controlling fluid flow on the device, and a system for recording the results obtained. These components have been successfully implemented and tested. Preliminary test results show that microfluidic functions such as pumping and valving of fluids can be successfully achieved, as well as the generation of monodisperse microfluidic droplets, providing a complete centrifugal microfluidic platform and the building blocks on which to develop a variety of applications, including point-of-care diagnostics. The lab-on-a-disc platform has the potential to provide new diagnostic solutions at the point-of-need in health- and industry-related areas. This paves the way for providing resource limited areas with services such as improved, decentralised health-care access or water-quality monitoring, and reduced diagnosis times at a low cost.

  16. Application of SharePoint Portal Technologies in Public Enterprises

    Directory of Open Access Journals (Sweden)

    Dragan Đokić

    2015-03-01

    Full Text Available Nowadays, systematic reforms are realized acrossmany countries. One of the characteristics of these reforms is necessity for rationalization of expenses in governmental and public enterprises. Rationalization of expenses can be achieved by more extensive application of information and communication technologies based on internet technologies and cloud computing. These systems include huge number of services, applications, resources, users and roles. At the same time, concepts of scalability, availability, ubiquity and pervasiveness need to be applied. This paper deals with application of portal technologies for enhanced content management, document management, and collaboration within public enterprises. The goal is to achieve efficient exchange of information on all hierarchical levels, as well as mechanisms of reporting and performance measurements, such as business intelligence and key performance indicators. The model is based on SharePoint portal technologies. A case study of application within the public enterprise Post of Serbia is described.

  17. Time Series UAV Image-Based Point Clouds for Landslide Progression Evaluation Applications.

    Science.gov (United States)

    Al-Rawabdeh, Abdulla; Moussa, Adel; Foroutan, Marzieh; El-Sheimy, Naser; Habib, Ayman

    2017-10-18

    Landslides are major and constantly changing threats to urban landscapes and infrastructure. It is essential to detect and capture landslide changes regularly. Traditional methods for monitoring landslides are time-consuming, costly, dangerous, and the quality and quantity of the data is sometimes unable to meet the necessary requirements of geotechnical projects. This motivates the development of more automatic and efficient remote sensing approaches for landslide progression evaluation. Automatic change detection involving low-altitude unmanned aerial vehicle image-based point clouds, although proven, is relatively unexplored, and little research has been done in terms of accounting for volumetric changes. In this study, a methodology for automatically deriving change displacement rates, in a horizontal direction based on comparisons between extracted landslide scarps from multiple time periods, has been developed. Compared with the iterative closest projected point (ICPP) registration method, the developed method takes full advantage of automated geometric measuring, leading to fast processing. The proposed approach easily processes a large number of images from different epochs and enables the creation of registered image-based point clouds without the use of extensive ground control point information or further processing such as interpretation and image correlation. The produced results are promising for use in the field of landslide research.

  18. Applications of pattern recognition techniques to online fault detection

    International Nuclear Information System (INIS)

    Singer, R.M.; Gross, K.C.; King, R.W.

    1993-01-01

    A common problem to operators of complex industrial systems is the early detection of incipient degradation of sensors and components in order to avoid unplanned outages, to orderly plan for anticipated maintenance activities and to assure continued safe operation. In such systems, there usually are a large number of sensors (upwards of several thousand is not uncommon) serving many functions, ranging from input to control systems, monitoring of safety parameters and component performance limits, system environmental conditions, etc. Although sensors deemed to measure important process conditions are generally alarmed, the alarm set points usually are just high-low limits and the operator's response to such alarms is based on written procedures and his or her experience and training. In many systems this approach has been successful, but in situations where the cost of a forced outage is high an improved method is needed. In such cases it is desirable, if not necessary, to detect disturbances in either sensors or the process prior to any actual failure that could either shut down the process or challenge any safety system that is present. Recent advances in various artificial intelligence techniques have provided the opportunity to perform such functions of early detection and diagnosis. In this paper, the experience gained through the application of several pattern-recognition techniques to the on-line monitoring and incipient disturbance detection of several coolant pumps and numerous sensors at the Experimental Breeder Reactor-II (EBR-II) which is located at the Idaho National Engineering Laboratory is presented

  19. A density based algorithm to detect cavities and holes from planar points

    Science.gov (United States)

    Zhu, Jie; Sun, Yizhong; Pang, Yueyong

    2017-12-01

    Delaunay-based shape reconstruction algorithms are widely used in approximating the shape from planar points. However, these algorithms cannot ensure the optimality of varied reconstructed cavity boundaries and hole boundaries. This inadequate reconstruction can be primarily attributed to the lack of efficient mathematic formulation for the two structures (hole and cavity). In this paper, we develop an efficient algorithm for generating cavities and holes from planar points. The algorithm yields the final boundary based on an iterative removal of the Delaunay triangulation. Our algorithm is mainly divided into two steps, namely, rough and refined shape reconstructions. The rough shape reconstruction performed by the algorithm is controlled by a relative parameter. Based on the rough result, the refined shape reconstruction mainly aims to detect holes and pure cavities. Cavity and hole are conceptualized as a structure with a low-density region surrounded by the high-density region. With this structure, cavity and hole are characterized by a mathematic formulation called as compactness of point formed by the length variation of the edges incident to point in Delaunay triangulation. The boundaries of cavity and hole are then found by locating a shape gradient change in compactness of point set. The experimental comparison with other shape reconstruction approaches shows that the proposed algorithm is able to accurately yield the boundaries of cavity and hole with varying point set densities and distributions.

  20. Aerial Neutron Detection: Neutron Signatures for Nonproliferation and Emergency Response Applications

    Energy Technology Data Exchange (ETDEWEB)

    Maurer, Richard J.; Stampahar, Thomas G.; Smith, Ethan X.; Mukhopadhyay, Sanjoy; Wolff, Ronald S.; Rourke, Timothy J.; LeDonne, Jeffrey P.; Avaro, Emanuele; Butler, D. Andre; Borders, Kevin L.; Stampahar, Jezabel; Schuck, William H.; Selfridge, Thomas L.; McKissack, Thomas M.; Duncan, William W.; Hendricks, Thane J.

    2012-10-17

    From 2007 to the present, the Remote Sensing Laboratory has been conducting a series of studies designed to expand our fundamental understanding of aerial neutron detection with the goal of designing an enhanced sensitivity detection system for long range neutron detection. Over 35 hours of aerial measurements in a helicopter were conducted for a variety of neutron emitters such as neutron point sources, a commercial nuclear power reactor, nuclear reactor spent fuel in dry cask storage, depleted uranium hexafluoride and depleted uranium metal. The goals of the project were to increase the detection sensitivity of our instruments such that a 5.4 × 104 neutron/second source could be detected at 100 feet above ground level at a speed of 70 knots and to enhance the long-range detection sensitivity for larger neutron sources, i.e., detection ranges above 1000 feet. In order to increase the sensitivity of aerial neutron detection instruments, it is important to understand the dynamics of the neutron background as a function of altitude. For aerial neutron detection, studies have shown that the neutron background primarily originates from above the aircraft, being produced in the upper atmosphere by galactic cosmic-ray interactions with air molecules. These interactions produce energetic neutrons and charged particles that cascade to the earth’s surface, producing additional neutrons in secondary collisions. Hence, the neutron background increases as a function of altitude which is an impediment to long-range neutron detection. In order to increase the sensitivity for long range detection, it is necessary to maintain a low neutron background as a function of altitude. Initial investigations show the variation in the neutron background can be decreased with the application of a cosmic-ray shield. The results of the studies along with a representative data set are presented.

  1. Heteroduplex analysis of the dystrophin gene: Application to point mutation and carrier detection

    Energy Technology Data Exchange (ETDEWEB)

    Prior, T.W.; Papp, A.C.; Snyder, P.J.; Sedra, M.S.; Western, L.M.; Bartolo, C.; Mendell, J.R. [Ohio State Univ., Columbus, OH (United States); Moxley, R.T. [Univ. of Rochester Medical Center, NY (United States)

    1994-03-01

    Approximately one-third of Duchenne muscular dystrophy patients have undefined mutations in the dystrophin gene. For carrier and prenatal studies in families without detectable mutations, the indirect restriction fragment length polymorphism linkage approach is used. Using a multiplex amplification and heteroduplex analysis of dystrophin exons, the authors identified nonsense mutations in two DMD patients. Although the nonsense mutations are predicted to severely truncate the dystrophin protein, both patients presented with mild clinical courses of the disease. As a result of identifying the mutation in the affected boys, direct carrier studies by heteroduplex analysis were extended to other relatives. The authors conclude that the technique is not only ideal for mutation detection but is also useful for diagnostic testing. 29 refs., 4 figs.

  2. A Software Application to Detect Dental Color

    Directory of Open Access Journals (Sweden)

    Dan SÎMPĂLEAN

    2015-09-01

    Full Text Available Choosing dental color for missing teeth or tooth reconstruction is an important step and it usually raises difficulties for dentists due to a significant amount of subjective factors that can influence the color selection. Dental reconstruction presumes the combination between dentistry and chromatics, thus implying important challenges. Purpose: The aim of this study was to develop and implement a software application for detecting dental color to come to the aid of dentists and largely to remove the inherent subjectiveness of the human vision. Basic Methods: The implemented application was named Color Detection and the application’s source code is written using the C++ language. During application development, for creating the GUI (graphical user interface the wxWidgets 2.8 library it was used. Results: The application displays the average color of the selected area of interest, the reference color from the key collection existent in the program and also the degree of similarity between the original (the selected area of interest and the nearest reference key. This degree of similarity is expressed as a percentage. Conclusions: The Color Detection Program, by eliminating the subjectivity inherent to human sight, can help the dentist to select an appropriate dental color with precision.

  3. Outlier detection using autoencoders

    CERN Document Server

    Lyudchik, Olga

    2016-01-01

    Outlier detection is a crucial part of any data analysis applications. The goal of outlier detection is to separate a core of regular observations from some polluting ones, called “outliers”. We propose an outlier detection method using deep autoencoder. In our research the invented method was applied to detect outlier points in the MNIST dataset of handwriting digits. The experimental results show that the proposed method has a potential to be used for anomaly detection.

  4. Detecting cardiometabolic syndrome using World Health Organization public health action points for Asians and Pacific Islanders.

    Science.gov (United States)

    Grandinetti, Andrew; Kaholokula, Joseph K; Mau, Marjorie K; Chow, Dominic C

    2010-01-01

    To assess the screening characteristics of World Health Organization (WHO) body mass index action points for cardiometabolic syndrome (CMS) in Native Hawaiians and people of Asian ancestry (ie, Filipino and Japanese). Cross-sectional data were collected from 1,452 residents of a rural community of Hawai'i between 1997 and 2000, of which 1,198 were analyzed in this study. Ethnic ancestry was determined by self-report. Metabolic status was assessed using National Cholesterol Education Program Adult Treatment Panel III (NCEP-ATPIII) criteria. Screening characteristics of WHO criteria for overweight and obesity were compared to WHO public health action points or to WHO West Pacific Regional Office (WPRO) cut-points. Among Asian-ancestry participants, WHO public health action points improved both sensitivity and specificity for detecting CMS. However, similar improvements were not observed for WPRO criteria for Native Hawaiians. Moreover, predictive values were high regardless of which criteria were utilized due to high CMS prevalence. WHO public health actions points for Asians provide a significant improvement in sensitivity in detection of CMS. However, predictive value, which varies greatly with disease prevalence, should be considered when deciding which criteria to apply.

  5. Applications of multiple change point detections to monthly streamflow and rainfall in Xijiang River in southern China, part II: trend and mean

    Science.gov (United States)

    Chen, Yongqin David; Jiang, Jianmin; Zhu, Yuxiang; Huang, Changxing; Zhang, Qiang

    2018-05-01

    This article, as part II, illustrates applications of other two algorithms, i.e., the scanning F test of change points in trend and the scanning t test of change points in mean, to both series of the normalized streamflow index (NSI) at Makou section in the Xijiang River and the normalized precipitation index (NPI) over the watershed of Xijiang River. The results from these two tests show mainly positive coherency of changes between the NSI and NPI. However, some minor negative coherency patches may expose somewhat impacts of human activities, but they were often associated with nearly normal climate periods. These suggest that the runoff still depends upon well the precipitation in the Xijiang catchment. The anthropogenic disturbances have not yet reached up to violating natural relationship on the whole in this river.

  6. Model-based decoding, information estimation, and change-point detection techniques for multineuron spike trains.

    Science.gov (United States)

    Pillow, Jonathan W; Ahmadian, Yashar; Paninski, Liam

    2011-01-01

    One of the central problems in systems neuroscience is to understand how neural spike trains convey sensory information. Decoding methods, which provide an explicit means for reading out the information contained in neural spike responses, offer a powerful set of tools for studying the neural coding problem. Here we develop several decoding methods based on point-process neural encoding models, or forward models that predict spike responses to stimuli. These models have concave log-likelihood functions, which allow efficient maximum-likelihood model fitting and stimulus decoding. We present several applications of the encoding model framework to the problem of decoding stimulus information from population spike responses: (1) a tractable algorithm for computing the maximum a posteriori (MAP) estimate of the stimulus, the most probable stimulus to have generated an observed single- or multiple-neuron spike train response, given some prior distribution over the stimulus; (2) a gaussian approximation to the posterior stimulus distribution that can be used to quantify the fidelity with which various stimulus features are encoded; (3) an efficient method for estimating the mutual information between the stimulus and the spike trains emitted by a neural population; and (4) a framework for the detection of change-point times (the time at which the stimulus undergoes a change in mean or variance) by marginalizing over the posterior stimulus distribution. We provide several examples illustrating the performance of these estimators with simulated and real neural data.

  7. Synthesis and applications of magnetic nanoparticles for biorecognition and point of care medical diagnostics

    International Nuclear Information System (INIS)

    Sandhu, Adarsh; Handa, Hiroshi; Abe, Masanori

    2010-01-01

    ' by nanometer sized 'target beads', enabling the detection of small concentrations of beads as small as 8 nm in 'pumpless' microcapillary systems. Finally, we describe a 'label-less homogeneous' procedure referred to as 'magneto-optical transmission (MT) sensing', where the optical transmission of a solution containing rotating linear chains of magnetic nanobeads was used to detect biomolecules with pM-level sensitivity with a dynamic range of more than four orders of magnitude. Our research on the synthesis and applications of nanoparticles is particularly suitable for point of care diagnostics. (topical review)

  8. 75 FR 27119 - ViewPoint Financial Group, Inc., Plano, Texas; Approval of Conversion Application

    Science.gov (United States)

    2010-05-13

    ..., 2010, the Office of Thrift Supervision approved the application of ViewPoint MHC and ViewPoint Bank... DEPARTMENT OF THE TREASURY Office of Thrift Supervision [AC-37: OTS No. H-47111] ViewPoint... Carpenter Freeway, Suite 500, Irving, Texas 75062-2326. Dated: May 7, 2010. By the Office of Thrift...

  9. Asymmetrical floating point array processors, their application to exploration and exploitation

    Energy Technology Data Exchange (ETDEWEB)

    Geriepy, B L

    1983-01-01

    An asymmetrical floating point array processor is a special-purpose scientific computer which operates under asymmetrical control of a host computer. Although an array processor can receive fixed point input and produce fixed point output, its primary mode of operation is floating point. The first generation of array processors was oriented towards time series information. The next generation of array processors has proved much more versatile and their applicability ranges from petroleum reservoir simulation to speech syntheses. Array processors are becoming commonplace in mining, the primary usage being construction of grids-by usual methods or by kriging. The Australian mining community is among the world's leaders in regard to computer-assisted exploration and exploitation systems. Part of this leadership role must be providing guidance to computer vendors in regard to current and future requirements.

  10. The resolution of point sources of light as analyzed by quantum detection theory

    Science.gov (United States)

    Helstrom, C. W.

    1972-01-01

    The resolvability of point sources of incoherent light is analyzed by quantum detection theory in terms of two hypothesis-testing problems. In the first, the observer must decide whether there are two sources of equal radiant power at given locations, or whether there is only one source of twice the power located midway between them. In the second problem, either one, but not both, of two point sources is radiating, and the observer must decide which it is. The decisions are based on optimum processing of the electromagnetic field at the aperture of an optical instrument. In both problems the density operators of the field under the two hypotheses do not commute. The error probabilities, determined as functions of the separation of the points and the mean number of received photons, characterize the ultimate resolvability of the sources.

  11. Entropy-Based Application Layer DDoS Attack Detection Using Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    Khundrakpam Johnson Singh

    2016-10-01

    Full Text Available Distributed denial-of-service (DDoS attack is one of the major threats to the web server. The rapid increase of DDoS attacks on the Internet has clearly pointed out the limitations in current intrusion detection systems or intrusion prevention systems (IDS/IPS, mostly caused by application-layer DDoS attacks. Within this context, the objective of the paper is to detect a DDoS attack using a multilayer perceptron (MLP classification algorithm with genetic algorithm (GA as learning algorithm. In this work, we analyzed the standard EPA-HTTP (environmental protection agency-hypertext transfer protocol dataset and selected the parameters that will be used as input to the classifier model for differentiating the attack from normal profile. The parameters selected are the HTTP GET request count, entropy, and variance for every connection. The proposed model can provide a better accuracy of 98.31%, sensitivity of 0.9962, and specificity of 0.0561 when compared to other traditional classification models.

  12. Test sensitivity is important for detecting variability in pointing comprehension in canines.

    Science.gov (United States)

    Pongrácz, Péter; Gácsi, Márta; Hegedüs, Dorottya; Péter, András; Miklósi, Adám

    2013-09-01

    Several articles have been recently published on dogs' (Canis familiaris) performance in two-way object choice experiments in which subjects had to find hidden food by utilizing human pointing. The interpretation of results has led to a vivid theoretical debate about the cognitive background of human gestural signal understanding in dogs, despite the fact that many important details of the testing method have not yet been standardized. We report three experiments that aim to reveal how some procedural differences influence adult companion dogs' performance in these tests. Utilizing a large sample in Experiment 1, we provide evidence that neither the keeping conditions (garden/house) nor the location of the testing (outdoor/indoor) affect a dogs' performance. In Experiment 2, we compare dogs' performance using three different types of pointing gestures. Dogs' performance varied between momentary distal and momentary cross-pointing but "low" and "high" performer dogs chose uniformly better than chance level if they responded to sustained pointing gestures with reinforcement (food reward and a clicking sound; "clicker pointing"). In Experiment 3, we show that single features of the aforementioned "clicker pointing" method can slightly improve dogs' success rate if they were added one by one to the momentary distal pointing method. These results provide evidence that although companion dogs show a robust performance at different testing locations regardless of their keeping conditions, the exact execution of the human gesture and additional reinforcement techniques have substantial effect on the outcomes. Consequently, researchers should standardize their methodology before engaging in debates on the comparative aspects of socio-cognitive skills because the procedures they utilize may differ in sensitivity for detecting differences.

  13. Technical Reviews on the Radioisotope Application for Leak Detection in Reservoirs

    International Nuclear Information System (INIS)

    Kim, Jin Seop; Jung, Sung Hee; Kim, Jong Bum; Kim, Jae Ho

    2006-02-01

    The previous techniques on the detection of leaks from reservoirs are difficult to identify the leak points and leak pathways in reservoirs. Additionally the complexity and ambiguity of data analysis resulted from them can increase the failures of leak detection. While, The technique using radioisotope as a tracer is considered to be very promising. In the same context, systematic studies led by IAEA are being practiced by organizing the task force team. The detection technique using natural tracer can give information about the age of ground water and the interconnection between ground water and reservoir water and the seepage origin. On the other hand, the one using artificial tracer can identify the leak point in reservoirs directly, in which radioactive cloud migration method and radioactive tracer adsorption method are included. The former is using hydrophilic radioisotope tracer, and the latter adsorptive radioisotope tracer which is emitting gamma ray. The radiotracer are injected at a point of the reservoir near to the bottom. Afterwards, the migration of the radioactive tracer is followed by means of submerged scintillation detectors suspended from boats. Usually 131 I, 82 Br, 46 Sc, and 198 Au etc. can be used as tracer. The point reaching the maximum concentration of tracer corresponds to the leak point in reservoirs

  14. Technical Reviews on the Radioisotope Application for Leak Detection in Reservoirs

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Jin Seop; Jung, Sung Hee; Kim, Jong Bum; Kim, Jae Ho

    2006-02-15

    The previous techniques on the detection of leaks from reservoirs are difficult to identify the leak points and leak pathways in reservoirs. Additionally the complexity and ambiguity of data analysis resulted from them can increase the failures of leak detection. While, The technique using radioisotope as a tracer is considered to be very promising. In the same context, systematic studies led by IAEA are being practiced by organizing the task force team. The detection technique using natural tracer can give information about the age of ground water and the interconnection between ground water and reservoir water and the seepage origin. On the other hand, the one using artificial tracer can identify the leak point in reservoirs directly, in which radioactive cloud migration method and radioactive tracer adsorption method are included. The former is using hydrophilic radioisotope tracer, and the latter adsorptive radioisotope tracer which is emitting gamma ray. The radiotracer are injected at a point of the reservoir near to the bottom. Afterwards, the migration of the radioactive tracer is followed by means of submerged scintillation detectors suspended from boats. Usually {sup 131}I, {sup 82}Br, {sup 46}Sc, and {sup 198}Au etc. can be used as tracer. The point reaching the maximum concentration of tracer corresponds to the leak point in reservoirs.

  15. Automatic detection of measurement points for non-contact vibrometer-based diagnosis of cardiac arrhythmias

    Science.gov (United States)

    Metzler, Jürgen; Kroschel, Kristian; Willersinn, Dieter

    2017-03-01

    Monitoring of the heart rhythm is the cornerstone of the diagnosis of cardiac arrhythmias. It is done by means of electrocardiography which relies on electrodes attached to the skin of the patient. We present a new system approach based on the so-called vibrocardiogram that allows an automatic non-contact registration of the heart rhythm. Because of the contactless principle, the technique offers potential application advantages in medical fields like emergency medicine (burn patient) or premature baby care where adhesive electrodes are not easily applicable. A laser-based, mobile, contactless vibrometer for on-site diagnostics that works with the principle of laser Doppler vibrometry allows the acquisition of vital functions in form of a vibrocardiogram. Preliminary clinical studies at the Klinikum Karlsruhe have shown that the region around the carotid artery and the chest region are appropriate therefore. However, the challenge is to find a suitable measurement point in these parts of the body that differs from person to person due to e. g. physiological properties of the skin. Therefore, we propose a new Microsoft Kinect-based approach. When a suitable measurement area on the appropriate parts of the body are detected by processing the Kinect data, the vibrometer is automatically aligned on an initial location within this area. Then, vibrocardiograms on different locations within this area are successively acquired until a sufficient measuring quality is achieved. This optimal location is found by exploiting the autocorrelation function.

  16. Nanomaterials application in electrochemical detection of heavy metals

    International Nuclear Information System (INIS)

    Aragay, Gemma; Merkoçi, Arben

    2012-01-01

    Highlights: ► We review the recent trends in the application of nanomaterials for electrochemical detection of heavy metals. ► Different types of nanomaterials including metal nanoparticles, different carbon nanomaterials or nanochannels have been applied on the electrochemical analysis of heavy metals in various sensing formats/configurations. ► The great properties of nanomaterials allow the new devices to show advantages in terms of sensing performance (i.e. increase the sensitivity, decrease the detection limits and improve the stability). ► Between the various electrochemical techniques, voltammetric and potentiometric based ones are particularly taking interesting advantages by the incorporation of new nanomaterials due to the improved electrocatalytic properties beside the increase of the sensor's transducing area. - Abstract: Recent trends in the application of nanomaterials for electrochemical detection of heavy metals are shown. Various nanomaterials such as nanoparticles, nanowires, nanotubes, nanochannels, graphene, etc. have been explored either as modifiers of electrodes or as new electrode materials with interest to be applied in electrochemical stripping analysis, ion-selective detection, field-effect transistors or other indirect heavy metals (bio)detection alternatives. The developed devices have shown increased sensitivity and decreased detection limits between other improvements of analytical performance data. The phenomena behind nanomaterials responses are also discussed and some typical responses data of the developed systems either in standard solutions or in real samples are given. The developed nanomaterials based electrochemical systems are giving new inputs to the existing devices or leading to the development of novel heavy metal detection tools with interest for applications in field such as diagnostics, environmental and safety and security controls or other industries.

  17. Potentiometric end point detection in the EDTA titrimetric determination of gallium

    International Nuclear Information System (INIS)

    Gopinath, N.; Renuka, M.; Aggarwal, S.K.

    2001-01-01

    Gallium is titrated in presence of known amount of Fe (III) with EDTA in HNO 3 solution at pH 2 to 3. The end point is detected potentiometrically employing a bright platinum wire - saturated calomel (SCE) reference electrode system, the redox couple being Fe (III) / Fe (II). Since Fe (III) is also titrated by EDTA, it is, therefore, subtracted from titre value to get the EDTA equivalent to gallium only. Precision and accuracy 0.2 to 0.4% was obtained in the results of gallium in the range of 8 to 2 mg. (author)

  18. Mobile/android application for QRS detection using zero cross method

    Science.gov (United States)

    Rizqyawan, M. I.; Simbolon, A. I.; Suhendra, M. A.; Amri, M. F.; Kusumandari, D. E.

    2018-03-01

    In automatic ECG signal processing, one of the main topics of research is QRS complex detection. Detecting correct QRS complex or R peak is important since it is used to measure several other ECG metrics. One of the robust methods for QRS detection is Zero Cross method. This method uses an addition of high-frequency signal and zero crossing count to detect QRS complex which has a low-frequency oscillation. This paper presents an application of QRS detection using Zero Cross algorithm in the Android-based system. The performance of the algorithm in the mobile environment is measured. The result shows that this method is suitable for real-time QRS detection in a mobile application.

  19. Parametric change point estimation, testing and confidence interval ...

    African Journals Online (AJOL)

    In many applications like finance, industry and medicine, it is important to consider that the model parameters may undergo changes at unknown moment in time. This paper deals with estimation, testing and confidence interval of a change point for a univariate variable which is assumed to be normally distributed. To detect ...

  20. A feasibility study of stateful automaton packet inspection for streaming application detection systems

    Science.gov (United States)

    Tseng, Kuo-Kun; Lo, Jiao; Liu, Yiming; Chang, Shih-Hao; Merabti, Madjid; Ng, Felix, C. K.; Wu, C. H.

    2017-10-01

    The rapid development of the internet has brought huge benefits and social impacts; however, internet security has also become a great problem for users, since traditional approaches to packet classification cannot achieve satisfactory detection performance due to their low accuracy and efficiency. In this paper, a new stateful packet inspection method is introduced, which can be embedded in the network gateway and used by a streaming application detection system. This new detection method leverages the inexact automaton approach, using part of the header field and part of the application layer data of a packet. Based on this approach, an advanced detection system is proposed for streaming applications. The workflow of the system involves two stages: the training stage and the detection stage. In the training stage, the system initially captures characteristic patterns from a set of application packet flows. After this training is completed, the detection stage allows the user to detect the target application by capturing new application flows. This new detection approach is also evaluated using experimental analysis; the results of this analysis show that this new approach not only simplifies the management of the state detection system, but also improves the accuracy of data flow detection, making it feasible for real-world network applications.

  1. Application of 3D Laser Scanning Technology in Inspection and Dynamic Reserves Detection of Open-Pit Mine

    Science.gov (United States)

    Hu, Zhumin; Wei, Shiyu; Jiang, Jun

    2017-10-01

    The traditional open-pit mine mining rights verification and dynamic reserve detection means rely on the total station and RTK to collect the results of the turning point coordinates of mining surface contours. It resulted in obtaining the results of low precision and large error in the means that is limited by the traditional measurement equipment accuracy and measurement methods. The three-dimensional scanning technology can obtain the three-dimensional coordinate data of the surface of the measured object in a large area at high resolution. This paper expounds the commonly used application of 3D scanning technology in the inspection and dynamic reserve detection of open mine mining rights.

  2. SQUID sensor application for small metallic particle detection

    International Nuclear Information System (INIS)

    Tanaka, Saburo; Hatsukade, Yoshimi; Ohtani, Takeyoshi; Suzuki, Shuichi

    2009-01-01

    High-Tc superconducting quantum interference device (SQUID) is an ultra-sensitive magnetic sensor. Since the performance of the SQUID is improved and stabilized, now it is ready for application. One strong candidate for application is a detection system of magnetic foreign matters in industrial products or beverages. There is a possibility that ultra-small metallic foreign matter has been accidentally mixed with industrial products such as lithium ion batteries. If this happens, the manufacturer of the product suffers a great loss recalling products. The outer dimension of metallic particles less than 100 μm cannot be detected by an X-ray imaging, which is commonly used for the inspection. Ionization of the material is also a big issue for beverages in the case of the X-ray imaging. Therefore a highly sensitive and safety detection system for small foreign matters is required. We developed detection systems based on high-Tc SQUID with a high-performance magnetic shield. We could successfully measure small iron particles of 100 μm on a belt conveyer and stainless steel balls of 300 μm in water. These detection levels were hard to be achieved by a conventional X-ray detection or other methods

  3. Interior intrusion detection systems

    Energy Technology Data Exchange (ETDEWEB)

    Rodriguez, J.R.; Matter, J.C. (Sandia National Labs., Albuquerque, NM (United States)); Dry, B. (BE, Inc., Barnwell, SC (United States))

    1991-10-01

    The purpose of this NUREG is to present technical information that should be useful to NRC licensees in designing interior intrusion detection systems. Interior intrusion sensors are discussed according to their primary application: boundary-penetration detection, volumetric detection, and point protection. Information necessary for implementation of an effective interior intrusion detection system is presented, including principles of operation, performance characteristics and guidelines for design, procurement, installation, testing, and maintenance. A glossary of sensor data terms is included. 36 figs., 6 tabs.

  4. Interior intrusion detection systems

    International Nuclear Information System (INIS)

    Rodriguez, J.R.; Matter, J.C.; Dry, B.

    1991-10-01

    The purpose of this NUREG is to present technical information that should be useful to NRC licensees in designing interior intrusion detection systems. Interior intrusion sensors are discussed according to their primary application: boundary-penetration detection, volumetric detection, and point protection. Information necessary for implementation of an effective interior intrusion detection system is presented, including principles of operation, performance characteristics and guidelines for design, procurement, installation, testing, and maintenance. A glossary of sensor data terms is included. 36 figs., 6 tabs

  5. Applicability estimation of flowmeter logging for detecting hydraulic pass

    International Nuclear Information System (INIS)

    Miyakawa, Kimio; Tanaka, Yasuji; Tanaka, Kazuhiro

    1997-01-01

    Estimation of the hydraulic pass governing hydrogeological structure contributes significantly to the siting HLW repository. Flowmeter logging can detect hydraulic passes by measuring vertical flow velocity of groundwater in the borehole. We reviewed application of this logging in situ. The hydraulic pass was detected with combination of ambient flow logging, with pumping and/or injecting induced flow logging. This application showed that the flowmeter logging detected hydraulic passes conveniently and accurately compared with other hydraulic tests. Hydraulic conductivity by using flowmeter logging was assessed above 10 -6 m/sec and within one order from comparison with injection packer tests. We suggest that appropriate application of the flowmeter logging for the siting is conducted before hydraulic tests because test sections and monitoring sections are decided rationally for procurement of quantitative hydraulic data. (author)

  6. Detecting changes in real-time data: a user's guide to optimal detection.

    Science.gov (United States)

    Johnson, P; Moriarty, J; Peskir, G

    2017-08-13

    The real-time detection of changes in a noisily observed signal is an important problem in applied science and engineering. The study of parametric optimal detection theory began in the 1930s, motivated by applications in production and defence. Today this theory, which aims to minimize a given measure of detection delay under accuracy constraints, finds applications in domains including radar, sonar, seismic activity, global positioning, psychological testing, quality control, communications and power systems engineering. This paper reviews developments in optimal detection theory and sequential analysis, including sequential hypothesis testing and change-point detection, in both Bayesian and classical (non-Bayesian) settings. For clarity of exposition, we work in discrete time and provide a brief discussion of the continuous time setting, including recent developments using stochastic calculus. Different measures of detection delay are presented, together with the corresponding optimal solutions. We emphasize the important role of the signal-to-noise ratio and discuss both the underlying assumptions and some typical applications for each formulation.This article is part of the themed issue 'Energy management: flexibility, risk and optimization'. © 2017 The Author(s).

  7. APPLICABILITY ANALYSIS OF CLOTH SIMULATION FILTERING ALGORITHM FOR MOBILE LIDAR POINT CLOUD

    Directory of Open Access Journals (Sweden)

    S. Cai

    2018-04-01

    Full Text Available Classifying the original point clouds into ground and non-ground points is a key step in LiDAR (light detection and ranging data post-processing. Cloth simulation filtering (CSF algorithm, which based on a physical process, has been validated to be an accurate, automatic and easy-to-use algorithm for airborne LiDAR point cloud. As a new technique of three-dimensional data collection, the mobile laser scanning (MLS has been gradually applied in various fields, such as reconstruction of digital terrain models (DTM, 3D building modeling and forest inventory and management. Compared with airborne LiDAR point cloud, there are some different features (such as point density feature, distribution feature and complexity feature for mobile LiDAR point cloud. Some filtering algorithms for airborne LiDAR data were directly used in mobile LiDAR point cloud, but it did not give satisfactory results. In this paper, we explore the ability of the CSF algorithm for mobile LiDAR point cloud. Three samples with different shape of the terrain are selected to test the performance of this algorithm, which respectively yields total errors of 0.44 %, 0.77 % and1.20 %. Additionally, large area dataset is also tested to further validate the effectiveness of this algorithm, and results show that it can quickly and accurately separate point clouds into ground and non-ground points. In summary, this algorithm is efficient and reliable for mobile LiDAR point cloud.

  8. Interior Point Methods on GPU with application to Model Predictive Control

    DEFF Research Database (Denmark)

    Gade-Nielsen, Nicolai Fog

    The goal of this thesis is to investigate the application of interior point methods to solve dynamical optimization problems, using a graphical processing unit (GPU) with a focus on problems arising in Model Predictice Control (MPC). Multi-core processors have been available for over ten years now...... software package called GPUOPT, available under the non-restrictive MIT license. GPUOPT includes includes a primal-dual interior-point method, which supports both the CPU and the GPU. It is implemented as multiple components, where the matrix operations and solver for the Newton directions is separated...

  9. Synthesis and applications of magnetic nanoparticles for biorecognition and point of care medical diagnostics

    Energy Technology Data Exchange (ETDEWEB)

    Sandhu, Adarsh [Electronics-Inspired Interdisciplinary Research Institute (EIIRIS), Toyohashi University of Technology, 1-1 Hibarigaoka, Tempaku, Toyohashi 441-8580 (Japan); Handa, Hiroshi [Integrated Research Institute, Tokyo Institute of Technology, Yokohama 226-8503 (Japan); Abe, Masanori [Department of Electrical and Electronic Engineering, Tokyo Institute of Technology, 2-12-1 O-okayama, Meguro-ku, Tokyo 152-8552 (Japan)

    2010-11-05

    sized 'probe beads' by nanometer sized 'target beads', enabling the detection of small concentrations of beads as small as 8 nm in 'pumpless' microcapillary systems. Finally, we describe a 'label-less homogeneous' procedure referred to as 'magneto-optical transmission (MT) sensing', where the optical transmission of a solution containing rotating linear chains of magnetic nanobeads was used to detect biomolecules with pM-level sensitivity with a dynamic range of more than four orders of magnitude. Our research on the synthesis and applications of nanoparticles is particularly suitable for point of care diagnostics. (topical review)

  10. A multi-analyte biosensor for the simultaneous label-free detection of pathogens and biomarkers in point-of-need animal testing.

    Science.gov (United States)

    Ewald, Melanie; Fechner, Peter; Gauglitz, Günter

    2015-05-01

    For the first time, a multi-analyte biosensor platform has been developed using the label-free 1-lambda-reflectometry technique. This platform is the first, which does not use imaging techniques, but is able to perform multi-analyte measurements. It is designed to be portable and cost-effective and therefore allows for point-of-need testing or on-site field-testing with possible applications in diagnostics. This work highlights the application possibilities of this platform in the field of animal testing, but is also relevant and transferable to human diagnostics. The performance of the platform has been evaluated using relevant reference systems like biomarker (C-reactive protein) and serology (anti-Salmonella antibodies) as well as a panel of real samples (animal sera). The comparison of the working range and limit of detection shows no loss of performance transferring the separate assays to the multi-analyte setup. Moreover, the new multi-analyte platform allows for discrimination between sera of animals infected with different Salmonella subtypes.

  11. Theory and Application of Magnetic Flux Leakage Pipeline Detection.

    Science.gov (United States)

    Shi, Yan; Zhang, Chao; Li, Rui; Cai, Maolin; Jia, Guanwei

    2015-12-10

    Magnetic flux leakage (MFL) detection is one of the most popular methods of pipeline inspection. It is a nondestructive testing technique which uses magnetic sensitive sensors to detect the magnetic leakage field of defects on both the internal and external surfaces of pipelines. This paper introduces the main principles, measurement and processing of MFL data. As the key point of a quantitative analysis of MFL detection, the identification of the leakage magnetic signal is also discussed. In addition, the advantages and disadvantages of different identification methods are analyzed. Then the paper briefly introduces the expert systems used. At the end of this paper, future developments in pipeline MFL detection are predicted.

  12. Acquisition, tracking, and pointing III; Proceedings of the Meeting, Orlando, FL, Mar. 27-29, 1989

    Science.gov (United States)

    Gowrinathan, Sankaran

    1989-09-01

    The present conference on components and sensors, image processing algorithms, and astronomical applications for pointing and tracking gives attention to a CCD daylight stellar sensor, an optical coordinate transfer assembly for precision boresight applications, a grating carousel mechanism for the HST high resolution spectrograph, an IR antiship-seeker simulator, line-of-sight stabilization using image motion compensation, the effects of illumination beam jitter on photodetection statistics, and the enhancement of armored vehicle fire control performance. Also discussed are active angular tracking with a photon-bucket, moving target estimation with autodyne detection, multiresolution object detection and segmentation, a beacon tracker and point-ahead system for optical communications, a precision-pointing mechanism for intersatellite optical communication, high-precision lunar tracking for laser ranging, multimirror beam control, and fundamental limits in the resolution of double-star targets.

  13. An effective means for damage detection of bridges using the contact-point response of a moving test vehicle

    Science.gov (United States)

    Zhang, Bin; Qian, Yao; Wu, Yuntian; Yang, Y. B.

    2018-04-01

    To further the technique of indirect measurement, the contact-point response of a moving test vehicle is adopted for the damage detection of bridges. First, the contact-point response of the vehicle moving over the bridge is derived both analytically and in central difference form (for field use). Then, the instantaneous amplitude squared (IAS) of the driving component of the contact-point response is calculated by the Hilbert transform, making use of its narrow-band feature. The IAS peaks serve as the key parameter for damage detection. In the numerical simulation, a damage (crack) is modeled by a hinge-spring unit. The feasibility of the proposed method to detect the location and severity of a damage or multi damages of the bridge is verified. Also, the effects of surface roughness, vehicle speed, measurement noise and random traffic are studied. In the presence of ongoing traffic, the damages of the bridge are identified from the repeated or invariant IAS peaks generated for different traffic flows by the same test vehicle over the bridge.

  14. Comparative Study of Outlier Detection Algorithms via Fundamental Analysis Variables: An Application on Firms Listed in Borsa Istanbul

    Directory of Open Access Journals (Sweden)

    Senol Emir

    2016-04-01

    Full Text Available In a data set, an outlier refers to a data point that is considerably different from the others. Detecting outliers provides useful application-specific insights and leads to choosing right prediction models. Outlier detection (also known as anomaly detection or novelty detection has been studied in statistics and machine learning for a long time. It is an essential preprocessing step of data mining process. In this study, outlier detection step in the data mining process is applied for identifying the top 20 outlier firms. Three outlier detection algorithms are utilized using fundamental analysis variables of firms listed in Borsa Istanbul for the 2011-2014 period. The results of each algorithm are presented and compared. Findings show that 15 different firms are identified by three different outlier detection methods. KCHOL and SAHOL have the greatest number of appearances with 12 observations among these firms. By investigating the results, it is concluded that each of three algorithms makes different outlier firm lists due to differences in their approaches for outlier detection.

  15. Anomaly Detection Based on Sensor Data in Petroleum Industry Applications

    Directory of Open Access Journals (Sweden)

    Luis Martí

    2015-01-01

    Full Text Available Anomaly detection is the problem of finding patterns in data that do not conform to an a priori expected behavior. This is related to the problem in which some samples are distant, in terms of a given metric, from the rest of the dataset, where these anomalous samples are indicated as outliers. Anomaly detection has recently attracted the attention of the research community, because of its relevance in real-world applications, like intrusion detection, fraud detection, fault detection and system health monitoring, among many others. Anomalies themselves can have a positive or negative nature, depending on their context and interpretation. However, in either case, it is important for decision makers to be able to detect them in order to take appropriate actions. The petroleum industry is one of the application contexts where these problems are present. The correct detection of such types of unusual information empowers the decision maker with the capacity to act on the system in order to correctly avoid, correct or react to the situations associated with them. In that application context, heavy extraction machines for pumping and generation operations, like turbomachines, are intensively monitored by hundreds of sensors each that send measurements with a high frequency for damage prevention. In this paper, we propose a combination of yet another segmentation algorithm (YASA, a novel fast and high quality segmentation algorithm, with a one-class support vector machine approach for efficient anomaly detection in turbomachines. The proposal is meant for dealing with the aforementioned task and to cope with the lack of labeled training data. As a result, we perform a series of empirical studies comparing our approach to other methods applied to benchmark problems and a real-life application related to oil platform turbomachinery anomaly detection.

  16. Plastic Gamma Sensors: An Application in Detection of Radioisotopes

    International Nuclear Information System (INIS)

    Mukhopadhyay, S.

    2003-01-01

    A brief survey of plastic scintillators for various radiation measurement applications is presented here. The utility of plastic scintillators for practical applications such as gamma radiation monitoring, real-time radioisotope detection and screening is evaluated in laboratory and field measurements. This study also reports results of Monte Carlo-type predictive responses of common plastic scintillators in gamma and neutron radiation fields. Small-size plastic detectors are evaluated for static and dynamic gamma-ray detection sensitivity of selected radiation sources

  17. Photonic crystals: emerging biosensors and their promise for point-of-care applications.

    Science.gov (United States)

    Inan, Hakan; Poyraz, Muhammet; Inci, Fatih; Lifson, Mark A; Baday, Murat; Cunningham, Brian T; Demirci, Utkan

    2017-01-23

    Biosensors are extensively employed for diagnosing a broad array of diseases and disorders in clinical settings worldwide. The implementation of biosensors at the point-of-care (POC), such as at primary clinics or the bedside, faces impediments because they may require highly trained personnel, have long assay times, large sizes, and high instrumental cost. Thus, there exists a need to develop inexpensive, reliable, user-friendly, and compact biosensing systems at the POC. Biosensors incorporated with photonic crystal (PC) structures hold promise to address many of the aforementioned challenges facing the development of new POC diagnostics. Currently, PC-based biosensors have been employed for detecting a variety of biotargets, such as cells, pathogens, proteins, antibodies, and nucleic acids, with high efficiency and selectivity. In this review, we provide a broad overview of PCs by explaining their structures, fabrication techniques, and sensing principles. Furthermore, we discuss recent applications of PC-based biosensors incorporated with emerging technologies, including telemedicine, flexible and wearable sensing, smart materials and metamaterials. Finally, we discuss current challenges associated with existing biosensors, and provide an outlook for PC-based biosensors and their promise at the POC.

