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Sample records for detection method based

  1. Lagrangian based methods for coherent structure detection

    Energy Technology Data Exchange (ETDEWEB)

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

    2015-09-15

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

  2. 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.

  3. Anomaly-based Network Intrusion Detection Methods

    Directory of Open Access Journals (Sweden)

    Pavel Nevlud

    2013-01-01

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

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

    African Journals Online (AJOL)

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

  5. Distance Based Method for Outlier Detection of Body Sensor Networks

    Directory of Open Access Journals (Sweden)

    Haibin Zhang

    2016-01-01

    Full Text Available We propose a distance based method for the outlier detection of body sensor networks. Firstly, we use a Kernel Density Estimation (KDE to calculate the probability of the distance to k nearest neighbors for diagnosed data. If the probability is less than a threshold, and the distance of this data to its left and right neighbors is greater than a pre-defined value, the diagnosed data is decided as an outlier. Further, we formalize a sliding window based method to improve the outlier detection performance. Finally, to estimate the KDE by training sensor readings with errors, we introduce a Hidden Markov Model (HMM based method to estimate the most probable ground truth values which have the maximum probability to produce the training data. Simulation results show that the proposed method possesses a good detection accuracy with a low false alarm rate.

  6. Dim target detection method based on salient graph fusion

    Science.gov (United States)

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

    2018-02-01

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

  7. Transistor-based particle detection systems and methods

    Science.gov (United States)

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

    2015-06-09

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

  8. Study on UPF Harmonic Current Detection Method Based on DSP

    Energy Technology Data Exchange (ETDEWEB)

    Zhao, H J [Northwestern Polytechnical University, Xi' an 710072 (China); Pang, Y F [Xi' an University of Technology, Xi' an 710048 (China); Qiu, Z M [Xi' an University of Technology, Xi' an 710048 (China); Chen, M [Northwestern Polytechnical University, Xi' an 710072 (China)

    2006-10-15

    Unity power factor (UPF) harmonic current detection method applied to active power filter (APF) is presented in this paper. The intention of this method is to make nonlinear loads and active power filter in parallel to be an equivalent resistance. So after compensation, source current is sinusoidal, and has the same shape of source voltage. Meanwhile, there is no harmonic in source current, and the power factor becomes one. The mathematic model of proposed method and the optimum project for equivalent low pass filter in measurement are presented. Finally, the proposed detection method applied to a shunt active power filter experimental prototype based on DSP TMS320F2812 is developed. Simulation and experiment results indicate the method is simple and easy to implement, and can obtain the real-time calculation of harmonic current exactly.

  9. An Automata Based Intrusion Detection Method for Internet of Things

    Directory of Open Access Journals (Sweden)

    Yulong Fu

    2017-01-01

    Full Text Available Internet of Things (IoT transforms network communication to Machine-to-Machine (M2M basis and provides open access and new services to citizens and companies. It extends the border of Internet and will be developed as one part of the future 5G networks. However, as the resources of IoT’s front devices are constrained, many security mechanisms are hard to be implemented to protect the IoT networks. Intrusion detection system (IDS is an efficient technique that can be used to detect the attackers when cryptography is broken, and it can be used to enforce the security of IoT networks. In this article, we analyzed the intrusion detection requirements of IoT networks and then proposed a uniform intrusion detection method for the vast heterogeneous IoT networks based on an automata model. The proposed method can detect and report the possible IoT attacks with three types: jam-attack, false-attack, and reply-attack automatically. We also design an experiment to verify the proposed IDS method and examine the attack of RADIUS application.

  10. Edge detection methods based on generalized type-2 fuzzy logic

    CERN Document Server

    Gonzalez, Claudia I; Castro, Juan R; Castillo, Oscar

    2017-01-01

    In this book four new methods are proposed. In the first method the generalized type-2 fuzzy logic is combined with the morphological gra-dient technique. The second method combines the general type-2 fuzzy systems (GT2 FSs) and the Sobel operator; in the third approach the me-thodology based on Sobel operator and GT2 FSs is improved to be applied on color images. In the fourth approach, we proposed a novel edge detec-tion method where, a digital image is converted a generalized type-2 fuzzy image. In this book it is also included a comparative study of type-1, inter-val type-2 and generalized type-2 fuzzy systems as tools to enhance edge detection in digital images when used in conjunction with the morphologi-cal gradient and the Sobel operator. The proposed generalized type-2 fuzzy edge detection methods were tested with benchmark images and synthetic images, in a grayscale and color format. Another contribution in this book is that the generalized type-2 fuzzy edge detector method is applied in the preproc...

  11. DNS Tunneling Detection Method Based on Multilabel Support Vector Machine

    Directory of Open Access Journals (Sweden)

    Ahmed Almusawi

    2018-01-01

    Full Text Available DNS tunneling is a method used by malicious users who intend to bypass the firewall to send or receive commands and data. This has a significant impact on revealing or releasing classified information. Several researchers have examined the use of machine learning in terms of detecting DNS tunneling. However, these studies have treated the problem of DNS tunneling as a binary classification where the class label is either legitimate or tunnel. In fact, there are different types of DNS tunneling such as FTP-DNS tunneling, HTTP-DNS tunneling, HTTPS-DNS tunneling, and POP3-DNS tunneling. Therefore, there is a vital demand to not only detect the DNS tunneling but rather classify such tunnel. This study aims to propose a multilabel support vector machine in order to detect and classify the DNS tunneling. The proposed method has been evaluated using a benchmark dataset that contains numerous DNS queries and is compared with a multilabel Bayesian classifier based on the number of corrected classified DNS tunneling instances. Experimental results demonstrate the efficacy of the proposed SVM classification method by obtaining an f-measure of 0.80.

  12. Detection of communities with Naming Game-based methods

    Science.gov (United States)

    Ribeiro, Carlos Henrique Costa

    2017-01-01

    Complex networks are often organized in groups or communities of agents that share the same features and/or functions, and this structural organization is built naturally with the formation of the system. In social networks, we argue that the dynamic of linguistic interactions of agreement among people can be a crucial factor in generating this community structure, given that sharing opinions with another person bounds them together, and disagreeing constantly would probably weaken the relationship. We present here a computational model of opinion exchange that uncovers the community structure of a network. Our aim is not to present a new community detection method proper, but to show how a model of social communication dynamics can reveal the (simple and overlapping) community structure in an emergent way. Our model is based on a standard Naming Game, but takes into consideration three social features: trust, uncertainty and opinion preference, that are built over time as agents communicate among themselves. We show that the separate addition of each social feature in the Naming Game results in gradual improvements with respect to community detection. In addition, the resulting uncertainty and trust values classify nodes and edges according to role and position in the network. Also, our model has shown a degree of accuracy both for non-overlapping and overlapping communities that are comparable with most algorithms specifically designed for topological community detection. PMID:28797097

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

    African Journals Online (AJOL)

    STORAGESEVER

    2009-05-04

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

  14. Updating National Topographic Data Base Using Change Detection Methods

    Science.gov (United States)

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

    2016-06-01

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

  15. Method of Multiobject Detecting and Tracking Based on DM643

    Directory of Open Access Journals (Sweden)

    Yitao Liang

    2014-01-01

    Full Text Available The technology of moving objects detection has become an important research subject for its extensive application prospect. In this paper, it is presented that interframe difference algorithm and background difference algorithm are combined to update the background. The algorithm can deal with the flaw of background difference algorithm. The mathematical morphology method is employed to denoise the image, which may be helpful to improve the accuracy of the detection. The Pyramid algorithm is used to compress each frame data of video sequence. Then, the detecting and tracking of moving objects are tested on the hardware platform (DM643 and the software frame (RF5. The running speed is about 3 times faster than before. The result shows that the accuracy demanded by the detection is met. This method can provide a useful reference for similar application.

  16. UPDATING NATIONAL TOPOGRAPHIC DATA BASE USING CHANGE DETECTION METHODS

    Directory of Open Access Journals (Sweden)

    E. Keinan

    2016-06-01

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

  17. Colour based fire detection method with temporal intensity variation filtration

    Science.gov (United States)

    Trambitckii, K.; Anding, K.; Musalimov, V.; Linß, G.

    2015-02-01

    Development of video, computing technologies and computer vision gives a possibility of automatic fire detection on video information. Under that project different algorithms was implemented to find more efficient way of fire detection. In that article colour based fire detection algorithm is described. But it is not enough to use only colour information to detect fire properly. The main reason of this is that in the shooting conditions may be a lot of things having colour similar to fire. A temporary intensity variation of pixels is used to separate them from the fire. These variations are averaged over the series of several frames. This algorithm shows robust work and was realised as a computer program by using of the OpenCV library.

  18. Colour based fire detection method with temporal intensity variation filtration

    International Nuclear Information System (INIS)

    Trambitckii, K; Musalimov, V; Anding, K; Linß, G

    2015-01-01

    Development of video, computing technologies and computer vision gives a possibility of automatic fire detection on video information. Under that project different algorithms was implemented to find more efficient way of fire detection. In that article colour based fire detection algorithm is described. But it is not enough to use only colour information to detect fire properly. The main reason of this is that in the shooting conditions may be a lot of things having colour similar to fire. A temporary intensity variation of pixels is used to separate them from the fire. These variations are averaged over the series of several frames. This algorithm shows robust work and was realised as a computer program by using of the OpenCV library

  19. Ensemble method: Community detection based on game theory

    Science.gov (United States)

    Zhang, Xia; Xia, Zhengyou; Xu, Shengwu; Wang, J. D.

    2014-08-01

    Timely and cost-effective analytics over social network has emerged as a key ingredient for success in many businesses and government endeavors. Community detection is an active research area of relevance to analyze online social network. The problem of selecting a particular community detection algorithm is crucial if the aim is to unveil the community structure of a network. The choice of a given methodology could affect the outcome of the experiments because different algorithms have different advantages and depend on tuning specific parameters. In this paper, we propose a community division model based on the notion of game theory, which can combine advantages of previous algorithms effectively to get a better community classification result. By making experiments on some standard dataset, it verifies that our community detection model based on game theory is valid and better.

  20. PAUT-based defect detection method for submarine pressure hulls

    Directory of Open Access Journals (Sweden)

    Min-jae Jung

    2018-03-01

    Full Text Available A submarine has a pressure hull that can withstand high hydraulic pressure and therefore, requires the use of highly advanced shipbuilding technology. When producing a pressure hull, periodic inspection, repair, and maintenance are conducted to maintain its soundness. Of the maintenance methods, Non-Destructive Testing (NDT is the most effective, because it does not damage the target but sustains its original form and function while inspecting internal and external defects. The NDT process to detect defects in the welded parts of the submarine is applied through Magnetic particle Testing (MT to detect surface defects and Ultrasonic Testing (UT and Radiography Testing (RT to detect internal defects. In comparison with RT, UT encounters difficulties in distinguishing the types of defects, can yield different results depending on the skills of the inspector, and stores no inspection record. At the same time, the use of RT gives rise to issues related to worker safety due to radiation exposure. RT is also difficult to apply from the perspectives of the manufacturing of the submarine and economic feasibility. Therefore, in this study, the Phased Array Ultrasonic Testing (PAUT method was applied to propose an inspection method that can address the above disadvantages by designing a probe to enhance the precision of detection of hull defects and the reliability of calculations of defect size. Keywords: Submarine pressure hull, Non-destructive testing, Phased array ultrasonic testing

  1. Novel DNA sequence detection method based on fluorescence energy transfer

    International Nuclear Information System (INIS)

    Kobayashi, S.; Tamiya, E.; Karube, I.

    1987-01-01

    Recently the detection of specific DNA sequence, DNA analysis, has been becoming more important for diagnosis of viral genomes causing infections disease and human sequences related to inherited disorders. These methods typically involve electrophoresis, the immobilization of DNA on a solid support, hybridization to a complementary probe, the detection using labeled with /sup 32/P or nonisotopically with a biotin-avidin-enzyme system, and so on. These techniques are highly effective, but they are very time-consuming and expensive. A principle of fluorescene energy transfer is that the light energy from an excited donor (fluorophore) is transferred to an acceptor (fluorophore), if the acceptor exists in the vicinity of the donor and the excitation spectrum of donor overlaps the emission spectrum of acceptor. In this study, the fluorescence energy transfer was applied to the detection of specific DNA sequence using the hybridization method. The analyte, single-stranded DNA labeled with the donor fluorophore is hybridized to a probe DNA labeled with the acceptor. Because of the complementary DNA duplex formation, two fluorophores became to be closed to each other, and the fluorescence energy transfer was occurred

  2. Ranking-based Method for News Stance Detection

    KAUST Repository

    Zhang, Qiang; Yilmaz, Emine; Liang, Shangsong

    2018-01-01

    A valuable step towards news veracity assessment is to understand stance from different information sources, and the process is known as the stance detection. Specifically, the stance detection is to detect four kinds of stances (

  3. Ranking-based Method for News Stance Detection

    KAUST Repository

    Zhang, Qiang

    2018-04-18

    A valuable step towards news veracity assessment is to understand stance from different information sources, and the process is known as the stance detection. Specifically, the stance detection is to detect four kinds of stances (

  4. Human Detection System by Fusing Depth Map-Based Method and Convolutional Neural Network-Based Method

    Directory of Open Access Journals (Sweden)

    Anh Vu Le

    2017-01-01

    Full Text Available In this paper, the depth images and the colour images provided by Kinect sensors are used to enhance the accuracy of human detection. The depth-based human detection method is fast but less accurate. On the other hand, the faster region convolutional neural network-based human detection method is accurate but requires a rather complex hardware configuration. To simultaneously leverage the advantages and relieve the drawbacks of each method, one master and one client system is proposed. The final goal is to make a novel Robot Operation System (ROS-based Perception Sensor Network (PSN system, which is more accurate and ready for the real time application. The experimental results demonstrate the outperforming of the proposed method compared with other conventional methods in the challenging scenarios.

  5. The design method and research status of vehicle detection system based on geomagnetic detection principle

    Science.gov (United States)

    Lin, Y. H.; Bai, R.; Qian, Z. H.

    2018-03-01

    Vehicle detection systems are applied to obtain real-time information of vehicles, realize traffic control and reduce traffic pressure. This paper reviews geomagnetic sensors as well as the research status of the vehicle detection system. Presented in the paper are also our work on the vehicle detection system, including detection algorithms and experimental results. It is found that the GMR based vehicle detection system has a detection accuracy up to 98% with a high potential for application in the road traffic control area.

  6. Ultrafast laser based coherent control methods for explosives detection

    Energy Technology Data Exchange (ETDEWEB)

    Moore, David Steven [Los Alamos National Laboratory

    2010-12-06

    The detection of explosives is a notoriously difficult problem, especially at stand-off, due to their (generally) low vapor pressure, environmental and matrix interferences, and packaging. We are exploring Optimal Dynamic Detection of Explosives (ODD-Ex), which exploits the best capabilities of recent advances in laser technology and recent discoveries in optimal shaping of laser pulses for control of molecular processes to significantly enhance the standoff detection of explosives. The core of the ODD-Ex technique is the introduction of optimally shaped laser pulses to simultaneously enhance sensitivity to explosives signatures while dramatically improving specificity, particularly against matrix materials and background interferences. These goals are being addressed by operating in an optimal non-linear fashion, typically with a single shaped laser pulse inherently containing within it coherently locked control and probe subpulses. Recent results will be presented.

  7. [An automatic peak detection method for LIBS spectrum based on continuous wavelet transform].

    Science.gov (United States)

    Chen, Peng-Fei; Tian, Di; Qiao, Shu-Jun; Yang, Guang

    2014-07-01

    Spectrum peak detection in the laser-induced breakdown spectroscopy (LIBS) is an essential step, but the presence of background and noise seriously disturb the accuracy of peak position. The present paper proposed a method applied to automatic peak detection for LIBS spectrum in order to enhance the ability of overlapping peaks searching and adaptivity. We introduced the ridge peak detection method based on continuous wavelet transform to LIBS, and discussed the choice of the mother wavelet and optimized the scale factor and the shift factor. This method also improved the ridge peak detection method with a correcting ridge method. The experimental results show that compared with other peak detection methods (the direct comparison method, derivative method and ridge peak search method), our method had a significant advantage on the ability to distinguish overlapping peaks and the precision of peak detection, and could be be applied to data processing in LIBS.

  8. The harmonics detection method based on neural network applied ...

    African Journals Online (AJOL)

    Several different methods have been used to sense load currents and extract its ... in order to produce a reference current in shunt active power filters (SAPF), and ... technique compared to other similar methods are found quite satisfactory by ...

  9. 78 FR 16513 - Application of Advances in Nucleic Acid and Protein Based Detection Methods to Multiplex...

    Science.gov (United States)

    2013-03-15

    ... Methods to Multiplex Detection of Transfusion- Transmissible Agents and Blood Cell Antigens in Blood... Transfusion-Transmissible Agents and Blood Cell Antigens in Blood Donations; Public Workshop AGENCY: Food and... technological advances in gene based and protein based pathogen and blood cell antigen detection methods and to...

  10. The harmonics detection method based on neural network applied ...

    African Journals Online (AJOL)

    user

    Keywords: Artificial Neural Networks (ANN), p-q theory, (SAPF), Harmonics, Total ..... Genetic algorithm-based self-learning fuzzy PI controller for shunt active filter, ... Verification of global optimality of the OFC active power filters by means of ...

  11. Intrusion detection method based on nonlinear correlation measure

    NARCIS (Netherlands)

    Ambusaidi, Mohammed A.; Tan, Zhiyuan; He, Xiangjian; Nanda, Priyadarsi; Lu, Liang Fu; Jamdagni, Aruna

    2014-01-01

    Cyber crimes and malicious network activities have posed serious threats to the entire internet and its users. This issue is becoming more critical, as network-based services, are more widespread and closely related to our daily life. Thus, it has raised a serious concern in individual internet

  12. Diffusion Geometry Based Nonlinear Methods for Hyperspectral Change Detection

    Science.gov (United States)

    2010-05-12

    for matching biological spectra across a data base of hyperspectral pathology slides acquires with different instruments in different conditions, as...generalizing wavelets and similar scaling mechanisms. Plain Sight Systems, Inc. -7- Proprietary and Confidential To be specific, let the bi-Markov...remarkably well. Conventional nearest neighbor search , compared with a diffusion search. The data is a pathology slide ,each pixel is a digital

  13. A Novel Fusion-Based Ship Detection Method from Pol-SAR Images

    Directory of Open Access Journals (Sweden)

    Wenguang Wang

    2015-09-01

    Full Text Available A novel fusion-based ship detection method from polarimetric Synthetic Aperture Radar (Pol-SAR images is proposed in this paper. After feature extraction and constant false alarm rate (CFAR detection, the detection results of HH channel, diplane scattering by Pauli decomposition and helical factor by Barnes decomposition are fused together. The confirmed targets and potential target pixels can be obtained after the fusion process. Using the difference degree of the target, potential target pixels can be classified. The fusion-based ship detection method works accurately by utilizing three different features comprehensively. The result of applying the technique to measured Airborne Synthetic Radar (AIRSAR data shows that the novel detection method can achieve better performance in both ship’s detection and ship’s shape preservation compared to the result of K-means clustering method and the Notch Filter method.

  14. A Hybrid Vehicle Detection Method Based on Viola-Jones and HOG + SVM from UAV Images.

    Science.gov (United States)

    Xu, Yongzheng; Yu, Guizhen; Wang, Yunpeng; Wu, Xinkai; Ma, Yalong

    2016-08-19

    A new hybrid vehicle detection scheme which integrates the Viola-Jones (V-J) and linear SVM classifier with HOG feature (HOG + SVM) methods is proposed for vehicle detection from low-altitude unmanned aerial vehicle (UAV) images. As both V-J and HOG + SVM are sensitive to on-road vehicles' in-plane rotation, the proposed scheme first adopts a roadway orientation adjustment method, which rotates each UAV image to align the roads with the horizontal direction so the original V-J or HOG + SVM method can be directly applied to achieve fast detection and high accuracy. To address the issue of descending detection speed for V-J and HOG + SVM, the proposed scheme further develops an adaptive switching strategy which sophistically integrates V-J and HOG + SVM methods based on their different descending trends of detection speed to improve detection efficiency. A comprehensive evaluation shows that the switching strategy, combined with the road orientation adjustment method, can significantly improve the efficiency and effectiveness of the vehicle detection from UAV images. The results also show that the proposed vehicle detection method is competitive compared with other existing vehicle detection methods. Furthermore, since the proposed vehicle detection method can be performed on videos captured from moving UAV platforms without the need of image registration or additional road database, it has great potentials of field applications. Future research will be focusing on expanding the current method for detecting other transportation modes such as buses, trucks, motors, bicycles, and pedestrians.

  15. A Hybrid Vehicle Detection Method Based on Viola-Jones and HOG + SVM from UAV Images

    Science.gov (United States)

    Xu, Yongzheng; Yu, Guizhen; Wang, Yunpeng; Wu, Xinkai; Ma, Yalong

    2016-01-01

    A new hybrid vehicle detection scheme which integrates the Viola-Jones (V-J) and linear SVM classifier with HOG feature (HOG + SVM) methods is proposed for vehicle detection from low-altitude unmanned aerial vehicle (UAV) images. As both V-J and HOG + SVM are sensitive to on-road vehicles’ in-plane rotation, the proposed scheme first adopts a roadway orientation adjustment method, which rotates each UAV image to align the roads with the horizontal direction so the original V-J or HOG + SVM method can be directly applied to achieve fast detection and high accuracy. To address the issue of descending detection speed for V-J and HOG + SVM, the proposed scheme further develops an adaptive switching strategy which sophistically integrates V-J and HOG + SVM methods based on their different descending trends of detection speed to improve detection efficiency. A comprehensive evaluation shows that the switching strategy, combined with the road orientation adjustment method, can significantly improve the efficiency and effectiveness of the vehicle detection from UAV images. The results also show that the proposed vehicle detection method is competitive compared with other existing vehicle detection methods. Furthermore, since the proposed vehicle detection method can be performed on videos captured from moving UAV platforms without the need of image registration or additional road database, it has great potentials of field applications. Future research will be focusing on expanding the current method for detecting other transportation modes such as buses, trucks, motors, bicycles, and pedestrians. PMID:27548179

  16. Hand-Eye LRF-Based Iterative Plane Detection Method for Autonomous Robotic Welding

    Directory of Open Access Journals (Sweden)

    Sungmin Lee

    2015-12-01

    Full Text Available This paper proposes a hand-eye LRF-based (laser range finder welding plane-detection method for autonomous robotic welding in the field of shipbuilding. The hand-eye LRF system consists of a 6 DOF manipulator and an LRF attached to the wrist of the manipulator. The welding plane is detected by the LRF with only the wrist's rotation to minimize a mechanical error caused by the manipulator's motion. A position on the plane is determined as an average position of the detected points on the plane, and a normal vector to the plane is determined by applying PCA (principal component analysis to the detected points. In this case, the accuracy of the detected plane is analysed by simulations with respect to the wrist's angle interval and the plane angle. As a result of the analysis, an iterative plane-detection method with the manipulator's alignment motion is proposed to improve the performance of plane detection. For verifying the feasibility and effectiveness of the proposed plane-detection method, experiments are carried out with a prototype of the hand-eye LRF-based system, which consists of a 1 DOF wrist's joint, an LRF system and a rotatable plane. In addition, the experimental results of the PCA-based plane detection method are compared with those of the two representative plane-detection methods, based on RANSAC (RANdom SAmple Consensus and the 3D Hough transform in both accuracy and computation time's points of view.

  17. Data-driven fault detection for industrial processes canonical correlation analysis and projection based methods

    CERN Document Server

    Chen, Zhiwen

    2017-01-01

    Zhiwen Chen aims to develop advanced fault detection (FD) methods for the monitoring of industrial processes. With the ever increasing demands on reliability and safety in industrial processes, fault detection has become an important issue. Although the model-based fault detection theory has been well studied in the past decades, its applications are limited to large-scale industrial processes because it is difficult to build accurate models. Furthermore, motivated by the limitations of existing data-driven FD methods, novel canonical correlation analysis (CCA) and projection-based methods are proposed from the perspectives of process input and output data, less engineering effort and wide application scope. For performance evaluation of FD methods, a new index is also developed. Contents A New Index for Performance Evaluation of FD Methods CCA-based FD Method for the Monitoring of Stationary Processes Projection-based FD Method for the Monitoring of Dynamic Processes Benchmark Study and Real-Time Implementat...

  18. Novel Fingertip Image-Based Heart Rate Detection Methods for a Smartphone

    Directory of Open Access Journals (Sweden)

    Rifat Zaman

    2017-02-01

    Full Text Available We hypothesize that our fingertip image-based heart rate detection methods using smartphone reliably detect the heart rhythm and rate of subjects. We propose fingertip curve line movement-based and fingertip image intensity-based detection methods, which both use the movement of successive fingertip images obtained from smartphone cameras. To investigate the performance of the proposed methods, heart rhythm and rate of the proposed methods are compared to those of the conventional method, which is based on average image pixel intensity. Using a smartphone, we collected 120 s pulsatile time series data from each recruited subject. The results show that the proposed fingertip curve line movement-based method detects heart rate with a maximum deviation of 0.0832 Hz and 0.124 Hz using time- and frequency-domain based estimation, respectively, compared to the conventional method. Moreover, another proposed fingertip image intensity-based method detects heart rate with a maximum deviation of 0.125 Hz and 0.03 Hz using time- and frequency-based estimation, respectively.

  19. Rapid detection of Salmonella in pet food: design and evaluation of integrated methods based on real-time PCR detection.

    Science.gov (United States)

    Balachandran, Priya; Friberg, Maria; Vanlandingham, V; Kozak, K; Manolis, Amanda; Brevnov, Maxim; Crowley, Erin; Bird, Patrick; Goins, David; Furtado, Manohar R; Petrauskene, Olga V; Tebbs, Robert S; Charbonneau, Duane

    2012-02-01

    Reducing the risk of Salmonella contamination in pet food is critical for both companion animals and humans, and its importance is reflected by the substantial increase in the demand for pathogen testing. Accurate and rapid detection of foodborne pathogens improves food safety, protects the public health, and benefits food producers by assuring product quality while facilitating product release in a timely manner. Traditional culture-based methods for Salmonella screening are laborious and can take 5 to 7 days to obtain definitive results. In this study, we developed two methods for the detection of low levels of Salmonella in pet food using real-time PCR: (i) detection of Salmonella in 25 g of dried pet food in less than 14 h with an automated magnetic bead-based nucleic acid extraction method and (ii) detection of Salmonella in 375 g of composite dry pet food matrix in less than 24 h with a manual centrifugation-based nucleic acid preparation method. Both methods included a preclarification step using a novel protocol that removes food matrix-associated debris and PCR inhibitors and improves the sensitivity of detection. Validation studies revealed no significant differences between the two real-time PCR methods and the standard U.S. Food and Drug Administration Bacteriological Analytical Manual (chapter 5) culture confirmation method.

  20. Proposed Sandia frequency shift for anti-islanding detection method based on artificial immune system

    Directory of Open Access Journals (Sweden)

    A.Y. Hatata

    2018-03-01

    Full Text Available Sandia frequency shift (SFS is one of the active anti-islanding detection methods that depend on frequency drift to detect an islanding condition for inverter-based distributed generation. The non-detection zone (NDZ of the SFS method depends to a great extent on its parameters. Improper adjusting of these parameters may result in failure of the method. This paper presents a proposed artificial immune system (AIS-based technique to obtain optimal parameters of SFS anti-islanding detection method. The immune system is highly distributed, highly adaptive, and self-organizing in nature, maintains a memory of past encounters, and has the ability to continually learn about new encounters. The proposed method generates less total harmonic distortion (THD than the conventional SFS, which results in faster island detection and better non-detection zone. The performance of the proposed method is derived analytically and simulated using Matlab/Simulink. Two case studies are used to verify the proposed method. The first case includes a photovoltaic (PV connected to grid and the second includes a wind turbine connected to grid. The deduced optimized parameter setting helps to achieve the “non-islanding inverter” as well as least potential adverse impact on power quality. Keywords: Anti-islanding detection, Sandia frequency shift (SFS, Non-detection zone (NDZ, Total harmonic distortion (THD, Artificial immune system (AIS, Clonal selection algorithm

  1. Improved Ordinary Measure and Image Entropy Theory based intelligent Copy Detection Method

    Directory of Open Access Journals (Sweden)

    Dengpan Ye

    2011-10-01

    Full Text Available Nowadays, more and more multimedia websites appear in social network. It brings some security problems, such as privacy, piracy, disclosure of sensitive contents and so on. Aiming at copyright protection, the copy detection technology of multimedia contents becomes a hot topic. In our previous work, a new computer-based copyright control system used to detect the media has been proposed. Based on this system, this paper proposes an improved media feature matching measure and an entropy based copy detection method. The Levenshtein Distance was used to enhance the matching degree when using for feature matching measure in copy detection. For entropy based copy detection, we make a fusion of the two features of entropy matrix of the entropy feature we extracted. Firstly,we extract the entropy matrix of the image and normalize it. Then, we make a fusion of the eigenvalue feature and the transfer matrix feature of the entropy matrix. The fused features will be used for image copy detection. The experiments show that compared to use these two kinds of features for image detection singly, using feature fusion matching method is apparent robustness and effectiveness. The fused feature has a high detection for copy images which have been received some attacks such as noise, compression, zoom, rotation and so on. Comparing with referred methods, the method proposed is more intelligent and can be achieved good performance.

  2. INCREMENTAL PRINCIPAL COMPONENT ANALYSIS BASED OUTLIER DETECTION METHODS FOR SPATIOTEMPORAL DATA STREAMS

    Directory of Open Access Journals (Sweden)

    A. Bhushan

    2015-07-01

    Full Text Available In this paper, we address outliers in spatiotemporal data streams obtained from sensors placed across geographically distributed locations. Outliers may appear in such sensor data due to various reasons such as instrumental error and environmental change. Real-time detection of these outliers is essential to prevent propagation of errors in subsequent analyses and results. Incremental Principal Component Analysis (IPCA is one possible approach for detecting outliers in such type of spatiotemporal data streams. IPCA has been widely used in many real-time applications such as credit card fraud detection, pattern recognition, and image analysis. However, the suitability of applying IPCA for outlier detection in spatiotemporal data streams is unknown and needs to be investigated. To fill this research gap, this paper contributes by presenting two new IPCA-based outlier detection methods and performing a comparative analysis with the existing IPCA-based outlier detection methods to assess their suitability for spatiotemporal sensor data streams.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2010-07-01

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

  4. Real-time biscuit tile image segmentation method based on edge detection.

    Science.gov (United States)

    Matić, Tomislav; Aleksi, Ivan; Hocenski, Željko; Kraus, Dieter

    2018-05-01

    In this paper we propose a novel real-time Biscuit Tile Segmentation (BTS) method for images from ceramic tile production line. BTS method is based on signal change detection and contour tracing with a main goal of separating tile pixels from background in images captured on the production line. Usually, human operators are visually inspecting and classifying produced ceramic tiles. Computer vision and image processing techniques can automate visual inspection process if they fulfill real-time requirements. Important step in this process is a real-time tile pixels segmentation. BTS method is implemented for parallel execution on a GPU device to satisfy the real-time constraints of tile production line. BTS method outperforms 2D threshold-based methods, 1D edge detection methods and contour-based methods. Proposed BTS method is in use in the biscuit tile production line. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

  5. Infrared video based gas leak detection method using modified FAST features

    Science.gov (United States)

    Wang, Min; Hong, Hanyu; Huang, Likun

    2018-03-01

    In order to detect the invisible leaking gas that is usually dangerous and easily leads to fire or explosion in time, many new technologies have arisen in the recent years, among which the infrared video based gas leak detection is widely recognized as a viable tool. However, all the moving regions of a video frame can be detected as leaking gas regions by the existing infrared video based gas leak detection methods, without discriminating the property of each detected region, e.g., a walking person in a video frame may be also detected as gas by the current gas leak detection methods.To solve this problem, we propose a novel infrared video based gas leak detection method in this paper, which is able to effectively suppress strong motion disturbances.Firstly, the Gaussian mixture model(GMM) is used to establish the background model.Then due to the observation that the shapes of gas regions are different from most rigid moving objects, we modify the Features From Accelerated Segment Test (FAST) algorithm and use the modified FAST (mFAST) features to describe each connected component. In view of the fact that the statistical property of the mFAST features extracted from gas regions is different from that of other motion regions, we propose the Pixel-Per-Points (PPP) condition to further select candidate connected components.Experimental results show that the algorithm is able to effectively suppress most strong motion disturbances and achieve real-time leaking gas detection.

  6. A DDoS Attack Detection Method Based on Hybrid Heterogeneous Multiclassifier Ensemble Learning

    Directory of Open Access Journals (Sweden)

    Bin Jia

    2017-01-01

    Full Text Available The explosive growth of network traffic and its multitype on Internet have brought new and severe challenges to DDoS attack detection. To get the higher True Negative Rate (TNR, accuracy, and precision and to guarantee the robustness, stability, and universality of detection system, in this paper, we propose a DDoS attack detection method based on hybrid heterogeneous multiclassifier ensemble learning and design a heuristic detection algorithm based on Singular Value Decomposition (SVD to construct our detection system. Experimental results show that our detection method is excellent in TNR, accuracy, and precision. Therefore, our algorithm has good detective performance for DDoS attack. Through the comparisons with Random Forest, k-Nearest Neighbor (k-NN, and Bagging comprising the component classifiers when the three algorithms are used alone by SVD and by un-SVD, it is shown that our model is superior to the state-of-the-art attack detection techniques in system generalization ability, detection stability, and overall detection performance.

  7. Pornographic information of Internet views detection method based on the connected areas

    Science.gov (United States)

    Wang, Huibai; Fan, Ajie

    2017-01-01

    Nowadays online porn video broadcasting and downloading is very popular. In view of the widespread phenomenon of Internet pornography, this paper proposed a new method of pornographic video detection based on connected areas. Firstly, decode the video into a serious of static images and detect skin color on the extracted key frames. If the area of skin color reaches a certain threshold, use the AdaBoost algorithm to detect the human face. Judge the connectivity of the human face and the large area of skin color to determine whether detect the sensitive area finally. The experimental results show that the method can effectively remove the non-pornographic videos contain human who wear less. This method can improve the efficiency and reduce the workload of detection.

  8. An operant-based detection method for inferring tinnitus in mice.

    Science.gov (United States)

    Zuo, Hongyan; Lei, Debin; Sivaramakrishnan, Shobhana; Howie, Benjamin; Mulvany, Jessica; Bao, Jianxin

    2017-11-01

    Subjective tinnitus is a hearing disorder in which a person perceives sound when no external sound is present. It can be acute or chronic. Because our current understanding of its pathology is incomplete, no effective cures have yet been established. Mouse models are useful for studying the pathophysiology of tinnitus as well as for developing therapeutic treatments. We have developed a new method for determining acute and chronic tinnitus in mice, called sound-based avoidance detection (SBAD). The SBAD method utilizes one paradigm to detect tinnitus and another paradigm to monitor possible confounding factors, such as motor impairment, loss of motivation, and deficits in learning and memory. The SBAD method has succeeded in monitoring both acute and chronic tinnitus in mice. Its detection ability is further validated by functional studies demonstrating an abnormal increase in neuronal activity in the inferior colliculus of mice that had previously been identified as having tinnitus by the SBAD method. The SBAD method provides a new means by which investigators can detect tinnitus in a single mouse accurately and with more control over potential confounding factors than existing methods. This work establishes a new behavioral method for detecting tinnitus in mice. The detection outcome is consistent with functional validation. One key advantage of mouse models is they provide researchers the opportunity to utilize an extensive array of genetic tools. This new method could lead to a deeper understanding of the molecular pathways underlying tinnitus pathology. Copyright © 2017 Elsevier B.V. All rights reserved.

  9. Remote sensing image ship target detection method based on visual attention model

    Science.gov (United States)

    Sun, Yuejiao; Lei, Wuhu; Ren, Xiaodong

    2017-11-01

    The traditional methods of detecting ship targets in remote sensing images mostly use sliding window to search the whole image comprehensively. However, the target usually occupies only a small fraction of the image. This method has high computational complexity for large format visible image data. The bottom-up selective attention mechanism can selectively allocate computing resources according to visual stimuli, thus improving the computational efficiency and reducing the difficulty of analysis. Considering of that, a method of ship target detection in remote sensing images based on visual attention model was proposed in this paper. The experimental results show that the proposed method can reduce the computational complexity while improving the detection accuracy, and improve the detection efficiency of ship targets in remote sensing images.

  10. Early detection of pharmacovigilance signals with automated methods based on false discovery rates: a comparative study.

    Science.gov (United States)

    Ahmed, Ismaïl; Thiessard, Frantz; Miremont-Salamé, Ghada; Haramburu, Françoise; Kreft-Jais, Carmen; Bégaud, Bernard; Tubert-Bitter, Pascale

    2012-06-01

    Improving the detection of drug safety signals has led several pharmacovigilance regulatory agencies to incorporate automated quantitative methods into their spontaneous reporting management systems. The three largest worldwide pharmacovigilance databases are routinely screened by the lower bound of the 95% confidence interval of proportional reporting ratio (PRR₀₂.₅), the 2.5% quantile of the Information Component (IC₀₂.₅) or the 5% quantile of the Gamma Poisson Shrinker (GPS₀₅). More recently, Bayesian and non-Bayesian False Discovery Rate (FDR)-based methods were proposed that address the arbitrariness of thresholds and allow for a built-in estimate of the FDR. These methods were also shown through simulation studies to be interesting alternatives to the currently used methods. The objective of this work was twofold. Based on an extensive retrospective study, we compared PRR₀₂.₅, GPS₀₅ and IC₀₂.₅ with two FDR-based methods derived from the Fisher's exact test and the GPS model (GPS(pH0) [posterior probability of the null hypothesis H₀ calculated from the Gamma Poisson Shrinker model]). Secondly, restricting the analysis to GPS(pH0), we aimed to evaluate the added value of using automated signal detection tools compared with 'traditional' methods, i.e. non-automated surveillance operated by pharmacovigilance experts. The analysis was performed sequentially, i.e. every month, and retrospectively on the whole French pharmacovigilance database over the period 1 January 1996-1 July 2002. Evaluation was based on a list of 243 reference signals (RSs) corresponding to investigations launched by the French Pharmacovigilance Technical Committee (PhVTC) during the same period. The comparison of detection methods was made on the basis of the number of RSs detected as well as the time to detection. Results comparing the five automated quantitative methods were in favour of GPS(pH0) in terms of both number of detections of true signals and

  11. Multi person detection and tracking based on hierarchical level-set method

    Science.gov (United States)

    Khraief, Chadia; Benzarti, Faouzi; Amiri, Hamid

    2018-04-01

    In this paper, we propose an efficient unsupervised method for mutli-person tracking based on hierarchical level-set approach. The proposed method uses both edge and region information in order to effectively detect objects. The persons are tracked on each frame of the sequence by minimizing an energy functional that combines color, texture and shape information. These features are enrolled in covariance matrix as region descriptor. The present method is fully automated without the need to manually specify the initial contour of Level-set. It is based on combined person detection and background subtraction methods. The edge-based is employed to maintain a stable evolution, guide the segmentation towards apparent boundaries and inhibit regions fusion. The computational cost of level-set is reduced by using narrow band technique. Many experimental results are performed on challenging video sequences and show the effectiveness of the proposed method.

  12. Doppler Radar Vital Signs Detection Method Based on Higher Order Cyclostationary.

    Science.gov (United States)

    Yu, Zhibin; Zhao, Duo; Zhang, Zhiqiang

    2017-12-26

    Due to the non-contact nature, using Doppler radar sensors to detect vital signs such as heart and respiration rates of a human subject is getting more and more attention. However, the related detection-method research meets lots of challenges due to electromagnetic interferences, clutter and random motion interferences. In this paper, a novel third-order cyclic cummulant (TOCC) detection method, which is insensitive to Gaussian interference and non-cyclic signals, is proposed to investigate the heart and respiration rate based on continuous wave Doppler radars. The k -th order cyclostationary properties of the radar signal with hidden periodicities and random motions are analyzed. The third-order cyclostationary detection theory of the heart and respiration rate is studied. Experimental results show that the third-order cyclostationary approach has better estimation accuracy for detecting the vital signs from the received radar signal under low SNR, strong clutter noise and random motion interferences.

  13. Leak detection method for long pipeline based on dynamic pressure and wavelet analysis

    Energy Technology Data Exchange (ETDEWEB)

    Xu, Bin; Wang, Likun; Wang, Hongchao; Xiong, Min; Yu, Dongliang; Tan, Dongjie [RnD center of PetroChina Pipeline Company, Langfang, Hebei, (China)

    2010-07-01

    Leaks appear frequently in pipelines, raising the possibility of safety issues. The detection of pipeline leakage is very important for the pipeline industry. This paper investigated a leak detection method on a long pipeline using a dynamic pressure sensor. A new leakage system is proposed based on the measurements obtained from this dynamic pressure sensor. The data were analyzed using the wavelet transformation method. First, the signal provided by the pressure sensor its denoised and then leaks are detected from the presence of singularities in the signal. Field tests were carried out on a product oil pipeline of 94 km length. The in-field test results showed that the minimum ratio of detectable leakage is 0.6 % of throughput and the location error is below 300 m. The response time is less than 120 seconds. This new system has been applied in 5000 km pipelines in China and is proving its efficiency in detecting leak points.

  14. Local region power spectrum-based unfocused ship detection method in synthetic aperture radar images

    Science.gov (United States)

    Wei, Xiangfei; Wang, Xiaoqing; Chong, Jinsong

    2018-01-01

    Ships on synthetic aperture radar (SAR) images will be severely defocused and their energy will disperse into numerous resolution cells under long SAR integration time. Therefore, the image intensity of ships is weak and sometimes even overwhelmed by sea clutter on SAR image. Consequently, it is hard to detect the ships from SAR intensity images. A ship detection method based on local region power spectrum of SAR complex image is proposed. Although the energies of the ships are dispersed on SAR intensity images, their spectral energies are rather concentrated or will cause the power spectra of local areas of SAR images to deviate from that of sea surface background. Therefore, the key idea of the proposed method is to detect ships via the power spectra distortion of local areas of SAR images. The local region power spectrum of a moving target on SAR image is analyzed and the way to obtain the detection threshold through the probability density function (pdf) of the power spectrum is illustrated. Numerical P- and L-band airborne SAR ocean data are utilized and the detection results are also illustrated. Results show that the proposed method can well detect the unfocused ships, with a detection rate of 93.6% and a false-alarm rate of 8.6%. Moreover, by comparing with some other algorithms, it indicates that the proposed method performs better under long SAR integration time. Finally, the applicability of the proposed method and the way of parameters selection are also discussed.

  15. A fast button surface defects detection method based on convolutional neural network

    Science.gov (United States)

    Liu, Lizhe; Cao, Danhua; Wu, Songlin; Wu, Yubin; Wei, Taoran

    2018-01-01

    Considering the complexity of the button surface texture and the variety of buttons and defects, we propose a fast visual method for button surface defect detection, based on convolutional neural network (CNN). CNN has the ability to extract the essential features by training, avoiding designing complex feature operators adapted to different kinds of buttons, textures and defects. Firstly, we obtain the normalized button region and then use HOG-SVM method to identify the front and back side of the button. Finally, a convolutional neural network is developed to recognize the defects. Aiming at detecting the subtle defects, we propose a network structure with multiple feature channels input. To deal with the defects of different scales, we take a strategy of multi-scale image block detection. The experimental results show that our method is valid for a variety of buttons and able to recognize all kinds of defects that have occurred, including dent, crack, stain, hole, wrong paint and uneven. The detection rate exceeds 96%, which is much better than traditional methods based on SVM and methods based on template match. Our method can reach the speed of 5 fps on DSP based smart camera with 600 MHz frequency.

  16. Cellular Neural Network-Based Methods for Distributed Network Intrusion Detection

    Directory of Open Access Journals (Sweden)

    Kang Xie

    2015-01-01

    Full Text Available According to the problems of current distributed architecture intrusion detection systems (DIDS, a new online distributed intrusion detection model based on cellular neural network (CNN was proposed, in which discrete-time CNN (DTCNN was used as weak classifier in each local node and state-controlled CNN (SCCNN was used as global detection method, respectively. We further proposed a new method for design template parameters of SCCNN via solving Linear Matrix Inequality. Experimental results based on KDD CUP 99 dataset show its feasibility and effectiveness. Emerging evidence has indicated that this new approach is affordable to parallelism and analog very large scale integration (VLSI implementation which allows the distributed intrusion detection to be performed better.

  17. Detection method of flexion relaxation phenomenon based on wavelets for patients with low back pain

    Science.gov (United States)

    Nougarou, François; Massicotte, Daniel; Descarreaux, Martin

    2012-12-01

    The flexion relaxation phenomenon (FRP) can be defined as a reduction or silence of myoelectric activity of the lumbar erector spinae muscle during full trunk flexion. It is typically absent in patients with chronic low back pain (LBP). Before any broad clinical utilization of this neuromuscular response can be made, effective, standardized, and accurate methods of identifying FRP limits are needed. However, this phenomenon is clearly more difficult to detect for LBP patients than for healthy patients. The main goal of this study is to develop an automated method based on wavelet transformation that would improve time point limits detection of surface electromyography signals of the FRP in case of LBP patients. Conventional visual identification and proposed automated methods of time point limits detection of relaxation phase were compared on experimental data using criteria of accuracy and repeatability based on physiological properties. The evaluation demonstrates that the use of wavelet transform (WT) yields better results than methods without wavelet decomposition. Furthermore, methods based on wavelet per packet transform are more effective than algorithms employing discrete WT. Compared to visual detection, in addition to demonstrating an obvious saving of time, the use of wavelet per packet transform improves the accuracy and repeatability in the detection of the FRP limits. These results clearly highlight the value of the proposed technique in identifying onset and offset of the flexion relaxation response in LBP subjects.

  18. Hybrid islanding detection method by using grid impedance estimation in parallel-inverters-based microgrid

    DEFF Research Database (Denmark)

    Ghzaiel, Walid; Jebali-Ben Ghorbal, Manel; Slama-Belkhodja, Ilhem

    2014-01-01

    This paper presents a hybrid islanding detection algorithm integrated on the distributed generation unit more close to the point of common coupling of a Microgrid based on parallel inverters where one of them is responsible to control the system. The method is based on resonance excitation under...... parameters, both resistive and inductive parts, from the injected resonance frequency determination. Finally, the inverter will disconnect the microgrid from the faulty grid and reconnect the parallel inverter system to the controllable distributed system in order to ensure high power quality. This paper...... shows that grid impedance variation detection estimation can be an efficient method for islanding detection in microgrid systems. Theoretical analysis and simulation results are presented to validate the proposed method....

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

    International Nuclear Information System (INIS)

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

    2014-01-01

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

  20. A novel method based on learning automata for automatic lesion detection in breast magnetic resonance imaging.

    Science.gov (United States)

    Salehi, Leila; Azmi, Reza

    2014-07-01

    Breast cancer continues to be a significant public health problem in the world. Early detection is the key for improving breast cancer prognosis. In this way, magnetic resonance imaging (MRI) is emerging as a powerful tool for the detection of breast cancer. Breast MRI presently has two major challenges. First, its specificity is relatively poor, and it detects many false positives (FPs). Second, the method involves acquiring several high-resolution image volumes before, during, and after the injection of a contrast agent. The large volume of data makes the task of interpretation by the radiologist both complex and time-consuming. These challenges have led to the development of the computer-aided detection systems to improve the efficiency and accuracy of the interpretation process. Detection of suspicious regions of interests (ROIs) is a critical preprocessing step in dynamic contrast-enhanced (DCE)-MRI data evaluation. In this regard, this paper introduces a new automatic method to detect the suspicious ROIs for breast DCE-MRI based on region growing. The results indicate that the proposed method is thoroughly able to identify suspicious regions (accuracy of 75.39 ± 3.37 on PIDER breast MRI dataset). Furthermore, the FP per image in this method is averagely 7.92, which shows considerable improvement comparing to other methods like ROI hunter.

  1. Multiple-Features-Based Semisupervised Clustering DDoS Detection Method

    Directory of Open Access Journals (Sweden)

    Yonghao Gu

    2017-01-01

    Full Text Available DDoS attack stream from different agent host converged at victim host will become very large, which will lead to system halt or network congestion. Therefore, it is necessary to propose an effective method to detect the DDoS attack behavior from the massive data stream. In order to solve the problem that large numbers of labeled data are not provided in supervised learning method, and the relatively low detection accuracy and convergence speed of unsupervised k-means algorithm, this paper presents a semisupervised clustering detection method using multiple features. In this detection method, we firstly select three features according to the characteristics of DDoS attacks to form detection feature vector. Then, Multiple-Features-Based Constrained-K-Means (MF-CKM algorithm is proposed based on semisupervised clustering. Finally, using MIT Laboratory Scenario (DDoS 1.0 data set, we verify that the proposed method can improve the convergence speed and accuracy of the algorithm under the condition of using a small amount of labeled data sets.

  2. Grid impedance estimation based hybrid islanding detection method for AC microgrids

    DEFF Research Database (Denmark)

    Ghzaiel, Walid; Jebali-Ben Ghorbal, Manel; Slama-Belkhodja, Ilhem

    2017-01-01

    This paper focuses on a hybrid islanding detection algorithm for parallel-inverters-based microgrids. The proposed algorithm is implemented on the unit ensuring the control of the intelligent bypass switch connecting or disconnecting the microgrid from the utility. This method employs a grid...... to avoid interactions with other units. The selected inverter will be the one closest to the controllable distributed generation system or to a healthy grid side in case of meshed microgrid with multiple-grid connections. The detection algorithm is applied to quickly detect the resonance phenomena, so...

  3. A method based on temporal concept analysis for detecting and profiling human trafficking suspects

    NARCIS (Netherlands)

    Poelmans, J.; Elzinga, P.; Viaene, S.; Dedene, G.; Hamza, M.H.

    2010-01-01

    Human trafficking and forced prostitution are a serious problem for the Amsterdam-Amstelland police (the Netherlands). In this paper, we present a method based on Temporal Concept Analysis for detecting and profiling human trafficking suspects. Using traditional Formal Concept Analysis, we first

  4. A novel intrusion detection method based on OCSVM and K-means recursive clustering

    Directory of Open Access Journals (Sweden)

    Leandros A. Maglaras

    2015-01-01

    Full Text Available In this paper we present an intrusion detection module capable of detecting malicious network traffic in a SCADA (Supervisory Control and Data Acquisition system, based on the combination of One-Class Support Vector Machine (OCSVM with RBF kernel and recursive k-means clustering. Important parameters of OCSVM, such as Gaussian width o and parameter v affect the performance of the classifier. Tuning of these parameters is of great importance in order to avoid false positives and over fitting. The combination of OCSVM with recursive k- means clustering leads the proposed intrusion detection module to distinguish real alarms from possible attacks regardless of the values of parameters o and v, making it ideal for real-time intrusion detection mechanisms for SCADA systems. Extensive simulations have been conducted with datasets extracted from small and medium sized HTB SCADA testbeds, in order to compare the accuracy, false alarm rate and execution time against the base line OCSVM method.

  5. Full-waveform detection of non-impulsive seismic events based on time-reversal methods

    Science.gov (United States)

    Solano, Ericka Alinne; Hjörleifsdóttir, Vala; Liu, Qinya

    2017-12-01

    We present a full-waveform detection method for non-impulsive seismic events, based on time-reversal principles. We use the strain Green's tensor as a matched filter, correlating it with continuous observed seismograms, to detect non-impulsive seismic events. We show that this is mathematically equivalent to an adjoint method for detecting earthquakes. We define the detection function, a scalar valued function, which depends on the stacked correlations for a group of stations. Event detections are given by the times at which the amplitude of the detection function exceeds a given value relative to the noise level. The method can make use of the whole seismic waveform or any combination of time-windows with different filters. It is expected to have an advantage compared to traditional detection methods for events that do not produce energetic and impulsive P waves, for example glacial events, landslides, volcanic events and transform-fault earthquakes for events which velocity structure along the path is relatively well known. Furthermore, the method has advantages over empirical Greens functions template matching methods, as it does not depend on records from previously detected events, and therefore is not limited to events occurring in similar regions and with similar focal mechanisms as these events. The method is not specific to any particular way of calculating the synthetic seismograms, and therefore complicated structural models can be used. This is particularly beneficial for intermediate size events that are registered on regional networks, for which the effect of lateral structure on the waveforms can be significant. To demonstrate the feasibility of the method, we apply it to two different areas located along the mid-oceanic ridge system west of Mexico where non-impulsive events have been reported. The first study area is between Clipperton and Siqueiros transform faults (9°N), during the time of two earthquake swarms, occurring in March 2012 and May

  6. A Novel Method for Surface Defect Detection of Photovoltaic Module Based on Independent Component Analysis

    Directory of Open Access Journals (Sweden)

    Xuewu Zhang

    2013-01-01

    Full Text Available This paper proposed a new method for surface defect detection of photovoltaic module based on independent component analysis (ICA reconstruction algorithm. Firstly, a faultless image is used as the training image. The demixing matrix and corresponding ICs are obtained by applying the ICA in the training image. Then we reorder the ICs according to the range values and reform the de-mixing matrix. Then the reformed de-mixing matrix is used to reconstruct the defect image. The resulting image can remove the background structures and enhance the local anomalies. Experimental results have shown that the proposed method can effectively detect the presence of defects in periodically patterned surfaces.

  7. A New Method Based on Two-Stage Detection Mechanism for Detecting Ships in High-Resolution SAR Images

    Directory of Open Access Journals (Sweden)

    Xu Yongli

    2017-01-01

    Full Text Available Ship detection in synthetic aperture radar (SAR remote sensing images, being a fundamental but challenging problem in the field of satellite image analysis, plays an important role for a wide range of applications and is receiving significant attention in recent years. Aiming at the requirements of ship detection in high-resolution SAR images, the accuracy, the intelligent level, a better real-time operation and processing efficiency, The characteristics of ocean background and ship target in high-resolution SAR images were analyzed, we put forward a ship detection algorithm in high-resolution SAR images. The algorithm consists of two detection stages: The first step designs a pre-training classifier based on improved spectral residual visual model to obtain the visual salient regions containing ship targets quickly, then achieve the purpose of probably detection of ships. In the second stage, considering the Bayesian theory of binary hypothesis detection, a local maximum posterior probability (MAP classifier is designed for the classification of pixels. After the parameter estimation and judgment criterion, the classification of pixels are carried out in the target areas to achieve the classification of two types of pixels in the salient regions. In the paper, several types of satellite image data, such as TerraSAR-X (TS-X, Radarsat-2, are used to evaluate the performance of detection methods. Comparing with classical CFAR detection algorithms, experimental results show that the algorithm can achieve a better effect of suppressing false alarms, which caused by the speckle noise and ocean clutter background inhomogeneity. At the same time, the detection speed is increased by 25% to 45%.

  8. 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.

  9. A Mass Spectrometric Analysis Method Based on PPCA and SVM for Early Detection of Ovarian Cancer.

    Science.gov (United States)

    Wu, Jiang; Ji, Yanju; Zhao, Ling; Ji, Mengying; Ye, Zhuang; Li, Suyi

    2016-01-01

    Background. Surfaced-enhanced laser desorption-ionization-time of flight mass spectrometry (SELDI-TOF-MS) technology plays an important role in the early diagnosis of ovarian cancer. However, the raw MS data is highly dimensional and redundant. Therefore, it is necessary to study rapid and accurate detection methods from the massive MS data. Methods. The clinical data set used in the experiments for early cancer detection consisted of 216 SELDI-TOF-MS samples. An MS analysis method based on probabilistic principal components analysis (PPCA) and support vector machine (SVM) was proposed and applied to the ovarian cancer early classification in the data set. Additionally, by the same data set, we also established a traditional PCA-SVM model. Finally we compared the two models in detection accuracy, specificity, and sensitivity. Results. Using independent training and testing experiments 10 times to evaluate the ovarian cancer detection models, the average prediction accuracy, sensitivity, and specificity of the PCA-SVM model were 83.34%, 82.70%, and 83.88%, respectively. In contrast, those of the PPCA-SVM model were 90.80%, 92.98%, and 88.97%, respectively. Conclusions. The PPCA-SVM model had better detection performance. And the model combined with the SELDI-TOF-MS technology had a prospect in early clinical detection and diagnosis of ovarian cancer.

  10. EEMD-based multiscale ICA method for slewing bearing fault detection and diagnosis

    Science.gov (United States)

    Žvokelj, Matej; Zupan, Samo; Prebil, Ivan

    2016-05-01

    A novel multivariate and multiscale statistical process monitoring method is proposed with the aim of detecting incipient failures in large slewing bearings, where subjective influence plays a minor role. The proposed method integrates the strengths of the Independent Component Analysis (ICA) multivariate monitoring approach with the benefits of Ensemble Empirical Mode Decomposition (EEMD), which adaptively decomposes signals into different time scales and can thus cope with multiscale system dynamics. The method, which was named EEMD-based multiscale ICA (EEMD-MSICA), not only enables bearing fault detection but also offers a mechanism of multivariate signal denoising and, in combination with the Envelope Analysis (EA), a diagnostic tool. The multiscale nature of the proposed approach makes the method convenient to cope with data which emanate from bearings in complex real-world rotating machinery and frequently represent the cumulative effect of many underlying phenomena occupying different regions in the time-frequency plane. The efficiency of the proposed method was tested on simulated as well as real vibration and Acoustic Emission (AE) signals obtained through conducting an accelerated run-to-failure lifetime experiment on a purpose-built laboratory slewing bearing test stand. The ability to detect and locate the early-stage rolling-sliding contact fatigue failure of the bearing indicates that AE and vibration signals carry sufficient information on the bearing condition and that the developed EEMD-MSICA method is able to effectively extract it, thereby representing a reliable bearing fault detection and diagnosis strategy.