  18. Seed Dispersal, Microsites or Competition—What Drives Gap Regeneration in an Old-Growth Forest? An Application of Spatial Point Process Modelling

    Directory of Open Access Journals (Sweden)

    Georg Gratzer

    2018-04-01

    Full Text Available The spatial structure of trees is a template for forest dynamics and the outcome of a variety of processes in ecosystems. Identifying the contribution and magnitude of the different drivers is an age-old task in plant ecology. Recently, the modelling of a spatial point process was used to identify factors driving the spatial distribution of trees at stand scales. Processes driving the coexistence of trees, however, frequently unfold within gaps and questions on the role of resource heterogeneity within-gaps have become central issues in community ecology. We tested the applicability of a spatial point process modelling approach for quantifying the effects of seed dispersal, within gap light environment, microsite heterogeneity, and competition on the generation of within gap spatial structure of small tree seedlings in a temperate, old growth, mixed-species forest. By fitting a non-homogeneous Neyman–Scott point process model, we could disentangle the role of seed dispersal from niche partitioning for within gap tree establishment and did not detect seed densities as a factor explaining the clustering of small trees. We found only a very weak indication for partitioning of within gap light among the three species and detected a clear niche segregation of Picea abies (L. Karst. on nurse logs. The other two dominating species, Abies alba Mill. and Fagus sylvatica L., did not show signs of within gap segregation.

  19. The application of hazard analysis and critical control points and risk management in the preparation of anti-cancer drugs.

    Science.gov (United States)

    Bonan, Brigitte; Martelli, Nicolas; Berhoune, Malik; Maestroni, Marie-Laure; Havard, Laurent; Prognon, Patrice

    2009-02-01

    To apply the Hazard analysis and Critical Control Points method to the preparation of anti-cancer drugs. To identify critical control points in our cancer chemotherapy process and to propose control measures and corrective actions to manage these processes. The Hazard Analysis and Critical Control Points application began in January 2004 in our centralized chemotherapy compounding unit. From October 2004 to August 2005, monitoring of the process nonconformities was performed to assess the method. According to the Hazard Analysis and Critical Control Points method, a multidisciplinary team was formed to describe and assess the cancer chemotherapy process. This team listed all of the critical points and calculated their risk indexes according to their frequency of occurrence, their severity and their detectability. The team defined monitoring, control measures and corrective actions for each identified risk. Finally, over a 10-month period, pharmacists reported each non-conformity of the process in a follow-up document. Our team described 11 steps in the cancer chemotherapy process. The team identified 39 critical control points, including 11 of higher importance with a high-risk index. Over 10 months, 16,647 preparations were performed; 1225 nonconformities were reported during this same period. The Hazard Analysis and Critical Control Points method is relevant when it is used to target a specific process such as the preparation of anti-cancer drugs. This method helped us to focus on the production steps, which can have a critical influence on product quality, and led us to improve our process.

  20. Solar thermal power systems point-focusing thermal and electric applications projects. Volume 1: Executive summary

    Science.gov (United States)

    Marriott, A.

    1980-01-01

    The activities of the Point-Focusing Thermal and Electric Applications (PETEA) project for the fiscal year 1979 are summarized. The main thrust of the PFTEA Project, the small community solar thermal power experiment, was completed. Concept definition studies included a small central receiver approach, a point-focusing distributed receiver system with central power generation, and a point-focusing distributed receiver concept with distributed power generation. The first experiment in the Isolated Application Series was initiated. Planning for the third engineering experiment series, which addresses the industrial market sector, was also initiated. In addition to the experiment-related activities, several contracts to industry were let and studies were conducted to explore the market potential for point-focusing distributed receiver (PFDR) systems. System analysis studies were completed that looked at PFDR technology relative to other small power system technology candidates for the utility market sector.

  1. The change points of HbA(1C) for detection of retinopathy in Chinese type 2 diabetic patients.

    Science.gov (United States)

    Hou, Jia-Ning; Bi, Yu-Fang; Xu, Min; Huang, Yun; Li, Xiao-Ying; Wang, Wei-Qing; Chen, Yu-Hong; Ning, Guang

    2011-03-01

    To investigate the change points of HbA(1C) for detection of retinopathy in Chinese type 2 diabetic patients. This cross-sectional investigation included 992 diagnosed type 2 diabetic patients, who received non-mydriatic digital fundus photography examination. Joinpoint regression software was adopted to identify the change points of HbA(1C) in association with retinopathy prevalence. The mean age of all patients was 59.1 ± 8.4 years and the duration of diabetes was 5.5 (95% CI: 5.2-5.9) years. The prevalence of retinopathy was 10.3% in total, and 4.1%, 7.4% and 19.6% in patients with different diabetes duration of ≤ 5 years, 5-10 years and >10 years, respectively. The change point of HbA(1C) was 6.5% (95%CI 5.8-7.5%), at which retinopathy prevalence began to rise sharply. Furthermore, in subjects with diabetes duration ≤ 5 years, 5-10 years and >10 years, the change points of HbA(1C) were 8.1% (95%CI 7.9-8.3%), 6.1% (95%CI 5.7-6.8%), 5.6% (95%CI 5.1-8.1%) for detection of retinopathy, respectively. The steepest increase in retinopathy prevalence occurred when HbA(1C) reached 6.5%. However, the duration of diabetes should be taken into concern, when using the change points of HbA(1C) for detection of retinopathy in diabetic patients. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

  2. Point-point and point-line moving-window correlation spectroscopy and its applications

    Science.gov (United States)

    Zhou, Qun; Sun, Suqin; Zhan, Daqi; Yu, Zhiwu

    2008-07-01

    In this paper, we present a new extension of generalized two-dimensional (2D) correlation spectroscopy. Two new algorithms, namely point-point (P-P) correlation and point-line (P-L) correlation, have been introduced to do the moving-window 2D correlation (MW2D) analysis. The new method has been applied to a spectral model consisting of two different processes. The results indicate that P-P correlation spectroscopy can unveil the details and re-constitute the entire process, whilst the P-L can provide general feature of the concerned processes. Phase transition behavior of dimyristoylphosphotidylethanolamine (DMPE) has been studied using MW2D correlation spectroscopy. The newly proposed method verifies that the phase transition temperature is 56 °C, same as the result got from a differential scanning calorimeter. To illustrate the new method further, a lysine and lactose mixture has been studied under thermo perturbation. Using the P-P MW2D, the Maillard reaction of the mixture was clearly monitored, which has been very difficult using conventional display of FTIR spectra.

  3. Detection of uterine MMG contractions using a multiple change point estimator and the K-means cluster algorithm.

    Science.gov (United States)

    La Rosa, Patricio S; Nehorai, Arye; Eswaran, Hari; Lowery, Curtis L; Preissl, Hubert

    2008-02-01

    We propose a single channel two-stage time-segment discriminator of uterine magnetomyogram (MMG) contractions during pregnancy. We assume that the preprocessed signals are piecewise stationary having distribution in a common family with a fixed number of parameters. Therefore, at the first stage, we propose a model-based segmentation procedure, which detects multiple change-points in the parameters of a piecewise constant time-varying autoregressive model using a robust formulation of the Schwarz information criterion (SIC) and a binary search approach. In particular, we propose a test statistic that depends on the SIC, derive its asymptotic distribution, and obtain closed-form optimal detection thresholds in the sense of the Neyman-Pearson criterion; therefore, we control the probability of false alarm and maximize the probability of change-point detection in each stage of the binary search algorithm. We compute and evaluate the relative energy variation [root mean squares (RMS)] and the dominant frequency component [first order zero crossing (FOZC)] in discriminating between time segments with and without contractions. The former consistently detects a time segment with contractions. Thus, at the second stage, we apply a nonsupervised K-means cluster algorithm to classify the detected time segments using the RMS values. We apply our detection algorithm to real MMG records obtained from ten patients admitted to the hospital for contractions with gestational ages between 31 and 40 weeks. We evaluate the performance of our detection algorithm in computing the detection and false alarm rate, respectively, using as a reference the patients' feedback. We also analyze the fusion of the decision signals from all the sensors as in the parallel distributed detection approach.

  4. Towards Detection and Diagnosis of Ebola Virus Disease at Point-of-Care

    Science.gov (United States)

    Kaushik, Ajeet; Tiwari, Sneham; Jayant, Rahul Dev; Marty, Aileen; Nair, Madhavan

    2015-01-01

    Ebola outbreak-2014 (mainly Zaire strain related Ebola virus) has been declared most widely spread deadly persistent epidemic due to unavailability of rapid diagnostic, detection, and therapeutics. Ebola virus disease (EVD), a severe viral hemorrhagic fever syndrome caused by Ebola virus (EBOV) is transmitted by direct contact with the body fluids of infected person and objects contaminated with virus or infected animals. World Health Organization (WHO) has declared EVD epidemic as public health emergency of international concern with severe global economic burden. At fatal EBOV infection stage, patients usually die before the antibody response. Currently, rapid blood tests to diagnose EBOV infection include the antigen or antibodies capture using ELISA and RNA detection using RT/Q-PCR within 3–10 days after the onset of symptoms. Moreover, few nanotechnology-based colorimetric and paper-based immunoassay methods have been recently reported to detect Ebola virus. Unfortunately, these methods are limited to laboratory only. As state-of-the art (SoA) diagnostics time to confirm Ebola infection, varies from 6 hours to about 3 days, it causes delay in therapeutic approaches. Thus developing a cost-effective, rapid, sensitive, and selective sensor to detect EVD at point-of-care (POC) is certainly worth exploring to establish rapid diagnostics to decide therapeutics. This review highlights SoA of Ebola diagnostics and also a call to develop rapid, selective and sensitive POC detection of EBOV for global health care. We propose that adopting miniaturized electrochemical EBOV immunosensing can detect virus level at pM concentration within ~40 minute compared to 3 days of ELISA test at nM levels. PMID:26319169

  5. A Review of Point-Wise Motion Tracking Algorithms for Fetal Magnetic Resonance Imaging.

    Science.gov (United States)

    Chikop, Shivaprasad; Koulagi, Girish; Kumbara, Ankita; Geethanath, Sairam

    2016-01-01

    We review recent feature-based tracking algorithms as applied to fetal magnetic resonance imaging (MRI). Motion in fetal MRI is an active and challenging area of research, but the challenge can be mitigated by strategies related to patient setup, acquisition, reconstruction, and image processing. We focus on fetal motion correction through methods based on tracking algorithms for registration of slices with similar anatomy in multiple volumes. We describe five motion detection algorithms based on corner detection and region-based methods through pseudocodes, illustrating the results of their application to fetal MRI. We compare the performance of these methods on the basis of error in registration and minimum number of feature points required for registration. Harris, a corner detection method, provides similar error when compared to the other methods and has the lowest number of feature points required at that error level. We do not discuss group-wise methods here. Finally, we attempt to communicate the application of available feature extraction methods to fetal MRI.

  6. DTM GENERATION WITH UAV BASED PHOTOGRAMMETRIC POINT CLOUD

    Directory of Open Access Journals (Sweden)

    N. Polat

    2017-11-01

    Full Text Available Nowadays Unmanned Aerial Vehicles (UAVs are widely used in many applications for different purposes. Their benefits however are not entirely detected due to the integration capabilities of other equipment such as; digital camera, GPS, or laser scanner. The main scope of this paper is evaluating performance of cameras integrated UAV for geomatic applications by the way of Digital Terrain Model (DTM generation in a small area. In this purpose, 7 ground control points are surveyed with RTK and 420 photographs are captured. Over 30 million georeferenced points were used in DTM generation process. Accuracy of the DTM was evaluated with 5 check points. The root mean square error is calculated as 17.1 cm for an altitude of 100 m. Besides, a LiDAR derived DTM is used as reference in order to calculate correlation. The UAV based DTM has o 94.5 % correlation with reference DTM. Outcomes of the study show that it is possible to use the UAV Photogrammetry data as map producing, surveying, and some other engineering applications with the advantages of low-cost, time conservation, and minimum field work.

  7. DTM Generation with Uav Based Photogrammetric Point Cloud

    Science.gov (United States)

    Polat, N.; Uysal, M.

    2017-11-01

    Nowadays Unmanned Aerial Vehicles (UAVs) are widely used in many applications for different purposes. Their benefits however are not entirely detected due to the integration capabilities of other equipment such as; digital camera, GPS, or laser scanner. The main scope of this paper is evaluating performance of cameras integrated UAV for geomatic applications by the way of Digital Terrain Model (DTM) generation in a small area. In this purpose, 7 ground control points are surveyed with RTK and 420 photographs are captured. Over 30 million georeferenced points were used in DTM generation process. Accuracy of the DTM was evaluated with 5 check points. The root mean square error is calculated as 17.1 cm for an altitude of 100 m. Besides, a LiDAR derived DTM is used as reference in order to calculate correlation. The UAV based DTM has o 94.5 % correlation with reference DTM. Outcomes of the study show that it is possible to use the UAV Photogrammetry data as map producing, surveying, and some other engineering applications with the advantages of low-cost, time conservation, and minimum field work.

  8. Optical generation,detection and non-destructive testing applications of terahertz waves

    Institute of Scientific and Technical Information of China (English)

    ZHANG; Weili; LIANG; Dachuan; TIAN; Zhen; HAN; Jiaguang; GU; Jianqiang; HE; Mingxia; OUYANG; Chunmei

    2016-01-01

    Optoelectronic terahertz generation and detection play a key role in the applications of non-destructive testing,which involves different areas such as physics,biological,material science,imaging,explosions detection,astronomy applications,semiconductor technology and superconductiong electronics. In this article,we present a reviewof the principle and performance of typical terahertz sources,detectors and non-destructive testing applications. On this basis,the newdevelopment and trends of terahertz radiation detectors are also discussed.

  9. 3D Printing and Assay Development for Point-of-Care Applications

    Science.gov (United States)

    Jagadeesh, Shreesha

    Existing centralized labs do not serve patients adequately in remote areas. To enable universal timely healthcare, there is a need to develop low cost, portable systems that can diagnose multiple disease (Point-of-Care (POC) devices). Future POC diagnostics can be more multi-functional if medical device vendors can develop interoperability standards. This thesis developed the following medical diagnostic modules: Plasma from 25 microl blood was extracted through a filter membrane to demonstrate a 3D printed sample preparation module. Sepsis biomarker, C - reactive protein, was quantified through adsorption on nylon beads to demonstrate bead-based assay suitable for 3D printed disposable cartridge module. Finally, a modular fluorescent detection kit was built using 3D printed parts to detect CD4 cells in a disposable cartridge from ChipCare Corp. Due to the modularity enabled by 3D printing technique, the developed units can be easily adapted to detect other diseases.

  10. Laser-based instrumentation for the detection of chemical agents

    International Nuclear Information System (INIS)

    Hartford, A. Jr.; Sander, R.K.; Quigley, G.P.; Radziemski, L.J.; Cremers, D.A.

    1982-01-01

    Several laser-based techniques are being evaluated for the remote, point, and surface detection of chemical agents. Among the methods under investigation are optoacoustic spectroscopy, laser-induced breakdown spectroscopy (LIBS), and synchronous detection of laser-induced fluorescence (SDLIF). Optoacoustic detection has already been shown to be capable of extremely sensitive point detection. Its application to remote sensing of chemical agents is currently being evaluated. Atomic emission from the region of a laser-generated plasma has been used to identify the characteristic elements contained in nerve (P and F) and blister (S and Cl) agents. Employing this LIBS approach, detection of chemical agent simulants dispersed in air and adsorbed on a variety of surfaces has been achieved. Synchronous detection of laser-induced fluorescence provides an attractive alternative to conventional LIF, in that an artificial narrowing of the fluorescence emission is obtained. The application of this technique to chemical agent simulants has been successfully demonstrated. 19 figures

  11. Three-point statistics of cosmological stochastic gravitational waves

    International Nuclear Information System (INIS)

    Adshead, Peter; Lim, Eugene A.

    2010-01-01

    We consider the three-point function (i.e. the bispectrum or non-Gaussianity) for stochastic backgrounds of gravitational waves. We estimate the amplitude of this signal for the primordial inflationary background, gravitational waves generated during preheating, and for gravitational waves produced by self-ordering scalar fields following a global phase transition. To assess detectability, we describe how to extract the three-point signal from an idealized interferometric experiment and compute the signal to noise ratio as a function of integration time. The three-point signal for the stochastic gravitational wave background generated by inflation is unsurprisingly tiny. For gravitational radiation generated by purely causal, classical mechanisms we find that, no matter how nonlinear the process is, the three-point correlations produced vanish in direct detection experiments. On the other hand, we show that in scenarios where the B-mode of the cosmic microwave background is sourced by gravitational waves generated by a global phase transition, a strong three-point signal among the polarization modes is also produced. This may provide another method of distinguishing inflationary B-modes. To carry out this computation, we have developed a diagrammatic approach to the calculation of stochastic gravitational waves sourced by scalar fluids, which has applications beyond the present scenario.

  12. Application of point system in the project control of Ling'ao Nuclear Power Station

    International Nuclear Information System (INIS)

    Xie ahai

    2005-01-01

    Schedule control and cost control are very complicated issues even we set up the detail schedules and engineering measurements requirements for erection of a nuclear power project. In order to solve these problems, a Point System is used in Ling Ao (LA) Nuclear Power Project. This paper introduces the method. The Point System is a measurement system of workload. The measurement unit of any erection works is a Point only. A Point of workload is defined as the equivalent measurement quantities, which could be completed by a relevant skill worker within an hour. A set of procedure manuals for different installations has been set up. The calculation models of equipment installation, piping, cabling are addressed for example in the paper. The application of the Point System in the schedule control is shown in the paper. The following issues are highlighted: to define the duration of a piping activity in the Project Level 2 Schedule, to draught the curves of Point Schedules for different erection fields, to analyze the productive efficiency, to define erection quota of each month for different erection teams, to follow up the erection progress on site. The application of the Point System in the payment of erection contract is outlined. The calculation formula of a monthly payment is given. The advantage of the payment calculation method is discussed, for example, more accurate, very easy and clearly to check the measurement quantities completed on site, to control lump-sum cost. (authors)

  13. A Field Evaluation of the Time-of-Detection Method to Estimate Population Size and Density for Aural Avian Point Counts

    Directory of Open Access Journals (Sweden)

    Mathew W. Alldredge

    2007-12-01

    Full Text Available The time-of-detection method for aural avian point counts is a new method of estimating abundance, allowing for uncertain probability of detection. The method has been specifically designed to allow for variation in singing rates of birds. It involves dividing the time interval of the point count into several subintervals and recording the detection history of the subintervals when each bird sings. The method can be viewed as generating data equivalent to closed capture-recapture information. The method is different from the distance and multiple-observer methods in that it is not required that all the birds sing during the point count. As this method is new and there is some concern as to how well individual birds can be followed, we carried out a field test of the method using simulated known populations of singing birds, using a laptop computer to send signals to audio stations distributed around a point. The system mimics actual aural avian point counts, but also allows us to know the size and spatial distribution of the populations we are sampling. Fifty 8-min point counts (broken into four 2-min intervals using eight species of birds were simulated. Singing rate of an individual bird of a species was simulated following a Markovian process (singing bouts followed by periods of silence, which we felt was more realistic than a truly random process. The main emphasis of our paper is to compare results from species singing at (high and low homogenous rates per interval with those singing at (high and low heterogeneous rates. Population size was estimated accurately for the species simulated, with a high homogeneous probability of singing. Populations of simulated species with lower but homogeneous singing probabilities were somewhat underestimated. Populations of species simulated with heterogeneous singing probabilities were substantially underestimated. Underestimation was caused by both the very low detection probabilities of all distant

  14. [Application of THz technology to nondestructive detection of agricultural product quality].

    Science.gov (United States)

    Jiang, Yu-ying; Ge, Hong-yi; Lian, Fei-yu; Zhang, Yuan; Xia, Shan-hong

    2014-08-01

    With recent development of THz sources and detector, applications of THz radiation to nondestructive testing and quality control have expanded in many fields, such as agriculture, safety inspection and quality control, medicine, biochemistry, communication etc. Compared with other detection technique, being a new kind of technique, THz radiation has low energy, good perspectivity, and high signal-to-noise ratio, and thus can obtain physical, chemical and biological information. This paper first introduces the basic concept of THz radiation and the major properties, then gives an extensive review of recent research progress in detection of the quality of agricultural products via THz technique, analyzes the existing shortcomings of THz detection and discusses the outlook of potential application, finally proposes the new application of THz technique to detection of quality of stored grain.

  15. Detecting Silent Data Corruption for Extreme-Scale Applications through Data Mining

    Energy Technology Data Exchange (ETDEWEB)

    Bautista-Gomez, Leonardo [Argonne National Lab. (ANL), Argonne, IL (United States); Cappello, Franck [Argonne National Lab. (ANL), Argonne, IL (United States)

    2014-01-16

    Supercomputers allow scientists to study natural phenomena by means of computer simulations. Next-generation machines are expected to have more components and, at the same time, consume several times less energy per operation. These trends are pushing supercomputer construction to the limits of miniaturization and energy-saving strategies. Consequently, the number of soft errors is expected to increase dramatically in the coming years. While mechanisms are in place to correct or at least detect some soft errors, a significant percentage of those errors pass unnoticed by the hardware. Such silent errors are extremely damaging because they can make applications silently produce wrong results. In this work we propose a technique that leverages certain properties of high-performance computing applications in order to detect silent errors at the application level. Our technique detects corruption solely based on the behavior of the application datasets and is completely application-agnostic. We propose multiple corruption detectors, and we couple them to work together in a fashion transparent to the user. We demonstrate that this strategy can detect the majority of the corruptions, while incurring negligible overhead. We show that with the help of these detectors, applications can have up to 80% of coverage against data corruption.

  16. A 3D clustering approach for point clouds to detect and quantify changes at a rock glacier front

    Science.gov (United States)

    Micheletti, Natan; Tonini, Marj; Lane, Stuart N.

    2016-04-01

    Terrestrial Laser Scanners (TLS) are extensively used in geomorphology to remotely-sense landforms and surfaces of any type and to derive digital elevation models (DEMs). Modern devices are able to collect many millions of points, so that working on the resulting dataset is often troublesome in terms of computational efforts. Indeed, it is not unusual that raw point clouds are filtered prior to DEM creation, so that only a subset of points is retained and the interpolation process becomes less of a burden. Whilst this procedure is in many cases necessary, it implicates a considerable loss of valuable information. First, and even without eliminating points, the common interpolation of points to a regular grid causes a loss of potentially useful detail. Second, it inevitably causes the transition from 3D information to only 2.5D data where each (x,y) pair must have a unique z-value. Vector-based DEMs (e.g. triangulated irregular networks) partially mitigate these issues, but still require a set of parameters to be set and a considerable burden in terms of calculation and storage. Because of the reasons above, being able to perform geomorphological research directly on point clouds would be profitable. Here, we propose an approach to identify erosion and deposition patterns on a very active rock glacier front in the Swiss Alps to monitor sediment dynamics. The general aim is to set up a semiautomatic method to isolate mass movements using 3D-feature identification directly from LiDAR data. An ultra-long range LiDAR RIEGL VZ-6000 scanner was employed to acquire point clouds during three consecutive summers. In order to isolate single clusters of erosion and deposition we applied the Density-Based Scan Algorithm with Noise (DBSCAN), previously successfully employed by Tonini and Abellan (2014) in a similar case for rockfall detection. DBSCAN requires two input parameters, strongly influencing the number, shape and size of the detected clusters: the minimum number of

  17. Influence of call broadcast timing within point counts and survey duration on detection probability of marsh breeding birds

    Directory of Open Access Journals (Sweden)

    Douglas C. Tozer

    2017-12-01

    Full Text Available The Standardized North American Marsh Bird Monitoring Protocol recommends point counts consisting of a 5-min passive observation period, meant to be free of broadcast bias, followed by call broadcasts to entice elusive species to reveal their presence. Prior to this protocol, some monitoring programs used point counts with broadcasts during the first 5 min of 10-min counts, and have since used 15-min counts with an initial 5-min passive period (P1 followed by 5 min of broadcasts (B and a second 5-min passive period (P2 to ensure consistency across years and programs. Influence of timing of broadcasts within point counts and point count duration, however, have rarely been assessed. Using data from 23,973 broadcast-assisted 15-min point counts conducted throughout the Great Lakes-St. Lawrence region between 2008 and 2016 by Bird Studies Canada's Marsh Monitoring Program and Central Michigan University's Great Lakes Coastal Wetland Monitoring Program, we estimated detection probabilities of individuals for 14 marsh breeding bird species during P1B compared to BP2, P1 compared to P2, and P1B compared to P1BP2. For six broadcast species and American Bittern (Botaurus lentiginosus, we found no significant difference in detection during P1B compared to BP2, and no significant difference in four of the same seven species during P1 compared to P2. We observed small but significant differences in detection for 7 of 14 species during P1B compared to P1BP2. We conclude that differences in timing of broadcasts causes no bias based on counts from entire 10-minute surveys, although P1B should be favored over BP2 because the same amount of effort in P1B avoids broadcast bias in all broadcast species, and 10-min surveys are superior to 15-min surveys because modest gains in detection of some species does not warrant the additional effort. We recommend point counts consisting of 5 min of passive observation followed by broadcasts, consistent with the standardized

  18. Solid state nuclear track detection principles, methods and applications

    CERN Document Server

    Durrani, S A; ter Haar, D

    1987-01-01

    Solid State Nuclear Track Detection: Principles, Methods and Applications is the second book written by the authors after Nuclear Tracks in Solids: Principles and Applications. The book is meant as an introduction to the subject solid state of nuclear track detection. The text covers the interactions of charged particles with matter; the nature of the charged-particle track; the methodology and geometry of track etching; thermal fading of latent damage trails on tracks; the use of dielectric track recorders in particle identification; radiation dossimetry; and solid state nuclear track detecti

  19. Non-Uniqueness of the Point of Application of the Buoyancy Force

    Science.gov (United States)

    Kliava, Janis; Megel, Jacques

    2010-01-01

    Even though the buoyancy force (also known as the Archimedes force) has always been an important topic of academic studies in physics, its point of application has not been explicitly identified yet. We present a quantitative approach to this problem based on the concept of the hydrostatic energy, considered here for a general shape of the…

  20. DETECT: a MATLAB toolbox for event detection and identification in time series, with applications to artifact detection in EEG signals.

    Science.gov (United States)

    Lawhern, Vernon; Hairston, W David; Robbins, Kay

    2013-01-01

    Recent advances in sensor and recording technology have allowed scientists to acquire very large time-series datasets. Researchers often analyze these datasets in the context of events, which are intervals of time where the properties of the signal change relative to a baseline signal. We have developed DETECT, a MATLAB toolbox for detecting event time intervals in long, multi-channel time series. Our primary goal is to produce a toolbox that is simple for researchers to use, allowing them to quickly train a model on multiple classes of events, assess the accuracy of the model, and determine how closely the results agree with their own manual identification of events without requiring extensive programming knowledge or machine learning experience. As an illustration, we discuss application of the DETECT toolbox for detecting signal artifacts found in continuous multi-channel EEG recordings and show the functionality of the tools found in the toolbox. We also discuss the application of DETECT for identifying irregular heartbeat waveforms found in electrocardiogram (ECG) data as an additional illustration.

  1. DETECT: a MATLAB toolbox for event detection and identification in time series, with applications to artifact detection in EEG signals.

    Directory of Open Access Journals (Sweden)

    Vernon Lawhern

    Full Text Available Recent advances in sensor and recording technology have allowed scientists to acquire very large time-series datasets. Researchers often analyze these datasets in the context of events, which are intervals of time where the properties of the signal change relative to a baseline signal. We have developed DETECT, a MATLAB toolbox for detecting event time intervals in long, multi-channel time series. Our primary goal is to produce a toolbox that is simple for researchers to use, allowing them to quickly train a model on multiple classes of events, assess the accuracy of the model, and determine how closely the results agree with their own manual identification of events without requiring extensive programming knowledge or machine learning experience. As an illustration, we discuss application of the DETECT toolbox for detecting signal artifacts found in continuous multi-channel EEG recordings and show the functionality of the tools found in the toolbox. We also discuss the application of DETECT for identifying irregular heartbeat waveforms found in electrocardiogram (ECG data as an additional illustration.

  2. Guided wave testing for touch point corrosion

    International Nuclear Information System (INIS)

    Alleyne, David

    2012-01-01

    Guided wave testing (GWT) is established in the petrochemical and related industries, primarily for the detection of corrosion flaws. Touch point corrosion at support positions in pipe-work has become a significant problem within many operating gas, chemical and petro-chemical plants world-wide, particularly as a high proportion of these plants have been operational for many decades. This article demonstrates how GWT using guided waves sent axially along the pipe can be performed for the detection and accurate classification of touchpoint corrosion. The major advantage of GWT methods for the detection of touch point corrosion is its ability to examine several support positions from a single easy to access transducer position. The strategy is then to prioritize or rank the condition of the pipe at the supports by removing those with negligible wall loss from scheduling for further inspection. Guided waves are accurate at detecting and classifying corrosion patches at support positions, but deep pits within such patches are more difficult to accurately identify. Examples using data from routine inspection testing are used to support the development of the methods and testing approaches presented. Recent developments of the interpretation methods, testing procedures and calibration methods have significantly enhanced the capabilities of GWT for this important application.

  3. Ensemble Learning Method for Outlier Detection and its Application to Astronomical Light Curves

    Science.gov (United States)

    Nun, Isadora; Protopapas, Pavlos; Sim, Brandon; Chen, Wesley

    2016-09-01

    Outlier detection is necessary for automated data analysis, with specific applications spanning almost every domain from financial markets to epidemiology to fraud detection. We introduce a novel mixture of the experts outlier detection model, which uses a dynamically trained, weighted network of five distinct outlier detection methods. After dimensionality reduction, individual outlier detection methods score each data point for “outlierness” in this new feature space. Our model then uses dynamically trained parameters to weigh the scores of each method, allowing for a finalized outlier score. We find that the mixture of experts model performs, on average, better than any single expert model in identifying both artificially and manually picked outliers. This mixture model is applied to a data set of astronomical light curves, after dimensionality reduction via time series feature extraction. Our model was tested using three fields from the MACHO catalog and generated a list of anomalous candidates. We confirm that the outliers detected using this method belong to rare classes, like Novae, He-burning, and red giant stars; other outlier light curves identified have no available information associated with them. To elucidate their nature, we created a website containing the light-curve data and information about these objects. Users can attempt to classify the light curves, give conjectures about their identities, and sign up for follow up messages about the progress made on identifying these objects. This user submitted data can be used further train of our mixture of experts model. Our code is publicly available to all who are interested.

  4. Application of a two-sinker densimeter for phase-equilibrium measurements: A new technique for the detection of dew points and measurements on the (methane + propane) system

    International Nuclear Information System (INIS)

    McLinden, Mark O.; Richter, Markus

    2016-01-01

    Highlights: • A new technique for detecting dew points in fluid mixtures is described. • The method makes use of a two-sinker densimeter. • The technique is based on a quantitative measurement of sample mass adsorbed onto the surface of the densimeter sinkers. • The dew-point density and dew-point pressure are determined with low uncertainty. • The method is applied to the (methane + propane) system and compared to traditional methods. - Abstract: We explore a novel method for determining the dew-point density and dew-point pressure of fluid mixtures and compare it to traditional methods. The (p, ρ, T, x) behavior of three (methane + propane) mixtures was investigated with a two-sinker magnetic suspension densimeter over the temperature range of (248.15–293.15) K; the measurements extended from low pressures into the two-phase region. The compositions of the gravimetrically prepared mixtures were (0.74977, 0.50688, and 0.26579) mole fraction methane. We analyzed isothermal data by: (1) a “traditional” analysis of the intersection of a virial fit of the (p vs. ρ) data in the single-phase region with a linear fit of the data in the two-phase region; and (2) an analysis of the adsorbed mass on the sinker surfaces. We compared these to a traditional isochoric experiment. We conclude that the “adsorbed mass” analysis of an isothermal experiment provides an accurate determination of the dew-point temperature, pressure, and density. However, a two-sinker densimeter is required.

  5. The Development of an UAV Borne Direct Georeferenced Photogrammetric Platform for Ground Control Point Free Applications

    Directory of Open Access Journals (Sweden)

    Chien-Hsun Chu

    2012-07-01

    Full Text Available To facilitate applications such as environment detection or disaster monitoring, the development of rapid low cost systems for collecting near real time spatial information is very critical. Rapid spatial information collection has become an emerging trend for remote sensing and mapping applications. In this study, a fixed-wing Unmanned Aerial Vehicle (UAV-based spatial information acquisition platform that can operate in Ground Control Point (GCP free environments is developed and evaluated. The proposed UAV based photogrammetric platform has a Direct Georeferencing (DG module that includes a low cost Micro Electro Mechanical Systems (MEMS Inertial Navigation System (INS/ Global Positioning System (GPS integrated system. The DG module is able to provide GPS single frequency carrier phase measurements for differential processing to obtain sufficient positioning accuracy. All necessary calibration procedures are implemented. Ultimately, a flight test is performed to verify the positioning accuracy in DG mode without using GCPs. The preliminary results of positioning accuracy in DG mode illustrate that horizontal positioning accuracies in the x and y axes are around 5 m at 300 m flight height above the ground. The positioning accuracy of the z axis is below 10 m. Therefore, the proposed platform is relatively safe and inexpensive for collecting critical spatial information for urgent response such as disaster relief and assessment applications where GCPs are not available.

  6. Application of point-to-point matching algorithms for background correction in on-line liquid chromatography-Fourier transform infrared spectrometry (LC-FTIR).

    Science.gov (United States)

    Kuligowski, J; Quintás, G; Garrigues, S; de la Guardia, M

    2010-03-15

    A new background correction method for the on-line coupling of gradient liquid chromatography and Fourier transform infrared spectrometry has been developed. It is based on the use of a point-to-point matching algorithm that compares the absorption spectra of the sample data set with those of a previously recorded reference data set in order to select an appropriate reference spectrum. The spectral range used for the point-to-point comparison is selected with minimal user-interaction, thus facilitating considerably the application of the whole method. The background correction method has been successfully tested on a chromatographic separation of four nitrophenols running acetonitrile (0.08%, v/v TFA):water (0.08%, v/v TFA) gradients with compositions ranging from 35 to 85% (v/v) acetonitrile, giving accurate results for both, baseline resolved and overlapped peaks. Copyright (c) 2009 Elsevier B.V. All rights reserved.

  7. CURB-BASED STREET FLOOR EXTRACTION FROM MOBILE TERRESTRIAL LIDAR POINT CLOUD

    Directory of Open Access Journals (Sweden)

    S. Ibrahim

    2012-07-01

    Full Text Available Mobile terrestrial laser scanners (MTLS produce huge 3D point clouds describing the terrestrial surface, from which objects like different street furniture can be generated. Extraction and modelling of the street curb and the street floor from MTLS point clouds is important for many applications such as right-of-way asset inventory, road maintenance and city planning. The proposed pipeline for the curb and street floor extraction consists of a sequence of five steps: organizing the 3D point cloud and nearest neighbour search; 3D density-based segmentation to segment the ground; morphological analysis to refine out the ground segment; derivative of Gaussian filtering to detect the curb; solving the travelling salesman problem to form a closed polygon of the curb and point-inpolygon test to extract the street floor. Two mobile laser scanning datasets of different scenes are tested with the proposed pipeline. The results of the extracted curb and street floor are evaluated based on a truth data. The obtained detection rates for the extracted street floor for the datasets are 95% and 96.53%. This study presents a novel approach to the detection and extraction of the road curb and the street floor from unorganized 3D point clouds captured by MTLS. It utilizes only the 3D coordinates of the point cloud.

  8. Data-Driven Jump Detection Thresholds for Application in Jump Regressions

    Directory of Open Access Journals (Sweden)

    Robert Davies

    2018-03-01

    Full Text Available This paper develops a method to select the threshold in threshold-based jump detection methods. The method is motivated by an analysis of threshold-based jump detection methods in the context of jump-diffusion models. We show that over the range of sampling frequencies a researcher is most likely to encounter that the usual in-fill asymptotics provide a poor guide for selecting the jump threshold. Because of this we develop a sample-based method. Our method estimates the number of jumps over a grid of thresholds and selects the optimal threshold at what we term the ‘take-off’ point in the estimated number of jumps. We show that this method consistently estimates the jumps and their indices as the sampling interval goes to zero. In several Monte Carlo studies we evaluate the performance of our method based on its ability to accurately locate jumps and its ability to distinguish between true jumps and large diffusive moves. In one of these Monte Carlo studies we evaluate the performance of our method in a jump regression context. Finally, we apply our method in two empirical studies. In one we estimate the number of jumps and report the jump threshold our method selects for three commonly used market indices. In the other empirical application we perform a series of jump regressions using our method to select the jump threshold.

  9. Rapid and sensitive detection of Feline immunodeficiency virus using an insulated isothermal PCR-based assay with a point-of-need PCR detection platform.

    Science.gov (United States)

    Wilkes, Rebecca Penrose; Kania, Stephen A; Tsai, Yun-Long; Lee, Pei-Yu Alison; Chang, Hsiu-Hui; Ma, Li-Juan; Chang, Hsiao-Fen Grace; Wang, Hwa-Tang Thomas

    2015-07-01

    Feline immunodeficiency virus (FIV) is an important infectious agent of cats. Clinical syndromes resulting from FIV infection include immunodeficiency, opportunistic infections, and neoplasia. In our study, a 5' long terminal repeat/gag region-based reverse transcription insulated isothermal polymerase chain reaction (RT-iiPCR) was developed to amplify all known FIV strains to facilitate point-of-need FIV diagnosis. The RT-iiPCR method was applied in a point-of-need PCR detection platform--a field-deployable device capable of generating automatically interpreted RT-iiPCR results from nucleic acids within 1 hr. Limit of detection 95% of FIV RT-iiPCR was calculated to be 95 copies standard in vitro transcription RNA per reaction. Endpoint dilution studies with serial dilutions of an ATCC FIV type strain showed that the sensitivity of lyophilized FIV RT-iiPCR reagent was comparable to that of a reference nested PCR. The established reaction did not amplify any nontargeted feline pathogens, including Felid herpesvirus 1, feline coronavirus, Feline calicivirus, Feline leukemia virus, Mycoplasma haemofelis, and Chlamydophila felis. Based on analysis of 76 clinical samples (including blood and bone marrow) with the FIV RT-iiPCR, test sensitivity was 97.78% (44/45), specificity was 100.00% (31/31), and agreement was 98.65% (75/76), determined against a reference nested-PCR assay. A kappa value of 0.97 indicated excellent correlation between these 2 methods. The lyophilized FIV RT-iiPCR reagent, deployed on a user-friendly portable device, has potential utility for rapid and easy point-of-need detection of FIV in cats. © 2015 The Author(s).

  10. Routine use of point-of-care tests: usefulness and application in clinical microbiology.

    Science.gov (United States)

    Clerc, O; Greub, G

    2010-08-01

    Point-of-care (POC) tests offer potentially substantial benefits for the management of infectious diseases, mainly by shortening the time to result and by making the test available at the bedside or at remote care centres. Commercial POC tests are already widely available for the diagnosis of bacterial and viral infections and for parasitic diseases, including malaria. Infectious diseases specialists and clinical microbiologists should be aware of the indications and limitations of each rapid test, so that they can use them appropriately and correctly interpret their results. The clinical applications and performance of the most relevant and commonly used POC tests are reviewed. Some of these tests exhibit insufficient sensitivity, and should therefore be coupled to confirmatory tests when the results are negative (e.g. Streptococcus pyogenes rapid antigen detection test), whereas the results of others need to be confirmed when positive (e.g. malaria). New molecular-based tests exhibit better sensitivity and specificity than former immunochromatographic assays (e.g. Streptococcus agalactiae detection). In the coming years, further evolution of POC tests may lead to new diagnostic approaches, such as panel testing, targeting not just a single pathogen, but all possible agents suspected in a specific clinical setting. To reach this goal, the development of serology-based and/or molecular-based microarrays/multiplexed tests will be needed. The availability of modern technology and new microfluidic devices will provide clinical microbiologists with the opportunity to be back at the bedside, proposing a large variety of POC tests that will allow quicker diagnosis and improved patient care.

  11. Application of Micro-cloud point extraction for spectrophotometric determination of Malachite green, Crystal violet and Rhodamine B in aqueous samples

    Science.gov (United States)

    Ghasemi, Elham; Kaykhaii, Massoud

    2016-07-01

    A novel, green, simple and fast method was developed for spectrophotometric determination of Malachite green, Crystal violet, and Rhodamine B in water samples based on Micro-cloud Point extraction (MCPE) at room temperature. This is the first report on the application of MCPE on dyes. In this method, to reach the cloud point at room temperature, the MCPE procedure was carried out in brine using Triton X-114 as a non-ionic surfactant. The factors influencing the extraction efficiency were investigated and optimized. Under the optimized condition, calibration curves were found to be linear in the concentration range of 0.06-0.60 mg/L, 0.10-0.80 mg/L, and 0.03-0.30 mg/L with the enrichment factors of 29.26, 85.47 and 28.36, respectively for Malachite green, Crystal violet, and Rhodamine B. Limit of detections were between 2.2 and 5.1 μg/L.

  12. Applicability of point-dipoles approximation to all-dielectric metamaterials

    DEFF Research Database (Denmark)

    Kuznetsova, S. M.; Andryieuski, Andrei; Lavrinenko, Andrei

    2015-01-01

    All-dielectric metamaterials consisting of high-dielectric inclusions in a low-dielectric matrix are considered as a low-loss alternative to resonant metal-based metamaterials. In this paper we investigate the applicability of the point electric and magnetic dipoles approximation to dielectric meta......-atoms on the example of a dielectric ring metamaterial. Despite the large electrical size of high-dielectric meta-atoms, the dipole approximation allows for accurate prediction of the metamaterials properties for the rings with diameters up to approximate to 0.8 of the lattice constant. The results provide important...... guidelines for design and optimization of all-dielectric metamaterials....

  13. Electrically-detected electron paramagnetic resonance of point centers in 6H-SiC nanostructures

    Czech Academy of Sciences Publication Activity Database

    Bagraev, N.T.; Gets, D.S.; Kalabukhova, E.N.; Klyachkin, L.E.; Malyarenko, A.M.; Mashkov, V.A.; Savchenko, Dariia; Shanina, B.D.

    2014-01-01

    Roč. 48, č. 11 (2014), s. 1467-1480 ISSN 1063-7826 R&D Projects: GA MŠk(CZ) LM2011029 Grant - others:SAFMAT(XE) CZ.2.16/3.1.00/22132 Institutional support: RVO:68378271 Keywords : electron paramagnetic resonance * electrically- detected electron paramagnetic resonance * 6H -SiC nanostructures * nitrogen-vacancy defect * point defect Subject RIV: BM - Solid Matter Physics ; Magnetism Impact factor: 0.739, year: 2014

  14. Context-based adaptive filtering of interest points in image retrieval

    DEFF Research Database (Denmark)

    Nguyen, Phuong Giang; Andersen, Hans Jørgen

    2009-01-01

    Interest points have been used as local features with success in many computer vision applications such as image/video retrieval and object recognition. However, a major issue when using this approach is a large number of interest points detected from each image and created a dense feature space...... a subset of features. Our approach differs from others in a fact that selected feature is based on the context of the given image. Our experimental results show a significant reduction rate of features while preserving the retrieval performance....

  15. Automated Detection of Geomorphic Features in LiDAR Point Clouds of Various Spatial Density

    Science.gov (United States)

    Dorninger, Peter; Székely, Balázs; Zámolyi, András.; Nothegger, Clemens

    2010-05-01

    extraction and modeling of buildings (Dorninger & Pfeifer, 2008) we expected that similar generalizations for geomorphic features can be achieved. Our aim is to recognize as many features as possible from the point cloud in the same processing loop, if they can be geometrically described with appropriate accuracy (e.g., as a plane). For this, we propose to apply a segmentation process allowing determining connected, planar structures within a surface represented by a point cloud. It is based on a robust determination of local tangential planes for all points acquired (Nothegger & Dorninger, 2009). It assumes that for points, belonging to a distinct planar structure, similar tangential planes can be determined. In passing, points acquired at continuous such as vegetation can be identified and eliminated. The plane parameters are used to define a four-dimensional feature space which is used to determine seed-clusters globally for the whole are of interest. Starting from these seeds, all points defining a connected, planar region are assigned to a segment. Due to the design of the algorithm, millions of input points can be processed with acceptable processing time on standard computer systems. This allows for processing geomorphically representative areas at once. For each segment, numerous parameter are derived which can be used for further exploitation. These are, for example, location, area, aspect, slope, and roughness. To prove the applicability of our method for automated geomorphic terrain analysis, we used terrestrial and airborne laser scanning data, acquired at two locations. The data of the Doren landslide located in Vorarlberg, Austria, was acquired by a terrestrial Riegl LS-321 laser scanner in 2008, by a terrestrial Riegl LMS-Z420i laser scanner in 2009, and additionally by three airborne LiDAR measurement campaigns, organized by the Landesvermessungsamt Vorarlberg, Feldkirch, in 2003, 2006, and 2007. The measurement distance of the terrestrial measurements was

  16. Electronic aroma detection technology for forensic and law enforcement applications

    Energy Technology Data Exchange (ETDEWEB)

    Barshick, S.-A.; Griest, W.H.; Vass, A.A.

    1996-12-31

    A major problem hindering criminal investigations is the lack of appropriate tools for proper crime scene investigations. Often locating important pieces of evidence means relying on the ability of trained detection canines. Development of analytical technology to uncover and analyze evidence, potentially at the scene, could serve to expedite criminal investigations, searches, and court proceedings. To address this problem, a new technology based on gas sensor arrays was investigated for its applicability to forensic and law enforcement problems. The technology employs an array of sensors that respond to volatile chemical components yielding a characteristic `fingerprint` pattern representative of the vapor- phase composition of a sample. Sample aromas can be analyzed and identified using artificial neural networks that are trained on known aroma patterns. Several candidate applications based on known technological needs of the forensic and law enforcement communities have been investigated. These applications have included the detection of aromas emanating from cadavers to aid in determining time since death, drug detection for deterring the manufacture, sale, and use of drugs of abuse, and the analysis of fire debris for accelerant identification. The results to date for these applications have been extremely promising and demonstrate the potential applicability of this technology for forensic use.

  17. High-performance floating-point image computing workstation for medical applications

    Science.gov (United States)

    Mills, Karl S.; Wong, Gilman K.; Kim, Yongmin

    1990-07-01

    The medical imaging field relies increasingly on imaging and graphics techniques in diverse applications with needs similar to (or more stringent than) those of the military, industrial and scientific communities. However, most image processing and graphics systems available for use in medical imaging today are either expensive, specialized, or in most cases both. High performance imaging and graphics workstations which can provide real-time results for a number of applications, while maintaining affordability and flexibility, can facilitate the application of digital image computing techniques in many different areas. This paper describes the hardware and software architecture of a medium-cost floating-point image processing and display subsystem for the NeXT computer, and its applications as a medical imaging workstation. Medical imaging applications of the workstation include use in a Picture Archiving and Communications System (PACS), in multimodal image processing and 3-D graphics workstation for a broad range of imaging modalities, and as an electronic alternator utilizing its multiple monitor display capability and large and fast frame buffer. The subsystem provides a 2048 x 2048 x 32-bit frame buffer (16 Mbytes of image storage) and supports both 8-bit gray scale and 32-bit true color images. When used to display 8-bit gray scale images, up to four different 256-color palettes may be used for each of four 2K x 2K x 8-bit image frames. Three of these image frames can be used simultaneously to provide pixel selectable region of interest display. A 1280 x 1024 pixel screen with 1: 1 aspect ratio can be windowed into the frame buffer for display of any portion of the processed image or images. In addition, the system provides hardware support for integer zoom and an 82-color cursor. This subsystem is implemented on an add-in board occupying a single slot in the NeXT computer. Up to three boards may be added to the NeXT for multiple display capability (e

  18. Fixed point theorems for mappings satisfying contractive conditions of integral type and applications

    Directory of Open Access Journals (Sweden)

    Kang Shin

    2011-01-01

    Full Text Available Abstract In this paper, the existence, uniqueness and iterative approximations of fixed points for contractive mappings of integral type in complete metric spaces are established. As applications, the existence, uniqueness and iterative approximations of solutions for a class of functional equations arising in dynamic programming are discussed. The results presented in this paper extend and improve essentially the results of Branciari (A fixed point theorem for mappings satisfying a general contractive condition of integral type. Int. J. Math. Math. Sci. 29, 531-536, 2002, Kannan (Some results on fixed points. Bull. Calcutta Math. Soc. 60, 71-76, 1968 and several known results. Four concrete examples involving the contractive mappings of integral type with uncountably many points are constructed. 2010 Mathematics Subject Classfication: 54H25, 47H10, 49L20, 49L99, 90C39

  19. A Flexible VHDL Floating Point Module for Control Algorithm Implementation in Space Applications

    Science.gov (United States)

    Padierna, A.; Nicoleau, C.; Sanchez, J.; Hidalgo, I.; Elvira, S.

    2012-08-01

    The implementation of control loops for space applications is an area with great potential. However, the characteristics of this kind of systems, such as its wide dynamic range of numeric values, make inadequate the use of fixed-point algorithms.However, because the generic chips available for the treatment of floating point data are, in general, not qualified to operate in space environments and the possibility of using an IP module in a FPGA/ASIC qualified for space is not viable due to the low amount of logic cells available for these type of devices, it is necessary to find a viable alternative.For these reasons, in this paper a VHDL Floating Point Module is presented. This proposal allows the design and execution of floating point algorithms with acceptable occupancy to be implemented in FPGAs/ASICs qualified for space environments.

  20. Face pose tracking using the four-point algorithm

    Science.gov (United States)

    Fung, Ho Yin; Wong, Kin Hong; Yu, Ying Kin; Tsui, Kwan Pang; Kam, Ho Chuen

    2017-06-01

    In this paper, we have developed an algorithm to track the pose of a human face robustly and efficiently. Face pose estimation is very useful in many applications such as building virtual reality systems and creating an alternative input method for the disabled. Firstly, we have modified a face detection toolbox called DLib for the detection of a face in front of a camera. The detected face features are passed to a pose estimation method, known as the four-point algorithm, for pose computation. The theory applied and the technical problems encountered during system development are discussed in the paper. It is demonstrated that the system is able to track the pose of a face in real time using a consumer grade laptop computer.

  1. Can a novel smartphone application detect periodic limb movements?

    Science.gov (United States)

    Bhopi, Rashmi; Nagy, David; Erichsen, Daniel

    2012-01-01

    Periodic limb movements (PLMs) are repetitive, stereotypical and unconscious movements, typically of the legs, that occur in sleep and are associated with several sleep disorders. The gold standard for detecting PLMs is overnight electromyography which, although highly sensitive and specific, is time and labour consuming. The current generation of smart phones is equipped with tri-axial accelerometers that record movement. To develop a smart phone application that can detect PLMs remotely. A leg movement sensing application (LMSA) was programmed in iOS 5x and incorporated into an iPhone 4S (Apple INC.). A healthy adult male subject underwent simultaneous EMG and LMSA measurements of voluntary stereotypical leg movements. The mean number of leg movements recorded by EMG and by the LMSA was compared. A total of 403 leg movements were scored by EMG of which the LMSA recorded 392 (97%). There was no statistical difference in mean number of leg movements recorded between the two modalities (p = 0.3). These preliminary results indicate that a smart phone application is able to accurately detect leg movements outside of the hospital environment and may be a useful tool for screening and follow up of patients with PLMs.

  2. Note on Studying Change Point of LRD Traffic Based on Li's Detection of DDoS Flood Attacking

    Directory of Open Access Journals (Sweden)

    Zhengmin Xia

    2010-01-01

    Full Text Available Distributed denial-of-service (DDoS flood attacks remain great threats to the Internet. To ensure network usability and reliability, accurate detection of these attacks is critical. Based on Li's work on DDoS flood attack detection, we propose a DDoS detection method by monitoring the Hurst variation of long-range dependant traffic. Specifically, we use an autoregressive system to estimate the Hurst parameter of normal traffic. If the actual Hurst parameter varies significantly from the estimation, we assume that DDoS attack happens. Meanwhile, we propose two methods to determine the change point of Hurst parameter that indicates the occurrence of DDoS attacks. The detection rate associated with one method and false alarm rate for the other method are also derived. The test results on DARPA intrusion detection evaluation data show that the proposed approaches can achieve better detection performance than some well-known self-similarity-based detection methods.

  3. Power-limited low-thrust trajectory optimization with operation point detection

    Science.gov (United States)

    Chi, Zhemin; Li, Haiyang; Jiang, Fanghua; Li, Junfeng

    2018-06-01

    The power-limited solar electric propulsion system is considered more practical in mission design. An accurate mathematical model of the propulsion system, based on experimental data of the power generation system, is used in this paper. An indirect method is used to deal with the time-optimal and fuel-optimal control problems, in which the solar electric propulsion system is described using a finite number of operation points, which are characterized by different pairs of thruster input power. In order to guarantee the integral accuracy for the discrete power-limited problem, a power operation detection technique is embedded in the fourth-order Runge-Kutta algorithm with fixed step. Moreover, the logarithmic homotopy method and normalization technique are employed to overcome the difficulties caused by using indirect methods. Three numerical simulations with actual propulsion systems are given to substantiate the feasibility and efficiency of the proposed method.

  4. A Colorimetric Enzyme-Linked Immunosorbent Assay (ELISA) Detection Platform for a Point-of-Care Dengue Detection System on a Lab-on-Compact-Disc

    Science.gov (United States)

    Thiha, Aung; Ibrahim, Fatimah

    2015-01-01

    The enzyme-linked Immunosorbent Assay (ELISA) is the gold standard clinical diagnostic tool for the detection and quantification of protein biomarkers. However, conventional ELISA tests have drawbacks in their requirement of time, expensive equipment and expertise for operation. Hence, for the purpose of rapid, high throughput screening and point-of-care diagnosis, researchers are miniaturizing sandwich ELISA procedures on Lab-on-a-Chip and Lab-on-Compact Disc (LOCD) platforms. This paper presents a novel integrated device to detect and interpret the ELISA test results on a LOCD platform. The system applies absorption spectrophotometry to measure the absorbance (optical density) of the sample using a monochromatic light source and optical sensor. The device performs automated analysis of the results and presents absorbance values and diagnostic test results via a graphical display or via Bluetooth to a smartphone platform which also acts as controller of the device. The efficacy of the device was evaluated by performing dengue antibody IgG ELISA on 64 hospitalized patients suspected of dengue. The results demonstrate high accuracy of the device, with 95% sensitivity and 100% specificity in detection when compared with gold standard commercial ELISA microplate readers. This sensor platform represents a significant step towards establishing ELISA as a rapid, inexpensive and automatic testing method for the purpose of point-of-care-testing (POCT) in resource-limited settings. PMID:25993517

  5. A Colorimetric Enzyme-Linked Immunosorbent Assay (ELISA) Detection Platform for a Point-of-Care Dengue Detection System on a Lab-on-Compact-Disc.

    Science.gov (United States)

    Thiha, Aung; Ibrahim, Fatimah

    2015-05-18

    The enzyme-linked Immunosorbent Assay (ELISA) is the gold standard clinical diagnostic tool for the detection and quantification of protein biomarkers. However, conventional ELISA tests have drawbacks in their requirement of time, expensive equipment and expertise for operation. Hence, for the purpose of rapid, high throughput screening and point-of-care diagnosis, researchers are miniaturizing sandwich ELISA procedures on Lab-on-a-Chip and Lab-on-Compact Disc (LOCD) platforms. This paper presents a novel integrated device to detect and interpret the ELISA test results on a LOCD platform. The system applies absorption spectrophotometry to measure the absorbance (optical density) of the sample using a monochromatic light source and optical sensor. The device performs automated analysis of the results and presents absorbance values and diagnostic test results via a graphical display or via Bluetooth to a smartphone platform which also acts as controller of the device. The efficacy of the device was evaluated by performing dengue antibody IgG ELISA on 64 hospitalized patients suspected of dengue. The results demonstrate high accuracy of the device, with 95% sensitivity and 100% specificity in detection when compared with gold standard commercial ELISA microplate readers. This sensor platform represents a significant step towards establishing ELISA as a rapid, inexpensive and automatic testing method for the purpose of point-of-care-testing (POCT) in resource-limited settings.

  6. Green Grape Detection and Picking-Point Calculation in a Night-Time Natural Environment Using a Charge-Coupled Device (CCD Vision Sensor with Artificial Illumination

    Directory of Open Access Journals (Sweden)

    Juntao Xiong

    2018-03-01

    Full Text Available Night-time fruit-picking technology is important to picking robots. This paper proposes a method of night-time detection and picking-point positioning for green grape-picking robots to solve the difficult problem of green grape detection and picking in night-time conditions with artificial lighting systems. Taking a representative green grape named Centennial Seedless as the research object, daytime and night-time grape images were captured by a custom-designed visual system. Detection was conducted employing the following steps: (1 The RGB (red, green and blue. Color model was determined for night-time green grape detection through analysis of color features of grape images under daytime natural light and night-time artificial lighting. The R component of the RGB color model was rotated and the image resolution was compressed; (2 The improved Chan–Vese (C–V level set model and morphological processing method were used to remove the background of the image, leaving out the grape fruit; (3 Based on the character of grape vertical suspension, combining the principle of the minimum circumscribed rectangle of fruit and the Hough straight line detection method, straight-line fitting for the fruit stem was conducted and the picking point was calculated using the stem with an angle of fitting line and vertical line less than 15°. The visual detection experiment results showed that the accuracy of grape fruit detection was 91.67% and the average running time of the proposed algorithm was 0.46 s. The picking-point calculation experiment results showed that the highest accuracy for the picking-point calculation was 92.5%, while the lowest was 80%. The results demonstrate that the proposed method of night-time green grape detection and picking-point calculation can provide technical support to the grape-picking robots.

  7. The Segmentation of Point Clouds with K-Means and ANN (artifical Neural Network)

    Science.gov (United States)

    Kuçak, R. A.; Özdemir, E.; Erol, S.

    2017-05-01

    Segmentation of point clouds is recently used in many Geomatics Engineering applications such as the building extraction in urban areas, Digital Terrain Model (DTM) generation and the road or urban furniture extraction. Segmentation is a process of dividing point clouds according to their special characteristic layers. The present paper discusses K-means and self-organizing map (SOM) which is a type of ANN (Artificial Neural Network) segmentation algorithm which treats the segmentation of point cloud. The point clouds which generate with photogrammetric method and Terrestrial Lidar System (TLS) were segmented according to surface normal, intensity and curvature. Thus, the results were evaluated. LIDAR (Light Detection and Ranging) and Photogrammetry are commonly used to obtain point clouds in many remote sensing and geodesy applications. By photogrammetric method or LIDAR method, it is possible to obtain point cloud from terrestrial or airborne systems. In this study, the measurements were made with a Leica C10 laser scanner in LIDAR method. In photogrammetric method, the point cloud was obtained from photographs taken from the ground with a 13 MP non-metric camera.

  8. THE SEGMENTATION OF POINT CLOUDS WITH K-MEANS AND ANN (ARTIFICAL NEURAL NETWORK

    Directory of Open Access Journals (Sweden)

    R. A. Kuçak

    2017-05-01

    Full Text Available Segmentation of point clouds is recently used in many Geomatics Engineering applications such as the building extraction in urban areas, Digital Terrain Model (DTM generation and the road or urban furniture extraction. Segmentation is a process of dividing point clouds according to their special characteristic layers. The present paper discusses K-means and self-organizing map (SOM which is a type of ANN (Artificial Neural Network segmentation algorithm which treats the segmentation of point cloud. The point clouds which generate with photogrammetric method and Terrestrial Lidar System (TLS were segmented according to surface normal, intensity and curvature. Thus, the results were evaluated. LIDAR (Light Detection and Ranging and Photogrammetry are commonly used to obtain point clouds in many remote sensing and geodesy applications. By photogrammetric method or LIDAR method, it is possible to obtain point cloud from terrestrial or airborne systems. In this study, the measurements were made with a Leica C10 laser scanner in LIDAR method. In photogrammetric method, the point cloud was obtained from photographs taken from the ground with a 13 MP non-metric camera.

  9. Nearest Neighbour Corner Points Matching Detection Algorithm

    Directory of Open Access Journals (Sweden)

    Zhang Changlong

    2015-01-01

    Full Text Available Accurate detection towards the corners plays an important part in camera calibration. To deal with the instability and inaccuracies of present corner detection algorithm, the nearest neighbour corners match-ing detection algorithms was brought forward. First, it dilates the binary image of the photographed pictures, searches and reserves quadrilateral outline of the image. Second, the blocks which accord with chess-board-corners are classified into a class. If too many blocks in class, it will be deleted; if not, it will be added, and then let the midpoint of the two vertex coordinates be the rough position of corner. At last, it precisely locates the position of the corners. The Experimental results have shown that the algorithm has obvious advantages on accuracy and validity in corner detection, and it can give security for camera calibration in traffic accident measurement.

  10. CVD diamond for nuclear detection applications

    CERN Document Server

    Bergonzo, P; Tromson, D; Mer, C; Guizard, B; Marshall, R D; Foulon, F

    2002-01-01

    Chemically vapour deposited (CVD) diamond is a remarkable material for the fabrication of radiation detectors. In fact, there exist several applications where other standard semiconductor detectors do not fulfil the specific requirements imposed by corrosive, hot and/or high radiation dose environments. The improvement of the electronic properties of CVD diamond has been under intensive investigations and led to the development of a few applications that are addressing specific industrial needs. Here, we report on CVD diamond-based detector developments and we describe how this material, even though of a polycrystalline nature, is readily of great interest for applications in the nuclear industry as well as for physics experiments. Improvements in the material synthesis as well as on device fabrication especially concern the synthesis of films that do not exhibit space charge build up effects which are often encountered in CVD diamond materials and that are highly detrimental for detection devices. On a pre-i...

  11. Applicability of a desiccant dew-point cooling system independent of external water sources

    DEFF Research Database (Denmark)

    Bellemo, Lorenzo; Elmegaard, Brian; Kærn, Martin Ryhl

    2015-01-01

    The applicability of a technical solution for making desiccant cooling systems independent of external water sources is investigated. Water is produced by condensing the desorbed water vapour in a closed regeneration circuit. Desorbed water recovery is applied to a desiccant dew-point cooling...... system, which includes a desiccant wheel and a dew point cooler. The system is simulated during the summer period in the Mediterranean climate of Rome and it results completely independent of external water sources. The seasonal thermal COP drops 8% in comparison to the open regeneration circuit solution...

  12. Adaptive error detection for HDR/PDR brachytherapy: Guidance for decision making during real-time in vivo point dosimetry

    DEFF Research Database (Denmark)

    Kertzscher Schwencke, Gustavo Adolfo Vladimir; Andersen, Claus E.; Tanderup, Kari

    2014-01-01

    Purpose:This study presents an adaptive error detection algorithm (AEDA) for real-timein vivo point dosimetry during high dose rate (HDR) or pulsed dose rate (PDR) brachytherapy (BT) where the error identification, in contrast to existing approaches, does not depend on an a priori reconstruction ......, and the AEDA’s capacity to distinguish between true and false error scenarios. The study further shows that the AEDA can offer guidance in decision making in the event of potential errors detected with real-time in vivo point dosimetry....... of the dosimeter position reconstruction. Given its nearly exclusive dependence on stable dosimeter positioning, the AEDA allows for a substantially simplified and time efficient real-time in vivo BT dosimetry implementation. Methods:In the event of a measured potential treatment error, the AEDA proposes the most...

  13. Detection of Single Tree Stems in Forested Areas from High Density ALS Point Clouds Using 3d Shape Descriptors

    Science.gov (United States)

    Amiri, N.; Polewski, P.; Yao, W.; Krzystek, P.; Skidmore, A. K.

    2017-09-01

    Airborne Laser Scanning (ALS) is a widespread method for forest mapping and management purposes. While common ALS techniques provide valuable information about the forest canopy and intermediate layers, the point density near the ground may be poor due to dense overstory conditions. The current study highlights a new method for detecting stems of single trees in 3D point clouds obtained from high density ALS with a density of 300 points/m2. Compared to standard ALS data, due to lower flight height (150-200 m) this elevated point density leads to more laser reflections from tree stems. In this work, we propose a three-tiered method which works on the point, segment and object levels. First, for each point we calculate the likelihood that it belongs to a tree stem, derived from the radiometric and geometric features of its neighboring points. In the next step, we construct short stem segments based on high-probability stem points, and classify the segments by considering the distribution of points around them as well as their spatial orientation, which encodes the prior knowledge that trees are mainly vertically aligned due to gravity. Finally, we apply hierarchical clustering on the positively classified segments to obtain point sets corresponding to single stems, and perform ℓ1-based orthogonal distance regression to robustly fit lines through each stem point set. The ℓ1-based method is less sensitive to outliers compared to the least square approaches. From the fitted lines, the planimetric tree positions can then be derived. Experiments were performed on two plots from the Hochficht forest in Oberösterreich region located in Austria.We marked a total of 196 reference stems in the point clouds of both plots by visual interpretation. The evaluation of the automatically detected stems showed a classification precision of 0.86 and 0.85, respectively for Plot 1 and 2, with recall values of 0.7 and 0.67.

  14. A Robust Shape Reconstruction Method for Facial Feature Point Detection

    Directory of Open Access Journals (Sweden)

    Shuqiu Tan

    2017-01-01

    Full Text Available Facial feature point detection has been receiving great research advances in recent years. Numerous methods have been developed and applied in practical face analysis systems. However, it is still a quite challenging task because of the large variability in expression and gestures and the existence of occlusions in real-world photo shoot. In this paper, we present a robust sparse reconstruction method for the face alignment problems. Instead of a direct regression between the feature space and the shape space, the concept of shape increment reconstruction is introduced. Moreover, a set of coupled overcomplete dictionaries termed the shape increment dictionary and the local appearance dictionary are learned in a regressive manner to select robust features and fit shape increments. Additionally, to make the learned model more generalized, we select the best matched parameter set through extensive validation tests. Experimental results on three public datasets demonstrate that the proposed method achieves a better robustness over the state-of-the-art methods.

  15. Applicability of low-melting-point microcrystalline wax to develop temperature-sensitive formulations.

    Science.gov (United States)

    Matsumoto, Kohei; Kimura, Shin-Ichiro; Iwao, Yasunori; Itai, Shigeru

    2017-10-30

    Low-melting-point substances are widely used to develop temperature-sensitive formulations. In this study, we focused on microcrystalline wax (MCW) as a low-melting-point substance. We evaluated the drug release behavior of wax matrix (WM) particles using various MCW under various temperature conditions. WM particles containing acetaminophen were prepared using a spray congealing technique. In the dissolution test at 37°C, WM particles containing low-melting-point MCWs whose melting was starting at approx. 40°C (Hi-Mic-1045 or 1070) released the drug initially followed by the release of only a small amount. On the other hand, in the dissolution test at 20 and 25°C for WM particles containing Hi-Mic-1045 and at 20, 25, and 30°C for that containing Hi-Mic-1070, both WM particles showed faster drug release than at 37°C. The characteristic drug release suppression of WM particles containing low-melting-point MCWs at 37°C was thought attributable to MCW melting, as evidenced by differential scanning calorimetry analysis and powder X-ray diffraction analysis. Taken together, low-melting-point MCWs may be applicable to develop implantable temperature-sensitive formulations that drug release is accelerated by cooling at administered site. Copyright © 2017 Elsevier B.V. All rights reserved.

  16. Application of functionalized lanthanide-based nanoparticles for the detection of okadaic acid-specific immunoglobulin G.

    Science.gov (United States)

    Stipić, Filip; Pletikapić, Galja; Jakšić, Željko; Frkanec, Leo; Zgrablić, Goran; Burić, Petra; Lyons, Daniel M

    2015-01-29

    Marine biotoxins are widespread in the environment and impact human health via contaminated shellfish, causing diarrhetic, amnesic, paralytic, or neurotoxic poisoning. In spite of this, methods for determining if poisoning has occurred are limited. We show the development of a simple and sensitive luminescence resonance energy transfer (LRET)-based concept which allows the detection of anti-okadaic acid rabbit polyclonal IgG (mouse monoclonal IgG1) using functionalized lanthanide-based nanoparticles. Upon UV excitation, the functionalized nanoparticles were shown to undergo LRET with fluorophore-labeled anti-okadaic acid antibodies which had been captured and bound by okadaic acid-decorated nanoparticles. The linear dependence of fluorescence emission intensity with antigen-antibody binding events was recorded in the nanomolar to micromolar range, while essentially no LRET signal was detected in the absence of antibody. These results may find applications in new, cheap, and robust sensors for detecting not only immune responses to biotoxins but also a wide range of biomolecules based on antigen-antibody recognition systems. Further, as the system is based on solution chemistry it may be sufficiently simple and versatile to be applied at point-of-care.

  17. Size-exclusion chromatography for the determination of the boiling point distribution of high-boiling petroleum fractions.

    Science.gov (United States)

    Boczkaj, Grzegorz; Przyjazny, Andrzej; Kamiński, Marian

    2015-03-01

    The paper describes a new procedure for the determination of boiling point distribution of high-boiling petroleum fractions using size-exclusion chromatography with refractive index detection. Thus far, the determination of boiling range distribution by chromatography has been accomplished using simulated distillation with gas chromatography with flame ionization detection. This study revealed that in spite of substantial differences in the separation mechanism and the detection mode, the size-exclusion chromatography technique yields similar results for the determination of boiling point distribution compared with simulated distillation and novel empty column gas chromatography. The developed procedure using size-exclusion chromatography has a substantial applicability, especially for the determination of exact final boiling point values for high-boiling mixtures, for which a standard high-temperature simulated distillation would have to be used. In this case, the precision of final boiling point determination is low due to the high final temperatures of the gas chromatograph oven and an insufficient thermal stability of both the gas chromatography stationary phase and the sample. Additionally, the use of high-performance liquid chromatography detectors more sensitive than refractive index detection allows a lower detection limit for high-molar-mass aromatic compounds, and thus increases the sensitivity of final boiling point determination. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  18. Maximum Power Point Tracking of Photovoltaic System for Traffic Light Application

    OpenAIRE

    Muhida, Riza; Mohamad, Nor Hilmi; Legowo, Ari; Irawan, Rudi; Astuti, Winda

    2013-01-01

    Photovoltaic traffic light system is a significant application of renewable energy source. The development of the system is an alternative effort of local authority to reduce expenditure for paying fees to power supplier which the power comes from conventional energy source. Since photovoltaic (PV) modules still have relatively low conversion efficiency, an alternative control of maximum power point tracking (MPPT) method is applied to the traffic light system. MPPT is intended to catch up th...

  19. Consistency considerations in the use of point kinetics for BWR application

    International Nuclear Information System (INIS)

    Holzer, J.M.; Habert, R.; Pilat, E.E.

    1981-01-01

    The basic question of producing point reactivity parameters for use in RETRAN anaylses is addressed. The technique used in establishing a methodology consists of a stepwise reduction of resolution, in space and time, so as to identify possible areas in which error may be induced and to establish procedures that retain consistency and accuracy. The presented calculational flow plan culminating from this analysis will ultimately be used at Yankee Atomic Electric for design application

  20. Person detection and tracking with a 360° lidar system

    Science.gov (United States)

    Hammer, Marcus; Hebel, Marcus; Arens, Michael

    2017-10-01

    Today it is easily possible to generate dense point clouds of the sensor environment using 360° LiDAR (Light Detection and Ranging) sensors which are available since a number of years. The interpretation of these data is much more challenging. For the automated data evaluation the detection and classification of objects is a fundamental task. Especially in urban scenarios moving objects like persons or vehicles are of particular interest, for instance in automatic collision avoidance, for mobile sensor platforms or surveillance tasks. In literature there are several approaches for automated person detection in point clouds. While most techniques show acceptable results in object detection, the computation time is often crucial. The runtime can be problematic, especially due to the amount of data in the panoramic 360° point clouds. On the other hand, for most applications an object detection and classification in real time is needed. The paper presents a proposal for a fast, real-time capable algorithm for person detection, classification and tracking in panoramic point clouds.

  1. Detecting content adaptive scaling of images for forensic applications

    Science.gov (United States)

    Fillion, Claude; Sharma, Gaurav

    2010-01-01

    Content-aware resizing methods have recently been developed, among which, seam-carving has achieved the most widespread use. Seam-carving's versatility enables deliberate object removal and benign image resizing, in which perceptually important content is preserved. Both types of modifications compromise the utility and validity of the modified images as evidence in legal and journalistic applications. It is therefore desirable that image forensic techniques detect the presence of seam-carving. In this paper we address detection of seam-carving for forensic purposes. As in other forensic applications, we pose the problem of seam-carving detection as the problem of classifying a test image in either of two classes: a) seam-carved or b) non-seam-carved. We adopt a pattern recognition approach in which a set of features is extracted from the test image and then a Support Vector Machine based classifier, trained over a set of images, is utilized to estimate which of the two classes the test image lies in. Based on our study of the seam-carving algorithm, we propose a set of intuitively motivated features for the detection of seam-carving. Our methodology for detection of seam-carving is then evaluated over a test database of images. We demonstrate that the proposed method provides the capability for detecting seam-carving with high accuracy. For images which have been reduced 30% by benign seam-carving, our method provides a classification accuracy of 91%.

  2. A point-to-point simple telehealth application for cardiovascular prevention: the ESINO LARIO experience. Cardiovascular prevention at point of care.

    Science.gov (United States)

    Malacarne, Mara; Gobbi, Giorgio; Pizzinelli, Paolo; Lesma, Alessandro; Castelli, Alberto; Lucini, Daniela; Pagani, Massimo

    2009-01-01

    Recent epidemiological evidence indicates that chronic degenerative diseases, notably cardiovascular, represent the major toll in terms of death and of impaired quality of life. Recent estimates indicate that a small increase in financial resources in a number of clinical cases may be sufficient to minimize the consequences of elevated cardiovascular risk per individual. The observation that lifestyle choices, and in particular increased physical exercise, might strongly impact cardiovascular risk, suggests a redesign of preventive strategies, based on the combination of pharmacological and behavioral interventions. Following our recent experience with the INteractive teleConsultation network for worldwide healthcAre Services (INCAS) system, we designed a simpler point-to-point telehealth infrastructure, to be employed in cardiovascular risk reduction programs, predicting a high level of acceptance from the population, at the cost of very limited investment. This model was tested on 181 subjects (ages 18-80 years) in the Italian mountain village of Esino Lario. These subjects underwent a screening test to evaluate arrhythmia and cardiometabolic risks (arrhythmias were found in 14% of subjects, systolic arterial pressure was observed in 43% of subjects above 140 mm Hg, diastolic arterial pressure in 31% above 90 mm Hg). This study demonstrates the feasibility of a scaled-down telehealth application particularly suited to cardiovascular prevention in remote areas, such as in mountain villages.

  3. Application of nanomaterials in the bioanalytical detection of disease-related genes.

    Science.gov (United States)

    Zhu, Xiaoqian; Li, Jiao; He, Hanping; Huang, Min; Zhang, Xiuhua; Wang, Shengfu

    2015-12-15

    In the diagnosis of genetic diseases and disorders, nanomaterials-based gene detection systems have significant advantages over conventional diagnostic systems in terms of simplicity, sensitivity, specificity, and portability. In this review, we describe the application of nanomaterials for disease-related genes detection in different methods excluding PCR-related method, such as colorimetry, fluorescence-based methods, electrochemistry, microarray methods, surface-enhanced Raman spectroscopy (SERS), quartz crystal microbalance (QCM) methods, and dynamic light scattering (DLS). The most commonly used nanomaterials are gold, silver, carbon and semiconducting nanoparticles. Various nanomaterials-based gene detection methods are introduced, their respective advantages are discussed, and selected examples are provided to illustrate the properties of these nanomaterials and their emerging applications for the detection of specific nucleic acid sequences. Copyright © 2015. Published by Elsevier B.V.

  4. A MEMS-based super fast dew point hygrometer—construction and medical applications

    International Nuclear Information System (INIS)

    Jachowicz, Ryszard S; Weremczuk, Jerzy; Paczesny, Daniel; Tarapata, Grzegorz

    2009-01-01

    The paper shows how MEMS (micro-electro-mechanical system) technology and a modified principle of fast temperature control (by heat injection instead of careful control of cooling) can considerably improve the dynamic parameters of dew point hygrometers. Some aspects of MEMS-type integrated sensor construction and technology, whole measurement system design, the control algorithm to run the system as well as empirical dynamic parameters from the tests are discussed too. The hygrometer can easily obtain five to six measurements per second with an uncertainty of less than 0.3 K. The meter range is between −10 °C and 40 °C dew point. In the second part of the paper (section 2), two different successful applications in medicine based on fast humidity measurements have been discussed. Some specific constructions of these super fast dew point hygrometers based on a MEMS sensor as well as limited empirical results from clinical tests have been reported too

  5. A MEMS-based super fast dew point hygrometer—construction and medical applications

    Science.gov (United States)

    Jachowicz, Ryszard S.; Weremczuk, Jerzy; Paczesny, Daniel; Tarapata, Grzegorz

    2009-12-01

    The paper shows how MEMS (micro-electro-mechanical system) technology and a modified principle of fast temperature control (by heat injection instead of careful control of cooling) can considerably improve the dynamic parameters of dew point hygrometers. Some aspects of MEMS-type integrated sensor construction and technology, whole measurement system design, the control algorithm to run the system as well as empirical dynamic parameters from the tests are discussed too. The hygrometer can easily obtain five to six measurements per second with an uncertainty of less than 0.3 K. The meter range is between -10 °C and 40 °C dew point. In the second part of the paper (section 2), two different successful applications in medicine based on fast humidity measurements have been discussed. Some specific constructions of these super fast dew point hygrometers based on a MEMS sensor as well as limited empirical results from clinical tests have been reported too.

  6. 3D Interest Point Detection using Local Surface Characteristics with Application in Action Recognition

    DEFF Research Database (Denmark)

    Holte, Michael Boelstoft

    2014-01-01

    . The proposed Difference-of-Normals (DoN) 3D IP detector operates on the surface mesh, and evaluates the surface structure (curvature) locally (per vertex) in the mesh data. We present an exam- ple of application in action recognition from a sequence of 3-dimensional geometrical data, where local 3D motion de...

  7. An Entropy-Based Network Anomaly Detection Method

    Directory of Open Access Journals (Sweden)

    Przemysław Bereziński

    2015-04-01

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

  8. The Applications of Gold Nanoparticle-Initialed Chemiluminescence in Biomedical Detection

    Science.gov (United States)

    Liu, Zezhong; Zhao, Furong; Gao, Shandian; Shao, Junjun; Chang, Huiyun

    2016-10-01

    Chemiluminescence technique as a novel detection method has gained much attention in recent years owning to the merits of high sensitivity, wider linear ranges, and low background signal. Similarly, nanotechnology especially for gold nanoparticles has emerged as detection tools due to their unique physical and chemical properties. Recently, it has become increasingly popular to couple gold nanoparticles with chemiluminescence technique in biological agents' detection. In this review, we describe the superiority of both chemiluminescence and gold nanoparticles and conclude the different applications of gold nanoparticle-initialed chemiluminescence in biomedical detection.

  9. The effect of tandem-ovoid titanium applicator on points A, B, bladder, and rectum doses in gynecological brachytherapy using 192Ir.

    Science.gov (United States)

    Sadeghi, Mohammad Hosein; Sina, Sedigheh; Mehdizadeh, Amir; Faghihi, Reza; Moharramzadeh, Vahed; Meigooni, Ali Soleimani

    2018-02-01

    The dosimetry procedure by simple superposition accounts only for the self-shielding of the source and does not take into account the attenuation of photons by the applicators. The purpose of this investigation is an estimation of the effects of the tandem and ovoid applicator on dose distribution inside the phantom by MCNP5 Monte Carlo simulations. In this study, the superposition method is used for obtaining the dose distribution in the phantom without using the applicator for a typical gynecological brachytherapy (superposition-1). Then, the sources are simulated inside the tandem and ovoid applicator to identify the effect of applicator attenuation (superposition-2), and the dose at points A, B, bladder, and rectum were compared with the results of superposition. The exact dwell positions, times of the source, and positions of the dosimetry points were determined in images of a patient and treatment data of an adult woman patient from a cancer center. The MCNP5 Monte Carlo (MC) code was used for simulation of the phantoms, applicators, and the sources. The results of this study showed no significant differences between the results of superposition method and the MC simulations for different dosimetry points. The difference in all important dosimetry points was found to be less than 5%. According to the results, applicator attenuation has no significant effect on the calculated points dose, the superposition method, adding the dose of each source obtained by the MC simulation, can estimate the dose to points A, B, bladder, and rectum with good accuracy.

  10. Tree detection in urban regions from aerial imagery and DSM based on local maxima points

    Science.gov (United States)

    Korkmaz, Özgür; Yardımcı ćetin, Yasemin; Yilmaz, Erdal

    2017-05-01

    In this study, we propose an automatic approach for tree detection and classification in registered 3-band aerial images and associated digital surface models (DSM). The tree detection results can be used in 3D city modelling and urban planning. This problem is magnified when trees are in close proximity to each other or other objects such as rooftops in the scenes. This study presents a method for locating individual trees and estimation of crown size based on local maxima from DSM accompanied by color and texture information. For this purpose, segment level classifier trained for 10 classes and classification results are improved by analyzing the class probabilities of neighbour segments. Later, the tree classes under a certain height were eliminated using the Digital Terrain Model (DTM). For the tree classes, local maxima points are obtained and the tree radius estimate is made from the vertical and horizontal height profiles passing through these points. The final tree list containing the centers and radius of the trees is obtained by selecting from the list of tree candidates according to the overlapping and selection parameters. Although the limited number of train sets are used in this study, tree classification and localization results are competitive.

  11. Spatial-Spectral Approaches to Edge Detection in Hyperspectral Remote Sensing

    Science.gov (United States)

    Cox, Cary M.

    This dissertation advances geoinformation science at the intersection of hyperspectral remote sensing and edge detection methods. A relatively new phenomenology among its remote sensing peers, hyperspectral imagery (HSI) comprises only about 7% of all remote sensing research - there are five times as many radar-focused peer reviewed journal articles than hyperspectral-focused peer reviewed journal articles. Similarly, edge detection studies comprise only about 8% of image processing research, most of which is dedicated to image processing techniques most closely associated with end results, such as image classification and feature extraction. Given the centrality of edge detection to mapping, that most important of geographic functions, improving the collective understanding of hyperspectral imagery edge detection methods constitutes a research objective aligned to the heart of geoinformation sciences. Consequently, this dissertation endeavors to narrow the HSI edge detection research gap by advancing three HSI edge detection methods designed to leverage HSI's unique chemical identification capabilities in pursuit of generating accurate, high-quality edge planes. The Di Zenzo-based gradient edge detection algorithm, an innovative version of the Resmini HySPADE edge detection algorithm and a level set-based edge detection algorithm are tested against 15 traditional and non-traditional HSI datasets spanning a range of HSI data configurations, spectral resolutions, spatial resolutions, bandpasses and applications. This study empirically measures algorithm performance against Dr. John Canny's six criteria for a good edge operator: false positives, false negatives, localization, single-point response, robustness to noise and unbroken edges. The end state is a suite of spatial-spectral edge detection algorithms that produce satisfactory edge results against a range of hyperspectral data types applicable to a diverse set of earth remote sensing applications. This work

  12. Datum Feature Extraction and Deformation Analysis Method Based on Normal Vector of Point Cloud

    Science.gov (United States)

    Sun, W.; Wang, J.; Jin, F.; Liang, Z.; Yang, Y.

    2018-04-01

    In order to solve the problem lacking applicable analysis method in the application of three-dimensional laser scanning technology to the field of deformation monitoring, an efficient method extracting datum feature and analysing deformation based on normal vector of point cloud was proposed. Firstly, the kd-tree is used to establish the topological relation. Datum points are detected by tracking the normal vector of point cloud determined by the normal vector of local planar. Then, the cubic B-spline curve fitting is performed on the datum points. Finally, datum elevation and the inclination angle of the radial point are calculated according to the fitted curve and then the deformation information was analyzed. The proposed approach was verified on real large-scale tank data set captured with terrestrial laser scanner in a chemical plant. The results show that the method could obtain the entire information of the monitor object quickly and comprehensively, and reflect accurately the datum feature deformation.

  13. Real-Time Detection of Application-Layer DDoS Attack Using Time Series Analysis

    Directory of Open Access Journals (Sweden)

    Tongguang Ni

    2013-01-01

    Full Text Available Distributed denial of service (DDoS attacks are one of the major threats to the current Internet, and application-layer DDoS attacks utilizing legitimate HTTP requests to overwhelm victim resources are more undetectable. Consequently, neither intrusion detection systems (IDS nor victim server can detect malicious packets. In this paper, a novel approach to detect application-layer DDoS attack is proposed based on entropy of HTTP GET requests per source IP address (HRPI. By approximating the adaptive autoregressive (AAR model, the HRPI time series is transformed into a multidimensional vector series. Then, a trained support vector machine (SVM classifier is applied to identify the attacks. The experiments with several databases are performed and results show that this approach can detect application-layer DDoS attacks effectively.