  11. Detection-Discrimination Method for Multiple Repeater False Targets Based on Radar Polarization Echoes

    Directory of Open Access Journals (Sweden)

    Z. W. ZONG

    2014-04-01

    Full Text Available Multiple repeat false targets (RFTs, created by the digital radio frequency memory (DRFM system of jammer, are widely used in practical to effectively exhaust the limited tracking and discrimination resource of defence radar. In this paper, common characteristic of radar polarization echoes of multiple RFTs is used for target recognition. Based on the echoes from two receiving polarization channels, the instantaneous polarization radio (IPR is defined and its variance is derived by employing Taylor series expansion. A detection-discrimination method is designed based on probability grids. By using the data from microwave anechoic chamber, the detection threshold of the method is confirmed. Theoretical analysis and simulations indicate that the method is valid and feasible. Furthermore, the estimation performance of IPRs of RFTs due to the influence of signal noise ratio (SNR is also covered.

  12. A speeded-up saliency region-based contrast detection method for small targets

    Science.gov (United States)

    Li, Zhengjie; Zhang, Haiying; Bai, Jiaojiao; Zhou, Zhongjun; Zheng, Huihuang

    2018-04-01

    To cope with the rapid development of the real applications for infrared small targets, the researchers have tried their best to pursue more robust detection methods. At present, the contrast measure-based method has become a promising research branch. Following the framework, in this paper, a speeded-up contrast measure scheme is proposed based on the saliency detection and density clustering. First, the saliency region is segmented by saliency detection method, and then, the Multi-scale contrast calculation is carried out on it instead of traversing the whole image. Second, the target with a certain "integrity" property in spatial is exploited to distinguish the target from the isolated noises by density clustering. Finally, the targets are detected by a self-adaptation threshold. Compared with time-consuming MPCM (Multiscale Patch Contrast Map), the time cost of the speeded-up version is within a few seconds. Additional, due to the use of "clustering segmentation", the false alarm caused by heavy noises can be restrained to a lower level. The experiments show that our method has a satisfied FASR (False alarm suppression ratio) and real-time performance compared with the state-of-art algorithms no matter in cloudy sky or sea-sky background.

  13. A Method Based on Multi-Sensor Data Fusion for Fault Detection of Planetary Gearboxes

    Directory of Open Access Journals (Sweden)

    Detong Kong

    2012-02-01

    Full Text Available Studies on fault detection and diagnosis of planetary gearboxes are quite limited compared with those of fixed-axis gearboxes. Different from fixed-axis gearboxes, planetary gearboxes exhibit unique behaviors, which invalidate fault diagnosis methods that work well for fixed-axis gearboxes. It is a fact that for systems as complex as planetary gearboxes, multiple sensors mounted on different locations provide complementary information on the health condition of the systems. On this basis, a fault detection method based on multi-sensor data fusion is introduced in this paper. In this method, two features developed for planetary gearboxes are used to characterize the gear health conditions, and an adaptive neuro-fuzzy inference system (ANFIS is utilized to fuse all features from different sensors. In order to demonstrate the effectiveness of the proposed method, experiments are carried out on a planetary gearbox test rig, on which multiple accelerometers are mounted for data collection. The comparisons between the proposed method and the methods based on individual sensors show that the former achieves much higher accuracies in detecting planetary gearbox faults.

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

    Science.gov (United States)

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

    2014-03-01

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

  15. An infrared small target detection method based on multiscale local homogeneity measure

    Science.gov (United States)

    Nie, Jinyan; Qu, Shaocheng; Wei, Yantao; Zhang, Liming; Deng, Lizhen

    2018-05-01

    Infrared (IR) small target detection plays an important role in the field of image detection area owing to its intrinsic characteristics. This paper presents a multiscale local homogeneity measure (MLHM) for infrared small target detection, which can enhance the performance of IR small target detection system. Firstly, intra-patch homogeneity of the target itself and the inter-patch heterogeneity between target and the local background regions are integrated to enhance the significant of small target. Secondly, a multiscale measure based on local regions is proposed to obtain the most appropriate response. Finally, an adaptive threshold method is applied to small target segmentation. Experimental results on three different scenarios indicate that the MLHM has good performance under the interference of strong noise.

  16. A Shellcode Detection Method Based on Full Native API Sequence and Support Vector Machine

    Science.gov (United States)

    Cheng, Yixuan; Fan, Wenqing; Huang, Wei; An, Jing

    2017-09-01

    Dynamic monitoring the behavior of a program is widely used to discriminate between benign program and malware. It is usually based on the dynamic characteristics of a program, such as API call sequence or API call frequency to judge. The key innovation of this paper is to consider the full Native API sequence and use the support vector machine to detect the shellcode. We also use the Markov chain to extract and digitize Native API sequence features. Our experimental results show that the method proposed in this paper has high accuracy and low detection rate.

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

    Directory of Open Access Journals (Sweden)

    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.

  18. A hybrid network-based method for the detection of disease-related genes

    Science.gov (United States)

    Cui, Ying; Cai, Meng; Dai, Yang; Stanley, H. Eugene

    2018-02-01

    Detecting disease-related genes is crucial in disease diagnosis and drug design. The accepted view is that neighbors of a disease-causing gene in a molecular network tend to cause the same or similar diseases, and network-based methods have been recently developed to identify novel hereditary disease-genes in available biomedical networks. Despite the steady increase in the discovery of disease-associated genes, there is still a large fraction of disease genes that remains under the tip of the iceberg. In this paper we exploit the topological properties of the protein-protein interaction (PPI) network to detect disease-related genes. We compute, analyze, and compare the topological properties of disease genes with non-disease genes in PPI networks. We also design an improved random forest classifier based on these network topological features, and a cross-validation test confirms that our method performs better than previous similar studies.

  19. A method of detection to the grinding wheel layer thickness based on computer vision

    Science.gov (United States)

    Ji, Yuchen; Fu, Luhua; Yang, Dujuan; Wang, Lei; Liu, Changjie; Wang, Zhong

    2018-01-01

    This paper proposed a method of detection to the grinding wheel layer thickness based on computer vision. A camera is used to capture images of grinding wheel layer on the whole circle. Forward lighting and back lighting are used to enables a clear image to be acquired. Image processing is then executed on the images captured, which consists of image preprocessing, binarization and subpixel subdivision. The aim of binarization is to help the location of a chord and the corresponding ring width. After subpixel subdivision, the thickness of the grinding layer can be calculated finally. Compared with methods usually used to detect grinding wheel wear, method in this paper can directly and quickly get the information of thickness. Also, the eccentric error and the error of pixel equivalent are discussed in this paper.

  20. A DDoS Attack Detection Method Based on SVM in Software Defined Network

    Directory of Open Access Journals (Sweden)

    Jin Ye

    2018-01-01

    Full Text Available The detection of DDoS attacks is an important topic in the field of network security. The occurrence of software defined network (SDN (Zhang et al., 2018 brings up some novel methods to this topic in which some deep learning algorithm is adopted to model the attack behavior based on collecting from the SDN controller. However, the existing methods such as neural network algorithm are not practical enough to be applied. In this paper, the SDN environment by mininet and floodlight (Ning et al., 2014 simulation platform is constructed, 6-tuple characteristic values of the switch flow table is extracted, and then DDoS attack model is built by combining the SVM classification algorithms. The experiments show that average accuracy rate of our method is 95.24% with a small amount of flow collecting. Our work is of good value for the detection of DDoS attack in SDN.

  1. A new method of small target detection based on neural network

    Science.gov (United States)

    Hu, Jing; Hu, Yongli; Lu, Xinxin

    2018-02-01

    The detection and tracking of moving dim target in infrared image have been an research hotspot for many years. The target in each frame of images only occupies several pixels without any shape and structure information. Moreover, infrared small target is often submerged in complicated background with low signal-to-clutter ratio, making the detection very difficult. Different backgrounds exhibit different statistical properties, making it becomes extremely complex to detect the target. If the threshold segmentation is not reasonable, there may be more noise points in the final detection, which is unfavorable for the detection of the trajectory of the target. Single-frame target detection may not be able to obtain the desired target and cause high false alarm rate. We believe the combination of suspicious target detection spatially in each frame and temporal association for target tracking will increase reliability of tracking dim target. The detection of dim target is mainly divided into two parts, In the first part, we adopt bilateral filtering method in background suppression, after the threshold segmentation, the suspicious target in each frame are extracted, then we use LSTM(long short term memory) neural network to predict coordinates of target of the next frame. It is a brand-new method base on the movement characteristic of the target in sequence images which could respond to the changes in the relationship between past and future values of the values. Simulation results demonstrate proposed algorithm can effectively predict the trajectory of the moving small target and work efficiently and robustly with low false alarm.

  2. Detecting Malware with an Ensemble Method Based on Deep Neural Network

    Directory of Open Access Journals (Sweden)

    Jinpei Yan

    2018-01-01

    Full Text Available Malware detection plays a crucial role in computer security. Recent researches mainly use machine learning based methods heavily relying on domain knowledge for manually extracting malicious features. In this paper, we propose MalNet, a novel malware detection method that learns features automatically from the raw data. Concretely, we first generate a grayscale image from malware file, meanwhile extracting its opcode sequences with the decompilation tool IDA. Then MalNet uses CNN and LSTM networks to learn from grayscale image and opcode sequence, respectively, and takes a stacking ensemble for malware classification. We perform experiments on more than 40,000 samples including 20,650 benign files collected from online software providers and 21,736 malwares provided by Microsoft. The evaluation result shows that MalNet achieves 99.88% validation accuracy for malware detection. In addition, we also take malware family classification experiment on 9 malware families to compare MalNet with other related works, in which MalNet outperforms most of related works with 99.36% detection accuracy and achieves a considerable speed-up on detecting efficiency comparing with two state-of-the-art results on Microsoft malware dataset.

  3. Effects of rust in the crack face on crack detection based on Sonic-IR method

    International Nuclear Information System (INIS)

    Harai, Y.; Izumi, Y.; Tanabe, H.; Takamatsu, T.; Sakagami, T.

    2015-01-01

    Sonic-IR, which is based on the thermographic detection of the temperature rise due to frictional heating at the defect faces under ultrasonic excitation, has an advantage in the detection of closed and small defects. However, this method has a lot of nuclear factors relating to heat generation. In this study, effects of rust in the crack faces on the crack detection based on the sonic-IR method is experimentally investigated by using crack specimens. The heat generation by ultrasonic excitation was observed regularly during rust accelerated test using original device. The distribution of temperature change around the crack was changed with the progress of rust. This change in heat generation, it believed to be due to change in the contact state of the crack surface due to rust. As a result, it was found that heat generation by ultrasonic excitation is affected by rust in the crack faces. And it was also found that crack detection can be conducted by sonic-IR even if rust was generated in the crack faces. (author)

  4. A Sea-Sky Line Detection Method for Unmanned Surface Vehicles Based on Gradient Saliency.

    Science.gov (United States)

    Wang, Bo; Su, Yumin; Wan, Lei

    2016-04-15

    Special features in real marine environments such as cloud clutter, sea glint and weather conditions always result in various kinds of interference in optical images, which make it very difficult for unmanned surface vehicles (USVs) to detect the sea-sky line (SSL) accurately. To solve this problem a saliency-based SSL detection method is proposed. Through the computation of gradient saliency the line features of SSL are enhanced effectively, while other interference factors are relatively suppressed, and line support regions are obtained by a region growing method on gradient orientation. The SSL identification is achieved according to region contrast, line segment length and orientation features, and optimal state estimation of SSL detection is implemented by introducing a cubature Kalman filter (CKF). In the end, the proposed method is tested on a benchmark dataset from the "XL" USV in a real marine environment, and the experimental results demonstrate that the proposed method is significantly superior to other state-of-the-art methods in terms of accuracy rate and real-time performance, and its accuracy and stability are effectively improved by the CKF.

  5. A Sea-Sky Line Detection Method for Unmanned Surface Vehicles Based on Gradient Saliency

    Directory of Open Access Journals (Sweden)

    Bo Wang

    2016-04-01

    Full Text Available Special features in real marine environments such as cloud clutter, sea glint and weather conditions always result in various kinds of interference in optical images, which make it very difficult for unmanned surface vehicles (USVs to detect the sea-sky line (SSL accurately. To solve this problem a saliency-based SSL detection method is proposed. Through the computation of gradient saliency the line features of SSL are enhanced effectively, while other interference factors are relatively suppressed, and line support regions are obtained by a region growing method on gradient orientation. The SSL identification is achieved according to region contrast, line segment length and orientation features, and optimal state estimation of SSL detection is implemented by introducing a cubature Kalman filter (CKF. In the end, the proposed method is tested on a benchmark dataset from the “XL” USV in a real marine environment, and the experimental results demonstrate that the proposed method is significantly superior to other state-of-the-art methods in terms of accuracy rate and real-time performance, and its accuracy and stability are effectively improved by the CKF.

  6. Detection of needle to nerve contact based on electric bioimpedance and machine learning methods.

    Science.gov (United States)

    Kalvoy, Havard; Tronstad, Christian; Ullensvang, Kyrre; Steinfeldt, Thorsten; Sauter, Axel R

    2017-07-01

    In an ongoing project for electrical impedance-based needle guidance we have previously showed in an animal model that intraneural needle positions can be detected with bioimpedance measurement. To enhance the power of this method we in this study have investigated whether an early detection of the needle only touching the nerve also is feasible. Measurement of complex impedance during needle to nerve contact was compared with needle positions in surrounding tissues in a volunteer study on 32 subjects. Classification analysis using Support-Vector Machines demonstrated that discrimination is possible, but that the sensitivity and specificity for the nerve touch algorithm not is at the same level of performance as for intra-neuralintraneural detection.

  7. A Markov blanket-based method for detecting causal SNPs in GWAS

    Directory of Open Access Journals (Sweden)

    Han Bing

    2010-04-01

    Full Text Available Abstract Background Detecting epistatic interactions associated with complex and common diseases can help to improve prevention, diagnosis and treatment of these diseases. With the development of genome-wide association studies (GWAS, designing powerful and robust computational method for identifying epistatic interactions associated with common diseases becomes a great challenge to bioinformatics society, because the study of epistatic interactions often deals with the large size of the genotyped data and the huge amount of combinations of all the possible genetic factors. Most existing computational detection methods are based on the classification capacity of SNP sets, which may fail to identify SNP sets that are strongly associated with the diseases and introduce a lot of false positives. In addition, most methods are not suitable for genome-wide scale studies due to their computational complexity. Results We propose a new Markov Blanket-based method, DASSO-MB (Detection of ASSOciations using Markov Blanket to detect epistatic interactions in case-control GWAS. Markov blanket of a target variable T can completely shield T from all other variables. Thus, we can guarantee that the SNP set detected by DASSO-MB has a strong association with diseases and contains fewest false positives. Furthermore, DASSO-MB uses a heuristic search strategy by calculating the association between variables to avoid the time-consuming training process as in other machine-learning methods. We apply our algorithm to simulated datasets and a real case-control dataset. We compare DASSO-MB to other commonly-used methods and show that our method significantly outperforms other methods and is capable of finding SNPs strongly associated with diseases. Conclusions Our study shows that DASSO-MB can identify a minimal set of causal SNPs associated with diseases, which contains less false positives compared to other existing methods. Given the huge size of genomic dataset

  8. A new detection method based on CFAR and DE for OFPS

    Science.gov (United States)

    Qiu, Zezheng; Zheng, Tong; Qu, Hongquan; Pang, Liping

    2016-09-01

    Optical fiber pre-warning system (OFPS) is widely utilized in pipeline transport fields. The intrusions of OFPS need to be located. In this system, the original signals consist of noises, interferences, and intrusion signals. Here, noises are background and harmless interferences possessing with high power, and the intrusion signals are the main target of detection in this system. Hence, the study stresses on extracting the intrusion signals from the total ones. The proposed method can be divided into two parts, constant false alarm rate (CFAR) and dilation and erosion (DE). The former is applied to eliminate noises, and the latter is to remove interferences. According to some researches, the feature of noise background accords with the CFAR spatial detection. Furthermore, the detection results after CFAR can be presented as a binary image of time and space. Besides, interferences are relatively disconnected. Consequently, they can be eliminated by DE which is introduced from the image processing. To sum up, this novel method is based on CFAR and DE which can eliminate noises and interferences effectively. Moreover, it performs a brilliant detection performance. A series of tests were developed in Men Tou Gou of Beijing, China, and the reliability of proposed method can be verified by these tests.

  9. Evaluation of DNA Extraction Methods Suitable for PCR-based Detection and Genotyping of Clostridium botulinum

    DEFF Research Database (Denmark)

    Auricchio, Bruna; Anniballi, Fabrizio; Fiore, Alfonsina

    2013-01-01

    in terms of cost, time, labor, and supplies. Eleven botulinum toxin–producing clostridia strains and 25 samples (10 food, 13 clinical, and 2 environmental samples) naturally contaminated with botulinum toxin–producing clostridia were used to compare 4 DNA extraction procedures: Chelex® 100 matrix, Phenol......Sufficient quality and quantity of extracted DNA is critical to detecting and performing genotyping of Clostridium botulinum by means of PCR-based methods. An ideal extraction method has to optimize DNA yield, minimize DNA degradation, allow multiple samples to be extracted, and be efficient...

  10. ESR based detection method for irradiated dry fish, tomato soup powder and sweet-meats

    International Nuclear Information System (INIS)

    Brij Bhushan; Warrier, S.B.; Sharma, Arun

    2003-01-01

    Full text: Radiation Processing is increasingly being accepted as one of the most effective and economic method to treat agricultural and horticultural commodities for hygienization and disinfestation purposes and also in overcoming strict quarantine barriers in international trade. At present there is a growing concern about the presence of insecticides and pesticides and their residues in various foods, we consume. In view of this, irradiation, being a physical and cold process, emerges as the best bet towards having an uninterrupted supply of safe and quality food. The process has been endorsed as safe by several international and national bodies. A suitable detection method is however required to meet the basic requirements of consumers and law enforcement authorities, regulating the trade. Dried, sliced Pollack and File fishes were subjected to radiation dose of 4 kGy for elimination of coliforms and for improvement in quality standards during storage. Bones separated served as sample source for ESR based detection method of the radiation treatment. Bones with hard crystalline matrix served as trap for free radicals and facilitated evolution of an ESR based detection method. It showed a linear dose response curve at γ=2.0037, whereas, those from non-irradiated fish fillets failed to show any ESR signal. Re-irradiation helped in calculation of dose delivered to dried fishes. Sachets -containing tomato soup ingredients, including sugars exposed to 0.25 to 2 kGy gamma radiation doses for hygienization and quarantine purposes were used in the experiments. In-pack sugar crystals served as free radicals trap for ESR based detection method for radiation hygienized tomato soup powder. Similarly, it was observed that radiation hygienization of sugar bearing sweet-meats, like Peda (an evaporated milk preparation), Petha (a sugar syrup soaked vegetable preparation) and dry fruits like raisins could be detected using ESR. Suitable methodology was developed to detect

  11. A HYPERSPECTRAL BASED METHOD TO DETECT CANNABIS PLANTATION IN INACCESSIBLE AREAS

    Directory of Open Access Journals (Sweden)

    M. Houmi

    2018-04-01

    Full Text Available The increase in drug use worldwide has led to sophisticated illegal planting methods. Most countries depend on helicopters, and local knowledge to identify such illegal plantations. However, remote sensing techniques can provide special advantages for monitoring the extent of illegal drug production. This paper sought to assess the ability of the Satellite remote sensing to detect Cannabis plantations. This was achieved in two stages: 1- Preprocessing of Hyperspectral data EO-1, and testing the capability to collect the spectral signature of Cannabis in different sites of the study area (Morocco from well-known Cannabis plantation fields. 2- Applying the method of Spectral Angle Mapper (SAM based on a specific angle threshold on Hyperion data EO-1 in well-known Cannabis plantation sites, and other sites with negative Cannabis plantation in another study area (Algeria, to avoid any false Cannabis detection using these spectra. This study emphasizes the benefits of using hyperspectral remote sensing data as an effective detection tool for illegal Cannabis plantation in inaccessible areas based on SAM classification method with a maximum angle (radians less than 0.03.

  12. a Hyperspectral Based Method to Detect Cannabis Plantation in Inaccessible Areas

    Science.gov (United States)

    Houmi, M.; Mohamadi, B.; Balz, T.

    2018-04-01

    The increase in drug use worldwide has led to sophisticated illegal planting methods. Most countries depend on helicopters, and local knowledge to identify such illegal plantations. However, remote sensing techniques can provide special advantages for monitoring the extent of illegal drug production. This paper sought to assess the ability of the Satellite remote sensing to detect Cannabis plantations. This was achieved in two stages: 1- Preprocessing of Hyperspectral data EO-1, and testing the capability to collect the spectral signature of Cannabis in different sites of the study area (Morocco) from well-known Cannabis plantation fields. 2- Applying the method of Spectral Angle Mapper (SAM) based on a specific angle threshold on Hyperion data EO-1 in well-known Cannabis plantation sites, and other sites with negative Cannabis plantation in another study area (Algeria), to avoid any false Cannabis detection using these spectra. This study emphasizes the benefits of using hyperspectral remote sensing data as an effective detection tool for illegal Cannabis plantation in inaccessible areas based on SAM classification method with a maximum angle (radians) less than 0.03.

  13. Development of an aptamer-based concentration method for the detection of Trypanosoma cruzi in blood.

    Directory of Open Access Journals (Sweden)

    Rana Nagarkatti

    Full Text Available Trypanosoma cruzi, a blood-borne parasite, is the etiological agent of Chagas disease. T. cruzi trypomastigotes, the infectious life cycle stage, can be detected in blood of infected individuals using PCR-based methods. However, soon after a natural infection, or during the chronic phase of Chagas disease, the number of parasites in blood may be very low and thus difficult to detect by PCR. To facilitate PCR-based detection methods, a parasite concentration approach was explored. A whole cell SELEX strategy was utilized to develop serum stable RNA aptamers that bind to live T. cruzi trypomastigotes. These aptamers bound to the parasite with high affinities (8-25 nM range. The highest affinity aptamer, Apt68, also demonstrated high specificity as it did not interact with the insect stage epimastigotes of T. cruzi nor with other related trypanosomatid parasites, L. donovani and T. brucei, suggesting that the target of Apt68 was expressed only on T. cruzi trypomastigotes. Biotinylated Apt68, immobilized on a solid phase, was able to capture live parasites. These captured parasites were visible microscopically, as large motile aggregates, formed when the aptamer coated paramagnetic beads bound to the surface of the trypomastigotes. Additionally, Apt68 was also able to capture and aggregate trypomastigotes from several isolates of the two major genotypes of the parasite. Using a magnet, these parasite-bead aggregates could be purified from parasite-spiked whole blood samples, even at concentrations as low as 5 parasites in 15 ml of whole blood, as detected by a real-time PCR assay. Our results show that aptamers can be used as pathogen specific ligands to capture and facilitate PCR-based detection of T. cruzi in blood.

  14. Voltage Based Detection Method for High Impedance Fault in a Distribution System

    Science.gov (United States)

    Thomas, Mini Shaji; Bhaskar, Namrata; Prakash, Anupama

    2016-09-01

    High-impedance faults (HIFs) on distribution feeders cannot be detected by conventional protection schemes, as HIFs are characterized by their low fault current level and waveform distortion due to the nonlinearity of the ground return path. This paper proposes a method to identify the HIFs in distribution system and isolate the faulty section, to reduce downtime. This method is based on voltage measurements along the distribution feeder and utilizes the sequence components of the voltages. Three models of high impedance faults have been considered and source side and load side breaking of the conductor have been studied in this work to capture a wide range of scenarios. The effect of neutral grounding of the source side transformer is also accounted in this study. The results show that the algorithm detects the HIFs accurately and rapidly. Thus, the faulty section can be isolated and service can be restored to the rest of the consumers.

  15. Highly sensitive electrochemical detection of human telomerase activity based on bio-barcode method.

    Science.gov (United States)

    Li, Ying; Liu, Bangwei; Li, Xia; Wei, Qingli

    2010-07-15

    In the present study, an electrochemical method for highly sensitive detection of human telomerase activity was developed based on bio-barcode amplification assay. Telomerase was extracted from HeLa cells, then the extract was mixed with telomerase substrate (TS) primer to perform extension reaction. The extension product was hybridized with the capture DNA immobilized on the Au electrode and then reacted with the signal DNA on Au nanoparticles to form a sandwich hybridization mode. Electrochemical signals were generated by chronocoulometric interrogation of [Ru(NH(3))(6)](3+) that quantitatively binds to the DNA on Au nanoparticles via electrostatic interaction. This method can detect the telomerase activity from as little as 10 cultured cancer cells without the polymerase chain reaction (PCR) amplification of telomerase extension product. Copyright (c) 2010 Elsevier B.V. All rights reserved.

  16. Introducing two Random Forest based methods for cloud detection in remote sensing images

    Science.gov (United States)

    Ghasemian, Nafiseh; Akhoondzadeh, Mehdi

    2018-07-01

    Cloud detection is a necessary phase in satellite images processing to retrieve the atmospheric and lithospheric parameters. Currently, some cloud detection methods based on Random Forest (RF) model have been proposed but they do not consider both spectral and textural characteristics of the image. Furthermore, they have not been tested in the presence of snow/ice. In this paper, we introduce two RF based algorithms, Feature Level Fusion Random Forest (FLFRF) and Decision Level Fusion Random Forest (DLFRF) to incorporate visible, infrared (IR) and thermal spectral and textural features (FLFRF) including Gray Level Co-occurrence Matrix (GLCM) and Robust Extended Local Binary Pattern (RELBP_CI) or visible, IR and thermal classifiers (DLFRF) for highly accurate cloud detection on remote sensing images. FLFRF first fuses visible, IR and thermal features. Thereafter, it uses the RF model to classify pixels to cloud, snow/ice and background or thick cloud, thin cloud and background. DLFRF considers visible, IR and thermal features (both spectral and textural) separately and inserts each set of features to RF model. Then, it holds vote matrix of each run of the model. Finally, it fuses the classifiers using the majority vote method. To demonstrate the effectiveness of the proposed algorithms, 10 Terra MODIS and 15 Landsat 8 OLI/TIRS images with different spatial resolutions are used in this paper. Quantitative analyses are based on manually selected ground truth data. Results show that after adding RELBP_CI to input feature set cloud detection accuracy improves. Also, the average cloud kappa values of FLFRF and DLFRF on MODIS images (1 and 0.99) are higher than other machine learning methods, Linear Discriminate Analysis (LDA), Classification And Regression Tree (CART), K Nearest Neighbor (KNN) and Support Vector Machine (SVM) (0.96). The average snow/ice kappa values of FLFRF and DLFRF on MODIS images (1 and 0.85) are higher than other traditional methods. The

  17. A robust sub-pixel edge detection method of infrared image based on tremor-based retinal receptive field model

    Science.gov (United States)

    Gao, Kun; Yang, Hu; Chen, Xiaomei; Ni, Guoqiang

    2008-03-01

    Because of complex thermal objects in an infrared image, the prevalent image edge detection operators are often suitable for a certain scene and extract too wide edges sometimes. From a biological point of view, the image edge detection operators work reliably when assuming a convolution-based receptive field architecture. A DoG (Difference-of- Gaussians) model filter based on ON-center retinal ganglion cell receptive field architecture with artificial eye tremors introduced is proposed for the image contour detection. Aiming at the blurred edges of an infrared image, the subsequent orthogonal polynomial interpolation and sub-pixel level edge detection in rough edge pixel neighborhood is adopted to locate the foregoing rough edges in sub-pixel level. Numerical simulations show that this method can locate the target edge accurately and robustly.

  18. Ship Detection in Optical Satellite Image Based on RX Method and PCAnet

    Science.gov (United States)

    Shao, Xiu; Li, Huali; Lin, Hui; Kang, Xudong; Lu, Ting

    2017-12-01

    In this paper, we present a novel method for ship detection in optical satellite image based on the ReedXiaoli (RX) method and the principal component analysis network (PCAnet). The proposed method consists of the following three steps. First, the spatially adjacent pixels in optical image are arranged into a vector, transforming the optical image into a 3D cube image. By taking this process, the contextual information of the spatially adjacent pixels can be integrated to magnify the discrimination between ship and background. Second, the RX anomaly detection method is adopted to preliminarily extract ship candidates from the produced 3D cube image. Finally, real ships are further confirmed among ship candidates by applying the PCAnet and the support vector machine (SVM). Specifically, the PCAnet is a simple deep learning network which is exploited to perform feature extraction, and the SVM is applied to achieve feature pooling and decision making. Experimental results demonstrate that our approach is effective in discriminating between ships and false alarms, and has a good ship detection performance.

  19. 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.

  20. Leak detection of complex pipelines based on the filter diagonalization method: robust technique for eigenvalue assessment

    International Nuclear Information System (INIS)

    Lay-Ekuakille, Aimé; Pariset, Carlo; Trotta, Amerigo

    2010-01-01

    The FDM (filter diagonalization method), an interesting technique used in nuclear magnetic resonance data processing for tackling FFT (fast Fourier transform) limitations, can be used by considering pipelines, especially complex configurations, as a vascular apparatus with arteries, veins, capillaries, etc. Thrombosis, which might occur in humans, can be considered as a leakage for the complex pipeline, the human vascular apparatus. The choice of eigenvalues in FDM or in spectra-based techniques is a key issue in recovering the solution of the main equation (for FDM) or frequency domain transformation (for FFT) in order to determine the accuracy in detecting leaks in pipelines. This paper deals with the possibility of improving the leak detection accuracy of the FDM technique thanks to a robust algorithm by assessing the problem of eigenvalues, making it less experimental and more analytical using Tikhonov-based regularization techniques. The paper starts from the results of previous experimental procedures carried out by the authors

  1. Detection of Internal Short Circuit in Lithium Ion Battery Using Model-Based Switching Model Method

    Directory of Open Access Journals (Sweden)

    Minhwan Seo

    2017-01-01

    Full Text Available Early detection of an internal short circuit (ISCr in a Li-ion battery can prevent it from undergoing thermal runaway, and thereby ensure battery safety. In this paper, a model-based switching model method (SMM is proposed to detect the ISCr in the Li-ion battery. The SMM updates the model of the Li-ion battery with ISCr to improve the accuracy of ISCr resistance R I S C f estimates. The open circuit voltage (OCV and the state of charge (SOC are estimated by applying the equivalent circuit model, and by using the recursive least squares algorithm and the relation between OCV and SOC. As a fault index, the R I S C f is estimated from the estimated OCVs and SOCs to detect the ISCr, and used to update the model; this process yields accurate estimates of OCV and R I S C f . Then the next R I S C f is estimated and used to update the model iteratively. Simulation data from a MATLAB/Simulink model and experimental data verify that this algorithm shows high accuracy of R I S C f estimates to detect the ISCr, thereby helping the battery management system to fulfill early detection of the ISCr.

  2. Edge detection of optical subaperture image based on improved differential box-counting method

    Science.gov (United States)

    Li, Yi; Hui, Mei; Liu, Ming; Dong, Liquan; Kong, Lingqin; Zhao, Yuejin

    2018-01-01

    Optical synthetic aperture imaging technology is an effective approach to improve imaging resolution. Compared with monolithic mirror system, the image of optical synthetic aperture system is often more complex at the edge, and as a result of the existence of gap between segments, which makes stitching becomes a difficult problem. So it is necessary to extract the edge of subaperture image for achieving effective stitching. Fractal dimension as a measure feature can describe image surface texture characteristics, which provides a new approach for edge detection. In our research, an improved differential box-counting method is used to calculate fractal dimension of image, then the obtained fractal dimension is mapped to grayscale image to detect edges. Compared with original differential box-counting method, this method has two improvements as follows: by modifying the box-counting mechanism, a box with a fixed height is replaced by a box with adaptive height, which solves the problem of over-counting the number of boxes covering image intensity surface; an image reconstruction method based on super-resolution convolutional neural network is used to enlarge small size image, which can solve the problem that fractal dimension can't be calculated accurately under the small size image, and this method may well maintain scale invariability of fractal dimension. The experimental results show that the proposed algorithm can effectively eliminate noise and has a lower false detection rate compared with the traditional edge detection algorithms. In addition, this algorithm can maintain the integrity and continuity of image edge in the case of retaining important edge information.

  3. A ROC-based feature selection method for computer-aided detection and diagnosis

    Science.gov (United States)

    Wang, Songyuan; Zhang, Guopeng; Liao, Qimei; Zhang, Junying; Jiao, Chun; Lu, Hongbing

    2014-03-01

    Image-based computer-aided detection and diagnosis (CAD) has been a very active research topic aiming to assist physicians to detect lesions and distinguish them from benign to malignant. However, the datasets fed into a classifier usually suffer from small number of samples, as well as significantly less samples available in one class (have a disease) than the other, resulting in the classifier's suboptimal performance. How to identifying the most characterizing features of the observed data for lesion detection is critical to improve the sensitivity and minimize false positives of a CAD system. In this study, we propose a novel feature selection method mR-FAST that combines the minimal-redundancymaximal relevance (mRMR) framework with a selection metric FAST (feature assessment by sliding thresholds) based on the area under a ROC curve (AUC) generated on optimal simple linear discriminants. With three feature datasets extracted from CAD systems for colon polyps and bladder cancer, we show that the space of candidate features selected by mR-FAST is more characterizing for lesion detection with higher AUC, enabling to find a compact subset of superior features at low cost.

  4. A SVM-based quantitative fMRI method for resting-state functional network detection.

    Science.gov (United States)

    Song, Xiaomu; Chen, Nan-kuei

    2014-09-01

    Resting-state functional magnetic resonance imaging (fMRI) aims to measure baseline neuronal connectivity independent of specific functional tasks and to capture changes in the connectivity due to neurological diseases. Most existing network detection methods rely on a fixed threshold to identify functionally connected voxels under the resting state. Due to fMRI non-stationarity, the threshold cannot adapt to variation of data characteristics across sessions and subjects, and generates unreliable mapping results. In this study, a new method is presented for resting-state fMRI data analysis. Specifically, the resting-state network mapping is formulated as an outlier detection process that is implemented using one-class support vector machine (SVM). The results are refined by using a spatial-feature domain prototype selection method and two-class SVM reclassification. The final decision on each voxel is made by comparing its probabilities of functionally connected and unconnected instead of a threshold. Multiple features for resting-state analysis were extracted and examined using an SVM-based feature selection method, and the most representative features were identified. The proposed method was evaluated using synthetic and experimental fMRI data. A comparison study was also performed with independent component analysis (ICA) and correlation analysis. The experimental results show that the proposed method can provide comparable or better network detection performance than ICA and correlation analysis. The method is potentially applicable to various resting-state quantitative fMRI studies. Copyright © 2014 Elsevier Inc. All rights reserved.

  5. Surface Plasmon Resonance Biosensor Method for Palytoxin Detection Based on Na+,K+-ATPase Affinity

    Science.gov (United States)

    Alfonso, Amparo; Pazos, María-José; Fernández-Araujo, Andrea; Tobio, Araceli; Alfonso, Carmen; Vieytes, Mercedes R.; Botana, Luis M.

    2013-01-01

    Palytoxin (PLTX), produced by dinoflagellates from the genus Ostreopsis was first discovered, isolated, and purified from zoanthids belonging to the genus Palythoa. The detection of this toxin in contaminated shellfish is essential for human health preservation. A broad range of studies indicate that mammalian Na+,K+-ATPase is a high affinity cellular receptor for PLTX. The toxin converts the pump into an open channel that stimulates sodium influx and potassium efflux. In this work we develop a detection method for PLTX based on its binding to the Na+,K+-ATPase. The method was developed by using the phenomenon of surface plasmon resonance (SPR) to monitor biomolecular reactions. This technique does not require any labeling of components. The interaction of PLTX over immobilized Na+,K+-ATPase is quantified by injecting different concentrations of toxin in the biosensor and checking the binding rate constant (kobs). From the representation of kobs versus PLTX concentration, the kinetic equilibrium dissociation constant (KD) for the PLTX-Na+,K+-ATPase association can be calculated. The value of this constant is KD = 6.38 × 10−7 ± 6.67 × 10−8 M PLTX. In this way the PLTX-Na+,K+-ATPase association was used as a suitable method for determination of the toxin concentration in a sample. This method represents a new and useful approach to easily detect the presence of PLTX-like compounds in marine products using the mechanism of action of these toxins and in this way reduce the use of other more expensive and animal based methods. PMID:24379088

  6. Colonic polyp detection method from 3D abdominal CT images based on local intensity analysis

    International Nuclear Information System (INIS)

    Oda, M.; Nakada, Y.; Kitasaka, T.; Mori, K.; Suenaga, Y.; Takayama, T.; Takabatake, H.; Mori, M.; Natori, H.; Nawano, S.

    2007-01-01

    This paper presents a detection method of colonic polyps from 3D abdominal CT images based on local intensity analysis. Recently, virtual colonoscopy (VC) has widely received attention as a new colon diagnostic method. VC is considered as a less-invasive inspection method which reduces patient load. However, since the colon has many haustra and its shape is long and convoluted, a physician has to change the viewpoint and the viewing direction of the virtual camera of VC many times while diagnosis. Additionally, there is a risk to overlook lesions existing in blinded areas caused by haustra. This paper proposes an automated colonic polyp detection method from 3D abdominal CT images. Colonic polyps are located on the colonic wall. Their CT values are higher than those of colonic lumen regions and lower than those of fecal materials tagged by an X-ray opaque contrast agent. CT values inside polyps which exist outside the tagged fecal materials tend to gradually increase from outward to inward (blob-like structure). CT values inside polyps that exist inside the tagged fecal materials tend to gradually decrease from outward to inward (inv-blob-like structure). We employ the blob and the inv-blob structure enhancement filters based on the eigenvalues of the Hessian matrix to detect polyps using intensity characteristic of polyps. Connected components with low output values of the enhancement filter are eliminated in false positive reduction process. Small connected components are also eliminated. We applied the proposed method to 44 cases of abdominal CT images. Sensitivity for polyps of 6 mm or larger was 80% with 4.7 false positives per case. (orig.)

  7. Surface plasmon resonance biosensor method for palytoxin detection based on Na+,K+-ATPase affinity.

    Science.gov (United States)

    Alfonso, Amparo; Pazos, María-José; Fernández-Araujo, Andrea; Tobio, Araceli; Alfonso, Carmen; Vieytes, Mercedes R; Botana, Luis M

    2013-12-27

    Palytoxin (PLTX), produced by dinoflagellates from the genus Ostreopsis was first discovered, isolated, and purified from zoanthids belonging to the genus Palythoa. The detection of this toxin in contaminated shellfish is essential for human health preservation. A broad range of studies indicate that mammalian Na+,K+-ATPase is a high affinity cellular receptor for PLTX. The toxin converts the pump into an open channel that stimulates sodium influx and potassium efflux. In this work we develop a detection method for PLTX based on its binding to the Na+,K+-ATPase. The method was developed by using the phenomenon of surface plasmon resonance (SPR) to monitor biomolecular reactions. This technique does not require any labeling of components. The interaction of PLTX over immobilized Na+,K+-ATPase is quantified by injecting different concentrations of toxin in the biosensor and checking the binding rate constant (Kobs). From the representation of Kobs versus PLTX concentration, the kinetic equilibrium dissociation constant (K(D)) for the PLTX-Na+,K+-ATPase association can be calculated. The value of this constant is K(D) = 6.38 × 10-7 ± 6.67 × 10-8 M PLTX. In this way the PLTX-Na+,K+-ATPase association was used as a suitable method for determination of the toxin concentration in a sample. This method represents a new and useful approach to easily detect the presence of PLTX-like compounds in marine products using the mechanism of action of these toxins and in this way reduce the use of other more expensive and animal based methods.

  8. Surface Plasmon Resonance Biosensor Method for Palytoxin Detection Based on Na+,K+-ATPase Affinity

    Directory of Open Access Journals (Sweden)

    Amparo Alfonso

    2013-12-01

    Full Text Available Palytoxin (PLTX, produced by dinoflagellates from the genus Ostreopsis was first discovered, isolated, and purified from zoanthids belonging to the genus Palythoa. The detection of this toxin in contaminated shellfish is essential for human health preservation. A broad range of studies indicate that mammalian Na+,K+-ATPase is a high affinity cellular receptor for PLTX. The toxin converts the pump into an open channel that stimulates sodium influx and potassium efflux. In this work we develop a detection method for PLTX based on its binding to the Na+,K+-ATPase. The method was developed by using the phenomenon of surface plasmon resonance (SPR to monitor biomolecular reactions. This technique does not require any labeling of components. The interaction of PLTX over immobilized Na+,K+-ATPase is quantified by injecting different concentrations of toxin in the biosensor and checking the binding rate constant (kobs. From the representation of kobs versus PLTX concentration, the kinetic equilibrium dissociation constant (KD for the PLTX-Na+,K+-ATPase association can be calculated. The value of this constant is KD = 6.38 × 10−7 ± 6.67 × 10−8 M PLTX. In this way the PLTX-Na+,K+-ATPase association was used as a suitable method for determination of the toxin concentration in a sample. This method represents a new and useful approach to easily detect the presence of PLTX-like compounds in marine products using the mechanism of action of these toxins and in this way reduce the use of other more expensive and animal based methods.

  9. Physics-based, Bayesian sequential detection method and system for radioactive contraband

    Science.gov (United States)

    Candy, James V; Axelrod, Michael C; Breitfeller, Eric F; Chambers, David H; Guidry, Brian L; Manatt, Douglas R; Meyer, Alan W; Sale, Kenneth E

    2014-03-18

    A distributed sequential method and system for detecting and identifying radioactive contraband from highly uncertain (noisy) low-count, radionuclide measurements, i.e. an event mode sequence (EMS), using a statistical approach based on Bayesian inference and physics-model-based signal processing based on the representation of a radionuclide as a monoenergetic decomposition of monoenergetic sources. For a given photon event of the EMS, the appropriate monoenergy processing channel is determined using a confidence interval condition-based discriminator for the energy amplitude and interarrival time and parameter estimates are used to update a measured probability density function estimate for a target radionuclide. A sequential likelihood ratio test is then used to determine one of two threshold conditions signifying that the EMS is either identified as the target radionuclide or not, and if not, then repeating the process for the next sequential photon event of the EMS until one of the two threshold conditions is satisfied.

  10. An imbalance fault detection method based on data normalization and EMD for marine current turbines.

    Science.gov (United States)

    Zhang, Milu; Wang, Tianzhen; Tang, Tianhao; Benbouzid, Mohamed; Diallo, Demba

    2017-05-01

    This paper proposes an imbalance fault detection method based on data normalization and Empirical Mode Decomposition (EMD) for variable speed direct-drive Marine Current Turbine (MCT) system. The method is based on the MCT stator current under the condition of wave and turbulence. The goal of this method is to extract blade imbalance fault feature, which is concealed by the supply frequency and the environment noise. First, a Generalized Likelihood Ratio Test (GLRT) detector is developed and the monitoring variable is selected by analyzing the relationship between the variables. Then, the selected monitoring variable is converted into a time series through data normalization, which makes the imbalance fault characteristic frequency into a constant. At the end, the monitoring variable is filtered out by EMD method to eliminate the effect of turbulence. The experiments show that the proposed method is robust against turbulence through comparing the different fault severities and the different turbulence intensities. Comparison with other methods, the experimental results indicate the feasibility and efficacy of the proposed method. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  11. A Photoluminescence-Based Field Method for Detection of Traces of Explosives

    Directory of Open Access Journals (Sweden)

    E. Roland Menzel

    2004-01-01

    Full Text Available We report a photoluminescence-based field method for detecting traces of explosives. In its standard version, the method utilizes a commercially available color spot test kit for treating explosive traces on filter paper after swabbing. The colored products are fluorescent under illumination with a laser that operates on three C-size flashlight batteries and delivers light at 532 nm. In the fluorescence detection mode, by visual inspection, the typical sensitivity gain is a factor of 100. The method is applicable to a wide variety of explosives. In its time-resolved version, intended for in situ work, explosives are tagged with europium complexes. Instrumentation-wise, the time-resolved detection, again visual, can be accomplished in facile fashion. The europium luminescence excitation utilizes a laser operating at 355 nm. We demonstrate the feasibility of CdSe quantum dot sensitization of europium luminescence for time-resolved purposes. This would allow the use of the above 532 nm laser.

  12. The method for detecting small lesions in medical image based on sliding window

    Science.gov (United States)

    Han, Guilai; Jiao, Yuan

    2016-10-01

    At present, the research on computer-aided diagnosis includes the sample image segmentation, extracting visual features, generating the classification model by learning, and according to the model generated to classify and judge the inspected images. However, this method has a large scale of calculation and speed is slow. And because medical images are usually low contrast, when the traditional image segmentation method is applied to the medical image, there is a complete failure. As soon as possible to find the region of interest, improve detection speed, this topic attempts to introduce the current popular visual attention model into small lesions detection. However, Itti model is mainly for natural images. But the effect is not ideal when it is used to medical images which usually are gray images. Especially in the early stages of some cancers, the focus of a disease in the whole image is not the most significant region and sometimes is very difficult to be found. But these lesions are prominent in the local areas. This paper proposes a visual attention mechanism based on sliding window, and use sliding window to calculate the significance of a local area. Combined with the characteristics of the lesion, select the features of gray, entropy, corner and edge to generate a saliency map. Then the significant region is segmented and distinguished. This method reduces the difficulty of image segmentation, and improves the detection accuracy of small lesions, and it has great significance to early discovery, early diagnosis and treatment of cancers.

  13. A Novel Interference Detection Method of STAP Based on Simplified TT Transform

    Directory of Open Access Journals (Sweden)

    Qiang Wang

    2017-01-01

    Full Text Available Training samples contaminated by target-like signals is one of the major reasons for inhomogeneous clutter environment. In such environment, clutter covariance matrix in STAP (space-time adaptive processing is estimated inaccurately, which finally leads to detection performance reduction. In terms of this problem, a STAP interference detection method based on simplified TT (time-time transform is proposed in this letter. Considering the sparse physical property of clutter in the space-time plane, data on each range cell is first converted into a discrete slow time series. Then, the expression of simplified TT transform about sample data is derived step by step. Thirdly, the energy of each training sample is focalized and extracted by simplified TT transform from energy-variant difference between the unpolluted and polluted stage, and the physical significance of discarding the contaminated samples is analyzed. Lastly, the contaminated samples are picked out in light of the simplified TT transform-spectrum difference. The result on Monte Carlo simulation indicates that when training samples are contaminated by large power target-like signals, the proposed method is more effective in getting rid of the contaminated samples, reduces the computational complexity significantly, and promotes the target detection performance compared with the method of GIP (generalized inner product.

  14. Automated microaneurysm detection method based on double ring filter in retinal fundus images

    Science.gov (United States)

    Mizutani, Atsushi; Muramatsu, Chisako; Hatanaka, Yuji; Suemori, Shinsuke; Hara, Takeshi; Fujita, Hiroshi

    2009-02-01

    The presence of microaneurysms in the eye is one of the early signs of diabetic retinopathy, which is one of the leading causes of vision loss. We have been investigating a computerized method for the detection of microaneurysms on retinal fundus images, which were obtained from the Retinopathy Online Challenge (ROC) database. The ROC provides 50 training cases, in which "gold standard" locations of microaneurysms are provided, and 50 test cases without the gold standard locations. In this study, the computerized scheme was developed by using the training cases. Although the results for the test cases are also included, this paper mainly discusses the results for the training cases because the "gold standard" for the test cases is not known. After image preprocessing, candidate regions for microaneurysms were detected using a double-ring filter. Any potential false positives located in the regions corresponding to blood vessels were removed by automatic extraction of blood vessels from the images. Twelve image features were determined, and the candidate lesions were classified into microaneurysms or false positives using the rule-based method and an artificial neural network. The true positive fraction of the proposed method was 0.45 at 27 false positives per image. Forty-two percent of microaneurysms in the 50 training cases were considered invisible by the consensus of two co-investigators. When the method was evaluated for visible microaneurysms, the sensitivity for detecting microaneurysms was 65% at 27 false positives per image. Our computerized detection scheme could be improved for helping ophthalmologists in the early diagnosis of diabetic retinopathy.

  15. A Method for Harmonic Sources Detection based on Harmonic Distortion Power Rate

    Science.gov (United States)

    Lin, Ruixing; Xu, Lin; Zheng, Xian

    2018-03-01

    Harmonic sources detection at the point of common coupling is an essential step for harmonic contribution determination and harmonic mitigation. The harmonic distortion power rate index is proposed for harmonic source location based on IEEE Std 1459-2010 in the paper. The method only based on harmonic distortion power is not suitable when the background harmonic is large. To solve this problem, a threshold is determined by the prior information, when the harmonic distortion power is larger than the threshold, the customer side is considered as the main harmonic source, otherwise, the utility side is. A simple model of public power system was built in MATLAB/Simulink and field test results of typical harmonic loads verified the effectiveness of proposed method.

  16. Protein complex detection in PPI networks based on data integration and supervised learning method.

    Science.gov (United States)

    Yu, Feng; Yang, Zhi; Hu, Xiao; Sun, Yuan; Lin, Hong; Wang, Jian

    2015-01-01

    Revealing protein complexes are important for understanding principles of cellular organization and function. High-throughput experimental techniques have produced a large amount of protein interactions, which makes it possible to predict protein complexes from protein-protein interaction (PPI) networks. However, the small amount of known physical interactions may limit protein complex detection. The new PPI networks are constructed by integrating PPI datasets with the large and readily available PPI data from biomedical literature, and then the less reliable PPI between two proteins are filtered out based on semantic similarity and topological similarity of the two proteins. Finally, the supervised learning protein complex detection (SLPC), which can make full use of the information of available known complexes, is applied to detect protein complex on the new PPI networks. The experimental results of SLPC on two different categories yeast PPI networks demonstrate effectiveness of the approach: compared with the original PPI networks, the best average improvements of 4.76, 6.81 and 15.75 percentage units in the F-score, accuracy and maximum matching ratio (MMR) are achieved respectively; compared with the denoising PPI networks, the best average improvements of 3.91, 4.61 and 12.10 percentage units in the F-score, accuracy and MMR are achieved respectively; compared with ClusterONE, the start-of the-art complex detection method, on the denoising extended PPI networks, the average improvements of 26.02 and 22.40 percentage units in the F-score and MMR are achieved respectively. The experimental results show that the performances of SLPC have a large improvement through integration of new receivable PPI data from biomedical literature into original PPI networks and denoising PPI networks. In addition, our protein complexes detection method can achieve better performance than ClusterONE.

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

    Science.gov (United States)

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

    2016-06-01

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

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

    Directory of Open Access Journals (Sweden)

    C. H. Yang

    2016-06-01

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

  19. Benchmarking of a T-wave alternans detection method based on empirical mode decomposition.

    Science.gov (United States)

    Blanco-Velasco, Manuel; Goya-Esteban, Rebeca; Cruz-Roldán, Fernando; García-Alberola, Arcadi; Rojo-Álvarez, José Luis

    2017-07-01

    T-wave alternans (TWA) is a fluctuation of the ST-T complex occurring on an every-other-beat basis of the surface electrocardiogram (ECG). It has been shown to be an informative risk stratifier for sudden cardiac death, though the lack of gold standard to benchmark detection methods has promoted the use of synthetic signals. This work proposes a novel signal model to study the performance of a TWA detection. Additionally, the methodological validation of a denoising technique based on empirical mode decomposition (EMD), which is used here along with the spectral method, is also tackled. The proposed test bed system is based on the following guidelines: (1) use of open source databases to enable experimental replication; (2) use of real ECG signals and physiological noise; (3) inclusion of randomized TWA episodes. Both sensitivity (Se) and specificity (Sp) are separately analyzed. Also a nonparametric hypothesis test, based on Bootstrap resampling, is used to determine whether the presence of the EMD block actually improves the performance. The results show an outstanding specificity when the EMD block is used, even in very noisy conditions (0.96 compared to 0.72 for SNR = 8 dB), being always superior than that of the conventional SM alone. Regarding the sensitivity, using the EMD method also outperforms in noisy conditions (0.57 compared to 0.46 for SNR=8 dB), while it decreases in noiseless conditions. The proposed test setting designed to analyze the performance guarantees that the actual physiological variability of the cardiac system is reproduced. The use of the EMD-based block in noisy environment enables the identification of most patients with fatal arrhythmias. Copyright © 2017 Elsevier B.V. All rights reserved.

  20. Multicenter validation of PCR-based method for detection of Salmonella in chicken and pig samples

    DEFF Research Database (Denmark)

    Malorny, B.; Cook, N.; D'Agostino, M.

    2004-01-01

    As part of a standardization project, an interlaboratory trial including 15 laboratories from 13 European countries was conducted to evaluate the performance of a noproprietary polymerase chain reaction (PCR)-based method for the detection of Salmonella on artificially contaminated chicken rinse...... or positive. Outlier results caused, for example, by gross departures from the experimental protocol, were omitted from the analysis. For both the chicken rinse and the pig swab samples, the diagnostic sensitivity was 100%, with 100% accordance (repeatability) and concordance (reproducibility). The diagnostic...... specificity was 80.1% (with 85.7% accordance and 67.5% concordance) for chicken rinse, and 91.7% (with 100% accordance and 83.3% concordance) for pig swab. Thus, the interlaboratory variation due to personnel, reagents, thermal cyclers, etc., did not affect the performance of the method, which...

  1. Fluorescence-based methods for the detection of pressure-induced spore germination and inactivation

    Science.gov (United States)

    Baier, Daniel; Reineke, Kai; Doehner, Isabel; Mathys, Alexander; Knorr, Dietrich

    2011-03-01

    The application of high pressure (HP) provides an opportunity for the non-thermal preservation of high-quality foods, whereas highly resistant bacterial endospores play an important role. It is known that the germination of spores can be initiated by the application of HP. Moreover, the resistance properties of spores are highly dependent on their physiological states, which are passed through during the germination. To distinguish between different physiological states and to detect the amount of germinated spores after HP treatments, two fluorescence-based methods were applied. A flow cytometric method using a double staining with SYTO 16 as an indicator for germination and propidium iodide as an indicator for membrane damage was used to detect different physiological states of the spores. During the first step of germination, the spore-specific dipicolinic acid (DPA) is released [P. Setlow, Spore germination, Curr. Opin. Microbiol. 6 (2003), pp. 550-556]. DPA reacts with added terbium to form a distinctive fluorescent complex. After measuring the fluorescence intensity at 270 nm excitation wavelength in a fluorescence spectrophotometer, the amount of germinated spores can be determined. Spores of Bacillus subtilis were treated at pressures from 150 to 600 MPa and temperatures from 37 °C to 60 °C in 0.05 M ACES buffer solution (pH 7) for dwell times of up to 2 h. During the HP treatments, inactivation up to 2log 10 cycles and thermal sensitive populations up to 4log 10 cycles could be detected by plate counts. With an increasing number of thermal sensitive spores, an increased proportion of spores in germinated states was detected by flow cytometry. Also the released amount of DPA increased during the dwell times. Moreover, a clear pressure-temperature-time-dependency was shown by screening different conditions. The fluorescence-based measurement of the released DPA can provide the opportunity of an online monitoring of the germination of spores under HP inside

  2. Gear-box fault detection using time-frequency based methods

    DEFF Research Database (Denmark)

    Odgaard, Peter Fogh; Stoustrup, Jakob

    2015-01-01

    Gear-box fault monitoring and detection is important for optimization of power generation and availability of wind turbines. The current industrial approach is to use condition monitoring systems, which runs in parallel with the wind turbine control system, using expensive additional sensors...... in the gear-box resonance frequency can be detected. Two different time–frequency based approaches are presented in this paper. One is a filter based approach and the other is based on a Karhunen–Loeve basis. Both of them detect the gear-box fault with an acceptable detection delay of maximum 100s, which...... is neglectable compared with the fault developing time....

  3. A new method to detect event-related potentials based on Pearson's correlation.

    Science.gov (United States)

    Giroldini, William; Pederzoli, Luciano; Bilucaglia, Marco; Melloni, Simone; Tressoldi, Patrizio

    2016-12-01

    Event-related potentials (ERPs) are widely used in brain-computer interface applications and in neuroscience.  Normal EEG activity is rich in background noise, and therefore, in order to detect ERPs, it is usually necessary to take the average from multiple trials to reduce the effects of this noise.  The noise produced by EEG activity itself is not correlated with the ERP waveform and so, by calculating the average, the noise is decreased by a factor inversely proportional to the square root of N , where N is the number of averaged epochs. This is the easiest strategy currently used to detect ERPs, which is based on calculating the average of all ERP's waveform, these waveforms being time- and phase-locked.  In this paper, a new method called GW6 is proposed, which calculates the ERP using a mathematical method based only on Pearson's correlation. The result is a graph with the same time resolution as the classical ERP and which shows only positive peaks representing the increase-in consonance with the stimuli-in EEG signal correlation over all channels.  This new method is also useful for selectively identifying and highlighting some hidden components of the ERP response that are not phase-locked, and that are usually hidden in the standard and simple method based on the averaging of all the epochs.  These hidden components seem to be caused by variations (between each successive stimulus) of the ERP's inherent phase latency period (jitter), although the same stimulus across all EEG channels produces a reasonably constant phase. For this reason, this new method could be very helpful to investigate these hidden components of the ERP response and to develop applications for scientific and medical purposes. Moreover, this new method is more resistant to EEG artifacts than the standard calculations of the average and could be very useful in research and neurology.  The method we are proposing can be directly used in the form of a process written in the well

  4. A New Method of Cloud Detection Based on Cascaded AdaBoost

    International Nuclear Information System (INIS)

    Ma, C; Chen, F; Liu, J; Duan, J

    2014-01-01

    Cloud detection of remote sensing image is a critical step in the processing of the remote sensing images. How to quickly, accurately and effectively detect cloud on remote sensing images, is still a challenging issue in this area. In order to avoid disadvantages of the current algorithms, the cascaded AdaBoost classifier algorithm is successfully applied to the cloud detection. A new algorithm combined cascaded AdaBoost classifier and multi-features, is proposed in this paper. First, multi-features based on the color, texture and spectral features are extracted from the remote sensing image. Second, the automatic cloud detection model is obtained based on the cascaded AdaBoost algorithm. In this paper, the results show that the new algorithm can determine cloud detection model and threshold values adaptively for different resolution remote sensing training data. The accuracy of cloud detection is improved. So it is a new effective algorithm for the cloud detection of remote sensing images

  5. A Voltage Quality Detection Method

    DEFF Research Database (Denmark)

    Chen, Zhe; Wei, Mu

    2008-01-01

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

  6. Prioritizing alarms from sensor-based detection models in livestock production - A review on model performance and alarm reducing methods

    DEFF Research Database (Denmark)

    Dominiak, Katarina Sylow; Kristensen, Anders Ringgaard

    2017-01-01

    The objective of this review is to present, evaluate and discuss methods for reducing false alarms in sensor-based detection models developed for livestock production as described in the scientific literature. Papers included in this review are all peer-reviewed and present sensor-based detection...

  7. Detection of nitrite based on fluorescent carbon dots by the hydrothermal method with folic acid

    Science.gov (United States)

    Lin, Haitao; Ding, Liyun; Zhang, Bingyu; Huang, Jun

    2018-05-01

    A fluorescent carbon dots probe for the detection of aqueous nitrite was fabricated by a one-pot hydrothermal method, and the transmission electron microscope, X-ray diffractometer, UV-Vis absorption spectrometer and fluorescence spectrophotometer were used to study the property of carbon dots. The fluorescent property of carbon dots influenced by the concentration of aqueous nitrite was studied. The interaction between the electron-donating functional groups and the electron-accepting nitrous acid could account for the quenching effect on carbon dots by adding aqueous nitrite. The products of the hydrolysis of aqueous nitrite performed a stronger quenching effect at lower pH. The relationship between the relative fluorescence intensity of carbon dots and the concentration of nitrite was described by the Stern-Volmer equation (I0/I - 1 = 0.046[Q]) with a fine linearity (R2 = 0.99). The carbon dots-based probe provides a convenient method for the detection of nitrite concentration.

  8. An Energy-Efficient Cluster-Based Vehicle Detection on Road Network Using Intention Numeration Method

    Directory of Open Access Journals (Sweden)

    Deepa Devasenapathy

    2015-01-01

    Full Text Available The traffic in the road network is progressively increasing at a greater extent. Good knowledge of network traffic can minimize congestions using information pertaining to road network obtained with the aid of communal callers, pavement detectors, and so on. Using these methods, low featured information is generated with respect to the user in the road network. Although the existing schemes obtain urban traffic information, they fail to calculate the energy drain rate of nodes and to locate equilibrium between the overhead and quality of the routing protocol that renders a great challenge. Thus, an energy-efficient cluster-based vehicle detection in road network using the intention numeration method (CVDRN-IN is developed. Initially, sensor nodes that detect a vehicle are grouped into separate clusters. Further, we approximate the strength of the node drain rate for a cluster using polynomial regression function. In addition, the total node energy is estimated by taking the integral over the area. Finally, enhanced data aggregation is performed to reduce the amount of data transmission using digital signature tree. The experimental performance is evaluated with Dodgers loop sensor data set from UCI repository and the performance evaluation outperforms existing work on energy consumption, clustering efficiency, and node drain rate.

  9. An energy-efficient cluster-based vehicle detection on road network using intention numeration method.

    Science.gov (United States)

    Devasenapathy, Deepa; Kannan, Kathiravan

    2015-01-01

    The traffic in the road network is progressively increasing at a greater extent. Good knowledge of network traffic can minimize congestions using information pertaining to road network obtained with the aid of communal callers, pavement detectors, and so on. Using these methods, low featured information is generated with respect to the user in the road network. Although the existing schemes obtain urban traffic information, they fail to calculate the energy drain rate of nodes and to locate equilibrium between the overhead and quality of the routing protocol that renders a great challenge. Thus, an energy-efficient cluster-based vehicle detection in road network using the intention numeration method (CVDRN-IN) is developed. Initially, sensor nodes that detect a vehicle are grouped into separate clusters. Further, we approximate the strength of the node drain rate for a cluster using polynomial regression function. In addition, the total node energy is estimated by taking the integral over the area. Finally, enhanced data aggregation is performed to reduce the amount of data transmission using digital signature tree. The experimental performance is evaluated with Dodgers loop sensor data set from UCI repository and the performance evaluation outperforms existing work on energy consumption, clustering efficiency, and node drain rate.

  10. A method of detecting sea fogs using CALIOP data and its application to improve MODIS-based sea fog detection

    International Nuclear Information System (INIS)

    Wu, Dong; Lu, Bo; Zhang, Tianche; Yan, Fengqi

    2015-01-01

    A method to detect sea fogs from the measurement data acquired by the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) aboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite is proposed in this paper. Because of the unique capability of vertical-resolved measurements, sea fogs and low clouds can be more easily distinguished in the CALIOP data compared with passive satellite measurements. Yellow Sea where sea fogs occur frequently is selected to test the method. Nine cases of daytime sea fog events from 2008 to 2011 in the Yellow Sea are studied intensively to characterize the remotely sensed radiation properties of various targets, such as clear-sky sea surface, sea fog, low cloud and high cloud. These fog cases are then used in an attempt to evaluate sea fogs identified from the MODIS measurements. The method proposed in this paper can also be used for nighttime cases. Multi-year sea fog dataset can be made from the CALIOP measurement and used to validate the MODIS sea fog detection. - Highlights: • A method of sea fog detection from the CALIOP measurements is proposed. • CALIOP VFM and 532-nm attenuated backscatter products are integrated used. • Sea fogs and low clouds can be more easily distinguished in the CALIOP data. • 9 Cases of daytime sea fog events in the Yellow Sea are selected to test the method. • The MODIS sea fog detections are evaluated using the collocated CALIOP data

  11. Design parameter based method of partial discharge detection and location in power transformers

    Directory of Open Access Journals (Sweden)

    Kumar Santosh Annadurai

    2009-01-01

    Full Text Available Insulation defect detection in time ensures higher operational reliability of power system assets. Power transformers are the most critical unit of power systems both from economical and operational front. Hence it becomes necessary to have knowledge of the actual insulation condition of transformer to increase dependability of the system. The performance and ageing of the transformer insulation is mainly affected by Partial discharges (PD. Proper diagnosis in terms of amplitude and location of partial discharge in a power transformer enables us to predict well in advance, with much confidence, the defect in insulation system, which avoids large catastrophic failures. In this work a 20kVA, 230/50kV single phase core type transformer is used for evaluation of the transfer function-based partial discharge detection and location using modeling of the winding, using design data. The simulation of capturing on-line PD pulses across the bushing tap capacitor is done for various tap positions. Standard PD source model is used to inject PD pulse signal at 10 tap locations in the winding and corresponding response signatures are captured at the bushing tap end (across 1000pF. The equivalent high frequency model of the winding is derived from the design parameters using analytical calculations and simulations in packages such as MAGNET and ANSOFT. The test conditions are simulated using ORCAD-9 and the results are evaluated for location accuracy using design parameter based PD monitoring method. .

  12. Evaluation of DNA extraction methods for PCR-based detection of Listeria monocytogenes from vegetables.

    Science.gov (United States)

    Vojkovska, H; Kubikova, I; Kralik, P

    2015-03-01

    Epidemiological data indicate that raw vegetables are associated with outbreaks of Listeria monocytogenes. Therefore, there is a demand for the availability of rapid and sensitive methods, such as PCR assays, for the detection and accurate discrimination of L. monocytogenes. However, the efficiency of PCR methods can be negatively affected by inhibitory compounds commonly found in vegetable matrices that may cause false-negative results. Therefore, the sample processing and DNA isolation steps must be carefully evaluated prior to the introduction of such methods into routine practice. In this study, we compared the ability of three column-based and four magnetic bead-based commercial DNA isolation kits to extract DNA of the model micro-organism L. monocytogenes from raw vegetables. The DNA isolation efficiency of all isolation kits was determined using a triplex real-time qPCR assay designed to specifically detect L. monocytogenes. The kit with best performance, the PowerSoil(™) Microbial DNA Isolation Kit, is suitable for the extraction of amplifiable DNA from L. monocytogenes cells in vegetable with efficiencies ranging between 29.6 and 70.3%. Coupled with the triplex real-time qPCR assay, this DNA isolation kit is applicable to the samples with bacterial loads of 10(3) bacterial cells per gram of L. monocytogenes. Several recent outbreaks of Listeria monocytogenes have been associated with the consumption of fruits and vegetables. Real-time PCR assays allow fast detection and accurate quantification of microbes. However, the success of real-time PCR is dependent on the success with which template DNA can be extracted. The results of this study suggest that the PowerSoil(™) Microbial DNA Isolation Kit can be used for the extraction of amplifiable DNA from L. monocytogenes cells in vegetable with efficiencies ranging between 29.6 and 70.3%. This method is applicable to samples with bacterial loads of 10(3) bacterial cells per gram of L. monocytogenes. © 2014

  13. Online Adaboost-Based Parameterized Methods for Dynamic Distributed Network Intrusion Detection.

    Science.gov (United States)

    Hu, Weiming; Gao, Jun; Wang, Yanguo; Wu, Ou; Maybank, Stephen

    2014-01-01

    Current network intrusion detection systems lack adaptability to the frequently changing network environments. Furthermore, intrusion detection in the new distributed architectures is now a major requirement. In this paper, we propose two online Adaboost-based intrusion detection algorithms. In the first algorithm, a traditional online Adaboost process is used where decision stumps are used as weak classifiers. In the second algorithm, an improved online Adaboost process is proposed, and online Gaussian mixture models (GMMs) are used as weak classifiers. We further propose a distributed intrusion detection framework, in which a local parameterized detection model is constructed in each node using the online Adaboost algorithm. A global detection model is constructed in each node by combining the local parametric models using a small number of samples in the node. This combination is achieved using an algorithm based on particle swarm optimization (PSO) and support vector machines. The global model in each node is used to detect intrusions. Experimental results show that the improved online Adaboost process with GMMs obtains a higher detection rate and a lower false alarm rate than the traditional online Adaboost process that uses decision stumps. Both the algorithms outperform existing intrusion detection algorithms. It is also shown that our PSO, and SVM-based algorithm effectively combines the local detection models into the global model in each node; the global model in a node can handle the intrusion types that are found in other nodes, without sharing the samples of these intrusion types.

  14. SUPERPIXEL BASED FACTOR ANALYSIS AND TARGET TRANSFORMATION METHOD FOR MARTIAN MINERALS DETECTION

    Directory of Open Access Journals (Sweden)

    X. Wu

    2018-04-01

    Full Text Available The Factor analysis and target transformation (FATT is an effective method to test for the presence of particular mineral on Martian surface. It has been used both in thermal infrared (Thermal Emission Spectrometer, TES and near-infrared (Compact Reconnaissance Imaging Spectrometer for Mars, CRISM hyperspectral data. FATT derived a set of orthogonal eigenvectors from a mixed system and typically selected first 10 eigenvectors to least square fit the library mineral spectra. However, minerals present only in a limited pixels will be ignored because its weak spectral features compared with full image signatures. Here, we proposed a superpixel based FATT method to detect the mineral distributions on Mars. The simple linear iterative clustering (SLIC algorithm was used to partition the CRISM image into multiple connected image regions with spectral homogeneous to enhance the weak signatures by increasing their proportion in a mixed system. A least square fitting was used in target transformation and performed to each region iteratively. Finally, the distribution of the specific minerals in image was obtained, where fitting residual less than a threshold represent presence and otherwise absence. We validate our method by identifying carbonates in a well analysed CRISM image in Nili Fossae on Mars. Our experimental results indicate that the proposed method work well both in simulated and real data sets.

  15. A current detection based on an extension of the Prony's method

    Energy Technology Data Exchange (ETDEWEB)

    Deng, C.; Xia, X.; Gong, F. [Changsha Univ. of Science and Technology, Changsha (China). College of Electrical Engineering

    2009-07-01

    The Prony method for spectrum estimation was combined with an adaptive frequency tracking and current frequency demultiplication method as a harmonic detection system. An injective active power filter was used for effective harmonic wave management. The automated system includes a digital signal processor and a high-speed interfacing device. An algorithm was developed to consider the slow voltage changes in the power grid as well as potential mutations in current harmonics. Widrow-Hoff's LMS algorithm was used to develop rolling steps for the filter. The method was used to detect harmonic waves with a sampling frequency of 400 Hz. Results of the study showed that the detection method can be used in real time to detect fundamental and first harmonics in electric power grids. 10 refs., 2 tabs., 1 fig.

  16. Shack-Hartmann centroid detection method based on high dynamic range imaging and normalization techniques

    International Nuclear Information System (INIS)

    Vargas, Javier; Gonzalez-Fernandez, Luis; Quiroga, Juan Antonio; Belenguer, Tomas

    2010-01-01

    In the optical quality measuring process of an optical system, including diamond-turning components, the use of a laser light source can produce an undesirable speckle effect in a Shack-Hartmann (SH) CCD sensor. This speckle noise can deteriorate the precision and accuracy of the wavefront sensor measurement. Here we present a SH centroid detection method founded on computer-based techniques and capable of measurement in the presence of strong speckle noise. The method extends the dynamic range imaging capabilities of the SH sensor through the use of a set of different CCD integration times. The resultant extended range spot map is normalized to accurately obtain the spot centroids. The proposed method has been applied to measure the optical quality of the main optical system (MOS) of the mid-infrared instrument telescope smulator. The wavefront at the exit of this optical system is affected by speckle noise when it is illuminated by a laser source and by air turbulence because it has a long back focal length (3017 mm). Using the proposed technique, the MOS wavefront error was measured and satisfactory results were obtained.

  17. Model-based temperature noise monitoring methods for LMFBR core anomaly detection

    International Nuclear Information System (INIS)

    Tamaoki, Tetsuo; Sonoda, Yukio; Sato, Masuo; Takahashi, Ryoichi.

    1994-01-01

    Temperature noise, measured by thermocouples mounted at each core fuel subassembly, is considered to be the most useful signal for detecting and locating local cooling anomalies in an LMFBR core. However, the core outlet temperature noise contains background noise due to fluctuations in the operating parameters including reactor power. It is therefore necessary to reduce this background noise for highly sensitive anomaly detection by subtracting predictable components from the measured signal. In the present study, both a physical model and an autoregressive model were applied to noise data measured in the experimental fast reactor JOYO. The results indicate that the autoregressive model has a higher precision than the physical model in background noise prediction. Based on these results, an 'autoregressive model modification method' is proposed, in which a temporary autoregressive model is generated by interpolation or extrapolation of reference models identified under a small number of different operating conditions. The generated autoregressive model has shown sufficient precision over a wide range of reactor power in applications to artificial noise data produced by an LMFBR noise simulator even when the coolant flow rate was changed to keep a constant power-to-flow ratio. (author)

  18. Detecting and Identifying Industrial Gases by a Method Based on Olfactory Machine at Different Concentrations

    OpenAIRE

    Sun, Yunlong; Luo, Dehan; Li, Hui; Zhu, Chuchu; Xu, Ou; Gholam Hosseini, Hamid

    2018-01-01

    Gas sensors have been widely reported for industrial gas detection and monitoring. However, the rapid detection and identification of industrial gases are still a challenge. In this work, we measure four typical industrial gases including CO2, CH4, NH3, and volatile organic compounds (VOCs) based on electronic nose (EN) at different concentrations. To solve the problem of effective classification and identification of different industrial gases, we propose an algorithm based on the selective ...

  19. Novel method for edge detection of retinal vessels based on the model of the retinal vascular network and mathematical morphology

    Science.gov (United States)

    Xu, Lei; Zheng, Xiaoxiang; Zhang, Hengyi; Yu, Yajun

    1998-09-01

    Accurate edge detection of retinal vessels is a prerequisite for quantitative analysis of subtle morphological changes of retinal vessels under different pathological conditions. A novel method for edge detection of retinal vessels is presented in this paper. Methods: (1) Wavelet-based image preprocessing. (2) The signed edge detection algorithm and mathematical morphological operation are applied to get the approximate regions that contain retinal vessels. (3) By convolving the preprocessed image with a LoG operator only on the detected approximate regions of retinal vessels, followed by edges refining, clear edge maps of the retinal vessels are fast obtained. Results: A detailed performance evaluation together with the existing techniques is given to demonstrate the strong features of our method. Conclusions: True edge locations of retinal vessels can be fast detected with continuous structures of retinal vessels, less non- vessel segments left and insensitivity to noise. The method is also suitable for other application fields such as road edge detection.

  20. Hybrid approach for detection of dental caries based on the methods FCM and level sets

    Science.gov (United States)

    Chaabene, Marwa; Ben Ali, Ramzi; Ejbali, Ridha; Zaied, Mourad

    2017-03-01

    This paper presents a new technique for detection of dental caries that is a bacterial disease that destroys the tooth structure. In our approach, we have achieved a new segmentation method that combines the advantages of fuzzy C mean algorithm and level set method. The results obtained by the FCM algorithm will be used by Level sets algorithm to reduce the influence of the noise effect on the working of each of these algorithms, to facilitate level sets manipulation and to lead to more robust segmentation. The sensitivity and specificity confirm the effectiveness of proposed method for caries detection.

  1. Fisk-based criteria to support validation of detection methods for drinking water and air.

    Energy Technology Data Exchange (ETDEWEB)

    MacDonell, M.; Bhattacharyya, M.; Finster, M.; Williams, M.; Picel, K.; Chang, Y.-S.; Peterson, J.; Adeshina, F.; Sonich-Mullin, C.; Environmental Science Division; EPA

    2009-02-18

    This report was prepared to support the validation of analytical methods for threat contaminants under the U.S. Environmental Protection Agency (EPA) National Homeland Security Research Center (NHSRC) program. It is designed to serve as a resource for certain applications of benchmark and fate information for homeland security threat contaminants. The report identifies risk-based criteria from existing health benchmarks for drinking water and air for potential use as validation targets. The focus is on benchmarks for chronic public exposures. The priority sources are standard EPA concentration limits for drinking water and air, along with oral and inhalation toxicity values. Many contaminants identified as homeland security threats to drinking water or air would convert to other chemicals within minutes to hours of being released. For this reason, a fate analysis has been performed to identify potential transformation products and removal half-lives in air and water so appropriate forms can be targeted for detection over time. The risk-based criteria presented in this report to frame method validation are expected to be lower than actual operational targets based on realistic exposures following a release. Note that many target criteria provided in this report are taken from available benchmarks without assessing the underlying toxicological details. That is, although the relevance of the chemical form and analogues are evaluated, the toxicological interpretations and extrapolations conducted by the authoring organizations are not. It is also important to emphasize that such targets in the current analysis are not health-based advisory levels to guide homeland security responses. This integrated evaluation of chronic public benchmarks and contaminant fate has identified more than 200 risk-based criteria as method validation targets across numerous contaminants and fate products in drinking water and air combined. The gap in directly applicable values is

  2. An image overall complexity evaluation method based on LSD line detection

    Science.gov (United States)

    Li, Jianan; Duan, Jin; Yang, Xu; Xiao, Bo

    2017-04-01

    In the artificial world, whether it is the city's traffic roads or engineering buildings contain a lot of linear features. Therefore, the research on the image complexity of linear information has become an important research direction in digital image processing field. This paper, by detecting the straight line information in the image and using the straight line as the parameter index, establishing the quantitative and accurate mathematics relationship. In this paper, we use LSD line detection algorithm which has good straight-line detection effect to detect the straight line, and divide the detected line by the expert consultation strategy. Then we use the neural network to carry on the weight training and get the weight coefficient of the index. The image complexity is calculated by the complexity calculation model. The experimental results show that the proposed method is effective. The number of straight lines in the image, the degree of dispersion, uniformity and so on will affect the complexity of the image.

  3. Application of Modal Parameter Estimation Methods for Continuous Wavelet Transform-Based Damage Detection for Beam-Like Structures

    Directory of Open Access Journals (Sweden)

    Zhi Qiu

    2015-02-01

    Full Text Available This paper presents a hybrid damage detection method based on continuous wavelet transform (CWT and modal parameter identification techniques for beam-like structures. First, two kinds of mode shape estimation methods, herein referred to as the quadrature peaks picking (QPP and rational fraction polynomial (RFP methods, are used to identify the first four mode shapes of an intact beam-like structure based on the hammer/accelerometer modal experiment. The results are compared and validated using a numerical simulation with ABAQUS software. In order to determine the damage detection effectiveness between the QPP-based method and the RFP-based method when applying the CWT technique, the first two mode shapes calculated by the QPP and RFP methods are analyzed using CWT. The experiment, performed on different damage scenarios involving beam-like structures, shows that, due to the outstanding advantage of the denoising characteristic of the RFP-based (RFP-CWT technique, the RFP-CWT method gives a clearer indication of the damage location than the conventionally used QPP-based (QPP-CWT method. Finally, an overall evaluation of the damage detection is outlined, as the identification results suggest that the newly proposed RFP-CWT method is accurate and reliable in terms of detection of damage locations on beam-like structures.

  4. Omega-3 chicken egg detection system using a mobile-based image processing segmentation method

    Science.gov (United States)

    Nurhayati, Oky Dwi; Kurniawan Teguh, M.; Cintya Amalia, P.

    2017-02-01

    An Omega-3 chicken egg is a chicken egg produced through food engineering technology. It is produced by hen fed with high omega-3 fatty acids. So, it has fifteen times nutrient content of omega-3 higher than Leghorn's. Visually, its shell has the same shape and colour as Leghorn's. Each egg can be distinguished by breaking the egg's shell and testing the egg yolk's nutrient content in a laboratory. But, those methods were proven not effective and efficient. Observing this problem, the purpose of this research is to make an application to detect the type of omega-3 chicken egg by using a mobile-based computer vision. This application was built in OpenCV computer vision library to support Android Operating System. This experiment required some chicken egg images taken using an egg candling box. We used 60 omega-3 chicken and Leghorn eggs as samples. Then, using an Android smartphone, image acquisition of the egg was obtained. After that, we applied several steps using image processing methods such as Grab Cut, convert RGB image to eight bit grayscale, median filter, P-Tile segmentation, and morphology technique in this research. The next steps were feature extraction which was used to extract feature values via mean, variance, skewness, and kurtosis from each image. Finally, using digital image measurement, some chicken egg images were classified. The result showed that omega-3 chicken egg and Leghorn egg had different values. This system is able to provide accurate reading around of 91%.

  5. New EDTA determination method based on ion chromatography with suppressed conductimetric detection

    International Nuclear Information System (INIS)

    Gyoergy Patzay; Yahya Ramadan; Csilla Tonko

    2014-01-01

    A novel direct method for the determination of EDTA in alkaline radioactive evaporator residue solution was developed and validated based on ion chromatography with suppressed conductimetric detection and anion exchange columns (A Supp 4, 4 mm × 250 mm and A Supp 5, 4 mm × 150 mm). The yttrium-EDTA complex resulted one single chromatographic peak in the eluent and allowed the correct determination of EDTA in an alkaline, high concentration radioactive waste water. Depending on coexisting substances, suitable eluent is 10.0 mM carbonate buffer/pH 10.6 or 10.75 (t R ,Y-EDTA = 7.01 and 6.4 min, respectively). For 10.0 mM carbonate buffer/pH 10.6 and isocratic flow rate of 1.0 cm 3 /min, a linear calibration curve was obtained from 5 to 40 mg/dm 3 (r > 0.999) EDTA. Good resolution was achieved from commonly coexisting anions (chloride, nitrite, nitrate, sulphate, phosphate, bromide and citrate). The developed simple ion chromatographic method was applied for the assay of EDTA in various radioactive alkaline solutions. (author)

  6. 3D shape detection of the indoor space based on 3D-Hough method

    OpenAIRE

    安齋, 達也; ANZAI, Tatsuya

    2013-01-01

    This paper describes methods for detecting the 3D shapes of the indoor space that is represented as a combination of planes such as a wall, desk, or whatnot. Detecting the planes makes it possible to perform calibration of multiple sensors and 3D mapping, and then produces various services such as the acquisition of life logs, AR interaction, and invader detection. This paper proposes and verifies three algorithms. First, it mentions a way to use2D-Hough.The proposed technique converts 3D dat...

  7. Fault Detection for Nonlinear Process With Deterministic Disturbances: A Just-In-Time Learning Based Data Driven Method.

    Science.gov (United States)

    Yin, Shen; Gao, Huijun; Qiu, Jianbin; Kaynak, Okyay

    2017-11-01

    Data-driven fault detection plays an important role in industrial systems due to its applicability in case of unknown physical models. In fault detection, disturbances must be taken into account as an inherent characteristic of processes. Nevertheless, fault detection for nonlinear processes with deterministic disturbances still receive little attention, especially in data-driven field. To solve this problem, a just-in-time learning-based data-driven (JITL-DD) fault detection method for nonlinear processes with deterministic disturbances is proposed in this paper. JITL-DD employs JITL scheme for process description with local model structures to cope with processes dynamics and nonlinearity. The proposed method provides a data-driven fault detection solution for nonlinear processes with deterministic disturbances, and owns inherent online adaptation and high accuracy of fault detection. Two nonlinear systems, i.e., a numerical example and a sewage treatment process benchmark, are employed to show the effectiveness of the proposed method.

  8. Impact detection method for composite winglets based on neural network implementation

    Science.gov (United States)

    Viscardi, Massimo; Arena, Maurizio; Napolitano, Pasquale

    2018-03-01

    Maintenance tasks and safety aspects represent a strategic role in the managing of the modern aircraft fleets. The demand for reliable techniques for structural health monitoring represent so a key aspect looking forward to new generation aircraft. In particular, the use of more technologically complex materials and manufacturing methods requires anyway more efficient as well as rapid application processes to improve the design strength and service life. Actually, it is necessary to rely on survey instruments, which allow for safeguarding the structural integrity of the aircraft, especially after the wide use of composite structures highly susceptible to non-detected damages as delamination of the ply. In this paper, the authors have investigated the feasibility to implement a neural network-based algorithm to predict the impact event at low frequency, typically due to the bird collision. Relying upon a numerical model, representative of a composite flat panel, the approach has been also experimentally validated. The purpose of the work is therefore the presentation of an innovative application within the Non Destructive Testing field based upon vibration measurements. The aim of the research has been the development of a Non Destructive Test which meets most of the mandatory requirements for effective health monitoring systems while, at the same time, reducing as much as possible the complexity of the data analysis algorithm and the experimental acquisition instrumentation. Future activities will be addressed to test such technique on a more complex aeronautical system.

  9. Vibration-Based Adaptive Novelty Detection Method for Monitoring Faults in a Kinematic Chain

    Directory of Open Access Journals (Sweden)

    Jesus Adolfo Cariño-Corrales

    2016-01-01

    Full Text Available This paper presents an adaptive novelty detection methodology applied to a kinematic chain for the monitoring of faults. The proposed approach has the premise that only information of the healthy operation of the machine is initially available and fault scenarios will eventually develop. This approach aims to cover some of the challenges presented when condition monitoring is applied under a continuous learning framework. The structure of the method is divided into two recursive stages: first, an offline stage for initialization and retraining of the feature reduction and novelty detection modules and, second, an online monitoring stage to continuously assess the condition of the machine. Contrary to classical static feature reduction approaches, the proposed method reformulates the features by employing first a Laplacian Score ranking and then the Fisher Score ranking for retraining. The proposed methodology is validated experimentally by monitoring the vibration measurements of a kinematic chain driven by an induction motor. Two faults are induced in the motor to validate the method performance to detect anomalies and adapt the feature reduction and novelty detection modules to the new information. The obtained results show the advantages of employing an adaptive approach for novelty detection and feature reduction making the proposed method suitable for industrial machinery diagnosis applications.

  10. 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...

  11. A hierarchical detection method in external communication for self-driving vehicles based on TDMA

    Science.gov (United States)

    Al-ani, Muzhir Shaban; McDonald-Maier, Klaus

    2018-01-01

    Security is considered a major challenge for self-driving and semi self-driving vehicles. These vehicles depend heavily on communications to predict and sense their external environment used in their motion. They use a type of ad hoc network termed Vehicular ad hoc networks (VANETs). Unfortunately, VANETs are potentially exposed to many attacks on network and application level. This paper, proposes a new intrusion detection system to protect the communication system of self-driving cars; utilising a combination of hierarchical models based on clusters and log parameters. This security system is designed to detect Sybil and Wormhole attacks in highway usage scenarios. It is based on clusters, utilising Time Division Multiple Access (TDMA) to overcome some of the obstacles of VANETs such as high density, high mobility and bandwidth limitations in exchanging messages. This makes the security system more efficient, accurate and capable of real time detection and quick in identification of malicious behaviour in VANETs. In this scheme, each vehicle log calculates and stores different parameter values after receiving the cooperative awareness messages from nearby vehicles. The vehicles exchange their log data and determine the difference between the parameters, which is utilised to detect Sybil attacks and Wormhole attacks. In order to realize efficient and effective intrusion detection system, we use the well-known network simulator (ns-2) to verify the performance of the security system. Simulation results indicate that the security system can achieve high detection rates and effectively detect anomalies with low rate of false alarms. PMID:29315302

  12. A hierarchical detection method in external communication for self-driving vehicles based on TDMA.

    Science.gov (United States)

    Alheeti, Khattab M Ali; Al-Ani, Muzhir Shaban; McDonald-Maier, Klaus

    2018-01-01

    Security is considered a major challenge for self-driving and semi self-driving vehicles. These vehicles depend heavily on communications to predict and sense their external environment used in their motion. They use a type of ad hoc network termed Vehicular ad hoc networks (VANETs). Unfortunately, VANETs are potentially exposed to many attacks on network and application level. This paper, proposes a new intrusion detection system to protect the communication system of self-driving cars; utilising a combination of hierarchical models based on clusters and log parameters. This security system is designed to detect Sybil and Wormhole attacks in highway usage scenarios. It is based on clusters, utilising Time Division Multiple Access (TDMA) to overcome some of the obstacles of VANETs such as high density, high mobility and bandwidth limitations in exchanging messages. This makes the security system more efficient, accurate and capable of real time detection and quick in identification of malicious behaviour in VANETs. In this scheme, each vehicle log calculates and stores different parameter values after receiving the cooperative awareness messages from nearby vehicles. The vehicles exchange their log data and determine the difference between the parameters, which is utilised to detect Sybil attacks and Wormhole attacks. In order to realize efficient and effective intrusion detection system, we use the well-known network simulator (ns-2) to verify the performance of the security system. Simulation results indicate that the security system can achieve high detection rates and effectively detect anomalies with low rate of false alarms.

  13. Monoclonal antibody-based serological methods for detection of Cucumber green mottle mosaic virus

    Directory of Open Access Journals (Sweden)

    Qian Yajuan

    2011-05-01

    Full Text Available Abstract Background Cucumber green mottle mosaic virus (CGMMV, a member of the genus Tobamovirus, can be transmitted by seeds and infects many cucurbit species, causing serious yield losses in cucumber and watermelon plants. In this paper, five serological methods including antigen-coated plate enzyme-linked immunosorbent assay (ACP-ELISA, triple antibody sandwich enzyme-linked immunosorbent assay (TAS-ELISA, Dot-immunobinding assay (DBIA, direct tissue blot immunoassay (DTBIA and immunocapture reverse transcriptase polymerase chain reaction (IC-RT-PCR were described for detection and diagnosis of CGMMV. Results Using the purified CGMMV particles as immunogens, six murine monoclonal antibodies (MAbs were produced. Five serological methods were established using the MAb 4H1 and detection sensitivity was compared using purified preparations and infected-plant tissue extracts. The detection sensitivity of ACP-ELISA was 0.16 ng of purified CGMMV, whereas TAS-ELISA was more sensitive than ACP-ELISA with a minimum detection of 0.04 ng of purified CGMMV. The sensitivities of TAS-ELISA and DBIA were similar for detecting CGMMV in infected-plant tissue extracts, and were four times higher than ACP-ELISA. The IC-RT-PCR was the most sensitive method, which could detect as little as 0.1 pg of purified virus. The detection sensitivity of IC-RT-PCR for CGMMV-infected plant tissues was about 400 times higher than that of TAS-ELISA and DBIA. Conclusions The established ACP-ELISA, TAS-ELISA, DBIA and DTBIA are suitable for routine CGMMV detection of large-scale samples in the field survey, while IC-RT-PCR is more sensitive and suitable for acquiring information about the viral genome.

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

    Directory of Open Access Journals (Sweden)

    Lei Ma

    2016-09-01

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

  15. [Study on Ammonia Emission Rules in a Dairy Feedlot Based on Laser Spectroscopy Detection Method].

    Science.gov (United States)

    He, Ying; Zhang, Yu-jun; You, Kun; Wang, Li-ming; Gao, Yan-wei; Xu, Jin-feng; Gao, Zhi-ling; Ma, Wen-qi

    2016-03-01

    It needs on-line monitoring of ammonia concentration on dairy feedlot to disclose ammonia emissions characteristics accurately for reducing ammonia emissions and improving the ecological environment. The on-line monitoring system for ammonia concentration has been designed based on Tunable Diode Laser Absorption Spectroscopy (TDLAS) technology combining with long open-path technology, then the study has been carried out with inverse dispersion technique and the system. The ammonia concentration in-situ has been detected and ammonia emission rules have been analyzed on a dairy feedlot in Baoding in autumn and winter of 2013. The monitoring indicated that the peak of ammonia concentration was 6.11 x 10(-6) in autumn, and that was 6.56 x 10(-6) in winter. The concentration results show that the variation of ammonia concentration had an obvious diurnal periodicity, and the general characteristic of diurnal variation was that the concentration was low in the daytime and was high at night. The ammonia emissions characteristic was obtained with inverse dispersion model that the peak of ammonia emissions velocity appeared at noon. The emission velocity was from 1.48 kg/head/hr to 130.6 kg/head/hr in autumn, and it was from 0.004 5 kg/head/hr to 43.32 kg/head/hr in winter which was lower than that in autumn. The results demonstrated ammonia emissions had certain seasonal differences in dairy feedlot scale. In conclusion, the ammonia concentration was detected with optical technology, and the ammonia emissions results were acquired by inverse dispersion model analysis with large range, high sensitivity, quick response without gas sampling. Thus, it's an effective method for ammonia emissions monitoring in dairy feedlot that provides technical support for scientific breeding.

  16. A Model System for Concurrent Detection of Antigen and Antibody Based on Immunological Fluorescent Method

    Directory of Open Access Journals (Sweden)

    Yuan-Cheng Cao

    2015-01-01

    Full Text Available This paper describes a combined antigen/antibody immunoassay implemented in a 96-well plate using fluorescent spectroscopic method. First, goat anti-human IgG was used to capture human IgG (model antigen; goat anti-human IgG (Cy3 or FITC was used to detect the model antigen; a saturating level of model antigen was then added followed by unlabelled goat anti-human IgG (model antibody; finally, Cy3 labelled rabbit anti-goat IgG was used to detect the model antibody. Two approaches were applied to the concomitant assay to analyze the feasibility. The first approach applied FITC and Cy3 when both targets were present at the same time, resulting in 50 ng/mL of the antibody detection limit and 10 ng/mL of antigen detection limit in the quantitative measurements of target concentration, taking the consideration of FRET efficiency of 68% between donor and acceptor. The sequential approach tended to lower the signal/noise (S/N ratio and the detection of the model antigen (lower than 1 ng/mL had better sensitivity than the model antibody (lower than 50 ng/mL. This combined antigen/antibody method might be useful for combined detection of antigens and antibodies. It will be helpful to screen for both antigen and antibody particularly in the situations of the multiserotype and high-frequency mutant virus infections.

  17. A new method for non-labeling attomolar detection of diseases based on an individual gold nanorod immunosensor

    DEFF Research Database (Denmark)

    Phuoc Long, Truong; Cao, Cuong; Park, Sungho

    2011-01-01

    Herein, we present the use of a single gold nanorod sensor for detection of diseases on an antibodyfunctionalized surface, based on antibody–antigen interaction and the localized surface plasmon resonance (LSPR) lmax shifts of the resonant Rayleigh light scattering spectra. By replacing...... can be equally compared to the assays based on DNA biobarcodes. This study shows that a gold nanorod has been used as a single nanobiosensor to detect antigens for the first time; and the detection method based on the resonant Rayleigh scattering spectrum of individual gold nanorods enables a simple...

  18. Active damage detection method based on support vector machine and impulse response

    International Nuclear Information System (INIS)

    Taniguchi, Ryuta; Mita, Akira

    2004-01-01

    An active damage detection method was proposed to characterize damage in bolted joints. The purpose of this study is to propose a damage detection method that can obtain the detailed information of the damage by creating feature vectors for pattern recognition. In the proposed method, the wavelet transform is applied to the sensor signals, and the feature vectors are defined by second power average of the amplitude. The feature vectors generated by experiments were successfully used as the training data for Support Vector Machine (SVM). By applying the wavelet transform to time-frequency analysis, the accuracy of pattern recognition was raised in both correlation coefficient and SVM applications. Moreover, the SVM could identify the damage with very strong discernment capability than others. Applicability of the proposed method was successfully demonstrated. (author)

  19. A Time-Domain Structural Damage Detection Method Based on Improved Multiparticle Swarm Coevolution Optimization Algorithm

    Directory of Open Access Journals (Sweden)

    Shao-Fei Jiang

    2014-01-01

    Full Text Available Optimization techniques have been applied to structural health monitoring and damage detection of civil infrastructures for two decades. The standard particle swarm optimization (PSO is easy to fall into the local optimum and such deficiency also exists in the multiparticle swarm coevolution optimization (MPSCO. This paper presents an improved MPSCO algorithm (IMPSCO firstly and then integrates it with Newmark’s algorithm to localize and quantify the structural damage by using the damage threshold proposed. To validate the proposed method, a numerical simulation and an experimental study of a seven-story steel frame were employed finally, and a comparison was made between the proposed method and the genetic algorithm (GA. The results show threefold: (1 the proposed method not only is capable of localization and quantification of damage, but also has good noise-tolerance; (2 the damage location can be accurately detected using the damage threshold proposed in this paper; and (3 compared with the GA, the IMPSCO algorithm is more efficient and accurate for damage detection problems in general. This implies that the proposed method is applicable and effective in the community of damage detection and structural health monitoring.

  20. Molecular analysis of dolphin morbillivirus: A new sensitive detection method based on nested RT-PCR.

    Science.gov (United States)

    Centelleghe, Cinzia; Beffagna, Giorgia; Zanetti, Rossella; Zappulli, Valentina; Di Guardo, Giovanni; Mazzariol, Sandro

    2016-09-01

    Cetacean Morbillivirus (CeMV) has been identified as the most pathogenic virus for cetaceans. Over the past three decades, this RNA virus has caused several outbreaks of lethal disease in odontocetes and mysticetes worldwide. Isolation and identification of CeMV RNA is very challenging in whales because of the poor preservation status frequently shown by tissues from stranded animals. Nested reverse transcription polymerase chain reaction (nested RT-PCR) is used instead of conventional RT-PCR when it is necessary to increase the sensitivity and the specificity of the reaction. This study describes a new nested RT-PCR technique useful to amplify small amounts of the cDNA copy of Cetacean morbillivirus (CeMV) when it is present in scant quantity in whales' biological specimens. This technique was used to analyze different tissues (lung, brain, spleen and other lymphoid tissues) from one under human care seal and seven cetaceans stranded along the Italian coastline between October 2011 and September 2015. A well-characterized, 200 base pair (bp) fragment of the dolphin Morbillivirus (DMV) haemagglutinin (H) gene, obtained by nested RT-PCR, was sequenced and used to confirm DMV positivity in all the eight marine mammals under study. In conclusion, this nested RT-PCR protocol can represent a sensitive detection method to identify CeMV-positive, poorly preserved tissue samples. Furthermore, this is also a rather inexpensive molecular technique, relatively easy to apply. Copyright © 2016 Elsevier B.V. All rights reserved.

  1. Leak detection method

    International Nuclear Information System (INIS)

    1978-01-01

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

  2. A Fractional Lower Order Statistics-Based MIMO Detection Method in Impulse Noise for Power Line Channel

    Directory of Open Access Journals (Sweden)

    CHEN, Z.

    2014-11-01

    Full Text Available Impulse noise in power line communication (PLC channel seriously degrades the performance of Multiple-Input Multiple-Output (MIMO system. To remedy this problem, a MIMO detection method based on fractional lower order statistics (FLOS for PLC channel with impulse noise is proposed in this paper. The alpha stable distribution is used to model impulse noise, and FLOS is applied to construct the criteria of MIMO detection. Then the optimal detection solution is obtained by recursive least squares algorithm. Finally, the transmitted signals in PLC MIMO system are restored with the obtained detection matrix. The proposed method does not require channel estimation and has low computational complexity. The simulation results show that the proposed method has a better PLC MIMO detection performance than the existing ones under impulsive noise environment.

  3. Evaluating a Team-Based Learning Method for Detecting Dental Caries in Dental Students

    Science.gov (United States)

    Park, Sang E.; Kim, Junhyck; Anderson, Nina

    2014-01-01

    The purpose of the study was to investigate whether the team-based learning environment facilitated the competency of third year dental students in caries detection and activity assessment. Corresponding data were achieved using digital radiographs to determine the carious lesions in three clinical cases. The distribution of the caries evaluations…

  4. An Islanding Detection Method by Using Frequency Positive Feedback Based on FLL for Single-Phase Microgrid

    DEFF Research Database (Denmark)

    Sun, Qinfei; Guerrero, Josep M.; Jing, Tianjun

    2017-01-01

    An active islanding detection method based on Frequency-Locked Loop (FLL) for constant power controlled inverter in single-phase microgrid is proposed. This method generates a phase shift comparing the instantaneous frequency obtained from FLL unit with the nominal frequency to modify the reference...

  5. Drugs of abuse detection in saliva based on actuated optical method

    Science.gov (United States)

    Shao, Jie; Li, Zhenyu; Jiang, Hong; Wang, Wenlong; Wu, Yixuan

    2014-12-01

    There has been a considerable increase in the abuse of drugs during the past decade. Combing drug use with driving is very dangerous. More than 11% of drivers in a roadside survey tested positive for drugs, while 18% of drivers killed in accidents tested positive for drugs as reported in USA, 2007. Toward developing a rapid drug screening device, we use saliva as the sample, and combining the traditional immunoassays method with optical magnetic technology. There were several methods for magnetic nanoparticles detection, such as magnetic coils, SQUID, microscopic imaging, and Hall sensors. All of these methods were not suitable for our demands. By developing a novel optical scheme, we demonstrate high-sensitivity detection in saliva. Drugs of abuse are detected at sub-nano gram per milliliter levels in less than 120 seconds. Evanescent wave principle has been applied to sensitively monitor the presence of magnetic nanoparticles on the binding surface. Like the total internal reflection fluorescence microscope (TIRFM), evanescent optical field is generated at the plastic/fluid interface, which decays exponentially and penetrates into the fluid by only a sub-wavelength distance. By disturbance total internal reflection with magnetic nanoparticles, the optical intensity would be influenced. We then detected optical output by imaging the sensor surface onto a CCD camera. We tested four drugs tetrahydrocannabinol (THC), methamphetamine (MAMP), ketamine (KET), morphine (OPI), using this technology. 100 ng mL-1 sensitivity was achieved, and obvious evidence showed that this results could be improved in further researches.

  6. Microscope image based fully automated stomata detection and pore measurement method for grapevines

    Directory of Open Access Journals (Sweden)

    Hiranya Jayakody

    2017-11-01

    Full Text Available Abstract Background Stomatal behavior in grapevines has been identified as a good indicator of the water stress level and overall health of the plant. Microscope images are often used to analyze stomatal behavior in plants. However, most of the current approaches involve manual measurement of stomatal features. The main aim of this research is to develop a fully automated stomata detection and pore measurement method for grapevines, taking microscope images as the input. The proposed approach, which employs machine learning and image processing techniques, can outperform available manual and semi-automatic methods used to identify and estimate stomatal morphological features. Results First, a cascade object detection learning algorithm is developed to correctly identify multiple stomata in a large microscopic image. Once the regions of interest which contain stomata are identified and extracted, a combination of image processing techniques are applied to estimate the pore dimensions of the stomata. The stomata detection approach was compared with an existing fully automated template matching technique and a semi-automatic maximum stable extremal regions approach, with the proposed method clearly surpassing the performance of the existing techniques with a precision of 91.68% and an F1-score of 0.85. Next, the morphological features of the detected stomata were measured. Contrary to existing approaches, the proposed image segmentation and skeletonization method allows us to estimate the pore dimensions even in cases where the stomatal pore boundary is only partially visible in the microscope image. A test conducted using 1267 images of stomata showed that the segmentation and skeletonization approach was able to correctly identify the stoma opening 86.27% of the time. Further comparisons made with manually traced stoma openings indicated that the proposed method is able to estimate stomata morphological features with accuracies of 89.03% for area

  7. Novel PCR Assays Complement Laser Biosensor-Based Method and Facilitate Listeria Species Detection from Food

    Directory of Open Access Journals (Sweden)

    Kwang-Pyo Kim

    2015-09-01

    Full Text Available The goal of this study was to develop the Listeria species-specific PCR assays based on a house-keeping gene (lmo1634 encoding alcohol acetaldehyde dehydrogenase (Aad, previously designated as Listeria adhesion protein (LAP, and compare results with a label-free light scattering sensor, BARDOT (bacterial rapid detection using optical scattering technology. PCR primer sets targeting the lap genes from the species of Listeria sensu stricto were designed and tested with 47 Listeria and 8 non-Listeria strains. The resulting PCR primer sets detected either all species of Listeria sensu stricto or individual L. innocua, L. ivanovii and L. seeligeri, L. welshimeri, and L. marthii without producing any amplified products from other bacteria tested. The PCR assays with Listeria sensu stricto-specific primers also successfully detected all species of Listeria sensu stricto and/or Listeria innocua from mixed culture-inoculated food samples, and each bacterium in food was verified by using the light scattering sensor that generated unique scatter signature for each species of Listeria tested. The PCR assays based on the house-keeping gene aad (lap can be used for detection of either all species of Listeria sensu stricto or certain individual Listeria species in a mixture from food with a detection limit of about 104 CFU/mL.

  8. Development of PCR-based detection methods for the quarantine phytopathogen Synchytrium endobioticum, causal agent of wart disease

    NARCIS (Netherlands)

    Boogert, van den P.H.J.F.; Gent-Pelzer, van M.P.E.; Bonants, P.J.M.; Boer, de S.H.; Wander, J.G.N.; Lévesque, C.A.; Leeuwen, van G.C.M.; Baayen, R.P.

    2005-01-01

    Abstract PCR-based methods were developed for the detection and quantification of the potato pathogen Synchytrium endobioticum in soil extracts and in planta. PCR primers, based on the internal transcribed spacer region of the multi-copy gene rDNA were tested for specificity, sensitivity and

  9. Hot Spots Detection of Operating PV Arrays through IR Thermal Image Using Method Based on Curve Fitting of Gray Histogram

    Directory of Open Access Journals (Sweden)

    Jiang Lin

    2016-01-01

    Full Text Available The overall efficiency of PV arrays is affected by hot spots which should be detected and diagnosed by applying responsible monitoring techniques. The method using the IR thermal image to detect hot spots has been studied as a direct, noncontact, nondestructive technique. However, IR thermal images suffer from relatively high stochastic noise and non-uniformity clutter, so the conventional methods of image processing are not effective. The paper proposes a method to detect hotspots based on curve fitting of gray histogram. The result of MATLAB simulation proves the method proposed in the paper is effective to detect the hot spots suppressing the noise generated during the process of image acquisition.

  10. A magnetic bead-based method for concentrating DNA from human urine for downstream detection.

    Science.gov (United States)

    Bordelon, Hali; Russ, Patricia K; Wright, David W; Haselton, Frederick R

    2013-01-01

    Due to the presence of PCR inhibitors, PCR cannot be used directly on most clinical samples, including human urine, without pre-treatment. A magnetic bead-based strategy is one potential method to collect biomarkers from urine samples and separate the biomarkers from PCR inhibitors. In this report, a 1 mL urine sample was mixed within the bulb of a transfer pipette containing lyophilized nucleic acid-silica adsorption buffer and silica-coated magnetic beads. After mixing, the sample was transferred from the pipette bulb to a small diameter tube, and captured biomarkers were concentrated using magnetic entrainment of beads through pre-arrayed wash solutions separated by small air gaps. Feasibility was tested using synthetic segments of the 140 bp tuberculosis IS6110 DNA sequence spiked into pooled human urine samples. DNA recovery was evaluated by qPCR. Despite the presence of spiked DNA, no DNA was detectable in unextracted urine samples, presumably due to the presence of PCR inhibitors. However, following extraction with the magnetic bead-based method, we found that ∼50% of spiked TB DNA was recovered from human urine containing roughly 5×10(3) to 5×10(8) copies of IS6110 DNA. In addition, the DNA was concentrated approximately ten-fold into water. The final concentration of DNA in the eluate was 5×10(6), 14×10(6), and 8×10(6) copies/µL for 1, 3, and 5 mL urine samples, respectively. Lyophilized and freshly prepared reagents within the transfer pipette produced similar results, suggesting that long-term storage without refrigeration is possible. DNA recovery increased with the length of the spiked DNA segments from 10±0.9% for a 75 bp DNA sequence to 42±4% for a 100 bp segment and 58±9% for a 140 bp segment. The estimated LOD was 77 copies of DNA/µL of urine. The strategy presented here provides a simple means to achieve high nucleic acid recovery from easily obtained urine samples, which does not contain inhibitors of PCR.

  11. A magnetic bead-based method for concentrating DNA from human urine for downstream detection.

    Directory of Open Access Journals (Sweden)

    Hali Bordelon

    Full Text Available Due to the presence of PCR inhibitors, PCR cannot be used directly on most clinical samples, including human urine, without pre-treatment. A magnetic bead-based strategy is one potential method to collect biomarkers from urine samples and separate the biomarkers from PCR inhibitors. In this report, a 1 mL urine sample was mixed within the bulb of a transfer pipette containing lyophilized nucleic acid-silica adsorption buffer and silica-coated magnetic beads. After mixing, the sample was transferred from the pipette bulb to a small diameter tube, and captured biomarkers were concentrated using magnetic entrainment of beads through pre-arrayed wash solutions separated by small air gaps. Feasibility was tested using synthetic segments of the 140 bp tuberculosis IS6110 DNA sequence spiked into pooled human urine samples. DNA recovery was evaluated by qPCR. Despite the presence of spiked DNA, no DNA was detectable in unextracted urine samples, presumably due to the presence of PCR inhibitors. However, following extraction with the magnetic bead-based method, we found that ∼50% of spiked TB DNA was recovered from human urine containing roughly 5×10(3 to 5×10(8 copies of IS6110 DNA. In addition, the DNA was concentrated approximately ten-fold into water. The final concentration of DNA in the eluate was 5×10(6, 14×10(6, and 8×10(6 copies/µL for 1, 3, and 5 mL urine samples, respectively. Lyophilized and freshly prepared reagents within the transfer pipette produced similar results, suggesting that long-term storage without refrigeration is possible. DNA recovery increased with the length of the spiked DNA segments from 10±0.9% for a 75 bp DNA sequence to 42±4% for a 100 bp segment and 58±9% for a 140 bp segment. The estimated LOD was 77 copies of DNA/µL of urine. The strategy presented here provides a simple means to achieve high nucleic acid recovery from easily obtained urine samples, which does not contain inhibitors of PCR.

  12. An Overview of Deep Learning Based Methods for Unsupervised and Semi-Supervised Anomaly Detection in Videos

    Directory of Open Access Journals (Sweden)

    B. Ravi Kiran

    2018-02-01

    Full Text Available Videos represent the primary source of information for surveillance applications. Video material is often available in large quantities but in most cases it contains little or no annotation for supervised learning. This article reviews the state-of-the-art deep learning based methods for video anomaly detection and categorizes them based on the type of model and criteria of detection. We also perform simple studies to understand the different approaches and provide the criteria of evaluation for spatio-temporal anomaly detection.

  13. Improved detection of Mycobacterium bovis infection in bovine lymph node tissue using immunomagnetic separation (IMS-based methods.

    Directory of Open Access Journals (Sweden)

    Linda D Stewart

    Full Text Available Immunomagnetic separation (IMS can selectively isolate and concentrate Mycobacterium bovis cells from lymph node tissue to facilitate subsequent detection by PCR (IMS-PCR or culture (IMS-MGIT. This study describes application of these novel IMS-based methods to test for M. bovis in a survey of 280 bovine lymph nodes (206 visibly lesioned (VL, 74 non-visibly lesioned (NVL collected at slaughter as part of the Northern Ireland bovine TB eradication programme. Their performance was evaluated relative to culture. Overall, 174 (62.1% lymph node samples tested positive by culture, 162 (57.8% by IMS-PCR (targeting IS6110, and 191 (68.2% by IMS-MGIT culture. Twelve (6.9% of the 174 culture positive lymph node samples were not detected by either of the IMS-based methods. However, an additional 79 M. bovis positive lymph node samples (27 (13.1% VL and 52 (70.3% NVL were detected by the IMS-based methods and not by culture. When low numbers of viable M. bovis are present in lymph nodes (e.g. in NVLs of skin test reactor cattle decontamination prior to culture may adversely affect viability, leading to false negative culture results. In contrast, IMS specifically captures whole M. bovis cells (live, dead or potentially dormant which are not subject to any deleterious treatment before detection by PCR or MGIT culture. During this study only 2.7% of NVL lymph nodes tested culture positive, whereas 70.3% of the same samples tested M. bovis positive by the IMS-based tests. Results clearly demonstrate that not only are the IMS-based methods more rapid but they have greater detection sensitivity than the culture approach currently used for the detection of M. bovis infection in cattle. Adoption of the IMS-based methods for lymph node testing would have the potential to improve M. bovis detection in clinical samples.

  14. Weak wide-band signal detection method based on small-scale periodic state of Duffing oscillator

    Science.gov (United States)

    Hou, Jian; Yan, Xiao-peng; Li, Ping; Hao, Xin-hong

    2018-03-01

    The conventional Duffing oscillator weak signal detection method, which is based on a strong reference signal, has inherent deficiencies. To address these issues, the characteristics of the Duffing oscillatorʼs phase trajectory in a small-scale periodic state are analyzed by introducing the theory of stopping oscillation system. Based on this approach, a novel Duffing oscillator weak wide-band signal detection method is proposed. In this novel method, the reference signal is discarded, and the to-be-detected signal is directly used as a driving force. By calculating the cosine function of a phase space angle, a single Duffing oscillator can be used for weak wide-band signal detection instead of an array of uncoupled Duffing oscillators. Simulation results indicate that, compared with the conventional Duffing oscillator detection method, this approach performs better in frequency detection intervals, and reduces the signal-to-noise ratio detection threshold, while improving the real-time performance of the system. Project supported by the National Natural Science Foundation of China (Grant No. 61673066).

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

    Science.gov (United States)

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

    2018-04-01

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

  16. Mass spectrometry-based methods for detection and differentiation of botulinum neurotoxins

    Science.gov (United States)

    Schmidt, Jurgen G [Los Alamos, NM; Boyer, Anne E [Atlanta, GA; Kalb, Suzanne R [Atlanta, GA; Moura, Hercules [Tucker, GA; Barr, John R [Suwannee, GA; Woolfitt, Adrian R [Atlanta, GA

    2009-11-03

    The present invention is directed to a method for detecting the presence of clostridial neurotoxins in a sample by mixing a sample with a peptide that can serve as a substrate for proteolytic activity of a clostridial neurotoxin; and measuring for proteolytic activity of a clostridial neurotoxin by a mass spectroscopy technique. In one embodiment, the peptide can have an affinity tag attached at two or more sites.

  17. The Continuous Monitoring of Desert Dust using an Infrared-based Dust Detection and Retrieval Method

    Science.gov (United States)

    Duda, David P.; Minnis, Patrick; Trepte, Qing; Sun-Mack, Sunny

    2006-01-01

    Airborne dust and sand are significant aerosol sources that can impact the atmospheric and surface radiation budgets. Because airborne dust affects visibility and air quality, it is desirable to monitor the location and concentrations of this aerosol for transportation and public health. Although aerosol retrievals have been derived for many years using visible and near-infrared reflectance measurements from satellites, the detection and quantification of dust from these channels is problematic over bright surfaces, or when dust concentrations are large. In addition, aerosol retrievals from polar orbiting satellites lack the ability to monitor the progression and sources of dust storms. As a complement to current aerosol dust retrieval algorithms, multi-spectral thermal infrared (8-12 micron) data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Meteosat-8 Spinning Enhanced Visible and Infrared Imager (SEVIRI) are used in the development of a prototype dust detection method and dust property retrieval that can monitor the progress of Saharan dust fields continuously, both night and day. The dust detection method is incorporated into the processing of CERES (Clouds and the Earth s Radiant Energy System) aerosol retrievals to produce dust property retrievals. Both MODIS (from Terra and Aqua) and SEVERI data are used to develop the method.

  18. Method for Detection of Airborne UEs based on LTE Radio Measurements

    DEFF Research Database (Denmark)

    Wigard, Jeroen; Amorim, Rafhael Medeiros de; Nguyen, Huan Cong

    2017-01-01

    management can be optimized for UAVs separately from terrestrial UEs. In this paper, we present a classification algorithm using existing LTE UE radio measurements to identify whether a UE is airborne or terrestrial. The method is verified with LTE measurements made in a rural area at different heights......, including terrestrial measurements and it is shown that the method in 3 out of the 4 different measurement cases can detect a UE to be airborne with 99% likelihood, while the fourth case still can classify a UE correctly in 95% of the cases. The right classification can further be improved by taking...

  19. An improved AE detection method of rail defect based on multi-level ANC with VSS-LMS

    Science.gov (United States)

    Zhang, Xin; Cui, Yiming; Wang, Yan; Sun, Mingjian; Hu, Hengshan

    2018-01-01

    In order to ensure the safety and reliability of railway system, Acoustic Emission (AE) method is employed to investigate rail defect detection. However, little attention has been paid to the defect detection at high speed, especially for noise interference suppression. Based on AE technology, this paper presents an improved rail defect detection method by multi-level ANC with VSS-LMS. Multi-level noise cancellation based on SANC and ANC is utilized to eliminate complex noises at high speed, and tongue-shaped curve with index adjustment factor is proposed to enhance the performance of variable step-size algorithm. Defect signals and reference signals are acquired by the rail-wheel test rig. The features of noise signals and defect signals are analyzed for effective detection. The effectiveness of the proposed method is demonstrated by comparing with the previous study, and different filter lengths are investigated to obtain a better noise suppression performance. Meanwhile, the detection ability of the proposed method is verified at the top speed of the test rig. The results clearly illustrate that the proposed method is effective in detecting rail defects at high speed, especially for noise interference suppression.