  14. Point application with Angong Niuhuang sticker protects hippocampal and cortical neurons in rats with cerebral ischemia

    Directory of Open Access Journals (Sweden)

    Dong-shu Zhang

    2015-01-01

    Full Text Available Angong Niuhuang pill, a Chinese materia medica preparation, can improve neurological functions after acute ischemic stroke. Because of its inconvenient application and toxic components (Cinnabaris and Realgar, we used transdermal enhancers to deliver Angong Niuhuang pill by modern technology, which expanded the safe dose range and clinical indications. In this study, Angong Niuhuang stickers administered at different point application doses (1.35, 2.7, and 5.4 g/kg were administered to the Dazhui (DU14, Qihai (RN6 and Mingmen (DU4 of rats with chronic cerebral ischemia, for 4 weeks. The Morris water maze was used to determine the learning and memory ability of rats. Hematoxylin-eosin staining and Nissl staining were used to observe neuronal damage of the cortex and hippocampal CA1 region in rats with chronic cerebral ischemia. The middle- and high-dose point application of Angong Niuhuang stickers attenuated neuronal damage in the cortex and hippocampal CA1 region, and improved the memory of rats with chronic cerebral ischemia with an efficacy similar to interventions by electroacupuncture at Dazhui (DU14, Qihai (RN6 and Mingmen (DU4. Our experimental findings indicate that point application with Angong Niuhuang stickers can improve cognitive function after chronic cerebral ischemia in rats and is neuroprotective with an equivalent efficacy to acupuncture.

  15. Raster Vs. Point Cloud LiDAR Data Classification

    Science.gov (United States)

    El-Ashmawy, N.; Shaker, A.

    2014-09-01

    Airborne Laser Scanning systems with light detection and ranging (LiDAR) technology is one of the fast and accurate 3D point data acquisition techniques. Generating accurate digital terrain and/or surface models (DTM/DSM) is the main application of collecting LiDAR range data. Recently, LiDAR range and intensity data have been used for land cover classification applications. Data range and Intensity, (strength of the backscattered signals measured by the LiDAR systems), are affected by the flying height, the ground elevation, scanning angle and the physical characteristics of the objects surface. These effects may lead to uneven distribution of point cloud or some gaps that may affect the classification process. Researchers have investigated the conversion of LiDAR range point data to raster image for terrain modelling. Interpolation techniques have been used to achieve the best representation of surfaces, and to fill the gaps between the LiDAR footprints. Interpolation methods are also investigated to generate LiDAR range and intensity image data for land cover classification applications. In this paper, different approach has been followed to classifying the LiDAR data (range and intensity) for land cover mapping. The methodology relies on the classification of the point cloud data based on their range and intensity and then converted the classified points into raster image. The gaps in the data are filled based on the classes of the nearest neighbour. Land cover maps are produced using two approaches using: (a) the conventional raster image data based on point interpolation; and (b) the proposed point data classification. A study area covering an urban district in Burnaby, British Colombia, Canada, is selected to compare the results of the two approaches. Five different land cover classes can be distinguished in that area: buildings, roads and parking areas, trees, low vegetation (grass), and bare soil. The results show that an improvement of around 10 % in the

  16. The application of microwave photonic detection in quantum communication

    Science.gov (United States)

    Diao, Wenting; Zhuang, Yongyong; Song, Xuerui; Wang, Liujun; Duan, Chongdi

    2018-03-01

    Quantum communication has attracted much attention in recent years, provides an ultimate level of security, and uniquely it is one of the most likely practical quantum technologies at present. In order to realize global coverage of quantum communication networks, not only need the help of satellite to realize wide area quantum communication, need implementation of optical fiber system to realize city to city quantum communication, but also, it is necessary to implement end-to-end quantum communications intercity and wireless quantum communications that can be received by handheld devices. Because of the limitation of application of light in buildings, it needs quantum communication with microwave band to achieve quantum reception of wireless handheld devices. The single microwave photon energy is very low, it is difficult to directly detect, which become a difficulty in microwave quantum detection. This paper summarizes the mode of single microwave photon detection methods and the possibility of application in microwave quantum communication, and promotes the development of quantum communication in microwave band and quantum radar.

  17. Adaptive 4d Psi-Based Change Detection

    Science.gov (United States)

    Yang, Chia-Hsiang; Soergel, Uwe

    2018-04-01

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

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

    Directory of Open Access Journals (Sweden)

    Linda C. Rogers

    2016-01-01

    Full Text Available 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.

  19. Preliminary studies on DNA retardation by MutS applied to the detection of point mutations in clinical samples

    International Nuclear Information System (INIS)

    Stanislawska-Sachadyn, Anna; Paszko, Zygmunt; Kluska, Anna; Skasko, Elzibieta; Sromek, Maria; Balabas, Aneta; Janiec-Jankowska, Aneta; Wisniewska, Alicja; Kur, Jozef; Sachadyn, Pawel

    2005-01-01

    MutS ability to bind DNA mismatches was applied to the detection of point mutations in PCR products. MutS recognized mismatches from single up to five nucleotides and retarded the electrophoretic migration of mismatched DNA. The electrophoretic detection of insertions/deletions above three nucleotides is also possible without MutS, thanks to the DNA mobility shift caused by the presence of large insertion/deletion loops in the heteroduplex DNA. Thus, the method enables the search for a broad range of mutations: from single up to several nucleotides. The mobility shift assays were carried out in polyacrylamide gels stained with SYBR-Gold. One assay required 50-200 ng of PCR product and 1-3 μg of Thermus thermophilus his 6 -MutS protein. The advantages of this approach are: the small amounts of DNA required for the examination, simple and fast staining, no demand for PCR product purification, no labelling and radioisotopes required. The method was tested in the detection of cancer predisposing mutations in RET, hMSH2, hMLH1, BRCA1, BRCA2 and NBS1 genes. The approach appears to be promising in screening for unknown point mutations

  20. Recent developments in optical detection methods for microchip separations.

    Science.gov (United States)

    Götz, Sebastian; Karst, Uwe

    2007-01-01

    This paper summarizes the features and performances of optical detection systems currently applied in order to monitor separations on microchip devices. Fluorescence detection, which delivers very high sensitivity and selectivity, is still the most widely applied method of detection. Instruments utilizing laser-induced fluorescence (LIF) and lamp-based fluorescence along with recent applications of light-emitting diodes (LED) as excitation sources are also covered in this paper. Since chemiluminescence detection can be achieved using extremely simple devices which no longer require light sources and optical components for focusing and collimation, interesting approaches based on this technique are presented, too. Although UV/vis absorbance is a detection method that is commonly used in standard desktop electrophoresis and liquid chromatography instruments, it has not yet reached the same level of popularity for microchip applications. Current applications of UV/vis absorbance detection to microchip separations and innovative approaches that increase sensitivity are described. This article, which contains 85 references, focuses on developments and applications published within the last three years, points out exciting new approaches, and provides future perspectives on this field.

  1. The application of new technologies in food microbiological inspection and detection

    Directory of Open Access Journals (Sweden)

    CHEN Wenwen

    2016-02-01

    Full Text Available In today′s society,as people′s demand for food increases,the problem of food safety is getting more and more concerns.Therefore it is very necessary to seek and to establish the rapid method detection of food microorganisms.This paper presents several new technologies for rapid detection of food microorganism and their application in the practical detection.

  2. Microfabricated Chemical Sensors for Aerospace Fire Detection Applications

    Science.gov (United States)

    Hunter, Gary W.; Neudeck, Philip G.; Fralick, Gustave; Thomas, Valarie; Makel, D.; Liu, C. C.; Ward, B.; Wu, Q. H.

    2001-01-01

    The detection of fires on-board commercial aircraft is extremely important for safety reasons. Although dependable fire detection equipment presently exists within the cabin, detection of fire within the cargo hold has been less reliable and susceptible to false alarms. A second, independent method of fire detection to complement the conventional smoke detection techniques, such as the measurement of chemical species indicative of a fire, will help reduce false alarms and improve aircraft safety. Although many chemical species are indicative of a fire, two species of particular interest are CO and CO2. This paper discusses microfabricated chemical sensor development tailored to meet the needs of fire safety applications. This development is based on progress in three types of technology: 1) Micromachining and microfabrication (Microsystem) technology to fabricate miniaturized sensors. 2) The use of nanocrystalline materials to develop sensors with improved stability combined with higher sensitivity. 3) The development of high temperature semiconductors, especially silicon carbide. The individual sensor being developed and their level of maturity will be presented.

  3. Web Based Application for Early Detection of Vitamin and Mineral Deficiency

    Directory of Open Access Journals (Sweden)

    Nina Sevani

    2016-10-01

    Full Text Available Deficiency of vitamin and mineral as part of micronutrient deficiency may lower human productivity. In general, lack of public understanding about micronutrient, limited number of nutritionist, time and cost, became the reason for people reluctant to meet nutritionist. The use of web-based computer application can be implemented to overcome the difficulty to get nutritionist’s services. Using the application, user can detect and check their micronutrient condition independently. User can submit their physical condition by answering questions from the application. Using forward chaining inference, data from user will be proceed using certainty factor method. The application’s output are the possible type of micronutrient’s deficiency and the weight that shown the level of confidence of the result. The evaluation process shown that the application functioning properly in line with the expectation. Beside helping people to make early detection independenly, the presence of the application is also expected to increase public awareness about the importance of micronutrient in their life.   

  4. Fast Occlusion and Shadow Detection for High Resolution Remote Sensing Image Combined with LIDAR Point Cloud

    Science.gov (United States)

    Hu, X.; Li, X.

    2012-08-01

    The orthophoto is an important component of GIS database and has been applied in many fields. But occlusion and shadow causes the loss of feature information which has a great effect on the quality of images. One of the critical steps in true orthophoto generation is the detection of occlusion and shadow. Nowadays LiDAR can obtain the digital surface model (DSM) directly. Combined with this technology, image occlusion and shadow can be detected automatically. In this paper, the Z-Buffer is applied for occlusion detection. The shadow detection can be regarded as a same problem with occlusion detection considering the angle between the sun and the camera. However, the Z-Buffer algorithm is computationally expensive. And the volume of scanned data and remote sensing images is very large. Efficient algorithm is another challenge. Modern graphics processing unit (GPU) is much more powerful than central processing unit (CPU). We introduce this technology to speed up the Z-Buffer algorithm and get 7 times increase in speed compared with CPU. The results of experiments demonstrate that Z-Buffer algorithm plays well in occlusion and shadow detection combined with high density of point cloud and GPU can speed up the computation significantly.

  5. FAST OCCLUSION AND SHADOW DETECTION FOR HIGH RESOLUTION REMOTE SENSING IMAGE COMBINED WITH LIDAR POINT CLOUD

    Directory of Open Access Journals (Sweden)

    X. Hu

    2012-08-01

    Full Text Available The orthophoto is an important component of GIS database and has been applied in many fields. But occlusion and shadow causes the loss of feature information which has a great effect on the quality of images. One of the critical steps in true orthophoto generation is the detection of occlusion and shadow. Nowadays LiDAR can obtain the digital surface model (DSM directly. Combined with this technology, image occlusion and shadow can be detected automatically. In this paper, the Z-Buffer is applied for occlusion detection. The shadow detection can be regarded as a same problem with occlusion detection considering the angle between the sun and the camera. However, the Z-Buffer algorithm is computationally expensive. And the volume of scanned data and remote sensing images is very large. Efficient algorithm is another challenge. Modern graphics processing unit (GPU is much more powerful than central processing unit (CPU. We introduce this technology to speed up the Z-Buffer algorithm and get 7 times increase in speed compared with CPU. The results of experiments demonstrate that Z-Buffer algorithm plays well in occlusion and shadow detection combined with high density of point cloud and GPU can speed up the computation significantly.

  6. CANDU pressure tube leak detection by annulus gas dew point measurement. A critical review

    International Nuclear Information System (INIS)

    Greening, F.R.

    2017-01-01

    In the event of a pressure tube leak from a small through-wall crack during CANDU reactor operations, there is a regulatory requirement - referred to as Leak Before Break (LBB) - for the licensee to demonstrate that there will be sufficient time for the leak to be detected and the reactor shut down before the crack grows to the critical size for fast-uncontrolled rupture. In all currently operating CANDU reactors, worldwide, this LBB requirement is met via continuous dew point measurements of the CO_2 gas circulating in the reactor's Annulus Gas System (AGS). In this paper the historical development and current status of this leak detection capability is reviewed and the use of moisture injection tests as a verification procedure is critiqued. It is concluded that these tests do not represent AGS conditions that are to be expected in the event of a real pressure tube leak.

  7. CANDU pressure tube leak detection by annulus gas dew point measurement. A critical review

    Energy Technology Data Exchange (ETDEWEB)

    Greening, F.R. [CTS-NA, Tiverton, ON (Canada)

    2017-03-15

    In the event of a pressure tube leak from a small through-wall crack during CANDU reactor operations, there is a regulatory requirement - referred to as Leak Before Break (LBB) - for the licensee to demonstrate that there will be sufficient time for the leak to be detected and the reactor shut down before the crack grows to the critical size for fast-uncontrolled rupture. In all currently operating CANDU reactors, worldwide, this LBB requirement is met via continuous dew point measurements of the CO{sub 2} gas circulating in the reactor's Annulus Gas System (AGS). In this paper the historical development and current status of this leak detection capability is reviewed and the use of moisture injection tests as a verification procedure is critiqued. It is concluded that these tests do not represent AGS conditions that are to be expected in the event of a real pressure tube leak.

  8. Criteria required for an acceptable point-of-care test for UTI detection: Obtaining consensus using the Delphi technique.

    Science.gov (United States)

    Weir, Nichola-Jane M; Pattison, Sally H; Kearney, Paddy; Stafford, Bob; Gormley, Gerard J; Crockard, Martin A; Gilpin, Deirdre F; Tunney, Michael M; Hughes, Carmel M

    2018-01-01

    Urinary Tract Infections (UTIs) are common bacterial infections, second only to respiratory tract infections and particularly prevalent within primary care. Conventional detection of UTIs is culture, however, return of results can take between 24 and 72 hours. The introduction of a point of care (POC) test would allow for more timely identification of UTIs, facilitating improved, targeted treatment. This study aimed to obtain consensus on the criteria required for a POC UTI test, to meet patient need within primary care. Criteria for consideration were compiled by the research team. These criteria were validated through a two-round Delphi process, utilising an expert panel of healthcare professionals from across Europe and United States of America. Using web-based questionnaires, panellists recorded their level of agreement with each criterion based on a 5-point Likert Scale, with space for comments. Using median response, interquartile range and comments provided, criteria were accepted/rejected/revised depending on pre-agreed cut-off scores. The first round questionnaire presented thirty-three criteria to the panel, of which 22 were accepted. Consensus was not achieved for the remaining 11 criteria. Following response review, one criterion was removed, while after revision, the remaining 10 criteria entered the second round. Of these, four were subsequently accepted, resulting in 26 criteria considered appropriate for a POC test to detect urinary infections. This study generated an approved set of criteria for a POC test to detect urinary infections. Criteria acceptance and comments provided by the healthcare professionals also supports the development of a multiplex point of care UTI test.

  9. Use of dew-point detection for quantitative measurement of sweating rate

    Science.gov (United States)

    Brengelmann, G. L.; Mckeag, M.; Rowell, L. B.

    1975-01-01

    A method of measuring sweat rate (SR) based on detection of dew point (DP) is proposed which has advantages that may be attractive to other laboratories concerned with recording SR from selected areas of skin. It is similar to other methods in that dry gas is passed through a capsule which isolates several square centimeters of skin surface. The difference is in the means of determining how much gaseous water is carried off in the effluent moist gas. The DP detector used is free of the drawbacks of previous devices. DP is obtained through the fundamental technique of determining the temperature at which condensate forms on a mirror. Variations in DP are tracked rapidly, and accurately (+ or - 0.8 C nominal, sensitivity + or - 0.05 C) over a wide range ( -40 C to +50 C) without measurable hysteresis. The detector asembly is rugged and readily opened for cleaning and inspection.

  10. Low-current solutions for wireless point-to-point sensor data transmission for long-term applications; Stromsparende Loesungen fuer drahtlose Punkt-zu-Punkt-Sensordatenuebertragung fuer langjaehrigen Betrieb

    Energy Technology Data Exchange (ETDEWEB)

    Milosiu, H. [Fraunhofer-Institut fuer Integrierte Schaltungen IIS, Erlangen (Germany)

    2008-07-01

    Choosing wireless standard such as Bluetooth or Zigbee, the customer can find numerous low-cost chip sets. In particular applications proprietary solutions are superior to wireless standard solutions, especially for transmission of small data amounts from point to point. The complex transmission protocol of a wireless standard forms a inflexible precondition for the user and may exclude the choice of a wireless standard. In addition, a relatively high energy consumption disables battery-operated low-maintenance applications. Fraunhofer Institute for Integrated Circuits IIS in Erlangen now offers a solution to that problem. This article would like to show the benefits of low-current proprietary wireless systems. An implementation of a lowcurrent wireless system using BiCMOS technology for wireless sensor networks is presented. (orig.)

  11. An automated three-dimensional detection and segmentation method for touching cells by integrating concave points clustering and random walker algorithm.

    Directory of Open Access Journals (Sweden)

    Yong He

    Full Text Available Characterizing cytoarchitecture is crucial for understanding brain functions and neural diseases. In neuroanatomy, it is an important task to accurately extract cell populations' centroids and contours. Recent advances have permitted imaging at single cell resolution for an entire mouse brain using the Nissl staining method. However, it is difficult to precisely segment numerous cells, especially those cells touching each other. As presented herein, we have developed an automated three-dimensional detection and segmentation method applied to the Nissl staining data, with the following two key steps: 1 concave points clustering to determine the seed points of touching cells; and 2 random walker segmentation to obtain cell contours. Also, we have evaluated the performance of our proposed method with several mouse brain datasets, which were captured with the micro-optical sectioning tomography imaging system, and the datasets include closely touching cells. Comparing with traditional detection and segmentation methods, our approach shows promising detection accuracy and high robustness.

  12. Application of Peptide Nucleic Acid-based Assays Toward Detection of Somatic Mosaicism

    Directory of Open Access Journals (Sweden)

    Christopher S Hong

    2016-01-01

    Full Text Available Peptide nucleic acids (PNAs are synthetic oligonucleotides with many applications. Compared with DNA, PNAs bind their complementary DNA strand with higher specificity and strength, an attribute that can make it an effective polymerase chain reaction clamp. A growing body of work has demonstrated the utility of PNAs in detecting low levels of mutant DNA, particularly in the detection of circulating mutated tumor cells in the peripheral blood. The PNA-based assay has greater sensitivity than direct sequencing and is significantly more affordable and rapid than next-generation deep sequencing. We have previously demonstrated that PNAs can successfully detect somatic mosaicism in patients with suspected disease phenotypes. In this report, we detail our methodology behind PNA design and application. We describe our protocol for optimizing the PNA for sequencing use and for determining the sensitivity of the PNA-based assay. Lastly, we discuss the potential applications of our assay for future laboratory and clinical purposes and highlight the role of PNAs in the detection of somatic mosaicism.

  13. Optical detection of random features for high security applications

    Science.gov (United States)

    Haist, T.; Tiziani, H. J.

    1998-02-01

    Optical detection of random features in combination with digital signatures based on public key codes in order to recognize counterfeit objects will be discussed. Without applying expensive production techniques objects are protected against counterfeiting. Verification is done off-line by optical means without a central authority. The method is applied for protecting banknotes. Experimental results for this application are presented. The method is also applicable for identity verification of a credit- or chip-card holder.

  14. Section-Based Tree Species Identification Using Airborne LIDAR Point Cloud

    Science.gov (United States)

    Yao, C.; Zhang, X.; Liu, H.

    2017-09-01

    The application of LiDAR data in forestry initially focused on mapping forest community, particularly and primarily intended for largescale forest management and planning. Then with the smaller footprint and higher sampling density LiDAR data available, detecting individual tree overstory, estimating crowns parameters and identifying tree species are demonstrated practicable. This paper proposes a section-based protocol of tree species identification taking palm tree as an example. Section-based method is to detect objects through certain profile among different direction, basically along X-axis or Y-axis. And this method improve the utilization of spatial information to generate accurate results. Firstly, separate the tree points from manmade-object points by decision-tree-based rules, and create Crown Height Mode (CHM) by subtracting the Digital Terrain Model (DTM) from the digital surface model (DSM). Then calculate and extract key points to locate individual trees, thus estimate specific tree parameters related to species information, such as crown height, crown radius, and cross point etc. Finally, with parameters we are able to identify certain tree species. Comparing to species information measured on ground, the portion correctly identified trees on all plots could reach up to 90.65 %. The identification result in this research demonstrate the ability to distinguish palm tree using LiDAR point cloud. Furthermore, with more prior knowledge, section-based method enable the process to classify trees into different classes.

  15. Nanomechanical resonators and their applications in biological/chemical detection: Nanomechanics principles

    International Nuclear Information System (INIS)

    Eom, Kilho; Park, Harold S.; Yoon, Dae Sung; Kwon, Taeyun

    2011-01-01

    Recent advances in nanotechnology have led to the development of nano-electro-mechanical systems (NEMS) such as nanomechanical resonators, which have recently received significant attention from the scientific community. This is not only due to their capability of label-free detection of bio/chemical molecules at single-molecule (or atomic) resolution for future applications such as the early diagnosis of diseases like cancer, but also due to their unprecedented ability to detect physical quantities such as molecular weight, elastic stiffness, surface stress, and surface elastic stiffness for adsorbed molecules on the surface. Most experimental works on resonator-based molecular detection have been based on the principle that molecular adsorption onto a resonator surface increases the effective mass, and consequently decreases the resonant frequencies of the nanomechanical resonator. However, this principle is insufficient to provide fundamental insights into resonator-based molecular detection at the nanoscale; this is due to recently proposed novel nanoscale detection principles including various effects such as surface effects, nonlinear oscillations, coupled resonance, and stiffness effects. Furthermore, these effects have only recently been incorporated into existing physical models for resonators, and therefore the universal physical principles governing nanoresonator-based detection have not been completely described. Therefore, our objective in this review is to overview the current attempts to understand the underlying mechanisms in nanoresonator-based detection using physical models coupled to computational simulations and/or experiments. Specifically, we will focus on issues of special relevance to the dynamic behavior of nanoresonators and their applications in biological/chemical detection: the resonance behavior of micro/nanoresonators; resonator-based chemical/biological detection; physical models of various nanoresonators such as nanowires, carbon

  16. Development of a point-kinetic verification scheme for nuclear reactor applications

    Energy Technology Data Exchange (ETDEWEB)

    Demazière, C., E-mail: demaz@chalmers.se; Dykin, V.; Jareteg, K.

    2017-06-15

    In this paper, a new method that can be used for checking the proper implementation of time- or frequency-dependent neutron transport models and for verifying their ability to recover some basic reactor physics properties is proposed. This method makes use of the application of a stationary perturbation to the system at a given frequency and extraction of the point-kinetic component of the system response. Even for strongly heterogeneous systems for which an analytical solution does not exist, the point-kinetic component follows, as a function of frequency, a simple analytical form. The comparison between the extracted point-kinetic component and its expected analytical form provides an opportunity to verify and validate neutron transport solvers. The proposed method is tested on two diffusion-based codes, one working in the time domain and the other working in the frequency domain. As long as the applied perturbation has a non-zero reactivity effect, it is demonstrated that the method can be successfully applied to verify and validate time- or frequency-dependent neutron transport solvers. Although the method is demonstrated in the present paper in a diffusion theory framework, higher order neutron transport methods could be verified based on the same principles.

  17. Change detection using landsat time series: A review of frequencies, preprocessing, algorithms, and applications

    Science.gov (United States)

    Zhu, Zhe

    2017-08-01

    The free and open access to all archived Landsat images in 2008 has completely changed the way of using Landsat data. Many novel change detection algorithms based on Landsat time series have been developed We present a comprehensive review of four important aspects of change detection studies based on Landsat time series, including frequencies, preprocessing, algorithms, and applications. We observed the trend that the more recent the study, the higher the frequency of Landsat time series used. We reviewed a series of image preprocessing steps, including atmospheric correction, cloud and cloud shadow detection, and composite/fusion/metrics techniques. We divided all change detection algorithms into six categories, including thresholding, differencing, segmentation, trajectory classification, statistical boundary, and regression. Within each category, six major characteristics of different algorithms, such as frequency, change index, univariate/multivariate, online/offline, abrupt/gradual change, and sub-pixel/pixel/spatial were analyzed. Moreover, some of the widely-used change detection algorithms were also discussed. Finally, we reviewed different change detection applications by dividing these applications into two categories, change target and change agent detection.

  18. Point-of-care ultrasound in aerospace medicine: known and potential applications.

    Science.gov (United States)

    Wagner, Michael S; Garcia, Kathleen; Martin, David S

    2014-07-01

    Since its initial introduction into the bedside assessment of the trauma patient via the Focused Assessment with Sonography for Trauma (FAST) exam, the use of point-of-care ultrasound has expanded rapidly. A growing body of literature demonstrates ultrasound can be used by nonradiologists as an extension of the physical exam to accurately diagnose or exclude a variety of conditions. These conditions include, but are not limited to, hemoperitoneum, pneumothorax, pulmonary edema, long-bone fracture, deep vein thrombosis, and elevated intracranial pressure. As ultrasound machines have become more compact and portable, their use has extended outside of hospitals to places where the physical exam and diagnostic capabilities may be limited, including the aviation environment. A number of studies using focused sonography have been performed to meet the diagnostic challenges of space medicine. The following article reviews the available literature on portable ultrasound use in aerospace medicine and highlights both known and potential applications of point-of-care ultrasound for the aeromedical clinician.

  19. A New Method of Gold Foil Damage Detection in Stone Carving Relics Based on Multi-Temporal 3D LiDAR Point Clouds

    Directory of Open Access Journals (Sweden)

    Miaole Hou

    2016-05-01

    Full Text Available The timely detection of gold foil damage in gold-overlaid stone carvings and the associated maintenance of these relics pose several challenges to both the research and heritage protection communities internationally. This paper presents a new method for detecting gold foil damage by making use of multi-temporal 3D LiDAR point clouds. By analyzing the errors involved in the detection process, a formula is developed for calculation of the damage detection threshold. An improved division method for the linear octree that only allocates memory to the non-blank nodes, is proposed, which improves storage and retrieval efficiency for the point clouds. Meanwhile, the damage-occurrence regions are determined according to Hausdorff distances. Using a triangular mesh, damaged regions can be identified and measured in order to determine the relic’s total damaged area. Results demonstrate that this method can effectively detect gold foil damage in stone carvings. The identified surface area of damaged regions can provide the information needed for subsequent restoration and protection of relics of this type.

  20. A feature point identification method for positron emission particle tracking with multiple tracers

    Energy Technology Data Exchange (ETDEWEB)

    Wiggins, Cody, E-mail: cwiggin2@vols.utk.edu [University of Tennessee-Knoxville, Department of Physics and Astronomy, 1408 Circle Drive, Knoxville, TN 37996 (United States); Santos, Roque [University of Tennessee-Knoxville, Department of Nuclear Engineering (United States); Escuela Politécnica Nacional, Departamento de Ciencias Nucleares (Ecuador); Ruggles, Arthur [University of Tennessee-Knoxville, Department of Nuclear Engineering (United States)

    2017-01-21

    A novel detection algorithm for Positron Emission Particle Tracking (PEPT) with multiple tracers based on optical feature point identification (FPI) methods is presented. This new method, the FPI method, is compared to a previous multiple PEPT method via analyses of experimental and simulated data. The FPI method outperforms the older method in cases of large particle numbers and fine time resolution. Simulated data show the FPI method to be capable of identifying 100 particles at 0.5 mm average spatial error. Detection error is seen to vary with the inverse square root of the number of lines of response (LORs) used for detection and increases as particle separation decreases. - Highlights: • A new approach to positron emission particle tracking is presented. • Using optical feature point identification analogs, multiple particle tracking is achieved. • Method is compared to previous multiple particle method. • Accuracy and applicability of method is explored.

  1. Detecting Levels of Polyquaternium-10 (PQ-10) via Potentiometric Titration with Dextran Sulphate and Monitoring the Equivalence Point with a Polymeric Membrane-Based Polyion Sensor.

    Science.gov (United States)

    Ferguson, Stephen A; Wang, Xuewei; Meyerhoff, Mark E

    2016-08-07

    Polymeric quaternary ammonium salts (polyquaterniums) have found increasing use in industrial and cosmetic applications in recent years. More specifically, polyquaternium-10 (PQ-10) is routinely used in cosmetic applications as a conditioner in personal care product formulations. Herein, we demonstrate the use of potentiometric polyion-sensitive polymeric membrane-based electrodes to quantify PQ-10 levels. Mixtures containing both PQ-10 and sodium lauryl sulfate (SLS) are used as model samples to illustrate this new method. SLS is often present in cosmetic samples that contain PQ-10 (e.g., shampoos, etc.) and this surfactant species interferes with the polyion sensor detection chemistry. However, it is shown here that SLS can be readily separated from the PQ-10/SLS mixture by use of an anion-exchange resin and that the PQ-10 can then be titrated with dextran sulphate (DS). This titration is monitored by potentiometric polyanion sensors to provide equivalence points that are directly proportional to PQ-10 concentrations.

  2. Derivation of Pal-Bell equations for two-point reactors, and its application to correlation measurements at KUCA

    International Nuclear Information System (INIS)

    Murata, Naoyuki; Yamane, Yoshihiro; Nishina, Kojiro; Shiroya, Seiji; Kanda, Keiji.

    1980-01-01

    A probability is defined for an event in which m neutrons exist at time t sub(f) in core I of a coupled-core system, originating from a neutron injected into the core I at an earlier time t; we call it P sub(I,I,m)(t sub(f)/t). Similarly, P sub(I,II,m)(t sub(f)/t) is defined as the probability for m neutrons to exist in core II of the system at time t sub(f), originating from a neutron injected into the core I at time t. Then a system of coupled equations are derived for the generating functions G sub(Ij)(z, t sub(f)/t) = μP sub(Ijm)(t sub(f)/t).z sup(m), where j = I, II. By similar procedures equations are derived for the generating functions associated with joint probability of the following events: a given combination of numbers of neutrons are detected during given series of detection time intervals by a detector inserted in one of the cores. The above two kinds of systems of equations can be regarded as a two-point version of Pal-Bell's equations. As the application of these formulations, analyzing formula for correlation measurements, namely (1) Feynman-alpha experiment and (2) Rossi-alpha experiment of Orndoff-type, are derived, and their feasibility is verified by experiments carried out at KUCA. (author)

  3. Application of nanotechnology in detection of mycotoxins and in agricultural sector

    Directory of Open Access Journals (Sweden)

    Nadejda Sertova

    2015-06-01

    Full Text Available A brief review of nanotechnology application in detection of mycotoxins and in agriculture sector was presented. Mycotoxins are secondary metabolites produced by fungi. Their toxicity is the reason for implementation of various screening methods to detect them. During the last years, the highlight was put on nanoscale materials included in biosensors, which were some of the smart devices used for determination of mycotoxins, and in agriculture sector. Over the next decade, the progress of nanotechnology will demonstrated a way to improve detection of contaminated feed and food. To achieve this purpose the innovations of nanomaterials reported every year would be applied. In the paper, some of the applications developed by nanotechnology that would contribute to the implementation of new tools for analysis of mycotoxins and agricultural products were discussed.

  4. Application of thermometric methods for detection and characterization of leakages in embankment dams

    Energy Technology Data Exchange (ETDEWEB)

    Beck, Y.L.; Cunat, P.; Fry, J.J. [EDF, Grenoble (France); Faure, Y.H. [LTHE, Saint Martin d' Heres (France)

    2010-07-01

    The earliest possible detection of leakages in dikes is essential. Distributed temperature measurements using fibre optics allow the monitoring of large sections of the dike with a high spatial and temperature resolution. This paper presented the application of thermometric methods for detection and characterization of leakage in embankment dams. After a brief description of the system used, its application on a controlled experimental site and an EDF industrial site instrumented with fibre optics was presented. The instrumentation is complemented by installation of local temperature and pressure sensors in the piezometers for complete characterization of the detected leakages. The analysis of the results data clearly allowed detecting the leakages. The vertical location, intensity and location of the detected leakages were also identified. It was found that thermometry is potentially very powerful for detecting leaks and as a diagnostic tool.

  5. Simple Approaches to Minimally-Instrumented, Microfluidic-Based Point-of-Care Nucleic Acid Amplification Tests

    Science.gov (United States)

    Mauk, Michael G.; Song, Jinzhao; Liu, Changchun; Bau, Haim H.

    2018-01-01

    Designs and applications of microfluidics-based devices for molecular diagnostics (Nucleic Acid Amplification Tests, NAATs) in infectious disease testing are reviewed, with emphasis on minimally instrumented, point-of-care (POC) tests for resource-limited settings. Microfluidic cartridges (‘chips’) that combine solid-phase nucleic acid extraction; isothermal enzymatic nucleic acid amplification; pre-stored, paraffin-encapsulated lyophilized reagents; and real-time or endpoint optical detection are described. These chips can be used with a companion module for separating plasma from blood through a combined sedimentation-filtration effect. Three reporter types: Fluorescence, colorimetric dyes, and bioluminescence; and a new paradigm for end-point detection based on a diffusion-reaction column are compared. Multiplexing (parallel amplification and detection of multiple targets) is demonstrated. Low-cost detection and added functionality (data analysis, control, communication) can be realized using a cellphone platform with the chip. Some related and similar-purposed approaches by others are surveyed. PMID:29495424

  6. Simple Approaches to Minimally-Instrumented, Microfluidic-Based Point-of-Care Nucleic Acid Amplification Tests

    Directory of Open Access Journals (Sweden)

    Michael G. Mauk

    2018-02-01

    Full Text Available Designs and applications of microfluidics-based devices for molecular diagnostics (Nucleic Acid Amplification Tests, NAATs in infectious disease testing are reviewed, with emphasis on minimally instrumented, point-of-care (POC tests for resource-limited settings. Microfluidic cartridges (‘chips’ that combine solid-phase nucleic acid extraction; isothermal enzymatic nucleic acid amplification; pre-stored, paraffin-encapsulated lyophilized reagents; and real-time or endpoint optical detection are described. These chips can be used with a companion module for separating plasma from blood through a combined sedimentation-filtration effect. Three reporter types: Fluorescence, colorimetric dyes, and bioluminescence; and a new paradigm for end-point detection based on a diffusion-reaction column are compared. Multiplexing (parallel amplification and detection of multiple targets is demonstrated. Low-cost detection and added functionality (data analysis, control, communication can be realized using a cellphone platform with the chip. Some related and similar-purposed approaches by others are surveyed.

  7. Periodic Application of Concurrent Error Detection in Processor Array Architectures. PhD. Thesis -

    Science.gov (United States)

    Chen, Paul Peichuan

    1993-01-01

    Processor arrays can provide an attractive architecture for some applications. Featuring modularity, regular interconnection and high parallelism, such arrays are well-suited for VLSI/WSI implementations, and applications with high computational requirements, such as real-time signal processing. Preserving the integrity of results can be of paramount importance for certain applications. In these cases, fault tolerance should be used to ensure reliable delivery of a system's service. One aspect of fault tolerance is the detection of errors caused by faults. Concurrent error detection (CED) techniques offer the advantage that transient and intermittent faults may be detected with greater probability than with off-line diagnostic tests. Applying time-redundant CED techniques can reduce hardware redundancy costs. However, most time-redundant CED techniques degrade a system's performance.

  8. Pedestrian Detection by Laser Scanning and Depth Imagery

    Science.gov (United States)

    Barsi, A.; Lovas, T.; Molnar, B.; Somogyi, A.; Igazvolgyi, Z.

    2016-06-01

    Pedestrian flow is much less regulated and controlled compared to vehicle traffic. Estimating flow parameters would support many safety, security or commercial applications. Current paper discusses a method that enables acquiring information on pedestrian movements without disturbing and changing their motion. Profile laser scanner and depth camera have been applied to capture the geometry of the moving people as time series. Procedures have been developed to derive complex flow parameters, such as count, volume, walking direction and velocity from laser scanned point clouds. Since no images are captured from the faces of pedestrians, no privacy issues raised. The paper includes accuracy analysis of the estimated parameters based on video footage as reference. Due to the dense point clouds, detailed geometry analysis has been conducted to obtain the height and shoulder width of pedestrians and to detect whether luggage has been carried or not. The derived parameters support safety (e.g. detecting critical pedestrian density in mass events), security (e.g. detecting prohibited baggage in endangered areas) and commercial applications (e.g. counting pedestrians at all entrances/exits of a shopping mall).

  9. The application of the detection filter to aircraft control surface and actuator failure detection and isolation

    Science.gov (United States)

    Bonnice, W. F.; Wagner, E.; Motyka, P.; Hall, S. R.

    1985-01-01

    The performance of the detection filter in detecting and isolating aircraft control surface and actuator failures is evaluated. The basic detection filter theory assumption of no direct input-output coupling is violated in this application due to the use of acceleration measurements for detecting and isolating failures. With this coupling, residuals produced by control surface failures may only be constrained to a known plane rather than to a single direction. A detection filter design with such planar failure signatures is presented, with the design issues briefly addressed. In addition, a modification to constrain the residual to a single known direction even with direct input-output coupling is also presented. Both the detection filter and the modification are tested using a nonlinear aircraft simulation. While no thresholds were selected, both filters demonstrated an ability to detect control surface and actuator failures. Failure isolation may be a problem if there are several control surfaces which produce similar effects on the aircraft. In addition, the detection filter was sensitive to wind turbulence and modeling errors.

  10. Real-time Detection of Antihydrogen Annihilations and Applications to Spectroscopy

    Directory of Open Access Journals (Sweden)

    Stracka Simone

    2014-04-01

    Full Text Available A detection scheme based on real-time measurement of antihydrogen annihilations during radiation injection is presented, which allows an efficient use of the trapped atoms for laser and microwave spectroscopy. The application of real-time detection of H¯$\\bar H$ annihilations to microwave spectroscopy, which yielded the first evidence of microwave induced spin-flip transitions in trapped antihydrogen [1], is reported.

  11. Application of catastrophe theory to a point model for bumpy torus with neoclassical non-resonant electrons

    Energy Technology Data Exchange (ETDEWEB)

    Punjabi, A; Vahala, G [College of William and Mary, Williamsburg, VA (USA). Dept. of Physics

    1983-12-01

    The point model for the toroidal core plasma in the ELMO Bumpy Torus (with neoclassical non-resonant electrons) is examined in the light of catastrophe theory. Even though the point model equations do not constitute a gradient dynamic system, the equilibrium surfaces are similar to those of the canonical cusp catastrophe. The point model is then extended to incorporate ion cyclotron resonance heating. A detailed parametric study of the equilibria is presented. Further, the nonlinear time evolution of these equilibria is studied, and it is observed that the point model obeys the delay convention (and hence hysteresis) and shows catastrophes at the fold edges of the equilibrium surfaces. Tentative applications are made to experimental results.

  12. A point cloud based pipeline for depth reconstruction from autostereoscopic sets

    Science.gov (United States)

    Niquin, Cédric; Prévost, Stéphanie; Remion, Yannick

    2010-02-01

    This is a three step pipeline to construct a 3D mesh of a scene from a set of N images, destined to be viewed on auto-stereoscopic displays. The first step matches the pixels to create a point cloud using a new algorithm based on graph-cuts. It exploits the data redundancy of the N images to ensure the geometric consistency of the scene and to reduce the graph complexity, in order to speed up the computation. It performs an accurate detection of occlusions and its results can then be used in applications like view synthesis. The second step slightly moves the points along the Z-axis to refine the point cloud. It uses a new cost including both occlusion positions and light variations deduced from the matching. The Z values are selected using a dynamic programming algorithm. This step finally generates a point cloud, which is fine enough for applications like augmented reality. From any of the two previously defined point clouds, the last step creates a colored mesh, which is a convenient data structure to be used in graphics APIs. It also generates N depth maps, allowing a comparison between the results of our method with those of other methods.

  13. Applicability of bacterial cellulose as an alternative to paper points in endodontic treatment.

    Science.gov (United States)

    Yoshino, Aya; Tabuchi, Mari; Uo, Motohiro; Tatsumi, Hiroto; Hideshima, Katsumi; Kondo, Seiji; Sekine, Joji

    2013-04-01

    Dental root canal treatment is required when dental caries progress to infection of the dental pulp. A major goal of this treatment is to provide complete decontamination of the dental root canal system. However, the morphology of dental root canal systems is complex, and many human dental roots have inaccessible areas. In addition, dental reinfection is fairly common. In conventional treatment, a cotton pellet and paper point made from plant cellulose is used to dry and sterilize the dental root canal. Such sterilization requires a treatment material with high absorbency to remove any residue, the ability to improve the efficacy of intracanal medication and high biocompatibility. Bacterial cellulose (BC) is produced by certain strains of bacteria. In this study, we developed BC in a pointed form and evaluated its applicability as a novel material for dental canal treatment with regard to solution absorption, expansion, tensile strength, drug release and biocompatibility. We found that BC has excellent material and biological characteristics compared with conventional materials, such as paper points (plant cellulose). BC showed noticeably higher absorption and expansion than paper points, and maintained a high tensile strength even when wet. The cumulative release of a model drug was significantly greater from BC than from paper points, and BC showed greater compatibility than paper points. Taken together, BC has great potential for use in dental root canal treatment. Copyright © 2012 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

  14. 3D Sensor-Based Obstacle Detection Comparing Octrees and Point clouds Using CUDA

    Directory of Open Access Journals (Sweden)

    K.B. Kaldestad

    2012-10-01

    Full Text Available This paper presents adaptable methods for achieving fast collision detection using the GPU and Nvidia CUDA together with Octrees. Earlier related work have focused on serial methods, while this paper presents a parallel solution which shows that there is a great increase in time if the number of operations is large. Two different models of the environment and the industrial robot are presented, the first is Octrees at different resolutions, the second is a point cloud representation. The relative merits of the two different world model representations are shown. In particular, the experimental results show the potential of adapting the resolution of the robot and environment models to the task at hand.

  15. Subtraction electrocardiography: Detection of ischemia-induced ST displacement without the need to identify the J point.

    Science.gov (United States)

    Ter Haar, C Cato; Man, Sum-Che; Maan, Arie C; Schalij, Martin J; Swenne, Cees A

    2016-01-01

    When triaging a patient with acute chest pain at first medical contact, an electrocardiogram (ECG) is routinely made and inspected for signs of myocardial ischemia. The guidelines recommend comparison of the acute and an earlier-made ECG, when available. No concrete recommendations for this comparison exist, neither is known how to handle J-point identification difficulties. Here we present a J-point independent method for such a comparison. After conversion to vectorcardiograms, baseline and acute ischemic ECGs after 3minutes of balloon occlusion during elective PCI were compared in 81 patients of the STAFF III ECG database. Baseline vectorcardiograms were subtracted from ischemic vectorcardiograms using either the QRS onsets or the J points as synchronization instants, yielding vector magnitude difference signals, ΔH. Output variables for the J-point synchronized differences were ΔH at the actual J point and at 20, 40, 60 and 80ms thereafter. Output variables for the onset-QRS synchronized differences were the ΔH at 80, 100, 120, 140 and 160ms after onset QRS. Finally, linear regressions of all combinations of ΔHJ+… versus ΔHQRS+… were made, and the best combination was identified. The highest correlation, 0.93 (pJ point and 160ms after the onset of the QRS complex. With a ΔH ischemia threshold of 0.05mV, 66/81 (J-point synchronized differences) and 68/81 (onset-QRS synchronized differences) subjects were above the ischemia threshold, corresponding to sensitivities of 81% and 84%, respectively. Our current study opens an alternative way to detect cardiac ischemia without the need for human expertise for determination of the J point by measuring the difference vector magnitude at 160ms after the onset of the QRS complex. Copyright © 2016 Elsevier Inc. All rights reserved.

  16. Toward General Software Level Silent Data Corruption Detection for Parallel Applications

    Energy Technology Data Exchange (ETDEWEB)

    Berrocal, Eduardo; Bautista-Gomez, Leonardo; Di, Sheng; Lan, Zhiling; Cappello, Franck

    2017-12-01

    Silent data corruption (SDC) poses a great challenge for high-performance computing (HPC) applications as we move to extreme-scale systems. Mechanisms have been proposed that are able to detect SDC in HPC applications by using the peculiarities of the data (more specifically, its “smoothness” in time and space) to make predictions. However, these data-analytic solutions are still far from fully protecting applications to a level comparable with more expensive solutions such as full replication. In this work, we propose partial replication to overcome this limitation. More specifically, we have observed that not all processes of an MPI application experience the same level of data variability at exactly the same time. Thus, we can smartly choose and replicate only those processes for which the lightweight data-analytic detectors would perform poorly. In addition, we propose a new evaluation method based on the probability that a corruption will pass unnoticed by a particular detector (instead of just reporting overall single-bit precision and recall). In our experiments, we use four applications dealing with different explosions. Our results indicate that our new approach can protect the MPI applications analyzed with 7–70% less overhead (depending on the application) than that of full duplication with similar detection recall.

  17. Automatic Cloud and Shadow Detection in Optical Satellite Imagery Without Using Thermal Bands—Application to Suomi NPP VIIRS Images over Fennoscandia

    Directory of Open Access Journals (Sweden)

    Eija Parmes

    2017-08-01

    Full Text Available In land monitoring applications, clouds and shadows are considered noise that should be removed as automatically and quickly as possible, before further analysis. This paper presents a method to detect clouds and shadows in Suomi NPP satellite’s VIIRS (Visible Infrared Imaging Radiometer Suite satellite images. The proposed cloud and shadow detection method has two distinct features when compared to many other methods. First, the method does not use the thermal bands and can thus be applied to other sensors which do not contain thermal channels, such as Sentinel-2 data. Secondly, the method uses the ratio between blue and green reflectance to detect shadows. Seven hundred and forty-seven VIIRS images over Fennoscandia from August 2014 to April 2016 were processed to train and develop the method. Twenty four points from every tenth of the images were used in accuracy assessment. These 1752 points were interpreted visually to cloud, cloud shadow and clear classes, then compared to the output of the cloud and shadow detection. The comparison on VIIRS images showed 94.2% correct detection rates and 11.1% false alarms for clouds, and respectively 36.1% and 82.7% for shadows. The results on cloud detection were similar to state-of-the-art methods. Shadows showed correctly on the northern edge of the clouds, but many shadows were wrongly assigned to other classes in some cases (e.g., to water class on lake and forest boundary, or with shadows over cloud. This may be due to the low spatial resolution of VIIRS images, where shadows are only a few pixels wide and contain lots of mixed pixels.

  18. End-point detection in potentiometric titration by continuous wavelet transform.

    Science.gov (United States)

    Jakubowska, Małgorzata; Baś, Bogusław; Kubiak, Władysław W

    2009-10-15

    The aim of this work was construction of the new wavelet function and verification that a continuous wavelet transform with a specially defined dedicated mother wavelet is a useful tool for precise detection of end-point in a potentiometric titration. The proposed algorithm does not require any initial information about the nature or the type of analyte and/or the shape of the titration curve. The signal imperfection, as well as random noise or spikes has no influence on the operation of the procedure. The optimization of the new algorithm was done using simulated curves and next experimental data were considered. In the case of well-shaped and noise-free titration data, the proposed method gives the same accuracy and precision as commonly used algorithms. But, in the case of noisy or badly shaped curves, the presented approach works good (relative error mainly below 2% and coefficients of variability below 5%) while traditional procedures fail. Therefore, the proposed algorithm may be useful in interpretation of the experimental data and also in automation of the typical titration analysis, specially in the case when random noise interfere with analytical signal.

  19. Thermodynamic framework to assess low abundance DNA mutation detection by hybridization

    Science.gov (United States)

    Willems, Hanny; Jacobs, An; Hadiwikarta, Wahyu Wijaya; Venken, Tom; Valkenborg, Dirk; Van Roy, Nadine; Vandesompele, Jo; Hooyberghs, Jef

    2017-01-01

    The knowledge of genomic DNA variations in patient samples has a high and increasing value for human diagnostics in its broadest sense. Although many methods and sensors to detect or quantify these variations are available or under development, the number of underlying physico-chemical detection principles is limited. One of these principles is the hybridization of sample target DNA versus nucleic acid probes. We introduce a novel thermodynamics approach and develop a framework to exploit the specific detection capabilities of nucleic acid hybridization, using generic principles applicable to any platform. As a case study, we detect point mutations in the KRAS oncogene on a microarray platform. For the given platform and hybridization conditions, we demonstrate the multiplex detection capability of hybridization and assess the detection limit using thermodynamic considerations; DNA containing point mutations in a background of wild type sequences can be identified down to at least 1% relative concentration. In order to show the clinical relevance, the detection capabilities are confirmed on challenging formalin-fixed paraffin-embedded clinical tumor samples. This enzyme-free detection framework contains the accuracy and efficiency to screen for hundreds of mutations in a single run with many potential applications in molecular diagnostics and the field of personalised medicine. PMID:28542229

  20. Anomalous transparency in photonic crystals and its application to point-by-point grating inscription in photonic crystal fibers.

    Science.gov (United States)

    Baghdasaryan, Tigran; Geernaert, Thomas; Chah, Karima; Caucheteur, Christophe; Schuster, Kay; Kobelke, Jens; Thienpont, Hugo; Berghmans, Francis

    2018-04-03

    It is common belief that photonic crystals behave similarly to isotropic and transparent media only when their feature sizes are much smaller than the wavelength of light. Here, we counter that belief and we report on photonic crystals that are transparent for anomalously high normalized frequencies up to 0.9, where the crystal's feature sizes are comparable with the free space wavelength. Using traditional photonic band theory, we demonstrate that the isofrequency curves can be circular in the region above the first stop band for triangular lattice photonic crystals. In addition, by simulating how efficiently a tightly focused Gaussian beam propagates through the photonic crystal slab, we judge on the photonic crystal's transparency rather than on isotropy only. Using this approach, we identified a wide range of photonic crystal parameters that provide anomalous transparency. Our findings indicate the possibility to scale up the features of photonic crystals and to extend their operational wavelength range for applications including optical cloaking and graded index guiding. We applied our result in the domain of femtosecond laser micromachining, by demonstrating what we believe to be the first point-by-point grating inscribed in a multi-ring photonic crystal fiber.

  1. Point-of-care diagnostics for niche applications.

    Science.gov (United States)

    Cummins, Brian M; Ligler, Frances S; Walker, Glenn M

    2016-01-01

    Point-of-care or point-of-use diagnostics are analytical devices that provide clinically relevant information without the need for a core clinical laboratory. In this review we define point-of-care diagnostics as portable versions of assays performed in a traditional clinical chemistry laboratory. This review discusses five areas relevant to human and animal health where increased attention could produce significant impact: veterinary medicine, space travel, sports medicine, emergency medicine, and operating room efficiency. For each of these areas, clinical need, available commercial products, and ongoing research into new devices are highlighted. Copyright © 2016 Elsevier Inc. All rights reserved.

  2. New methods to interpolate large volume of data from points or particles (Mesh-Free) methods application for its scientific visualization

    International Nuclear Information System (INIS)

    Reyes Lopez, Y.; Yervilla Herrera, H.; Viamontes Esquivel, A.; Recarey Morfa, C. A.

    2009-01-01

    In the following paper we developed a new method to interpolate large volumes of scattered data, focused mainly on the results of the Mesh free Methods, Points Methods and the Particles Methods application. Through this one, we use local radial basis function as interpolating functions. We also use over-tree as the data structure that allows to accelerate the localization of the data that influences to interpolate the values at a new point, speeding up the application of scientific visualization techniques to generate images from large data volumes from the application of Mesh-free Methods, Points and Particle Methods, in the resolution of diverse models of physics-mathematics. As an example, the results obtained after applying this method using the local interpolation functions of Shepard are shown. (Author) 22 refs

  3. Professional SharePoint 2013 development

    CERN Document Server

    Alirezaei, Reza; Ranlett, Matt; Hillier, Scot; Wilson, Brian; Fried, Jeff; Swider, Paul

    2013-01-01

    Thorough coverage of development in SharePoint 2013 A team of well-known Microsoft MVPs joins forces in this fully updated resource, providing you with in-depth coverage of development tools in the latest iteration of the immensely popular SharePoint. From building solutions to building custom workflow and content management applications, this book shares field-tested best practices on all aspect of SharePoint 2013 development. Offers a thorough look at Windows Azure and SharePoint 2013Includes new chapters on Application Life Cycle Management, developing apps in ShareP

  4. CVD diamond for nuclear detection applications

    International Nuclear Information System (INIS)

    Bergonzo, P.; Brambilla, A.; Tromson, D.; Mer, C.; Guizard, B.; Marshall, R.D.; Foulon, F.

    2002-01-01

    Chemically vapour deposited (CVD) diamond is a remarkable material for the fabrication of radiation detectors. In fact, there exist several applications where other standard semiconductor detectors do not fulfil the specific requirements imposed by corrosive, hot and/or high radiation dose environments. The improvement of the electronic properties of CVD diamond has been under intensive investigations and led to the development of a few applications that are addressing specific industrial needs. Here, we report on CVD diamond-based detector developments and we describe how this material, even though of a polycrystalline nature, is readily of great interest for applications in the nuclear industry as well as for physics experiments. Improvements in the material synthesis as well as on device fabrication especially concern the synthesis of films that do not exhibit space charge build up effects which are often encountered in CVD diamond materials and that are highly detrimental for detection devices. On a pre-industrial basis, CVD diamond detectors have been fabricated for nuclear industry applications in hostile environments. Such devices can operate in harsh environments and overcome limitations encountered with the standard semiconductor materials. Of these, this paper presents devices for the monitoring of the alpha activity in corrosive nuclear waste solutions, such as those encountered in nuclear fuel assembly reprocessing facilities, as well as diamond-based thermal neutron detectors exhibiting a high neutron to gamma selectivity. All these demonstrate the effectiveness of a demanding industrial need that relies on the remarkable resilience of CVD diamond

  5. Application of image processing technology in yarn hairiness detection

    Directory of Open Access Journals (Sweden)

    Guohong ZHANG

    2016-02-01

    Full Text Available Digital image processing technology is one of the new methods for yarn detection, which can realize the digital characterization and objective evaluation of yarn appearance. This paper overviews the current status of development and application of digital image processing technology used for yarn hairiness evaluation, and analyzes and compares the traditional detection methods and this new developed method. Compared with the traditional methods, the image processing technology based method is more objective, fast and accurate, which is the vital development trend of the yarn appearance evaluation.

  6. Some Fixed Point Results for Caristi Type Mappings in Modular Metric Spaces with an Application

    Directory of Open Access Journals (Sweden)

    Duran Turkoglu

    2016-08-01

    Full Text Available In this paper we give Caristi type fixed point theorem in complete modular metric spaces. Moreover we give a theorem which can be derived from Caristi type. Also an application for the bounded solution of funcional equations is investigated.

  7. Self-Similarity Based Corresponding-Point Extraction from Weakly Textured Stereo Pairs

    Directory of Open Access Journals (Sweden)

    Min Mao

    2014-01-01

    Full Text Available For the areas of low textured in image pairs, there is nearly no point that can be detected by traditional methods. The information in these areas will not be extracted by classical interest-point detectors. In this paper, a novel weakly textured point detection method is presented. The points with weakly textured characteristic are detected by the symmetry concept. The proposed approach considers the gray variability of the weakly textured local regions. The detection mechanism can be separated into three steps: region-similarity computation, candidate point searching, and refinement of weakly textured point set. The mechanism of radius scale selection and texture strength conception are used in the second step and the third step, respectively. The matching algorithm based on sparse representation (SRM is used for matching the detected points in different images. The results obtained on image sets with different objects show high robustness of the method to background and intraclass variations as well as to different photometric and geometric transformations; the points detected by this method are also the complement of points detected by classical detectors from the literature. And we also verify the efficacy of SRM by comparing with classical algorithms under the occlusion and corruption situations for matching the weakly textured points. Experiments demonstrate the effectiveness of the proposed weakly textured point detection algorithm.

  8. 25 CFR 1000.70 - What criteria will the Director use to rank the applications and how many maximum points can be...

    Science.gov (United States)

    2010-04-01

    ... 25 Indians 2 2010-04-01 2010-04-01 false What criteria will the Director use to rank the applications and how many maximum points can be awarded for each criterion? 1000.70 Section 1000.70 Indians... Process § 1000.70 What criteria will the Director use to rank the applications and how many maximum points...

  9. FPGA-Based Flexible Hardware Architecture for Image Interest Point Detection

    Directory of Open Access Journals (Sweden)

    Ana Hernandez-Lopez

    2015-07-01

    Full Text Available An important challenge in computer vision is the implementation of fast and accurate feature detectors, as they are the basis for high-level image processing analysis and understanding. However, image feature detectors cannot be easily applied in embedded scenarios, mainly due to the fact that they are time consuming and require a significant amount of processing power. Although some feature detectors have been implemented in hardware, most implementations target a single detector under very specific constraints. This paper proposes a flexible hardware implementation approach for computing interest point extraction from grey-level images based on two different detectors, Harris and SUSAN, suitable for robotic applications. The design is based on parallel and configurable processing elements for window operators and a buffering strategy to support a coarse-grain pipeline scheme for operator sequencing. When targeted to a Virtex-6 FPGA, a throughput of 49.45 Mpixel/s (processing rate of 161 frames per second of VGA image resolution is achieved at a clock frequency of 50 MHz.

  10. Application of image editing software for forensic detection of image ...

    African Journals Online (AJOL)

    Application of image editing software for forensic detection of image. ... The image editing software's available today is apt for creating visually compelling and sophisticated fake images, ... EMAIL FREE FULL TEXT EMAIL FREE FULL TEXT

  11. Automatic Registration of Vehicle-borne Mobile Mapping Laser Point Cloud and Sequent Panoramas

    Directory of Open Access Journals (Sweden)

    CHEN Chi

    2018-02-01

    Full Text Available An automatic registration method of mobile mapping system laser point cloud and sequence panoramic image is proposed in this paper.Firstly,hierarchical object extraction method is applied on LiDAR data to extract the building façade and outline polygons are generated to construct the skyline vectors.A virtual imaging method is proposed to solve the distortion on panoramas and corners on skylines are further detected on the virtual images combining segmentation and corner detection results.Secondly,the detected skyline vectors are taken as the registration primitives.Registration graphs are built according to the extracted skyline vector and further matched under graph edit distance minimization criteria.The matched conjugate primitives are utilized to solve the 2D-3D rough registration model to obtain the initial transformation between the sequence panoramic image coordinate system and the LiDAR point cloud coordinate system.Finally,to reduce the impact of registration primitives extraction and matching error on the registration results,the optimal transformation between the multi view stereo matching dens point cloud generated from the virtual imaging of the sequent panoramas and the LiDAR point cloud are solved by a 3D-3D ICP registration algorithm variant,thus,refine the exterior orientation parameters of panoramas indirectly.Experiments are undertaken to validate the proposed method and the results show that 1.5 pixel level registration results are achieved on the experiment dataset.The registration results can be applied to point cloud and panoramas fusion applications such as true color point cloud generation.

  12. A Data Filter for Identifying Steady-State Operating Points in Engine Flight Data for Condition Monitoring Applications

    Science.gov (United States)

    Simon, Donald L.; Litt, Jonathan S.

    2010-01-01

    This paper presents an algorithm that automatically identifies and extracts steady-state engine operating points from engine flight data. It calculates the mean and standard deviation of select parameters contained in the incoming flight data stream. If the standard deviation of the data falls below defined constraints, the engine is assumed to be at a steady-state operating point, and the mean measurement data at that point are archived for subsequent condition monitoring purposes. The fundamental design of the steady-state data filter is completely generic and applicable for any dynamic system. Additional domain-specific logic constraints are applied to reduce data outliers and variance within the collected steady-state data. The filter is designed for on-line real-time processing of streaming data as opposed to post-processing of the data in batch mode. Results of applying the steady-state data filter to recorded helicopter engine flight data are shown, demonstrating its utility for engine condition monitoring applications.

  13. An OMIC biomarker detection algorithm TriVote and its application in methylomic biomarker detection.

    Science.gov (United States)

    Xu, Cheng; Liu, Jiamei; Yang, Weifeng; Shu, Yayun; Wei, Zhipeng; Zheng, Weiwei; Feng, Xin; Zhou, Fengfeng

    2018-04-01

    Transcriptomic and methylomic patterns represent two major OMIC data sources impacted by both inheritable genetic information and environmental factors, and have been widely used as disease diagnosis and prognosis biomarkers. Modern transcriptomic and methylomic profiling technologies detect the status of tens of thousands or even millions of probing residues in the human genome, and introduce a major computational challenge for the existing feature selection algorithms. This study proposes a three-step feature selection algorithm, TriVote, to detect a subset of transcriptomic or methylomic residues with highly accurate binary classification performance. TriVote outperforms both filter and wrapper feature selection algorithms with both higher classification accuracy and smaller feature number on 17 transcriptomes and two methylomes. Biological functions of the methylome biomarkers detected by TriVote were discussed for their disease associations. An easy-to-use Python package is also released to facilitate the further applications.

  14. HIERARCHICAL REGULARIZATION OF POLYGONS FOR PHOTOGRAMMETRIC POINT CLOUDS OF OBLIQUE IMAGES

    Directory of Open Access Journals (Sweden)

    L. Xie

    2017-05-01

    Full Text Available Despite the success of multi-view stereo (MVS reconstruction from massive oblique images in city scale, only point clouds and triangulated meshes are available from existing MVS pipelines, which are topologically defect laden, free of semantical information and hard to edit and manipulate interactively in further applications. On the other hand, 2D polygons and polygonal models are still the industrial standard. However, extraction of the 2D polygons from MVS point clouds is still a non-trivial task, given the fact that the boundaries of the detected planes are zigzagged and regularities, such as parallel and orthogonal, cannot preserve. Aiming to solve these issues, this paper proposes a hierarchical polygon regularization method for the photogrammetric point clouds from existing MVS pipelines, which comprises of local and global levels. After boundary points extraction, e.g. using alpha shapes, the local level is used to consolidate the original points, by refining the orientation and position of the points using linear priors. The points are then grouped into local segments by forward searching. In the global level, regularities are enforced through a labeling process, which encourage the segments share the same label and the same label represents segments are parallel or orthogonal. This is formulated as Markov Random Field and solved efficiently. Preliminary results are made with point clouds from aerial oblique images and compared with two classical regularization methods, which have revealed that the proposed method are more powerful in abstracting a single building and is promising for further 3D polygonal model reconstruction and GIS applications.

  15. Detection-Guided Fast Affine Projection Channel Estimator for Speech Applications

    Directory of Open Access Journals (Sweden)

    Yan Wu Jennifer

    2007-04-01

    Full Text Available In various adaptive estimation applications, such as acoustic echo cancellation within teleconferencing systems, the input signal is a highly correlated speech. This, in general, leads to extremely slow convergence of the NLMS adaptive FIR estimator. As a result, for such applications, the affine projection algorithm (APA or the low-complexity version, the fast affine projection (FAP algorithm, is commonly employed instead of the NLMS algorithm. In such applications, the signal propagation channel may have a relatively low-dimensional impulse response structure, that is, the number m of active or significant taps within the (discrete-time modelled channel impulse response is much less than the overall tap length n of the channel impulse response. For such cases, we investigate the inclusion of an active-parameter detection-guided concept within the fast affine projection FIR channel estimator. Simulation results indicate that the proposed detection-guided fast affine projection channel estimator has improved convergence speed and has lead to better steady-state performance than the standard fast affine projection channel estimator, especially in the important case of highly correlated speech input signals.

  16. Detection of image structures using the Fisher information and the Rao metric.

    Science.gov (United States)

    Maybank, Stephen J

    2004-12-01

    In many detection problems, the structures to be detected are parameterized by the points of a parameter space. If the conditional probability density function for the measurements is known, then detection can be achieved by sampling the parameter space at a finite number of points and checking each point to see if the corresponding structure is supported by the data. The number of samples and the distances between neighboring samples are calculated using the Rao metric on the parameter space. The Rao metric is obtained from the Fisher information which is, in turn, obtained from the conditional probability density function. An upper bound is obtained for the probability of a false detection. The calculations are simplified in the low noise case by making an asymptotic approximation to the Fisher information. An application to line detection is described. Expressions are obtained for the asymptotic approximation to the Fisher information, the volume of the parameter space, and the number of samples. The time complexity for line detection is estimated. An experimental comparison is made with a Hough transform-based method for detecting lines.

  17. Contour-Based Corner Detection and Classification by Using Mean Projection Transform

    Directory of Open Access Journals (Sweden)

    Seyed Mostafa Mousavi Kahaki

    2014-02-01

    Full Text Available Image corner detection is a fundamental task in computer vision. Many applications require reliable detectors to accurately detect corner points, commonly achieved by using image contour information. The curvature definition is sensitive to local variation and edge aliasing, and available smoothing methods are not sufficient to address these problems properly. Hence, we propose Mean Projection Transform (MPT as a corner classifier and parabolic fit approximation to form a robust detector. The first step is to extract corner candidates using MPT based on the integral properties of the local contours in both the horizontal and vertical directions. Then, an approximation of the parabolic fit is calculated to localize the candidate corner points. The proposed method presents fewer false-positive (FP and false-negative (FN points compared with recent standard corner detection techniques, especially in comparison with curvature scale space (CSS methods. Moreover, a new evaluation metric, called accuracy of repeatability (AR, is introduced. AR combines repeatability and the localization error (Le for finding the probability of correct detection in the target image. The output results exhibit better repeatability, localization, and AR for the detected points compared with the criteria in original and transformed images.

  18. Probabilistic pipe fracture evaluations for leak-rate-detection applications

    International Nuclear Information System (INIS)

    Rahman, S.; Ghadiali, N.; Paul, D.; Wilkowski, G.

    1995-04-01

    Regulatory Guide 1.45, open-quotes Reactor Coolant Pressure Boundary Leakage Detection Systems,close quotes was published by the U.S. Nuclear Regulatory Commission (NRC) in May 1973, and provides guidance on leak detection methods and system requirements for Light Water Reactors. Additionally, leak detection limits are specified in plant Technical Specifications and are different for Boiling Water Reactors (BWRs) and Pressurized Water Reactors (PWRs). These leak detection limits are also used in leak-before-break evaluations performed in accordance with Draft Standard Review Plan, Section 3.6.3, open-quotes Leak Before Break Evaluation Proceduresclose quotes where a margin of 10 on the leak detection limit is used in determining the crack size considered in subsequent fracture analyses. This study was requested by the NRC to: (1) evaluate the conditional failure probability for BWR and PWR piping for pipes that were leaking at the allowable leak detection limit, and (2) evaluate the margin of 10 to determine if it was unnecessarily large. A probabilistic approach was undertaken to conduct fracture evaluations of circumferentially cracked pipes for leak-rate-detection applications. Sixteen nuclear piping systems in BWR and PWR plants were analyzed to evaluate conditional failure probability and effects of crack-morphology variability on the current margins used in leak rate detection for leak-before-break

  19. Simultaneous point-of-care detection of anemia and sickle cell disease in Tanzania: the RAPID study.

    Science.gov (United States)

    Smart, Luke R; Ambrose, Emmanuela E; Raphael, Kevin C; Hokororo, Adolfine; Kamugisha, Erasmus; Tyburski, Erika A; Lam, Wilbur A; Ware, Russell E; McGann, Patrick T

    2018-02-01

    Both anemia and sickle cell disease (SCD) are highly prevalent across sub-Saharan Africa, and limited resources exist to diagnose these conditions quickly and accurately. The development of simple, inexpensive, and accurate point-of-care (POC) assays represents an important advance for global hematology, one that could facilitate timely and life-saving medical interventions. In this prospective study, Robust Assays for Point-of-care Identification of Disease (RAPID), we simultaneously evaluated a POC immunoassay (Sickle SCAN™) to diagnose SCD and a first-generation POC color-based assay to detect anemia. Performed at Bugando Medical Center in Mwanza, Tanzania, RAPID tested 752 participants (age 1 day to 20 years) in four busy clinical locations. With minimally trained medical staff, the SCD POC assay diagnosed SCD with 98.1% sensitivity and 91.1% specificity. The hemoglobin POC assay had 83.2% sensitivity and 74.5% specificity for detection of severe anemia (Hb ≤ 7 g/dL). Interobserver agreement was excellent for both POC assays (r = 0.95-0.96). Results for the hemoglobin POC assay have informed the second-generation assay design to be more suitable for low-resource settings. RAPID provides practical feasibility data regarding two novel POC assays for the diagnosis of anemia and SCD in real-world field evaluations and documents the utility and potential impact of these POC assays for sub-Saharan Africa.

  20. Radiation Detection for Homeland Security Applications

    Science.gov (United States)

    Ely, James

    2008-05-01

    In the past twenty years or so, there have been significant changes in the strategy and applications for homeland security. Recently there have been significant at deterring and interdicting terrorists and associated organizations. This is a shift in the normal paradigm of deterrence and surveillance of a nation and the `conventional' methods of warfare to the `unconventional' means that terrorist organizations resort to. With that shift comes the responsibility to monitor international borders for weapons of mass destruction, including radiological weapons. As a result, countries around the world are deploying radiation detection instrumentation to interdict the illegal shipment of radioactive material crossing international borders. These efforts include deployments at land, rail, air, and sea ports of entry in the US and in European and Asian countries. Radioactive signatures of concern include radiation dispersal devices (RDD), nuclear warheads, and special nuclear material (SNM). Radiation portal monitors (RPMs) are used as the main screening tool for vehicles and cargo at borders, supplemented by handheld detectors, personal radiation detectors, and x-ray imaging systems. This talk will present an overview of radiation detection equipment with emphasis on radiation portal monitors. In the US, the deployment of radiation detection equipment is being coordinated by the Domestic Nuclear Detection Office within the Department of Homeland Security, and a brief summary of the program will be covered. Challenges with current generation systems will be discussed as well as areas of investigation and opportunities for improvements. The next generation of radiation portal monitors is being produced under the Advanced Spectroscopic Portal program and will be available for deployment in the near future. Additional technologies, from commercially available to experimental, that provide additional information for radiation screening, such as density imaging equipment, will

  1. FDM and DMT performance comparison in high capacity point-to-point fibre links for intra/inter-datacentre connections

    Science.gov (United States)

    Gatto, A.; Parolari, P.; Boffi, P.

    2018-05-01

    Frequency division multiplexing (FDM) is attractive to achieve high capacities in multiple access networks characterized by direct modulation and direct detection. In this paper we take into account point-to-point intra- and inter-datacenter connections to understand the performance of FDM operation compared with the ones achievable with standard multiple carrier modulation approach based on discrete multitone (DMT). DMT and FDM allow to match the non-uniform and bandwidth-limited response of the system under test, associated with the employment of low-cost directly-modulated sources, such as VCSELs with high-frequency chirp, and with fibre-propagation in presence of chromatic dispersion. While for very short distances typical of intra-datacentre communications, the huge number of DMT subcarriers permits to increase the transported capacity with respect to the FDM employment, in case of few tens-km reaches typical of inter-datacentre connections, the capabilities of FDM are more evident, providing system performance similar to the case of DMT application.

  2. Using temporal orientation, category fluency, and word recall for detecting cognitive impairment: the 10-point cognitive screener (10-CS).

    Science.gov (United States)

    Apolinario, Daniel; Lichtenthaler, Daniel Gomes; Magaldi, Regina Miksian; Soares, Aline Thomaz; Busse, Alexandre Leopold; Amaral, Jose Renato das Gracas; Jacob-Filho, Wilson; Brucki, Sonia Maria Dozzi

    2016-01-01

    A screening strategy composed of three-item temporal orientation and three-word recall has been increasingly used for detecting cognitive impairment. However, the intervening task administered between presentation and recall has varied. We evaluated six brief tasks that could be useful as intervening distractors and possibly provide incremental accuracy: serial subtraction, clock drawing, category fluency, letter fluency, timed visual detection, and digits backwards. Older adults (n = 230) consecutively referred for suspected cognitive impairment underwent a comprehensive assessment for gold-standard diagnosis, of whom 56 (24%) presented cognitive impairment not dementia and 68 (30%) presented dementia. Among those with dementia, 87% presented very mild or mild stages (Clinical Dementia Rating 0.5 or 1). The incremental value of each candidate intervening task in a model already containing orientation and word recall was assessed. Category fluency (animal naming) presented the highest incremental value among the six candidate intervening tasks. Reclassification analyses revealed a net gain of 12% among cognitively impaired and 17% among normal participants. A four-point scaled score of the animal naming task was added to three-item temporal orientation and three-word recall to compose the 10-point Cognitive Screener. The education-adjusted 10-point Cognitive Screener outperformed the longer Mini-Mental State Examination for detecting both cognitive impairment (area under the curve 0.85 vs 0.77; p = 0.027) and dementia (area under the curve 0.90 vs 0.83; p = 0.015). Based on empirical data, we have developed a brief and easy-to-use screening strategy with higher accuracy and some practical advantages compared with commonly used tools. Copyright © 2015 John Wiley & Sons, Ltd.

  3. A ROBUST REGISTRATION ALGORITHM FOR POINT CLOUDS FROM UAV IMAGES FOR CHANGE DETECTION

    Directory of Open Access Journals (Sweden)

    A. Al-Rawabdeh

    2016-06-01

    Full Text Available Landslides are among the major threats to urban landscape and manmade infrastructure. They often cause economic losses, property damages, and loss of lives. Temporal monitoring data of landslides from different epochs empowers the evaluation of landslide progression. Alignment of overlapping surfaces from two or more epochs is crucial for the proper analysis of landslide dynamics. The traditional methods for point-cloud-based landslide monitoring rely on using a variation of the Iterative Closest Point (ICP registration procedure to align any reconstructed surfaces from different epochs to a common reference frame. However, sometimes the ICP-based registration can fail or may not provide sufficient accuracy. For example, point clouds from different epochs might fit to local minima due to lack of geometrical variability within the data. Also, manual interaction is required to exclude any non-stable areas from the registration process. In this paper, a robust image-based registration method is introduced for the simultaneous evaluation of all registration parameters. This includes the Interior Orientation Parameters (IOPs of the camera and the Exterior Orientation Parameters (EOPs of the involved images from all available observation epochs via a bundle block adjustment with self-calibration. Next, a semi-global dense matching technique is implemented to generate dense 3D point clouds for each epoch using the images captured in a particular epoch separately. The normal distances between any two consecutive point clouds can then be readily computed, because the point clouds are already effectively co-registered. A low-cost DJI Phantom II Unmanned Aerial Vehicle (UAV was customised and used in this research for temporal data collection over an active soil creep area in Lethbridge, Alberta, Canada. The customisation included adding a GPS logger and a Large-Field-Of-View (LFOV action camera which facilitated capturing high-resolution geo-tagged images

  4. a Robust Registration Algorithm for Point Clouds from Uav Images for Change Detection

    Science.gov (United States)

    Al-Rawabdeh, A.; Al-Gurrani, H.; Al-Durgham, K.; Detchev, I.; He, F.; El-Sheimy, N.; Habib, A.

    2016-06-01

    Landslides are among the major threats to urban landscape and manmade infrastructure. They often cause economic losses, property damages, and loss of lives. Temporal monitoring data of landslides from different epochs empowers the evaluation of landslide progression. Alignment of overlapping surfaces from two or more epochs is crucial for the proper analysis of landslide dynamics. The traditional methods for point-cloud-based landslide monitoring rely on using a variation of the Iterative Closest Point (ICP) registration procedure to align any reconstructed surfaces from different epochs to a common reference frame. However, sometimes the ICP-based registration can fail or may not provide sufficient accuracy. For example, point clouds from different epochs might fit to local minima due to lack of geometrical variability within the data. Also, manual interaction is required to exclude any non-stable areas from the registration process. In this paper, a robust image-based registration method is introduced for the simultaneous evaluation of all registration parameters. This includes the Interior Orientation Parameters (IOPs) of the camera and the Exterior Orientation Parameters (EOPs) of the involved images from all available observation epochs via a bundle block adjustment with self-calibration. Next, a semi-global dense matching technique is implemented to generate dense 3D point clouds for each epoch using the images captured in a particular epoch separately. The normal distances between any two consecutive point clouds can then be readily computed, because the point clouds are already effectively co-registered. A low-cost DJI Phantom II Unmanned Aerial Vehicle (UAV) was customised and used in this research for temporal data collection over an active soil creep area in Lethbridge, Alberta, Canada. The customisation included adding a GPS logger and a Large-Field-Of-View (LFOV) action camera which facilitated capturing high-resolution geo-tagged images in two epochs

  5. PEDESTRIAN DETECTION BY LASER SCANNING AND DEPTH IMAGERY

    Directory of Open Access Journals (Sweden)

    A. Barsi

    2016-06-01

    Full Text Available Pedestrian flow is much less regulated and controlled compared to vehicle traffic. Estimating flow parameters would support many safety, security or commercial applications. Current paper discusses a method that enables acquiring information on pedestrian movements without disturbing and changing their motion. Profile laser scanner and depth camera have been applied to capture the geometry of the moving people as time series. Procedures have been developed to derive complex flow parameters, such as count, volume, walking direction and velocity from laser scanned point clouds. Since no images are captured from the faces of pedestrians, no privacy issues raised. The paper includes accuracy analysis of the estimated parameters based on video footage as reference. Due to the dense point clouds, detailed geometry analysis has been conducted to obtain the height and shoulder width of pedestrians and to detect whether luggage has been carried or not. The derived parameters support safety (e.g. detecting critical pedestrian density in mass events, security (e.g. detecting prohibited baggage in endangered areas and commercial applications (e.g. counting pedestrians at all entrances/exits of a shopping mall.

  6. Event Detection Challenges, Methods, and Applications in Natural and Artificial Systems

    Science.gov (United States)

    2009-03-01

    Sauvageon, Agogino, Mehr, and Tumer [2006], for instance, use a fourth degree polynomial within an event detection algorithm to sense high... cancer , and coronary artery disease. His study examines the age at which to begin screening exams, the intervals between the exams, and (possibly...AM, Mehr AF, and Tumer IY. 2006. “Comparison of Event Detection Methods for Centralized Sensor Networks.” IEEE Sensors Applications Symposium 2006

  7. Spherical Projection Based Straight Line Segment Extraction for Single Station Terrestrial Laser Point Cloud

    Directory of Open Access Journals (Sweden)

    ZHANG Fan

    2015-06-01

    Full Text Available Due to the discrete distribution computing errors and lack of adaptability are ubiquitous in the current straight line extraction for TLS data methods. A 3D straight line segment extraction method is proposed based on spherical projection for single station terrestrial laser point clouds. Firstly, horizontal and vertical angles of each laser point are calculated by means of spherical coordinates, intensity panoramic image according to the two angles is generated. Secondly, edges which include straight line features are detected from intensity panoramic image by using of edge detection algorithm. Thirdly, great circles are detected from edges of panoramic image using spherical Hough transform. According to the axiom that a straight line segment in 3D space is a spherical great circle after spherical projection, detecting great circles from spherical projected data sets is essentially detecting straight line segments from 3D data sets without spherical projection. Finally, a robust 3D straight line fitting method is employed to fitting the straight lines and calculating parameters of the straight line segments. Experiments using different data sets and comparison with other methods show the accuracy and applicability of the proposed method.

  8. Exact analytical solution of time-independent neutron transport equation, and its applications to systems with a point source

    International Nuclear Information System (INIS)

    Mikata, Y.

    2014-01-01

    Highlights: • An exact solution for the one-speed neutron transport equation is obtained. • This solution as well as its derivation are believed to be new. • Neutron flux for a purely absorbing material with a point neutron source off the origin is obtained. • Spherically as well as cylindrically piecewise constant cross sections are studied. • Neutron flux expressions for a point neutron source off the origin are believed to be new. - Abstract: An exact analytical solution of the time-independent monoenergetic neutron transport equation is obtained in this paper. The solution is applied to systems with a point source. Systematic analysis of the solution of the time-independent neutron transport equation, and its applications represent the primary goal of this paper. To the best of the author’s knowledge, certain key results on the scalar neutron flux as well as their derivations are new. As an application of these results, a scalar neutron flux for a purely absorbing medium with a spherically piecewise constant cross section and an isotropic point neutron source off the origin as well as that for a cylindrically piecewise constant cross section with a point neutron source off the origin are obtained. Both of these results are believed to be new

  9. Nonlinear Dynamics, Fixed Points and Coupled Fixed Points in Generalized Gauge Spaces with Applications to a System of Integral Equations

    Directory of Open Access Journals (Sweden)

    Adrian Petruşel

    2015-01-01

    Full Text Available We will discuss discrete dynamics generated by single-valued and multivalued operators in spaces endowed with a generalized metric structure. More precisely, the behavior of the sequence (fn(xn∈N of successive approximations in complete generalized gauge spaces is discussed. In the same setting, the case of multivalued operators is also considered. The coupled fixed points for mappings t1:X1×X2→X1 and t2:X1×X2→X2 are discussed and an application to a system of nonlinear integral equations is given.

  10. Detecting outliers and/or leverage points: a robust two-stage procedure with bootstrap cut-off points

    Directory of Open Access Journals (Sweden)

    Ettore Marubini

    2014-01-01

    Full Text Available This paper presents a robust two-stage procedure for identification of outlying observations in regression analysis. The exploratory stage identifies leverage points and vertical outliers through a robust distance estimator based on Minimum Covariance Determinant (MCD. After deletion of these points, the confirmatory stage carries out an Ordinary Least Squares (OLS analysis on the remaining subset of data and investigates the effect of adding back in the previously deleted observations. Cut-off points pertinent to different diagnostics are generated by bootstrapping and the cases are definitely labelled as good-leverage, bad-leverage, vertical outliers and typical cases. The procedure is applied to four examples.

  11. Building Contour Extraction Based on LiDAR Point Cloud

    Directory of Open Access Journals (Sweden)

    Zhang Xu-Qing

    2017-01-01

    Full Text Available This paper presents a new method for solving the problem of utilizing the LiDAR data to extract the building contour line. For detection of the edge points between the building test points by using the least squares fitting to get the edge line of buildings and give the weight determining of the building of edge line slope depend on the length of the edge line. And then get the weighted mean of the positive and negative slope of the building edge line. Based on the structure of the adjacent edge perpendicular hypothesis, regularization processing to extract the edge of the skeleton line perpendicular. The experiments show that the extracted building edges have the good accuracy and have the good applicability in complex urban areas.

  12. APPLICATION OF MALARIA DETECTION OF DRAWING BLOOD CELLS USING MICROSCOPIC OpenCV

    Directory of Open Access Journals (Sweden)

    Antonius Herusutopo

    2011-10-01

    Full Text Available The goal of the research is to produce an application, which can detect malaria on patient through microscopic digital image of blood sample. The research methods are data collection, design analysis, testing and evaluation. The used application methods are image pre-processing, morphology and image segmentation using OpenCV. The expected result is a creation of application, which can be able to detect malaria on a microscopic digital image of patient blood sample. The conclusion is that the application can detect malaria from young trophozoites stadium and gametesocytes from the picture.Keywords: Detection; Malaria; Computer Vision; OpenCVINTRODUCTIONSystem technology of computer-based with artificial intelligence already can be used in medicine field, for example, to resolve the problems: detecting specific disease and its symptoms, analyzing the content of a sample, monitoring the condition of an organ, and others. Nevertheless, the medical field is very wide, so for detecting diseases problems, not yet much disease that detection can be done with a computer-based system. One example of the issues is well-known disease detection, which is malaria. Malaria is classified as a serious disease because it can cause death if it is not treated properly. Malaria has various types and can affect anyone anywhere. The symptoms of malaria is really common as it may appear in daily life, but cannot always indicate that a person infected with malaria. Indications, which can show that a person infected with malaria, are the clinical examination and blood tests.With the blood test, the treatment of malaria can be implemented correctly and precisely. It needs technology that can detect malaria correctly and precisely. The solution is the method of support vector machine that can detect malaria in humans by viewing image of appearance blood cells.METHODThe methods used in this research are data collection, analysis and design. The data collection includes

  13. Current state of commercial radiation detection equipment for homeland security applications

    International Nuclear Information System (INIS)

    Klann, R.T.; Shergur, J.; Mattesich, G.

    2009-01-01

    With the creation of the U.S. Department of Homeland Security (DHS) came the increased concern that terrorist groups would attempt to manufacture and use an improvised nuclear device or radiological dispersal device. As such, a primary mission of DHS is to protect the public against the use of these devices and to assist state and local responders in finding, locating, and identifying these types of devices and materials used to manufacture these devices. This assistance from DHS to state and local responders comes in the form of grant money to procure radiation detection equipment. In addition to this grant program, DHS has supported the development of American National Standards Institute standards for radiation detection equipment and has conducted testing of commercially available instruments. This paper identifies the types and kinds of commercially available equipment that can be used to detect and identify radiological material - for use in traditional search applications as well as primary and secondary screening of personnel, vehicles, and cargo containers. In doing so, key considerations for the conduct of operations are described as well as critical features of the instruments for specific applications. The current state of commercial instruments is described for different categories of detection equipment including personal radiation detectors, radioisotope identifiers, man-portable detection equipment, and radiation portal monitors. In addition, emerging technologies are also discussed, such as spectroscopic detectors and advanced spectroscopic portal monitors

  14. Sensorless speed detection of squirrel-cage induction machines using stator neutral point voltage harmonics

    Science.gov (United States)

    Petrovic, Goran; Kilic, Tomislav; Terzic, Bozo

    2009-04-01

    In this paper a sensorless speed detection method of induction squirrel-cage machines is presented. This method is based on frequency determination of the stator neutral point voltage primary slot harmonic, which is dependent on rotor speed. In order to prove method in steady state and dynamic conditions the simulation and experimental study was carried out. For theoretical investigation the mathematical model of squirrel cage induction machines, which takes into consideration actual geometry and windings layout, is used. Speed-related harmonics that arise from rotor slotting are analyzed using digital signal processing and DFT algorithm with Hanning window. The performance of the method is demonstrated over a wide range of load conditions.

  15. Nutrient Losses from Non-Point Sources or from Unidentified Point Sources? Application Examples of the Smartphone Based Nitrate App.

    Science.gov (United States)

    Rozemeijer, J.; Ekkelenkamp, R.; van der Zaan, B.