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

    Directory of Open Access Journals (Sweden)

    ZHANG Zhiqiang

    2018-01-01

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

  1. Development of quench detection/protection system based on active power method for superconducting magnet by using capacitor circuit

    International Nuclear Information System (INIS)

    Nanato, N.; Otsuka, T.; Hesaka, S.; Murase, S.

    2013-01-01

    Highlights: ► The authors have presented an active power method for quench detection. ► A method for improving its characteristics using a capacitor circuit was proposed. ► Quench detection/protection test for a Bi2223 superconducting coil was carried out. ► The proposed method was more useful than the conventional one. -- Abstract: When a quench occurs in a superconducting magnet, excessive joule heating in normal region may damage the magnet. It is necessary to detect the quench as soon as possible and discharge magnetic energy stored in the magnet. The authors have presented a quench detection/protection system based on an active power method which detects the quench regardless of a self-inductive and mutual-inductive voltages and electromagnetic noise. In the conventional active power method, the inductive voltages are removed by cancel coils. In this paper, the authors propose a method to cancel an inductive voltage using a capacitor circuit. The quench detection/protection system becomes more precise and smaller than the conventional system through the capacitor circuit

  2. An Efficient Forensic Method for Copy–move Forgery Detection based on DWT-FWHT

    Directory of Open Access Journals (Sweden)

    B. Yang

    2013-12-01

    Full Text Available As the increased availability of sophisticated image processing software and the widespread use of Internet, digital images are easy to acquire and manipulate. The authenticity of the received images is becoming more and more important. Copy-move forgery is one of the most common forgery methods. When creating a Copy-move forgery, it is often necessary to add or remove important features from an image. To carry out such forensic analysis, various technological instruments have been developed in the literatures. However, most of them are time-consuming. In this paper, a more efficient method is proposed. First, the image size is reduced by Discrete Wavelet Transform (DWT. Second, the image is divided into overlapping blocks of equal size and, feature of each block is extracted by fast Walsh-Hadamard Transform (FWHT. Duplicated regions are then detected by lexicographically sorting all features of the image blocks. To make the range matching more efficient, multi-hop jump (MHJ algorithm is using to jump over some the “unnecessary testing blocks” (UTB. Experimental results demonstrated that the proposed method not only is able to detect the copy-move forgery accurately but also can reduce the processing time greatly compared with other methods.

  3. Nonlinear Multiantenna Detection Methods

    Directory of Open Access Journals (Sweden)

    Chen Sheng

    2004-01-01

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

  4. Establishment and application of a multiplex genetic mutation-detection method of lung cancer based on MassARRAY platform

    International Nuclear Information System (INIS)

    Tian, Hong-Xia; Zhang, Xu-Chao; Wang, Zhen; Chen, Jian-Guang; Chen, Shi-Liang; Guo, Wei-Bang; Wu, Yi-Long

    2016-01-01

    Objective: This study aims to establish a method for highly parallel multiplexed detection of genetic mutations in Chinese lung cancer samples through Agena iPLEX chemistry and matrix-assisted laser desorption ionization time-of-flight analysis on MassARRAY mass spectrometry platform. Methods: We reviewed the related literature and data on lung cancer treatments. We also identified 99 mutation hot spots in 13 target genes closely related to the pathogenesis, drug resistance, and metastasis of lung cancer. A total of 297 primers, composed of 99 paired forward and reverse amplification primers and 99 matched extension primers, were designed using Assay Design software. The detection method was established by analyzing eight cell lines and six lung cancer specimens. The proposed method was then validated through comparisons by using a LungCarta TM kit. The sensitivity and specificity of the proposed method were evaluated by directly sequencing EGFR and KRAS genes in 100 lung cancer cases. Results: The proposed method was able to detect multiplex genetic mutations in lung cancer cell lines. This finding was consistent with the observations on previously reported mutations. The proposed method can also detect such mutations in clinical lung cancer specimens. This result was consistent with the observations with LungCarta TM kit. However, an FGFR2 mutation was detected only through the proposed method. The measured sensitivity and specificity were 100% and 96.3%, respectively. Conclusions: The proposed MassARRAY technology-based multiplex method can detect genetic mutations in Chinese lung cancer patients. Therefore, the proposed method can be applied to detect mutations in other cancer tissues

  5. A CNN-Based Method of Vehicle Detection from Aerial Images Using Hard Example Mining

    Directory of Open Access Journals (Sweden)

    Yohei Koga

    2018-01-01

    Full Text Available Recently, deep learning techniques have had a practical role in vehicle detection. While much effort has been spent on applying deep learning to vehicle detection, the effective use of training data has not been thoroughly studied, although it has great potential for improving training results, especially in cases where the training data are sparse. In this paper, we proposed using hard example mining (HEM in the training process of a convolutional neural network (CNN for vehicle detection in aerial images. We applied HEM to stochastic gradient descent (SGD to choose the most informative training data by calculating the loss values in each batch and employing the examples with the largest losses. We picked 100 out of both 500 and 1000 examples for training in one iteration, and we tested different ratios of positive to negative examples in the training data to evaluate how the balance of positive and negative examples would affect the performance. In any case, our method always outperformed the plain SGD. The experimental results for images from New York showed improved performance over a CNN trained in plain SGD where the F1 score of our method was 0.02 higher.

  6. Remote detection device and detection method therefor

    International Nuclear Information System (INIS)

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

    1997-01-01

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

  7. A study on new method of noninvasive esophageal venous pressure measurement based on the airflow and laser detection technology.

    Science.gov (United States)

    Hu, Chenghuan; Huang, Feizhou; Zhang, Rui; Zhu, Shaihong; Nie, Wanpin; Liu, Xunyang; Liu, Yinglong; Li, Peng

    2015-01-01

    Using optics combined with automatic control and computer real-time image detection technology, a novel noninvasive method of noncontact pressure manometry was developed based on the airflow and laser detection technology in this study. The new esophageal venous pressure measurement system was tested in-vitro experiments. A stable and adjustable pulse stream was produced from a self-developed pump and a laser emitting apparatus could generate optical signals which can be captured by image acquisition and analysis system program. A synchronization system simultaneous measured the changes of air pressure and the deformation of the vein wall to capture the vascular deformation while simultaneously record the current pressure value. The results of this study indicated that the pressure values tested by the new method have good correlation with the actual pressure value in animal experiments. The new method of noninvasive pressure measurement based on the airflow and laser detection technology is accurate, feasible, repeatable and has a good application prospects.

  8. 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.

  9. An Automatic Detection Method of Nanocomposite Film Element Based on GLCM and Adaboost M1

    Directory of Open Access Journals (Sweden)

    Hai Guo

    2015-01-01

    Full Text Available An automatic detection model adopting pattern recognition technology is proposed in this paper; it can realize the measurement to the element of nanocomposite film. The features of gray level cooccurrence matrix (GLCM can be extracted from different types of surface morphology images of film; after that, the dimension reduction of film can be handled by principal component analysis (PCA. So it is possible to identify the element of film according to the Adaboost M1 algorithm of a strong classifier with ten decision tree classifiers. The experimental result shows that this model is superior to the ones of SVM (support vector machine, NN and BayesNet. The method proposed can be widely applied to the automatic detection of not only nanocomposite film element but also other nanocomposite material elements.

  10. Detecting and Identifying Industrial Gases by a Method Based on Olfactory Machine at Different Concentrations

    Directory of Open Access Journals (Sweden)

    Yunlong Sun

    2018-01-01

    Full Text Available Gas sensors have been widely reported for industrial gas detection and monitoring. However, the rapid detection and identification of industrial gases are still a challenge. In this work, we measure four typical industrial gases including CO2, CH4, NH3, and volatile organic compounds (VOCs based on electronic nose (EN at different concentrations. To solve the problem of effective classification and identification of different industrial gases, we propose an algorithm based on the selective local linear embedding (SLLE to reduce the dimensionality and extract the features of high-dimensional data. Combining the Euclidean distance (ED formula with the proposed algorithm, we can achieve better classification and identification of four kinds of gases. We compared the classification and recognition results of classical principal component analysis (PCA, linear discriminate analysis (LDA, and PCA + LDA algorithms with the proposed SLLE algorithm after selecting the original data and performing feature extraction. The experimental results show that the recognition accuracy rate of the SLLE reaches 91.36%, which is better than the other three algorithms. In addition, the SLLE algorithm provides more efficient and accurate responses to high-dimensional industrial gas data. It can be used in real-time industrial gas detection and monitoring combined with gas sensor networks.

  11. A FUZZY AUTOMATIC CAR DETECTION METHOD BASED ON HIGH RESOLUTION SATELLITE IMAGERY AND GEODESIC MORPHOLOGY

    Directory of Open Access Journals (Sweden)

    N. Zarrinpanjeh

    2017-09-01

    Full Text Available Automatic car detection and recognition from aerial and satellite images is mostly practiced for the purpose of easy and fast traffic monitoring in cities and rural areas where direct approaches are proved to be costly and inefficient. Towards the goal of automatic car detection and in parallel with many other published solutions, in this paper, morphological operators and specifically Geodesic dilation are studied and applied on GeoEye-1 images to extract car items in accordance with available vector maps. The results of Geodesic dilation are then segmented and labeled to generate primitive car items to be introduced to a fuzzy decision making system, to be verified. The verification is performed inspecting major and minor axes of each region and the orientations of the cars with respect to the road direction. The proposed method is implemented and tested using GeoEye-1 pansharpen imagery. Generating the results it is observed that the proposed method is successful according to overall accuracy of 83%. It is also concluded that the results are sensitive to the quality of available vector map and to overcome the shortcomings of this method, it is recommended to consider spectral information in the process of hypothesis verification.

  12. a Fuzzy Automatic CAR Detection Method Based on High Resolution Satellite Imagery and Geodesic Morphology

    Science.gov (United States)

    Zarrinpanjeh, N.; Dadrassjavan, F.

    2017-09-01

    Automatic car detection and recognition from aerial and satellite images is mostly practiced for the purpose of easy and fast traffic monitoring in cities and rural areas where direct approaches are proved to be costly and inefficient. Towards the goal of automatic car detection and in parallel with many other published solutions, in this paper, morphological operators and specifically Geodesic dilation are studied and applied on GeoEye-1 images to extract car items in accordance with available vector maps. The results of Geodesic dilation are then segmented and labeled to generate primitive car items to be introduced to a fuzzy decision making system, to be verified. The verification is performed inspecting major and minor axes of each region and the orientations of the cars with respect to the road direction. The proposed method is implemented and tested using GeoEye-1 pansharpen imagery. Generating the results it is observed that the proposed method is successful according to overall accuracy of 83%. It is also concluded that the results are sensitive to the quality of available vector map and to overcome the shortcomings of this method, it is recommended to consider spectral information in the process of hypothesis verification.

  13. A Benchmark of Lidar-Based Single Tree Detection Methods Using Heterogeneous Forest Data from the Alpine Space

    Directory of Open Access Journals (Sweden)

    Lothar Eysn

    2015-05-01

    Full Text Available In this study, eight airborne laser scanning (ALS-based single tree detection methods are benchmarked and investigated. The methods were applied to a unique dataset originating from different regions of the Alpine Space covering different study areas, forest types, and structures. This is the first benchmark ever performed for different forests within the Alps. The evaluation of the detection results was carried out in a reproducible way by automatically matching them to precise in situ forest inventory data using a restricted nearest neighbor detection approach. Quantitative statistical parameters such as percentages of correctly matched trees and omission and commission errors are presented. The proposed automated matching procedure presented herein shows an overall accuracy of 97%. Method based analysis, investigations per forest type, and an overall benchmark performance are presented. The best matching rate was obtained for single-layered coniferous forests. Dominated trees were challenging for all methods. The overall performance shows a matching rate of 47%, which is comparable to results of other benchmarks performed in the past. The study provides new insight regarding the potential and limits of tree detection with ALS and underlines some key aspects regarding the choice of method when performing single tree detection for the various forest types encountered in alpine regions.

  14. A model-based clustering method to detect infectious disease transmission outbreaks from sequence variation.

    Directory of Open Access Journals (Sweden)

    Rosemary M McCloskey

    2017-11-01

    Full Text Available Clustering infections by genetic similarity is a popular technique for identifying potential outbreaks of infectious disease, in part because sequences are now routinely collected for clinical management of many infections. A diverse number of nonparametric clustering methods have been developed for this purpose. These methods are generally intuitive, rapid to compute, and readily scale with large data sets. However, we have found that nonparametric clustering methods can be biased towards identifying clusters of diagnosis-where individuals are sampled sooner post-infection-rather than the clusters of rapid transmission that are meant to be potential foci for public health efforts. We develop a fundamentally new approach to genetic clustering based on fitting a Markov-modulated Poisson process (MMPP, which represents the evolution of transmission rates along the tree relating different infections. We evaluated this model-based method alongside five nonparametric clustering methods using both simulated and actual HIV sequence data sets. For simulated clusters of rapid transmission, the MMPP clustering method obtained higher mean sensitivity (85% and specificity (91% than the nonparametric methods. When we applied these clustering methods to published sequences from a study of HIV-1 genetic clusters in Seattle, USA, we found that the MMPP method categorized about half (46% as many individuals to clusters compared to the other methods. Furthermore, the mean internal branch lengths that approximate transmission rates were significantly shorter in clusters extracted using MMPP, but not by other methods. We determined that the computing time for the MMPP method scaled linearly with the size of trees, requiring about 30 seconds for a tree of 1,000 tips and about 20 minutes for 50,000 tips on a single computer. This new approach to genetic clustering has significant implications for the application of pathogen sequence analysis to public health, where

  15. A spectral method to detect community structure based on distance modularity matrix

    Science.gov (United States)

    Yang, Jin-Xuan; Zhang, Xiao-Dong

    2017-08-01

    There are many community organizations in social and biological networks. How to identify these community structure in complex networks has become a hot issue. In this paper, an algorithm to detect community structure of networks is proposed by using spectra of distance modularity matrix. The proposed algorithm focuses on the distance of vertices within communities, rather than the most weakly connected vertex pairs or number of edges between communities. The experimental results show that our method achieves better effectiveness to identify community structure for a variety of real-world networks and computer generated networks with a little more time-consumption.

  16. A Trajectory Generation Method Based on Edge Detection for Auto-Sealant Cartesian Robot

    Directory of Open Access Journals (Sweden)

    Eka Samsul Maarif

    2014-07-01

    Full Text Available This paper presents algorithm ingenerating trajectory for sealant process using captured image. Cartesian robot as auto-sealant in manufacturing process has increased productivity, reduces human error and saves time. But, different sealant path in many engine models means not only different trajectory but also different program. Therefore robot with detection ability to generate its own trajectory is needed. This paper describes best lighting technique in capturing image and applies edge detection in trajectory generation as the solution. The algorithm comprises image capturing, Canny edge detection, integral projection in localizing outer most edge, scanning coordinates, and generating vector direction codes. The experiment results show that the best technique is diffuse lighting at 10 Cd. The developed method gives connected point to point trajectory which forms sealant path with a point to next point distance is equal to 90° motor rotation. Directional movement for point to point trajectory is controlled by generated codes which are ready to be sent by serial communication to robot controller as instruction for motors which actuate axes X and Y directions.

  17. An Improved Azimuth Angle Estimation Method with a Single Acoustic Vector Sensor Based on an Active Sonar Detection System.

    Science.gov (United States)

    Zhao, Anbang; Ma, Lin; Ma, Xuefei; Hui, Juan

    2017-02-20

    In this paper, an improved azimuth angle estimation method with a single acoustic vector sensor (AVS) is proposed based on matched filtering theory. The proposed method is mainly applied in an active sonar detection system. According to the conventional passive method based on complex acoustic intensity measurement, the mathematical and physical model of this proposed method is described in detail. The computer simulation and lake experiments results indicate that this method can realize the azimuth angle estimation with high precision by using only a single AVS. Compared with the conventional method, the proposed method achieves better estimation performance. Moreover, the proposed method does not require complex operations in frequencydomain and achieves computational complexity reduction.

  18. An Improved Azimuth Angle Estimation Method with a Single Acoustic Vector Sensor Based on an Active Sonar Detection System

    Directory of Open Access Journals (Sweden)

    Anbang Zhao

    2017-02-01

    Full Text Available In this paper, an improved azimuth angle estimation method with a single acoustic vector sensor (AVS is proposed based on matched filtering theory. The proposed method is mainly applied in an active sonar detection system. According to the conventional passive method based on complex acoustic intensity measurement, the mathematical and physical model of this proposed method is described in detail. The computer simulation and lake experiments results indicate that this method can realize the azimuth angle estimation with high precision by using only a single AVS. Compared with the conventional method, the proposed method achieves better estimation performance. Moreover, the proposed method does not require complex operations in frequencydomain and achieves computational complexity reduction.

  19. A Novel Ship Detection Method Based on Gradient and Integral Feature for Single-Polarization Synthetic Aperture Radar Imagery

    Directory of Open Access Journals (Sweden)

    Hao Shi

    2018-02-01

    Full Text Available With the rapid development of remote sensing technologies, SAR satellites like China’s Gaofen-3 satellite have more imaging modes and higher resolution. With the availability of high-resolution SAR images, automatic ship target detection has become an important topic in maritime research. In this paper, a novel ship detection method based on gradient and integral features is proposed. This method is mainly composed of three steps. First, in the preprocessing step, a filter is employed to smooth the clutters and the smoothing effect can be adaptive adjusted according to the statistics information of the sub-window. Thus, it can retain details while achieving noise suppression. Second, in the candidate area extraction, a sea-land segmentation method based on gradient enhancement is presented. The integral image method is employed to accelerate computation. Finally, in the ship target identification step, a feature extraction strategy based on Haar-like gradient information and a Radon transform is proposed. This strategy decreases the number of templates found in traditional Haar-like methods. Experiments were performed using Gaofen-3 single-polarization SAR images, and the results showed that the proposed method has high detection accuracy and rapid computational efficiency. In addition, this method has the potential for on-board processing.

  20. Development of a Tandem Repeat-Based Polymerase Chain Displacement Reaction Method for Highly Sensitive Detection of 'Candidatus Liberibacter asiaticus'.

    Science.gov (United States)

    Lou, Binghai; Song, Yaqin; RoyChowdhury, Moytri; Deng, Chongling; Niu, Ying; Fan, Qijun; Tang, Yan; Zhou, Changyong

    2018-02-01

    Huanglongbing (HLB) is one of the most destructive diseases in citrus production worldwide. Early detection of HLB pathogens can facilitate timely removal of infected citrus trees in the field. However, low titer and uneven distribution of HLB pathogens in host plants make reliable detection challenging. Therefore, the development of effective detection methods with high sensitivity is imperative. This study reports the development of a novel method, tandem repeat-based polymerase chain displacement reaction (TR-PCDR), for the detection of 'Candidatus Liberibacter asiaticus', a widely distributed HLB-associated bacterium. A uniquely designed primer set (TR2-PCDR-F/TR2-PCDR-1R) and a thermostable Taq DNA polymerase mutant with strand displacement activity were used for TR-PCDR amplification. Performed in a regular thermal cycler, TR-PCDR could produce more than two amplicons after each amplification cycle. Sensitivity of the developed TR-PCDR was 10 copies of target DNA fragment. The sensitive level was proven to be 100× higher than conventional PCR and similar to real-time PCR. Data from the detection of 'Ca. L. asiaticus' with filed samples using the above three methods also showed similar results. No false-positive TR-PCDR amplification was observed from healthy citrus samples and water controls. These results thereby illustrated that the developed TR-PCDR method can be applied to the reliable, highly sensitive, and cost-effective detection of 'Ca. L. asiaticus'.

  1. Detection of HIV-1 p24 Gag in plasma by a nanoparticle-based bio-barcode-amplification method.

    Science.gov (United States)

    Kim, Eun-Young; Stanton, Jennifer; Korber, Bette T M; Krebs, Kendall; Bogdan, Derek; Kunstman, Kevin; Wu, Samuel; Phair, John P; Mirkin, Chad A; Wolinsky, Steven M

    2008-06-01

    Detection of HIV-1 in patients is limited by the sensitivity and selectivity of available tests. The nanotechnology-based bio-barcode-amplification method offers an innovative approach to detect specific HIV-1 antigens from diverse HIV-1 subtypes. We evaluated the efficacy of this protein-detection method in detecting HIV-1 in men enrolled in the Chicago component of the Multicenter AIDS Cohort Study (MACS). The method relies on magnetic microparticles with antibodies that specifically bind the HIV-1 p24 Gag protein and nanoparticles that are encoded with DNA and antibodies that can sandwich the target protein captured by the microparticle-bound antibodies. The aggregate sandwich structures are magnetically separated from solution, and treated to remove the conjugated barcode DNA. The DNA barcodes (hundreds per target) were identified by a nanoparticle-based detection method that does not rely on PCR. Of 112 plasma samples from HIV-1-infected subjects, 111 were positive for HIV-1 p24 Gag protein (range: 0.11-71.5 ng/ml of plasma) by the bio-barcode-amplification method. HIV-1 p24 Gag protein was detected in only 23 out of 112 men by the conventional ELISA. A total of 34 uninfected subjects were negative by both tests. Thus, the specificity of the bio-barcode-amplification method was 100% and the sensitivity 99%. The bio-barcode-amplification method detected HIV-1 p24 Gag protein in plasma from all study subjects with less than 200 CD4(+) T cells/microl of plasma (100%) and 19 out of 20 (95%) HIV-1-infected men who had less than 50 copies/ml of plasma of HIV-1 RNA. In a separate group of 60 diverse international isolates, representative of clades A, B, C and D and circulating recombinant forms CRF01_AE and CRF02_AG, the bio-barcode-amplification method identified the presence of virus correctly. The bio-barcode-amplification method was superior to the conventional ELISA assay for the detection of HIV-1 p24 Gag protein in plasma with a breadth of coverage for diverse

  2. A Hybrid Wavelet-Based Method for the Peak Detection of Photoplethysmography Signals

    Directory of Open Access Journals (Sweden)

    Suyi Li

    2017-01-01

    Full Text Available The noninvasive peripheral oxygen saturation (SpO2 and the pulse rate can be extracted from photoplethysmography (PPG signals. However, the accuracy of the extraction is directly affected by the quality of the signal obtained and the peak of the signal identified; therefore, a hybrid wavelet-based method is proposed in this study. Firstly, we suppressed the partial motion artifacts and corrected the baseline drift by using a wavelet method based on the principle of wavelet multiresolution. And then, we designed a quadratic spline wavelet modulus maximum algorithm to identify the PPG peaks automatically. To evaluate this hybrid method, a reflective pulse oximeter was used to acquire ten subjects’ PPG signals under sitting, raising hand, and gently walking postures, and the peak recognition results on the raw signal and on the corrected signal were compared, respectively. The results showed that the hybrid method not only corrected the morphologies of the signal well but also optimized the peaks identification quality, subsequently elevating the measurement accuracy of SpO2 and the pulse rate. As a result, our hybrid wavelet-based method profoundly optimized the evaluation of respiratory function and heart rate variability analysis.

  3. A Hybrid Wavelet-Based Method for the Peak Detection of Photoplethysmography Signals.

    Science.gov (United States)

    Li, Suyi; Jiang, Shanqing; Jiang, Shan; Wu, Jiang; Xiong, Wenji; Diao, Shu

    2017-01-01

    The noninvasive peripheral oxygen saturation (SpO 2 ) and the pulse rate can be extracted from photoplethysmography (PPG) signals. However, the accuracy of the extraction is directly affected by the quality of the signal obtained and the peak of the signal identified; therefore, a hybrid wavelet-based method is proposed in this study. Firstly, we suppressed the partial motion artifacts and corrected the baseline drift by using a wavelet method based on the principle of wavelet multiresolution. And then, we designed a quadratic spline wavelet modulus maximum algorithm to identify the PPG peaks automatically. To evaluate this hybrid method, a reflective pulse oximeter was used to acquire ten subjects' PPG signals under sitting, raising hand, and gently walking postures, and the peak recognition results on the raw signal and on the corrected signal were compared, respectively. The results showed that the hybrid method not only corrected the morphologies of the signal well but also optimized the peaks identification quality, subsequently elevating the measurement accuracy of SpO 2 and the pulse rate. As a result, our hybrid wavelet-based method profoundly optimized the evaluation of respiratory function and heart rate variability analysis.

  4. A Hybrid Wavelet-Based Method for the Peak Detection of Photoplethysmography Signals

    Science.gov (United States)

    Jiang, Shanqing; Jiang, Shan; Wu, Jiang; Xiong, Wenji

    2017-01-01

    The noninvasive peripheral oxygen saturation (SpO2) and the pulse rate can be extracted from photoplethysmography (PPG) signals. However, the accuracy of the extraction is directly affected by the quality of the signal obtained and the peak of the signal identified; therefore, a hybrid wavelet-based method is proposed in this study. Firstly, we suppressed the partial motion artifacts and corrected the baseline drift by using a wavelet method based on the principle of wavelet multiresolution. And then, we designed a quadratic spline wavelet modulus maximum algorithm to identify the PPG peaks automatically. To evaluate this hybrid method, a reflective pulse oximeter was used to acquire ten subjects' PPG signals under sitting, raising hand, and gently walking postures, and the peak recognition results on the raw signal and on the corrected signal were compared, respectively. The results showed that the hybrid method not only corrected the morphologies of the signal well but also optimized the peaks identification quality, subsequently elevating the measurement accuracy of SpO2 and the pulse rate. As a result, our hybrid wavelet-based method profoundly optimized the evaluation of respiratory function and heart rate variability analysis. PMID:29250135

  5. A multilevel-ROI-features-based machine learning method for detection of morphometric biomarkers in Parkinson's disease.

    Science.gov (United States)

    Peng, Bo; Wang, Suhong; Zhou, Zhiyong; Liu, Yan; Tong, Baotong; Zhang, Tao; Dai, Yakang

    2017-06-09

    Machine learning methods have been widely used in recent years for detection of neuroimaging biomarkers in regions of interest (ROIs) and assisting diagnosis of neurodegenerative diseases. The innovation of this study is to use multilevel-ROI-features-based machine learning method to detect sensitive morphometric biomarkers in Parkinson's disease (PD). Specifically, the low-level ROI features (gray matter volume, cortical thickness, etc.) and high-level correlative features (connectivity between ROIs) are integrated to construct the multilevel ROI features. Filter- and wrapper- based feature selection method and multi-kernel support vector machine (SVM) are used in the classification algorithm. T1-weighted brain magnetic resonance (MR) images of 69 PD patients and 103 normal controls from the Parkinson's Progression Markers Initiative (PPMI) dataset are included in the study. The machine learning method performs well in classification between PD patients and normal controls with an accuracy of 85.78%, a specificity of 87.79%, and a sensitivity of 87.64%. The most sensitive biomarkers between PD patients and normal controls are mainly distributed in frontal lobe, parental lobe, limbic lobe, temporal lobe, and central region. The classification performance of our method with multilevel ROI features is significantly improved comparing with other classification methods using single-level features. The proposed method shows promising identification ability for detecting morphometric biomarkers in PD, thus confirming the potentiality of our method in assisting diagnosis of the disease. Copyright © 2017 Elsevier B.V. All rights reserved.

  6. Spices, irradiation and detection methods

    International Nuclear Information System (INIS)

    Sjoeberg, A.M.; Manninen, M.

    1991-01-01

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

  7. Validation of a PCR-based method for detection of food-borne thermotolerant Campylobacters in a multicenter collaborative trial

    DEFF Research Database (Denmark)

    Josefsen, Mathilde Hartmann; Cook, N.; D'Agostino, M.

    2004-01-01

    A PCR-based method for rapid detection of food-borne thermotolerant campylobacters was evaluated through a collaborative trial with 12 laboratories testing spiked carcass rinse samples. The method showed an interlaboratory diagnostic sensitivity of 96.7% and a diagnostic specificity of 100% for c......% for chicken samples, while these values were 94.2 and 83.3%, respectively, for pig samples....

  8. Trends in Thyroid Cancer Incidence in Korean Children (1999-2012) Based on Palpation and Nonpalpation Detection Methods

    Science.gov (United States)

    Cho, Yoon Young; Jang, Hye Won; Joung, Ji Young; Park, Sun-Mi; Jeong, Dae Joon; Kim, Sun Wook; Chung, Jae Hoon

    2015-01-01

    Background The incidence of childhood thyroid cancer is increasing in several populations; however, contributing factors have not been adequately discussed. Objectives Our aim was to identify trends of childhood thyroid cancer based on the Korea Central Cancer Registry (KCCR) database and to elucidate changes in detection methods of cancers using a single-center database. Methods Data from the KCCR and Statistics Korea between 1999 and 2012 were used to calculate the crude incidence of thyroid cancer in children. To analyze detection methods for cancers, pediatric patients (aged 0-19 years, n = 126) who underwent thyroid surgery for thyroid cancers at our institution were identified. Subjects were divided into two groups by detection method: (1) palpation group and (2) screening group. Results The crude incidence of childhood thyroid cancer increased from 0.5 per 100,000 in 1999 to 1.7 in 2012. The proportion of thyroid cancer among total cancers also increased from 4.4% in 1999 to 10.6% in 2012. Among 126 children from our institution, 91 cases (72%) were identified as palpable neck masses, and the remainder were discovered during imaging studies. The numbers in both groups gradually increased during the study period. Conclusions The incidence of childhood thyroid cancer has steadily increased in Korea. Regarding the detection methods of cancers, most tumors are detected by palpation rather than screening, although the rate of masses identified during screening has increased. PMID:26835429

  9. Detection methods for irradiated foods

    International Nuclear Information System (INIS)

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

    2005-01-01

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

  10. A method for studies on interactions between a gold-based drug and plasma proteins based on capillary electrophoresis with inductively coupled plasma mass spectrometry detection

    DEFF Research Database (Denmark)

    Nguyen, Tam T T N; Østergaard, Jesper; Gammelgaard, Bente

    2015-01-01

    An analytical method based on capillary electrophoresis (CE) and inductively coupled plasma mass spectrometry (ICP-MS) detection was developed for studies on the interaction of gold-containing drugs and plasma proteins using auranofin as example. A detection limit of 18 ng/mL of auranofin corresp...

  11. European validation of a real-time PCR-based method for detection of Listeria monocytogenes in soft cheese.

    Science.gov (United States)

    Gianfranceschi, Monica Virginia; Rodriguez-Lazaro, David; Hernandez, Marta; González-García, Patricia; Comin, Damiano; Gattuso, Antonietta; Delibato, Elisabetta; Sonnessa, Michele; Pasquali, Frederique; Prencipe, Vincenza; Sreter-Lancz, Zuzsanna; Saiz-Abajo, María-José; Pérez-De-Juan, Javier; Butrón, Javier; Kozačinski, Lidija; Tomic, Danijela Horvatek; Zdolec, Nevijo; Johannessen, Gro S; Jakočiūnė, Džiuginta; Olsen, John Elmerdahl; De Santis, Paola; Lovari, Sarah; Bertasi, Barbara; Pavoni, Enrico; Paiusco, Antonella; De Cesare, Alessandra; Manfreda, Gerardo; De Medici, Dario

    2014-08-01

    The classical microbiological method for detection of Listeria monocytogenes requires around 7 days for final confirmation, and due to perishable nature of RTE food products, there is a clear need for an alternative methodology for detection of this pathogen. This study presents an international (at European level) ISO 16140-based validation trial of a non-proprietary real-time PCR-based methodology that can generate final results in the following day of the analysis. This methodology is based on an ISO compatible enrichment coupled to a bacterial DNA extraction and a consolidated real-time PCR assay. Twelve laboratories from six European countries participated in this trial, and soft cheese was selected as food model since it can represent a difficult matrix for the bacterial DNA extraction and real-time PCR amplification. The limit of detection observed was down to 10 CFU per 25 of sample, showing excellent concordance and accordance values between samples and laboratories (>75%). In addition, excellent values were obtained for relative accuracy, specificity and sensitivity (82.75%, 96.70% and 97.62%, respectively) when the results obtained for the real-time PCR-based methods were compared to those of the ISO 11290-1 standard method. An interesting observation was that the L. monocytogenes detection by the real-time PCR method was less affected in the presence of Listeria innocua in the contaminated samples, proving therefore to be more reliable than the reference method. The results of this international trial demonstrate that the evaluated real-time PCR-based method represents an excellent alterative to the ISO standard since it shows a higher performance as well as reduce the extent of the analytical process, and can be easily implemented routinely by the competent authorities and food industry laboratories. Copyright © 2014 Elsevier B.V. All rights reserved.

  12. Development of an in situ magnetic beads based RT-PCR method for electrochemiluminescent detection of rotavirus

    Science.gov (United States)

    Zhan, Fangfang; Zhou, Xiaoming

    2012-12-01

    Rotaviruses are double-stranded RNA viruses belonging to the family of enteric pathogens. It is a major cause of diarrhoeal disease in infants and young children worldwide. Consequently, rapid and accurate detection of rotaviruses is of great importance in controlling and preventing food- and waterborne diseases and outbreaks. Reverse transcription-polymerase chain reaction (RT-PCR) is a reliable method that possesses high specificity and sensitivity. It has been widely used to detection of viruses. Electrochemiluminescence (ECL) can be considered as an important and powerful tool in analytical and clinical application with high sensitivity, excellent specificity, and low cost. Here we have developed a method for the detection of rotavirus by combining in situ magnetic beads (MBs) based RT-PCR with ECL. RT of rotavirus RNA was carried out in a traditional way and the resulting cDNA was directly amplified on MBs. Forward primers were covalently bounded to MBs and reverse primers were labeled with tris-(2, 2'-bipyridyl) ruthenium (TBR). During the PCR cycling, the TBR labeled products were directly loaded and enriched on the surface of MBs. Then the MBs-TBR complexes could be analyzed by a magnetic ECL platform without any post-modification or post-incubation which avoid some laborious manual operations and achieve rapid yet sensitive detection. In this study, rotavirus from fecal specimens was successfully detected within 2 h, and the limit of detection was estimated to be 104copies/μL. This novel in situ MBs based RT-PCR with ECL detection method can be used for pathogen detection in food safety field and clinical diagnosis.

  13. Seismic detection method for small-scale discontinuities based on dictionary learning and sparse representation

    Science.gov (United States)

    Yu, Caixia; Zhao, Jingtao; Wang, Yanfei

    2017-02-01

    Studying small-scale geologic discontinuities, such as faults, cavities and fractures, plays a vital role in analyzing the inner conditions of reservoirs, as these geologic structures and elements can provide storage spaces and migration pathways for petroleum. However, these geologic discontinuities have weak energy and are easily contaminated with noises, and therefore effectively extracting them from seismic data becomes a challenging problem. In this paper, a method for detecting small-scale discontinuities using dictionary learning and sparse representation is proposed that can dig up high-resolution information by sparse coding. A K-SVD (K-means clustering via Singular Value Decomposition) sparse representation model that contains two stage of iteration procedure: sparse coding and dictionary updating, is suggested for mathematically expressing these seismic small-scale discontinuities. Generally, the orthogonal matching pursuit (OMP) algorithm is employed for sparse coding. However, the method can only update one dictionary atom at one time. In order to improve calculation efficiency, a regularized version of OMP algorithm is presented for simultaneously updating a number of atoms at one time. Two numerical experiments demonstrate the validity of the developed method for clarifying and enhancing small-scale discontinuities. The field example of carbonate reservoirs further demonstrates its effectiveness in revealing masked tiny faults and small-scale cavities.

  14. Comparing a Perceptual and an Automated Vision-Based Method for Lie Detection in Younger Children.

    Science.gov (United States)

    Serras Pereira, Mariana; Cozijn, Reinier; Postma, Eric; Shahid, Suleman; Swerts, Marc

    2016-01-01

    The present study investigates how easily it can be detected whether a child is being truthful or not in a game situation, and it explores the cue validity of bodily movements for such type of classification. To achieve this, we introduce an innovative methodology - the combination of perception studies (in which eye-tracking technology is being used) and automated movement analysis. Film fragments from truthful and deceptive children were shown to human judges who were given the task to decide whether the recorded child was being truthful or not. Results reveal that judges are able to accurately distinguish truthful clips from lying clips in both perception studies. Even though the automated movement analysis for overall and specific body regions did not yield significant results between the experimental conditions, we did find a positive correlation between the amount of movement in a child and the perception of lies, i.e., the more movement the children exhibited during a clip, the higher the chance that the clip was perceived as a lie. The eye-tracking study revealed that, even when there is movement happening in different body regions, judges tend to focus their attention mainly on the face region. This is the first study that compares a perceptual and an automated method for the detection of deceptive behavior in children whose data have been elicited through an ecologically valid paradigm.

  15. Binocular optical axis parallelism detection precision analysis based on Monte Carlo method

    Science.gov (United States)

    Ying, Jiaju; Liu, Bingqi

    2018-02-01

    According to the working principle of the binocular photoelectric instrument optical axis parallelism digital calibration instrument, and in view of all components of the instrument, the various factors affect the system precision is analyzed, and then precision analysis model is established. Based on the error distribution, Monte Carlo method is used to analyze the relationship between the comprehensive error and the change of the center coordinate of the circle target image. The method can further guide the error distribution, optimize control the factors which have greater influence on the comprehensive error, and improve the measurement accuracy of the optical axis parallelism digital calibration instrument.

  16. Research on the algorithm of infrared target detection based on the frame difference and background subtraction method

    Science.gov (United States)

    Liu, Yun; Zhao, Yuejin; Liu, Ming; Dong, Liquan; Hui, Mei; Liu, Xiaohua; Wu, Yijian

    2015-09-01

    As an important branch of infrared imaging technology, infrared target tracking and detection has a very important scientific value and a wide range of applications in both military and civilian areas. For the infrared image which is characterized by low SNR and serious disturbance of background noise, an innovative and effective target detection algorithm is proposed in this paper, according to the correlation of moving target frame-to-frame and the irrelevance of noise in sequential images based on OpenCV. Firstly, since the temporal differencing and background subtraction are very complementary, we use a combined detection method of frame difference and background subtraction which is based on adaptive background updating. Results indicate that it is simple and can extract the foreground moving target from the video sequence stably. For the background updating mechanism continuously updating each pixel, we can detect the infrared moving target more accurately. It paves the way for eventually realizing real-time infrared target detection and tracking, when transplanting the algorithms on OpenCV to the DSP platform. Afterwards, we use the optimal thresholding arithmetic to segment image. It transforms the gray images to black-white images in order to provide a better condition for the image sequences detection. Finally, according to the relevance of moving objects between different frames and mathematical morphology processing, we can eliminate noise, decrease the area, and smooth region boundaries. Experimental results proves that our algorithm precisely achieve the purpose of rapid detection of small infrared target.

  17. Detecting and classifying method based on similarity matching of Android malware behavior with profile.

    Science.gov (United States)

    Jang, Jae-Wook; Yun, Jaesung; Mohaisen, Aziz; Woo, Jiyoung; Kim, Huy Kang

    2016-01-01

    Mass-market mobile security threats have increased recently due to the growth of mobile technologies and the popularity of mobile devices. Accordingly, techniques have been introduced for identifying, classifying, and defending against mobile threats utilizing static, dynamic, on-device, and off-device techniques. Static techniques are easy to evade, while dynamic techniques are expensive. On-device techniques are evasion, while off-device techniques need being always online. To address some of those shortcomings, we introduce Andro-profiler, a hybrid behavior based analysis and classification system for mobile malware. Andro-profiler main goals are efficiency, scalability, and accuracy. For that, Andro-profiler classifies malware by exploiting the behavior profiling extracted from the integrated system logs including system calls. Andro-profiler executes a malicious application on an emulator in order to generate the integrated system logs, and creates human-readable behavior profiles by analyzing the integrated system logs. By comparing the behavior profile of malicious application with representative behavior profile for each malware family using a weighted similarity matching technique, Andro-profiler detects and classifies it into malware families. The experiment results demonstrate that Andro-profiler is scalable, performs well in detecting and classifying malware with accuracy greater than 98 %, outperforms the existing state-of-the-art work, and is capable of identifying 0-day mobile malware samples.

  18. Ultra-sensitive "turn-on" detection method for Hg(2+) based on mispairing biosensor and emulsion PCR.

    Science.gov (United States)

    Zhu, Pengyu; Tian, Wenying; Cheng, Nan; Huang, Kunlun; Luo, Yunbo; Xu, Wentao

    2016-08-01

    Sensor-based detection methods have inspired the idea that chemical or physical signals could be converted to nucleic acid signals to be quantitatively detected using a combination of appropriate detection tools. To achieve ultra-sensitive and absolute quantitative detection of mercury ion (Hg(2+)), we have combined a mispairing biosensor for Hg(2+) and emulsion PCR. The parameters that might influence the biosensor step, such as the duration of isothermal amplification and the concentration of the sensor oligonucleotide, have been firstly optimized in our study to achieve the most efficient biosensor detection. The evaluation results of secondary structures between the biosensors with different number of T-Hg-T structures achieved by Circular Dichroism have indicated that the secondary hairpin structure would be varied according to the change of number of T-Hg-T structures, which could influence the quantitative detection results. Further optimization of number of T-Hg-T within the biosensor sequences showed that 5 T-Hg-T structures could generate the most efficient amplification. After the above optimizations, the emulsion PCR has been employed to achieve the absolute quantitation of nucleic acid signals. The final results have shown that the limit of quantitation (LOQ) in our study was as low as 40fmol, and the limit of detection (LOD) was 10fmol. The practical detection tests showed that the quantitative results were stable and accurate for all substrates. In conclusion, by combining a mispairing biosensor with emulsion PCR, we developed a flexible and stable quantitative "turn-on" detection method with ultra-sensitivity that can detect trace amounts Hg(2+) within different substrates. Copyright © 2016 Elsevier B.V. All rights reserved.

  19. Failed fuel detection method

    International Nuclear Information System (INIS)

    Utamura, Motoaki; Urata, Megumu.

    1976-01-01

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

  20. A simple method for detecting tumor in T2-weighted MRI brain images. An image-based analysis

    International Nuclear Information System (INIS)

    Lau, Phooi-Yee; Ozawa, Shinji

    2006-01-01

    The objective of this paper is to present a decision support system which uses a computer-based procedure to detect tumor blocks or lesions in digitized medical images. The authors developed a simple method with a low computation effort to detect tumors on T2-weighted Magnetic Resonance Imaging (MRI) brain images, focusing on the connection between the spatial pixel value and tumor properties from four different perspectives: cases having minuscule differences between two images using a fixed block-based method, tumor shape and size using the edge and binary images, tumor properties based on texture values using spatial pixel intensity distribution controlled by a global discriminate value, and the occurrence of content-specific tumor pixel for threshold images. Measurements of the following medical datasets were performed: different time interval images, and different brain disease images on single and multiple slice images. Experimental results have revealed that our proposed technique incurred an overall error smaller than those in other proposed methods. In particular, the proposed method allowed decrements of false alarm and missed alarm errors, which demonstrate the effectiveness of our proposed technique. In this paper, we also present a prototype system, known as PCB, to evaluate the performance of the proposed methods by actual experiments, comparing the detection accuracy and system performance. (author)

  1. Detection and Identification of Multiple Stationary Human Targets Via Bio-Radar Based on the Cross-Correlation Method

    Directory of Open Access Journals (Sweden)

    Yang Zhang

    2016-10-01

    Full Text Available Ultra-wideband (UWB radar has been widely used for detecting human physiological signals (respiration, movement, etc. in the fields of rescue, security, and medicine owing to its high penetrability and range resolution. In these applications, especially in rescue after disaster (earthquake, collapse, mine accident, etc., the presence, number, and location of the trapped victims to be detected and rescued are the key issues of concern. Ample research has been done on the first issue, whereas the identification and localization of multi-targets remains a challenge. False positive and negative identification results are two common problems associated with the detection of multiple stationary human targets. This is mainly because the energy of the signal reflected from the target close to the receiving antenna is considerably stronger than those of the targets at further range, often leading to missing or false recognition if the identification method is based on the energy of the respiratory signal. Therefore, a novel method based on cross-correlation is proposed in this paper that is based on the relativity and periodicity of the signals, rather than on the energy. The validity of this method is confirmed through experiments using different scenarios; the results indicate a discernible improvement in the detection precision and identification of the multiple stationary targets.

  2. Detection and Identification of Multiple Stationary Human Targets Via Bio-Radar Based on the Cross-Correlation Method.

    Science.gov (United States)

    Zhang, Yang; Chen, Fuming; Xue, Huijun; Li, Zhao; An, Qiang; Wang, Jianqi; Zhang, Yang

    2016-10-27

    Ultra-wideband (UWB) radar has been widely used for detecting human physiological signals (respiration, movement, etc.) in the fields of rescue, security, and medicine owing to its high penetrability and range resolution. In these applications, especially in rescue after disaster (earthquake, collapse, mine accident, etc.), the presence, number, and location of the trapped victims to be detected and rescued are the key issues of concern. Ample research has been done on the first issue, whereas the identification and localization of multi-targets remains a challenge. False positive and negative identification results are two common problems associated with the detection of multiple stationary human targets. This is mainly because the energy of the signal reflected from the target close to the receiving antenna is considerably stronger than those of the targets at further range, often leading to missing or false recognition if the identification method is based on the energy of the respiratory signal. Therefore, a novel method based on cross-correlation is proposed in this paper that is based on the relativity and periodicity of the signals, rather than on the energy. The validity of this method is confirmed through experiments using different scenarios; the results indicate a discernible improvement in the detection precision and identification of the multiple stationary targets.

  3. Research on detection method of UAV obstruction based on binocular vision

    Science.gov (United States)

    Zhu, Xiongwei; Lei, Xusheng; Sui, Zhehao

    2018-04-01

    For the autonomous obstacle positioning and ranging in the process of UAV (unmanned aerial vehicle) flight, a system based on binocular vision is constructed. A three-stage image preprocessing method is proposed to solve the problem of the noise and brightness difference in the actual captured image. The distance of the nearest obstacle is calculated by using the disparity map that generated by binocular vision. Then the contour of the obstacle is extracted by post-processing of the disparity map, and a color-based adaptive parameter adjustment algorithm is designed to extract contours of obstacle automatically. Finally, the safety distance measurement and obstacle positioning during the UAV flight process are achieved. Based on a series of tests, the error of distance measurement can keep within 2.24% of the measuring range from 5 m to 20 m.

  4. A Pedestrian Detection Scheme Using a Coherent Phase Difference Method Based on 2D Range-Doppler FMCW Radar

    Science.gov (United States)

    Hyun, Eugin; Jin, Young-Seok; Lee, Jong-Hun

    2016-01-01

    For an automotive pedestrian detection radar system, fast-ramp based 2D range-Doppler Frequency Modulated Continuous Wave (FMCW) radar is effective for distinguishing between moving targets and unwanted clutter. However, when a weak moving target such as a pedestrian exists together with strong clutter, the pedestrian may be masked by the side-lobe of the clutter even though they are notably separated in the Doppler dimension. To prevent this problem, one popular solution is the use of a windowing scheme with a weighting function. However, this method leads to a spread spectrum, so the pedestrian with weak signal power and slow Doppler may also be masked by the main-lobe of clutter. With a fast-ramp based FMCW radar, if the target is moving, the complex spectrum of the range- Fast Fourier Transform (FFT) is changed with a constant phase difference over ramps. In contrast, the clutter exhibits constant phase irrespective of the ramps. Based on this fact, in this paper we propose a pedestrian detection for highly cluttered environments using a coherent phase difference method. By detecting the coherent phase difference from the complex spectrum of the range-FFT, we first extract the range profile of the moving pedestrians. Then, through the Doppler FFT, we obtain the 2D range-Doppler map for only the pedestrian. To test the proposed detection scheme, we have developed a real-time data logging system with a 24 GHz FMCW transceiver. In laboratory tests, we verified that the signal processing results from the proposed method were much better than those expected from the conventional 2D FFT-based detection method. PMID:26805835

  5. A Pedestrian Detection Scheme Using a Coherent Phase Difference Method Based on 2D Range-Doppler FMCW Radar

    Directory of Open Access Journals (Sweden)

    Eugin Hyun

    2016-01-01

    Full Text Available For an automotive pedestrian detection radar system, fast-ramp based 2D range-Doppler Frequency Modulated Continuous Wave (FMCW radar is effective for distinguishing between moving targets and unwanted clutter. However, when a weak moving target such as a pedestrian exists together with strong clutter, the pedestrian may be masked by the side-lobe of the clutter even though they are notably separated in the Doppler dimension. To prevent this problem, one popular solution is the use of a windowing scheme with a weighting function. However, this method leads to a spread spectrum, so the pedestrian with weak signal power and slow Doppler may also be masked by the main-lobe of clutter. With a fast-ramp based FMCW radar, if the target is moving, the complex spectrum of the range- Fast Fourier Transform (FFT is changed with a constant phase difference over ramps. In contrast, the clutter exhibits constant phase irrespective of the ramps. Based on this fact, in this paper we propose a pedestrian detection for highly cluttered environments using a coherent phase difference method. By detecting the coherent phase difference from the complex spectrum of the range-FFT, we first extract the range profile of the moving pedestrians. Then, through the Doppler FFT, we obtain the 2D range-Doppler map for only the pedestrian. To test the proposed detection scheme, we have developed a real-time data logging system with a 24 GHz FMCW transceiver. In laboratory tests, we verified that the signal processing results from the proposed method were much better than those expected from the conventional 2D FFT-based detection method.

  6. Application of a robust vibration-based non-destructive method for detection of fatigue cracks in structures

    International Nuclear Information System (INIS)

    Razi, Pejman; Esmaeel, Ramadan A; Taheri, Farid

    2011-01-01

    This paper presents the application of a novel vibration-based technique for detecting fatigue cracks in structures. The method utilizes the empirical mode decomposition method (EMD) to establish an effective energy-based damage index. To investigate the feasibility of the method, fatigue cracks of different sizes were introduced in an aluminum beam subjected to a cyclic load under a three-point bending configuration. The vibration signals corresponding to the healthy and the damaged states of the beam were acquired via piezoceramic sensors. The signals were then processed by the proposed methodology to obtain the damage indices. In addition, for the sake of comparison, the frequency and damping analysis were performed on the test specimen. The results of this study concluded with two major observations. Firstly, the method was highly successful in not only predicting the presence of the fatigue crack, but also in quantifying its progression. Secondly, the proposed energy-based damage index was proved to be superior to the frequency-based methods in terms of sensitivity to the damage detection and quantification. As a result, this technique could be regarded as an efficient non-destructive tool, since it is simple, cost-effective and does not rely on analytical modeling of structures. In addition, the capability of the finite element method (FEM) in mimicking the experiments, and hence for consideration as an effective tool for conducting future parametric studies, was also investigated

  7. Detection of water-quality contamination events based on multi-sensor fusion using an extented Dempster–Shafer method

    International Nuclear Information System (INIS)

    Hou, Dibo; He, Huimei; Huang, Pingjie; Zhang, Guangxin; Loaiciga, Hugo

    2013-01-01

    This study presents a method for detecting contamination events of sources of drinking water based on the Dempster–Shafer (D-S) evidence theory. The detection method has the purpose of protecting water supply systems against accidental and intentional contamination events. This purpose is achieved by first predicting future water-quality parameters using an autoregressive (AR) model. The AR model predicts future water-quality parameters using recent measurements of these parameters made with automated (on-line) water-quality sensors. Next, a probabilistic method assigns probabilities to the time series of residuals formed by comparing predicted water-quality parameters with threshold values. Finally, the D-S fusion method searches for anomalous probabilities of the residuals and uses the result of that search to determine whether the current water quality is normal (that is, free of pollution) or contaminated. The D-S fusion method is extended and improved in this paper by weighted averaging of water-contamination evidence and by the analysis of the persistence of anomalous probabilities of water-quality parameters. The extended D-S fusion method makes determinations that have a high probability of being correct concerning whether or not a source of drinking water has been contaminated. This paper's method for detecting water-contamination events was tested with water-quality time series from automated (on-line) water quality sensors. In addition, a small-scale, experimental, water-pipe network was tested to detect water-contamination events. The two tests demonstrated that the extended D-S fusion method achieves a low false alarm rate and high probabilities of detecting water contamination events. (paper)

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

    Science.gov (United States)

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

    2018-03-01

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

  9. Method for Car in Dangerous Action Detection by Means of Wavelet Multi Resolution Analysis Based on Appropriate Support Length of Base Function

    OpenAIRE

    Kohei Arai; Tomoko Nishikawa

    2013-01-01

    Multi-Resolution Analysis: MRA based on the mother wavelet function with which support length differs from the image of the automobile rear under run is performed, and the run characteristic of a car is searched for. Speed, deflection, etc. are analyzed and the method of detecting vehicles with high accident danger is proposed. The experimental results show that vehicles in a dangerous action can be detected by the proposed method.

  10. PCR-free quantitative detection of genetically modified organism from raw materials. An electrochemiluminescence-based bio bar code method.

    Science.gov (United States)

    Zhu, Debin; Tang, Yabing; Xing, Da; Chen, Wei R

    2008-05-15

    A bio bar code assay based on oligonucleotide-modified gold nanoparticles (Au-NPs) provides a PCR-free method for quantitative detection of nucleic acid targets. However, the current bio bar code assay requires lengthy experimental procedures including the preparation and release of bar code DNA probes from the target-nanoparticle complex and immobilization and hybridization of the probes for quantification. Herein, we report a novel PCR-free electrochemiluminescence (ECL)-based bio bar code assay for the quantitative detection of genetically modified organism (GMO) from raw materials. It consists of tris-(2,2'-bipyridyl) ruthenium (TBR)-labeled bar code DNA, nucleic acid hybridization using Au-NPs and biotin-labeled probes, and selective capture of the hybridization complex by streptavidin-coated paramagnetic beads. The detection of target DNA is realized by direct measurement of ECL emission of TBR. It can quantitatively detect target nucleic acids with high speed and sensitivity. This method can be used to quantitatively detect GMO fragments from real GMO products.

  11. Computerized detection of multiple sclerosis candidate regions based on a level set method using an artificial neural network

    International Nuclear Information System (INIS)

    Kuwazuru, Junpei; Magome, Taiki; Arimura, Hidetaka; Yamashita, Yasuo; Oki, Masafumi; Toyofuku, Fukai; Kakeda, Shingo; Yamamoto, Daisuke

    2010-01-01

    Yamamoto et al. developed the system for computer-aided detection of multiple sclerosis (MS) candidate regions. In a level set method in their proposed method, they employed the constant threshold value for the edge indicator function related to a speed function of the level set method. However, it would be appropriate to adjust the threshold value to each MS candidate region, because the edge magnitudes in MS candidates differ from each other. Our purpose of this study was to develop a computerized detection of MS candidate regions in MR images based on a level set method using an artificial neural network (ANN). To adjust the threshold value for the edge indicator function in the level set method to each true positive (TP) and false positive (FP) region, we constructed the ANN. The ANN could provide the suitable threshold value for each candidate region in the proposed level set method so that TP regions can be segmented and FP regions can be removed. Our proposed method detected MS regions at a sensitivity of 82.1% with 0.204 FPs per slice and similarity index of MS candidate regions was 0.717 on average. (author)

  12. A new physics-based method for detecting weak nuclear signals via spectral decomposition

    International Nuclear Information System (INIS)

    Chan, Kung-Sik; Li, Jinzheng; Eichinger, William; Bai, Erwei

    2012-01-01

    We propose a new physics-based method to determine the presence of the spectral signature of one or more nuclides from a poorly resolved spectra with weak signatures. The method is different from traditional methods that rely primarily on peak finding algorithms. The new approach considers each of the signatures in the library to be a linear combination of subspectra. These subspectra are obtained by assuming a signature consisting of just one of the unique gamma rays emitted by the nuclei. We propose a Poisson regression model for deducing which nuclei are present in the observed spectrum. In recognition that a radiation source generally comprises few nuclear materials, the underlying Poisson model is sparse, i.e. most of the regression coefficients are zero (positive coefficients correspond to the presence of nuclear materials). We develop an iterative algorithm for a penalized likelihood estimation that prompts sparsity. We illustrate the efficacy of the proposed method by simulations using a variety of poorly resolved, low signal-to-noise ratio (SNR) situations, which show that the proposed approach enjoys excellent empirical performance even with SNR as low as to -15 db.

  13. A new method of explosive detection based on dual-energy X-ray technology and forward-scattering

    International Nuclear Information System (INIS)

    Zhao Kun; Li Jianmin

    2004-01-01

    Based on dual-energy X-ray technology combined with forward-scattering, a brand new explosive detection method is presented. Dual-energy technology can give the information on the effective atomic number (Z eff ) of an irradiated component, while the intensity of the forward scattered photons can reveal the density information according to our research. Therefore, the existence of the explosive can be effectively identified by combining these two characteristic quantities. Compared with the earlier inspection approaches, the new one has a series of particular advantages, such as high detection rate, low false alarm rate, automatic alarm and so forth. The project is ongoing. (authors)

  14. A Kriging Model Based Finite Element Model Updating Method for Damage Detection

    Directory of Open Access Journals (Sweden)

    Xiuming Yang

    2017-10-01

    Full Text Available Model updating is an effective means of damage identification and surrogate modeling has attracted considerable attention for saving computational cost in finite element (FE model updating, especially for large-scale structures. In this context, a surrogate model of frequency is normally constructed for damage identification, while the frequency response function (FRF is rarely used as it usually changes dramatically with updating parameters. This paper presents a new surrogate model based model updating method taking advantage of the measured FRFs. The Frequency Domain Assurance Criterion (FDAC is used to build the objective function, whose nonlinear response surface is constructed by the Kriging model. Then, the efficient global optimization (EGO algorithm is introduced to get the model updating results. The proposed method has good accuracy and robustness, which have been verified by a numerical simulation of a cantilever and experimental test data of a laboratory three-story structure.