    2017-12-01

    In 2016 Deltares launched the free to use Nitrate App which accurately reads and interprets nitrate test strips. The app directly displays the measured concentration and gives the option to share the result. Shared results are visualised in map functionality within the app and online. Since its introduction we've been seeing an increasing number of nitrate app applications. In this presentation we show some unanticipated types of application. The Nitrate App was originally intended to enable farmers to measure nitrate concentrations on their own farms. This may encourage farmers to talk to specialists about the right nutrient best management practices (BMP's) for their farm. Several groups of farmers have recently started to apply the Nitrate App and to discuss their results with each other and with the authorities. Nitrate concentration routings in catchments have proven to be another useful application. Within a day a person can generate a catchment scale nitrate concentration map identifying nitrate loss hotspots. In several routings in agricultural catchments clear point sources were found, for example at small scale manure processing plants. These routings proved that the Nitrate App can help water managers to target conservation practices more accurately to areas with the highest nitrate concentrations and loads. Other current applications are the screening of domestic water wells in California, the collection of extra measurements (also pH and NH4) in the National Monitoring Network for the Evaluation of the Manure Policy in the Netherlands, and several educational initiatives in cooperation with schools and universities.

  16. Generating Impact Maps from Automatically Detected Bomb Craters in Aerial Wartime Images Using Marked Point Processes

    Science.gov (United States)

    Kruse, Christian; Rottensteiner, Franz; Hoberg, Thorsten; Ziems, Marcel; Rebke, Julia; Heipke, Christian

    2018-04-01

    The aftermath of wartime attacks is often felt long after the war ended, as numerous unexploded bombs may still exist in the ground. Typically, such areas are documented in so-called impact maps which are based on the detection of bomb craters. This paper proposes a method for the automatic detection of bomb craters in aerial wartime images that were taken during the Second World War. The object model for the bomb craters is represented by ellipses. A probabilistic approach based on marked point processes determines the most likely configuration of objects within the scene. Adding and removing new objects to and from the current configuration, respectively, changing their positions and modifying the ellipse parameters randomly creates new object configurations. Each configuration is evaluated using an energy function. High gradient magnitudes along the border of the ellipse are favored and overlapping ellipses are penalized. Reversible Jump Markov Chain Monte Carlo sampling in combination with simulated annealing provides the global energy optimum, which describes the conformance with a predefined model. For generating the impact map a probability map is defined which is created from the automatic detections via kernel density estimation. By setting a threshold, areas around the detections are classified as contaminated or uncontaminated sites, respectively. Our results show the general potential of the method for the automatic detection of bomb craters and its automated generation of an impact map in a heterogeneous image stock.

  17. On-line safeguards design: an application of estimation/detection

    International Nuclear Information System (INIS)

    Candy, J.V.; Dunn, D.R.; Rozsa, R.B.

    1979-01-01

    The applicability of madern signal processing techniques to the safeguards problem for a plutonium nitrate storage tank and concentrator is addressed. The techniques involve mathematical modeling, optimal estimation of process variables, and the detection of abnormal changes in these variables due to adversary diversion. The performance of these techniques is preesented for various diversion scenarios

  18. SU-E-T-310: Targeting Safety Improvements Through Analysis of Near-Miss Error Detection Points in An Incident Learning Database

    International Nuclear Information System (INIS)

    Novak, A; Nyflot, M; Sponseller, P; Howard, J; Logan, W; Holland, L; Jordan, L; Carlson, J; Ermoian, R; Kane, G; Ford, E; Zeng, J

    2014-01-01

    Purpose: Radiation treatment planning involves a complex workflow that can make safety improvement efforts challenging. This study utilizes an incident reporting system to identify detection points of near-miss errors, in order to guide our departmental safety improvement efforts. Previous studies have examined where errors arise, but not where they are detected or their patterns. Methods: 1377 incidents were analyzed from a departmental nearmiss error reporting system from 3/2012–10/2013. All incidents were prospectively reviewed weekly by a multi-disciplinary team, and assigned a near-miss severity score ranging from 0–4 reflecting potential harm (no harm to critical). A 98-step consensus workflow was used to determine origination and detection points of near-miss errors, categorized into 7 major steps (patient assessment/orders, simulation, contouring/treatment planning, pre-treatment plan checks, therapist/on-treatment review, post-treatment checks, and equipment issues). Categories were compared using ANOVA. Results: In the 7-step workflow, 23% of near-miss errors were detected within the same step in the workflow, while an additional 37% were detected by the next step in the workflow, and 23% were detected two steps downstream. Errors detected further from origination were more severe (p<.001; Figure 1). The most common source of near-miss errors was treatment planning/contouring, with 476 near misses (35%). Of those 476, only 72(15%) were found before leaving treatment planning, 213(45%) were found at physics plan checks, and 191(40%) were caught at the therapist pre-treatment chart review or on portal imaging. Errors that passed through physics plan checks and were detected by therapists were more severe than other errors originating in contouring/treatment planning (1.81 vs 1.33, p<0.001). Conclusion: Errors caught by radiation treatment therapists tend to be more severe than errors caught earlier in the workflow, highlighting the importance of safety

  19. An Energy efficient application specific integrated circuit for electrocardiogram feature detection and its potential for ambulatory cardiovascular disease detection.

    Science.gov (United States)

    Jain, Sanjeev Kumar; Bhaumik, Basabi

    2016-03-01

    A novel algorithm based on forward search is developed for real-time electrocardiogram (ECG) signal processing and implemented in application specific integrated circuit (ASIC) for QRS complex related cardiovascular disease diagnosis. The authors have evaluated their algorithm using MIT-BIH database and achieve sensitivity of 99.86% and specificity of 99.93% for QRS complex peak detection. In this Letter, Physionet PTB diagnostic ECG database is used for QRS complex related disease detection. An ASIC for cardiovascular disease detection is fabricated using 130-nm CMOS high-speed process technology. The area of the ASIC is 0.5 mm(2). The power dissipation is 1.73 μW at the operating frequency of 1 kHz with a supply voltage of 0.6 V. The output from the ASIC is fed to their Android application that generates diagnostic report and can be sent to a cardiologist through email. Their ASIC result shows average failed detection rate of 0.16% for six leads data of 290 patients in PTB diagnostic ECG database. They also have implemented a low-leakage version of their ASIC. The ASIC dissipates only 45 pJ with a supply voltage of 0.9 V. Their proposed ASIC is most suitable for energy efficient telemetry cardiovascular disease detection system.

  20. Application of hazard analysis critical control points (HACCP) to organic chemical contaminants in food.

    Science.gov (United States)

    Ropkins, K; Beck, A J

    2002-03-01

    Hazard Analysis Critical Control Points (HACCP) is a systematic approach to the identification, assessment, and control of hazards that was developed as an effective alternative to conventional end-point analysis to control food safety. It has been described as the most effective means of controlling foodborne diseases, and its application to the control of microbiological hazards has been accepted internationally. By contrast, relatively little has been reported relating to the potential use of HACCP, or HACCP-like procedures, to control chemical contaminants of food. This article presents an overview of the implementation of HACCP and discusses its application to the control of organic chemical contaminants in the food chain. Although this is likely to result in many of the advantages previously identified for microbiological HACCP, that is, more effective, efficient, and economical hazard management, a number of areas are identified that require further research and development. These include: (1) a need to refine the methods of chemical contaminant identification and risk assessment employed, (2) develop more cost-effective monitoring and control methods for routine chemical contaminant surveillance of food, and (3) improve the effectiveness of process optimization for the control of chemical contaminants in food.

  1. Maximum Power Point Tracking of Photovoltaic System for Traffic Light Application

    Directory of Open Access Journals (Sweden)

    Riza Muhida

    2013-07-01

    Full Text Available Photovoltaic traffic light system is a significant application of renewable energy source. The development of the system is an alternative effort of local authority to reduce expenditure for paying fees to power supplier which the power comes from conventional energy source. Since photovoltaic (PV modules still have relatively low conversion efficiency, an alternative control of maximum power point tracking (MPPT method is applied to the traffic light system. MPPT is intended to catch up the maximum power at daytime in order to charge the battery at the maximum rate in which the power from the battery is intended to be used at night time or cloudy day. MPPT is actually a DC-DC converter that can step up or down voltage in order to achieve the maximum power using Pulse Width Modulation (PWM control. From experiment, we obtained the voltage of operation using MPPT is at 16.454 V, this value has error of 2.6%, if we compared with maximum power point voltage of PV module that is 16.9 V. Based on this result it can be said that this MPPT control works successfully to deliver the power from PV module to battery maximally.

  2. Aging Detection of Electrical Point Machines Based on Support Vector Data Description

    Directory of Open Access Journals (Sweden)

    Jaewon Sa

    2017-11-01

    Full Text Available Electrical point machines (EPM must be replaced at an appropriate time to prevent the occurrence of operational safety or stability problems in trains resulting from aging or budget constraints. However, it is difficult to replace EPMs effectively because the aging conditions of EPMs depend on the operating environments, and thus, a guideline is typically not be suitable for replacing EPMs at the most timely moment. In this study, we propose a method of classification for the detection of an aging effect to facilitate the timely replacement of EPMs. We employ support vector data description to segregate data of “aged” and “not-yet-aged” equipment by analyzing the subtle differences in normalized electrical signals resulting from aging. Based on the before and after-replacement data that was obtained from experimental studies that were conducted on EPMs, we confirmed that the proposed method was capable of classifying machines based on exhibited aging effects with adequate accuracy.

  3. Human detection and motion analysis at security points

    Science.gov (United States)

    Ozer, I. Burak; Lv, Tiehan; Wolf, Wayne H.

    2003-08-01

    This paper presents a real-time video surveillance system for the recognition of specific human activities. Specifically, the proposed automatic motion analysis is used as an on-line alarm system to detect abnormal situations in a campus environment. A smart multi-camera system developed at Princeton University is extended for use in smart environments in which the camera detects the presence of multiple persons as well as their gestures and their interaction in real-time.

  4. Face Detection and Face Recognition in Android Mobile Applications

    Directory of Open Access Journals (Sweden)

    Octavian DOSPINESCU

    2016-01-01

    Full Text Available The quality of the smartphone’s camera enables us to capture high quality pictures at a high resolution, so we can perform different types of recognition on these images. Face detection is one of these types of recognition that is very common in our society. We use it every day on Facebook to tag friends in our pictures. It is also used in video games alongside Kinect concept, or in security to allow the access to private places only to authorized persons. These are just some examples of using facial recognition, because in modern society, detection and facial recognition tend to surround us everywhere. The aim of this article is to create an appli-cation for smartphones that can recognize human faces. The main goal of this application is to grant access to certain areas or rooms only to certain authorized persons. For example, we can speak here of hospitals or educational institutions where there are rooms where only certain employees can enter. Of course, this type of application can cover a wide range of uses, such as helping people suffering from Alzheimer's to recognize the people they loved, to fill gaps persons who can’t remember the names of their relatives or for example to automatically capture the face of our own children when they smile.

  5. Portable Amplifier Design for a Novel EEG Monitor in Point-of-Care Applications.

    Science.gov (United States)

    Luan, Bo; Sun, Mingui; Jia, Wenyan

    2012-01-01

    The Electroencephalography (EEG) is a common diagnostic tool for neurological diseases and dysfunctions, such as epilepsy and insomnia. However, the current EEG technology cannot be utilized quickly and conveniently at the point of care due to the complex skin preparation procedures required and the inconvenient EEG data acquisition systems. This work presents a portable amplifier design that integrates a set of skin screw electrodes and a wireless data link. The battery-operated amplifier contains an instrumentation amplifier, two noninverting amplifiers, two high-pass filters, and a low-pass filter. It is able to magnify the EEG signals over 10,000 times and has a high impedance, low noise, small size and low weight. Our electrode and amplifier are ideal for point-of-care applications, especially during transportation of patients suffering from traumatic brain injury or stroke.

  6. CERN Web Application Detection. Refactoring and release as open source software

    CERN Document Server

    Lizonczyk, Piotr

    2015-01-01

    This paper covers my work during my assignment as participant of CERN Summer Students 2015 programme. The project was aimed at refactoring and publication of the Web Application Detection tool, which was developed at CERN and priorly used internally by the Computer Security team. The range of tasks performed include initial refactoring of code, which was developed like a script rather than a Python package, through extracting components that were not specific to CERN usage, the subsequent final release of the source code on GitHub and the integration with third-party software i.e. the w3af tool. Ultimately, Web Application Detection software received positive responses, being downloaded ca. 1500 times at the time of writing this report.

  7. Point Defects in Two-Dimensional Layered Semiconductors: Physics and Its Applications

    Science.gov (United States)

    Suh, Joonki

    Recent advances in material science and semiconductor processing have been achieved largely based on in-depth understanding, efficient management and advanced application of point defects in host semiconductors, thus finding the relevant techniques such as doping and defect engineering as a traditional scientific and technological solution. Meanwhile, two- dimensional (2D) layered semiconductors currently draw tremendous attentions due to industrial needs and their rich physics at the nanoscale; as we approach the end of critical device dimensions in silicon-based technology, ultra-thin semiconductors have the potential as next- generation channel materials, and new physics also emerges at such reduced dimensions where confinement of electrons, phonons, and other quasi-particles is significant. It is therefore rewarding and interesting to understand and redefine the impact of lattice defects by investigating their interactions with energy/charge carriers of the host matter. Potentially, the established understanding will provide unprecedented opportunities for realizing new functionalities and enhancing the performance of energy harvesting and optoelectronic devices. In this thesis, multiple novel 2D layered semiconductors, such as bismuth and transition- metal chalcogenides, are explored. Following an introduction of conventional effects induced by point defects in semiconductors, the related physics of electronically active amphoteric defects is revisited in greater details. This can elucidate the complication of a two-dimensional electron gas coexisting with the topological states on the surface of bismuth chalcogenides, recently suggested as topological insulators. Therefore, native point defects are still one of the keys to understand and exploit topological insulators. In addition to from a fundamental science point of view, the effects of point defects on the integrated thermal-electrical transport, as well as the entropy-transporting process in

  8. 3D Modeling of Building Indoor Spaces and Closed Doors from Imagery and Point Clouds

    Directory of Open Access Journals (Sweden)

    Lucía Díaz-Vilariño

    2015-02-01

    Full Text Available 3D models of indoor environments are increasingly gaining importance due to the wide range of applications to which they can be subjected: from redesign and visualization to monitoring and simulation. These models usually exist only for newly constructed buildings; therefore, the development of automatic approaches for reconstructing 3D indoors from imagery and/or point clouds can make the process easier, faster and cheaper. Among the constructive elements defining a building interior, doors are very common elements and their detection can be very useful either for knowing the environment structure, to perform an efficient navigation or to plan appropriate evacuation routes. The fact that doors are topologically connected to walls by being coplanar, together with the unavoidable presence of clutter and occlusions indoors, increases the inherent complexity of the automation of the recognition process. In this work, we present a pipeline of techniques used for the reconstruction and interpretation of building interiors based on point clouds and images. The methodology analyses the visibility problem of indoor environments and goes in depth with door candidate detection. The presented approach is tested in real data sets showing its potential with a high door detection rate and applicability for robust and efficient envelope reconstruction.

  9. Hygienic-sanitary working practices and implementation of a Hazard Analysis and Critical Control Point (HACCP plan in lobster processing industries

    Directory of Open Access Journals (Sweden)

    Cristina Farias da Fonseca

    2013-03-01

    Full Text Available This study aimed to verify the hygienic-sanitary working practices and to create and implement a Hazard Analysis Critical Control Point (HACCP in two lobster processing industries in Pernambuco State, Brazil. The industries studied process frozen whole lobsters, frozen whole cooked lobsters, and frozen lobster tails for exportation. The application of the hygienic-sanitary checklist in the industries analyzed achieved conformity rates over 96% to the aspects evaluated. The use of the Hazard Analysis Critical Control Point (HACCP plan resulted in the detection of two critical control points (CCPs including the receiving and classification steps in the processing of frozen lobster and frozen lobster tails, and an additional critical control point (CCP was detected during the cooking step of processing of the whole frozen cooked lobster. The proper implementation of the Hazard Analysis Critical Control Point (HACCP plan in the lobster processing industries studied proved to be the safest and most cost-effective method to monitor each critical control point (CCP hazards.

  10. An ultrahigh-accuracy Miniature Dew Point Sensor based on an Integrated Photonics Platform

    Science.gov (United States)

    Tao, Jifang; Luo, Yu; Wang, Li; Cai, Hong; Sun, Tao; Song, Junfeng; Liu, Hui; Gu, Yuandong

    2016-07-01

    The dew point is the temperature at which vapour begins to condense out of the gaseous phase. The deterministic relationship between the dew point and humidity is the basis for the industry-standard “chilled-mirror” dew point hygrometers used for highly accurate humidity measurements, which are essential for a broad range of industrial and metrological applications. However, these instruments have several limitations, such as high cost, large size and slow response. In this report, we demonstrate a compact, integrated photonic dew point sensor (DPS) that features high accuracy, a small footprint, and fast response. The fundamental component of this DPS is a partially exposed photonic micro-ring resonator, which serves two functions simultaneously: 1) sensing the condensed water droplets via evanescent fields and 2) functioning as a highly accurate, in situ temperature sensor based on the thermo-optic effect (TOE). This device virtually eliminates most of the temperature-related errors that affect conventional “chilled-mirror” hygrometers. Moreover, this DPS outperforms conventional “chilled-mirror” hygrometers with respect to size, cost and response time, paving the way for on-chip dew point detection and extension to applications for which the conventional technology is unsuitable because of size, cost, and other constraints.

  11. DESIGN A FILTER TO DETECT AND REMOVE VEGETATION FROM ULTRA-CAM-X AERIAL IMAGES’ POINT CLOUD TO PRODUCE AUTOMATICALLY DIGITAL ELEVATION MODEL

    Directory of Open Access Journals (Sweden)

    H. Enayati

    2015-12-01

    segmented image is added to raster of elevation and vegetation elevation is detected. Results is showing that point clouds’ texture is a good data for filtering vegetation and generating DEM automatically.

  12. Collaborative Indoor Access Point Localization Using Autonomous Mobile Robot Swarm.

    Science.gov (United States)

    Awad, Fahed; Naserllah, Muhammad; Omar, Ammar; Abu-Hantash, Alaa; Al-Taj, Abrar

    2018-01-31

    Localization of access points has become an important research problem due to the wide range of applications it addresses such as dismantling critical security threats caused by rogue access points or optimizing wireless coverage of access points within a service area. Existing proposed solutions have mostly relied on theoretical hypotheses or computer simulation to demonstrate the efficiency of their methods. The techniques that rely on estimating the distance using samples of the received signal strength usually assume prior knowledge of the signal propagation characteristics of the indoor environment in hand and tend to take a relatively large number of uniformly distributed random samples. This paper presents an efficient and practical collaborative approach to detect the location of an access point in an indoor environment without any prior knowledge of the environment. The proposed approach comprises a swarm of wirelessly connected mobile robots that collaboratively and autonomously collect a relatively small number of non-uniformly distributed random samples of the access point's received signal strength. These samples are used to efficiently and accurately estimate the location of the access point. The experimental testing verified that the proposed approach can identify the location of the access point in an accurate and efficient manner.

  13. A survey of direct inversion methods having possible application to tunnel detection

    International Nuclear Information System (INIS)

    Mager, R.D.

    1985-01-01

    Within recent years there has been considerable interest in the development of geophysical methods for the location of hidden underground tunnels and cavities. Consideration of this problem has been motivated by military applications, such as the detection of shallow man-made tunnels and arm caches, as well as civilian applications such as detection of limestone cavities in karst terrain and the mapping of abandoned mine workings. There are also applications for in-situ coal gasification and for the monitoring of nuclear waste disposal sites. The most reliable method presently used to map these underground anomalies has been direct detection by closely spaced drilling. However, the high cost of drilling renders this method impractical except for detailed and localized mapping, and certainly unfeasible for any type of broad-scale reconnaissance activity. Largely motivated by petroleum and mineral exploration needs, however, the seismic industry has seen a virtual revolution in acquisition and processing techniques within the past ten years. Paralleling these developments have been corresponding developments in acoustical imaging and non-destructive testing. Researchers in the field of inverse scattering have produced a number of new methods for target imaging from backscattered reflection data

  14. Economic study of NHR application on high pour point oil field

    International Nuclear Information System (INIS)

    Zhao Gang; Zhang Zuoyi; Ma Yuanle

    1997-01-01

    In order to extent the application of NHR (nuclear heating reactor) and cut down the oil production costs, the authors designed different heating disposition by NHR and boiler heating stations in high pour point oil reservoir, total 16.9 km 2 , in Daqing oil field. This work was based on the study of history matching, water flood planning and hot water circulation for the reservoir. The analyzing results show that, the convert heating cost of NHR is a third of boiler's and the net oil production of NHR is 4 times more than the latter. Considering economization and reliability, authors suggest to adopt the scheme of two NHR with one boiler heating station

  15. LiDAR-IMU Time Delay Calibration Based on Iterative Closest Point and Iterated Sigma Point Kalman Filter.

    Science.gov (United States)

    Liu, Wanli

    2017-03-08

    The time delay calibration between Light Detection and Ranging (LiDAR) and Inertial Measurement Units (IMUs) is an essential prerequisite for its applications. However, the correspondences between LiDAR and IMU measurements are usually unknown, and thus cannot be computed directly for the time delay calibration. In order to solve the problem of LiDAR-IMU time delay calibration, this paper presents a fusion method based on iterative closest point (ICP) and iterated sigma point Kalman filter (ISPKF), which combines the advantages of ICP and ISPKF. The ICP algorithm can precisely determine the unknown transformation between LiDAR-IMU; and the ISPKF algorithm can optimally estimate the time delay calibration parameters. First of all, the coordinate transformation from the LiDAR frame to the IMU frame is realized. Second, the measurement model and time delay error model of LiDAR and IMU are established. Third, the methodology of the ICP and ISPKF procedure is presented for LiDAR-IMU time delay calibration. Experimental results are presented that validate the proposed method and demonstrate the time delay error can be accurately calibrated.

  16. [Endoscopic endonasal detection of cerebrospinal fluid leakage with topical fluorescein].

    Science.gov (United States)

    Sato, Taku; Kishida, Yugo; Watanabe, Tadashi; Tani, Akiko; Tada, Yasuhiro; Tamura, Takamitsu; Ichikawa, Masahiro; Sakuma, Jun; Omori, Koichi; Saito, Kiyoshi

    2013-08-01

    We evaluated the effectiveness of intraoperative topical application of fluorescein to detect the leakage point of cerebrospinal fluid(CSF)rhinorrhea. Three patients with CSF rhinorrhea were treated with an endoscopic endonasal technique. Ten percent fluorescein was topically used for intraoperative localization of the leak site. A change of the fluorescein color from brown to green due to dilation of CSF were recognized as evidence of CSF rhinorrhea. We repeated the procedure to detect any small defects. All CSF rhinorrheas were successfully repaired by this endoscopic endonasal approach. Topical application of fluorescein is simple and sensitive for identifying intraoperative CSF rhinorrhea.

  17. Fast Edge Detection and Segmentation of Terrestrial Laser Scans Through Normal Variation Analysis

    Science.gov (United States)

    Che, E.; Olsen, M. J.

    2017-09-01

    Terrestrial Laser Scanning (TLS) utilizes light detection and ranging (lidar) to effectively and efficiently acquire point cloud data for a wide variety of applications. Segmentation is a common procedure of post-processing to group the point cloud into a number of clusters to simplify the data for the sequential modelling and analysis needed for most applications. This paper presents a novel method to rapidly segment TLS data based on edge detection and region growing. First, by computing the projected incidence angles and performing the normal variation analysis, the silhouette edges and intersection edges are separated from the smooth surfaces. Then a modified region growing algorithm groups the points lying on the same smooth surface. The proposed method efficiently exploits the gridded scan pattern utilized during acquisition of TLS data from most sensors and takes advantage of parallel programming to process approximately 1 million points per second. Moreover, the proposed segmentation does not require estimation of the normal at each point, which limits the errors in normal estimation propagating to segmentation. Both an indoor and outdoor scene are used for an experiment to demonstrate and discuss the effectiveness and robustness of the proposed segmentation method.

  18. AppFA: A Novel Approach to Detect Malicious Android Applications on the Network

    Directory of Open Access Journals (Sweden)

    Gaofeng He

    2018-01-01

    Full Text Available We propose AppFA, an Application Flow Analysis approach, to detect malicious Android applications (simply apps on the network. Unlike most of the existing work, AppFA does not need to install programs on mobile devices or modify mobile operating systems to extract detection features. Besides, it is able to handle encrypted network traffic. Specifically, we propose a constrained clustering algorithm to classify apps network traffic, and use Kernel Principal Component Analysis to build their network behavior profiles. After that, peer group analysis is explored to detect malicious apps by comparing apps’ network behavior profiles with the historical data and the profiles of their selected peer groups. These steps can be repeated every several minutes to meet the requirement of online detection. We have implemented AppFA and tested it with a public dataset. The experimental results show that AppFA can cluster apps network traffic efficiently and detect malicious Android apps with high accuracy and low false positive rate. We have also tested the performance of AppFA from the computational time standpoint.

  19. Development and Application of Microfabricated Chemical Gas Sensors For Aerospace Applications

    Science.gov (United States)

    Hunter, G. W.; Neudeck, P. G.; Fralick, G.; Thomas, V.; Liu, C. C.; Wu, Q. H.; Sawayda, M. S.; Jin, A.; Hammond, J.; Makel, D.; hide

    1990-01-01

    Aerospace applications require the development of chemical sensors with capabilities beyond those of commercially available sensors. In particular, factors such as minimal sensor size, weight, and power consumption are particularly important. Development areas which have potential aerospace applications include launch vehicle leak detection, engine health monitoring and control, and fire detection. Sensor development for these applications is based on progress in three types of technology: 1) Micromachining and microfabrication (Microsystem) technology to fabricate miniaturized sensors. 2) The use of nanocrystalline materials to develop sensors with improved stability combined with higher sensitivity. 3) The development of high temperature semiconductors, especially silicon carbide. Sensor development for each application involves its own challenges in the fields of materials science and fabrication technology. This paper discusses the needs of space applications and the point-contact sensor technology being developed to address these needs. Sensors to measure hydrogen, hydrocarbons, nitrogen oxides (Nox, carbon monoxide, oxygen, and carbon dioxide are being developed. A description is given of each sensor type and its present stage of development. Demonstration and application these sensor technologies will be described. The demonstrations range from use of a microsystem based hydrogen sensor on the Shuttle to engine demonstration of a nanocrystalline based sensor for NO, detection. It is concluded that microfabricated sensor technology has significant potential for use in a range of aerospace applications.

  20. Methods for registration laser scanner point clouds in forest stands

    International Nuclear Information System (INIS)

    Bienert, A.; Pech, K.; Maas, H.-G.

    2011-01-01

    Laser scanning is a fast and efficient 3-D measurement technique to capture surface points describing the geometry of a complex object in an accurate and reliable way. Besides airborne laser scanning, terrestrial laser scanning finds growing interest for forestry applications. These two different recording platforms show large differences in resolution, recording area and scan viewing direction. Using both datasets for a combined point cloud analysis may yield advantages because of their largely complementary information. In this paper, methods will be presented to automatically register airborne and terrestrial laser scanner point clouds of a forest stand. In a first step, tree detection is performed in both datasets in an automatic manner. In a second step, corresponding tree positions are determined using RANSAC. Finally, the geometric transformation is performed, divided in a coarse and fine registration. After a coarse registration, the fine registration is done in an iterative manner (ICP) using the point clouds itself. The methods are tested and validated with a dataset of a forest stand. The presented registration results provide accuracies which fulfill the forestry requirements [de

  1. Application of Electronic Noses for Disease Diagnosis and Food Spoilage Detection

    OpenAIRE

    Casalinuovo, Ida A.; Di Pierro, Donato; Coletta, Massimiliano; Di Francesco, Paolo

    2006-01-01

    Over the last twenty years, newly developed chemical sensor systems (so-called “electronic noses”) have odour analyses made possible. This paper describes the applications of these systems for microbial detection in different fields such as medicine and the food industry, where fast detection methods are essential for appropriate management of health care. Several groups have employed different electronic noses for classification and quantification of bacteria and fungi to obtain accurate med...

  2. [MPLW515L point mutation in patients with myeloproliferative disease].

    Science.gov (United States)

    Xia, Jun; Xu, Wei; Zhang, Su-Jiang; Fan, Lei; Qiao, Chun; Li, Jian-Yong

    2008-12-01

    In order to investigate the frequency of MPLW515L and JAK2V617F point mutations of the patients with myeloproliferative disease (MPD) in Nanjing area, MPLW515L and JAK2V617F point mutations were simultaneously detected by alleles specific polymerase chain reaction (AS-PCR) and sequencing in 190 MPD patients. The results showed that MPLW515L point mutation was detected in 1 out of 102 essential thrombocythemia (ET) patients (1.0%) and was not detected in 32 polycythemia vera (PV) patients, 13 idiopathic myelofibrosis (IMF) patients, 43 chronic myelogenous leukemia (CML) patients. JAK2V617F point mutation was detected in 20 out of 32 PV patients (62.5%), 43 out of 102 ET patients (42.2%), 5 out of 13 IMF patients (38.5%), and was not detected in 43 CML patients. It is concluded that MPLW515L point mutation exists in ET patient, but is not found in PV, IMF and CML. JAK2V617F point mutation exists in PV, ET and IMF, but not in CML.

  3. Application of flaw detection methods for detection of fatigue processes in low-alloyed steel

    Directory of Open Access Journals (Sweden)

    Zbigniew H. śUREK

    2007-01-01

    Full Text Available The paper presents the investigations conducted in the Fraunhofer Institute (IZFP Saarbrücken by use of a BEMI microscope (BEMI= Barkhausenrausch- und Wirbelstrom-Mikroskopie or Barkhausen Noise and Eddy Current Microscopy. The ability to detect cyclic and contact fatigue load influences has been investigated. The measurement amplitudes obtained with Barkhausen Noise and Eddy Current probes havebeen analysed. Correlation of measurement results and material’s condition has been observed in case of the eddy current mode method for frequencies above 2 MHz (for contact-loaded material samples. Detection of material’s fatigue process (at 80 % fatiguelife in the sample subjected to series of high-cyclic loads has been proven to be practically impossible. Application of flaw detection methods in material fatigue tests requires modification of test methods and use of investigation methods relevant to physical parameters of the investigated material. The magnetic leakage field method, which has been abandoned by many researchers, may be of significant use in the material fatigue assessment and may provide new research prospects.

  4. A graph signal filtering-based approach for detection of different edge types on airborne lidar data

    Science.gov (United States)

    Bayram, Eda; Vural, Elif; Alatan, Aydin

    2017-10-01

    Airborne Laser Scanning is a well-known remote sensing technology, which provides a dense and highly accurate, yet unorganized point cloud of earth surface. During the last decade, extracting information from the data generated by airborne LiDAR systems has been addressed by many studies in geo-spatial analysis and urban monitoring applications. However, the processing of LiDAR point clouds is challenging due to their irregular structure and 3D geometry. In this study, we propose a novel framework for the detection of the boundaries of an object or scene captured by LiDAR. Our approach is motivated by edge detection techniques in vision research and it is established on graph signal filtering which is an exciting and promising field of signal processing for irregular data types. Due to the convenient applicability of graph signal processing tools on unstructured point clouds, we achieve the detection of the edge points directly on 3D data by using a graph representation that is constructed exclusively to answer the requirements of the application. Moreover, considering the elevation data as the (graph) signal, we leverage aerial characteristic of the airborne LiDAR data. The proposed method can be employed both for discovering the jump edges on a segmentation problem and for exploring the crease edges on a LiDAR object on a reconstruction/modeling problem, by only adjusting the filter characteristics.

  5. Speech endpoint detection with non-language speech sounds for generic speech processing applications

    Science.gov (United States)

    McClain, Matthew; Romanowski, Brian

    2009-05-01

    Non-language speech sounds (NLSS) are sounds produced by humans that do not carry linguistic information. Examples of these sounds are coughs, clicks, breaths, and filled pauses such as "uh" and "um" in English. NLSS are prominent in conversational speech, but can be a significant source of errors in speech processing applications. Traditionally, these sounds are ignored by speech endpoint detection algorithms, where speech regions are identified in the audio signal prior to processing. The ability to filter NLSS as a pre-processing step can significantly enhance the performance of many speech processing applications, such as speaker identification, language identification, and automatic speech recognition. In order to be used in all such applications, NLSS detection must be performed without the use of language models that provide knowledge of the phonology and lexical structure of speech. This is especially relevant to situations where the languages used in the audio are not known apriori. We present the results of preliminary experiments using data from American and British English speakers, in which segments of audio are classified as language speech sounds (LSS) or NLSS using a set of acoustic features designed for language-agnostic NLSS detection and a hidden-Markov model (HMM) to model speech generation. The results of these experiments indicate that the features and model used are capable of detection certain types of NLSS, such as breaths and clicks, while detection of other types of NLSS such as filled pauses will require future research.

  6. High mobility ZnO nanowires for terahertz detection applications

    International Nuclear Information System (INIS)

    Liu, Huiqiang; Peng, Rufang; Chu, Shijin; Chu, Sheng

    2014-01-01

    An oxide nanowire material was utilized for terahertz detection purpose. High quality ZnO nanowires were synthesized and field-effect transistors were fabricated. Electrical transport measurements demonstrated the nanowire with good transfer characteristics and fairly high electron mobility. It is shown that ZnO nanowires can be used as building blocks for the realization of terahertz detectors based on a one-dimensional plasmon detection configuration. Clear terahertz wave (∼0.3 THz) induced photovoltages were obtained at room temperature with varying incidence intensities. Further analysis showed that the terahertz photoresponse is closely related to the high electron mobility of the ZnO nanowire sample, which suggests that oxide nanoelectronics may find useful terahertz applications.

  7. Detection of bursts in extracellular spike trains using hidden semi-Markov point process models.

    Science.gov (United States)

    Tokdar, Surya; Xi, Peiyi; Kelly, Ryan C; Kass, Robert E

    2010-08-01

    Neurons in vitro and in vivo have epochs of bursting or "up state" activity during which firing rates are dramatically elevated. Various methods of detecting bursts in extracellular spike trains have appeared in the literature, the most widely used apparently being Poisson Surprise (PS). A natural description of the phenomenon assumes (1) there are two hidden states, which we label "burst" and "non-burst," (2) the neuron evolves stochastically, switching at random between these two states, and (3) within each state the spike train follows a time-homogeneous point process. If in (2) the transitions from non-burst to burst and burst to non-burst states are memoryless, this becomes a hidden Markov model (HMM). For HMMs, the state transitions follow exponential distributions, and are highly irregular. Because observed bursting may in some cases be fairly regular-exhibiting inter-burst intervals with small variation-we relaxed this assumption. When more general probability distributions are used to describe the state transitions the two-state point process model becomes a hidden semi-Markov model (HSMM). We developed an efficient Bayesian computational scheme to fit HSMMs to spike train data. Numerical simulations indicate the method can perform well, sometimes yielding very different results than those based on PS.

  8. [Application of lysosomal detection in marine pollution monitoring: research progress].

    Science.gov (United States)

    Weng, You-Zhu; Fang, Yong-Qiang; Zhang, Yu-Sheng

    2013-11-01

    Lysosome is an important organelle existing in eukaryotic cells. With the development of the study on the structure and function of lysosome in recent years, lysosome is considered as a target of toxic substances on subcellular level, and has been widely applied abroad in marine pollution monitoring. This paper summarized the biological characteristics of lysosomal marker enzyme, lysosome-autophagy system, and lysosomal membrane, and introduced the principles and methods of applying lysosomal detection in marine pollution monitoring. Bivalve shellfish digestive gland and fish liver are the most sensitive organs for lysosomal detection. By adopting the lysosomal detection techniques such as lysosomal membrane stability (LMS) test, neutral red retention time (NRRT) assay, morphological measurement (MM) of lysosome, immunohistochemical (Ih) assay of lysosomal marker enzyme, and electron microscopy (EM), the status of marine pollution can be evaluated. It was suggested that the lysosome could be used as a biomarker for monitoring marine environmental pollution. The advantages and disadvantages of lysosomal detection and some problems worthy of attention were analyzed, and the application prospects of lysosomal detection were discussed.

  9. Primary circuit leak detection an application on PWR vessel head penetrations

    International Nuclear Information System (INIS)

    Loisy, F.; Germain, J.L.; Chauvel, L.

    1996-01-01

    In 1991, cracks were discovered and localized in the lower part of certain vessel head adapters in EDF PWR units. While awaiting the replacement of the vessel heads in question, EDF developed systems to enable continuous monitoring of vessel head penetration, by means of early detection of leaks. One of these systems in based on detection of water vapour in a confined space above the vessel head. The efficiency of the measurement chain is particularly dependent on dilution of the leakage in the confined space prior TO entry in the sampling circuit. The detection threshold for this method is on the order of 1.2 liters/hour for a dilution rate of 1500 rate of 1500 m 3 /h and a dew point of 22 deg C. This system has now been in operation on three 1300-MW PWR units for three years, and has proved to function satisfactorily. (authors)

  10. PHP47 - Early assessment of highly innovative medical technology: clinical and economical gains of point-of-care applications for measuring potassium concentrations

    NARCIS (Netherlands)

    van de Wetering, G.; Hummel, J. Marjan; van Montfort, Augustinus P.W.P.; Montfoort, A.; IJzerman, Maarten Joost

    2009-01-01

    OBJECTIVES: Innovative point-of-care diagnostics are likely to be having a strong impact on health care. The aim of this study is to conduct an early assessment of point-of-care chips. These chips can detect many particles and, consequently, many product-market combinations can be developed. This

  11. A Contraction Fixed Point Theorem in Partially Ordered Metric Spaces and Application to Fractional Differential Equations

    Directory of Open Access Journals (Sweden)

    Xiangbing Zhou

    2012-01-01

    Full Text Available We generalize a fixed point theorem in partially ordered complete metric spaces in the study of A. Amini-Harandi and H. Emami (2010. We also give an application on the existence and uniqueness of the positive solution of a multipoint boundary value problem with fractional derivatives.

  12. Collaborative Indoor Access Point Localization Using Autonomous Mobile Robot Swarm

    Directory of Open Access Journals (Sweden)

    Fahed Awad

    2018-01-01

    Full Text Available Localization of access points has become an important research problem due to the wide range of applications it addresses such as dismantling critical security threats caused by rogue access points or optimizing wireless coverage of access points within a service area. Existing proposed solutions have mostly relied on theoretical hypotheses or computer simulation to demonstrate the efficiency of their methods. The techniques that rely on estimating the distance using samples of the received signal strength usually assume prior knowledge of the signal propagation characteristics of the indoor environment in hand and tend to take a relatively large number of uniformly distributed random samples. This paper presents an efficient and practical collaborative approach to detect the location of an access point in an indoor environment without any prior knowledge of the environment. The proposed approach comprises a swarm of wirelessly connected mobile robots that collaboratively and autonomously collect a relatively small number of non-uniformly distributed random samples of the access point’s received signal strength. These samples are used to efficiently and accurately estimate the location of the access point. The experimental testing verified that the proposed approach can identify the location of the access point in an accurate and efficient manner.

  13. Effective leaf area index retrieving from terrestrial point cloud data: coupling computational geometry application and Gaussian mixture model clustering

    Science.gov (United States)

    Jin, S.; Tamura, M.; Susaki, J.

    2014-09-01

    Leaf area index (LAI) is one of the most important structural parameters of forestry studies which manifests the ability of the green vegetation interacted with the solar illumination. Classic understanding about LAI is to consider the green canopy as integration of horizontal leaf layers. Since multi-angle remote sensing technique developed, LAI obliged to be deliberated according to the observation geometry. Effective LAI could formulate the leaf-light interaction virtually and precisely. To retrieve the LAI/effective LAI from remotely sensed data therefore becomes a challenge during the past decades. Laser scanning technique can provide accurate surface echoed coordinates with densely scanned intervals. To utilize the density based statistical algorithm for analyzing the voluminous amount of the 3-D points data is one of the subjects of the laser scanning applications. Computational geometry also provides some mature applications for point cloud data (PCD) processing and analysing. In this paper, authors investigated the feasibility of a new application for retrieving the effective LAI of an isolated broad leaf tree. Simplified curvature was calculated for each point in order to remove those non-photosynthetic tissues. Then PCD were discretized into voxel, and clustered by using Gaussian mixture model. Subsequently the area of each cluster was calculated by employing the computational geometry applications. In order to validate our application, we chose an indoor plant to estimate the leaf area, the correlation coefficient between calculation and measurement was 98.28 %. We finally calculated the effective LAI of the tree with 6 × 6 assumed observation directions.

  14. Multispectral Image Feature Points

    Directory of Open Access Journals (Sweden)

    Cristhian Aguilera

    2012-09-01

    Full Text Available This paper presents a novel feature point descriptor for the multispectral image case: Far-Infrared and Visible Spectrum images. It allows matching interest points on images of the same scene but acquired in different spectral bands. Initially, points of interest are detected on both images through a SIFT-like based scale space representation. Then, these points are characterized using an Edge Oriented Histogram (EOH descriptor. Finally, points of interest from multispectral images are matched by finding nearest couples using the information from the descriptor. The provided experimental results and comparisons with similar methods show both the validity of the proposed approach as well as the improvements it offers with respect to the current state-of-the-art.

  15. Multiplexed lateral flow biosensors: Technological advances for radically improving point-of-care diagnoses.

    Science.gov (United States)

    Li, Jia; Macdonald, Joanne

    2016-09-15

    Lateral flow biosensors are a leading technology in point-of-care diagnostics due to their simplicity, rapidness and low cost. Their primacy in this arena continues through technological breakthroughs such as multiplexing: the detection of more than one biomarker in a single assay. Multiplexing capacity is critical for improving diagnostic efficiency, enhancing the diagnostic precision for specific diseases and reducing diagnostic cost. Here we review, for the first time, the various types and strategies employed for creating multiplexed lateral flow biosensors. These are classified into four main categories in terms of specific application or multiplexing level, namely linear, parameter, spatial and conceptual. We describe the practical applications and implications for each approach and compare their advantages and disadvantages. Importantly, multiplexing is still subject to limitations of the traditional lateral flow biosensor, such as sensitivity and specificity. However, by pushing the limitations of the traditional medium into the multiplex arena, several technological breakthroughs are emerging with novel solutions that further expand the utility of lateral flow biosensing for point-of-care applications. Copyright © 2016 Elsevier B.V. All rights reserved.

  16. Ground Control Point - Wireless System Network for UAV-based environmental monitoring applications

    Science.gov (United States)

    Mejia-Aguilar, Abraham

    2016-04-01

    In recent years, Unmanned Aerial Vehicles (UAV) have seen widespread civil applications including usage for survey and monitoring services in areas such as agriculture, construction and civil engineering, private surveillance and reconnaissance services and cultural heritage management. Most aerial monitoring services require the integration of information acquired during the flight (such as imagery) with ground-based information (such as GPS information or others) for improved ground truth validation. For example, to obtain an accurate 3D and Digital Elevation Model based on aerial imagery, it is necessary to include ground-based information of coordinate points, which are normally acquired with surveying methods based on Global Position Systems (GPS). However, GPS surveys are very time consuming and especially for longer time series of monitoring data repeated GPS surveys are necessary. In order to improve speed of data collection and integration, this work presents an autonomous system based on Waspmote technologies build on single nodes interlinked in a Wireless Sensor Network (WSN) star-topology for ground based information collection and later integration with surveying data obtained by UAV. Nodes are designed to be visible from the air, to resist extreme weather conditions with low-power consumption. Besides, nodes are equipped with GPS as well as Inertial Measurement Unit (IMU), accelerometer, temperature and soil moisture sensors and thus provide significant advantages in a broad range of applications for environmental monitoring. For our purpose, the WSN transmits the environmental data with 3G/GPRS to a database on a regular time basis. This project provides a detailed case study and implementation of a Ground Control Point System Network for UAV-based vegetation monitoring of dry mountain grassland in the Matsch valley, Italy.