  15. Wave propagation numerical models in damage detection based on the time domain spectral element method

    International Nuclear Information System (INIS)

    Ostachowicz, W; Kudela, P

    2010-01-01

    A Spectral Element Method is used for wave propagation modelling. A 3D solid spectral element is derived with shape functions based on Lagrange interpolation and Gauss-Lobatto-Legendre points. This approach is applied for displacement approximation suited for fundamental modes of Lamb waves as well as potential distribution in piezoelectric transducers. The novelty is the model geometry extension from flat to curved elements for application in shell-like structures. Exemplary visualisations of waves excited by the piezoelectric transducers in curved shell structure made of aluminium alloy are presented. Simple signal analysis of wave interaction with crack is performed. The crack is modelled by separation of appropriate nodes between elements. An investigation of influence of the crack length on wave propagation signals is performed. Additionally, some aspects of the spectral element method implementation are discussed.

  16. Detection method based on Kalman filter for high speed rail defect AE signal on wheel-rail rolling rig

    Science.gov (United States)

    Hao, Qiushi; Shen, Yi; Wang, Yan; Zhang, Xin

    2018-01-01

    Nondestructive test (NDT) of rails has been carried out intermittently in traditional approaches, which highly restricts the detection efficiency under rapid development of high speed railway nowadays. It is necessary to put forward a dynamic rail defect detection method for rail health monitoring. Acoustic emission (AE) as a practical real-time detection technology takes advantage of dynamic AE signal emitted from plastic deformation of material. Detection capacities of AE on rail defects have been verified due to its sensitivity and dynamic merits. Whereas the application under normal train service circumstance has been impeded by synchronous background noises, which are directly linked to the wheel speed. In this paper, surveys on a wheel-rail rolling rig are performed to investigate defect AE signals with varying speed. A dynamic denoising method based on Kalman filter is proposed and its detection effectiveness and flexibility are demonstrated by theory and computational results. Moreover, after comparative analysis of modelling precision at different speeds, it is predicted that the method is also applicable for high speed condition beyond experiments.

  17. Development of melting temperature-based SYBR Green I polymerase chain reaction methods for multiplex genetically modified organism detection.

    Science.gov (United States)

    Hernández, Marta; Rodríguez-Lázaro, David; Esteve, Teresa; Prat, Salomé; Pla, Maria

    2003-12-15

    Commercialization of several genetically modified crops has been approved worldwide to date. Uniplex polymerase chain reaction (PCR)-based methods to identify these different insertion events have been developed, but their use in the analysis of all commercially available genetically modified organisms (GMOs) is becoming progressively insufficient. These methods require a large number of assays to detect all possible GMOs present in the sample and thereby the development of multiplex PCR systems using combined probes and primers targeted to sequences specific to various GMOs is needed for detection of this increasing number of GMOs. Here we report on the development of a multiplex real-time PCR suitable for multiple GMO identification, based on the intercalating dye SYBR Green I and the analysis of the melting curves of the amplified products. Using this method, different amplification products specific for Maximizer 176, Bt11, MON810, and GA21 maize and for GTS 40-3-2 soybean were obtained and identified by their specific Tm. We have combined amplification of these products in a number of multiplex reactions and show the suitability of the methods for identification of GMOs with a sensitivity of 0.1% in duplex reactions. The described methods offer an economic and simple alternative to real-time PCR systems based on sequence-specific probes (i.e., TaqMan chemistry). These methods can be used as selection tests and further optimized for uniplex GMO quantification.

  18. Laser Raman detection for oral cancer based on a Gaussian process classification method

    International Nuclear Information System (INIS)

    Du, Zhanwei; Yang, Yongjian; Bai, Yuan; Wang, Lijun; Zhang, Chijun; Chen, He; Luo, Yusheng; Su, Le; Chen, Yong; Li, Xianchang; Zhou, Xiaodong; Shen, Aiguo; Hu, Jiming; Jia, Jun

    2013-01-01

    Oral squamous cell carcinoma is the most common neoplasm of the oral cavity. The incidence rate accounts for 80% of total oral cancer and shows an upward trend in recent years. It has a high degree of malignancy and is difficult to detect in terms of differential diagnosis, as a consequence of which the timing of treatment is always delayed. In this work, Raman spectroscopy was adopted to differentially diagnose oral squamous cell carcinoma and oral gland carcinoma. In total, 852 entries of raw spectral data which consisted of 631 items from 36 oral squamous cell carcinoma patients, 87 items from four oral gland carcinoma patients and 134 items from five normal people were collected by utilizing an optical method on oral tissues. The probability distribution of the datasets corresponding to the spectral peaks of the oral squamous cell carcinoma tissue was analyzed and the experimental result showed that the data obeyed a normal distribution. Moreover, the distribution characteristic of the noise was also in compliance with a Gaussian distribution. A Gaussian process (GP) classification method was utilized to distinguish the normal people and the oral gland carcinoma patients from the oral squamous cell carcinoma patients. The experimental results showed that all the normal people could be recognized. 83.33% of the oral squamous cell carcinoma patients could be correctly diagnosed and the remaining ones would be diagnosed as having oral gland carcinoma. For the classification process of oral gland carcinoma and oral squamous cell carcinoma, the correct ratio was 66.67% and the erroneously diagnosed percentage was 33.33%. The total sensitivity was 80% and the specificity was 100% with the Matthews correlation coefficient (MCC) set to 0.447 213 595. Considering the numerical results above, the application prospects and clinical value of this technique are significantly impressive. (letter)

  19. Laser Raman detection for oral cancer based on a Gaussian process classification method

    Science.gov (United States)

    Du, Zhanwei; Yang, Yongjian; Bai, Yuan; Wang, Lijun; Zhang, Chijun; Chen, He; Luo, Yusheng; Su, Le; Chen, Yong; Li, Xianchang; Zhou, Xiaodong; Jia, Jun; Shen, Aiguo; Hu, Jiming

    2013-06-01

    Oral squamous cell carcinoma is the most common neoplasm of the oral cavity. The incidence rate accounts for 80% of total oral cancer and shows an upward trend in recent years. It has a high degree of malignancy and is difficult to detect in terms of differential diagnosis, as a consequence of which the timing of treatment is always delayed. In this work, Raman spectroscopy was adopted to differentially diagnose oral squamous cell carcinoma and oral gland carcinoma. In total, 852 entries of raw spectral data which consisted of 631 items from 36 oral squamous cell carcinoma patients, 87 items from four oral gland carcinoma patients and 134 items from five normal people were collected by utilizing an optical method on oral tissues. The probability distribution of the datasets corresponding to the spectral peaks of the oral squamous cell carcinoma tissue was analyzed and the experimental result showed that the data obeyed a normal distribution. Moreover, the distribution characteristic of the noise was also in compliance with a Gaussian distribution. A Gaussian process (GP) classification method was utilized to distinguish the normal people and the oral gland carcinoma patients from the oral squamous cell carcinoma patients. The experimental results showed that all the normal people could be recognized. 83.33% of the oral squamous cell carcinoma patients could be correctly diagnosed and the remaining ones would be diagnosed as having oral gland carcinoma. For the classification process of oral gland carcinoma and oral squamous cell carcinoma, the correct ratio was 66.67% and the erroneously diagnosed percentage was 33.33%. The total sensitivity was 80% and the specificity was 100% with the Matthews correlation coefficient (MCC) set to 0.447 213 595. Considering the numerical results above, the application prospects and clinical value of this technique are significantly impressive.

  20. Molecular beacon-based real-time PCR method for detection of porcine DNA in gelatin and gelatin capsules.

    Science.gov (United States)

    Mohamad, Nurhidayatul Asma; Mustafa, Shuhaimi; Khairil Mokhtar, Nur Fadhilah; El Sheikha, Aly Farag

    2018-03-05

    The pharmaceutical industry has boosted gelatin consumption worldwide. This is supported by the availability of cost-effective gelatin production from porcine by-products. However, cross-contamination of gelatin materials, where porcine gelatin was unintentionally included in the other animal sources of gelatin, has caused significant concerns about halal authenticity. The real-time polymerase chain reaction (PCR) has enabled a highly specific and sensitive animal species detection method in various food products. Hence, such a technique was employed in the present study to detect and quantify porcine DNA in gelatin using a molecular beacon probe, with differences in performance between mitochondrial (cytochrome b gene) and chromosomal DNA-(MPRE42 repetitive element) based porcine-specific PCR assays being compared. A higher sensitivity was observed in chromosomal DNA (MPRE-PCR assay), where this assay allows the detection of gelatin DNA at amounts as as low as 1 pg, whereas mitochondrial DNA (CBH-PCR assay) can only detect at levels down to 10 pg of gelatin DNA. When an analysis with commercial gelatin and gelatin capsule samples was conducted, the same result was observed, with a significantly more sensitive detection being provided by the repetitive element of chromosomal DNA. The present study has established highly sensitive DNA-based porcine detection systems derived from chromosomal DNA that are feasible for highly processed products such as gelatin and gelatin capsules containing a minute amount of DNA. This sensitive detection method can also be implemented to assist the halal authentication process of various food products available on the market. © 2018 Society of Chemical Industry. © 2018 Society of Chemical Industry.

  1. Study of material properties important for an optical property modulation-based radiation detection method for positron emission tomography

    OpenAIRE

    Tao, Li; Daghighian, Henry M.; Levin, Craig S.

    2017-01-01

    We compare the performance of two detector materials, cadmium telluride (CdTe) and bismuth silicon oxide (BSO), for optical property modulation-based radiation detection method for positron emission tomography (PET), which is a potential new direction to dramatically improve the annihilation photon pair coincidence time resolution. We have shown that the induced current flow in the detector crystal resulting from ionizing radiation determines the strength of optical modulation signal. A large...

  2. A Decision Mixture Model-Based Method for Inshore Ship Detection Using High-Resolution Remote Sensing Images.

    Science.gov (United States)

    Bi, Fukun; Chen, Jing; Zhuang, Yin; Bian, Mingming; Zhang, Qingjun

    2017-06-22

    With the rapid development of optical remote sensing satellites, ship detection and identification based on large-scale remote sensing images has become a significant maritime research topic. Compared with traditional ocean-going vessel detection, inshore ship detection has received increasing attention in harbor dynamic surveillance and maritime management. However, because the harbor environment is complex, gray information and texture features between docked ships and their connected dock regions are indistinguishable, most of the popular detection methods are limited by their calculation efficiency and detection accuracy. In this paper, a novel hierarchical method that combines an efficient candidate scanning strategy and an accurate candidate identification mixture model is presented for inshore ship detection in complex harbor areas. First, in the candidate region extraction phase, an omnidirectional intersected two-dimension scanning (OITDS) strategy is designed to rapidly extract candidate regions from the land-water segmented images. In the candidate region identification phase, a decision mixture model (DMM) is proposed to identify real ships from candidate objects. Specifically, to improve the robustness regarding the diversity of ships, a deformable part model (DPM) was employed to train a key part sub-model and a whole ship sub-model. Furthermore, to improve the identification accuracy, a surrounding correlation context sub-model is built. Finally, to increase the accuracy of candidate region identification, these three sub-models are integrated into the proposed DMM. Experiments were performed on numerous large-scale harbor remote sensing images, and the results showed that the proposed method has high detection accuracy and rapid computational efficiency.

  3. CNV-RF Is a Random Forest-Based Copy Number Variation Detection Method Using Next-Generation Sequencing.

    Science.gov (United States)

    Onsongo, Getiria; Baughn, Linda B; Bower, Matthew; Henzler, Christine; Schomaker, Matthew; Silverstein, Kevin A T; Thyagarajan, Bharat

    2016-11-01

    Simultaneous detection of small copy number variations (CNVs) (<0.5 kb) and single-nucleotide variants in clinically significant genes is of great interest for clinical laboratories. The analytical variability in next-generation sequencing (NGS) and artifacts in coverage data because of issues with mappability along with lack of robust bioinformatics tools for CNV detection have limited the utility of targeted NGS data to identify CNVs. We describe the development and implementation of a bioinformatics algorithm, copy number variation-random forest (CNV-RF), that incorporates a machine learning component to identify CNVs from targeted NGS data. Using CNV-RF, we identified 12 of 13 deletions in samples with known CNVs, two cases with duplications, and identified novel deletions in 22 additional cases. Furthermore, no CNVs were identified among 60 genes in 14 cases with normal copy number and no CNVs were identified in another 104 patients with clinical suspicion of CNVs. All positive deletions and duplications were confirmed using a quantitative PCR method. CNV-RF also detected heterozygous deletions and duplications with a specificity of 50% across 4813 genes. The ability of CNV-RF to detect clinically relevant CNVs with a high degree of sensitivity along with confirmation using a low-cost quantitative PCR method provides a framework for providing comprehensive NGS-based CNV/single-nucleotide variant detection in a clinical molecular diagnostics laboratory. Copyright © 2016 American Society for Investigative Pathology and the Association for Molecular Pathology. Published by Elsevier Inc. All rights reserved.

  4. Development of electrochemical immunosensors based on different serum antibody immobilization methods for detection of Japanese encephalitis virus

    International Nuclear Information System (INIS)

    Tran, Quang Huy; Hanh Nguyen, Thi Hong; Phan, Thi Nga; Mai, Anh Tuan; Nguyen, Thi Thuy; Vu, Quang Khue

    2012-01-01

    This paper describes the development of electrochemical immunosensors based on human serum antibodies with different immobilization methods for detection of Japanese encephalitis virus (JEV). Human serum containing anti-JEV antibodies was used to immobilize onto the surface of silanized interdigitated electrodes by four methods: direct adsorption (APTES-serum), covalent binding with a cross linker of glutaraldehyde (APTES-GA-serum), covalent binding with a cross linker of glutaraldehyde combined with anti-human IgG (APTES-GA-anti-HIgG-serum) and covalent binding with a cross linker of glutaraldehyde combined with a bioaffinity of protein A (APTES-GA-PrA-serum). Atomic force microscopy was used to verify surface characteristics of the interdigitated electrodes before and after treatment with serum antibodies. The output signal of the immunosensors was measured by the change of conductivity resulting from the specific binding of JEV antigens and serum antibodies immobilized on the electrodes, with the help of horseradish peroxidase (HRP)-labeled secondary antibody against JEV. The results showed that the APTES-GA-PrA-serum method provided the highest signal of the electrochemical immunosensor for detection of JEV antigens, with the linear range from 25 ng ml −1 to 1 μg ml −1 , and the limit of detection was about 10 ng ml −1 . This study shows a potential development of novel electrochemical immunosensors applied for virus detection in clinical samples in case of possible outbreaks

  5. Detection of palytoxin-like compounds by a flow cytometry-based immunoassay supported by functional and analytical methods.

    Science.gov (United States)

    Fraga, María; Vilariño, Natalia; Louzao, M Carmen; Fernández, Diego A; Poli, Mark; Botana, Luis M

    2016-01-15

    Palytoxin (PLTX) is a complex marine toxin produced by zoanthids (i.e. Palythoa), dinoflagellates (Ostreopsis) and cyanobacteria (Trichodesmium). PLTX outbreaks are usually associated with Indo-Pacific waters, however their recent repeated occurrence in Mediterranean-European Atlantic coasts demonstrate their current worldwide distribution. Human sickness and fatalities have been associated with toxic algal blooms and ingestion of seafood contaminated with PLTX-like molecules. These toxins represent a serious threat to human health. There is an immediate need to develop easy-to-use, rapid detection methods due to the lack of validated protocols for their detection and quantification. We have developed an immuno-detection method for PLTX-like molecules based on the use of microspheres coupled to flow-cytometry detection (Luminex 200™). The assay consisted of the competition between free PLTX-like compounds in solution and PLTX immobilized on the surface of microspheres for binding to a specific monoclonal anti-PLTX antibody. This method displays an IC50 of 1.83 ± 0.21 nM and a dynamic range of 0.47-6.54 nM for PLTX. An easy-to-perform extraction protocol, based on a mixture of methanol and acetate buffer, was applied to spiked mussel samples providing a recovery rate of 104 ± 8% and a range of detection from 374 ± 81 to 4430 ± 150 μg kg(-1) when assayed with this method. Extracts of Ostreopsis cf. siamensis and Palythoa tuberculosa were tested and yielded positive results for PLTX-like molecules. However, the data obtained for the coral sample suggested that this antibody did not detect 42-OH-PLTX efficiently. The same samples were further analyzed using a neuroblastoma cytotoxicity assay and UPLC-IT-TOF spectrometry, which also pointed to the presence of PLTX-like compounds. Therefore, this single detection method for PLTX provides a semi-quantitative tool useful for the screening of PLTX-like molecules in different matrixes. Copyright © 2015

  6. Antibody-nanoparticle conjugates to enhance the sensitivity of ELISA-based detection methods.

    Directory of Open Access Journals (Sweden)

    Margaret M Billingsley

    Full Text Available Accurate antigen detection is imperative for clinicians to diagnose disease, assess treatment success, and predict patient prognosis. The most common technique used for the detection of disease-associated biomarkers is the enzyme linked immunosorbent assay (ELISA. In an ELISA, primary antibodies are incubated with biological samples containing the biomarker of interest. Then, detectible secondary antibodies conjugated with horseradish peroxidase (HRP bind the primary antibodies. Upon addition of a color-changing substrate, the samples provide a colorimetric signal that directly correlates to the targeted biomarker concentration. While ELISAs are effective for analyzing samples with high biomarker content, they lack the sensitivity required to analyze samples with low antigen levels. We hypothesized that the sensitivity of ELISAs could be enhanced by replacing freely delivered primary antibodies with antibody-nanoparticle conjugates that provide excess binding sites for detectible secondary antibodies, ultimately leading to increased signal. Here, we investigated the use of nanoshells (NS decorated with antibodies specific to epidermal growth factor receptor (EGFR as a model system (EGFR-NS. We incubated one healthy and two breast cancer cell lines, each expressing different levels of EGFR, with EGFR-NS, untargeted NS, or unconjugated EGFR antibodies, as well as detectable secondary antibodies. We found that EGFR-NS consistently increased signal intensity relative to unconjugated EGFR antibodies, with a substantial 13-fold enhancement from cells expressing high levels of EGFR. Additionally, 40x more unconjugated antibodies were required to detect EGFR compared to those conjugated to NS. Our results demonstrate that antibody-nanoparticle conjugates lower the detection limit of traditional ELISAs and support further investigation of this strategy with other antibodies and nanoparticles. Owing to their enhanced sensitivity, we anticipate that

  7. A new 2D segmentation method based on dynamic programming applied to computer aided detection in mammography

    International Nuclear Information System (INIS)

    Timp, Sheila; Karssemeijer, Nico

    2004-01-01

    Mass segmentation plays a crucial role in computer-aided diagnosis (CAD) systems for classification of suspicious regions as normal, benign, or malignant. In this article we present a robust and automated segmentation technique--based on dynamic programming--to segment mass lesions from surrounding tissue. In addition, we propose an efficient algorithm to guarantee resulting contours to be closed. The segmentation method based on dynamic programming was quantitatively compared with two other automated segmentation methods (region growing and the discrete contour model) on a dataset of 1210 masses. For each mass an overlap criterion was calculated to determine the similarity with manual segmentation. The mean overlap percentage for dynamic programming was 0.69, for the other two methods 0.60 and 0.59, respectively. The difference in overlap percentage was statistically significant. To study the influence of the segmentation method on the performance of a CAD system two additional experiments were carried out. The first experiment studied the detection performance of the CAD system for the different segmentation methods. Free-response receiver operating characteristics analysis showed that the detection performance was nearly identical for the three segmentation methods. In the second experiment the ability of the classifier to discriminate between malignant and benign lesions was studied. For region based evaluation the area A z under the receiver operating characteristics curve was 0.74 for dynamic programming, 0.72 for the discrete contour model, and 0.67 for region growing. The difference in A z values obtained by the dynamic programming method and region growing was statistically significant. The differences between other methods were not significant

  8. Self-Tuning Method for Increased Obstacle Detection Reliability Based on Internet of Things LiDAR Sensor Models.

    Science.gov (United States)

    Castaño, Fernando; Beruvides, Gerardo; Villalonga, Alberto; Haber, Rodolfo E

    2018-05-10

    On-chip LiDAR sensors for vehicle collision avoidance are a rapidly expanding area of research and development. The assessment of reliable obstacle detection using data collected by LiDAR sensors has become a key issue that the scientific community is actively exploring. The design of a self-tuning methodology and its implementation are presented in this paper, to maximize the reliability of LiDAR sensors network for obstacle detection in the 'Internet of Things' (IoT) mobility scenarios. The Webots Automobile 3D simulation tool for emulating sensor interaction in complex driving environments is selected in order to achieve that objective. Furthermore, a model-based framework is defined that employs a point-cloud clustering technique, and an error-based prediction model library that is composed of a multilayer perceptron neural network, and k-nearest neighbors and linear regression models. Finally, a reinforcement learning technique, specifically a Q-learning method, is implemented to determine the number of LiDAR sensors that are required to increase sensor reliability for obstacle localization tasks. In addition, a IoT driving assistance user scenario, connecting a five LiDAR sensor network is designed and implemented to validate the accuracy of the computational intelligence-based framework. The results demonstrated that the self-tuning method is an appropriate strategy to increase the reliability of the sensor network while minimizing detection thresholds.

  9. Detection of ligand binding hot spots on protein surfaces via fragment-based methods: application to DJ-1 and glucocerebrosidase

    Energy Technology Data Exchange (ETDEWEB)

    Landon, Melissa R.; Lieberman, Raquel L.; Hoang, Quyen Q.; Ju, Shulin; Caaveiro, Jose M.M.; Orwig, Susan D.; Kozakov, Dima; Brenke, Ryan; Chuang, Gwo-Yu; Beglov, Dmitry; Vajda, Sandor; Petsko, Gregory A.; Ringe, Dagmar; (BU-M); (Brandeis); (GIT)

    2010-08-04

    The identification of hot spots, i.e., binding regions that contribute substantially to the free energy of ligand binding, is a critical step for structure-based drug design. Here we present the application of two fragment-based methods to the detection of hot spots for DJ-1 and glucocerebrosidase (GCase), targets for the development of therapeutics for Parkinson's and Gaucher's diseases, respectively. While the structures of these two proteins are known, binding information is lacking. In this study we employ the experimental multiple solvent crystal structures (MSCS) method and computational fragment mapping (FTMap) to identify regions suitable for the development of pharmacological chaperones for DJ-1 and GCase. Comparison of data derived via MSCS and FTMap also shows that FTMap, a computational method for the identification of fragment binding hot spots, is an accurate and robust alternative to the performance of expensive and difficult crystallographic experiments.

  10. Experimental validation of a structural damage detection method based on marginal Hilbert spectrum

    Science.gov (United States)

    Banerji, Srishti; Roy, Timir B.; Sabamehr, Ardalan; Bagchi, Ashutosh

    2017-04-01

    Structural Health Monitoring (SHM) using dynamic characteristics of structures is crucial for early damage detection. Damage detection can be performed by capturing and assessing structural responses. Instrumented structures are monitored by analyzing the responses recorded by deployed sensors in the form of signals. Signal processing is an important tool for the processing of the collected data to diagnose anomalies in structural behavior. The vibration signature of the structure varies with damage. In order to attain effective damage detection, preservation of non-linear and non-stationary features of real structural responses is important. Decomposition of the signals into Intrinsic Mode Functions (IMF) by Empirical Mode Decomposition (EMD) and application of Hilbert-Huang Transform (HHT) addresses the time-varying instantaneous properties of the structural response. The energy distribution among different vibration modes of the intact and damaged structure depicted by Marginal Hilbert Spectrum (MHS) detects location and severity of the damage. The present work investigates damage detection analytically and experimentally by employing MHS. The testing of this methodology for different damage scenarios of a frame structure resulted in its accurate damage identification. The sensitivity of Hilbert Spectral Analysis (HSA) is assessed with varying frequencies and damage locations by means of calculating Damage Indices (DI) from the Hilbert spectrum curves of the undamaged and damaged structures.

  11. A Novel Diagnostic Method to Detect Duck Tembusu Virus: A Colloidal Gold-Based Immunochromatographic Assay

    Directory of Open Access Journals (Sweden)

    Guanliu Yu

    2018-05-01

    Full Text Available Duck Tembusu virus (DTMUV is an emerging pathogenic flavivirus that has resulted in large economic losses to the duck-rearing industry in China since 2010. Therefore, an effective diagnostic approach to monitor the spread of DTMUV is necessary. Here, a novel diagnostic immunochromatographic strip (ICS assay was developed to detect DTMUV. The assay was carried out using colloidal gold coated with purified monoclonal antibody A12D3 against envelope E protein. Purified polyclonal C12D1 antibodies from BALB/c mice against the envelope E protein were used as the capture antibody. Goat anti-mouse IgG was used to detect DTMUV, which was also assembled on the ICS. Results showed that the ICS could specifically detect DTMUV within 10 min. It also could be stored 25 and 4°C for 4 and 6 months, respectively. The sensitivity of the ICS indicated that the dilution multiples of positive allantoic fluid of DTMUV (LD50: 104.33/0.2 ml was up to 200. Its specificity and sensibility showed no significant change under the above storage situations. Fifty clinical samples were simultaneously detected by ICS and reverse-transcription polymerase chain reaction with a 93.9% coincidence rate between them. It proved that the ICS in the present study was highly specific, sensitive, repeatable, and more convenient to rapidly detect DTMUV in clinical samples.

  12. Data-driven drug safety signal detection methods in pharmacovigilance using electronic primary care records: A population based study

    Directory of Open Access Journals (Sweden)

    Shang-Ming Zhou

    2017-04-01

    Data-driven analytic methods are a valuable aid to signal detection of ADEs from large electronic health records for drug safety monitoring. This study finds the methods can detect known ADE and so could potentially be used to detect unknown ADE.

  13. [Research on the temperature field detection method of hot forging based on long-wavelength infrared spectrum].

    Science.gov (United States)

    Zhang, Yu-Cun; Wei, Bin; Fu, Xian-Bin

    2014-02-01

    A temperature field detection method based on long-wavelength infrared spectrum for hot forging is proposed in the present paper. This method combines primary spectrum pyrometry and three-stage FP-cavity LCTF. By optimizing the solutions of three group nonlinear equations in the mathematical model of temperature detection, the errors are reduced, thus measuring results will be more objective and accurate. Then the system of three-stage FP-cavity LCTF was designed on the principle of crystal birefringence. The system realized rapid selection of any wavelength in a certain wavelength range. It makes the response of the temperature measuring system rapid and accurate. As a result, without the emissivity of hot forging, the method can acquire exact information of temperature field and effectively suppress the background light radiation around the hot forging and ambient light that impact the temperature detection accuracy. Finally, the results of MATLAB showed that the infrared spectroscopy through the three-stage FP-cavity LCTF could meet the requirements of design. And experiments verified the feasibility of temperature measuring method. Compared with traditional single-band thermal infrared imager, the accuracy of measuring result was improved.

  14. Tooth Fracture Detection in Spiral Bevel Gears System by Harmonic Response Based on Finite Element Method

    Directory of Open Access Journals (Sweden)

    Yuan Chen

    2017-01-01

    Full Text Available Spiral bevel gears occupy several advantages such as high contact ratio, strong carrying capacity, and smooth operation, which become one of the most widely used components in high-speed stage of the aeronautical transmission system. Its dynamic characteristics are addressed by many scholars. However, spiral bevel gears, especially tooth fracture occurrence and monitoring, are not to be investigated, according to the limited published issues. Therefore, this paper establishes a three-dimensional model and finite element model of the Gleason spiral bevel gear pair. The model considers the effect of tooth root fracture on the system due to fatigue. Finite element method is used to compute the mesh generation, set the boundary condition, and carry out the dynamic load. The harmonic response spectra of the base under tooth fracture are calculated and the influence of main parameters on monitoring failure is investigated as well. The results show that the change of torque affects insignificantly the determination of whether or not the system has tooth fracture. The intermediate frequency interval (200 Hz–1000 Hz is the best interval to judge tooth fracture occurrence. The best fault test region is located in the working area where the system is going through meshing. The simulation calculation provides a theoretical reference for spiral bevel gear system test and fault diagnosis.

  15. PZT-Based Detection of Compactness of Concrete in Concrete Filled Steel Tube Using Time Reversal Method

    Directory of Open Access Journals (Sweden)

    Shi Yan

    2014-01-01

    Full Text Available A smart aggregate-based approach is proposed for the concrete compactness detection of concrete filled steel tube (CFST columns. The piezoceramic-based smart aggregates (SAs were embedded in the predetermined locations prior to the casting of concrete columns to establish a wave-based smart sensing system for the concrete compactness detection purpose. To evaluate the efficiency of the developed approach, six specimens of the CFST columns with the rectangular cross-section were produced by placing some artificial defects during casting of concrete for simulating various uncompacted voids such as cavities, cracks, and debond. During the test, the time reversal technology was applied to rebuild the received signals and launch the reversed signals again by SAs, to overcome the issue of the lack of the prototype. Based on the proposed nonprototype, two indices of time reversibility (TR and symmetry (SYM were applied to relatively evaluate the level of concrete compactness in the range of the two SAs. The experimental results show that the developed method can effectively detect the compactness of concrete in CFST columns.

  16. Comparing a Perceptual and an Automated Vision-Based Method for Lie Detection in Younger Children

    NARCIS (Netherlands)

    Vieira Da Fonseca Serras Pereira, Mariana; Cozijn, Rein; Postma, Eric; Shahid, Suleman; Swerts, Marc

    2016-01-01

    The present study investigates how easily it can be detected whether a child is being truthful or not in a game situation, and it explores the cue validity of bodily movements for such type of classification. To achieve this, we introduce an innovative methodology – the combination of perception

  17. Phase-based x-ray scattering—A possible method to detect cancer cells in a very early stage

    Energy Technology Data Exchange (ETDEWEB)

    Feye-Treimer, U., E-mail: feye-treimer@helmholtz-berlin.de; Treimer, W. [Department of Mathematics, Physics and Chemistry, University of Applied Sciences, D-13353 Berlin, Germany and Joint Department G-GTOMO, Helmholtz Zentrum fuer Materialien und Energie Berlin, D-14109 Berlin (Germany)

    2014-05-15

    Purpose: This theoretical work contains a detailed investigation of the potential and sensitivity of phase-based x-ray scattering for cancer detection in biopsies if cancer is in a very early stage of development. Methods: Cancer cells in their early stage of development differ from healthy ones mainly due to their faster growing cell nuclei and the enlargement of their densities. This growth is accompanied by an altered nucleus–plasma relation for the benefit of the cell nuclei, that changes the physical properties especially the index of refraction of the cell and the one of the cell nuclei. Interaction of radiation with matter is known to be highly sensitive to small changes of the index of refraction of matter; therefore a detection of such changes of volume and density of cell nuclei by means of high angular resolved phase-based scattering of x rays might provide a technique to distinguish malignant cells from healthy ones ifthe cell–cell nucleus system is considered as a coherent phase shifting object. Then one can observe from a thin biopsy which represents a monolayer of cells (no multiple scattering) that phase-based x-ray scattering curves from healthy cells differ from those of cancer cells in their early stage of development. Results: Detailed calculations of x-ray scattering patterns from healthy and cancer cell nuclei yield graphs and numbers with which one can distinguish healthy cells from cancer ones, taking into account that both kinds of cells occur in a tissue within a range of size and density. One important result is the role and the influence of the (lateral) coherence width of the radiation on the scattering curves and the sensitivity of phase-based scattering for cancer detection. A major result is that a larger coherence width yields a larger sensitivity for cancer detection. Further import results are calculated limits for critical sizes and densities of cell nuclei in order to attribute the investigated tissue to be healthy or

  18. Marine neurotoxins: state of the art, bottlenecks, and perspectives for mode of action based methods of detection in seafood.

    Science.gov (United States)

    Nicolas, Jonathan; Hendriksen, Peter J M; Gerssen, Arjen; Bovee, Toine F H; Rietjens, Ivonne M C M

    2014-01-01

    Marine biotoxins can accumulate in fish and shellfish, representing a possible threat for consumers. Many marine biotoxins affect neuronal function essentially through their interaction with ion channels or receptors, leading to different symptoms including paralysis and even death. The detection of marine biotoxins in seafood products is therefore a priority. Official methods for control are often still using in vivo assays, such as the mouse bioassay. This test is considered unethical and the development of alternative assays is urgently required. Chemical analyses as well as in vitro assays have been developed to detect marine biotoxins in seafood. However, most of the current in vitro alternatives to animal testing present disadvantages: low throughput and lack of sensitivity resulting in a high number of false-negative results. Thus, there is an urgent need for the development of new in vitro tests that would allow the detection of marine biotoxins in seafood products at a low cost, with high throughput combined with high sensitivity, reproducibility, and predictivity. Mode of action based in vitro bioassays may provide tools that fulfil these requirements. This review covers the current state of the art of such mode of action based alternative assays to detect neurotoxic marine biotoxins in seafood. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  19. An electron microscopy based method for the detection and quantification of nanomaterial number concentration in environmentally relevant media

    Energy Technology Data Exchange (ETDEWEB)

    Prasad, A. [School of Geography, Earth and Environmental Sciences, College of Life and Environmental Sciences, University of Birmingham, Edgbaston, Birmingham B15 2TT (United Kingdom); Lead, J.R., E-mail: jlead@mailbox.sc.edu [School of Geography, Earth and Environmental Sciences, College of Life and Environmental Sciences, University of Birmingham, Edgbaston, Birmingham B15 2TT (United Kingdom); Center for Environmental Nanoscience and Risk, Department of Environmental Health Sciences, Arnold School of Public Health, University South Carolina, Columbia 29208, SC (United States); Baalousha, M., E-mail: mbaalous@mailbox.sc.edu [Center for Environmental Nanoscience and Risk, Department of Environmental Health Sciences, Arnold School of Public Health, University South Carolina, Columbia 29208, SC (United States)

    2015-12-15

    Improved detection and characterization of nanomaterials (NMs) in complex environmental media requires the development of novel sampling approaches to improve the detection limit to be close to environmentally realistic concentrations. Transmission electron microscopy (TEM) is an indispensable metrological tool in nanotechnology and environmental nanoscience due to its high spatial resolution and analytical capabilities when coupled to spectroscopic techniques. However, these capabilities are hampered by the conventional sample preparation methods, which suffer from low NM recovery. The current work presents a validated, fully quantitative sampling technique for TEM that overcomes conventional sample preparation shortcomings, and thus enables the use of TEM for measurement of particle number concentration and their detection in complex media at environmentally realistic concentrations. This sampling method is based on ultracentrifugation of NMs from suspension onto a poly-L-lysine (PLL) functionalized TEM grid, using active deposition (by ultracentrifugation) and retention (by PLL interactions with NM surface) of NMs on the substrate, enabling fully quantitative analysis. Similar analysis with AFM was satisfactory in simple media but the lack of chemical-selectivity of AFM limits its applicability for the detection of NMs in complex environmental samples. The sampling approach was validated using both citrate- and PVP-coated AuNMs in pure water, which demonstrated an even distribution of NM on the TEM grid and high NM recovery (80–100%) at environmentally relevant NM concentrations (ca. 0.20–100 μg L{sup −1}). The applicability of the sampling method to complex environmental samples was demonstrated by the quantification of particle number concentration of AuNMs in EPA soft water (with and without Suwannee River fulvic acid) and lake water. This sample preparation approach is also applicable to other types of NMs with some modifications (e.g. centrifugation

  20. An electron microscopy based method for the detection and quantification of nanomaterial number concentration in environmentally relevant media

    International Nuclear Information System (INIS)

    Prasad, A.; Lead, J.R.; Baalousha, M.

    2015-01-01

    Improved detection and characterization of nanomaterials (NMs) in complex environmental media requires the development of novel sampling approaches to improve the detection limit to be close to environmentally realistic concentrations. Transmission electron microscopy (TEM) is an indispensable metrological tool in nanotechnology and environmental nanoscience due to its high spatial resolution and analytical capabilities when coupled to spectroscopic techniques. However, these capabilities are hampered by the conventional sample preparation methods, which suffer from low NM recovery. The current work presents a validated, fully quantitative sampling technique for TEM that overcomes conventional sample preparation shortcomings, and thus enables the use of TEM for measurement of particle number concentration and their detection in complex media at environmentally realistic concentrations. This sampling method is based on ultracentrifugation of NMs from suspension onto a poly-L-lysine (PLL) functionalized TEM grid, using active deposition (by ultracentrifugation) and retention (by PLL interactions with NM surface) of NMs on the substrate, enabling fully quantitative analysis. Similar analysis with AFM was satisfactory in simple media but the lack of chemical-selectivity of AFM limits its applicability for the detection of NMs in complex environmental samples. The sampling approach was validated using both citrate- and PVP-coated AuNMs in pure water, which demonstrated an even distribution of NM on the TEM grid and high NM recovery (80–100%) at environmentally relevant NM concentrations (ca. 0.20–100 μg L"−"1). The applicability of the sampling method to complex environmental samples was demonstrated by the quantification of particle number concentration of AuNMs in EPA soft water (with and without Suwannee River fulvic acid) and lake water. This sample preparation approach is also applicable to other types of NMs with some modifications (e.g. centrifugation

  1. Crack detecting method

    International Nuclear Information System (INIS)

    Narita, Michiko; Aida, Shigekazu

    1998-01-01

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

  2. An Acoustic-Based Method to Detect and Quantify the Effect of Exhalation into a Dry Powder Inhaler.

    Science.gov (United States)

    Holmes, Martin S; Seheult, Jansen N; O'Connell, Peter; D'Arcy, Shona; Ehrhardt, Carsten; Healy, Anne Marie; Costello, Richard W; Reilly, Richard B

    2015-08-01

    Dry powder inhaler (DPI) users frequently exhale into their inhaler mouthpiece before the inhalation step. This error in technique compromises the integrity of the drug and results in poor bronchodilation. This study investigated the effect of four exhalation factors (exhalation flow rate, distance from mouth to inhaler, exhalation duration, and relative air humidity) on dry powder dose delivery. Given that acoustic energy can be related to the factors associated with exhalation sounds, we then aimed to develop a method of identifying and quantifying this critical inhaler technique error using acoustic based methods. An in vitro test rig was developed to simulate this critical error. The effect of the four factors on subsequent drug delivery were investigated using multivariate regression models. In a further study we then used an acoustic monitoring device to unobtrusively record the sounds 22 asthmatic patients made whilst using a Diskus(™) DPI. Acoustic energy was employed to automatically detect and analyze exhalation events in the audio files. All exhalation factors had a statistically significant effect on drug delivery (pacoustic method detected exhalations with an accuracy of 89.1%. We were able to classify exhalations occurring 5 cm or less in the direction of the inhaler mouthpiece or recording device with a sensitivity of 72.2% and specificity of 85.7%. Exhaling into a DPI has a significant detrimental effect. Acoustic based methods can be employed to objectively detect and analyze exhalations during inhaler use, thus providing a method of remotely monitoring inhaler technique and providing personalized inhaler technique feedback.

  3. Validation and User Evaluation of a Sensor-Based Method for Detecting Mobility-Related Activities in Older Adults.

    Directory of Open Access Journals (Sweden)

    Hilde A E Geraedts

    Full Text Available Regular physical activity is essential for older adults to stay healthy and independent. However, daily physical activity is generally low among older adults and mainly consists of activities such as standing and shuffling around indoors. Accurate measurement of this low-energy expenditure daily physical activity is crucial for stimulation of activity. The objective of this study was to assess the validity of a necklace-worn sensor-based method for detecting time-on-legs and daily life mobility related postures in older adults. In addition user opinion about the practical use of the sensor was evaluated. Twenty frail and non-frail older adults performed a standardized and free movement protocol in their own home. Results of the sensor-based method were compared to video observation. Sensitivity, specificity and overall agreement of sensor outcomes compared to video observation were calculated. Mobility was assessed based on time-on-legs. Further assessment included the categories standing, sitting, walking and lying. Time-on-legs based sensitivity, specificity and percentage agreement were good to excellent and comparable to laboratory outcomes in other studies. Category-based sensitivity, specificity and overall agreement were moderate to excellent. The necklace-worn sensor is considered an acceptable valid instrument for assessing home-based physical activity based upon time-on-legs in frail and non-frail older adults, but category-based assessment of gait and postures could be further developed.

  4. A rule-based fault detection method for air handling units

    Energy Technology Data Exchange (ETDEWEB)

    Schein, J.; Bushby, S. T.; Castro, N. S. [National Institute of Standards and Technology, Gaithersburg, MD (United States); House, J. M. [Iowa Energy Center, Ankeny, IA (United States)

    2006-07-01

    Air handling unit performance assessment rules (APAR) is a fault detection tool that uses a set of expert rules derived from mass and energy balances to detect faults in air handling units (AHUs). Control signals are used to determine the mode of operation of the AHU. A subset of the expert rules which correspond to that mode of operation are then evaluated to determine whether a fault exists. APAR is computationally simple enough that it can be embedded in commercial building automation and control systems and relies only upon the sensor data and control signals that are commonly available in these systems. APAR was tested using data sets collected from a 'hardware-in-the-loop' emulator and from several field sites. APAR was also embedded in commercial AHU controllers and tested in the emulator. (author)

  5. A DNA based method to detect the grapevine root-rotting fungus Roesleria subterranea in soil and root samples

    Directory of Open Access Journals (Sweden)

    S. Neuhauser

    2009-05-01

    Full Text Available Roesleria subterranea causes root rot in grapevine and fruit trees. The fungus has long been underestimated as a weak parasite, but during the last years it has been reported to cause severe damages in German vineyards. Direct, observation-based detection of the parasite is time consuming and destructive, as large parts of the rootstocks have to be uprooted and screened for the tiny, stipitate, hypogeous ascomata of R. subterranea. To facilitate rapid detection in vineyards, protocols to extract DNA from soil samples and grapevine roots, and R.-subterranea-specific PCR primers were designed. Twelve DNA-extraction protocols for soil samples were tested in small-scale experiments, and selected parameters were optimised. A protocol based on ball-mill homogenization, DNA extraction with SDS, skim milk, chloroform, and isopropanol, and subsequent purifi cation of the raw extracts with PVPP-spin-columns was most effective. This DNA extraction protocol was found to be suitable for a wide range of soil-types including clay, loam and humic-rich soils. For DNA extraction from grapevine roots a CTAB-based protocol was more reliable for various grapevine rootstock varieties. Roesleria-subterranea-specific primers for the ITS1-5.8S-ITS2 rDNA region were developed and tested for their specifi city to DNA extracts from eleven R. subterranea strains isolated from grapevine and fruit trees. No cross reactions were detected with DNA extracts from 44 different species of fungi isolated from vineyard soils. The sensitivity of the species-specifi c primers in combination with the DNA extraction method for soil was high: as little as 100 fg μl-1 R.-subterranea-DNA was suffi cient for a detection in soil samples and plant material. Given that specifi c primers are available, the presented method will also allow quick and large-scale testing for other root pathogens.

  6. Dynamic knock detection and quantification in a spark ignition engine by means of a pressure based method

    International Nuclear Information System (INIS)

    Galloni, Enzo

    2012-01-01

    Highlights: ► Experimental data have been analyzed by a pressure based method. ► Knock intensity level depends on a threshold varying with the engine operating point. ► A dynamic method is proposed to overcome the definition of a predetermined threshold. ► The knock intensity of each operating point is quantified by a dimensionless index. ► The knock limited spark advance can be detected by means of this index. - Abstract: In spark ignition engines, knock onset limits the maximum spark advance. An inaccurate identification of this limit penalises the fuel conversion efficiency. Thus it is very important to define a knock detection method able to assess the knock intensity of an engine operating point. Usually, in engine development, knock event is evaluated by analysing the in-cylinder pressure trace. Data are filtered and processed in order to obtain some indices correlated to the knock intensity, then the calculated value is compared to a predetermined threshold. The calibration of this threshold is complex and difficult; statistical approach should be used, but often empirical values are considered. In this paper a method that dynamically calculates the knock threshold necessary to determine the knock event is proposed. The purpose is to resolve cycle by cycle the knock intensity related to an individual engine cycle without setting a predetermined threshold. The method has been applied to an extensive set of experimental data relative to a gasoline spark-ignition engine. Results are correlated to those obtained considering a traditional method, where a statistical approach has been used to detect knock.

  7. A computer-based method for precise detection and calculation of affected skin areas

    DEFF Research Database (Denmark)

    Henriksen, Sille Mølvig; Nybing, Janus Damm; Bouert, Rasmus

    2016-01-01

    BACKGROUND: The aim of this study was to describe and validate a method to obtain reproducible and comparable results concerning extension of a specific skin area, unaffected by individual differences in body surface area. METHODS: A phantom simulating the human torso was equipped with three irre...

  8. The Detection of Subsynchronous Oscillation in HVDC Based on the Stochastic Subspace Identification Method

    Directory of Open Access Journals (Sweden)

    Chen Shi

    2014-01-01

    Full Text Available Subsynchronous oscillation (SSO usually caused by series compensation, power system stabilizer (PSS, high voltage direct current transmission (HVDC and other power electronic equipment, which will affect the safe operation of generator shafting even the system. It is very important to identify the modal parameters of SSO to take effective control strategies as well. Since the identification accuracy of traditional methods are not high enough, the stochastic subspace identification (SSI method is proposed to improve the identification accuracy of subsynchronous oscillation modal. The stochastic subspace identification method was compared with the other two methods on subsynchronous oscillation IEEE benchmark model and Xiang-Shang HVDC system model, the simulation results show that the stochastic subspace identification method has the advantages of high identification precision, high operation efficiency and strong ability of anti-noise.

  9. Evaluation of Gene-Based Family-Based Methods to Detect Novel Genes Associated With Familial Late Onset Alzheimer Disease

    Directory of Open Access Journals (Sweden)

    Maria V. Fernández

    2018-04-01

    Full Text Available Gene-based tests to study the combined effect of rare variants on a particular phenotype have been widely developed for case-control studies, but their evolution and adaptation for family-based studies, especially studies of complex incomplete families, has been slower. In this study, we have performed a practical examination of all the latest gene-based methods available for family-based study designs using both simulated and real datasets. We examined the performance of several collapsing, variance-component, and transmission disequilibrium tests across eight different software packages and 22 models utilizing a cohort of 285 families (N = 1,235 with late-onset Alzheimer disease (LOAD. After a thorough examination of each of these tests, we propose a methodological approach to identify, with high confidence, genes associated with the tested phenotype and we provide recommendations to select the best software and model for family-based gene-based analyses. Additionally, in our dataset, we identified PTK2B, a GWAS candidate gene for sporadic AD, along with six novel genes (CHRD, CLCN2, HDLBP, CPAMD8, NLRP9, and MAS1L as candidate genes for familial LOAD.

  10. A PCR based method to detect Russula spp. in soil samples and Limodorum abortivum roots in Mediterranean environments

    Directory of Open Access Journals (Sweden)

    Eduardo Larriba

    2015-04-01

    Full Text Available Aim of study: Orchidaceaehas the largest number of species of any family in the plant kingdom. This family is subject to a high risk of extinction in natural environments, such as natural parks and protected areas. Recent studies have shown the prevalence of many species of orchids to be linked to fungal soil diversity, due to their myco-heterotrophic behaviour. Plant communities determine fungal soil diversity, and both generate optimal conditions for orchid development. Area of study: The work was carried out in n the two most important natural parks in Alicante (Font Roja and Sierra Mariola, in South-eastern of Spain. Material and Methods: We designed a molecular tool to monitor the presence of Russula spp. in soil and orchids roots, combined with phytosociological methods. Main results: Using a PCR-based method, we detected the presence in the soil and Limodorum abortivum orchid roots of the mycorrhizal fungi Russula spp. The species with highest coverage was Quercus rotundifolia in areas where the orchid was present. Research highlights: We present a useful tool based on PCR to detect the presence of Russula spp. in a natural environment. These results are consistent with those obtained in different studies that linked the presence of the mycorrhizal fungi Russula spp. in roots of the species Limodorum and the interaction between these fungal species and Quercus ilex trees in Mediterranean forest environments.

  11. A Method against Interrupted-Sampling Repeater Jamming Based on Energy Function Detection and Band-Pass Filtering

    Directory of Open Access Journals (Sweden)

    Hui Yuan

    2017-01-01

    Full Text Available Interrupted-sampling repeater jamming (ISRJ is a new kind of coherent jamming to the large time-bandwidth linear frequency modulation (LFM signal. Many jamming modes, such as lifelike multiple false targets and dense false targets, can be made through setting up different parameters. According to the “storage-repeater-storage-repeater” characteristics of the ISRJ and the differences in the time-frequency-energy domain between the ISRJ signal and the target echo signal, one new method based on the energy function detection and band-pass filtering is proposed to suppress the ISRJ. The methods mainly consist of two parts: extracting the signal segments without ISRJ and constructing band-pass filtering function with low sidelobe. The simulation results show that the method is effective in the ISRJ with different parameters.

  12. A Novel Method for Inverter Faults Detection and Diagnosis in PMSM Drives of HEVs based on Discrete Wavelet Transform

    Directory of Open Access Journals (Sweden)

    AKTAS, M.

    2012-11-01

    Full Text Available The paper proposes a novel method, based on wavelet decomposition, for detection and diagnosis of faults (switch short-circuits and switch open-circuits in the driving systems with Field Oriented Controlled Permanent Magnet Synchro?nous Motors (PMSM of Hybrid Electric Vehicles. The fault behaviour of the analyzed system was simulated by Matlab/SIMULINK R2010a. The stator currents during transients were analysed up to the sixth level detail wavelet decomposition by Symlet2 wavelet. The results prove that the proposed fault diagnosis system have very good capabilities.

  13. Intelligent Detection of Structure from Remote Sensing Images Based on Deep Learning Method

    Science.gov (United States)

    Xin, L.

    2018-04-01

    Utilizing high-resolution remote sensing images for earth observation has become the common method of land use monitoring. It requires great human participation when dealing with traditional image interpretation, which is inefficient and difficult to guarantee the accuracy. At present, the artificial intelligent method such as deep learning has a large number of advantages in the aspect of image recognition. By means of a large amount of remote sensing image samples and deep neural network models, we can rapidly decipher the objects of interest such as buildings, etc. Whether in terms of efficiency or accuracy, deep learning method is more preponderant. This paper explains the research of deep learning method by a great mount of remote sensing image samples and verifies the feasibility of building extraction via experiments.

  14. Detection of Staphylococcus aureus among coagulase positive staphylococci from animal origin based on conventional and molecular methods

    Directory of Open Access Journals (Sweden)

    Nikolina Velizarova Rusenova

    2017-03-01

    Full Text Available The present study aimed to detect Staphylococcus aureus (S. aureus among other coagulase positive staphylococci from animal origin by using conventional methods (biochemical tests and latex agglutination and a molecular method, based on the nuc gene, as the gold standard and to assess the usefulness of these methods. For this purpose, total of 344 staphylococcal isolates were collected and analysed. A total of 156 isolates suspicious for S. aureus were detected by a conventional biochemical method – 88 from cows, 18 from goats, 7 from pigs, 17 from poultry, 7 from rabbits and 19 from dogs. The majority of S. aureus strains gave typical biochemical reactions with the exception of 30 (19.2% and 25 (16% that were VP negative and weak positive in fermenting mannitol, respectively. Twelve strains were found to be non-haemolytic (7.7% and four strains did not ferment trehalose (2.6%. Other staphylococci were identified as S. pseudintermedius (n = 103, S. hyicus (n = 23 and the rest were coagulase-negative staphylococci. Latex agglutination test resulted in rapid positive reactions with S. aureus with exception of 5 strains (3.2% from cow mastitis milk. Positive agglutination reactions were also established with S. pseudintermedius, and S. hyicus. PCR confirmed all strains that were preliminary identified as S. aureus by amplification of 270 bp fragment of nuc gene specific for this species. The atypical reactions in certain strains established in this study have shown that the precise detection of S. aureus from animal origin should be done by combination of conventional and molecular methods.

  15. Standoff Methods for the Detection of Threat Agents: A Review of Several Promising Laser-Based Techniques

    Directory of Open Access Journals (Sweden)

    J. Bruce Johnson

    2014-01-01

    Full Text Available Detection of explosives, explosive precursors, or other threat agents presents a number of technological challenges for optical sensing methods. Certainly detecting trace levels of threat agents against a complex background is chief among these challenges; however, the related issues of multiple target distances (from standoff to proximity and sampling time scales (from passive mines to rapid rate of march convoy protection for different applications make it unlikely that a single technique will be ideal for all sensing situations. A number of methods for spanning the range of optical sensor technologies exist which, when integrated, could produce a fused sensor system possessing a high level of sensitivity to threat agents and a moderate standoff real-time capability appropriate for portal screening of personnel or vehicles. In this work, we focus on several promising, and potentially synergistic, laser-based methods for sensing threat agents. For each method, we have briefly outlined the technique and report on the current level of capability.

  16. A parameter-free community detection method based on centrality and dispersion of nodes in complex networks

    Science.gov (United States)

    Li, Yafang; Jia, Caiyan; Yu, Jian

    2015-11-01

    K-means is a simple and efficient clustering algorithm to detect communities in networks. However, it may suffer from a bad choice of initial seeds (also called centers) that seriously affect the clustering accuracy and the convergence rate. Additionally, in K-means, the number of communities should be specified in advance. Till now, it is still an open problem on how to select initial seeds and how to determine the number of communities. In this study, a new parameter-free community detection method (named K-rank-D) was proposed. First, based on the fact that good initial seeds usually have high importance and are dispersedly located in a network, we proposed a modified PageRank centrality to evaluate the importance of a node, and drew a decision graph to depict the importance and the dispersion of nodes. Then, the initial seeds and the number of communities were selected from the decision graph actively and intuitively as the 'start' parameter of K-means. Experimental results on synthetic and real-world networks demonstrate the superior performance of our approach over competing methods for community detection.

  17. Gold Nanoparticle-Aptamer-Based LSPR Sensing of Ochratoxin A at a Widened Detection Range by Double Calibration Curve Method.

    Science.gov (United States)

    Liu, Boshi; Huang, Renliang; Yu, Yanjun; Su, Rongxin; Qi, Wei; He, Zhimin

    2018-01-01

    Ochratoxin A (OTA) is a type of mycotoxin generated from the metabolism of Aspergillus and Penicillium , and is extremely toxic to humans, livestock, and poultry. However, traditional assays for the detection of OTA are expensive and complicated. Other than OTA aptamer, OTA itself at high concentration can also adsorb on the surface of gold nanoparticles (AuNPs), and further inhibit AuNPs salt aggregation. We herein report a new OTA assay by applying the localized surface plasmon resonance effect of AuNPs and their aggregates. The result obtained from only one single linear calibration curve is not reliable, and so we developed a "double calibration curve" method to address this issue and widen the OTA detection range. A number of other analytes were also examined, and the structural properties of analytes that bind with the AuNPs were further discussed. We found that various considerations must be taken into account in the detection of these analytes when applying AuNP aggregation-based methods due to their different binding strengths.

  18. Temporal Methods to Detect Content-Based Anomalies in Social Media

    Energy Technology Data Exchange (ETDEWEB)

    Skryzalin, Jacek [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Field, Jr., Richard [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Fisher, Andrew N. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Bauer, Travis L. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2017-11-01

    Here, we develop a method for time-dependent topic tracking and meme trending in social media. Our objective is to identify time periods whose content differs signifcantly from normal, and we utilize two techniques to do so. The first is an information-theoretic analysis of the distributions of terms emitted during different periods of time. In the second, we cluster documents from each time period and analyze the tightness of each clustering. We also discuss a method of combining the scores created by each technique, and we provide ample empirical analysis of our methodology on various Twitter datasets.

  19. Real-time PCR-based method for rapid detection of Aspergillus niger and Aspergillus welwitschiae isolated from coffee.

    Science.gov (United States)

    von Hertwig, Aline Morgan; Sant'Ana, Anderson S; Sartori, Daniele; da Silva, Josué José; Nascimento, Maristela S; Iamanaka, Beatriz Thie; Pelegrinelli Fungaro, Maria Helena; Taniwaki, Marta Hiromi

    2018-05-01

    Some species from Aspergillus section Nigri are morphologically very similar and altogether have been called A. niger aggregate. Although the species included in this group are morphologically very similar, they differ in their ability to produce mycotoxins and other metabolites and their taxonomical status has evolved continuously. Among them, A. niger and A. welwitschiae are ochratoxin A and fumonisin B 2 producers and their detection and/or identification is of crucial importance for food safety. The aim of this study was the development of a real-time PCR-based method for simultaneous discrimination of A. niger and A. welwitschiae from other species of the A. niger aggregate isolated from coffee beans. One primer pair and a hybridization probe specific for detection of A. niger and A. welwitschiae strains were designed based on the BenA gene sequences, and used in a Real-time PCR assay for the rapid discrimination between both these species from all others of the A. niger aggregate. The Real-time PCR assay was shown to be 100% efficient in discriminating the 73 isolates of A. niger/A. welwitschiae from the other A. niger aggregate species analyzed as a negative control. This result testifies to the use of this technique as a good tool in the rapid detection of these important toxigenic species. Copyright © 2018 Elsevier B.V. All rights reserved.

  20. [Molecular beacon based PNA-FISH method combined with fluorescence scanning for rapid detection of Listeria monocytogenes].

    Science.gov (United States)

    Wu, Shan; Zhang, Xiaofeng; Shuai, Jiangbing; Li, Ke; Yu, Huizhen; Jin, Chenchen

    2016-07-04

    To simplify the PNA-FISH (Peptide nucleic acid-fluorescence in situ hybridization) test, molecular beacon based PNA probe combined with fluorescence scanning detection technology was applied to replace the original microscope observation to detect Listeria monocytogenes The 5′ end and 3′ end of the L. monocytogenes specific PNA probes were labeled with the fluorescent group and the quenching group respectively, to form a molecular beacon based PNA probe. When PNA probe used for fluorescence scanning and N1 treatment as the control, the false positive rate was 11.4%, and the false negative rate was 0; when N2 treatment as the control, the false positive rate decreased to 4.3%, but the false negative rate rose to 18.6%. When beacon based PNA probe used for fluorescence scanning, taken N1 treatment as blank control, the false positive rate was 8.6%, and the false negative rate was 1.4%; taken N2 treatment as blank control, the false positive rate was 5.7%, and the false negative rate was 1.4%. Compared with PNA probe, molecular beacon based PNA probe can effectively reduce false positives and false negatives. The success rates of hybridization of the two PNA probes were 83.3% and 95.2% respectively; and the rates of the two beacon based PNA probes were 91.7% and 90.5% respectively, which indicated that labeling the both ends of the PNA probe dose not decrease the hybridization rate with the target bacteria. The combination of liquid phase PNA-FISH and fluorescence scanning method, can significantly improve the detection efficiency.