  17. Noncompact Equilibrium Points and Applications

    Directory of Open Access Journals (Sweden)

    Zahra Al-Rumaih

    2012-01-01

    Full Text Available We prove an equilibrium existence result for vector functions defined on noncompact domain and we give some applications in optimization and Nash equilibrium in noncooperative game.

  18. High-sensitivity detection of cardiac troponin I with UV LED excitation for use in point-of-care immunoassay

    OpenAIRE

    Rodenko, Olga; Eriksson, Susann; Tidemand-Lichtenberg, Peter; Troldborg, Carl Peder; Fodgaard, Henrik; van Os, Sylvana; Pedersen, Christian

    2017-01-01

    High-sensitivity cardiac troponin assay development enables determination of biological variation in healthy populations, more accurate interpretation of clinical results and points towards earlier diagnosis and rule-out of acute myocardial infarction. In this paper, we report on preliminary tests of an immunoassay analyzer employing an optimized LED excitation to measure on a standard troponin I and a novel research high-sensitivity troponin I assay. The limit of detection is improved by fac...

  19. Applications of Monte Carlo technique in the detection of explosives, narcotics and fissile material using neutron sources

    International Nuclear Information System (INIS)

    Sinha, Amar; Kashyap, Yogesh; Roy, Tushar; Agrawal, Ashish; Sarkar, P.S.; Shukla, Mayank

    2009-01-01

    The problem of illicit trafficking of explosives, narcotics or fissile materials represents a real challenge to civil security. Neutron based detection systems are being actively explored worldwide as a confirmatory tool for applications in the detection of explosives either hidden inside a vehicle or a cargo container or buried inside soil. The development of a system and its experimental testing is a tedious process and to develop such a system each experimental condition needs to be theoretically simulated. Monte Carlo based methods are used to find an optimized design for such detection system. In order to design such systems, it is necessary to optimize source and detector system for each specific application. The present paper deals with such optimization studies using Monte Carlo technique for tagged neutron based system for explosives and narcotics detection hidden in a cargo and landmine detection using backscatter neutrons. We will also discuss some simulation studies on detection of fissile material and photo-neutron source design for applications on cargo scanning. (author)

  20. Biochemical sensor tubing for point-of-care monitoring of intravenous drugs and metabolites.

    Science.gov (United States)

    Choi, Charles J; Wu, Hsin-Yu; George, Sherine; Weyhenmeyer, Jonathan; Cunningham, Brian T

    2012-02-07

    In medical facilities, there is strong motivation to develop detection systems that can provide continuous analysis of fluids in medical tubing used to either deliver or remove fluids from a patient's body. Possible applications include systems that increase the safety of intravenous (IV) drug injection and point-of-care health monitoring. In this work, we incorporated a surface-enhanced Raman scattering (SERS) sensor comprised of an array of closely spaced metal nanodomes into flexible tubing commonly used for IV drug delivery and urinary catheters. The nanodome sensor was fabricated by a low-cost, large-area process that enables single use disposable operation. As exemplary demonstrations, the sensor was used to kinetically detect promethazine (pain medication) and urea (urinary metabolite) within their clinically relevant concentration ranges. Distinct SERS peaks for each analyte were used to demonstrate separate detection and co-detection of the analytes.

  1. The use of upconverting phosphors in point-of-care (POC) testing

    Science.gov (United States)

    Tanke, Hans J.; Zuiderwijk, Michel; Wiesmeijer, Karien C.; Breedveld, Robert N.; Abrams, William R.; de Dood, Claudia J.; Tjon Kon Fat, Elisa M.; Corstjens, Paul L. A. M.

    2014-03-01

    Point-of-care (POC) testing is increasingly applied as a cost effective alternative to many diagnostic tests. Key in POC testing is to create sufficient assay sensitivity with relatively low cost reagents and equipment. For this purpose we have employed a unique reporter, upconverting phosphor (UCP) particles, in combination with lateral flow (LF) assays. UCPs, submicron ceramic particles doped with rare earth ions (lanthanides), convert infrared to visible light and do not suffer from autofluorescence which limits conventional fluorescence based assays. Low cost handheld readers and microfluidics were evaluated in various applications. Designed assays are well suited for applications outside diagnostic laboratories, in resource poor settings, and can even be used by patients at home. Using two distinctly different UCP-LF assay formats, we focussed on assays for infectious diseases based on the detection of pathogen-specific antibodies and/or antigens including nucleic acids to demonstrate active infection with HIV. Only minor adaptation of the standard UCP-LF assay format is needed to render the format suitable for applications involving low affinity capture antibodies (e.g. in the detection of neurotoxin, botulism), capture of small molecules (e.g. detection of melatonin, a key hormone in chronopharmacology) or the use of dry UCP reagents (e.g. detection of protein based fruit-ripening markers, of economic interest in agriculture). Finally, we anticipate on developments in healthcare (personalized medicine) by discussing the potential of one of the UCP-LF assay formats to measure serum trough levels of immunodrugs (e.g. infliximab or adalimumab) in patients treated for inflammatory bowel disease and rheumatoid arthritis.

  2. The role of soil in NBT applications to landmine detection problem

    International Nuclear Information System (INIS)

    Obhodas, Jasmina; Sudac, Davorin; Nad, Karlo; Valkovic, Vlado; Nebbia, Giancarlo; Viesti, Giuseppe

    2003-01-01

    Long-term observations of soil water content as well as determination of physical and chemical properties of different types of soils in Croatia were made in order to provide the necessary background information for landmine explosive detection. Soil water content is the key attribute of soil as a background in neutron backscattering technique (NBT) landmine detection application. If the critical value of the soil water content is reached, the detection of landmine explosives is not possible. It is recommended that soil moisture content for NBT application does not exceed 0.1 kg.kg-1 [1]. Nineteen representative samples of different soil types from different parts of Croatia were collected in order to establish soil bank with the necessary physical and chemical properties determined for each type of soil. In addition soil water content was measured on daily and weekly basis on several locations in Croatia. This procedure also included daily soil moisture measurements in the test field made of different types of soils from several locations in Croatia. This was done in order to evaluate the behavior of different types of soils under the same weather conditions

  3. High-Level Synthesis of DSP Applications Using Adaptive Negative Cycle Detection

    Directory of Open Access Journals (Sweden)

    Nitin Chandrachoodan

    2002-09-01

    Full Text Available The problem of detecting negative weight cycles in a graph is examined in the context of the dynamic graph structures that arise in the process of high level synthesis (HLS. The concept of adaptive negative cycle detection is introduced, in which a graph changes over time and negative cycle detection needs to be done periodically, but not necessarily after every individual change. We present an algorithm for this problem, based on a novel extension of the well-known Bellman-Ford algorithm that allows us to adapt existing cycle information to the modified graph, and show by experiments that our algorithm significantly outperforms previous incremental approaches for dynamic graphs. In terms of applications, the adaptive technique leads to a very fast implementation of Lawlers algorithm for the computation of the maximum cycle mean (MCM of a graph, especially for a certain form of sparse graph. Such sparseness often occurs in practical circuits and systems, as demonstrated, for example, by the ISCAS 89/93 benchmarks. The application of the adaptive technique to design-space exploration (synthesis is also demonstrated by developing automated search techniques for scheduling iterative data-flow graphs.

  4. A reliable, fast and low cost maximum power point tracker for photovoltaic applications

    Energy Technology Data Exchange (ETDEWEB)

    Enrique, J.M.; Andujar, J.M.; Bohorquez, M.A. [Departamento de Ingenieria Electronica, de Sistemas Informaticos y Automatica, Universidad de Huelva (Spain)

    2010-01-15

    This work presents a new maximum power point tracker system for photovoltaic applications. The developed system is an analog version of the ''P and O-oriented'' algorithm. It maintains its main advantages: simplicity, reliability and easy practical implementation, and avoids its main disadvantages: inaccurateness and relatively slow response. Additionally, the developed system can be implemented in a practical way at a low cost, which means an added value. The system also shows an excellent behavior for very fast variables in incident radiation levels. (author)

  5. Power point 2002 for successful presentation

    International Nuclear Information System (INIS)

    Moon, Insoo

    2002-01-01

    This book mentions power point 2002 for successful presentation, which deals with power point and presentation, all guide, the latest gear, for presentation, basic of power point 2002 such as slide, text compile, insertion of picture, figure and application of office guide, setting up new year plan using text like insertion text with various methods, compile effective text, and 200% application of tab, and addiction of pretty shape of characters, finishing of conversion of chinese character, and elimination of typographical error with spell checker.

  6. Track length estimation applied to point detectors

    International Nuclear Information System (INIS)

    Rief, H.; Dubi, A.; Elperin, T.

    1984-01-01

    The concept of the track length estimator is applied to the uncollided point flux estimator (UCF) leading to a new algorithm of calculating fluxes at a point. It consists essentially of a line integral of the UCF, and although its variance is unbounded, the convergence rate is that of a bounded variance estimator. In certain applications, involving detector points in the vicinity of collimated beam sources, it has a lower variance than the once-more-collided point flux estimator, and its application is more straightforward

  7. Nanobody-Based Apolipoprotein E Immunosensor for Point-of-Care Testing.

    Science.gov (United States)

    Ren, Xiang; Yan, Junrong; Wu, Dan; Wei, Qin; Wan, Yakun

    2017-09-22

    Alzheimer's disease (AD) biomarkers can reflect the neurochemical indicators used to estimate the risk in clinical nephrology. Apolipoprotein E (ApoE) is an early biomarker for AD in clinical diagnosis. In this research, through bactrian camel immunization, lymphocyte isolation, RNA extraction, and library construction, ApoE-specific Nbs with high affinity were successfully separated from an immune phage display nanobody library. Herein, a colorimetric immunosensor was developed for the point-of-care testing of ApoE by layer-by-layer nanoassembly techniques and novel nanobodies (Nbs). Using highly oriented Nbs as the capture and detection antibodies, an on-site immunosensor was developed by detecting the mean gray value of fade color due to the glutaraldehyde@3-aminopropyltrimethoxysilane oxidation by H 2 O 2 . The detection limit of AopE is 0.42 pg/mL, and the clinical analysis achieves a good performance. The novel easily operated immunosensor may have potential application in the clinical diagnosis and real-time monitoring for AD.

  8. Efficient Device-Independent Entanglement Detection for Multipartite Systems

    Science.gov (United States)

    Baccari, F.; Cavalcanti, D.; Wittek, P.; Acín, A.

    2017-04-01

    Entanglement is one of the most studied properties of quantum mechanics for its application in quantum information protocols. Nevertheless, detecting the presence of entanglement in large multipartite states continues to be a great challenge both from the theoretical and the experimental point of view. Most of the known methods either have computational costs that scale inefficiently with the number of particles or require more information on the state than what is attainable in everyday experiments. We introduce a new technique for entanglement detection that provides several important advantages in these respects. First, it scales efficiently with the number of particles, thus allowing for application to systems composed by up to few tens of particles. Second, it needs only the knowledge of a subset of all possible measurements on the state, therefore being apt for experimental implementation. Moreover, since it is based on the detection of nonlocality, our method is device independent. We report several examples of its implementation for well-known multipartite states, showing that the introduced technique has a promising range of applications.

  9. LIDAR, Point Clouds, and their Archaeological Applications

    Energy Technology Data Exchange (ETDEWEB)

    White, Devin A [ORNL

    2013-01-01

    It is common in contemporary archaeological literature, in papers at archaeological conferences, and in grant proposals to see heritage professionals use the term LIDAR to refer to high spatial resolution digital elevation models and the technology used to produce them. The goal of this chapter is to break that association and introduce archaeologists to the world of point clouds, in which LIDAR is only one member of a larger family of techniques to obtain, visualize, and analyze three-dimensional measurements of archaeological features. After describing how point clouds are constructed, there is a brief discussion on the currently available software and analytical techniques designed to make sense of them.

  10. Accuracy Constraint Determination in Fixed-Point System Design

    Directory of Open Access Journals (Sweden)

    Serizel R

    2008-01-01

    Full Text Available Most of digital signal processing applications are specified and designed with floatingpoint arithmetic but are finally implemented using fixed-point architectures. Thus, the design flow requires a floating-point to fixed-point conversion stage which optimizes the implementation cost under execution time and accuracy constraints. This accuracy constraint is linked to the application performances and the determination of this constraint is one of the key issues of the conversion process. In this paper, a method is proposed to determine the accuracy constraint from the application performance. The fixed-point system is modeled with an infinite precision version of the system and a single noise source located at the system output. Then, an iterative approach for optimizing the fixed-point specification under the application performance constraint is defined and detailed. Finally the efficiency of our approach is demonstrated by experiments on an MP3 encoder.

  11. Laser desorption mass spectrometry for biomolecule detection and its applications

    Science.gov (United States)

    Winston Chen, C. H.; Sammartano, L. J.; Isola, N. R.; Allman, S. L.

    2001-08-01

    During the past few years, we developed and used laser desorption mass spectrometry for biomolecule detections. Matrix-assisted laser desorption/ionization (MALDI) was successfully used to detect DNA fragments with the size larger than 3000 base pairs. It was also successfully used to sequence DNA with both enzymatic and chemical degradation methods to produce DNA ladders. We also developed MALDI with fragmentation for direct DNA sequencing for short DNA probes. Since laser desorption mass spectrometry for DNA detection has the advantages of fast speed and no need of labeling, it has a great potential for molecular diagnosis for disease and person identification by DNA fingerprinting. We applied laser desorption mass spectrometry to succeed in the diagnosis of cystic fibrosis and several other nerve degenerative diseases such as Huntington's disease. We also succeeded in demonstrating DNA typing for forensic applications.

  12. Laser desorption mass spectrometry for biomolecule detection and its applications

    International Nuclear Information System (INIS)

    Winston Chen, C.H.; Allman, S.L.; Sammartano, L.J.; Isola, N.R.

    2001-01-01

    During the past few years, we developed and used laser desorption mass spectrometry for biomolecule detections. Matrix-assisted laser desorption/ionization (MALDI) was successfully used to detect DNA fragments with the size larger than 3000 base pairs. It was also successfully used to sequence DNA with both enzymatic and chemical degradation methods to produce DNA ladders. We also developed MALDI with fragmentation for direct DNA sequencing for short DNA probes. Since laser desorption mass spectrometry for DNA detection has the advantages of fast speed and no need of labeling, it has a great potential for molecular diagnosis for disease and person identification by DNA fingerprinting. We applied laser desorption mass spectrometry to succeed in the diagnosis of cystic fibrosis and several other nerve degenerative diseases such as Huntington's disease. We also succeeded in demonstrating DNA typing for forensic applications

  13. Modified Proofreading PCR for Detection of Point Mutations, Insertions and Deletions Using a ddNTP-Blocked Primer

    Science.gov (United States)

    Chen, Qianqian; Chen, Xiaoxiang; Zhang, Sichao; Lan, Ke; Lu, Jian; Zhang, Chiyu

    2015-01-01

    The development of simple, accurate, rapid and cost-effective technologies for mutation detection is crucial to the early diagnosis and prevention of numerous genetic diseases, pharmacogenetics, and drug resistance. Proofreading PCR (PR-PCR) was developed for mutation detection in 1998 but is rarely applied due to its low efficiency in allele discrimination. Here we developed a modified PR-PCR method using a ddNTP-blocked primer and a mixture of DNA polymerases with and without the 3'-5' proofreading function. The ddNTP-blocked primer exhibited the best blocking efficiency to avoid nonspecific primer extension while the mixture of a tiny amount of high-fidelity DNA polymerase with a routine amount of Taq DNA polymerase provided the best discrimination and amplification effects. The modified PR-PCR method is quite capable of detecting various mutation types, including point mutations and insertions/deletions (indels), and allows discrimination amplification when the mismatch is located within the last eight nucleotides from the 3'-end of the ddNTP-blocked primer. The modified PR-PCR has a sensitivity of 1-5 × 102 copies and a selectivity of 5 × 10-5 mutant among 107 copies of wild-type DNA. It showed a 100% accuracy rate in the detection of P72R germ-line mutation in the TP53 gene among 60 clinical blood samples, and a high potential to detect rifampin-resistant mutations at low frequency in Mycobacterium tuberculosis using an adaptor and a fusion-blocked primer. These results suggest that the modified PR-PCR technique is effective in detection of various mutations or polymorphisms as a simple, sensitive and promising approach. PMID:25915410

  14. Extracting Corresponding Point Based on Texture Synthesis for Nearly Flat Textureless Object Surface

    Directory of Open Access Journals (Sweden)

    Min Mao

    2015-01-01

    Full Text Available Since the image feature points are always gathered at the range with significant intensity change, such as textured portions or edges of an image, which can be detected by the state-of-the-art intensity based point-detectors, there is nearly no point in the areas of low textured detected by classical interest-point detectors. In this paper we describe a novel algorithm based on affine transform and graph cut for interest point detecting and matching from wide baseline image pairs with weakly textured object. The detection and matching mechanism can be separated into three steps: firstly, the information on the large textureless areas will be enhanced by adding textures through the proposed texture synthesis algorithm TSIQ. Secondly, the initial interest-point set is detected by classical interest-point detectors. Finally, graph cuts are used to find the globally optimal set of matching points on stereo pairs. The efficacy of the proposed algorithm is verified by three kinds of experiments, that is, the influence of point detecting from synthetic texture with different texture sample, the stability under the different geometric transformations, and the performance to improve the quasi-dense matching algorithm, respectively.

  15. DECANTeR: DEteCtion of Anomalous outbouNd HTTP Traffic by Passive Application Fingerprinting

    NARCIS (Netherlands)

    Bortolameotti, R.; Ede, T. van; Caselli, M.; Everts, M.H.; Hartel, P.; Hofstede, R.; Jonker, W.; Peter, A.

    2017-01-01

    We present DECANTeR, a system to detect anomalous outbound HTTP communication, which passively extracts fingerprints for each application running on a monitored host. The goal of our system is to detect unknown malware and backdoor communication indicated by unknown fingerprints extracted from a

  16. An Efficient and Packing-Resilient Two-Phase Android Cloned Application Detection Approach

    Directory of Open Access Journals (Sweden)

    Fang Lyu

    2017-01-01

    Full Text Available The huge benefit of mobile application industry has attracted a large number of developers and attendant attackers. Application repackaging provides help for the distribution of most Android malware. It is a serious threat to the entire Android ecosystem, as it not only compromises the security and privacy of the app users but also plunders app developers’ income. Although massive approaches have been proposed to address this issue, plagiarists try to fight back through packing their malicious code with the help of commercial packers. Previous works either do not consider the packing issue or rely on time-consuming computations, which are not scalable for large-scale real-world scenario. In this paper, we propose FUIDroid, a novel two-phase app clones detection system that can detect the packed cloned app. FUIDroid includes a function-based fast selection phase to quickly select suspicious apps by analyzing apps’ description and a further UI-based accurate detection phase to refine the detection result. We evaluate our system on two sets of apps. The result from experiment on 320 packed samples demonstrates that FUIDroid is resilient to packed apps. The evaluation on more than 150,000 real-world apps shows the efficiency of FUIDroid in large-scale scenario.

  17. A paper based graphene-nanocauliflower hybrid composite for point of care biosensing

    Science.gov (United States)

    Burrs, S. L.; Sidhu, R.; Bhargava, M.; Kiernan-Lewis, J.; Schwalb, N.; Rong, Y.; Gomes, C.; Claussen, J.; Vanegas, D. C.; McLamore, E. S.

    2016-05-01

    Graphene paper has diverse applications in printed circuit board electronics, bioassays, 3D cell culture, and biosensing. Although development of nanometal-graphene hybrid composites is commonplace in the sensing literature, to date there are only a few examples of nanometal-decorated graphene paper for use in biosensing. In this manuscript, we demonstrate the synthesis and application of Pt nano cauliflower-functionalized graphene paper for use in electrochemical biosensing of small molecules (glucose, acetone, methanol) or detection of pathogenic bacteria (Escherichia coli O157:H7). Raman spectroscopy, scanning electron microscopy and energy dispersive spectroscopy were used to show that graphene oxide deposited on nanocellulose crystals was partially reduced by both thermal and chemical treatment. Fractal platinum nanostructures were formed on the reduced graphene oxide paper, producing a conductive paper with an extremely high electroactive surface area, confirmed by cyclic voltammetry and electrochemical impedance spectroscopy. To show the broad applicability of the material, the platinum surface was functionalized with three different biomaterials: 1) glucose oxidase (via chitosan encapsulation); 2) a DNA aptamer (via covalent linking), or 3) a chemosensory protein (via his linking). We demonstrate the application of this device for point of care biosensing. The detection limit for both glucose (0.08 +/- 0.02 μM) and E. coli O157:H7 (1.3 +/- 0.1 CFU mL-1) were competitive with, or superior to, previously reported devices in the biosensing literature. The response time (6 sec for glucose and 10 min for E. coli) were also similar to silicon biochip and commercial electrode sensors. The results demonstrate that the nanocellulose-graphene-nanoplatinum material is an excellent paper-based platform for development of electrochemical biosensors targeting small molecules or whole cells for use in point of care biosensing.

  18. Performances improvement of maximum power point tracking perturb and observe method

    Energy Technology Data Exchange (ETDEWEB)

    Egiziano, L.; Femia, N.; Granozio, D.; Petrone, G.; Spagnuolo, G. [Salermo Univ., Salermo (Italy); Vitelli, M. [Seconda Univ. di Napoli, Napoli (Italy)

    2006-07-01

    Perturb and observe best operation conditions were investigated in order to identify edge efficiency performance capabilities of a maximum power point (MPP) tracking technique for photovoltaic (PV) applications. The strategy was developed to ensure a 3-points behavior across the MPP under a fixed irradiation level with a central point blocked on the MPP and 2 operating points operating at voltage values that guaranteed the same power levels. The system was also devised to quickly detect the MPP movement in the presence of varying atmospheric conditions by increasing the perturbation so that the MPP was guaranteed within a few sampling periods. A perturbation equation was selected where amplitude was represented as a function of the actual power drawn from the PV field together with the adoption of a parabolic interpolation of the sequence of the final 3 acquired voltage power couples corresponding to as many operating points. The technique was developed to ensure that the power difference between 2 consecutive operating points was higher than the power quantization error. Simulations were conducted to demonstrate that the proposed technique arranged operating points symmetrically around the MPP. The average power of the 3-points set was achieved by means of the parabolic prediction. Experiments conducted to validate the simulation showed a reduced power oscillation below the MPP and a real power gain. 2 refs., 8 figs.

  19. Feedback dew-point sensor utilizing optimally cut plastic optical fibres

    Science.gov (United States)

    Hadjiloucas, S.; Irvine, J.; Keating, D. A.

    2000-01-01

    A plastic optical fibre reflectance sensor that makes full use of the critical angle of the fibres is implemented to monitor dew formation on a Peltier-cooled reflector surface. The optical configuration permits isolation of optoelectronic components from the sensing head and better light coupling between the reflector and the detecting fibre, giving a better signal of the onset of dew formation on the reflector. Continuous monitoring of the rate of change in reflectance as well as the absolute reflectance signals, the use of a novel polymethyl-methacrylate-coated hydrophobic film reflector on the Peltier element and the application of feedback around the point of dew formation, further reduces the possibility of contamination of the sensor head. Under closed-loop operation, the sensor is capable of cycling around the point of dew formation at a frequency of 2.5 Hz.

  20. A prototype pixel readout chip for asynchronous detection applications

    International Nuclear Information System (INIS)

    Raymond, D.M.; Hall, G.; Lewis, A.J.; Sharp, P.H.

    1991-01-01

    A two-dimensional array of amplifier cells has been fabricated as a prototype readout system for a matching array of silicon diode detectors. Each cell contains a preamplifier, shaping amplifier, comparator and analogue signal storage in an area of 300 μmx320 μm using 3 μm CMOS technology. Full size chips will be bump bonded to pixel detector arrays. Low noise and asynchronous operation are novel design features. With noise levels of less than 250 rms electrons for input capacitances up to 600 fF, pixel detectors will be suitable for autoradiography, synchrotron X-ray and high energy particle detection applications. The design of the prototype chip is presented and future developments and prospects for applications are discussed. (orig.)

  1. Detection of Azo Dyes in Curry Powder Using a 1064-nm Dispersive Point-Scan Raman System

    Directory of Open Access Journals (Sweden)

    Sagar Dhakal

    2018-04-01

    Full Text Available Curry powder is extensively used in Southeast Asian dishes. It has been subject to adulteration by azo dyes. This study used a newly developed 1064 nm dispersive point-scan Raman system for detection of metanil yellow and Sudan-I contamination in curry powder. Curry powder was mixed with metanil yellow and (separately with Sudan-I, at concentration levels of 1%, 3%, 5%, 7%, and 10% (w/w. Each sample was packed into a nickel-plated sample container (25 mm × 25 mm × 1 mm. One Raman spectral image of each sample was acquired across the 25 mm × 25 mm surface area. Intensity threshold value was applied to the spectral images of Sudan-I mixtures (at 1593 cm−1 and metanil yellow mixtures (at 1147 cm−1 to obtain binary detection images. The results show that the number of detected adulterant pixels is linearly correlated with the sample concentration (R2 = 0.99. The Raman system was further used to obtain a Raman spectral image of a curry powder sample mixed together with Sudan-I and metanil yellow, with each contaminant at equal concentration of 5% (w/w. The multi-component spectra of the mixture sample were decomposed using self-modeling mixture analysis (SMA to extract pure component spectra, which were then identified as matching those of Sudan-I and metanil yellow using spectral information divergence (SID values. The results show that the 1064 nm dispersive Raman system is a potential tool for rapid and nondestructive detection of multiple chemical contaminants in the complex food matrix.

  2. Entropy Measures for Stochastic Processes with Applications in Functional Anomaly Detection

    Directory of Open Access Journals (Sweden)

    Gabriel Martos

    2018-01-01

    Full Text Available We propose a definition of entropy for stochastic processes. We provide a reproducing kernel Hilbert space model to estimate entropy from a random sample of realizations of a stochastic process, namely functional data, and introduce two approaches to estimate minimum entropy sets. These sets are relevant to detect anomalous or outlier functional data. A numerical experiment illustrates the performance of the proposed method; in addition, we conduct an analysis of mortality rate curves as an interesting application in a real-data context to explore functional anomaly detection.

  3. Novel Quantitative Real-Time LCR for the Sensitive Detection of SNP Frequencies in Pooled DNA: Method Development, Evaluation and Application

    Science.gov (United States)

    Psifidi, Androniki; Dovas, Chrysostomos; Banos, Georgios

    2011-01-01

    Background Single nucleotide polymorphisms (SNP) have proven to be powerful genetic markers for genetic applications in medicine, life science and agriculture. A variety of methods exist for SNP detection but few can quantify SNP frequencies when the mutated DNA molecules correspond to a small fraction of the wild-type DNA. Furthermore, there is no generally accepted gold standard for SNP quantification, and, in general, currently applied methods give inconsistent results in selected cohorts. In the present study we sought to develop a novel method for accurate detection and quantification of SNP in DNA pooled samples. Methods The development and evaluation of a novel Ligase Chain Reaction (LCR) protocol that uses a DNA-specific fluorescent dye to allow quantitative real-time analysis is described. Different reaction components and thermocycling parameters affecting the efficiency and specificity of LCR were examined. Several protocols, including gap-LCR modifications, were evaluated using plasmid standard and genomic DNA pools. A protocol of choice was identified and applied for the quantification of a polymorphism at codon 136 of the ovine PRNP gene that is associated with susceptibility to a transmissible spongiform encephalopathy in sheep. Conclusions The real-time LCR protocol developed in the present study showed high sensitivity, accuracy, reproducibility and a wide dynamic range of SNP quantification in different DNA pools. The limits of detection and quantification of SNP frequencies were 0.085% and 0.35%, respectively. Significance The proposed real-time LCR protocol is applicable when sensitive detection and accurate quantification of low copy number mutations in DNA pools is needed. Examples include oncogenes and tumour suppressor genes, infectious diseases, pathogenic bacteria, fungal species, viral mutants, drug resistance resulting from point mutations, and genetically modified organisms in food. PMID:21283808

  4. Three-dimensional imaging of individual point defects using selective detection angles in annular dark field scanning transmission electron microscopy

    Energy Technology Data Exchange (ETDEWEB)

    Johnson, Jared M.; Im, Soohyun; Windl, Wolfgang; Hwang, Jinwoo, E-mail: hwang.458@osu.edu

    2017-01-15

    We propose a new scanning transmission electron microscopy (STEM) technique that can realize the three-dimensional (3D) characterization of vacancies, lighter and heavier dopants with high precision. Using multislice STEM imaging and diffraction simulations of β-Ga{sub 2}O{sub 3} and SrTiO{sub 3}, we show that selecting a small range of low scattering angles can make the contrast of the defect-containing atomic columns substantially more depth-dependent. The origin of the depth-dependence is the de-channeling of electrons due to the existence of a point defect in the atomic column, which creates extra “ripples” at low scattering angles. The highest contrast of the point defect can be achieved when the de-channeling signal is captured using the 20–40 mrad detection angle range. The effect of sample thickness, crystal orientation, local strain, probe convergence angle, and experimental uncertainty to the depth-dependent contrast of the point defect will also be discussed. The proposed technique therefore opens new possibilities for highly precise 3D structural characterization of individual point defects in functional materials. - Highlights: • A new electron microscopy technique that can visualize 3D position of point defect is proposed. • The technique relies on the electron de-channeling signals at low scattering angles. • The technique enables precise determination of the depth of vacancies and lighter impurity atoms.

  5. Contactless measurement of muscles fatigue by tracking facial feature points in a video

    DEFF Research Database (Denmark)

    Irani, Ramin; Nasrollahi, Kamal; Moeslund, Thomas B.

    2014-01-01

    their exercises when the level of the fatigue might be dangerous for the patients. The current technology for measuring tiredness, like Electromyography (EMG), requires installing some sensors on the body. In some applications, like remote patient monitoring, this however might not be possible. To deal...... with such cases, in this paper we present a contactless method based on computer vision techniques to measure tiredness by detecting, tracking, and analyzing some facial feature points during the exercise. Experimental results on several test subjects and comparing them against ground truth data show...... that the proposed system can properly find the temporal point of tiredness of the muscles when the test subjects are doing physical exercises....

  6. High precision target center determination from a point cloud

    Directory of Open Access Journals (Sweden)

    K. Kregar

    2013-10-01

    Full Text Available Many applications of terrestrial laser scanners (TLS require the determination of a specific point from a point cloud. In this paper procedure of high precision planar target center acquisition from point cloud is presented. The process is based on an image matching algorithm but before we can deal with raster image to fit a target on it, we need to properly determine the best fitting plane and project points on it. The main emphasis of this paper is in the precision estimation and propagation through the whole procedure which allows us to obtain precision assessment of final results (target center coordinates. Theoretic precision estimations – obtained through the procedure were rather high so we compared them with the empiric precision estimations obtained as standard deviations of results of 60 independently scanned targets. An χ2-test confirmed that theoretic precisions are overestimated. The problem most probably lies in the overestimated precisions of the plane parameters due to vast redundancy of points. However, empirical precisions also confirmed that the proposed procedure can ensure a submillimeter precision level. The algorithm can automatically detect grossly erroneous results to some extent. It can operate when the incidence angles of a laser beam are as high as 80°, which is desirable property if one is going to use planar targets as tie points in scan registration. The proposed algorithm will also contribute to improve TLS calibration procedures.

  7. A single FPGA-based portable ultrasound imaging system for point-of-care applications.

    Science.gov (United States)

    Kim, Gi-Duck; Yoon, Changhan; Kye, Sang-Bum; Lee, Youngbae; Kang, Jeeun; Yoo, Yangmo; Song, Tai-kyong

    2012-07-01

    We present a cost-effective portable ultrasound system based on a single field-programmable gate array (FPGA) for point-of-care applications. In the portable ultrasound system developed, all the ultrasound signal and image processing modules, including an effective 32-channel receive beamformer with pseudo-dynamic focusing, are embedded in an FPGA chip. For overall system control, a mobile processor running Linux at 667 MHz is used. The scan-converted ultrasound image data from the FPGA are directly transferred to the system controller via external direct memory access without a video processing unit. The potable ultrasound system developed can provide real-time B-mode imaging with a maximum frame rate of 30, and it has a battery life of approximately 1.5 h. These results indicate that the single FPGA-based portable ultrasound system developed is able to meet the processing requirements in medical ultrasound imaging while providing improved flexibility for adapting to emerging POC applications.

  8. Fast Image Edge Detection based on Faber Schauder Wavelet and Otsu Threshold

    Directory of Open Access Journals (Sweden)

    Assma Azeroual

    2017-12-01

    Full Text Available Edge detection is a critical stage in many computer vision systems, such as image segmentation and object detection. As it is difficult to detect image edges with precision and with low complexity, it is appropriate to find new methods for edge detection. In this paper, we take advantage of Faber Schauder Wavelet (FSW and Otsu threshold to detect edges in a multi-scale way with low complexity, since the extrema coefficients of this wavelet are located on edge points and contain only arithmetic operations. First, the image is smoothed using bilateral filter depending on noise estimation. Second, the FSW extrema coefficients are selected based on Otsu threshold. Finally, the edge points are linked using a predictive edge linking algorithm to get the image edges. The effectiveness of the proposed method is supported by the experimental results which prove that our method is faster than many competing state-of-the-art approaches and can be used in real-time applications.

  9. Acquisition, tracking, and pointing IV; Proceedings of the Meeting, Orlando, FL, Apr. 19, 20, 1990

    Science.gov (United States)

    Gowrinathan, Sankaran

    1990-09-01

    Various papers on acquisition, tracking, and pointing are presented. Individual topics addressed include: backlash control techniques in geared servo mechanics; optical fiber and photodetector array for robotic seam tracking; star trackers for spacecraft applications; Starfire optical range tracking system for the 1.5 m telescope; real-time video image centroid tracker; optical alignment with a beamwalk system; line-of-sight stabilization requirements for target tracking system; image quality with narrow beam illumination in an active tracking system; IR sensor data fusion for target detection, identification, and tracking; target location and pointing algorithm for a three-axis stabilized line scanner. Also discussed are: adaptive control system techniques applied to inertial stabilization systems; supervisory control of electrooptic tracking and pointing; position loop compensation for flex-pivot-mounted gimbal stabilization systems; advanced testing methods for acquisition, tracking, and pointing; development of kinmatics for gimballed mirror systems.

  10. Diagnostic accuracy of point shear wave elastography in the detection of portal hypertension in pediatric patients.

    Science.gov (United States)

    Burak Özkan, M; Bilgici, M C; Eren, E; Caltepe, G

    2018-03-01

    The purpose of this study was to determine the usefulness of point shear wave elastography (p-SWE) of the liver and spleen for the detection of portal hypertension in pediatric patients. The study consisted of 38 healthy children and 56 pediatric patients with biopsy-proven liver disease who underwent splenic and liver p-SWE. The diagnostic performance of p-SWE in detecting clinically significant portal hypertension was assessed using receiver operating characteristic (ROC) curves. Reliable measurements of splenic and liver stiffness with p-SWE were obtained in 76/94 (81%) and 80/94 patients (85%), respectively. The splenic stiffness was highest in the portal hypertension group (Pportal hypertension was lower for splenic p-SWE than for liver p-SWE (0.906 vs. 0.746; P=0.0239). The cut-off value of splenic p-SWE for portal hypertension was 3.14m/s, with a specificity of 98.59% and a sensitivity of 68.18%. The cut-off value of liver p-SWE for portal hypertension was 2.09m/s, with a specificity of 80.28% and a sensitivity of 77.27%. In pediatric patients, p-SWE is a reliable method for detecting portal hypertension. However, splenic p-SWE is less accurate than liver p-SWE for the diagnosis of portal hypertension. Copyright © 2017 Editions françaises de radiologie. Published by Elsevier Masson SAS. All rights reserved.

  11. Singularity detection by wavelet approach: application to electrocardiogram signal

    Science.gov (United States)

    Jalil, Bushra; Beya, Ouadi; Fauvet, Eric; Laligant, Olivier

    2010-01-01

    In signal processing, the region of abrupt changes contains the most of the useful information about the nature of the signal. The region or the points where these changes occurred are often termed as singular point or singular region. The singularity is considered to be an important character of the signal, as it refers to the discontinuity and interruption present in the signal and the main purpose of the detection of such singular point is to identify the existence, location and size of those singularities. Electrocardiogram (ECG) signal is used to analyze the cardiovascular activity in the human body. However the presence of noise due to several reasons limits the doctor's decision and prevents accurate identification of different pathologies. In this work we attempt to analyze the ECG signal with energy based approach and some heuristic methods to segment and identify different signatures inside the signal. ECG signal has been initially denoised by empirical wavelet shrinkage approach based on Steins Unbiased Risk Estimate (SURE). At the second stage, the ECG signal has been analyzed by Mallat approach based on modulus maximas and Lipschitz exponent computation. The results from both approaches has been discussed and important aspects has been highlighted. In order to evaluate the algorithm, the analysis has been done on MIT-BIH Arrhythmia database; a set of ECG data records sampled at a rate of 360 Hz with 11 bit resolution over a 10mv range. The results have been examined and approved by medical doctors.

  12. Surface plasmon resonance biosensors for highly sensitive detection in real samples

    Science.gov (United States)

    Sepúlveda, B.; Carrascosa, L. G.; Regatos, D.; Otte, M. A.; Fariña, D.; Lechuga, L. M.

    2009-08-01

    In this work we summarize the main results obtained with the portable surface plasmon resonance (SPR) device developed in our group (commercialised by SENSIA, SL, Spain), highlighting its applicability for the real-time detection of extremely low concentrations of toxic pesticides in environmental water samples. In addition, we show applications in clinical diagnosis as, on the one hand, the real-time and label-free detection of DNA hybridization and single point mutations at the gene BRCA-1, related to the predisposition in women to develop an inherited breast cancer and, on the other hand, the analysis of protein biomarkers in biological samples (urine, serum) for early detection of diseases. Despite the large number of applications already proven, the SPR technology has two main drawbacks: (i) not enough sensitivity for some specific applications (where pM-fM or single-molecule detection are needed) (ii) low multiplexing capabilities. In order solve such drawbacks, we work in several alternative configurations as the Magneto-optical Surface Plasmon Resonance sensor (MOSPR) based on a combination of magnetooptical and ferromagnetic materials, to improve the SPR sensitivity, or the Localized Surface Plasmon Resonance (LSPR) based on nanostructures (nanoparticles, nanoholes,...), for higher multiplexing capabilities.

  13. EFFECTIVE DETECTION OF SUB-SURFACE ARCHEOLOGICAL FEATURES FROM LASER SCANNING POINT CLOUDS AND IMAGERY DATA

    Directory of Open Access Journals (Sweden)

    A. Fryskowska

    2017-08-01

    Full Text Available The archaeological heritage is non-renewable, and any invasive research or other actions leading to the intervention of mechanical or chemical into the ground lead to the destruction of the archaeological site in whole or in part. For this reason, modern archeology is looking for alternative methods of non-destructive and non-invasive methods of new objects identification. The concept of aerial archeology is relation between the presence of the archaeological site in the particular localization, and the phenomena that in the same place can be observed on the terrain surface form airborne platform. One of the most appreciated, moreover, extremely precise, methods of such measurements is airborne laser scanning. In research airborne laser scanning point cloud with a density of 5 points/sq. m was used. Additionally unmanned aerial vehicle imagery data was acquired. Test area is located in central Europe. The preliminary verification of potentially microstructures localization was the creation of digital terrain and surface models. These models gave an information about the differences in elevation, as well as regular shapes and sizes that can be related to the former settlement/sub-surface feature. The paper presents the results of the detection of potentially sub-surface microstructure fields in the forestry area.

  14. Effective Detection of Sub-Surface Archeological Features from Laser Scanning Point Clouds and Imagery Data

    Science.gov (United States)

    Fryskowska, A.; Kedzierski, M.; Walczykowski, P.; Wierzbicki, D.; Delis, P.; Lada, A.

    2017-08-01

    The archaeological heritage is non-renewable, and any invasive research or other actions leading to the intervention of mechanical or chemical into the ground lead to the destruction of the archaeological site in whole or in part. For this reason, modern archeology is looking for alternative methods of non-destructive and non-invasive methods of new objects identification. The concept of aerial archeology is relation between the presence of the archaeological site in the particular localization, and the phenomena that in the same place can be observed on the terrain surface form airborne platform. One of the most appreciated, moreover, extremely precise, methods of such measurements is airborne laser scanning. In research airborne laser scanning point cloud with a density of 5 points/sq. m was used. Additionally unmanned aerial vehicle imagery data was acquired. Test area is located in central Europe. The preliminary verification of potentially microstructures localization was the creation of digital terrain and surface models. These models gave an information about the differences in elevation, as well as regular shapes and sizes that can be related to the former settlement/sub-surface feature. The paper presents the results of the detection of potentially sub-surface microstructure fields in the forestry area.

  15. Optimal Power Flow by Interior Point and Non Interior Point Modern Optimization Algorithms

    Directory of Open Access Journals (Sweden)

    Marcin Połomski

    2013-03-01

    Full Text Available The idea of optimal power flow (OPF is to determine the optimal settings for control variables while respecting various constraints, and in general it is related to power system operational and planning optimization problems. A vast number of optimization methods have been applied to solve the OPF problem, but their performance is highly dependent on the size of a power system being optimized. The development of the OPF recently has tracked significant progress both in numerical optimization techniques and computer techniques application. In recent years, application of interior point methods to solve OPF problem has been paid great attention. This is due to the fact that IP methods are among the fastest algorithms, well suited to solve large-scale nonlinear optimization problems. This paper presents the primal-dual interior point method based optimal power flow algorithm and new variant of the non interior point method algorithm with application to optimal power flow problem. Described algorithms were implemented in custom software. The experiments show the usefulness of computational software and implemented algorithms for solving the optimal power flow problem, including the system model sizes comparable to the size of the National Power System.