  1. A Review of Automatic Methods Based on Image Processing Techniques for Tuberculosis Detection from Microscopic Sputum Smear Images.

    Science.gov (United States)

    Panicker, Rani Oomman; Soman, Biju; Saini, Gagan; Rajan, Jeny

    2016-01-01

    Tuberculosis (TB) is an infectious disease caused by the bacteria Mycobacterium tuberculosis. It primarily affects the lungs, but it can also affect other parts of the body. TB remains one of the leading causes of death in developing countries, and its recent resurgences in both developed and developing countries warrant global attention. The number of deaths due to TB is very high (as per the WHO report, 1.5 million died in 2013), although most are preventable if diagnosed early and treated. There are many tools for TB detection, but the most widely used one is sputum smear microscopy. It is done manually and is often time consuming; a laboratory technician is expected to spend at least 15 min per slide, limiting the number of slides that can be screened. Many countries, including India, have a dearth of properly trained technicians, and they often fail to detect TB cases due to the stress of a heavy workload. Automatic methods are generally considered as a solution to this problem. Attempts have been made to develop automatic approaches to identify TB bacteria from microscopic sputum smear images. In this paper, we provide a review of automatic methods based on image processing techniques published between 1998 and 2014. The review shows that the accuracy of algorithms for the automatic detection of TB increased significantly over the years and gladly acknowledges that commercial products based on published works also started appearing in the market. This review could be useful to researchers and practitioners working in the field of TB automation, providing a comprehensive and accessible overview of methods of this field of research.

  2. SERS-based detection methods for screening of genetically modified bacterial strains

    DEFF Research Database (Denmark)

    Morelli, Lidia

    factories vary largely, including industrial production of valuable compounds for biofuels, polymer synthesis and food, cosmetic and pharmaceutical industry. The improvement of computational and biochemical tools has revolutionized the synthesis of novel modified microbial strains, opening up new......The importance of metabolic engineering has been growing over the last decades, establishing the use of genetically modified microbial strains for overproduction of metabolites at industrial scale as an innovative, convenient and biosustainable method. Nowadays, application areas of microbial...

  3. Comparing a perceptual and an automated vision-based method for lie detection in younger children

    Directory of Open Access Journals (Sweden)

    Mariana Serras Pereira

    2016-12-01

    Full Text Available The present study investigates how easily it can be detected whether a child is being truthful or not in a game situation, and it explores the cue validity of bodily movements for such type of classification. To achieve this, we introduce an innovative methodology – the combination of perception studies (in which one uses eye-tracking technology and automated movement analysis. Film fragments from truthful and deceptive children were shown to human judges who were given the task to decide whether the recorded child was being truthful or not. Results reveal that judges are able to accurately distinguish truthful clips from lying clips in both perception studies. Even though the automated movement analysis for overall and specific body regions did not yield significant results between the experimental conditions, we did find a positive correlation between the amount of movement in a child and the perception of lies, i.e., the more movement the children exhibited during a clip, the higher the chance that the clip was perceived as a lie. The eye-tracking study revealed that, even when there is movement happening on different body regions, judges tend to focus their attention mainly on the face region.

  4. Time-windows-based filtering method for near-surface detection of leakage from geologic carbon sequestration sites

    Energy Technology Data Exchange (ETDEWEB)

    Pan, L.; Lewicki, J.L.; Oldenburg, C.M.; Fischer, M.L.

    2010-02-28

    We use process-based modeling techniques to characterize the temporal features of natural biologically controlled surface CO{sub 2} fluxes and the relationships between the assimilation and respiration fluxes. Based on these analyses, we develop a signal-enhancing technique that combines a novel time-window splitting scheme, a simple median filtering, and an appropriate scaling method to detect potential signals of leakage of CO{sub 2} from geologic carbon sequestration sites from within datasets of net near-surface CO{sub 2} flux measurements. The technique can be directly applied to measured data and does not require subjective gap filling or data-smoothing preprocessing. Preliminary application of the new method to flux measurements from a CO{sub 2} shallow-release experiment appears promising for detecting a leakage signal relative to background variability. The leakage index of ?2 was found to span the range of biological variability for various ecosystems as determined by observing CO{sub 2} flux data at various control sites for a number of years.

  5. Short-Term Wind Speed Forecasting Using Decomposition-Based Neural Networks Combining Abnormal Detection Method

    Directory of Open Access Journals (Sweden)

    Xuejun Chen

    2014-01-01

    Full Text Available As one of the most promising renewable resources in electricity generation, wind energy is acknowledged for its significant environmental contributions and economic competitiveness. Because wind fluctuates with strong variation, it is quite difficult to describe the characteristics of wind or to estimate the power output that will be injected into the grid. In particular, short-term wind speed forecasting, an essential support for the regulatory actions and short-term load dispatching planning during the operation of wind farms, is currently regarded as one of the most difficult problems to be solved. This paper contributes to short-term wind speed forecasting by developing two three-stage hybrid approaches; both are combinations of the five-three-Hanning (53H weighted average smoothing method, ensemble empirical mode decomposition (EEMD algorithm, and nonlinear autoregressive (NAR neural networks. The chosen datasets are ten-minute wind speed observations, including twelve samples, and our simulation indicates that the proposed methods perform much better than the traditional ones when addressing short-term wind speed forecasting problems.

  6. Multilevel Thresholding Method Based on Electromagnetism for Accurate Brain MRI Segmentation to Detect White Matter, Gray Matter, and CSF

    Directory of Open Access Journals (Sweden)

    G. Sandhya

    2017-01-01

    Full Text Available This work explains an advanced and accurate brain MRI segmentation method. MR brain image segmentation is to know the anatomical structure, to identify the abnormalities, and to detect various tissues which help in treatment planning prior to radiation therapy. This proposed technique is a Multilevel Thresholding (MT method based on the phenomenon of Electromagnetism and it segments the image into three tissues such as White Matter (WM, Gray Matter (GM, and CSF. The approach incorporates skull stripping and filtering using anisotropic diffusion filter in the preprocessing stage. This thresholding method uses the force of attraction-repulsion between the charged particles to increase the population. It is the combination of Electromagnetism-Like optimization algorithm with the Otsu and Kapur objective functions. The results obtained by using the proposed method are compared with the ground-truth images and have given best values for the measures sensitivity, specificity, and segmentation accuracy. The results using 10 MR brain images proved that the proposed method has accurately segmented the three brain tissues compared to the existing segmentation methods such as K-means, fuzzy C-means, OTSU MT, Particle Swarm Optimization (PSO, Bacterial Foraging Algorithm (BFA, Genetic Algorithm (GA, and Fuzzy Local Gaussian Mixture Model (FLGMM.

  7. Comparison of PCR-Based Diagnosis with Centrifuged-Based Enrichment Method for Detection of Borrelia persica in Animal Blood Samples.

    Science.gov (United States)

    Naddaf, S R; Kishdehi, M; Siavashi, Mr

    2011-01-01

    The mainstay of diagnosis of relapsing fever (RF) is demonstration of the spirochetes in Giemsa-stained thick blood smears, but during non fever periods the bacteria are very scanty and rarely detected in blood smears by microscopy. This study is aimed to evaluate the sensitivity of different methods developed for detection of low-grade spirochetemia. Animal blood samples with low degrees of spirochetemia were tested with two PCRs and a nested PCR targeting flaB, GlpQ, and rrs genes. Also, a centrifuged-based enrichment method and Giemsa staining were performed on blood samples with various degrees of spirochetemia. The flaB-PCR and nested rrs-PCR turned positive with various degrees of spirochetemia including the blood samples that turned negative with dark-field microscopy. The GlpQ-PCR was positive as far as at least one spirochete was seen in 5-10 microscopic fields. The sensitivity of GlpQ-PCR increased when DNA from Buffy Coat Layer (BCL) was used as template. The centrifuged-based enrichment method turned positive with as low concentration as 50 bacteria/ml blood, while Giemsa thick staining detected bacteria with concentrations ≥ 25000 bacteria/ml. Centrifuged-based enrichment method appeared as much as 500-fold more sensitive than thick smears, which makes it even superior to some PCR assays. Due to simplicity and minimal laboratory requirements, this method can be considered a valuable tool for diagnosis of RF in rural health centers.

  8. Leak detection by vibrational diagnostic methods

    International Nuclear Information System (INIS)

    Siklossy, P.

    1983-01-01

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

  9. Improving image quality for digital breast tomosynthesis: an automated detection and diffusion-based method for metal artifact reduction

    Science.gov (United States)

    Lu, Yao; Chan, Heang-Ping; Wei, Jun; Hadjiiski, Lubomir M.; Samala, Ravi K.

    2017-10-01

    In digital breast tomosynthesis (DBT), the high-attenuation metallic clips marking a previous biopsy site in the breast cause errors in the estimation of attenuation along the ray paths intersecting the markers during reconstruction, which result in interplane and inplane artifacts obscuring the visibility of subtle lesions. We proposed a new metal artifact reduction (MAR) method to improve image quality. Our method uses automatic detection and segmentation to generate a marker location map for each projection (PV). A voting technique based on the geometric correlation among different PVs is designed to reduce false positives (FPs) and to label the pixels on the PVs and the voxels in the imaged volume that represent the location and shape of the markers. An iterative diffusion method replaces the labeled pixels on the PVs with estimated tissue intensity from the neighboring regions while preserving the original pixel values in the neighboring regions. The inpainted PVs are then used for DBT reconstruction. The markers are repainted on the reconstructed DBT slices for radiologists’ information. The MAR method is independent of reconstruction techniques or acquisition geometry. For the training set, the method achieved 100% success rate with one FP in 19 views. For the test set, the success rate by view was 97.2% for core biopsy microclips and 66.7% for clusters of large post-lumpectomy markers with a total of 10 FPs in 58 views. All FPs were large dense benign calcifications that also generated artifacts if they were not corrected by MAR. For the views with successful detection, the metal artifacts were reduced to a level that was not visually apparent in the reconstructed slices. The visibility of breast lesions obscured by the reconstruction artifacts from the metallic markers was restored.

  10. Surface electromyography based muscle fatigue detection using high-resolution time-frequency methods and machine learning algorithms.

    Science.gov (United States)

    Karthick, P A; Ghosh, Diptasree Maitra; Ramakrishnan, S

    2018-02-01

    Surface electromyography (sEMG) based muscle fatigue research is widely preferred in sports science and occupational/rehabilitation studies due to its noninvasiveness. However, these signals are complex, multicomponent and highly nonstationary with large inter-subject variations, particularly during dynamic contractions. Hence, time-frequency based machine learning methodologies can improve the design of automated system for these signals. In this work, the analysis based on high-resolution time-frequency methods, namely, Stockwell transform (S-transform), B-distribution (BD) and extended modified B-distribution (EMBD) are proposed to differentiate the dynamic muscle nonfatigue and fatigue conditions. The nonfatigue and fatigue segments of sEMG signals recorded from the biceps brachii of 52 healthy volunteers are preprocessed and subjected to S-transform, BD and EMBD. Twelve features are extracted from each method and prominent features are selected using genetic algorithm (GA) and binary particle swarm optimization (BPSO). Five machine learning algorithms, namely, naïve Bayes, support vector machine (SVM) of polynomial and radial basis kernel, random forest and rotation forests are used for the classification. The results show that all the proposed time-frequency distributions (TFDs) are able to show the nonstationary variations of sEMG signals. Most of the features exhibit statistically significant difference in the muscle fatigue and nonfatigue conditions. The maximum number of features (66%) is reduced by GA and BPSO for EMBD and BD-TFD respectively. The combination of EMBD- polynomial kernel based SVM is found to be most accurate (91% accuracy) in classifying the conditions with the features selected using GA. The proposed methods are found to be capable of handling the nonstationary and multicomponent variations of sEMG signals recorded in dynamic fatiguing contractions. Particularly, the combination of EMBD- polynomial kernel based SVM could be used to

  11. A simple and sensitive method for L-cysteine detection based on the fluorescence intensity increment of quantum dots

    International Nuclear Information System (INIS)

    Huang Shan; Xiao Qi; Li Ran; Guan Hongliang; Liu Jing; Liu Xiaorong; He Zhike; Liu Yi

    2009-01-01

    In this contribution, a simple and sensitive method for L-cysteine detection was established based on the increment of the fluorescence intensity of mercaptoacetic acid-capped CdSe/ZnS quantum dots (QDs) in aqueous solution. Meanwhile, the fluorescence characteristics and the optimal conditions were investigated in detail. Under the optimized conditions, the linear range of QDs fluorescence intensity versus the concentration of L-cysteine was 10-800 nmol L -1 , with a correlation coefficient (R) of 0.9969 and a limit of detection (3σ black) of 3.8 nmol L -1 . The relative standard deviation (R.S.D.) for 0.5 μmol L -1 L-cysteine was 1.1% (n = 5). There was no interference to coexisting foreign substances including common ions, carbohydrates, nucleotide acids and other 19 amino acids. The proposed method possessed the advantages of simplicity, rapidity and sensitivity. Synthetic amino acid samples, medicine sample together with human urine samples were analyzed by the methodology and the results were satisfying.

  12. A highly sensitive and specific method for the screening detection of genetically modified organisms based on digital PCR without pretreatment.

    Science.gov (United States)

    Fu, Wei; Zhu, Pengyu; Wang, Chenguang; Huang, Kunlun; Du, Zhixin; Tian, Wenying; Wang, Qin; Wang, Huiyu; Xu, Wentao; Zhu, Shuifang

    2015-08-04

    Digital PCR has developed rapidly since it was first reported in the 1990 s. It was recently reported that an improved method facilitated the detection of genetically modified organisms (GMOs). However, to use this improved method, the samples must be pretreated, which could introduce inaccuracy into the results. In our study, we explored a pretreatment-free digital PCR detection method for the screening for GMOs. We chose the CaMV35s promoter and the NOS terminator as the templates in our assay. To determine the specificity of our method, 9 events of GMOs were collected, including MON810, MON863, TC1507, MIR604, MIR162, GA21, T25, NK603 and Bt176. Moreover, the sensitivity, intra-laboratory and inter-laboratory reproducibility of our detection method were assessed. The results showed that the limit of detection of our method was 0.1%, which was lower than the labeling threshold level of the EU. The specificity and stability among the 9 events were consistent, respectively. The intra-laboratory and inter-laboratory reproducibility were both good. Finally, the perfect fitness for the detection of eight double-blind samples indicated the good practicability of our method. In conclusion, the method in our study would allow more sensitive, specific and stable screening detection of the GMO content of international trading products.

  13. A New Method to Detect Driver Fatigue Based on EMG and ECG Collected by Portable Non-Contact Sensors

    Directory of Open Access Journals (Sweden)

    Lin Wang

    2017-11-01

    Full Text Available Recently, detection and prediction on driver fatigue have become interest of research worldwide. In the present work, a new method is built to effectively evaluate driver fatigue based on electromyography (EMG and electrocardiogram (ECG collected by portable real-time and non-contact sensors. First, under the non-disturbance condition for driver’s attention, mixed physiological signals (EMG, ECG and artefacts are collected by non-contact sensors located in a cushion on the driver’s seat. EMG and ECG are effectively separated by FastICA, and de-noised by empirical mode decomposition (EMD. Then, three physiological features, complexity of EMG, complexity of ECG, and sample entropy (SampEn of ECG, are extracted and analysed. Principal components are obtained by principal components analysis (PCA and are used as independent variables. Finally, a mathematical model of driver fatigue is built, and the accuracy of the model is up to 91%. Moreover, based on the questionnaire, the calculation results of model are consistent with real fatigue felt by the participants. Therefore, this model can effectively detect driver fatigue.

  14. PCR-based methods for the detection of L1014 kdr mutation in Anopheles culicifacies sensu lato

    Science.gov (United States)

    Singh, Om P; Bali, Prerna; Hemingway, Janet; Subbarao, Sarala K; Dash, Aditya P; Adak, Tridibes

    2009-01-01

    Background Anopheles culicifacies s.l., a major malaria vector in India, has developed widespread resistance to DDT and is becoming resistant to pyrethroids–the only insecticide class recommended for the impregnation of bed nets. Knock-down resistance due to a point mutation in the voltage gated sodium channel at L1014 residue (kdr) is a common mechanism of resistance to DDT and pyrethroids. The selection of this resistance may pose a serious threat to the success of the pyrethroid-impregnated bed net programme. This study reports the presence of kdr mutation (L1014F) in a field population of An. culicifacies s.l. and three new PCR-based methods for kdr genotyping. Methods The IIS4-IIS5 linker to IIS6 segments of the para type voltage gated sodium channel gene of DDT and pyrethroid resistant An. culicifacies s.l. population from the Surat district of India was sequenced. This revealed the presence of an A-to-T substitution at position 1014 leading to a leucine-phenylalanine mutation (L1014F) in a few individuals. Three molecular methods viz. Allele Specific PCR (AS-PCR), an Amplification Refractory Mutation System (ARMS) and Primer Introduced Restriction Analysis-PCR (PIRA-PCR) were developed and tested for kdr genotyping. The specificity of the three assays was validated following DNA sequencing of the samples genotyped. Results The genotyping of this An. culicifacies s.l. population by the three PCR based assays provided consistent result and were in agreement with DNA sequencing result. A low frequency of the kdr allele mostly in heterozygous condition was observed in the resistant population. Frequencies of the different genotypes were in Hardy-Weinberg equilibrium. Conclusion The Leu-Phe mutation, which generates the kdr phenotype in many insects, was detected in a pyrethroid and DDT resistant An. culicifacies s.l. population. Three PCR-based methods were developed for kdr genotyping. All the three assays were specific. The ARMS method was refractory to non

  15. PCR-based methods for the detection of L1014 kdr mutation in Anopheles culicifacies sensu lato

    Directory of Open Access Journals (Sweden)

    Dash Aditya P

    2009-07-01

    Full Text Available Abstract Background Anopheles culicifacies s.l., a major malaria vector in India, has developed widespread resistance to DDT and is becoming resistant to pyrethroids–the only insecticide class recommended for the impregnation of bed nets. Knock-down resistance due to a point mutation in the voltage gated sodium channel at L1014 residue (kdr is a common mechanism of resistance to DDT and pyrethroids. The selection of this resistance may pose a serious threat to the success of the pyrethroid-impregnated bed net programme. This study reports the presence of kdr mutation (L1014F in a field population of An. culicifacies s.l. and three new PCR-based methods for kdr genotyping. Methods The IIS4-IIS5 linker to IIS6 segments of the para type voltage gated sodium channel gene of DDT and pyrethroid resistant An. culicifacies s.l. population from the Surat district of India was sequenced. This revealed the presence of an A-to-T substitution at position 1014 leading to a leucine-phenylalanine mutation (L1014F in a few individuals. Three molecular methods viz. Allele Specific PCR (AS-PCR, an Amplification Refractory Mutation System (ARMS and Primer Introduced Restriction Analysis-PCR (PIRA-PCR were developed and tested for kdr genotyping. The specificity of the three assays was validated following DNA sequencing of the samples genotyped. Results The genotyping of this An. culicifacies s.l. population by the three PCR based assays provided consistent result and were in agreement with DNA sequencing result. A low frequency of the kdr allele mostly in heterozygous condition was observed in the resistant population. Frequencies of the different genotypes were in Hardy-Weinberg equilibrium. Conclusion The Leu-Phe mutation, which generates the kdr phenotype in many insects, was detected in a pyrethroid and DDT resistant An. culicifacies s.l. population. Three PCR-based methods were developed for kdr genotyping. All the three assays were specific. The ARMS method

  16. Bovine tuberculosis in South Darfur State, Sudan: an abattoir study based on microscopy and molecular detection methods.

    Science.gov (United States)

    Asil, El Tigani A; El Sanousi, Sulieman M; Gameel, Ahmed; El Beir, Haytham; Fathelrahman, Maha; Terab, Nasir M; Muaz, Magzoub A; Hamid, Mohamed E

    2013-02-01

    Bovine tuberculosis (BTB) is a widespread zoonosis in developing countries but has received little attention in many sub-Saharan African countries including Sudan and particularly in some parts such as Darfur states. This study aimed to detect bovine tuberculosis among caseous materials of cattle slaughtered in abattoirs in South Darfur State, Sudan by using microscopic and PCR-based methods. The study was a cross-sectional abattoir-based study which examined a total of 6,680 bovine carcasses for caseous lesions in South Darfur State between 2007 and 2009. Collected specimens were examined for the presence of acid-fast bacilli (AFB) by using microscopic and culture techniques. Isolated mycobacteria were identified by selected conventional cultural and biochemical tests in comparison to a single tube multiplex PCR (m-PCR) assay which detect Mycobacterium bovis-specific 168-bp amplicons. Of the total 6,680 slaughtered cattle examined in South Darfur, 400 (6 %) showed caseations restricted to lymph nodes (86.8 %) or generalized (13.2 %). Bovine tuberculosis was diagnosed in 12 (0.18 %), bovine farcy in 59 (0.88 %), unidentified mycobacteria in 6 (0.09 %), and missed or contaminated cultures in 7 (0.1 %). Out of 18 cultures with nonbranching acid-fast rods, 12 amplified unique 168-bp sequence specific for M. bovis and subsequently confirmed as M. bovis. With the exception of the reference M. tuberculosis strains, none of the remaining AFB amplified the 337-bp amplicon specific for M. tuberculosis. It could be concluded that bovine tuberculosis is prevalent among cattle in South Darfur representing 4.5 % from all slaughtered cattle with caseous lesions. The study sustains microscopy as a useful and accessible technique for detecting AFB. m-PCR assay proved to be valuable for confirmation of BTB and its differentiation from other related mycobacteriosis, notably bovine farcy.

  17. A Bootstrap Based Measure Robust to the Choice of Normalization Methods for Detecting Rhythmic Features in High Dimensional Data.

    Science.gov (United States)

    Larriba, Yolanda; Rueda, Cristina; Fernández, Miguel A; Peddada, Shyamal D

    2018-01-01

    Motivation: Gene-expression data obtained from high throughput technologies are subject to various sources of noise and accordingly the raw data are pre-processed before formally analyzed. Normalization of the data is a key pre-processing step, since it removes systematic variations across arrays. There are numerous normalization methods available in the literature. Based on our experience, in the context of oscillatory systems, such as cell-cycle, circadian clock, etc., the choice of the normalization method may substantially impact the determination of a gene to be rhythmic. Thus rhythmicity of a gene can purely be an artifact of how the data were normalized. Since the determination of rhythmic genes is an important component of modern toxicological and pharmacological studies, it is important to determine truly rhythmic genes that are robust to the choice of a normalization method. Results: In this paper we introduce a rhythmicity measure and a bootstrap methodology to detect rhythmic genes in an oscillatory system. Although the proposed methodology can be used for any high-throughput gene expression data, in this paper we illustrate the proposed methodology using several publicly available circadian clock microarray gene-expression datasets. We demonstrate that the choice of normalization method has very little effect on the proposed methodology. Specifically, for any pair of normalization methods considered in this paper, the resulting values of the rhythmicity measure are highly correlated. Thus it suggests that the proposed measure is robust to the choice of a normalization method. Consequently, the rhythmicity of a gene is potentially not a mere artifact of the normalization method used. Lastly, as demonstrated in the paper, the proposed bootstrap methodology can also be used for simulating data for genes participating in an oscillatory system using a reference dataset. Availability: A user friendly code implemented in R language can be downloaded from http://www.eio.uva.es/~miguel/robustdetectionprocedure.html.

  18. Detection methods for irradiated food

    International Nuclear Information System (INIS)

    Stevenson, M.H.

    1993-01-01

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

  19. SU-F-I-43: A Software-Based Statistical Method to Compute Low Contrast Detectability in Computed Tomography Images

    Energy Technology Data Exchange (ETDEWEB)

    Chacko, M; Aldoohan, S [University of Oklahoma Health Sciences Center, Oklahoma City, OK (United States)

    2016-06-15

    Purpose: The low contrast detectability (LCD) of a CT scanner is its ability to detect and display faint lesions. The current approach to quantify LCD is achieved using vendor-specific methods and phantoms, typically by subjectively observing the smallest size object at a contrast level above phantom background. However, this approach does not yield clinically applicable values for LCD. The current study proposes a statistical LCD metric using software tools to not only to assess scanner performance, but also to quantify the key factors affecting LCD. This approach was developed using uniform QC phantoms, and its applicability was then extended under simulated clinical conditions. Methods: MATLAB software was developed to compute LCD using a uniform image of a QC phantom. For a given virtual object size, the software randomly samples the image within a selected area, and uses statistical analysis based on Student’s t-distribution to compute the LCD as the minimal Hounsfield Unit’s that can be distinguished from the background at the 95% confidence level. Its validity was assessed by comparison with the behavior of a known QC phantom under various scan protocols and a tissue-mimicking phantom. The contributions of beam quality and scattered radiation upon the computed LCD were quantified by using various external beam-hardening filters and phantom lengths. Results: As expected, the LCD was inversely related to object size under all scan conditions. The type of image reconstruction kernel filter and tissue/organ type strongly influenced the background noise characteristics and therefore, the computed LCD for the associated image. Conclusion: The proposed metric and its associated software tools are vendor-independent and can be used to analyze any LCD scanner performance. Furthermore, the method employed can be used in conjunction with the relationships established in this study between LCD and tissue type to extend these concepts to patients’ clinical CT

  20. Rapid detection of food-borne Salmonella contamination using IMBs-qPCR method based on pagC gene

    Directory of Open Access Journals (Sweden)

    Jiashun Wang

    Full Text Available Abstract Detection of Salmonella is very important to minimize the food safety risk. In this study, the recombinant PagC protein and PagC antibody were prepared and coupled with immunomagnetic beads (IMBs to capture Salmonella cells from pork and milk samples. And then the SYBR Green qualitative PCR was developed to detect the pathogenic Salmonella. The results showed that the PagC polyclonal antiserum is of good specificity and the capture rate of 0.1 mg IMBs for Salmonella tended to be stable at the range of 70-74% corresponding to the concentrations between 101 and 104 CFU/mL. The method developed demonstrated high specificity for the positive Salmonella samples when compared to non-specific DNA samples, such as Escherichia coli, Staphylococcus aureus, Yersinia enterocolitica, and Yersinia pseudotuberculosis. The limit of detection of this assay was 18 CFU/mL. Detection and quantitative enumeration of Salmonella in samples of pork or milk shows good recoveries of 54.34% and 52.07%. In conclusion, the polyclonal antibody of recombinant PagC protein is effective to capture Salmonella from detected samples. The developed pagC antibody IMBs-qPCR method showed efficiency, sensitivity and specificity for 30 Salmonella detection, enabling detection within 10 h, which is a promising rapid method to detect Salmonella in emergency.

  1. Development of a Flow Cytometry-Based Method for Rapid Detection of Escherichia coli and Shigella Spp. Using an Oligonucleotide Probe

    Science.gov (United States)

    Xue, Yong; Wilkes, Jon G.; Moskal, Ted J.; Williams, Anna J.; Cooper, Willie M.; Nayak, Rajesh; Rafii, Fatemeh; Buzatu, Dan A.

    2016-01-01

    Standard methods to detect Escherichia coli contamination in food use the polymerase chain reaction (PCR) and agar culture plates. These methods require multiple incubation steps and take a long time to results. An improved rapid flow-cytometry based detection method was developed, using a fluorescence-labeled oligonucleotide probe specifically binding a16S rRNA sequence. The method positively detected 51 E. coli isolates as well as 4 Shigella species. All 27 non-E. coli strains tested gave negative results. Comparison of the new genetic assay with a total plate count (TPC) assay and agar plate counting indicated similar sensitivity, agreement between cytometry cell and colony counts. This method can detect a small number of E.coli cells in the presence of large numbers of other bacteria. This method can be used for rapid, economical, and stable detection of E. coli and Shigella contamination in the food industry and other contexts. PMID:26913737

  2. Development of a Flow Cytometry-Based Method for Rapid Detection of Escherichia coli and Shigella Spp. Using an Oligonucleotide Probe.

    Directory of Open Access Journals (Sweden)

    Yong Xue

    Full Text Available Standard methods to detect Escherichia coli contamination in food use the polymerase chain reaction (PCR and agar culture plates. These methods require multiple incubation steps and take a long time to results. An improved rapid flow-cytometry based detection method was developed, using a fluorescence-labeled oligonucleotide probe specifically binding a16S rRNA sequence. The method positively detected 51 E. coli isolates as well as 4 Shigella species. All 27 non-E. coli strains tested gave negative results. Comparison of the new genetic assay with a total plate count (TPC assay and agar plate counting indicated similar sensitivity, agreement between cytometry cell and colony counts. This method can detect a small number of E.coli cells in the presence of large numbers of other bacteria. This method can be used for rapid, economical, and stable detection of E. coli and Shigella contamination in the food industry and other contexts.

  3. Classification methods to detect sleep apnea in adults based on respiratory and oximetry signals: a systematic review.

    Science.gov (United States)

    Uddin, M B; Chow, C M; Su, S W

    2018-03-26

    Sleep apnea (SA), a common sleep disorder, can significantly decrease the quality of life, and is closely associated with major health risks such as cardiovascular disease, sudden death, depression, and hypertension. The normal diagnostic process of SA using polysomnography is costly and time consuming. In addition, the accuracy of different classification methods to detect SA varies with the use of different physiological signals. If an effective, reliable, and accurate classification method is developed, then the diagnosis of SA and its associated treatment will be time-efficient and economical. This study aims to systematically review the literature and present an overview of classification methods to detect SA using respiratory and oximetry signals and address the automated detection approach. Sixty-two included studies revealed the application of single and multiple signals (respiratory and oximetry) for the diagnosis of SA. Both airflow and oxygen saturation signals alone were effective in detecting SA in the case of binary decision-making, whereas multiple signals were good for multi-class detection. In addition, some machine learning methods were superior to the other classification methods for SA detection using respiratory and oximetry signals. To deal with the respiratory and oximetry signals, a good choice of classification method as well as the consideration of associated factors would result in high accuracy in the detection of SA. An accurate classification method should provide a high detection rate with an automated (independent of human action) analysis of respiratory and oximetry signals. Future high-quality automated studies using large samples of data from multiple patient groups or record batches are recommended.

  4. Comparison of PCR-Based Diagnosis with Centrifuged-Based Enrichment Method for Detection of Borrelia Persica in Animal Blood Samples

    Directory of Open Access Journals (Sweden)

    SR Naddaf

    2011-06-01

    Full Text Available Background: The mainstay of diagnosis of relapsing fever (RF is demonstration of the spirochetes in Giemsa-stained thick blood smears, but during non fever periods the bacteria are very scanty and rarely detected in blood smears by mi­cros­copy. This study is aimed to evaluate the sensitivity of different methods developed for detection of low-grade spi­ro­chetemia. Methods: Animal blood samples with low degrees of spirochetemia were tested with two PCRs and a nested PCR tar­get­ing flaB, GlpQ, and rrs genes. Also, a centrifuged-based enrichment method and Giemsa staining were per­formed on blood samples with various degrees of spirochetemia. Results: The flaB-PCR and nested rrs-PCR turned positive with various degrees of spirochetemia including the blood samples that turned negative with dark-field microscopy. The GlpQ-PCR was positive as far as at least one spi­ro­chete was seen in 5-10 microscopic fields. The sensitivity of GlpQ-PCR increased when DNA from Buffy Coat Layer (BCL was used as template. The centrifuged-based enrichment method turned positive with as low concentra­tion as 50 bacteria/ml blood, while Giemsa thick staining detected bacteria with concentrations ≥ 25000 bacteria/ml. Conclusion: Centrifuged-based enrichment method appeared as much as 500-fold more sensitive than thick smears, which makes it even superior to some PCR assays. Due to simplicity and minimal laboratory requirements, this method can be considered a valuable tool for diagnosis of RF in rural health centers.

  5. Comparison of PCR-Based Diagnosis with Centrifuged-Based Enrichment Method for Detection of Borrelia persica in Animal Blood Samples

    Directory of Open Access Journals (Sweden)

    SR Naddaf

    2011-06-01

    Background: The mainstay of diagnosis of relapsing fever (RF is demonstration of the spirochetes in Giemsa-stained thick blood smears, but during non fever periods the bacteria are very scanty and rarely detected in blood smears by mi­cros­copy. This study is aimed to evaluate the sensitivity of different methods developed for detection of low-grade spi­ro­chetemia. Methods: Animal blood samples with low degrees of spirochetemia were tested with two PCRs and a nested PCR tar­get­ing flaB, GlpQ, and rrs genes. Also, a centrifuged-based enrichment method and Giemsa staining were per­formed on blood samples with various degrees of spirochetemia. Results: The flaB-PCR and nested rrs-PCR turned positive with various degrees of spirochetemia including the blood samples that turned negative with dark-field microscopy. The GlpQ-PCR was positive as far as at least one spi­ro­chete was seen in 5-10 microscopic fields. The sensitivity of GlpQ-PCR increased when DNA from Buffy Coat Layer (BCL was used as template. The centrifuged-based enrichment method turned positive with as low concentra­tion as 50 bacteria/ml blood, while Giemsa thick staining detected bacteria with concentrations ≥ 25000 bacteria/ml.  Conclusion: Centrifuged-based enrichment method appeared as much as 500-fold more sensitive than thick smears, which makes it even superior to some PCR assays. Due to simplicity and minimal laboratory requirements, this method can be considered a valuable tool for diagnosis of RF in rural health centers.  

  6. A multiplex PCR-based method for the detection and early identification of wood rotting fungi in standing trees.

    Science.gov (United States)

    Guglielmo, F; Bergemann, S E; Gonthier, P; Nicolotti, G; Garbelotto, M

    2007-11-01

    The goal of this research was the development of a PCR-based assay to identify important decay fungi from wood of hardwood tree species in northern temperate regions. Eleven taxon-specific primers were designed for PCR amplification of either nuclear or mitochondrial ribosomal DNA regions of Armillaria spp., Ganoderma spp., Hericium spp., Hypoxylon thouarsianum var. thouarsianum, Inonotus/Phellinus-group, Laetiporus spp., Perenniporia fraxinea, Pleurotus spp., Schizophyllum spp., Stereum spp. and Trametes spp. Multiplex PCR reactions were developed and optimized to detect fungal DNA and identify each taxon with a sensitivity of at least 1 pg of target DNA in the template. This assay correctly identified the agents of decay in 82% of tested wood samples. The development and optimization of multiplex PCRs allowed for reliable identification of wood rotting fungi directly from wood. Early detection of wood decay fungi is crucial for assessment of tree stability in urban landscapes. Furthermore, this method may prove useful for prediction of the severity and the evolution of decay in standing trees.

  7. A BAND SELECTION METHOD FOR SUB-PIXEL TARGET DETECTION IN HYPERSPECTRAL IMAGES BASED ON LABORATORY AND FIELD REFLECTANCE SPECTRAL COMPARISON

    Directory of Open Access Journals (Sweden)

    S. Sharifi hashjin

    2016-06-01

    Full Text Available In recent years, developing target detection algorithms has received growing interest in hyperspectral images. In comparison to the classification field, few studies have been done on dimension reduction or band selection for target detection in hyperspectral images. This study presents a simple method to remove bad bands from the images in a supervised manner for sub-pixel target detection. The proposed method is based on comparing field and laboratory spectra of the target of interest for detecting bad bands. For evaluation, the target detection blind test dataset is used in this study. Experimental results show that the proposed method can improve efficiency of the two well-known target detection methods, ACE and CEM.

  8. Advantages and Limitations of Androgen Receptor-Based Methods for Detecting Anabolic Androgenic Steroid Abuse as Performance Enhancing Drugs

    Science.gov (United States)

    Bailey, Kathy; Yazdi, Tahmineh; Masharani, Umesh; Tyrrell, Blake; Butch, Anthony; Schaufele, Fred

    2016-01-01

    Testosterone (T) and related androgens are performance enhancing drugs (PEDs) abused by some athletes to gain competitive advantage. To monitor unauthorized androgen abuse, doping control programs use mass spectrometry (MS) to detect androgens, synthetic anabolic-androgenic steroids (AASs) and their metabolites in an athlete’s urine. AASs of unknown composition will not be detected by these procedures. Since AASs achieve their anabolic effects by activating the Androgen Receptor (AR), cell-based bioassays that measure the effect of a urine sample on AR activity are under investigation as complementary, pan-androgen detection methods. We evaluated an AR BioAssay as a monitor for androgen activity in urine pre-treated with glucuronidase, which releases T from the inactive T-glucuronide that predominates in urine. AR BioAssay activity levels were expressed as ‘T-equivalent’ concentrations by comparison to a T dose response curve. The T-equivalent concentrations of androgens in the urine of hypogonadal participants supplemented with T (in whom all androgenic activity should arise from T) were quantitatively identical to the T measurements conducted by MS at the UCLA Olympic Analytical Laboratory (0.96 ± 0.22). All 17 AASs studied were active in the AR BioAssay; other steroids were inactive. 12 metabolites of 10 commonly abused AASs, which are used for MS monitoring of AAS doping because of their prolonged presence in urine, had reduced or no AR BioAssay activity. Thus, the AR BioAssay can accurately and inexpensively monitor T, but its ability to monitor urinary AASs will be limited to a period immediately following doping in which the active AASs remain intact. PMID:26998755

  9. Advantages and Limitations of Androgen Receptor-Based Methods for Detecting Anabolic Androgenic Steroid Abuse as Performance Enhancing Drugs.

    Science.gov (United States)

    Bailey, Kathy; Yazdi, Tahmineh; Masharani, Umesh; Tyrrell, Blake; Butch, Anthony; Schaufele, Fred

    2016-01-01

    Testosterone (T) and related androgens are performance enhancing drugs (PEDs) abused by some athletes to gain competitive advantage. To monitor unauthorized androgen abuse, doping control programs use mass spectrometry (MS) to detect androgens, synthetic anabolic-androgenic steroids (AASs) and their metabolites in an athlete's urine. AASs of unknown composition will not be detected by these procedures. Since AASs achieve their anabolic effects by activating the Androgen Receptor (AR), cell-based bioassays that measure the effect of a urine sample on AR activity are under investigation as complementary, pan-androgen detection methods. We evaluated an AR BioAssay as a monitor for androgen activity in urine pre-treated with glucuronidase, which releases T from the inactive T-glucuronide that predominates in urine. AR BioAssay activity levels were expressed as 'T-equivalent' concentrations by comparison to a T dose response curve. The T-equivalent concentrations of androgens in the urine of hypogonadal participants supplemented with T (in whom all androgenic activity should arise from T) were quantitatively identical to the T measurements conducted by MS at the UCLA Olympic Analytical Laboratory (0.96 ± 0.22). All 17 AASs studied were active in the AR BioAssay; other steroids were inactive. 12 metabolites of 10 commonly abused AASs, which are used for MS monitoring of AAS doping because of their prolonged presence in urine, had reduced or no AR BioAssay activity. Thus, the AR BioAssay can accurately and inexpensively monitor T, but its ability to monitor urinary AASs will be limited to a period immediately following doping in which the active AASs remain intact.

  10. Cellular phone-based image acquisition and quantitative ratiometric method for detecting cocaine and benzoylecgonine for biological and forensic applications.

    Science.gov (United States)

    Cadle, Brian A; Rasmus, Kristin C; Varela, Juan A; Leverich, Leah S; O'Neill, Casey E; Bachtell, Ryan K; Cooper, Donald C

    2010-01-01

    Here we describe the first report of using low-cost cellular or web-based digital cameras to image and quantify standardized rapid immunoassay strips as a new point-of-care diagnostic and forensics tool with health applications. Quantitative ratiometric pixel density analysis (QRPDA) is an automated method requiring end-users to utilize inexpensive (∼ $1 USD/each) immunotest strips, a commonly available web or mobile phone camera or scanner, and internet or cellular service. A model is described whereby a central computer server and freely available IMAGEJ image analysis software records and analyzes the incoming image data with time-stamp and geo-tag information and performs the QRPDA using custom JAVA based macros (http://www.neurocloud.org). To demonstrate QRPDA we developed a standardized method using rapid immunotest strips directed against cocaine and its major metabolite, benzoylecgonine. Images from standardized samples were acquired using several devices, including a mobile phone camera, web cam, and scanner. We performed image analysis of three brands of commercially available dye-conjugated anti-cocaine/benzoylecgonine (COC/BE) antibody test strips in response to three different series of cocaine concentrations ranging from 0.1 to 300 ng/ml and BE concentrations ranging from 0.003 to 0.1 ng/ml. This data was then used to create standard curves to allow quantification of COC/BE in biological samples. Across all devices, QRPDA quantification of COC and BE proved to be a sensitive, economical, and faster alternative to more costly methods, such as gas chromatography-mass spectrometry, tandem mass spectrometry, or high pressure liquid chromatography. The limit of detection was determined to be between 0.1 and 5 ng/ml. To simulate conditions in the field, QRPDA was found to be robust under a variety of image acquisition and testing conditions that varied temperature, lighting, resolution, magnification and concentrations of biological fluid in a sample. To

  11. Cellular Phone-Based Image Acquisition and Quantitative Ratiometric Method for Detecting Cocaine and Benzoylecgonine for Biological and Forensic Applications

    Directory of Open Access Journals (Sweden)

    Brian A. Cadle

    2010-01-01

    Full Text Available Here we describe the first report of using low-cost cellular or web-based digital cameras to image and quantify standardized rapid immunoassay strips as a new point-of-care diagnostic and forensics tool with health applications. Quantitative ratiometric pixel density analysis (QRPDA is an automated method requiring end-users to utilize inexpensive (~ $1 USD/each immunotest strips, a commonly available web or mobile phone camera or scanner, and internet or cellular service. A model is described whereby a central computer server and freely available IMAGEJ image analysis software records and analyzes the incoming image data with time-stamp and geo-tag information and performs the QRPDA using custom JAVA based macros ( http://www.neurocloud.org . To demonstrate QRPDA we developed a standardized method using rapid immunotest strips directed against cocaine and its major metabolite, benzoylecgonine. Images from standardized samples were acquired using several devices, including a mobile phone camera, web cam, and scanner. We performed image analysis of three brands of commercially available dye-conjugated anti-cocaine/benzoylecgonine (COC/BE antibody test strips in response to three different series of cocaine concentrations ranging from 0.1 to 300 ng/ml and BE concentrations ranging from 0.003 to 0.1 ng/ml. This data was then used to create standard curves to allow quantification of COC/BE in biological samples. Across all devices, QRPDA quantification of COC and BE proved to be a sensitive, economical, and faster alternative to more costly methods, such as gas chromatography-mass spectrometry, tandem mass spectrometry, or high pressure liquid chromatography. The limit of detection was determined to be between 0.1 and 5 ng/ml. To simulate conditions in the field, QRPDA was found to be robust under a variety of image acquisition and testing conditions that varied temperature, lighting, resolution, magnification and concentrations of biological fluid

  12. A Small Leak Detection Method Based on VMD Adaptive De-Noising and Ambiguity Correlation Classification Intended for Natural Gas Pipelines.

    Science.gov (United States)

    Xiao, Qiyang; Li, Jian; Bai, Zhiliang; Sun, Jiedi; Zhou, Nan; Zeng, Zhoumo

    2016-12-13

    In this study, a small leak detection method based on variational mode decomposition (VMD) and ambiguity correlation classification (ACC) is proposed. The signals acquired from sensors were decomposed using the VMD, and numerous components were obtained. According to the probability density function (PDF), an adaptive de-noising algorithm based on VMD is proposed for noise component processing and de-noised components reconstruction. Furthermore, the ambiguity function image was employed for analysis of the reconstructed signals. Based on the correlation coefficient, ACC is proposed to detect the small leak of pipeline. The analysis of pipeline leakage signals, using 1 mm and 2 mm leaks, has shown that proposed detection method can detect a small leak accurately and effectively. Moreover, the experimental results have shown that the proposed method achieved better performances than support vector machine (SVM) and back propagation neural network (BP) methods.

  13. A Small Leak Detection Method Based on VMD Adaptive De-Noising and Ambiguity Correlation Classification Intended for Natural Gas Pipelines

    Directory of Open Access Journals (Sweden)

    Qiyang Xiao

    2016-12-01

    Full Text Available In this study, a small leak detection method based on variational mode decomposition (VMD and ambiguity correlation classification (ACC is proposed. The signals acquired from sensors were decomposed using the VMD, and numerous components were obtained. According to the probability density function (PDF, an adaptive de-noising algorithm based on VMD is proposed for noise component processing and de-noised components reconstruction. Furthermore, the ambiguity function image was employed for analysis of the reconstructed signals. Based on the correlation coefficient, ACC is proposed to detect the small leak of pipeline. The analysis of pipeline leakage signals, using 1 mm and 2 mm leaks, has shown that proposed detection method can detect a small leak accurately and effectively. Moreover, the experimental results have shown that the proposed method achieved better performances than support vector machine (SVM and back propagation neural network (BP methods.

  14. A field based detection method for Rose rosette virus using isothermal probe-based Reverse transcription-recombinase polymerase amplification assay.

    Science.gov (United States)

    Babu, Binoy; Washburn, Brian K; Ertek, Tülin Sarigül; Miller, Steven H; Riddle, Charles B; Knox, Gary W; Ochoa-Corona, Francisco M; Olson, Jennifer; Katırcıoğlu, Yakup Zekai; Paret, Mathews L

    2017-09-01

    Rose rosette disease, caused by Rose rosette virus (RRV; genus Emaravirus) is a major threat to the rose industry in the U.S. The only strategy currently available for disease management is early detection and eradication of the infected plants, thereby limiting its potential spread. Current RT-PCR based diagnostic methods for RRV are time consuming and are inconsistent in detecting the virus from symptomatic plants. Real-time RT-qPCR assay is highly sensitive for detection of RRV, but it is expensive and requires well-equipped laboratories. Both the RT-PCR and RT-qPCR cannot be used in a field-based testing for RRV. Hence a novel probe based, isothermal reverse transcription-recombinase polymerase amplification (RT-exoRPA) assay, using primer/probe designed based on the nucleocapsid gene of the RRV has been developed. The assay is highly specific and did not give a positive reaction to other viruses infecting roses belonging to both inclusive and exclusive genus. Dilution assays using the in vitro transcript showed that the primer/probe set is highly sensitive, with a detection limit of 1 fg/μl. In addition, a rapid technique for the extraction of viral RNA (rose varieties, collected from different states in the U.S. The entire process, including the extraction can be completed in 25min, with less sophisticated equipments. The developed assay can be used with high efficiency in large scale field testing for rapid detection of RRV in commercial nurseries and landscapes. Copyright © 2017 Elsevier B.V. All rights reserved.

  15. Self-Tuning Threshold Method for Real-Time Gait Phase Detection Based on Ground Contact Forces Using FSRs

    Directory of Open Access Journals (Sweden)

    Jing Tang

    2018-02-01

    Full Text Available This paper presents a novel methodology for detecting the gait phase of human walking on level ground. The previous threshold method (TM sets a threshold to divide the ground contact forces (GCFs into on-ground and off-ground states. However, the previous methods for gait phase detection demonstrate no adaptability to different people and different walking speeds. Therefore, this paper presents a self-tuning triple threshold algorithm (STTTA that calculates adjustable thresholds to adapt to human walking. Two force sensitive resistors (FSRs were placed on the ball and heel to measure GCFs. Three thresholds (i.e., high-threshold, middle-threshold andlow-threshold were used to search out the maximum and minimum GCFs for the self-adjustments of thresholds. The high-threshold was the main threshold used to divide the GCFs into on-ground and off-ground statuses. Then, the gait phases were obtained through the gait phase detection algorithm (GPDA, which provides the rules that determine calculations for STTTA. Finally, the STTTA reliability is determined by comparing the results between STTTA and Mariani method referenced as the timing analysis module (TAM and Lopez–Meyer methods. Experimental results show that the proposed method can be used to detect gait phases in real time and obtain high reliability when compared with the previous methods in the literature. In addition, the proposed method exhibits strong adaptability to different wearers walking at different walking speeds.

  16. In operando Detection of Three-Way Catalyst Aging by a Microwave-Based Method: Initial Studies

    Directory of Open Access Journals (Sweden)

    Gregor Beulertz

    2015-07-01

    Full Text Available Initial studies on aging detection of three way catalysts with a microwave cavity perturbation method were conducted. Two physico-chemical effects correlate with the aging state. At high temperatures, the resonance frequencies for oxidized catalysts (λ = 1.02 are not influenced by aging, but are significantly affected by aging in the reduced case (λ = 0.98. The catalyst aging state can therefore potentially be inferred from the resonance frequency differences between reduced and oxidized states or from the resonance frequency amplitudes during lambda oscillations. Secondly, adsorbed water at low temperatures strongly affects the resonance frequencies. Light-off experiment studies showed that the resonance frequency depends on the aging state at temperatures below the oxygen storage light-off. These differences were attributed to different water sorption capabilities of differently aged samples due to a surface area decrease with proceeding aging. In addition to the aging state, the water content in the feed gas and the temperature affect the amount of adsorbed water, leading to different integral electrical material properties of the catalyst and changing the resonance properties of the catalyst-filled canning. The classical aging-related properties of the catalyst (oxygen storage capacity, oxygen storage light-off, surface area, agreed very well with data obtained by the microwave-based method.

  17. Optimization of a Real Time PCR based method for the detection of Listeria monocytogenes in pork meat.

    Science.gov (United States)

    Gattuso, Antonietta; Gianfranceschi, Monica Virginia; Sonnessa, Michele; Delibato, Elisabetta; Marchesan, Massimo; Hernandez, Marta; De Medici, Dario; Rodriguez-Lazaro, David

    2014-08-01

    The aim of this study was to optimize a Real-Time PCR protocol for a rapid detection of Listeria monocytogenes in pork meat, using reduced volumes of primary selective enrichment broth and times of incubation to decrease the cost and time for analysis. Forty-five samples of pork meat were artificially contaminated with two different levels of L. monocytogenes (1-10 CFU per sample and 10-100 CFU per sample), homogenized in three different volumes of Half Fraser Broth (1:3; 1:5 and 1:10) and incubated at 30°C ± 1°C for 5h, 8h and 24h. The detection was conducted in parallel by Real-Time PCR and the ISO standard 11290-1 methods. L. monocytogenes was detected in all the samples after 24h by Real-Time PCR method, also using reduced volumes of Half Fraser Broth. This represents a clear advantage as the time to final detection and the inherent costs were significantly reduced compared to the ISO reference method. All samples artificially contaminated were correctly detected also after 8 of incubation at 30°C ± 1°C in Half Fraser Broth and 24h in Fraser Broth at 37°C ± 1°C using cultural method. Copyright © 2014 Elsevier B.V. All rights reserved.

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

    International Nuclear Information System (INIS)

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

    2014-01-01

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

  19. A comparison of two sleep spindle detection methods based on all night averages: individually adjusted versus fixed frequencies

    Directory of Open Access Journals (Sweden)

    Péter Przemyslaw Ujma

    2015-02-01

    Full Text Available Sleep spindles are frequently studied for their relationship with state and trait cognitive variables, and they are thought to play an important role in sleep-related memory consolidation. Due to their frequent occurrence in NREM sleep, the detection of sleep spindles is only feasible using automatic algorithms, of which a large number is available. We compared subject averages of the spindle parameters computed by a fixed frequency (11-13 Hz for slow spindles, 13-15 Hz for fast spindles automatic detection algorithm and the individual adjustment method (IAM, which uses individual frequency bands for sleep spindle detection. Fast spindle duration and amplitude are strongly correlated in the two algorithms, but there is little overlap in fast spindle density and slow spindle parameters in general. The agreement between fixed and manually determined sleep spindle frequencies is limited, especially in case of slow spindles. This is the most likely reason for the poor agreement between the two detection methods in case of slow spindle parameters. Our results suggest that while various algorithms may reliably detect fast spindles, a more sophisticated algorithm primed to individual spindle frequencies is necessary for the detection of slow spindles as well as individual variations in the number of spindles in general.

  20. Comparison of culture-based, vital stain and PMA-qPCR methods for the quantitative detection of viable hookworm ova.

    Science.gov (United States)

    Gyawali, P; Sidhu, J P S; Ahmed, W; Jagals, P; Toze, S

    2017-06-01

    Accurate quantitative measurement of viable hookworm ova from environmental samples is the key to controlling hookworm re-infections in the endemic regions. In this study, the accuracy of three quantitative detection methods [culture-based, vital stain and propidium monoazide-quantitative polymerase chain reaction (PMA-qPCR)] was evaluated by enumerating 1,000 ± 50 Ancylostoma caninum ova in the laboratory. The culture-based method was able to quantify an average of 397 ± 59 viable hookworm ova. Similarly, vital stain and PMA-qPCR methods quantified 644 ± 87 and 587 ± 91 viable ova, respectively. The numbers of viable ova estimated by the culture-based method were significantly (P methods. Therefore, both PMA-qPCR and vital stain methods appear to be suitable for the quantitative detection of viable hookworm ova. However, PMA-qPCR would be preferable over the vital stain method in scenarios where ova speciation is needed.

  1. A Videotape-Based Training Method for Improving the Detection of Depression in Residents of Long-Term Care Facilities

    Science.gov (United States)

    Wood, Stacey; Cummings, Jeffrey L.; Schnelle, Betha; Stephens, Mary

    2002-01-01

    Purpose: This article reviews the effectiveness of a new training program for improving nursing staffs' detection of depression within long-term care facilities. The course was designed to increase recognition of the Minimal Data Set (MDS) Mood Trigger items, to be brief, and to rely on images rather than didactics. Design and Methods: This study…

  2. Measurement agreement between a newly developed sensing insole and traditional laboratory-based method for footstrike pattern detection in runners.

    Directory of Open Access Journals (Sweden)

    Roy T H Cheung

    Full Text Available This study introduced a novel but simple method to continuously measure footstrike patterns in runners using inexpensive force sensors. Two force sensing resistors were firmly affixed at the heel and second toe of both insoles to collect the time signal of foot contact. A total of 109 healthy young adults (42 males and 67 females were recruited in this study. They ran on an instrumented treadmill at 0°, +10°, and -10° inclinations and attempted rearfoot, midfoot, and forefoot landings using real time visual biofeedback. Intra-step strike index and onset time difference between two force sensors were measured and analyzed with univariate linear regression. We analyzed 25,655 footfalls and found that onset time difference between two sensors explained 80-84% of variation in the prediction model of strike index (R-squared = 0.799-0.836, p<0.001. However, the time windows to detect footstrike patterns on different surface inclinations were not consistent. These findings may allow laboratory-based gait retraining to be implemented in natural running environments to aid in both injury prevention and performance enhancement.

  3. An Atmosphere-based Method for Detection and Quantification of Methane Emisions from Natural Gas Infrastructure in an Urban Environment

    Science.gov (United States)

    McKain, K.; Down, A.; Raciti, S. M.; Budney, J.; Hutyra, L.; Floerchinger, C. R.; Herndon, S. C.; Nehrkorn, T.; Zahniser, M. S.; Sargent, M. R.; Jackson, R. B.; Phillips, N. G.; Wofsy, S. C.

    2015-12-01

    Methane emissions from the natural gas supply-chain are highly uncertain and can vary widely among components and processes. We present an atmosphere-based method for detecting and quantifying the area and time-averaged surface flux of methane from natural gas infrastructure, and its application to the case-study of Boston, Massachusetts. Continuous measurements of atmospheric methane at a network of stations, inside and outside the city, are used to quantify the atmospheric methane gradient due to emissions from the urban area. Simultaneous observations of atmospheric ethane, and data on the ethane and methane content of the pipeline gas flowing through the region, are used to trace the atmospheric methane enhancement to the natural gas source. An atmospheric transport model is used to quantitatively relate the observed methane enhancement to a surface flux from the whole urban region. We find that methane emissions from natural gas in the urban region over one year was equal to 2.7 ± 0.6 % of the natural gas delivered to the region. Our findings for Boston suggest natural-gas-consuming regions, generally, may be larger sources of methane to the atmosphere than is current estimated and represent areas of significant resource loss.

  4. Measurement agreement between a newly developed sensing insole and traditional laboratory-based method for footstrike pattern detection in runners

    Science.gov (United States)

    Cheung, Roy T. H.; An, Winko W.; Au, Ivan P. H.; Zhang, Janet H.; Chan, Zoe Y. S.; Man, Alfred; Lau, Fannie O. Y.; Lam, Melody K. Y.; Lau, K. K.; Leung, C. Y.; Tsang, N. W.; Sze, Louis K. Y.; Lam, Gilbert W. K.