  16. Feasibility study on RI biochip Application to detection of risk factors of atherosclerosis

    International Nuclear Information System (INIS)

    Ko, Kyong Cheol; Choi, Mi Hee; Park, Sang Hyun; Cho, Kyung Hyun; Lee, Ki Teak

    2009-01-01

    Microarrays can be used to screen thousands of binding events in a parallel and high throughput fashion and are of major importance in discase diagnosis and drug discovery. The use of radioisotope is conventionally regarded as one of the most sensitive detection methods. Atherosclerosis is a common disorder affecting arterial blood vessels. It happens when fat, cholesterol, and other substances made in the arterial blood vessels form a hard substances called plaque. Lipoprotein-associated phospholipase A 2 (Lp-PLA 2 ), a phospholipase A 2 enzyme, is used as a marker for cardiac disease. The detection of Lp-PLA 2 was accomplished by using radioactive [ 3 H-acetyl] PAF as a substrate and a feasibility study on RI biochip application to detection of Lp-PLA 2 , a risk factors of atherosclerosis was performed. Inhibitive activity of a native plant extract was also determined by using the RI biochip. It was found to be applicable to a high-throughput screening of inhibitors for developing atherosclerosis therapeutic agents

  17. X-spectrographic method for plutonium detection. Application to contamination measurements in humans; Etude d'une methode de detection du plutonium par spectrographie X. Application a la mesure des contaminations sur l'homme

    Energy Technology Data Exchange (ETDEWEB)

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

    1967-07-01

    After reviewing the radio-toxicology of plutonium 239 and conventional detection methods using its {alpha}-radiation, the author considers the measurement of the X emission spectrum of plutonium 239 using a proportional counter filled with argon under pressure. This preliminary work leads to the third part of this research involving the detailed study of the possibilities of applying thin alkali halide crystal scintillators to the detection of soft plutonium X-rays; there follows a systematic study of all the parameters liable to render the detection as sensitive as possible: movement due to the photomultiplier itself and its accessory electronic equipment, nature and size of the crystal scintillator as well as its mode of preparation, shielding against external parasitic radiation. Examples of some applications to the measurement of contamination in humans give an idea of the sensitivity of this method. (author) [French] Apres un apercu de la radiotoxicologie du plutonium 239 et des methodes classiques de detection par son rayonnement {alpha}, on etudie le spectre d'emission X du plutonium 239 avec un compteur proportionnel rempli avec de l'argon sous pression. Ce travail preliminaire permet d'aborder la troisieme partie de cette etude dans laquelle nous examinons d'une fagon approfondie les possibilites d'application des cristaux scintillateurs minces d'halogenure alcalin a la detection du rayonnement X mou du plutonium; suit une etude systematique de tous les parametres susceptibles de rendre la detection aussi sensible que possible: mouvement propre du photomultiplicateur et de l'electronique associee, nature et dimensions du cristal scintillateur ainsi que son mode de fabrication, blindage contre les rayonnements parasites exterieurs. Quelques applications a la mesure des contaminations sur l'homme permettent d'apprecier la sensibilite de cette methode. (auteur)

  18. Geometric Edge Description and Classification in Point Cloud Data with Application to 3D Object Recognition

    DEFF Research Database (Denmark)

    Jørgensen, Troels Bo; Buch, Anders Glent; Kraft, Dirk

    2015-01-01

    descriptor allows for both fast computation and fast processing by having a low dimension, while still producing highly reliable edge detections. Lastly, we use our features in a 3D object recognition application using a well-established benchmark. We show that our edge features allow for significant...

  19. Application of SVM classifier in thermographic image classification for early detection of breast cancer

    Science.gov (United States)

    Oleszkiewicz, Witold; Cichosz, Paweł; Jagodziński, Dariusz; Matysiewicz, Mateusz; Neumann, Łukasz; Nowak, Robert M.; Okuniewski, Rafał

    2016-09-01

    This article presents the application of machine learning algorithms for early detection of breast cancer on the basis of thermographic images. Supervised learning model: Support vector machine (SVM) and Sequential Minimal Optimization algorithm (SMO) for the training of SVM classifier were implemented. The SVM classifier was included in a client-server application which enables to create a training set of examinations and to apply classifiers (including SVM) for the diagnosis and early detection of the breast cancer. The sensitivity and specificity of SVM classifier were calculated based on the thermographic images from studies. Furthermore, the heuristic method for SVM's parameters tuning was proposed.

  20. Detection of the Security Vulnerabilities in Web Applications

    Directory of Open Access Journals (Sweden)

    2009-01-01

    Full Text Available The contemporary organizations develop business processes in a very complex environment. The IT&C technologies are used by organizations to improve their competitive advantages. But, the IT&C technologies are not perfect. They are developed in an iterative process and their quality is the result of the lifecycle activities. The audit and evaluation processes are required by the increased complexity of the business processes supported by IT&C technologies. In order to organize and develop a high-quality audit process, the evaluation team must analyze the risks, threats and vulnerabilities of the information system. The paper highlights the security vulnerabilities in web applications and the processes of their detection. The web applications are used as IT&C tools to support the distributed information processes. They are a major component of the distributed information systems. The audit and evaluation processes are carried out in accordance with the international standards developed for information system security assurance.

  1. 20 CFR 670.480 - At what point is an applicant considered to be enrolled in Job Corps?

    Science.gov (United States)

    2010-04-01

    ... 20 Employees' Benefits 3 2010-04-01 2010-04-01 false At what point is an applicant considered to be enrolled in Job Corps? 670.480 Section 670.480 Employees' Benefits EMPLOYMENT AND TRAINING ADMINISTRATION, DEPARTMENT OF LABOR THE JOB CORPS UNDER TITLE I OF THE WORKFORCE INVESTMENT ACT Recruitment...

  2. Synthesis of cysteamine-coated CdTe quantum dots and its application in mercury (II) detection

    Energy Technology Data Exchange (ETDEWEB)

    Pei Jiying [State Key Laboratory of Electroanalytical Chemistry, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun 130022 (China); Department of Chemistry, University of Science and Technology of China (USTC), Hefei 230026 (China); Zhu Hui; Wang Xiaolei [State Key Laboratory of Electroanalytical Chemistry, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun 130022 (China); Zhang Hanchang [Department of Chemistry, University of Science and Technology of China (USTC), Hefei 230026 (China); Yang Xiurong, E-mail: xryang@ciac.jl.cn [State Key Laboratory of Electroanalytical Chemistry, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun 130022 (China)

    2012-12-13

    Highlights: Black-Right-Pointing-Pointer High-quality CA-CdTe QDs were synthesized with a kinetic-growth strategy. Black-Right-Pointing-Pointer The synthesis procedures were very simple. Black-Right-Pointing-Pointer The obtained QDs were used to detect Hg{sup 2+} without the interference of Cu{sup 2+}. - Abstract: High-quality cysteamine-coated CdTe quantum dots (CA-CdTe QDs) were successfully synthesized in aqueous phase by a facile one-pot method. Through hydroxylamine hydrochloride-promoted kinetic growth strategy, water-soluble CA-CdTe QDs could be obtained conveniently in a conical flask by a stepwise addition of raw materials. The photoluminescence quantum yield (PL QY) of the obtained QDs reached 9.2% at the emission peak of 520 nm. The optical property and the morphology of the QDs were characterized by UV-vis absorption spectra, photoluminescence spectra (PL) and transmission electron microscopy (TEM) respectively. Furthermore, the fluorescence of the resultant QDs was quenched by copper (II) (Cu{sup 2+}) and mercury (II) (Hg{sup 2+}) meanwhile. It is worthy of note that to separately detect Hg{sup 2+}, cyanide ion could be used to eliminate the interference of Cu{sup 2+}. Under the optimal conditions, the response was linearly proportional to the logarithm of Hg{sup 2+} concentration over the range of 0.08-3.33 {mu}M with a limit of detection (LOD) of 0.07 {mu}M.

  3. A hardware-algorithm co-design approach to optimize seizure detection algorithms for implantable applications.

    Science.gov (United States)

    Raghunathan, Shriram; Gupta, Sumeet K; Markandeya, Himanshu S; Roy, Kaushik; Irazoqui, Pedro P

    2010-10-30

    Implantable neural prostheses that deliver focal electrical stimulation upon demand are rapidly emerging as an alternate therapy for roughly a third of the epileptic patient population that is medically refractory. Seizure detection algorithms enable feedback mechanisms to provide focally and temporally specific intervention. Real-time feasibility and computational complexity often limit most reported detection algorithms to implementations using computers for bedside monitoring or external devices communicating with the implanted electrodes. A comparison of algorithms based on detection efficacy does not present a complete picture of the feasibility of the algorithm with limited computational power, as is the case with most battery-powered applications. We present a two-dimensional design optimization approach that takes into account both detection efficacy and hardware cost in evaluating algorithms for their feasibility in an implantable application. Detection features are first compared for their ability to detect electrographic seizures from micro-electrode data recorded from kainate-treated rats. Circuit models are then used to estimate the dynamic and leakage power consumption of the compared features. A score is assigned based on detection efficacy and the hardware cost for each of the features, then plotted on a two-dimensional design space. An optimal combination of compared features is used to construct an algorithm that provides maximal detection efficacy per unit hardware cost. The methods presented in this paper would facilitate the development of a common platform to benchmark seizure detection algorithms for comparison and feasibility analysis in the next generation of implantable neuroprosthetic devices to treat epilepsy. Copyright © 2010 Elsevier B.V. All rights reserved.

  4. Detection principles of biological and chemical FET sensors.

    Science.gov (United States)

    Kaisti, Matti

    2017-12-15

    The seminal importance of detecting ions and molecules for point-of-care tests has driven the search for more sensitive, specific, and robust sensors. Electronic detection holds promise for future miniaturized in-situ applications and can be integrated into existing electronic manufacturing processes and technology. The resulting small devices will be inherently well suited for multiplexed and parallel detection. In this review, different field-effect transistor (FET) structures and detection principles are discussed, including label-free and indirect detection mechanisms. The fundamental detection principle governing every potentiometric sensor is introduced, and different state-of-the-art FET sensor structures are reviewed. This is followed by an analysis of electrolyte interfaces and their influence on sensor operation. Finally, the fundamentals of different detection mechanisms are reviewed and some detection schemes are discussed. In the conclusion, current commercial efforts are briefly considered. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

  5. SharePoint 2010 Business Intelligence 24-Hour Trainer

    CERN Document Server

    Jorgensen, Adam; Knight, Devin; LeBlanc, Patrick; Schacht, Brad

    2011-01-01

    Learn to build and deliver SharePoint BI applications Written by a team of leading SharePoint and Business Intelligence (BI) experts, this unique book-and-DVD package shows you how to successfully build and deliver BI applications using SharePoint 2010. Assuming no previous SharePoint experience, the authors deliver a clear explanation of what SharePoint will do for your BI and information management capabilities. Each lesson in the book is reinforced with a helpful tutorial on the DVD and cover topics such as interactive reporting with Excel, document sharing for collaborative reporting, and

  6. Solid state nuclear track detection : theory and applications

    International Nuclear Information System (INIS)

    Bhagwat, A.M.

    1993-01-01

    Solid state nuclear track detection (SSNTD) technique is simple and inexpensive in nature. The two main steps involved in SSNTD are the formation of latent tracks and their subsequent development (visualisation) by chemical or other means. These are discussed in detail. Applications of SSNTD in the fields of nuclear physics, dosimetry, biology and for determination of contents of an element and its spatial distribution are described. The monograph is intended to serve both beginners and specialists. It also gives a list of simple experiments that can be conveniently introduced at the undergraduate/postgraduate level. (M.G.B.). 20 refs., 8 figs., 3 tabs

  7. Theory of inner product vector and its application to multi-location damage detection

    International Nuclear Information System (INIS)

    Wang Le; Yang Zhichun; Zhang Muyu; Waters, T P

    2011-01-01

    Structural damage detection methods using time domain vibration responses have shown appeal in recent years. In previous papers by the authors, the inner product vector (IPV) was proposed as a damage detection algorithm which uses cross correlation functions between vibration responses under white noise excitation or band pass white noise excitation. The proposed algorithm was verified by some simulative and experimental examples featuring a single damage location. However, damage at multiple locations was not considered. Therefore, this paper extends the application of IPV-based structural damage detection to the problem of multiple damage locations. Firstly, the theory of the IPV and its implementation in a damage detection context is reviewed. Then, two strategies for detecting multiple damages utilizing IPV are proposed. Finally, a damage detection experiment of a honeycomb sandwich composite beam is adopted to illustrate the feasibility and effectiveness of the IPV-based damage detection method.

  8. Reactor coolant flow measurements at Point Lepreau

    International Nuclear Information System (INIS)

    Brenciaglia, G.; Gurevich, Y.; Liu, G.

    1996-01-01

    The CROSSFLOW ultrasonic flow measurement system manufactured by AMAG is fully proven as reliable and accurate when applied to large piping in defined geometries for such applications as feedwater flows measurement. Its application to direct reactor coolant flow (RCF) measurements - both individual channel flows and bulk flows such as pump suction flow - has been well established through recent work by AMAG at Point Lepreau, with application to other reactor types (eg. PWR) imminent. At Point Lepreau, Measurements have been demonstrated at full power; improvements to consistently meet ±1% accuracy are in progress. The development and recent customization of CROSSFLOW to RCF measurement at Point Lepreau are described in this paper; typical measurement results are included. (author)

  9. Wireless LAN security management with location detection capability in hospitals.

    Science.gov (United States)

    Tanaka, K; Atarashi, H; Yamaguchi, I; Watanabe, H; Yamamoto, R; Ohe, K

    2012-01-01

    In medical institutions, unauthorized access points and terminals obstruct the stable operation of a large-scale wireless local area network (LAN) system. By establishing a real-time monitoring method to detect such unauthorized wireless devices, we can improve the efficiency of security management. We detected unauthorized wireless devices by using a centralized wireless LAN system and a location detection system at 370 access points at the University of Tokyo Hospital. By storing the detected radio signal strength and location information in a database, we evaluated the risk level from the detection history. We also evaluated the location detection performance in our hospital ward using Wi-Fi tags. The presence of electric waves outside the hospital and those emitted from portable game machines with wireless communication capability was confirmed from the detection result. The location detection performance showed an error margin of approximately 4 m in detection accuracy and approximately 5% in false detection. Therefore, it was effective to consider the radio signal strength as both an index of likelihood at the detection location and an index for the level of risk. We determined the location of wireless devices with high accuracy by filtering the detection results on the basis of radio signal strength and detection history. Results of this study showed that it would be effective to use the developed location database containing radio signal strength and detection history for security management of wireless LAN systems and more general-purpose location detection applications.

  10. Application of signal detection theory to optics. [image evaluation and restoration

    Science.gov (United States)

    Helstrom, C. W.

    1973-01-01

    Basic quantum detection and estimation theory, applications to optics, photon counting, and filtering theory are studied. Recent work on the restoration of degraded optical images received at photoelectrically emissive surfaces is also reported, the data used by the method are the numbers of electrons ejected from various parts of the surface.

  11. Beginning SharePoint Designer 2010

    CERN Document Server

    Windischman, Woodrow W; Rehmani, Asif

    2010-01-01

    Teaching Web designers, developers, and IT professionals how to use the new version of SharePoint Designer. Covering both the design and business applications of SharePoint Designer, this complete Wrox guide brings readers thoroughly up to speed on how to use SharePoint Designer in an enterprise. You'll learn to create and modify web pages, use CSS editing tools to modify themes, use Data View to create interactivity with SharePoint and other data, and much more. Coverage includes integration points with Visual Studio, Visio, and InfoPath.: Shows web designers, developers, and IT professionals

  12. Application of SVM on satellite images to detect hotspots in Jharia coal field region of India

    Energy Technology Data Exchange (ETDEWEB)

    Gautam, R.S.; Singh, D.; Mittal, A.; Sajin, P. [Indian Institute for Technology, Roorkee (India)

    2008-07-01

    The present paper deals with the application of Support Vector Machine (SVM) and image analysis techniques on NOAA/AVHRR satellite image to detect hotspots on the Jharia coal field region of India. One of the major advantages of using these satellite data is that the data are free with very good temporal resolution; while, one drawback is that these have low spatial resolution (i.e., approximately 1.1 km at nadir). Therefore, it is important to do research by applying some efficient optimization techniques along with the image analysis techniques to rectify these drawbacks and use satellite images for efficient hotspot detection and monitoring. For this purpose, SVM and multi-threshold techniques are explored for hotspot detection. The multi-threshold algorithm is developed to remove the cloud coverage from the land coverage. This algorithm also highlights the hotspots or fire spots in the suspected regions. SVM has the advantage over multi-thresholding technique that it can learn patterns from the examples and therefore is used to optimize the performance by removing the false points which are highlighted in the threshold technique. Both approaches can be used separately or in combination depending on the size of the image. The RBF (Radial Basis Function) kernel is used in training of three sets of inputs: brightness temperature of channel 3, Normalized Difference Vegetation Index (NDVI) and Global Environment Monitoring Index (GEMI), respectively. This makes a classified image in the output that highlights the hotspot and non-hotspot pixels. The performance of the SVM is also compared with the performance obtained from the neural networks and SVM appears to detect hotspots more accurately (greater than 91% classification accuracy) with lesser false alarm rate. The results obtained are found to be in good agreement with the ground based observations of the hotspots.

  13. Dynamic social community detection and its applications.

    Directory of Open Access Journals (Sweden)

    Nam P Nguyen

    Full Text Available Community structure is one of the most commonly observed features of Online Social Networks (OSNs in reality. The knowledge of this feature is of great advantage: it not only provides helpful insights into developing more efficient social-aware solutions but also promises a wide range of applications enabled by social and mobile networking, such as routing strategies in Mobile Ad Hoc Networks (MANETs and worm containment in OSNs. Unfortunately, understanding this structure is very challenging, especially in dynamic social networks where social interactions are evolving rapidly. Our work focuses on the following questions: How can we efficiently identify communities in dynamic social networks? How can we adaptively update the network community structure based on its history instead of recomputing from scratch? To this end, we present Quick Community Adaptation (QCA, an adaptive modularity-based framework for not only discovering but also tracing the evolution of network communities in dynamic OSNs. QCA is very fast and efficient in the sense that it adaptively updates and discovers the new community structure based on its history together with the network changes only. This flexible approach makes QCA an ideal framework applicable for analyzing large-scale dynamic social networks due to its lightweight computing-resource requirement. To illustrate the effectiveness of our framework, we extensively test QCA on both synthesized and real-world social networks including Enron, arXiv e-print citation, and Facebook networks. Finally, we demonstrate the applicability of QCA in real applications: (1 A social-aware message forwarding strategy in MANETs, and (2 worm propagation containment in OSNs. Competitive results in comparison with other methods reveal that social-based techniques employing QCA as a community detection core outperform current available methods.

  14. Dynamic social community detection and its applications.

    Science.gov (United States)

    Nguyen, Nam P; Dinh, Thang N; Shen, Yilin; Thai, My T

    2014-01-01

    Community structure is one of the most commonly observed features of Online Social Networks (OSNs) in reality. The knowledge of this feature is of great advantage: it not only provides helpful insights into developing more efficient social-aware solutions but also promises a wide range of applications enabled by social and mobile networking, such as routing strategies in Mobile Ad Hoc Networks (MANETs) and worm containment in OSNs. Unfortunately, understanding this structure is very challenging, especially in dynamic social networks where social interactions are evolving rapidly. Our work focuses on the following questions: How can we efficiently identify communities in dynamic social networks? How can we adaptively update the network community structure based on its history instead of recomputing from scratch? To this end, we present Quick Community Adaptation (QCA), an adaptive modularity-based framework for not only discovering but also tracing the evolution of network communities in dynamic OSNs. QCA is very fast and efficient in the sense that it adaptively updates and discovers the new community structure based on its history together with the network changes only. This flexible approach makes QCA an ideal framework applicable for analyzing large-scale dynamic social networks due to its lightweight computing-resource requirement. To illustrate the effectiveness of our framework, we extensively test QCA on both synthesized and real-world social networks including Enron, arXiv e-print citation, and Facebook networks. Finally, we demonstrate the applicability of QCA in real applications: (1) A social-aware message forwarding strategy in MANETs, and (2) worm propagation containment in OSNs. Competitive results in comparison with other methods reveal that social-based techniques employing QCA as a community detection core outperform current available methods.

  15. Aircraft applications of fault detection and isolation techniques

    Science.gov (United States)

    Marcos Esteban, Andres

    In this thesis the problems of fault detection & isolation and fault tolerant systems are studied from the perspective of LTI frequency-domain, model-based techniques. Emphasis is placed on the applicability of these LTI techniques to nonlinear models, especially to aerospace systems. Two applications of Hinfinity LTI fault diagnosis are given using an open-loop (no controller) design approach: one for the longitudinal motion of a Boeing 747-100/200 aircraft, the other for a turbofan jet engine. An algorithm formalizing a robust identification approach based on model validation ideas is also given and applied to the previous jet engine. A general linear fractional transformation formulation is given in terms of the Youla and Dual Youla parameterizations for the integrated (control and diagnosis filter) approach. This formulation provides better insight into the trade-off between the control and the diagnosis objectives. It also provides the basic groundwork towards the development of nested schemes for the integrated approach. These nested structures allow iterative improvements on the control/filter Youla parameters based on successive identification of the system uncertainty (as given by the Dual Youla parameter). The thesis concludes with an application of Hinfinity LTI techniques to the integrated design for the longitudinal motion of the previous Boeing 747-100/200 model.

  16. A fixed-point farrago

    CERN Document Server

    Shapiro, Joel H

    2016-01-01

    This text provides an introduction to some of the best-known fixed-point theorems, with an emphasis on their interactions with topics in analysis. The level of exposition increases gradually throughout the book, building from a basic requirement of undergraduate proficiency to graduate-level sophistication. Appendices provide an introduction to (or refresher on) some of the prerequisite material and exercises are integrated into the text, contributing to the volume’s ability to be used as a self-contained text. Readers will find the presentation especially useful for independent study or as a supplement to a graduate course in fixed-point theory. The material is split into four parts: the first introduces the Banach Contraction-Mapping Principle and the Brouwer Fixed-Point Theorem, along with a selection of interesting applications; the second focuses on Brouwer’s theorem and its application to John Nash’s work; the third applies Brouwer’s theorem to spaces of infinite dimension; and the fourth rests ...

  17. DISCRETE FIXED POINT THEOREMS AND THEIR APPLICATION TO NASH EQUILIBRIUM

    OpenAIRE

    Sato, Junichi; Kawasaki, Hidefumi

    2007-01-01

    Fixed point theorems are powerful tools in not only mathematics but also economic. In some economic problems, we need not real-valued but integer-valued equilibriums. However, classical fixed point theorems guarantee only real-valued equilibria. So we need discrete fixed point theorems in order to get discrete equilibria. In this paper, we first provide discrete fixed point theorems, next apply them to a non-cooperative game and prove the existence of a Nash equilibrium of pure strategies.

  18. Detection activity assessment and diagnosis of dental caries lesions

    DEFF Research Database (Denmark)

    Braga, Mariana M; Mendes, Fausto M; Ekstrand, Kim R

    2010-01-01

    This article reviews the current methods for detection and assessment of caries lesions focusing on applicability for daily clinical practice. The end point is to arrive at a diagnosis for each caries lesion. Visual inspection aided by a ball-ended probe is essential for caries lesions assessment...... and the method must be used for all patients. Use of indices, for example, the International Caries Detection and Assessment System (ICDAS), can improve the performance of this method. Using visual inspection, the clinician must decide about the presence, severity and activity of lesions. After this process...

  19. Designs, formats and applications of lateral flow assay: A literature review

    Directory of Open Access Journals (Sweden)

    Muhammad Sajid

    2015-11-01

    Full Text Available This manuscript provides a brief overview of latest research involving the use of lateral flow assay for qualitative and quantitative analysis in different areas. The excellent features and versatility of detection formats make these strips an ideal choice for point of care applications. We outline and critically discuss detection formats, molecular recognition probes, labels, and detection systems used in lateral flow assay. Applications in different fields along with selected examples from the literature have been included to show analytical performance of these devices. At the end, we summarize accomplishments, weaknesses and future challenges in the area of lateral flow strips.

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

    Science.gov (United States)

    He, K.; Zhu, W. D.

    2011-07-01

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

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

    International Nuclear Information System (INIS)

    He, K; Zhu, W D

    2011-01-01

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

  2. A flexible mobile-device biosensing instrumentation platform for point-of-care medical diagnostics applications

    DEFF Research Database (Denmark)

    Patou, François; Pfreundt, Andrea; Zulfiqar, Azeem

    2014-01-01

    helping to address this challenge. Specifically, Lab-on-Chip (LoC) devices have a key role to play in the advent of Point-of-Care (PoC) medical applications, driving a shift of the medical diagnostics paradigm and the transition from a centralized, technical, high-throughput biological sample analysis...... programmable electrical readout from LoCs potentially comprehending varied transducers addressing different targeted biological markers. A smart-phone/tablet docking-station embeds the hardware interface necessary for the implementation of a smart-phone digital lock-in amplifier. The platform is tested...

  3. Detection of flow separation and stagnation points using artificial hair sensors

    International Nuclear Information System (INIS)

    Phillips, D M; Baur, J W; Ray, C W; Hagen, B J; Reich, G W; Su, W

    2015-01-01

    Recent interest in fly-by-feel approaches for aircraft control has motivated the development of novel sensors for use in aerial systems. Artificial hair sensors (AHSs) are one type of device that promise to fill a unique niche in the sensory suite for aerial systems. In this work, we investigate the capability of an AHS based on structural glass fibers to directly identify flow stagnation and separation points on a cylindrical domain in a steady flow. The glass fibers are functionalized with a radially aligned carbon nanotube (CNT) forest and elicit a piezoresistive response as the CNT forest impinges on electrodes in a micropore when the hair is deflected due to viscous drag forces. Particle image velocimetry is used to measure the flow field allowing for the resulting moment and force acting on the hair to be correlated with the electrical response. It is demonstrated that the AHS provides estimates for the locations of both the stagnation and separation in steady flow. From this, a simulation of a heading estimation is presented to demonstrate a potential application for hair sensors. These results motivate the construction of large arrays of hair sensors for imaging and resolving flow structures in real time. (paper)

  4. Detection of progression of glaucomatous visual field damage using the point-wise method with the binomial test.

    Science.gov (United States)

    Karakawa, Ayako; Murata, Hiroshi; Hirasawa, Hiroyo; Mayama, Chihiro; Asaoka, Ryo

    2013-01-01

    To compare the performance of newly proposed point-wise linear regression (PLR) with the binomial test (binomial PLR) against mean deviation (MD) trend analysis and permutation analyses of PLR (PoPLR), in detecting global visual field (VF) progression in glaucoma. 15 VFs (Humphrey Field Analyzer, SITA standard, 24-2) were collected from 96 eyes of 59 open angle glaucoma patients (6.0 ± 1.5 [mean ± standard deviation] years). Using the total deviation of each point on the 2(nd) to 16(th) VFs (VF2-16), linear regression analysis was carried out. The numbers of VF test points with a significant trend at various probability levels (pbinomial test (one-side). A VF series was defined as "significant" if the median p-value from the binomial test was binomial PLR method (0.14 to 0.86) was significantly higher than MD trend analysis (0.04 to 0.89) and PoPLR (0.09 to 0.93). The PIS of the proposed method (0.0 to 0.17) was significantly lower than the MD approach (0.0 to 0.67) and PoPLR (0.07 to 0.33). The PBNS of the three approaches were not significantly different. The binomial BLR method gives more consistent results than MD trend analysis and PoPLR, hence it will be helpful as a tool to 'flag' possible VF deterioration.

  5. Automating quantum dot barcode assays using microfluidics and magnetism for the development of a point-of-care device.

    Science.gov (United States)

    Gao, Yali; Lam, Albert W Y; Chan, Warren C W

    2013-04-24

    The impact of detecting multiple infectious diseases simultaneously at point-of-care with good sensitivity, specificity, and reproducibility would be enormous for containing the spread of diseases in both resource-limited and rich countries. Many barcoding technologies have been introduced for addressing this need as barcodes can be applied to detecting thousands of genetic and protein biomarkers simultaneously. However, the assay process is not automated and is tedious and requires skilled technicians. Barcoding technology is currently limited to use in resource-rich settings. Here we used magnetism and microfluidics technology to automate the multiple steps in a quantum dot barcode assay. The quantum dot-barcoded microbeads are sequentially (a) introduced into the chip, (b) magnetically moved to a stream containing target molecules, (c) moved back to the original stream containing secondary probes, (d) washed, and (e) finally aligned for detection. The assay requires 20 min, has a limit of detection of 1.2 nM, and can detect genetic targets for HIV, hepatitis B, and syphilis. This study provides a simple strategy to automate the entire barcode assay process and moves barcoding technologies one step closer to point-of-care applications.

  6. Exceptional points enhance sensing in an optical microcavity

    Science.gov (United States)

    Chen, Weijian; Kaya Özdemir, Şahin; Zhao, Guangming; Wiersig, Jan; Yang, Lan

    2017-08-01

    Sensors play an important part in many aspects of daily life such as infrared sensors in home security systems, particle sensors for environmental monitoring and motion sensors in mobile phones. High-quality optical microcavities are prime candidates for sensing applications because of their ability to enhance light-matter interactions in a very confined volume. Examples of such devices include mechanical transducers, magnetometers, single-particle absorption spectrometers, and microcavity sensors for sizing single particles and detecting nanometre-scale objects such as single nanoparticles and atomic ions. Traditionally, a very small perturbation near an optical microcavity introduces either a change in the linewidth or a frequency shift or splitting of a resonance that is proportional to the strength of the perturbation. Here we demonstrate an alternative sensing scheme, by which the sensitivity of microcavities can be enhanced when operated at non-Hermitian spectral degeneracies known as exceptional points. In our experiments, we use two nanoscale scatterers to tune a whispering-gallery-mode micro-toroid cavity, in which light propagates along a concave surface by continuous total internal reflection, in a precise and controlled manner to exceptional points. A target nanoscale object that subsequently enters the evanescent field of the cavity perturbs the system from its exceptional point, leading to frequency splitting. Owing to the complex-square-root topology near an exceptional point, this frequency splitting scales as the square root of the perturbation strength and is therefore larger (for sufficiently small perturbations) than the splitting observed in traditional non-exceptional-point sensing schemes. Our demonstration of exceptional-point-enhanced sensitivity paves the way for sensors with unprecedented sensitivity.

  7. Numerical methods for polyline-to-point-cloud registration with applications to patient-specific stent reconstruction.

    Science.gov (United States)

    Lin, Claire Yilin; Veneziani, Alessandro; Ruthotto, Lars

    2018-03-01

    We present novel numerical methods for polyline-to-point-cloud registration and their application to patient-specific modeling of deployed coronary artery stents from image data. Patient-specific coronary stent reconstruction is an important challenge in computational hemodynamics and relevant to the design and improvement of the prostheses. It is an invaluable tool in large-scale clinical trials that computationally investigate the effect of new generations of stents on hemodynamics and eventually tissue remodeling. Given a point cloud of strut positions, which can be extracted from images, our stent reconstruction method aims at finding a geometrical transformation that aligns a model of the undeployed stent to the point cloud. Mathematically, we describe the undeployed stent as a polyline, which is a piecewise linear object defined by its vertices and edges. We formulate the nonlinear registration as an optimization problem whose objective function consists of a similarity measure, quantifying the distance between the polyline and the point cloud, and a regularization functional, penalizing undesired transformations. Using projections of points onto the polyline structure, we derive novel distance measures. Our formulation supports most commonly used transformation models including very flexible nonlinear deformations. We also propose 2 regularization approaches ensuring the smoothness of the estimated nonlinear transformation. We demonstrate the potential of our methods using an academic 2D example and a real-life 3D bioabsorbable stent reconstruction problem. Our results show that the registration problem can be solved to sufficient accuracy within seconds using only a few number of Gauss-Newton iterations. Copyright © 2017 John Wiley & Sons, Ltd.

  8. A Space Object Detection Algorithm using Fourier Domain Likelihood Ratio Test

    Science.gov (United States)

    Becker, D.; Cain, S.

    Space object detection is of great importance in the highly dependent yet competitive and congested space domain. Detection algorithms employed play a crucial role in fulfilling the detection component in the situational awareness mission to detect, track, characterize and catalog unknown space objects. Many current space detection algorithms use a matched filter or a spatial correlator to make a detection decision at a single pixel point of a spatial image based on the assumption that the data follows a Gaussian distribution. This paper explores the potential for detection performance advantages when operating in the Fourier domain of long exposure images of small and/or dim space objects from ground based telescopes. A binary hypothesis test is developed based on the joint probability distribution function of the image under the hypothesis that an object is present and under the hypothesis that the image only contains background noise. The detection algorithm tests each pixel point of the Fourier transformed images to make the determination if an object is present based on the criteria threshold found in the likelihood ratio test. Using simulated data, the performance of the Fourier domain detection algorithm is compared to the current algorithm used in space situational awareness applications to evaluate its value.

  9. Arrival-Time Detection and Ultrasonic Flow-Meter Applications

    International Nuclear Information System (INIS)

    Willatzen, Morten; Soendergaard, Peter; Latino, Carl; Voss, Frands; Andersen, Niels Lervad; Brokate, Martin; Bounaim, Aicha

    2006-01-01

    The Danfoss problem on ultrasonic flow measurement has been separated into three parts each handled by a subgroup of the authors listed above. The first subgroup deals with a presentation of modelling equations describing the physics of ultrasonic flow meters employing reciprocal ultrasonic transducer systems. The mathematical model presented allows the electrical output signal to be determined corresponding to any time-dependent electrical input signal. The transducers modelled consist of a piezoceramic material layer and a passive acoustic matching layer. The second subgroup analyzes the possibility of coding the input signal so as to simplify arrival-time detection by re.nding the coded input sequence in the received signal. The narrow-band nature of the transducers makes this problem non-trivial but suggestions for improvement are proposed. The analysis given is based on traditional autoand cross-correlation techniques. The third subgroup attempts to improve existing correlation methods in determining arrival-time detection of signals. A mathematical formulation of the problem is given and the application to a set of real signals provided by Danfoss A/S is performed with good results

  10. Swimming speed alteration of Artemia sp. and Brachionus plicatilis as a sub-lethal behavioural end-point for ecotoxicological surveys.

    Science.gov (United States)

    Garaventa, Francesca; Gambardella, Chiara; Di Fino, Alessio; Pittore, Massimiliano; Faimali, Marco

    2010-03-01

    In this study, we investigated the possibility to improve a new behavioural bioassay (Swimming Speed Alteration test-SSA test) using larvae of marine cyst-forming organisms: e.g. the brine shrimp Artemia sp. and the rotifer Brachionus plicatilis. Swimming speed was investigated as a behavioural end-point for application in ecotoxicology studies. A first experiment to analyse the linear swimming speed of the two organisms was performed to verify the applicability of the video-camera tracking system, here referred to as Swimming Behavioural Recorder (SBR). A second experiment was performed, exposing organisms to different toxic compounds (zinc pyrithione, Macrotrol MT-200, and Eserine). Swimming speed alteration was analyzed together with mortality. The results of the first experiment indicate that SBR is a suitable tool to detect linear swimming speed of the two organisms, since the values have been obtained in accordance with other studies using the same organisms (3.05 mm s(-1) for Artemia sp. and 0.62 mm s(-1) for B. plicatilis). Toxicity test results clearly indicate that swimming speed of Artemia sp. and B. plicatilis is a valid behavioural end-point to detect stress at sub-lethal toxic substance concentrations. Indeed, alterations in swimming speed have been detected at toxic compound concentrations as low as less then 0.1-5% of their LC(50) values. In conclusion, the SSA test with B. plicatilis and Artemia sp. can be a good behavioural integrated output for application in marine ecotoxicology and environmental monitoring programs.

  11. Evaluation of Optical Detection Platforms for Multiplexed Detection of Proteins and the Need for Point-of-Care Biosensors for Clinical Use

    Directory of Open Access Journals (Sweden)

    Samantha Spindel

    2014-11-01

    Full Text Available This review investigates optical sensor platforms for protein multiplexing, the ability to analyze multiple analytes simultaneously. Multiplexing is becoming increasingly important for clinical needs because disease and therapeutic response often involve the interplay between a variety of complex biological networks encompassing multiple, rather than single, proteins. Multiplexing is generally achieved through one of two routes, either through spatial separation on a surface (different wells or spots or with the use of unique identifiers/labels (such as spectral separation—different colored dyes, or unique beads—size or color. The strengths and weaknesses of conventional platforms such as immunoassays and new platforms involving protein arrays and lab-on-a-chip technology, including commercially-available devices, are discussed. Three major public health concerns are identified whereby detecting medically-relevant markers using Point-of-Care (POC multiplex assays could potentially allow for a more efficient diagnosis and treatment of diseases.

  12. Measuring coseismic displacements with point-like targets offset tracking

    KAUST Repository

    Hu, Xie; Wang, Teng; Liao, Mingsheng

    2014-01-01

    Offset tracking is an important complement to measure large ground displacements in both azimuth and range dimensions where synthetic aperture radar (SAR) interferometry is unfeasible. Subpixel offsets can be obtained by searching for the cross-correlation peak calculated from the match patches uniformly distributed on two SAR images. However, it has its limitations, including redundant computation and incorrect estimations on decorrelated patches. In this letter, we propose a simple strategy that performs offset tracking on detected point-like targets (PT). We first detect image patches within bright PT by using a sinc-like template from a single SAR image and then perform offset tracking on them to obtain the pixel shifts. Compared with the standard method, the application on the 2010 M 7.2 El Mayor-Cucapah earthquake shows that the proposed PT offset tracking can significantly increase the cross-correlation and thus result in both efficiency and reliability improvements. © 2013 IEEE.

  13. Common Fixed Points of Mappings and Set-Valued Mappings in Symmetric Spaces with Application to Probabilistic Spaces

    OpenAIRE

    M. Aamri; A. Bassou; S. Bennani; D. El Moutawakil

    2007-01-01

    The main purpose of this paper is to give some common fixed point theorems of mappings and set-valued mappings of a symmetric space with some applications to probabilistic spaces. In order to get these results, we define the concept of E-weak compatibility between set-valued and single-valued mappings of a symmetric space.

  14. Evaluation of the usefulness of smartphone-directed applications for measuring heart rate and arrhythmia detection

    Directory of Open Access Journals (Sweden)

    Michał Witkowski

    2017-12-01

    Conclusions: The majority of the free applications, available for smartphones, are able to measure HR precisely in patients with sinus rhythm, while in patients with AF, the exact measurement is significantly impeded by HR deficits. Only one out of 16 applications was able to measure HR in a patient with AF. None of the available applications could detect AF.

  15. High-sensitivity detection of cardiac troponin I with UV LED excitation for use in point-of-care immunoassay.

    Science.gov (United States)

    Rodenko, Olga; Eriksson, Susann; Tidemand-Lichtenberg, Peter; Troldborg, Carl Peder; Fodgaard, Henrik; van Os, Sylvana; Pedersen, Christian

    2017-08-01

    High-sensitivity cardiac troponin assay development enables determination of biological variation in healthy populations, more accurate interpretation of clinical results and points towards earlier diagnosis and rule-out of acute myocardial infarction. In this paper, we report on preliminary tests of an immunoassay analyzer employing an optimized LED excitation to measure on a standard troponin I and a novel research high-sensitivity troponin I assay. The limit of detection is improved by factor of 5 for standard troponin I and by factor of 3 for a research high-sensitivity troponin I assay, compared to the flash lamp excitation. The obtained limit of detection was 0.22 ng/L measured on plasma with the research high-sensitivity troponin I assay and 1.9 ng/L measured on tris-saline-azide buffer containing bovine serum albumin with the standard troponin I assay. We discuss the optimization of time-resolved detection of lanthanide fluorescence based on the time constants of the system and analyze the background and noise sources in a heterogeneous fluoroimmunoassay. We determine the limiting factors and their impact on the measurement performance. The suggested model can be generally applied to fluoroimmunoassays employing the dry-cup concept.

  16. APSET, an Android aPplication SEcurity Testing tool for detecting intent-based vulnerabilities.

    OpenAIRE

    Salva , Sébastien; Zamiharisoa , Stassia R.

    2014-01-01

    International audience; The Android messaging system, called in- tent, is a mechanism that ties components together to build applications for smartphones. Intents are kinds of messages composed of actions and data, sent by a com- ponent to another component to perform several opera- tions, e.g., launching a user interface. The intent mech- anism o er a lot of exibility for developing Android applications, but it might also be used as an entry point for security attacks. The latter can be easi...

  17. PowerPoint 2007 for Dummies

    CERN Document Server

    Lowe, Doug

    2007-01-01

    New and inexperienced PowerPoint users will discover how to use the latest enhancements to PowerPoint 2007 quickly and efficiently so that they can produce unique and informative presentations PowerPoint continues to be the world's most popular presentation software This updated For Dummies guide shows users different ways to create powerful and effective slideshow presentations that incorporate data from other applications in the form of charts, clip art, sound, and video Shares the key features of PowerPoint 2007 including creating and editing slides, working with hyperlinks and action butt

  18. Point Based Emotion Classification Using SVM

    OpenAIRE

    Swinkels, Wout

    2016-01-01

    The detection of emotions is a hot topic in the area of computer vision. Emotions are based on subtle changes in the face that are intuitively detected and interpreted by humans. Detecting these subtle changes, based on mathematical models, is a great challenge in the area of computer vision. In this thesis a new method is proposed to achieve state-of-the-art emotion detection performance. This method is based on facial feature points to monitor subtle changes in the face. Therefore the c...

  19. ON THE INFLUENTIAL POINTS IN THE FUNCTIONAL CIRCULAR RELATIONSHIP MODELS WITH AN APPLICATION ON WIND DATA

    Directory of Open Access Journals (Sweden)

    ALi Hassan Abuzaid

    2013-12-01

    Full Text Available If the interest is to calibrate two instruments then the functional relationship model is more appropriate than regression models. Fitting a straight line when both variables are circular and subject to errors has not received much attention. In this paper, we consider the problem of detecting influential points in two functional relationship models for circular variables. The first is based on the simple circular regression the (SC, while the last is derived from the complex linear regression the (CL.   The covariance matrices are derived and then the COVRATIO statistics are formulated for both models. The cut-off points are obtained and the power of performance is assessed via simulation studies.   The performance of COVRATIO statistics depends on the concentration of error, sample size and level of contamination. In the case of linear relationship between two circular variables COVRATIO statistics of the (SC model performs better than the (CL.  On the other hand, a novel diagram, the so-called spoke plot, is utilized to detect possible influential points For illustration purposes, the proposed procedures are applied on real data of wind directions measured by two different instruments. COVRATIO statistics and the spoke plot were able to identify two observations as influential points. Normal 0 false false false EN-US X-NONE AR-SA /* Style Definitions */ table.MsoNormalTable {mso-style-name:"جدول عادي"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin-top:0cm; mso-para-margin-right:0cm; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0cm; line-height:115%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:Arial; mso-bidi-theme-font:minor-bidi;}

  20. Hybrid Video Stabilization for Mobile Vehicle Detection on SURF in Aerial Surveillance

    Directory of Open Access Journals (Sweden)

    Gao Chunxian

    2015-01-01

    Full Text Available Detection of moving vehicles in aerial video sequences is of great importance with many promising applications in surveillance, intelligence transportation, or public service applications such as emergency evacuation and policy security. However, vehicle detection is a challenging task due to global camera motion, low resolution of vehicles, and low contrast between vehicles and background. In this paper, we present a hybrid method to efficiently detect moving vehicle in aerial videos. Firstly, local feature extraction and matching were performed to estimate the global motion. It was demonstrated that the Speeded Up Robust Feature (SURF key points were more suitable for the stabilization task. Then, a list of dynamic pixels was obtained and grouped for different moving vehicles by comparing the different optical flow normal. To enhance the precision of detection, some preprocessing methods were applied to the surveillance system, such as road extraction and other features. A quantitative evaluation on real video sequences indicated that the proposed method improved the detection performance significantly.