    2017-01-01

    This study introduced a novel but simple method to continuously measure footstrike patterns in runners using inexpensive force sensors. Two force sensing resistors were firmly affixed at the heel and second toe of both insoles to collect the time signal of foot contact. A total of 109 healthy young adults (42 males and 67 females) were recruited in this study. They ran on an instrumented treadmill at 0°, +10°, and -10° inclinations and attempted rearfoot, midfoot, and forefoot landings using real time visual biofeedback. Intra-step strike index and onset time difference between two force sensors were measured and analyzed with univariate linear regression. We analyzed 25,655 footfalls and found that onset time difference between two sensors explained 80–84% of variation in the prediction model of strike index (R-squared = 0.799–0.836, p<0.001). However, the time windows to detect footstrike patterns on different surface inclinations were not consistent. These findings may allow laboratory-based gait retraining to be implemented in natural running environments to aid in both injury prevention and performance enhancement. PMID:28599003

  5. Development of a general method for detection and quantification of the P35S promoter based on assessment of existing methods

    Science.gov (United States)

    Wu, Yuhua; Wang, Yulei; Li, Jun; Li, Wei; Zhang, Li; Li, Yunjing; Li, Xiaofei; Li, Jun; Zhu, Li; Wu, Gang

    2014-01-01

    The Cauliflower mosaic virus (CaMV) 35S promoter (P35S) is a commonly used target for detection of genetically modified organisms (GMOs). There are currently 24 reported detection methods, targeting different regions of the P35S promoter. Initial assessment revealed that due to the absence of primer binding sites in the P35S sequence, 19 of the 24 reported methods failed to detect P35S in MON88913 cotton, and the other two methods could only be applied to certain GMOs. The rest three reported methods were not suitable for measurement of P35S in some testing events, because SNPs in binding sites of the primer/probe would result in abnormal amplification plots and poor linear regression parameters. In this study, we discovered a conserved region in the P35S sequence through sequencing of P35S promoters from multiple transgenic events, and developed new qualitative and quantitative detection systems targeting this conserved region. The qualitative PCR could detect the P35S promoter in 23 unique GMO events with high specificity and sensitivity. The quantitative method was suitable for measurement of P35S promoter, exhibiting good agreement between the amount of template and Ct values for each testing event. This study provides a general P35S screening method, with greater coverage than existing methods. PMID:25483893

  6. Adjunct methods for caries detection

    DEFF Research Database (Denmark)

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

    2012-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Ryan G. Howell

    2017-03-01

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

  8. Detection of Mycobacterium avium subsp. paratuberculosis from cattle and buffaloes in Egypt using traditional culture, serological and molecular based methods

    Directory of Open Access Journals (Sweden)

    G. S. Abdellrazeq

    2014-08-01

    Full Text Available Background: Johne's disease (JD caused by Mycobacterium avium subsp. paratuberculosis (MAP represents a real threat to the agriculture and dairy food industries and believed to be a potential public health problem. Signs of infection in ruminant include weight loss, diarrhea, decreased milk production, and eventually death. The definition of an infected animal based either on the presence of anti-MAP antibodies, or positive bacterial culture. No treatment for the disease exists and controlling the disease is difficult due to its long latent period. JD is a worldwide problem and multiple studies in many countries have been carried out to determine the prevalence of MAP infections. Although some primary non intensive studies confirm presence of JD in Egypt, the disease is currently neglected by the official Egyptian veterinary agencies. There is no official data, no national control program, and no used vaccine. Aim: This study aimed to evaluate three conventional diagnostic methods for MAP under the Egyptian circumstances with a general aim to determine the appropriate strategy to develop a JD control program. These methods were pooled fecal culture, humoral response and insertion sequence IS900 targets polymerase chain reaction (IS900 PCR. Materials and Methods: Fecal and serum samples (500 each were collected from Holstein-Friesian cattle and buffaloes housed in five Egyptian governorates. Fecal samples were examined for MAP on the basis of a strategic pooling procedure and performed on Herrold's Egg Yolk Agar Medium (HEYM. Smears were prepared from developed colonies and stained using a Ziehl-Neelsen (ZN technique. The identity of developed colonies was further confirmed by PCR analysis of IS900 sequence. Sera from both culture-positive and culture-negative animals were evaluated individually for humoral response. Results: Out of 50 pooled specimens, 34 (68% fecal cultures were positive for MAP. Serum positive samples of culture

  9. A robust object-based shadow detection method for cloud-free high resolution satellite images over urban areas and water bodies

    Science.gov (United States)

    Tatar, Nurollah; Saadatseresht, Mohammad; Arefi, Hossein; Hadavand, Ahmad

    2018-06-01

    Unwanted contrast in high resolution satellite images such as shadow areas directly affects the result of further processing in urban remote sensing images. Detecting and finding the precise position of shadows is critical in different remote sensing processing chains such as change detection, image classification and digital elevation model generation from stereo images. The spectral similarity between shadow areas, water bodies, and some dark asphalt roads makes the development of robust shadow detection algorithms challenging. In addition, most of the existing methods work on pixel-level and neglect the contextual information contained in neighboring pixels. In this paper, a new object-based shadow detection framework is introduced. In the proposed method a pixel-level shadow mask is built by extending established thresholding methods with a new C4 index which enables to solve the ambiguity of shadow and water bodies. Then the pixel-based results are further processed in an object-based majority analysis to detect the final shadow objects. Four different high resolution satellite images are used to validate this new approach. The result shows the superiority of the proposed method over some state-of-the-art shadow detection method with an average of 96% in F-measure.

  10. Integration of Microchip Electrophoresis with Electrochemical Detection Using an Epoxy-Based Molding Method to Embed Multiple Electrode Materials

    Science.gov (United States)

    Johnson, Alicia S.; Selimovic, Asmira; Martin, R. Scott

    2012-01-01

    This paper describes the use of epoxy-encapsulated electrodes to integrate microchip-based electrophoresis with electrochemical detection. Devices with various electrode combinations can easily be developed. This includes a palladium decoupler with a downstream working electrode material of either gold, mercury/gold, platinum, glassy carbon, or a carbon fiber bundle. Additional device components such as the platinum wires for the electrophoresis separation and the counter electrode for detection can also be integrated into the epoxy base. The effect of the decoupler configuration was studied in terms of the separation performance, detector noise, and the ability to analyze samples of a high ionic strength. The ability of both glassy carbon and carbon fiber bundle electrodes to analyze a complex mixture was demonstrated. It was also shown that a PDMS-based valving microchip can be used along with the epoxy embedded electrodes to integrate microdialysis sampling with microchip electrophoresis and electrochemical detection, with the microdialysis tubing also being embedded in the epoxy substrate. This approach enables one to vary the detection electrode material as desired in a manner where the electrodes can be polished and modified in a similar fashion to electrochemical flow cells used in liquid chromatography. PMID:22038707

  11. GMDD: a database of GMO detection methods.

    Science.gov (United States)

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

    2008-06-04

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

  12. Novel Detection Method for Consecutive DC Commutation Failure Based on Daubechies Wavelet with 2nd-Order Vanishing Moments

    Directory of Open Access Journals (Sweden)

    Tao Lin

    2018-01-01

    Full Text Available Accurate detection and effective control strategy of commutation failure (CF of high voltage direct current (HVDC are of great significance for keeping the safe and stable operations of the hybrid power grid. At first, a novel detection method for consecutive CF is proposed. Concretely, the 2nd and higher orders’ derivative values of direct current are summarized as the core to judge CF by analyzing the physical characteristics of the direct current waveform of the converter station in CF. Then, the Daubechies wavelet coefficient that can represent the 2nd and higher order derivative values of direct current is derived. Once the wavelet coefficients of the sampling points are detected to exceed the threshold, the occurrence of CF is confirmed. Furthermore, by instantly increasing advanced firing angle β in the inverter side, an additional emergency control strategy to prevent subsequent CF is proposed. Eventually, with simulations of the benchmark model, the effectiveness and superiorities of the proposed detection method and additional control strategy in accuracy and rapidity are verified.

  13. Rate based failure detection

    Science.gov (United States)

    Johnson, Brett Emery Trabun; Gamage, Thoshitha Thanushka; Bakken, David Edward

    2018-01-02

    This disclosure describes, in part, a system management component and failure detection component for use in a power grid data network to identify anomalies within the network and systematically adjust the quality of service of data published by publishers and subscribed to by subscribers within the network. In one implementation, subscribers may identify a desired data rate, a minimum acceptable data rate, desired latency, minimum acceptable latency and a priority for each subscription. The failure detection component may identify an anomaly within the network and a source of the anomaly. Based on the identified anomaly, data rates and or data paths may be adjusted in real-time to ensure that the power grid data network does not become overloaded and/or fail.

  14. Method of detecting failed fuels

    International Nuclear Information System (INIS)

    Ishizaki, Hideaki; Suzumura, Takeshi.

    1982-01-01

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

  15. A robust physiology-based source separation method for QRS detection in low amplitude fetal ECG recordings

    International Nuclear Information System (INIS)

    Vullings, R; Bergmans, J W M; Peters, C H L; Hermans, M J M; Wijn, P F F; Oei, S G

    2010-01-01

    The use of the non-invasively obtained fetal electrocardiogram (ECG) in fetal monitoring is complicated by the low signal-to-noise ratio (SNR) of ECG signals. Even after removal of the predominant interference (i.e. the maternal ECG), the SNR is generally too low for medical diagnostics, and hence additional signal processing is still required. To this end, several methods for exploiting the spatial correlation of multi-channel fetal ECG recordings from the maternal abdomen have been proposed in the literature, of which principal component analysis (PCA) and independent component analysis (ICA) are the most prominent. Both PCA and ICA, however, suffer from the drawback that they are blind source separation (BSS) techniques and as such suboptimum in that they do not consider a priori knowledge on the abdominal electrode configuration and fetal heart activity. In this paper we propose a source separation technique that is based on the physiology of the fetal heart and on the knowledge of the electrode configuration. This technique operates by calculating the spatial fetal vectorcardiogram (VCG) and approximating the VCG for several overlayed heartbeats by an ellipse. By subsequently projecting the VCG onto the long axis of this ellipse, a source signal of the fetal ECG can be obtained. To evaluate the developed technique, its performance is compared to that of both PCA and ICA and to that of augmented versions of these techniques (aPCA and aICA; PCA and ICA applied on preprocessed signals) in generating a fetal ECG source signal with enhanced SNR that can be used to detect fetal QRS complexes. The evaluation shows that the developed source separation technique performs slightly better than aPCA and aICA and outperforms PCA and ICA and has the main advantage that, with respect to aPCA/PCA and aICA/ICA, it performs more robustly. This advantage renders it favorable for employment in automated, real-time fetal monitoring applications

  16. Study of material properties important for an optical property modulation-based radiation detection method for positron emission tomography.

    Science.gov (United States)

    Tao, Li; Daghighian, Henry M; Levin, Craig S

    2017-01-01

    We compare the performance of two detector materials, cadmium telluride (CdTe) and bismuth silicon oxide (BSO), for optical property modulation-based radiation detection method for positron emission tomography (PET), which is a potential new direction to dramatically improve the annihilation photon pair coincidence time resolution. We have shown that the induced current flow in the detector crystal resulting from ionizing radiation determines the strength of optical modulation signal. A larger resistivity is favorable for reducing the dark current (noise) in the detector crystal, and thus the higher resistivity BSO crystal has a lower (50% lower on average) noise level than CdTe. The CdTe and BSO crystals can achieve the same sensitivity under laser diode illumination at the same crystal bias voltage condition while the BSO crystal is not as sensitive to 511-keV photons as the CdTe crystal under the same crystal bias voltage. The amplitude of the modulation signal induced by 511-keV photons in BSO crystal is around 30% of that induced in CdTe crystal under the same bias condition. In addition, we have found that the optical modulation strength increases linearly with crystal bias voltage before saturation. The modulation signal with CdTe tends to saturate at bias voltages higher than 1500 V due to its lower resistivity (thus larger dark current) while the modulation signal strength with BSO still increases after 3500 V. Further increasing the bias voltage for BSO could potentially further enhance the modulation strength and thus, the sensitivity.

  17. Detection methods of irradiated foodstuffs

    Energy Technology Data Exchange (ETDEWEB)

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

    2005-07-01

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

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

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

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

  19. Detecting generalized synchronization of chaotic dynamical systems. A kernel-based method and choice of its parameter

    International Nuclear Information System (INIS)

    Suetani, Hiromichi; Iba, Yukito; Aihara, Kazuyuki

    2006-01-01

    An approach based on the kernel methods for capturing the nonlinear interdependence between two signals is introduced. It is demonstrated that the proposed approach is useful for characterizing generalized synchronization with a successful simple example. An attempt to choose an optimal kernel parameter based on cross validation is also discussed. (author)

  20. Comparative Evaluation of Veriflow® Salmonella Species to USDA and FDA Culture-Based Methods for the Detection of Salmonella spp. in Food and Environmental Samples.

    Science.gov (United States)

    Puri, Amrita; Joelsson, Adam C; Terkhorn, Shawn P; Brown, Ashley S; Gaudioso, Zara E; Siciliano, Nicholas A

    2017-09-01

    Veriflow® Salmonella species (Veriflow SS) is a molecular-based assay for the presumptive detection of Salmonella spp. from environmental surfaces (stainless steel, sealed concrete, plastic, and ceramic tile), dairy (2% milk), raw meat (20% fat ground beef), chicken carcasses, and ready-to-eat (RTE) food (hot dogs). The assay utilizes a PCR detection method coupled with a rapid, visual, flow-based assay that develops in 3 min post-PCR amplification and requires only an 18 h enrichment for maximum sensitivity. The Veriflow SS system eliminates the need for sample purification, gel electrophoresis, or fluorophore-based detection of target amplification and does not require complex data analysis. This Performance Tested MethodSM validation study demonstrated the ability of the Veriflow SS method to detect low levels of artificially inoculated or naturally occurring Salmonella spp. in eight distinct environmental and food matrixes. In each reference comparison study, probability of detection analysis indicated that there was no significant difference between the Veriflow SS method and the U.S. Department of Agriculture Food Safety and Inspection Service Microbiology Laboratory Guidebook Chapter 4.06 and the U.S. Food and Drug Administration Bacteriological Analytical Manual Chapter 5 reference methods. A total of 104 Salmonella strains were detected in the inclusivity study, and 35 nonspecific organisms went undetected in the exclusivity study. The study results show that the Veriflow SS method is a sensitive, selective, and robust assay for the presumptive detection of Salmonella spp. sampled from environmental surfaces (stainless steel, sealed concrete, plastic, and ceramic tile), dairy (2% milk), raw meat (20% fat ground beef), chicken carcasses, and RTE food (hot dogs).

  1. Method of detecting irradiated pepper

    International Nuclear Information System (INIS)

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

    1989-01-01

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

  2. Study of the analytical method based on charged particle excitation of elements and detection on the characteristic X-rays

    International Nuclear Information System (INIS)

    Poncet, Maryse; Engelmann, Charles

    1975-01-01

    Preliminary results obtained by bombarding thick or thin targets with protons of energies below 1.5 MeV are presented. In the former case, curves representing X-ray emission versus proton energy (between 0.4 and 1.4MeV) were determined for 12 elements (Al, Ti, V, Fe, Ni, Cu, Nb, Ag, Sn, W, Au, Pb). From these curves the variation in detection sensitivity with atomic number for a given energy was derived. For some elements (Cu, Ag, Sn, Pb), deposited in thin layers on a aluminium substrate, the X-ray emission was studied as a function of thickness at constant energy. The results show that the method may be used to determine elements of atomic number near 30, in thin layers at least 200μg.cm -2 thick, with a detection limit which could reach a few 10 -3 μg.cm -2 [fr

  3. Development of a Premature Stop Codon-detection method based on a bacterial two-hybrid system

    Directory of Open Access Journals (Sweden)

    Mayorga Luis S

    2006-09-01

    Full Text Available Abstract Background The detection of Premature Stop Codons (PSCs in human genes is very useful for the genetic diagnosis of different hereditary cancers, e.g. Familial Breast Cancer and Hereditary Non-Polyposis Colorectal Cancer (HNPCC. The products of these PSCs are truncated proteins, detectable in vitro by the Protein Truncation Test and in vivo by using the living translation machinery of yeast or bacteria. These living strategies are based on the construction of recombinant plasmids where the human sequence of interest is inserted upstream of a reporter gene. Although simple, these assays have their limitations. The yeast system requires extensive work to enhance its specificity, and the bacterial systems yield many false results due to translation re-initiation events occurring post PSCs. Our aim was to design a recombinant plasmid useful for detecting PSCs in human genes and resistant to bacterial translation re-initiation interferences. Results A functional recombinant plasmid (pREAL was designed based on a bacterial two-hybrid system. In our design, the in vivo translation of fused fragments of the Bordetella pertussis adenylate cyclase triggers the production of cAMP giving rise to a selectable bacterial phenotype. When a gene of interest is inserted between the two fragments, any PSC inhibits the enzymatic activity of the product, and translation re-initiation events post-PSC yield separated inactive fragments. We demonstrated that the system can accurately detect PSCs in human genes by inserting mutated fragments of the brca1 and msh2 gene. Western Blot assays revealed translation re-initiation events in all the tested colonies, implying that a simpler plasmid would not be resistant to this source of false negative results. The application of the system to a HNPCC family with a nonsense mutation in the msh2 gene correctly diagnosed wild type homozygous and heterozygous patients. Conclusion The developed pREAL is applicable to the

  4. 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.

  5. Semi-supervised spectral algorithms for community detection in complex networks based on equivalence of clustering methods

    Science.gov (United States)

    Ma, Xiaoke; Wang, Bingbo; Yu, Liang

    2018-01-01

    Community detection is fundamental for revealing the structure-functionality relationship in complex networks, which involves two issues-the quantitative function for community as well as algorithms to discover communities. Despite significant research on either of them, few attempt has been made to establish the connection between the two issues. To attack this problem, a generalized quantification function is proposed for community in weighted networks, which provides a framework that unifies several well-known measures. Then, we prove that the trace optimization of the proposed measure is equivalent with the objective functions of algorithms such as nonnegative matrix factorization, kernel K-means as well as spectral clustering. It serves as the theoretical foundation for designing algorithms for community detection. On the second issue, a semi-supervised spectral clustering algorithm is developed by exploring the equivalence relation via combining the nonnegative matrix factorization and spectral clustering. Different from the traditional semi-supervised algorithms, the partial supervision is integrated into the objective of the spectral algorithm. Finally, through extensive experiments on both artificial and real world networks, we demonstrate that the proposed method improves the accuracy of the traditional spectral algorithms in community detection.

  6. Endothelial cell-based methods for the detection of cyanobacterial anti-inflammatory and wound-healing promoting metabolites.

    Science.gov (United States)

    Wiesner, Christoph; Kopecky, Jiri; Pflueger, Maren; Hundsberger, Harald; Entler, Barbara; Kleber, Christoph; Atzler, Josef; Hrouzek, Pavel; Stys, Dalibor; Lukesova, Alena; Schuett, Wolfgang; Lucas, Rudolf

    2007-12-01

    Acute lung injury is accompanied by an increased endothelial chemokine production and adhesion molecule expression, which may result in an extensive neutrophil infiltration. Moreover, a destruction of the alveolar epithelium and capillary endothelium may result in permeability edema. As such, the search for novel anti-inflammatory substances, able to downregulate these parameters as well as the tissue damage holds therapeutic promise. We therefore describe here the use of human endothelial cell-based in vitro assays for the detection of anti-inflammatory and wound-healing metabolites from cyanobacteria.

  7. A new detection method for the K variant of butyrylcholinesterase based on PCR primer introduced restriction analysis (PCR-PIRA).

    Science.gov (United States)

    Shibuta, K; Abe, M; Suzuki, T

    1994-01-01

    The K variant of human butyrylcholinesterase is caused by a G/A transition in the butyrylcholinesterase gene, which neither creates nor destroys any restriction site. In an attempt to detect the K variant both simply and rapidly, we developed a two step method of "PCR primer introduced restriction analysis" (PCR-PIRA). The first step was used to introduce a new Fun4HI site into the normal allele for a screening test, while the second step was performed to create a new MaeIII site on the variant allele for a specific test. This method thus enabled us to distinguish clearly the K variant from the normal allele, and also showed that the frequency of the K variant allele is 0.164 in the Japanese population. Images PMID:7966197

  8. GMDD: a database of GMO detection methods

    NARCIS (Netherlands)

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

    2008-01-01

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

  9. Establishing a public health analytical service based on chemical methods for detecting and quantifying Pacific ciguatoxin in fish samples.

    Science.gov (United States)

    Stewart, Ian; Eaglesham, Geoffrey K; Poole, Sue; Graham, Glenn; Paulo, Carl; Wickramasinghe, Wasantha; Sadler, Ross; Shaw, Glen R

    2010-10-01

    A referee analysis method for the detection and quantification of Pacific ciguatoxins in fish flesh has recently been established by the public health analytical laboratory for the State of Queensland, Australia. Fifty-six fish samples were analysed, which included 10 fillets purchased as negative controls. P-CTX-1 was identified in 27 samples, and P-CTX-2 and P-CTX-3 were found in 26 of those samples. The range of P-CTX-1 concentrations was 0.04-11.4 microg/kg fish flesh; coefficient of variation from 90 replicate analyses was 7.4%. A liquid chromatography/tandem mass spectrometry (HPLC-MS/MS) method utilising a rapid methanol extraction and clean-up is reliable and reproducible, with the detection limit at 0.03 microg/kg fish flesh. Some matrix effects are evident, with fish oil content a likely signal suppression factor. Species identification of samples by DNA sequence analysis revealed some evidence of fish substitution or inadvertent misidentification, which may have implications for the management and prevention of ciguatera poisoning. Blinded inspection of case notes from suspect ciguatera poisoning cases showed that reporting of ciguatera-related paraesthesias was highly predictable for the presence of ciguatoxins in analysed fish, with 13 of 14 expected cases having consumed fish that contained P-CTX-1 (p<0.001, Fishers Exact Test). Crown Copyright 2009. Published by Elsevier Ltd. All rights reserved.

  10. A discriminative method for family-based protein remote homology detection that combines inductive logic programming and propositional models.

    Science.gov (United States)

    Bernardes, Juliana S; Carbone, Alessandra; Zaverucha, Gerson

    2011-03-23

    Remote homology detection is a hard computational problem. Most approaches have trained computational models by using either full protein sequences or multiple sequence alignments (MSA), including all positions. However, when we deal with proteins in the "twilight zone" we can observe that only some segments of sequences (motifs) are conserved. We introduce a novel logical representation that allows us to represent physico-chemical properties of sequences, conserved amino acid positions and conserved physico-chemical positions in the MSA. From this, Inductive Logic Programming (ILP) finds the most frequent patterns (motifs) and uses them to train propositional models, such as decision trees and support vector machines (SVM). We use the SCOP database to perform our experiments by evaluating protein recognition within the same superfamily. Our results show that our methodology when using SVM performs significantly better than some of the state of the art methods, and comparable to other. However, our method provides a comprehensible set of logical rules that can help to understand what determines a protein function. The strategy of selecting only the most frequent patterns is effective for the remote homology detection. This is possible through a suitable first-order logical representation of homologous properties, and through a set of frequent patterns, found by an ILP system, that summarizes essential features of protein functions.

  11. A versatile method to design stem-loop primer-based quantitative PCR assays for detecting small regulatory RNA molecules.

    Directory of Open Access Journals (Sweden)

    Zsolt Czimmerer

    Full Text Available Short regulatory RNA-s have been identified as key regulators of gene expression in eukaryotes. They have been involved in the regulation of both physiological and pathological processes such as embryonal development, immunoregulation and cancer. One of their relevant characteristics is their high stability, which makes them excellent candidates for use as biomarkers. Their number is constantly increasing as next generation sequencing methods reveal more and more details of their synthesis. These novel findings aim for new detection methods for the individual short regulatory RNA-s in order to be able to confirm the primary data and characterize newly identified subtypes in different biological conditions. We have developed a flexible method to design RT-qPCR assays that are very sensitive and robust. The newly designed assays were tested extensively in samples from plant, mouse and even human formalin fixed paraffin embedded tissues. Moreover, we have shown that these assays are able to quantify endogenously generated shRNA molecules. The assay design method is freely available for anyone who wishes to use a robust and flexible system for the quantitative analysis of matured regulatory RNA-s.

  12. An adaptive and tacholess order analysis method based on enhanced empirical wavelet transform for fault detection of bearings with varying speeds

    Science.gov (United States)

    Hu, Yue; Tu, Xiaotong; Li, Fucai; Li, Hongguang; Meng, Guang

    2017-11-01

    The order tracking method based on time-frequency representation is regarded as an effective tool for fault detection of bearings with varying rotating speeds. In the traditional order tracking methods, a tachometer is required to obtain the instantaneous speed which is hardly satisfied in practice due to the technical and economical limitations. Some tacholess order tracking methods have been developed in recent years. In these methods, the instantaneous frequency ridge extraction is one of the most important parts. However, the current ridge extraction methods are sensitive to noise and may easily get trapped in a local optimum. Due to the presence of noise and other unrelated components of the signal, bearing fault features are difficult to be detected from the envelope spectrum or envelope order spectrum. To overcome the abovementioned drawbacks, an adaptive and tacholess order analysis method is proposed in this paper. In this method, a novel ridge extraction algorithm based on dynamic path optimization is adopted to estimate the instantaneous frequency. This algorithm can overcome the shortcomings of the current ridge extraction algorithms. Meanwhile, the enhanced empirical wavelet transform (EEWT) algorithm is applied to extract the bearing fault features. Both simulated and experimental results demonstrate that the proposed method is robust to noise and effective for bearing fault detection under variable speed conditions.

  13. Study on the Detection of Moving Target in the Mining Method Based on Hybrid Algorithm for Sports Video Analysis

    Directory of Open Access Journals (Sweden)

    Huang Tian

    2014-10-01

    Full Text Available Moving object detection and tracking is the computer vision and image processing is a hot research direction, based on the analysis of the moving target detection and tracking algorithm in common use, focus on the sports video target tracking non rigid body. In sports video, non rigid athletes often have physical deformation in the process of movement, and may be associated with the occurrence of moving target under cover. Media data is surging to fast search and query causes more difficulties in data. However, the majority of users want to be able to quickly from the multimedia data to extract the interested content and implicit knowledge (concepts, rules, rules, models and correlation, retrieval and query quickly to take advantage of them, but also can provide the decision support problem solving hierarchy. Based on the motion in sport video object as the object of study, conducts the system research from the theoretical level and technical framework and so on, from the layer by layer mining between low level motion features to high-level semantic motion video, not only provides support for users to find information quickly, but also can provide decision support for the user to solve the problem.

  14. A novel colorimetric method based on copper nanoclusters with intrinsic peroxidase-like for detecting xanthine in serum samples

    Science.gov (United States)

    Yan, Zhengyu; Niu, Qianqian; Mou, Mingyao; Wu, Yi; Liu, Xiaoxuan; Liao, Shenghua

    2017-07-01

    A facile strategy for detecting xanthine in serum samples by copper nanocluster (CuNCs) with high intrinsic peroxidase-like activity was reported. Firstly, a simple, mild and time-saving method for preparing CuNCs was developed, in which dithiothreitol (DTT) and bovine serum albumin (BSA) were used as reductant and stabilizer, respectively. The as-prepared CuNCs exhibited a fluorescence emission at 590 nm with a quantum yield (QY) of approximately 5.29%, the fluorescence intensity of the as-prepared CuNCs exhibited no considerable change when stored under ambient condition with the lifetime is 1.75 μs. Moreover, the as-prepared CuNCs exhibited high intrinsic peroxidase-like activity with lower K m ( K m = 8.90 × 10-6 mol L-1) for H2O2, which indicated that CuNCs have a higher affinity for H2O2. Compared with natural enzyme, the as-synthesized CuNCs are more catalytic stable over a wide range of pH (4.0 13.0) and temperature (4 80 °C). Finally, an indirect method for sensing xanthine was established because xanthine oxidase can catalyse the oxidation of xanthine to produce H2O2. Xanthine could be detected as low as 3.8 × 10-7 mol L-1 with a linear range from 5.0 × 10-7 to 1.0 × 10-4 mol L-1. These results proved that the proposed method is sensitive and accurate and could be successfully applied to the determination of xanthine in the serum sample with satisfaction.

  15. Morphological observation and analysis using automated image cytometry for the comparison of trypan blue and fluorescence-based viability detection method.

    Science.gov (United States)

    Chan, Leo Li-Ying; Kuksin, Dmitry; Laverty, Daniel J; Saldi, Stephanie; Qiu, Jean

    2015-05-01

    The ability to accurately determine cell viability is essential to performing a well-controlled biological experiment. Typical experiments range from standard cell culturing to advanced cell-based assays that may require cell viability measurement for downstream experiments. The traditional cell viability measurement method has been the trypan blue (TB) exclusion assay. However, since the introduction of fluorescence-based dyes for cell viability measurement using flow or image-based cytometry systems, there have been numerous publications comparing the two detection methods. Although previous studies have shown discrepancies between TB exclusion and fluorescence-based viability measurements, image-based morphological analysis was not performed in order to examine the viability discrepancies. In this work, we compared TB exclusion and fluorescence-based viability detection methods using image cytometry to observe morphological changes due to the effect of TB on dead cells. Imaging results showed that as the viability of a naturally-dying Jurkat cell sample decreased below 70 %, many TB-stained cells began to exhibit non-uniform morphological characteristics. Dead cells with these characteristics may be difficult to count under light microscopy, thus generating an artificially higher viability measurement compared to fluorescence-based method. These morphological observations can potentially explain the differences in viability measurement between the two methods.

  16. A Bayesian method for detecting stellar flares

    Science.gov (United States)

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

    2014-12-01

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

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

    Directory of Open Access Journals (Sweden)

    Beran Ladislav

    2016-01-01

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

  18. Sensitivity improvement of an immuno-detection method for azaspiracids based on the use of microspheres coupled to a flow-fluorimetry system

    Directory of Open Access Journals (Sweden)

    María Fraga Corral

    2014-06-01

    These results demonstrate the high capability in terms of sensitivity of the microsphere-based immuno-detection assay for AZAs. The immobilization of AZA-1 instead of the synthetic AZA-2 used in Rodríguez et al (Rodriguez et al., 2014, combined with a lower mAb 8F4 concentration provided a remarkable improvement of sensitivity. The ON protocol used in Rodríguez et al. (Rodriguez et al., 2014 displayed a similar IC50 than the new short assay (around 1 nM while the new ON protocol provided an IC50 5-fold more sensitive (0.3 nM. Therefore, the new short assay allows a reduction of the experimental time. Additionally, the increase of sensitivity could help to avoid shellfish matrix interferences. Previously published works using immunoassays for the detection of phycotoxins present in shellfish avoided matrix interference by further extract dilution in combination with an increase of assay sensitivity (Fraga et al., 2012;Fraga et al., 2013. The extraction protocol described by Rodríguez et al. (Rodriguez et al., 2014 will probably be suitable for this newly optimized AZA-detection method since many reagents are the same and the higher sensitivity will allow higher extract dilution. Considering the extraction protocol recovery, sensitivity of the current assay and the regulated limit, shellfish extracts could be diluted up to 1:30 or 1:150 (v/v for detection with the short or long protocols, respectively. Additionally, mAb 8F4 was demonstrated to recognize AZA-2 and AZA-3 with cross-reactivities of 42 and 138 %, respectively. Presumably, this optimized assay will detect these analogs with similar cross-reactivity. The sensitivity of the microsphere-based assay for AZAs is enough to detect these compounds at the regulated levels in shellfish. This microsphere-based multi-detection method provides an easy-to-perform, highly sensitive and rapid method for the detection of AZAs. It could be included in a multi-detection method, which would allow time and sample volume

  19. Laser Raman detection for oral cancer based on an adaptive Gaussian process classification method with posterior probabilities

    International Nuclear Information System (INIS)

    Du, Zhanwei; Yang, Yongjian; Bai, Yuan; Wang, Lijun; Su, Le; Chen, Yong; Li, Xianchang; Zhou, Xiaodong; Shen, Aiguo; Hu, Jiming; Jia, Jun

    2013-01-01

    The existing methods for early and differential diagnosis of oral cancer are limited due to the unapparent early symptoms and the imperfect imaging examination methods. In this paper, the classification models of oral adenocarcinoma, carcinoma tissues and a control group with just four features are established by utilizing the hybrid Gaussian process (HGP) classification algorithm, with the introduction of the mechanisms of noise reduction and posterior probability. HGP shows much better performance in the experimental results. During the experimental process, oral tissues were divided into three groups, adenocarcinoma (n = 87), carcinoma (n = 100) and the control group (n = 134). The spectral data for these groups were collected. The prospective application of the proposed HGP classification method improved the diagnostic sensitivity to 56.35% and the specificity to about 70.00%, and resulted in a Matthews correlation coefficient (MCC) of 0.36. It is proved that the utilization of HGP in LRS detection analysis for the diagnosis of oral cancer gives accurate results. The prospect of application is also satisfactory. (paper)

  20. Laser Raman detection for oral cancer based on an adaptive Gaussian process classification method with posterior probabilities

    Science.gov (United States)

    Du, Zhanwei; Yang, Yongjian; Bai, Yuan; Wang, Lijun; Su, Le; Chen, Yong; Li, Xianchang; Zhou, Xiaodong; Jia, Jun; Shen, Aiguo; Hu, Jiming

    2013-03-01

    The existing methods for early and differential diagnosis of oral cancer are limited due to the unapparent early symptoms and the imperfect imaging examination methods. In this paper, the classification models of oral adenocarcinoma, carcinoma tissues and a control group with just four features are established by utilizing the hybrid Gaussian process (HGP) classification algorithm, with the introduction of the mechanisms of noise reduction and posterior probability. HGP shows much better performance in the experimental results. During the experimental process, oral tissues were divided into three groups, adenocarcinoma (n = 87), carcinoma (n = 100) and the control group (n = 134). The spectral data for these groups were collected. The prospective application of the proposed HGP classification method improved the diagnostic sensitivity to 56.35% and the specificity to about 70.00%, and resulted in a Matthews correlation coefficient (MCC) of 0.36. It is proved that the utilization of HGP in LRS detection analysis for the diagnosis of oral cancer gives accurate results. The prospect of application is also satisfactory.

  1. Method for detecting damage in carbon-fibre reinforced plastic-steel structures based on eddy current pulsed thermography

    Science.gov (United States)

    Li, Xuan; Liu, Zhiping; Jiang, Xiaoli; Lodewijks, Gabrol

    2018-01-01

    Eddy current pulsed thermography (ECPT) is well established for non-destructive testing of electrical conductive materials, featuring the advantages of contactless, intuitive detecting and efficient heating. The concept of divergence characterization of the damage rate of carbon fibre-reinforced plastic (CFRP)-steel structures can be extended to ECPT thermal pattern characterization. It was found in this study that the use of ECPT technology on CFRP-steel structures generated a sizeable amount of valuable information for comprehensive material diagnostics. The relationship between divergence and transient thermal patterns can be identified and analysed by deploying mathematical models to analyse the information about fibre texture-like orientations, gaps and undulations in these multi-layered materials. The developed algorithm enabled the removal of information about fibre texture and the extraction of damage features. The model of the CFRP-glue-steel structures with damage was established using COMSOL Multiphysics® software, and quantitative non-destructive damage evaluation from the ECPT image areas was derived. The results of this proposed method illustrate that damaged areas are highly affected by available information about fibre texture. This proposed work can be applied for detection of impact induced damage and quantitative evaluation of CFRP structures.

  2. A rapid method for detection of genetically modified organisms based on magnetic separation and surface-enhanced Raman scattering.

    Science.gov (United States)

    Guven, Burcu; Boyacı, İsmail Hakkı; Tamer, Ugur; Çalık, Pınar

    2012-01-07

    In this study, a new method combining magnetic separation (MS) and surface-enhanced Raman scattering (SERS) was developed to detect genetically modified organisms (GMOs). An oligonucleotide probe which is specific for 35 S DNA target was immobilized onto gold coated magnetic nanospheres to form oligonucleotide-coated nanoparticles. A self assembled monolayer was formed on gold nanorods using 5,5'-dithiobis (2-nitrobenzoic acid) (DTNB) and the second probe of the 35 S DNA target was immobilized on the activated nanorod surfaces. Probes on the nanoparticles were hybridized with the target oligonucleotide. Optimization parameters for hybridization were investigated by high performance liquid chromatography. Optimum hybridization parameters were determined as: 4 μM probe concentration, 20 min immobilization time, 30 min hybridization time, 55 °C hybridization temperature, 750 mM buffer salt concentration and pH: 7.4. Quantification of the target concentration was performed via SERS spectra of DTNB on the nanorods. The correlation between the target concentration and the SERS signal was found to be linear within the range of 25-100 nM. The analyses were performed with only one hybridization step in 40 min. Real sample analysis was conducted using Bt-176 maize sample. The results showed that the developed MS-SERS assay is capable of detecting GMOs in a rapid and selective manner. This journal is © The Royal Society of Chemistry 2012

  3. Development of a filter-based method for detecting silver nanoparticles and their heteroaggregation in aqueous environments by surface-enhanced Raman spectroscopy

    International Nuclear Information System (INIS)

    Guo, Huiyuan; Xing, Baoshan; He, Lili

    2016-01-01

    The rising application of silver nanoparticles (AgNPs) and subsequent release into aquatic systems have generated public concerns over their potential risk and harm to aquatic organisms and human health. Effective and practical analytical methods for AgNPs are urgently needed for their risk assessment. In this study we established an innovative approach to detect trace levels of AgNPs in environmental water through integrating a filtration technique into surface-enhanced Raman spectroscopy (SERS) and compared it with previously established centrifuge-based method. The purpose of filtration was to trap and enrich salt-aggregated AgNPs from water samples onto the filter membrane, through which indicator was then passed and complexed with AgNPs. The enhanced SERS signals of indicator could reflect the presence and quantity of AgNPs in the samples. The most favorable benefit of filtration is being able to process large volume samples, which is more practical for water samples, and greatly improves the sensitivity of AgNP detection. In this study, we tested 20 mL AgNPs-containing samples and the filter-based method is able to detect AgNPs as low as 5 μg/L, which is 20 folds lower than the centrifuge-based method. In addition, the speed and precision of the detection were greatly improved. This approach was used to detect trace levels of AgNPs in real environmental water successfully. Meanwhile, the heteroaggregation of AgNPs with minerals in water was reliably monitored by the new method. Overall, a combination of the filtration-SERS approach provides a rapid, simple, and sensitive way to detect AgNPs and analyze their environmental behavior. - Highlights: • We developed a filtration-SERS method for analyzing AgNPs in water. • Detection limit can be improved by increasing sample volume for filtration. • Trace levels of AgNPs in natural water samples can be successfully detected. • Filtration-SERS is more efficient and precise than centrifugation-SERS.

  4. K2: A NEW METHOD FOR THE DETECTION OF GALAXY CLUSTERS BASED ON CANADA-FRANCE-HAWAII TELESCOPE LEGACY SURVEY MULTICOLOR IMAGES

    International Nuclear Information System (INIS)

    Thanjavur, Karun; Willis, Jon; Crampton, David

    2009-01-01

    We have developed a new method, K2, optimized for the detection of galaxy clusters in multicolor images. Based on the Red Sequence approach, K2 detects clusters using simultaneous enhancements in both colors and position. The detection significance is robustly determined through extensive Monte Carlo simulations and through comparison with available cluster catalogs based on two different optical methods, and also on X-ray data. K2 also provides quantitative estimates of the candidate clusters' richness and photometric redshifts. Initially, K2 was applied to the two color (gri) 161 deg 2 images of the Canada-France-Hawaii Telescope Legacy Survey Wide (CFHTLS-W) data. Our simulations show that the false detection rate for these data, at our selected threshold, is only ∼1%, and that the cluster catalogs are ∼80% complete up to a redshift of z = 0.6 for Fornax-like and richer clusters and to z ∼ 0.3 for poorer clusters. Based on the g-, r-, and i-band photometric catalogs of the Terapix T05 release, 35 clusters/deg 2 are detected, with 1-2 Fornax-like or richer clusters every 2 deg 2 . Catalogs containing data for 6144 galaxy clusters have been prepared, of which 239 are rich clusters. These clusters, especially the latter, are being searched for gravitational lenses-one of our chief motivations for cluster detection in CFHTLS. The K2 method can be easily extended to use additional color information and thus improve overall cluster detection to higher redshifts. The complete set of K2 cluster catalogs, along with the supplementary catalogs for the member galaxies, are available on request from the authors.

  5. Optics based signal processing methods for intraoperative blood vessel detection and quantification in real time (Conference Presentation)

    Science.gov (United States)

    Chaturvedi, Amal; Shukair, Shetha A.; Le Rolland, Paul; Vijayvergia, Mayank; Subramanian, Hariharan; Gunn, Jonathan W.

    2016-03-01

    Minimally invasive operations require surgeons to make difficult cuts to blood vessels and other tissues with impaired tactile and visual feedback. This leads to inadvertent cuts to blood vessels hidden beneath tissue, causing serious health risks to patients and a non-reimbursable financial burden to hospitals. Intraoperative imaging technologies have been developed, but these expensive systems can be cumbersome and provide only a high-level view of blood vessel networks. In this research, we propose a lean reflectance-based system, comprised of a dual wavelength LED, photodiode, and novel signal processing algorithms for rapid vessel characterization. Since this system takes advantage of the inherent pulsatile light absorption characteristics of blood vessels, no contrast agent is required for its ability to detect the presence of a blood vessel buried deep inside any tissue type (up to a cm) in real time. Once a vessel is detected, the system is able to estimate the distance of the vessel from the probe and the diameter size of the vessel (with a resolution of ~2mm), as well as delineate the type of tissue surrounding the vessel. The system is low-cost, functions in real-time, and could be mounted on already existing surgical tools, such as Kittner dissectors or laparoscopic suction irrigation cannulae. Having been successfully validated ex vivo, this technology will next be tested in a live porcine study and eventually in clinical trials.

  6. Alternative Methods for the Detection of Emerging Marine Toxins: Biosensors, Biochemical Assays and Cell-Based Assays

    Directory of Open Access Journals (Sweden)

    Laia Reverté

    2014-11-01

    Full Text Available The emergence of marine toxins in water and seafood may have a considerable impact on public health. Although the tendency in Europe is to consolidate, when possible, official reference methods based on instrumental analysis, the development of alternative or complementary methods providing functional or toxicological information may provide advantages in terms of risk identification, but also low cost, simplicity, ease of use and high-throughput analysis. This article gives an overview of the immunoassays, cell-based assays, receptor-binding assays and biosensors that have been developed for the screening and quantification of emerging marine toxins: palytoxins, ciguatoxins, cyclic imines and tetrodotoxins. Their advantages and limitations are discussed, as well as their possible integration in research and monitoring programs.

  7. Alternative Methods for the Detection of Emerging Marine Toxins: Biosensors, Biochemical Assays and Cell-Based Assays

    Science.gov (United States)

    Reverté, Laia; Soliño, Lucía; Carnicer, Olga; Diogène, Jorge; Campàs, Mònica

    2014-01-01

    The emergence of marine toxins in water and seafood may have a considerable impact on public health. Although the tendency in Europe is to consolidate, when possible, official reference methods based on instrumental analysis, the development of alternative or complementary methods providing functional or toxicological information may provide advantages in terms of risk identification, but also low cost, simplicity, ease of use and high-throughput analysis. This article gives an overview of the immunoassays, cell-based assays, receptor-binding assays and biosensors that have been developed for the screening and quantification of emerging marine toxins: palytoxins, ciguatoxins, cyclic imines and tetrodotoxins. Their advantages and limitations are discussed, as well as their possible integration in research and monitoring programs. PMID:25431968

  8. Method to detect biological particles

    International Nuclear Information System (INIS)

    Giaever, I.

    1976-01-01

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

  9. Cellular Phone-Based Image Acquisition and Quantitative Ratiometric Method for Detecting Cocaine and Benzoylecgonine for Biological and Forensic Applications

    OpenAIRE

    Cadle, Brian A.; Rasmus, Kristin C.; Varela, Juan A.; Leverich, Leah S.; O’Neill, Casey E.; Bachtell, Ryan K.; Cooper, Donald C.

    2010-01-01

    Here we describe the first report of using low-cost cellular or web-based digital cameras to image and quantify standardized rapid immunoassay strips as a new point-of-care diagnostic and forensics tool with health applications. Quantitative ratiometric pixel density analysis (QRPDA) is an automated method requiring end-users to utilize inexpensive (~ $1 USD/each) immunotest strips, a commonly available web or mobile phone camera or scanner, and internet or cellular service. A model is descri...

  10. Proposed modifications of Environmental Protection Agency Method 1601 for detection of coliphages in drinking water, with same-day fluorescence-based detection and evaluation by the performance-based measurement system and alternative test protocol validation approaches.

    Science.gov (United States)

    Salter, Robert S; Durbin, Gregory W; Conklin, Ernestine; Rosen, Jeff; Clancy, Jennifer

    2010-12-01

    Coliphages are microbial indicators specified in the Ground Water Rule that can be used to monitor for potential fecal contamination of drinking water. The Total Coliform Rule specifies coliform and Escherichia coli indicators for municipal water quality testing; thus, coliphage indicator use is less common and advances in detection methodology are less frequent. Coliphages are viral structures and, compared to bacterial indicators, are more resistant to disinfection and diffuse further distances from pollution sources. Therefore, coliphage presence may serve as a better predictor of groundwater quality. This study describes Fast Phage, a 16- to 24-h presence/absence modification of U.S. Environmental Protection Agency (EPA) Method 1601 for detection of coliphages in 100 ml water. The objective of the study is to demonstrate that the somatic and male-specific coliphage modifications provide results equivalent to those of Method 1601. Five laboratories compared the modifications, featuring same-day fluorescence-based prediction, to Method 1601 by using the performance-based measurement system (PBMS) criterion. This requires a minimum 50% positive response in 10 replicates of 100-ml water samples at coliphage contamination levels of 1.3 to 1.5 PFU/100 ml. The laboratories showed that Fast Phage meets PBMS criteria with 83.5 to 92.1% correlation of the same-day rapid fluorescence-based prediction with the next-day result. Somatic coliphage PBMS data are compared to manufacturer development data that followed the EPA alternative test protocol (ATP) validation approach. Statistical analysis of the data sets indicates that PBMS utilizes fewer samples than does the ATP approach but with similar conclusions. Results support testing the coliphage modifications by using an EPA-approved national PBMS approach with collaboratively shared samples.

  11. A simple method for determination of carmine in food samples based on cloud point extraction and spectrophotometric detection.

    Science.gov (United States)

    Heydari, Rouhollah; Hosseini, Mohammad; Zarabi, Sanaz

    2015-01-01

    In this paper, a simple and cost effective method was developed for extraction and pre-concentration of carmine in food samples by using cloud point extraction (CPE) prior to its spectrophotometric determination. Carmine was extracted from aqueous solution using Triton X-100 as extracting solvent. The effects of main parameters such as solution pH, surfactant and salt concentrations, incubation time and temperature were investigated and optimized. Calibration graph was linear in the range of 0.04-5.0 μg mL(-1) of carmine in the initial solution with regression coefficient of 0.9995. The limit of detection (LOD) and limit of quantification were 0.012 and 0.04 μg mL(-1), respectively. Relative standard deviation (RSD) at low concentration level (0.05 μg mL(-1)) of carmine was 4.8% (n=7). Recovery values in different concentration levels were in the range of 93.7-105.8%. The obtained results demonstrate the proposed method can be applied satisfactory to determine the carmine in food samples. Copyright © 2015 Elsevier B.V. All rights reserved.

  12. A Real-Time Method to Estimate Speed of Object Based on Object Detection and Optical Flow Calculation

    Science.gov (United States)

    Liu, Kaizhan; Ye, Yunming; Li, Xutao; Li, Yan

    2018-04-01

    In recent years Convolutional Neural Network (CNN) has been widely used in computer vision field and makes great progress in lots of contents like object detection and classification. Even so, combining Convolutional Neural Network, which means making multiple CNN frameworks working synchronously and sharing their output information, could figure out useful message that each of them cannot provide singly. Here we introduce a method to real-time estimate speed of object by combining two CNN: YOLOv2 and FlowNet. In every frame, YOLOv2 provides object size; object location and object type while FlowNet providing the optical flow of whole image. On one hand, object size and object location help to select out the object part of optical flow image thus calculating out the average optical flow of every object. On the other hand, object type and object size help to figure out the relationship between optical flow and true speed by means of optics theory and priori knowledge. Therefore, with these two key information, speed of object can be estimated. This method manages to estimate multiple objects at real-time speed by only using a normal camera even in moving status, whose error is acceptable in most application fields like manless driving or robot vision.

  13. Cyclic voltammetry, square wave voltammetry, electrochemical impedance spectroscopy and colorimetric method for hydrogen peroxide detection based on chitosan/silver nanocomposite

    Directory of Open Access Journals (Sweden)

    Hoang V. Tran

    2018-05-01

    Full Text Available In this paper, we demonstrate a promising method to fabricate a non-enzymatic stable, highly sensitive and selective hydrogen peroxide sensor based on a chitosan/silver nanoparticles (CS/AgNPs hybrid. Using this composite, we elaborated both electrochemical and colorimetric sensors for hydrogen peroxide detection. The colorimetric sensor is based on a homogenous reaction which fades the color of CS/AgNPs solutions from red-orange to colorless depending on hydrogen peroxide concentration. For the electrochemical sensor, CS/AgNPs were immobilized on glassy carbon electrodes and hydrogen peroxide was measured using cyclic voltammetry, square wave voltammetry and electrochemical impedance spectroscopy. The response time is less than 10 s and the detection limit is 5 μM. Keywords: Spectrophotometric detection, Electrochemical impedance spectroscopy, Square wave voltammetry, Cyclic voltammetry, Chitosan/silver nanoparticles (CS/AgNPs hybrid, Hydrogen peroxide

  14. Development and Evaluation of a PCR and Mass Spectroscopy-based (PCR-MS) Method for Quantitative, Type-specific Detection of Human Papillomavirus

    Science.gov (United States)

    Patel, Divya A.; Shih, Yang-Jen; Newton, Duane W.; Michael, Claire W.; Oeth, Paul A.; Kane, Michael D.; Opipari, Anthony W.; Ruffin, Mack T.; Kalikin, Linda M.; Kurnit, David M.

    2010-01-01

    Knowledge of the central role of high-risk human papillomavirus (HPV) in cervical carcinogenesis, coupled with an emerging need to monitor the efficacy of newly introduced HPV vaccines, warrant development and evaluation of type-specific, quantitative HPV detection methods. In the present study, a prototype PCR and mass spectroscopy (PCR-MS)-based method to detect and quantitate 13 high-risk HPV types is compared to the Hybrid Capture 2 High Risk HPV DNA test (HC2; Digene Corp., Gaithersburg, MD) in 199 cervical scraping samples and to DNA sequencing in 77 cervical tumor samples. High-risk HPV types were detected in 76/77 (98.7%) cervical tumor samples by PCR-MS. Degenerate and type-specific sequencing confirmed the types detected by PCR-MS. In 199 cervical scraping samples, all 13 HPV types were detected by PCR-MS. Eighteen (14.5%) of 124 cervical scraping samples that were positive for high-risk HPV by HC2 were negative by PCR-MS. In all these cases, degenerate DNA sequencing failed to detect any of the 13 high-risk HPV types. Nearly half (46.7%) of the 75 cervical scraping samples that were negative for high-risk HPV by the HC2 assay were positive by PCR-MS. Type-specific sequencing in a subset of these samples confirmed the HPV type detected by PCR-MS. Quantitative PCR-MS results demonstrated that 11/75 (14.7%) samples contained as much HPV copies/cell as HC2-positive samples. These findings suggest that this prototype PCR-MS assay performs at least as well as HC2 for HPV detection, while offering the additional, unique advantages of type-specific identification and quantitation. Further validation work is underway to define clinically meaningful HPV detection thresholds and to evaluate the potential clinical application of future generations of the PCR-MS assay. PMID:19410602

  15. Development and evaluation of a PCR and mass spectroscopy (PCR-MS)-based method for quantitative, type-specific detection of human papillomavirus.

    Science.gov (United States)

    Patel, Divya A; Shih, Yang-Jen; Newton, Duane W; Michael, Claire W; Oeth, Paul A; Kane, Michael D; Opipari, Anthony W; Ruffin, Mack T; Kalikin, Linda M; Kurnit, David M

    2009-09-01

    Knowledge of the central role of high-risk human papillomavirus (HPV) in cervical carcinogenesis, coupled with an emerging need to monitor the efficacy of newly introduced HPV vaccines, warrant development and evaluation of type-specific, quantitative HPV detection methods. In the present study, a prototype PCR and mass spectroscopy (PCR-MS)-based method to detect and quantitate 13 high-risk HPV types is compared to the Hybrid Capture 2 High-Risk HPV DNA test (HC2; Digene Corp., Gaithersburg, MD) in 199 cervical scraping samples and to DNA sequencing in 77 cervical tumor samples. High-risk HPV types were detected in 76/77 (98.7%) cervical tumor samples by PCR-MS. Degenerate and type-specific sequencing confirmed the types detected by PCR-MS. In 199 cervical scraping samples, all 13 HPV types were detected by PCR-MS. Eighteen (14.5%) of 124 cervical scraping samples that were positive for high-risk HPV by HC2 were negative by PCR-MS. In all these cases, degenerate DNA sequencing failed to detect any of the 13 high-risk HPV types. Nearly half (46.7%) of the 75 cervical scraping samples that were negative for high-risk HPV by the HC2 assay were positive by PCR-MS. Type-specific sequencing in a subset of these samples confirmed the HPV type detected by PCR-MS. Quantitative PCR-MS results demonstrated that 11/75 (14.7%) samples contained as much HPV copies/cell as HC2-positive samples. These findings suggest that this prototype PCR-MS assay performs at least as well as HC2 for HPV detection, while offering the additional, unique advantages of type-specific identification and quantitation. Further validation work is underway to define clinically meaningful HPV detection thresholds and to evaluate the potential clinical application of future generations of the PCR-MS assay.

  16. PCR-free quantitative detection of genetically modified organism from raw materials – A novel electrochemiluminescence-based bio-barcode method

    Science.gov (United States)

    Zhu, Debin; Tang, Yabing; Xing, Da; Chen, Wei R.

    2018-01-01

    Bio-barcode assay based on oligonucleotide-modified gold nanoparticles (Au-NPs) provides a PCR-free method for quantitative detection of nucleic acid targets. However, the current bio-barcode assay requires lengthy experimental procedures including the preparation and release of barcode DNA probes from the target-nanoparticle complex, and immobilization and hybridization of the probes for quantification. Herein, we report a novel PCR-free electrochemiluminescence (ECL)-based bio-barcode assay for the quantitative detection of genetically modified organism (GMO) from raw materials. It consists of tris-(2’2’-bipyridyl) ruthenium (TBR)-labele barcode DNA, nucleic acid hybridization using Au-NPs and biotin-labeled probes, and selective capture of the hybridization complex by streptavidin-coated paramagnetic beads. The detection of target DNA is realized by direct measurement of ECL emission of TBR. It can quantitatively detect target nucleic acids with high speed and sensitivity. This method can be used to quantitatively detect GMO fragments from real GMO products. PMID:18386909

  17. A composite method based on formal grammar and DNA structural features in detecting human polymerase II promoter region.

    Directory of Open Access Journals (Sweden)

    Sutapa Datta

    Full Text Available An important step in understanding gene regulation is to identify the promoter regions where the transcription factor binding takes place. Predicting a promoter region de novo has been a theoretical goal for many researchers for a long time. There exists a number of in silico methods to predict the promoter region de novo but most of these methods are still suffering from various shortcomings, a major one being the selection of appropriate features of promoter region distinguishing them from non-promoters. In this communication, we have proposed a new composite method that predicts promoter sequences based on the interrelationship between structural profiles of DNA and primary sequence elements of the promoter regions. We have shown that a Context Free Grammar (CFG can formalize the relationships between different primary sequence features and by utilizing the CFG, we demonstrate that an efficient parser can be constructed for extracting these relationships from DNA sequences to distinguish the true promoter sequences from non-promoter sequences. Along with CFG, we have extracted the structural features of the promoter region to improve upon the efficiency of our prediction system. Extensive experiments performed on different datasets reveals that our method is effective in predicting promoter sequences on a genome-wide scale and performs satisfactorily as compared to other promoter prediction techniques.

  18. A Composite Method Based on Formal Grammar and DNA Structural Features in Detecting Human Polymerase II Promoter Region

    Science.gov (United States)

    Datta, Sutapa; Mukhopadhyay, Subhasis

    2013-01-01

    An important step in understanding gene regulation is to identify the promoter regions where the transcription factor binding takes place. Predicting a promoter region de novo has been a theoretical goal for many researchers for a long time. There exists a number of in silico methods to predict the promoter region de novo but most of these methods are still suffering from various shortcomings, a major one being the selection of appropriate features of promoter region distinguishing them from non-promoters. In this communication, we have proposed a new composite method that predicts promoter sequences based on the interrelationship between structural profiles of DNA and primary sequence elements of the promoter regions. We have shown that a Context Free Grammar (CFG) can formalize the relationships between different primary sequence features and by utilizing the CFG, we demonstrate that an efficient parser can be constructed for extracting these relationships from DNA sequences to distinguish the true promoter sequences from non-promoter sequences. Along with CFG, we have extracted the structural features of the promoter region to improve upon the efficiency of our prediction system. Extensive experiments performed on different datasets reveals that our method is effective in predicting promoter sequences on a genome-wide scale and performs satisfactorily as compared to other promoter prediction techniques. PMID:23437045

  19. Novel methods for detecting buried explosive devices

    Energy Technology Data Exchange (ETDEWEB)

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

    1997-04-01

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

  20. Meat authentication: a new HPLC-MS/MS based method for the fast and sensitive detection of horse and pork in highly processed food.

    Science.gov (United States)

    von Bargen, Christoph; Brockmeyer, Jens; Humpf, Hans-Ulrich

    2014-10-01

    Fraudulent blending of food products with meat from undeclared species is a problem on a global scale, as exemplified by the European horse meat scandal in 2013. Routinely used methods such as ELISA and PCR can suffer from limited sensitivity or specificity when processed food samples are analyzed. In this study, we have developed an optimized method for the detection of horse and pork in different processed food matrices using MRM and MRM(3) detection of species-specific tryptic marker peptides. Identified marker peptides were sufficiently stable to resist thermal processing of different meat products and thus allow the sensitive and specific detection of pork or horse in processed food down to 0.24% in a beef matrix system. In addition, we were able to establish a rapid 2-min extraction protocol for the efficient protein extraction from processed food using high molar urea and thiourea buffers. Together, we present here the specific and sensitive detection of horse and pork meat in different processed food matrices using MRM-based detection of marker peptides. Notably, prefractionation of proteins using 2D-PAGE or off-gel fractionation is not necessary. The presented method is therefore easily applicable in analytical routine laboratories without dedicated proteomics background.

  1. A solvent-dependent fluorescent detection method for Fe(3+) and Hg(2+) based on a rhodamine B derivative.

    Science.gov (United States)

    Li, Xutian; Yin, Yue; Deng, Junjie; Zhong, Huixian; Tang, Jian; Chen, Zhi; Yang, Liting; Ma, Li-Jun

    2016-07-01

    A new rhodamine B-benzofurazan based fluorescent probe (1) for Fe(3+) and Hg(2+) was synthesized. In aqueous solution containing 30% (v/v) ethanol, probe 1 shows a high selective fluorescent enhancement recognition to Fe(3+) with a binding ratio of 1:1 (probe 1: Fe(3+)), when the concentration of Fe(3+) is less than that of the probe. When the concentration of Fe(3+) is higher than that of the probe, it shows fluorescent "turn-on" response to Fe(3+) by opening the rhodamine spirolactam with a binding ratio of 1:2 (probe 1: Fe(3+)). Furthermore, probe 1 displays a high selectivity and a hypersensitivity (detection limit is 4.4nM) to Hg(2+) with a binding ratio of 1:1 in ethanol. NMR and UV-vis experiments indicate that the different fluorescent recognition signals to Fe(3+) and Hg(2+) are derived from different binding modes of 1-Fe(3+) and 1-Hg(2+). Copyright © 2016 Elsevier B.V. All rights reserved.

  2. Electromagnetic Methods of Lightning Detection

    Science.gov (United States)

    Rakov, V. A.

    2013-11-01

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

  3. A study on a real-time leak detection method for pressurized liquid refrigerant pipeline based on pressure and flow rate

    International Nuclear Information System (INIS)

    Tian, Shen; Du, Juanli; Shao, Shuangquan; Xu, Hongbo; Tian, Changqing

    2016-01-01

    Highlights: • A real-time leak detection method is developed for ammonia pipeline in cold storage. • A locating algorithm based on pressure difference profile is provided. • This method is validated by R22 and ammonia leak experiments. • The minimum detectable leak ratio is 1% for R22 and 4% for ammonia. • The location estimating errors are −27% ~ 17% for R22 and −27% ~ 27% for ammonia. - Graphical Abstract: - Abstract: Leakage from pressurized liquid ammonia pipeline has been a serious problem in large commercial cold storages because it might release large amount of liquid ammonia and without safety supervision in daily operations. The present paper shows a detection method for a pressurized liquid ammonia pipeline with a leak. The variations of pressure, flow rate and pressure difference profile are studied. A leak indicator (σ), proposed with the one-dimensional steady-state flow model, is used to detect the leak occurrence by comparing it with a threshold value (σ Le ). A locating algorithm based on pressure difference profile along the pipeline is also proposed, which has considered the effect of the static pressure increase at the leak point. Experiments on different leak positions and ratios from liquid R22 and ammonia pipelines are carried out to validate this method. It is found that, with a relatively low false alarm rate (as three percent), the minimum detectable leak ratio reached 1% for the R22 pipeline and 4% for the ammonia pipeline. The locating errors are between −27% ~ 17% for R22 pipeline and −27% ~ 27% for ammonia pipeline.

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

    Science.gov (United States)

    Roshan, Aditya; Zhang, Yun

    2014-06-01

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

  5. Particle detection systems and methods

    Science.gov (United States)

    Morris, Christopher L.; Makela, Mark F.

    2010-05-11

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

  6. A novel method of adrenaline concentration detection using fiber optical biosensor based on the catalysis of iron(II) phthalocyanine

    Science.gov (United States)

    Zhou, Xuan; Huang, Jun; Li, Mingtian; Wang, Bin

    2008-12-01

    As an effective alternative to the nature enzyme, metallophthalocyanine (MPc), having the advantages of easy accessibility, good stability and low cost, are used as catalyzer for the adrenaline (AD) oxidation. In this paper, the oxidation of AD by dioxygen using iron(II) phthalocyanine (FePc) as the catalyst was studied by electronic absorption spectra. The experimental results indicate that the oxidation product of AD catalyzed by FePc is adrenochrome with characteristic peaks at 298 nm and 267 nm. The catalytic activities of FePc are evaluated by the ratios of the absorbance at 298 nm of adrenochrome. The optimal concentration, pH and temperature for the oxidation of AD are 5.0×10-5 M, 8.0 and 55 oC, respectively. By using lock-in technology, the fiber optic adrenaline biosensor based on FePc catalysis and fluorescence quenching was fabricated and studied. A linear relationship between φ, the phase delay of the sensor head, and AD concentration was observed in the range of 2.0×10-6 to 9.0×10-6 M and 2.0×10-5 to 9.0×10-5 M. The standard deviation (SD) values are 4.7×10-8 (n = 5) and 5.9×10-7 (n = 5) M, respectively, while the detection limit is 4.0×10-7 M. The biosensor has the response time of about 15 min and the preferred reproducibility and stability.

  7. A new fault detection method for computer networks

    International Nuclear Information System (INIS)

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

    2013-01-01

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

  8. Fault-tolerant control for current sensors of doubly fed induction generators based on an improved fault detection method

    DEFF Research Database (Denmark)

    Li, Hui; Yang, Chao; Hu, Yaogang

    2014-01-01

    Fault-tolerant control of current sensors is studied in this paper to improve the reliability of a doubly fed induction generator (DFIG). A fault-tolerant control system of current sensors is presented for the DFIG, which consists of a new current observer and an improved current sensor fault...... detection algorithm, and fault-tolerant control system are investigated by simulation. The results indicate that the outputs of the observer and the sensor are highly coherent. The fault detection algorithm can efficiently detect both soft and hard faults in current sensors, and the fault-tolerant control...

  9. Detection of food irradiation - two analytical methods

    International Nuclear Information System (INIS)

    1994-01-01

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

  10. Research and Design of Rootkit Detection Method

    Science.gov (United States)

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

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

  11. Detection methods for irradiated mites and insects

    International Nuclear Information System (INIS)

    Ignatowicz, S.

    1999-01-01

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

  12. Vision-based Vehicle Detection Survey

    Directory of Open Access Journals (Sweden)

    Alex David S

    2016-03-01

    Full Text Available Nowadays thousands of drivers and passengers were losing their lives every year on road accident, due to deadly crashes between more than one vehicle. There are number of many research focuses were dedicated to the development of intellectual driver assistance systems and autonomous vehicles over the past decade, which reduces the danger by monitoring the on-road environment. In particular, researchers attracted towards the on-road detection of vehicles in recent years. Different parameters have been analyzed in this paper which includes camera placement and the various applications of monocular vehicle detection, common features and common classification methods, motion- based approaches and nighttime vehicle detection and monocular pose estimation. Previous works on the vehicle detection listed based on camera poisons, feature based detection and motion based detection works and night time detection.

  13. Comparison of Methods for Oscillation Detection

    DEFF Research Database (Denmark)

    Odgaard, Peter Fogh; Trangbæk, Klaus

    2006-01-01

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

  14. Development and validation of a SYBR Green I-based real-time polymerase chain reaction method for detection of haptoglobin gene deletion in clinical materials.

    Science.gov (United States)

    Soejima, Mikiko; Tsuchiya, Yuji; Egashira, Kouichi; Kawano, Hiroyuki; Sagawa, Kimitaka; Koda, Yoshiro

    2010-06-01

    Anhaptoglobinemic patients run the risk of severe anaphylactic transfusion reaction because they produce serum haptoglobin (Hp) antibodies. Being homozygous for the Hp gene deletion (HP(del)) is the only known cause of congenital anhaptoglobinemia, and clinical diagnosis of HP(del) before transfusion is important to prevent anaphylactic shock. We recently developed a 5'-nuclease (TaqMan) real-time polymerase chain reaction (PCR) method. A SYBR Green I-based duplex real-time PCR assay using two forward primers and a common reverse primer followed by melting curve analysis was developed to determine HP(del) zygosity in a single tube. In addition, to obviate initial DNA extraction, we examined serially diluted blood samples as PCR templates. Allelic discrimination of HP(del) yielded optimal results at blood sample dilutions of 1:64 to 1:1024. The results from 2231 blood samples were fully concordant with those obtained by the TaqMan-based real-time PCR method. The detection rate of the HP(del) allele by the SYBR Green I-based method is comparable with that using the TaqMan-based method. This method is readily applicable due to its low initial cost and analyzability using economical real-time PCR machines and is suitable for high-throughput analysis as an alternative method for allelic discrimination of HP(del).

  15. A rapid silica spin column-based method of RNA extraction from fruit trees for RT-PCR detection of viruses.

    Science.gov (United States)

    Yang, Fan; Wang, Guoping; Xu, Wenxing; Hong, Ni

    2017-09-01

    Efficient recovery of high quality RNA is very important for successful RT-PCR detection of plant RNA viruses. High levels of polyphenols and polysaccharides in plant tissues can irreversibly bind to and/or co-precipitate with RNA, which influences RNA isolation. In this study, a silica spin column-based RNA isolation method was developed by using commercially available silica columns combined with the application of a tissue lysis solution, and binding and washing buffers with high concentration guanidinium thiocyanate (GuSCN, 50% w/v), which helps remove plant proteins, polysaccharides and polyphenolic compounds. The method was successfully used to extract high quality RNA from citrus (Citrus aurantifolia), grapevine (Vitis vinifera), peach (Prunus persica), pear (Pyrus spp.), taro (Colocosia esculenta) and tobacco (Nicotiana benthamiana) samples. The method was comparable to conventional CTAB method in RNA isolation efficiency, but it was more sample-adaptable and cost-effective than commercial kits. High quality RNA isolated using silica spin column-based method was successfully used for the RT-PCR and/or multiplex RT-PCR amplification of woody fruit tree viruses and a viroid. The study provided a useful tool for the detection and characterization of plant viruses. Copyright © 2017 Elsevier B.V. All rights reserved.

  16. A simple, rapid and green method based on pulsed potentiostatic electrodeposition of reduced graphene oxide on glass carbon electrode for sensitive voltammetric detection of sophoridine

    International Nuclear Information System (INIS)

    Wang, Fei; Wu, Yanju; Lu, Kui; Gao, Lin; Ye, Baoxian

    2014-01-01

    Graphical abstract: A simple, rapid and green method, based on graphene nanosheets directly deposited onto a glassy carbon electrode by pulsed potentiostatic reduction of a graphene oxide colloidal solution, to build sensitive voltammetric sensor for the determination of sophoridine was presented. - Highlights: • A simple, rapid and green method to build sensitive voltammetric sensor was presented. • The proposed sensor has a high electrochemical sensitivity for determination of sophoridine. • The proposed sensor exhibited an excellent selectivity. - Abstract: A simple, rapid and green method was described for sensitive voltammetric detection of sophoridine based on graphene nanosheets directly deposited onto a glassy carbon electrode (GCE) by pulsed potentiostatic reduction of a graphene oxide (GO) colloidal solution. The resulting electrodes (PP-ERGO/GCE) were characterized by electrochemical methods and scanning electron microscopy. Moreover, the electrochemical behaviors of sophoridine at the modified electrode were investigated in detail by cyclic voltammetry (CV), chronoamperometry (CA) and chronocoulometry (CC). Compared with the bare GCE and the preparation of reduced graphene oxide (RGO) films by potentiostatic method (PM) modified GCE, PP-ERGO/GCE could intensively enhance the oxidation peak currents and decrease the overpotential of sophoridine. Under the selected conditions, the modified electrode showed a linear voltammetric response to sophoridine within the concentration range of 8.0 × 10 −7 ∼ 1.0 × 10 −4 mol L −11 , with the detection limit of 2.0 × 10 −7 mol L −1 . And, the method was also applied to detect sophoridine in spiked human urine with wonderful satisfactory

  17. Molecular methods for the detection of mutations.

    Science.gov (United States)

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

    2000-01-01

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

  18. A novel method for detection of apoptosis

    International Nuclear Information System (INIS)

    Zagariya, Alexander M.

    2012-01-01

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

  19. Highly selective and sensitive method for Cu2 + detection based on chiroptical activity of L-Cysteine mediated Au nanorod assemblies

    Science.gov (United States)

    Abbasi, Shahryar; Khani, Hamzeh

    2017-11-01

    Herein, we demonstrated a simple and efficient method to detect Cu2 + based on amplified optical activity in the chiral nanoassemblies of gold nanorods (Au NRs). L-Cysteine can induce side-by-side or end-to-end assembly of Au NRs with an evident plasmonic circular dichroism (PCD) response due to coupling between surface plasmon resonances (SPR) of Au NRs and the chiral signal of L-Cys. Because of the obvious stronger plasmonic circular dichrosim (CD) response of the side-by-side assembly compared with the end-to-end assemblies, SS assembled Au NRs was selected as a sensitive platform and used for Cu2 + detection. In the presence of Cu2 +, Cu2 + can catalyze O2 oxidation of cysteine to cystine. With an increase in Cu2 + concentration, the L-Cysteine-mediated assembly of Au NRs decreased because of decrease in the free cysteine thiol groups, and the PCD signal decreased. Taking advantage of this method, Cu2 + could be detected in the concentration range of 20 pM-5 nM. Under optimal conditions, the calculated detection limit was found to be 7 pM.

  20. Collaborative regression-based anatomical landmark detection

    International Nuclear Information System (INIS)

    Gao, Yaozong; Shen, Dinggang

    2015-01-01

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

  1. Marine neurotoxins: State of the art, bottlenecks, and perspectives for mode of action based methods of detection in seafood

    NARCIS (Netherlands)

    Nicolas, J.; Hendriksen, P.J.M.; Gerssen, A.; Bovee, T.F.H.; Rietjens, I.M.C.M.

    2014-01-01

    Marine biotoxins can accumulate in fish and shellfish, representing a possible threat for consumers. Many marine biotoxins affect neuronal function essentially through their interaction with ion channels or receptors, leading to different symptoms including paralysis and even death. The detection of

  2. Quencher-Free Fluorescence Method for the Detection of Mercury(II Based on Polymerase-Aided Photoinduced Electron Transfer Strategy

    Directory of Open Access Journals (Sweden)

    Haisheng Liu

    2016-11-01

    Full Text Available A new quencher-free Hg2+ ion assay method was developed based on polymerase-assisted photoinduced electron transfer (PIET. In this approach, a probe is designed with a mercury ion recognition sequence (MRS that is composed of two T-rich functional areas separated by a spacer of random bases at the 3′-end, and a sequence of stacked cytosines at the 5′-end, to which a fluorescein (FAM is attached. Upon addition of Hg2+ ions into this sensing system, the MRS folds into a hairpin structure at the 3′-end with Hg2+-mediated base pairs. In the presence of DNA polymerase, it will catalyze the extension reaction, resulting in the formation of stacked guanines, which will instantly quench the fluorescence of FAM through PIET. Under optimal conditions, the limit of detection for Hg2+ ions was estimated to be 5 nM which is higher than the US Environmental Protection Agency (EPA standard limit. In addition, no labeling with a quencher was requiring, and the present method is fairly simple, fast and low cost. It is expected that this cost-effective fluorescence method might hold considerable potential in the detection of Hg2+ ions in real biological and environmental samples.

  3. Quencher-Free Fluorescence Method for the Detection of Mercury(II) Based on Polymerase-Aided Photoinduced Electron Transfer Strategy.

    Science.gov (United States)

    Liu, Haisheng; Ma, Linbin; Ma, Changbei; Du, Junyan; Wang, Meilan; Wang, Kemin

    2016-11-18

    A new quencher-free Hg 2+ ion assay method was developed based on polymerase-assisted photoinduced electron transfer (PIET). In this approach, a probe is designed with a mercury ion recognition sequence (MRS) that is composed of two T-rich functional areas separated by a spacer of random bases at the 3'-end, and a sequence of stacked cytosines at the 5'-end, to which a fluorescein (FAM) is attached. Upon addition of Hg 2+ ions into this sensing system, the MRS folds into a hairpin structure at the 3'-end with Hg 2+ -mediated base pairs. In the presence of DNA polymerase, it will catalyze the extension reaction, resulting in the formation of stacked guanines, which will instantly quench the fluorescence of FAM through PIET. Under optimal conditions, the limit of detection for Hg 2+ ions was estimated to be 5 nM which is higher than the US Environmental Protection Agency (EPA) standard limit. In addition, no labeling with a quencher was requiring, and the present method is fairly simple, fast and low cost. It is expected that this cost-effective fluorescence method might hold considerable potential in the detection of Hg 2+ ions in real biological and environmental samples.

  4. Tracking-by-detection of surgical instruments in minimally invasive surgery via the convolutional neural network deep learning-based method.

    Science.gov (United States)

    Zhao, Zijian; Voros, Sandrine; Weng, Ying; Chang, Faliang; Li, Ruijian

    2017-12-01

    Worldwide propagation of minimally invasive surgeries (MIS) is hindered by their drawback of indirect observation and manipulation, while monitoring of surgical instruments moving in the operated body required by surgeons is a challenging problem. Tracking of surgical instruments by vision-based methods is quite lucrative, due to its flexible implementation via software-based control with no need to modify instruments or surgical workflow. A MIS instrument is conventionally split into a shaft and end-effector portions, while a 2D/3D tracking-by-detection framework is proposed, which performs the shaft tracking followed by the end-effector one. The former portion is described by line features via the RANSAC scheme, while the latter is depicted by special image features based on deep learning through a well-trained convolutional neural network. The method verification in 2D and 3D formulation is performed through the experiments on ex-vivo video sequences, while qualitative validation on in-vivo video sequences is obtained. The proposed method provides robust and accurate tracking, which is confirmed by the experimental results: its 3D performance in ex-vivo video sequences exceeds those of the available state-of -the-art methods. Moreover, the experiments on in-vivo sequences demonstrate that the proposed method can tackle the difficult condition of tracking with unknown camera parameters. Further refinements of the method will refer to the occlusion and multi-instrumental MIS applications.

  5. Cancer Detection and Diagnosis Methods - Annual Plan

    Science.gov (United States)

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

  6. A New Method for Rapid Detection of the Volume and Quality of Watermelon Based on Processing of X-Ray Images

    OpenAIRE

    Zou , Ling; Ming , Sun; Zhang , Di

    2014-01-01

    International audience; Real-time online detection of fruit quality system has been applied to production practice because online testing and grading of fruits screening technology has matured. However, fruit size and quality online testing have always been difficult. Many detection methods of fruit size and quality are very complicated and time consuming, which cannot meet the needs of real-time detection. In this paper, a new method for rapid detecting small watermelon of volume and quality...

  7. Laser-based optical detection of explosives

    CERN Document Server

    Pellegrino, Paul M; Farrell, Mikella E

    2015-01-01

    Laser-Based Optical Detection of Explosives offers a comprehensive review of past, present, and emerging laser-based methods for the detection of a variety of explosives. This book: Considers laser propagation safety and explains standard test material preparation for standoff optical-based detection system evaluation Explores explosives detection using deep ultraviolet native fluorescence, Raman spectroscopy, laser-induced breakdown spectroscopy, reflectometry, and hyperspectral imaging Examines photodissociation followed by laser-induced fluorescence, photothermal methods, cavity-enhanced absorption spectrometry, and short-pulse laser-based techniques Describes the detection and recognition of explosives using terahertz-frequency spectroscopic techniques Each chapter is authored by a leading expert on the respective technology, and is structured to supply historical perspective, address current advantages and challenges, and discuss novel research and applications. Readers are left with an in-depth understa...

  8. Experimental study on a de-noising system for gas and oil pipelines based on an acoustic leak detection and location method

    International Nuclear Information System (INIS)

    Liu, Cuiwei; Li, Yuxing; Fang, Liping; Xu, Minghai

    2017-01-01

    To protect the pipelines from significant danger, the acoustic leak detection and location method for oil and gas pipelines is studied, and a de-noising system is established to extract leakage characteristics from signals. A test loop for gas and oil is established to carry out experiments. First, according to the measured signals, fitting leakage signals are obtained, and then, the objective signals are constructed by adding noises to the fitting signals. Based on the proposed evaluation indexes, the filtering methods are then applied to process the constructed signals and the de-noising system is established. The established leakage extraction system is validated and then applied to process signals measured in gas pipelines that include a straight pipe, elbow pipe and reducing pipe. The leak detection and location is carried out effectively. Finally, the system is applied to process signals measured in water pipelines. The results demonstrate that the proposed de-noising system is effective at extracting leakage signals from measured signals and that the proposed leak detection and location method has a higher detection sensitivity and localization accuracy. For a pipeline with an inner diameter of 42 mm, the smallest leakage orifice that can be detected is 0.1 mm for gas and water and the largest location error is 0.874% for gas and 0.176% for water. - Highlights: • Three evaluation indexes are proposed: SNR, RMSE and ALPD. • The de-noising system is established in the gas and oil pipelines. • The established system is used for gas pipeline effectively, including interference pipes. • The established de-noising system is used for water pipeline effectively.

  9. A rapid method of accurate detection and differentiation of Newcastle disease virus pathotypes by demonstrating multiple bands in degenerate primer based nested RT-PCR.

    Science.gov (United States)

    Desingu, P A; Singh, S D; Dhama, K; Kumar, O R Vinodh; Singh, R; Singh, R K

    2015-02-01

    A rapid and accurate method of detection and differentiation of virulent and avirulent Newcastle disease virus (NDV) pathotypes was developed. The NDV detection was carried out for different domestic avian field isolates and pigeon paramyxo virus-1 (25 field isolates and 9 vaccine strains) by using APMV-I "fusion" (F) gene Class II specific external primer A and B (535bp), internal primer C and D (238bp) based reverses transcriptase PCR (RT-PCR). The internal degenerative reverse primer D is specific for F gene cleavage position of virulent strain of NDV. The nested RT-PCR products of avirulent strains showed two bands (535bp and 424bp) while virulent strains showed four bands (535bp, 424bp, 349bp and 238bp) on agar gel electrophoresis. This is the first report regarding development and use of degenerate primer based nested RT-PCR for accurate detection and differentiation of NDV pathotypes by demonstrating multiple PCR band patterns. Being a rapid, simple, and economical test, the developed method could serve as a valuable alternate diagnostic tool for characterizing NDV isolates and carrying out molecular epidemiological surveillance studies for this important pathogen of poultry. Copyright © 2014 Elsevier B.V. All rights reserved.

  10. Hough transform methods used for object detection

    International Nuclear Information System (INIS)

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

    2001-01-01

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

  11. VISION BASED OBSTACLE DETECTION IN UAV IMAGING

    Directory of Open Access Journals (Sweden)

    S. Badrloo

    2017-08-01

    Full Text Available Detecting and preventing incidence with obstacles is crucial in UAV navigation and control. Most of the common obstacle detection techniques are currently sensor-based. Small UAVs are not able to carry obstacle detection sensors such as radar; therefore, vision-based methods are considered, which can be divided into stereo-based and mono-based techniques. Mono-based methods are classified into two groups: Foreground-background separation, and brain-inspired methods. Brain-inspired methods are highly efficient in obstacle detection; hence, this research aims to detect obstacles using brain-inspired techniques, which try to enlarge the obstacle by approaching it. A recent research in this field, has concentrated on matching the SIFT points along with, SIFT size-ratio factor and area-ratio of convex hulls in two consecutive frames to detect obstacles. This method is not able to distinguish between near and far obstacles or the obstacles in complex environment, and is sensitive to wrong matched points. In order to solve the above mentioned problems, this research calculates the dist-ratio of matched points. Then, each and every point is investigated for Distinguishing between far and close obstacles. The results demonstrated the high efficiency of the proposed method in complex environments.

  12. Development of rapid hemocyte-based extraction methods for detection of hepatitis A virus and murine norovirus in contaminated oysters

    Science.gov (United States)

    The human enteric pathogens, hepatitis A virus and human norovirus, have been shown to contaminate molluscan shellfish and cause foodborne disease in consumers. Rapid viral extraction methods are needed to replace current time consuming methods, which use whole oysters or dissected tissues. In our ...

  13. Rapid methods for detection of bacteria

    DEFF Research Database (Denmark)

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

    2006-01-01

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

  14. Power Consumption Based Android Malware Detection

    Directory of Open Access Journals (Sweden)

    Hongyu Yang

    2016-01-01

    Full Text Available In order to solve the problem that Android platform’s sand-box mechanism prevents security protection software from accessing effective information to detect malware, this paper proposes a malicious software detection method based on power consumption. Firstly, the mobile battery consumption status information was obtained, and the Gaussian mixture model (GMM was built by using Mel frequency cepstral coefficients (MFCC. Then, the GMM was used to analyze power consumption; malicious software can be classified and detected through classification processing. Experiment results demonstrate that the function of an application and its power consumption have a close relationship, and our method can detect some typical malicious application software accurately.

  15. Rapid quantitative analysis of individual anthocyanin content based on high-performance liquid chromatography with diode array detection with the pH differential method.

    Science.gov (United States)

    Wang, Huayin

    2014-09-01

    A new quantitative technique for the simultaneous quantification of the individual anthocyanins based on the pH differential method and high-performance liquid chromatography with diode array detection is proposed in this paper. The six individual anthocyanins (cyanidin 3-glucoside, cyanidin 3-rutinoside, petunidin 3-glucoside, petunidin 3-rutinoside, and malvidin 3-rutinoside) from mulberry (Morus rubra) and Liriope platyphylla were used for demonstration and validation. The elution of anthocyanins was performed using a C18 column with stepwise gradient elution and individual anthocyanins were identified by high-performance liquid chromatography with tandem mass spectrometry. Based on the pH differential method, the high-performance liquid chromatography peak areas of maximum and reference absorption wavelengths of anthocyanin extracts were conducted to quantify individual anthocyanins. The calibration curves for these anthocyanins were linear within the range of 10-5500 mg/L. The correlation coefficients (r(2)) all exceeded 0.9972, and the limits of detection were in the range of 1-4 mg/L at a signal-to-noise ratio ≥5 for these anthocyanins. The proposed quantitative analysis was reproducible with good accuracy of all individual anthocyanins ranging from 96.3 to 104.2% and relative recoveries were in the range 98.4-103.2%. The proposed technique is performed without anthocyanin standards and is a simple, rapid, accurate, and economical method to determine individual anthocyanin contents. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  16. An image-processing method to detect sub-optical features based on understanding noise in intensity measurements.

    Science.gov (United States)

    Bhatia, Tripta

    2018-02-01

    Accurate quantitative analysis of image data requires that we distinguish between fluorescence intensity (true signal) and the noise inherent to its measurements to the extent possible. We image multilamellar membrane tubes and beads that grow from defects in the fluid lamellar phase of the lipid 1,2-dioleoyl-sn-glycero-3-phosphocholine dissolved in water and water-glycerol mixtures by using fluorescence confocal polarizing microscope. We quantify image noise and determine the noise statistics. Understanding the nature of image noise also helps in optimizing image processing to detect sub-optical features, which would otherwise remain hidden. We use an image-processing technique "optimum smoothening" to improve the signal-to-noise ratio of features of interest without smearing their structural details. A high SNR renders desired positional accuracy with which it is possible to resolve features of interest with width below optical resolution. Using optimum smoothening, the smallest and the largest core diameter detected is of width [Formula: see text] and [Formula: see text] nm, respectively, discussed in this paper. The image-processing and analysis techniques and the noise modeling discussed in this paper can be used for detailed morphological analysis of features down to sub-optical length scales that are obtained by any kind of fluorescence intensity imaging in the raster mode.

  17. Benchmark test cases for evaluation of computer-based methods for detection of setup errors: realistic digitally reconstructed electronic portal images with known setup errors

    International Nuclear Information System (INIS)

    Fritsch, Daniel S.; Raghavan, Suraj; Boxwala, Aziz; Earnhart, Jon; Tracton, Gregg; Cullip, Timothy; Chaney, Edward L.

    1997-01-01

    Purpose: The purpose of this investigation was to develop methods and software for computing realistic digitally reconstructed electronic portal images with known setup errors for use as benchmark test cases for evaluation and intercomparison of computer-based methods for image matching and detecting setup errors in electronic portal images. Methods and Materials: An existing software tool for computing digitally reconstructed radiographs was modified to compute simulated megavoltage images. An interface was added to allow the user to specify which setup parameter(s) will contain computer-induced random and systematic errors in a reference beam created during virtual simulation. Other software features include options for adding random and structured noise, Gaussian blurring to simulate geometric unsharpness, histogram matching with a 'typical' electronic portal image, specifying individual preferences for the appearance of the 'gold standard' image, and specifying the number of images generated. The visible male computed tomography data set from the National Library of Medicine was used as the planning image. Results: Digitally reconstructed electronic portal images with known setup errors have been generated and used to evaluate our methods for automatic image matching and error detection. Any number of different sets of test cases can be generated to investigate setup errors involving selected setup parameters and anatomic volumes. This approach has proved to be invaluable for determination of error detection sensitivity under ideal (rigid body) conditions and for guiding further development of image matching and error detection methods. Example images have been successfully exported for similar use at other sites. Conclusions: Because absolute truth is known, digitally reconstructed electronic portal images with known setup errors are well suited for evaluation of computer-aided image matching and error detection methods. High-quality planning images, such as

  18. APPLICATION OF THE SPECTROMETRIC METHOD FOR CALCULATING THE DOSE RATE FOR CREATING CALIBRATION HIGHLY SENSITIVE INSTRUMENTS BASED ON SCINTILLATION DETECTION UNITS

    Directory of Open Access Journals (Sweden)

    R. V. Lukashevich

    2017-01-01

    Full Text Available Devices based on scintillation detector are highly sensitive to photon radiation and are widely used to measure the environment dose rate. Modernization of the measuring path to minimize the error in measuring the response of the detector to gamma radiation has already reached its technological ceiling and does not give the proper effect. More promising for this purpose are new methods of processing the obtained spectrometric information. The purpose of this work is the development of highly sensitive instruments based on scintillation detection units using a spectrometric method for calculating dose rate.In this paper we consider the spectrometric method of dosimetry of gamma radiation based on the transformation of the measured instrumental spectrum. Using predetermined or measured functions of the detector response to the action of gamma radiation of a given energy and flux density, a certain function of the energy G(E is determined. Using this function as the core of the integral transformation from the field to dose characteristic, it is possible to obtain the dose value directly from the current instrumentation spectrum. Applying the function G(E to the energy distribution of the fluence of photon radiation in the environment, the total dose rate can be determined without information on the distribution of radioisotopes in the environment.To determine G(E by Monte-Carlo method instrumental response function of the scintillator detector to monoenergetic photon radiation sources as well as other characteristics are calculated. Then the whole full-scale energy range is divided into energy ranges for which the function G(E is calculated using a linear interpolation.Spectrometric method for dose calculation using the function G(E, which allows the use of scintillation detection units for a wide range of dosimetry applications is considered in the article. As well as describes the method of calculating this function by using Monte-Carlo methods

  19. Statistical methods for detecting and comparing periodic data and their application to the nycthemeral rhythm of bodily harm: A population based study

    LENUS (Irish Health Repository)

    Stroebel, Armin M

    2010-11-08

    Abstract Background Animals, including humans, exhibit a variety of biological rhythms. This article describes a method for the detection and simultaneous comparison of multiple nycthemeral rhythms. Methods A statistical method for detecting periodic patterns in time-related data via harmonic regression is described. The method is particularly capable of detecting nycthemeral rhythms in medical data. Additionally a method for simultaneously comparing two or more periodic patterns is described, which derives from the analysis of variance (ANOVA). This method statistically confirms or rejects equality of periodic patterns. Mathematical descriptions of the detecting method and the comparing method are displayed. Results Nycthemeral rhythms of incidents of bodily harm in Middle Franconia are analyzed in order to demonstrate both methods. Every day of the week showed a significant nycthemeral rhythm of bodily harm. These seven patterns of the week were compared to each other revealing only two different nycthemeral rhythms, one for Friday and Saturday and one for the other weekdays.

  20. A new amperometric method for rapid detection of Escherichia coli density using a self-assembled monolayer-based bienzyme biosensor

    International Nuclear Information System (INIS)

    Tang Hui; Zhang Wen; Geng Ping; Wang Qingjiang; Jin Litong; Wu Zirong; Lou Min

    2006-01-01

    A new amperometric method was developed for rapid detection of Escherichia coli (E. coli) density using a bienzyme biosensor. The bienzyme biosensor was fabricated based on the covalent immobilization of laccase and horseradish peroxidase (HRP) at indium tin oxide (ITO) electrode by (3-aminopropyl) triethoxysilane (APTES) monolayer. The bienzyme biosensor showed a high sensitivity in determination of the polyphenolic compounds, which was microbially generated from the salicylic acid (SA) added into the culture medium during the course of E. coli metabolism. Since the amount of polyphenolic compounds depends on E. coli density, the bienzyme biosensor was applied for the rapid and high sensitive detection of E. coli density after the E. coli solution was incubated in culture medium with salicylic acid for 2.5 h at 37 deg. C. By chronoamperometry, the amplified response current was obtained at the bienzyme biosensor, due to the substrate recycling of the polyphenolic compounds driven by bienzyme-catalyzed oxidation and electrochemical reduction. The amplified response current at the biosensor was linear with the E. coli density ranging from 1.6 x 10 3 to 1.0 x 10 7 cells/mL. The bienzyme biosensor could detect the E. coli density with a detection limit of 9.7 x 10 2 cells/mL within 3 h

  1. PCR method for the rapid detection and discrimination of Legionella spp. based on the amplification of pcs, pmtA, and 16S rRNA genes.

    Science.gov (United States)

    Janczarek, Monika; Palusińska-Szysz, Marta

    2016-05-01

    Legionella bacteria are organisms of public health interest due to their ability to cause pneumonia (Legionnaires' disease) in susceptible humans and their ubiquitous presence in water supply systems. Rapid diagnosis of Legionnaires' disease allows the use of therapy specific for the disease. L. pneumophila serogroup 1 is the most common cause of infection acquired in community and hospital environments. The non-L. pneumophila infections are likely under-detected because of a lack of effective diagnosis. In this work, simplex and duplex PCR assays with the use of new molecular markers pcs and pmtA involved in phosphatidylcholine synthesis were specified for rapid and cost-efficient identification and distinguishing Legionella species. The sets of primers developed were found to be sensitive and specific for reliable detection of Legionella belonging to the eight most clinically relevant species. Among these, four primer sets I, II, VI, and VII used for duplex-PCRs proved to have the highest identification power and reliability in the detection of the bacteria. Application of this PCR-based method should improve detection of Legionella spp. in both clinical and environmental settings and facilitate molecular typing of these organisms.

  2. Culture-Based Methods and Molecular Tools for Azole-Resistant Aspergillus fumigatus Detection in a Belgian University Hospital

    OpenAIRE

    Montesinos, I.; Argudín, M. A.; Hites, M.; Ahajjam, F.; Dodémont, M.; Dagyaran, C.; Bakkali, M.; Etienne, I.; Jacobs, F.; Knoop, C.; Patteet, S.; Lagrou, K.

    2017-01-01

    Azole-resistant Aspergillus fumigatus is an increasing worldwide problem with major clinical implications. Surveillance is warranted to guide clinicians to provide optimal treatment to patients. To investigate azole resistance in clinical Aspergillus isolates in our institution, a Belgian university hospital, we conducted a laboratory-based surveillance between June 2015 and October 2016. Two different approaches were used: a prospective culture-based surveillance using VIPcheck on unselected...

  3. Development of a Novel Method to Detect Prostate Cancer Circulating Tumor Cells (CTCs) Based on Epithelial-Mesenchymal Transition Biology

    Science.gov (United States)

    2015-12-01

    prostate cancer162. Other immunomagnetic-based systems, such as the AdnaTest (AdnaGen, Langenhagen, Germany ), MagSweeper Table 1. CTC enrichment based on...of p53 is common in metastatic PC, and loss of p53 function may promote EMT through TWIST1 deregulation , or through a separate pathway involving...microRNA deregulation [55]. Inhibitor of differentiation/DNA binding (Id-1) is another bHLH transcription factor that has a dominant negative effect on

  4. Elucidation of Listeria monocytogenes contamination routes in cold-smoked salmon processing plants detected by DNA-based typing methods

    DEFF Research Database (Denmark)

    Vogel, Birte Fonnesbech; Huss, Hans Henrik; Ojeniyi, B.

    2001-01-01

    and environment could not be excluded. Contamination of the product occurred in specific areas (the brining and slicing areas). In plant I, the same RAPD type (RAPD type 12) was found over a 4-year period, indicating that an established in-house flora persisted and was not eliminated by routine hygienic......, monocytogenes). A total of 429 strains of L. monocytogenes were subsequently compared by random amplified polymorphic DNA (RAPD) profiling, and 55 different RAPD types were found. The RAPD types detected on the products were identical to types found on the processing equipment and in the processing environment...... procedures. In plant II, where the prevalence of L, monocytogenes was much tower, no RAPD type persisted over long periods of time, and several different L, monocytogenes RAPD types were isolated. This indicates that persistent strains may be avoided by rigorous cleaning and sanitation; however, due...

  5. Detecting sea-level hazards: Simple regression-based methods for calculating the acceleration of sea level

    Science.gov (United States)

    Doran, Kara S.; Howd, Peter A.; Sallenger,, Asbury H.

    2016-01-04

    This report documents the development of statistical tools used to quantify the hazard presented by the response of sea-level elevation to natural or anthropogenic changes in climate and ocean circulation. A hazard is a physical process (or processes) that, when combined with vulnerability (or susceptibility to the hazard), results in risk. This study presents the development and comparison of new and existing sea-level analysis methods, exploration of the strengths and weaknesses of the methods using synthetic time series, and when appropriate, synthesis of the application of the method to observed sea-level time series. These reports are intended to enhance material presented in peer-reviewed journal articles where it is not always possible to provide the level of detail that might be necessary to fully support or recreate published results.

  6. Detection of concrete dam leakage using an integrated geophysical technique based on flow-field fitting method

    Science.gov (United States)

    Dai, Qianwei; Lin, Fangpeng; Wang, Xiaoping; Feng, Deshan; Bayless, Richard C.

    2017-05-01

    An integrated geophysical investigation was performed at S dam located at Dadu basin in China to assess the condition of the dam curtain. The key methodology of the integrated technique used was flow-field fitting method, which allowed identification of the hydraulic connections between the dam foundation and surface water sources (upstream and downstream), and location of the anomalous leakage outlets in the dam foundation. Limitations of the flow-field fitting method were complemented with resistivity logging to identify the internal erosion which had not yet developed into seepage pathways. The results of the flow-field fitting method and resistivity logging were consistent when compared with data provided by seismic tomography, borehole television, water injection test, and rock quality designation.

  7. Optimization of a 12-hour TaqMan PCR-based method for detection of Salmonella bacteria in meat

    DEFF Research Database (Denmark)

    Josefsen, Mathilde Hartmann; Krause, Michael; Hansen, F.

    2007-01-01

    no positive effects and resulted in decreased reproducibility. Increasing the amount of PCR template DNA from 5 to 20 mu l improved the threshold cycle value by approximately 2. The improved 12-h PCR method was successfully compared to a reference culture method with 100 minced meat and poultry samples...... the highest number of salmonellae. When analyzing minced meat samples, positive effects of increasing the initial sampling volume from 1 to 5 ml and increasing the amount of paramagnetic particles to 90 mu l were observed. However, washing the pellet and eluting the DNA in reduced volumes (25 and 50 mu l) had...

  8. Sensing Methods for Detecting Analog Television Signals

    Science.gov (United States)

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

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

  9. A detection method of vegetable oils in edible blended oil based on three-dimensional fluorescence spectroscopy technique.

    Science.gov (United States)

    Xu, Jing; Liu, Xiao-Fei; Wang, Yu-Tian

    2016-12-01

    Edible blended vegetable oils are made from two or more refined oils. Blended oils can provide a wider range of essential fatty acids than single vegetable oils, which helps support good nutrition. Nutritional components in blended oils are related to the type and content of vegetable oils used, and a new, more accurate, method is proposed to identify and quantify the vegetable oils present using cluster analysis and a Quasi-Monte Carlo integral. Three-dimensional fluorescence spectra were obtained at 250-400nm (excitation) and 260-750nm (emission). Mixtures of sunflower, soybean and peanut oils were used as typical examples to validate the effectiveness of the method. Copyright © 2016 Elsevier Ltd. All rights reserved.

  10. Measurement agreement between a newly developed sensing insole and traditional laboratory-based method for footstrike pattern detection in runners

    OpenAIRE

    Cheung, Roy T. H.; An, Winko W.; Au, Ivan P. H.; Zhang, Janet H.; Chan, Zoe Y. S.; Man, Alfred; Lau, Fannie O. Y.; Lam, Melody K. Y.; Lau, K. K.; Leung, C. Y.; Tsang, N. W.; Sze, Louis K. Y.; Lam, Gilbert W. K.

    2017-01-01

    This study introduced a novel but simple method to continuously measure footstrike patterns in runners using inexpensive force sensors. Two force sensing resistors were firmly affixed at the heel and second toe of both insoles to collect the time signal of foot contact. A total of 109 healthy young adults (42 males and 67 females) were recruited in this study. They ran on an instrumented treadmill at 0°, +10°, and -10° inclinations and attempted rearfoot, midfoot, and forefoot landings using ...

  11. A Versatile Method to Design Stem-Loop Primer-Based Quantitative PCR Assays for Detecting Small Regulatory RNA Molecules

    OpenAIRE

    Czimmerer, Zsolt; Hulvely, Julianna; Simandi, Zoltan; Varallyay, Eva; Havelda, Zoltan; Szabo, Erzsebet; Varga, Attila; Dezso, Balazs; Balogh, Maria; Horvath, Attila; Domokos, Balint; Torok, Zsolt; Nagy, Laszlo; Balint, Balint L.

    2013-01-01

    Short regulatory RNA-s have been identified as key regulators of gene expression in eukaryotes. They have been involved in the regulation of both physiological and pathological processes such as embryonal development, immunoregulation and cancer. One of their relevant characteristics is their high stability, which makes them excellent candidates for use as biomarkers. Their number is constantly increasing as next generation sequencing methods reveal more and more details of their synthesis. T...

  12. Regression toward the mean – a detection method for unknown population mean based on Mee and Chua's algorithm

    Directory of Open Access Journals (Sweden)

    Lüdtke Rainer

    2008-08-01

    Full Text Available Abstract Background Regression to the mean (RTM occurs in situations of repeated measurements when extreme values are followed by measurements in the same subjects that are closer to the mean of the basic population. In uncontrolled studies such changes are likely to be interpreted as a real treatment effect. Methods Several statistical approaches have been developed to analyse such situations, including the algorithm of Mee and Chua which assumes a known population mean μ. We extend this approach to a situation where μ is unknown and suggest to vary it systematically over a range of reasonable values. Using differential calculus we provide formulas to estimate the range of μ where treatment effects are likely to occur when RTM is present. Results We successfully applied our method to three real world examples denoting situations when (a no treatment effect can be confirmed regardless which μ is true, (b when a treatment effect must be assumed independent from the true μ and (c in the appraisal of results of uncontrolled studies. Conclusion Our method can be used to separate the wheat from the chaff in situations, when one has to interpret the results of uncontrolled studies. In meta-analysis, health-technology reports or systematic reviews this approach may be helpful to clarify the evidence given from uncontrolled observational studies.

  13. A non-destructive surface burn detection method for ferrous metals based on acoustic emission and ensemble empirical mode decomposition: from laser simulation to grinding process

    International Nuclear Information System (INIS)

    Yang, Zhensheng; Wu, Haixi; Yu, Zhonghua; Huang, Youfang

    2014-01-01

    Grinding is usually done in the final finishing of a component. As a result, the surface quality of finished products, e.g., surface roughness, hardness and residual stress, are affected by the grinding procedure. However, the lack of methods for monitoring of grinding makes it difficult to control the quality of the process. This paper focuses on the monitoring approaches for the surface burn phenomenon in grinding. A non-destructive burn detection method based on acoustic emission (AE) and ensemble empirical mode decomposition (EEMD) was proposed for this purpose. To precisely extract the AE features caused by phase transformation during burn formation, artificial burn was produced to mimic grinding burn by means of laser irradiation, since laser-induced burn involves less mechanical and electrical noise. The burn formation process was monitored by an AE sensor. The frequency band ranging from 150 to 400 kHz was believed to be related to surface burn formation in the laser irradiation process. The burn-sensitive frequency band was further used to instruct feature extraction during the grinding process based on EEMD. Linear classification results evidenced a distinct margin between samples with and without surface burn. This work provides a practical means for grinding burn detection. (paper)

  14. A safer, urea-based in situ hybridization method improves detection of gene expression in diverse animal species.

    Science.gov (United States)

    Sinigaglia, Chiara; Thiel, Daniel; Hejnol, Andreas; Houliston, Evelyn; Leclère, Lucas

    2018-02-01

    In situ hybridization is a widely employed technique allowing spatial visualization of gene expression in fixed specimens. It has greatly advanced our understanding of biological processes, including developmental regulation. In situ protocols are today routinely followed in numerous laboratories, and although details might change, they all include a hybridization step, where specific antisense RNA or DNA probes anneal to the target nucleic acid sequence. This step is generally carried out at high temperatures and in a denaturing solution, called hybridization buffer, commonly containing 50% (v/v) formamide - a hazardous chemical. When applied to the soft-bodied hydrozoan medusa Clytia hemisphaerica, we found that this traditional hybridization approach was not fully satisfactory, causing extensive deterioration of morphology and tissue texture which compromised our observation and interpretation of results. We thus tested alternative solutions for in situ detection of gene expression and, inspired by optimized protocols for Northern and Southern blot analysis, we substituted the 50% formamide with an equal volume of 8M urea solution in the hybridization buffer. Our new protocol not only yielded better morphologies and tissue consistency, but also notably improved the resolution of the signal, allowing more precise localization of gene expression and reducing aspecific staining associated with problematic areas. Given the improved results and reduced manipulation risks, we tested the urea protocol on other metazoans, two brachiopod species (Novocrania anomala and Terebratalia transversa) and the priapulid worm Priapulus caudatus, obtaining a similar reduction of aspecific probe binding. Overall, substitution of formamide by urea during in situ hybridization offers a safer alternative, potentially of widespread use in research, medical and teaching contexts. We encourage other workers to test this approach on their study organisms, and hope that they will also

  15. Efficient sample preparation method based on solvent-assisted dispersive solid-phase extraction for the trace detection of butachlor in urine and waste water samples.

    Science.gov (United States)

    Aladaghlo, Zolfaghar; Fakhari, Alireza; Behbahani, Mohammad

    2016-10-01

    In this work, an efficient sample preparation method termed solvent-assisted dispersive solid-phase extraction was applied. The used sample preparation method was based on the dispersion of the sorbent (benzophenone) into the aqueous sample to maximize the interaction surface. In this approach, the dispersion of the sorbent at a very low milligram level was achieved by inserting a solution of the sorbent and disperser solvent into the aqueous sample. The cloudy solution created from the dispersion of the sorbent in the bulk aqueous sample. After pre-concentration of the butachlor, the cloudy solution was centrifuged and butachlor in the sediment phase dissolved in ethanol and determined by gas chromatography with flame ionization detection. Under the optimized conditions (solution pH = 7.0, sorbent: benzophenone, 2%, disperser solvent: ethanol, 500 μL, centrifuged at 4000 rpm for 3 min), the method detection limit for butachlor was 2, 3 and 3 μg/L for distilled water, waste water, and urine sample, respectively. Furthermore, the preconcentration factor was 198.8, 175.0, and 174.2 in distilled water, waste water, and urine sample, respectively. Solvent-assisted dispersive solid-phase extraction was successfully used for the trace monitoring of butachlor in urine and waste water samples. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  16. Validation of a an analysis method of Marine Bio toxins Type Saxitoxin based on test coupled receptor (RBA) with Radiochemical Detection with liquid scintillation

    International Nuclear Information System (INIS)

    Selmi, Zied

    2009-01-01

    The saxitoxin s are bio toxins belonging to the family of toxins of the type PSP. They are paralysing toxins secreted by marine micro-organisms, phytoplankton, called Alexandrium. They constitute a risk for the human health in the event of their consumption in contaminated food. The acceptable maximum limit of these bio toxins in molluscs and shellfish is fixed to 800 μg /kg of meat of molluscs or shellfish. It proves, thus, that it is essential to develop and validate analytical methods for the level monitoring of contamination of the marine resources by these species in order to found a program of their monitoring and to guarantee an acceptable level of the food safety of the products available on the national and international markets. The present work allowed the validation of the quantification method of these toxins which is based on the use of the Receptor Binding Assay (RBA) with liquid scintillation nuclear technique detection using tritium as radiotracer and while proceeding by the different statistical tests of validation (Standard Nf XP T 90-210). The field of linearity ranged from 0 to 20 n M and the limit of detection was found to be 1 n M. The validation of this method will allow the reinforcement of the analytical means of analysis of marine bi toxins type SXT and to set up, in the near future, a monitoring and surveillance routine program for these bio toxins at the national, regional and African scales. (Author)

  17. Gold nanoparticles-based electrochemical method for the detection of protein kinase with a peptide-like inhibitor as the bioreceptor

    Directory of Open Access Journals (Sweden)

    Sun K

    2017-03-01

    Full Text Available Kai Sun, Yong Chang, Binbin Zhou, Xiaojin Wang, Lin Liu Henan Province of Key Laboratory of New Optoelectronic Functional Materials, College of Chemistry and Chemical Engineering, Anyang Normal University, Anyang, Henan, People’s Republic of China Abstract: This article presents a general method for the detection of protein kinase with a peptide-like kinase inhibitor as the bioreceptor, and it was done by converting gold nanoparticles (AuNPs-based colorimetric assay into sensitive electrochemical analysis. In the colorimetric assay, the kinase-specific aptameric peptide triggered the aggregation of AuNPs in solution. However, the specific binding of peptide to the target protein (kinase inhibited its ability to trigger the assembly of AuNPs. In the electrochemical analysis, peptides immobilized on a gold electrode and presented as solution triggered together the in situ formation of AuNPs-based network architecture on the electrode surface. Nevertheless, the formation of peptide–kinase complex on the electrode surface made the peptide-triggered AuNPs assembly difficult. Electrochemical impedance spectroscopy was used to measure the change in surface property in the binding events. When a ferrocene-labeled peptide (Fc-peptide was used in this design, the network of AuNPs/Fc-peptide produced a good voltammetric signal. The competitive assay allowed for the detection of protein kinase A with a detection limit of 20 mU/mL. This work should be valuable for designing novel optical or electronic biosensors and likely lead to many detection applications. Keywords: electrochemical biosensor, colorimetric assay, gold nanoparticle, aptameric peptide, protein kinase A, signal amplification 

  18. The power of gene-based rare variant methods to detect disease-associated variation and test hypotheses about complex disease.

    Directory of Open Access Journals (Sweden)

    Loukas Moutsianas

    2015-04-01

    Full Text Available Genome and exome sequencing in large cohorts enables characterization of the role of rare variation in complex diseases. Success in this endeavor, however, requires investigators to test a diverse array of genetic hypotheses which differ in the number, frequency and effect sizes of underlying causal variants. In this study, we evaluated the power of gene-based association methods to interrogate such hypotheses, and examined the implications for study design. We developed a flexible simulation approach, using 1000 Genomes data, to (a generate sequence variation at human genes in up to 10K case-control samples, and (b quantify the statistical power of a panel of widely used gene-based association tests under a variety of allelic architectures, locus effect sizes, and significance thresholds. For loci explaining ~1% of phenotypic variance underlying a common dichotomous trait, we find that all methods have low absolute power to achieve exome-wide significance (~5-20% power at α = 2.5 × 10(-6 in 3K individuals; even in 10K samples, power is modest (~60%. The combined application of multiple methods increases sensitivity, but does so at the expense of a higher false positive rate. MiST, SKAT-O, and KBAC have the highest individual mean power across simulated datasets, but we observe wide architecture-dependent variability in the individual loci detected by each test, suggesting that inferences about disease architecture from analysis of sequencing studies can differ depending on which methods are used. Our results imply that tens of thousands of individuals, extensive functional annotation, or highly targeted hypothesis testing will be required to confidently detect or exclude rare variant signals at complex disease loci.

  19. Detection of food irradiation with luminescence methods

    International Nuclear Information System (INIS)

    Anderle, H.

    1997-06-01

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

  20. Novel Methods of Hydrogen Leak Detection

    International Nuclear Information System (INIS)

    Pushpinder S Puri

    2006-01-01

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

  1. Application of microarray and functional-based screening methods for the detection of antimicrobial resistance genes in the microbiomes of healthy humans.

    Directory of Open Access Journals (Sweden)

    Roderick M Card

    Full Text Available The aim of this study was to screen for the presence of antimicrobial resistance genes within the saliva and faecal microbiomes of healthy adult human volunteers from five European countries. Two non-culture based approaches were employed to obviate potential bias associated with difficult to culture members of the microbiota. In a gene target-based approach, a microarray was employed to screen for the presence of over 70 clinically important resistance genes in the saliva and faecal microbiomes. A total of 14 different resistance genes were detected encoding resistances to six antibiotic classes (aminoglycosides, β-lactams, macrolides, sulphonamides, tetracyclines and trimethoprim. The most commonly detected genes were erm(B, blaTEM, and sul2. In a functional-based approach, DNA prepared from pooled saliva samples was cloned into Escherichia coli and screened for expression of resistance to ampicillin or sulphonamide, two of the most common resistances found by array. The functional ampicillin resistance screen recovered genes encoding components of a predicted AcrRAB efflux pump. In the functional sulphonamide resistance screen, folP genes were recovered encoding mutant dihydropteroate synthase, the target of sulphonamide action. The genes recovered from the functional screens were from the chromosomes of commensal species that are opportunistically pathogenic and capable of exchanging DNA with related pathogenic species. Genes identified by microarray were not recovered in the activity-based screen, indicating that these two methods can be complementary in facilitating the identification of a range of resistance mechanisms present within the human microbiome. It also provides further evidence of the diverse reservoir of resistance mechanisms present in bacterial populations in the human gut and saliva. In future the methods described in this study can be used to monitor changes in the resistome in response to antibiotic therapy.

  2. a Novel Ship Detection Method for Large-Scale Optical Satellite Images Based on Visual Lbp Feature and Visual Attention Model

    Science.gov (United States)

    Haigang, Sui; Zhina, Song

    2016-06-01

    Reliably ship detection in optical satellite images has a wide application in both military and civil fields. However, this problem is very difficult in complex backgrounds, such as waves, clouds, and small islands. Aiming at these issues, this paper explores an automatic and robust model for ship detection in large-scale optical satellite images, which relies on detecting statistical signatures of ship targets, in terms of biologically-inspired visual features. This model first selects salient candidate regions across large-scale images by using a mechanism based on biologically-inspired visual features, combined with visual attention model with local binary pattern (CVLBP). Different from traditional studies, the proposed algorithm is high-speed and helpful to focus on the suspected ship areas avoiding the separation step of land and sea. Largearea images are cut into small image chips and analyzed in two complementary ways: Sparse saliency using visual attention model and detail signatures using LBP features, thus accordant with sparseness of ship distribution on images. Then these features are employed to classify each chip as containing ship targets or not, using a support vector machine (SVM). After getting the suspicious areas, there are still some false alarms such as microwaves and small ribbon clouds, thus simple shape and texture analysis are adopted to distinguish between ships and nonships in suspicious areas. Experimental results show the proposed method is insensitive to waves, clouds, illumination and ship size.

  3. Direct Index Method of Beam Damage Location Detection Based on Difference Theory of Strain Modal Shapes and the Genetic Algorithms Application

    Directory of Open Access Journals (Sweden)

    Bao Zhenming

    2012-01-01

    Full Text Available Structural damage identification is to determine the structure health status and analyze the test results. The three key problems to be solved are as follows: the existence of damage in structure, to detect the damage location, and to confirm the damage degree or damage form. Damage generally changes the structure physical properties (i.e., stiffness, mass, and damping corresponding with the modal characteristics of the structure (i.e., natural frequencies, modal shapes, and modal damping. The research results show that strain mode can be more sensitive and effective for local damage. The direct index method of damage location detection is based on difference theory, without the modal parameter of the original structure. FEM numerical simulation to partial crack with different degree is done. The criteria of damage location detection can be obtained by strain mode difference curve through cubic spline interpolation. Also the genetic algorithm box in Matlab is used. It has been possible to identify the damage to a reasonable level of accuracy.

  4. Heart murmur detection based on wavelet transformation and a synergy between artificial neural network and modified neighbor annealing methods.

    Science.gov (United States)

    Eslamizadeh, Gholamhossein; Barati, Ramin

    2017-05-01

    Early recognition of heart disease plays a vital role in saving lives. Heart murmurs are one of the common heart problems. In this study, Artificial Neural Network (ANN) is trained with Modified Neighbor Annealing (MNA) to classify heart cycles into normal and murmur classes. Heart cycles are separated from heart sounds using wavelet transformer. The network inputs are features extracted from individual heart cycles, and two classification outputs. Classification accuracy of the proposed model is compared with five multilayer perceptron trained with Levenberg-Marquardt, Extreme-learning-machine, back-propagation, simulated-annealing, and neighbor-annealing algorithms. It is also compared with a Self-Organizing Map (SOM) ANN. The proposed model is trained and tested using real heart sounds available in the Pascal database to show the applicability of the proposed scheme. Also, a device to record real heart sounds has been developed and used for comparison purposes too. Based on the results of this study, MNA can be used to produce considerable results as a heart cycle classifier. Copyright © 2017 Elsevier B.V. All rights reserved.

  5. A liquid chromatography-mass spectrometry method based on class characteristic fragmentation pathways to detect the class of indole-derivative synthetic cannabinoids in biological samples.

    Science.gov (United States)

    Mazzarino, Monica; de la Torre, Xavier; Botrè, Francesco

    2014-07-21

    This article describes a liquid chromatographic/tandem mass spectrometric method, based on the use of precursor ion scan as the acquisition mode, specifically developed to detect indole-derived cannabinoids (phenylacetylindoles, naphthoylindoles and benzoylindoles) in biological fluids (saliva, urine and blood). The method is designed to recognize one or more common "structural markers", corresponding to mass spectral fragments originating from the specific portion of the molecular structure that is common to the aminoalkylindole analogues and that is fundamental for their pharmacological classification. As such, the method is also suitable for detecting unknown substances, provided they contain the targeted portion of the molecular structure. The pre-treatment procedure consists in a liquid/liquid extraction step carried out at neutral pH: this is the only pretreatment in the case of analyses carried out in saliva, while it follows an enzymatic hydrolysis procedure in the case of urine samples, or a protein precipitation step in the case of blood samples. The chromatographic separation is achieved using an octadecyl reverse-phase 5 μm fused-core particle column; while the mass spectrometric detection is carried out by a triple-quadrupole instrument in positive electrospray ionization and precursor ion scan as acquisition mode, selecting, as mass spectral fragments, the indole (m/z 144), the carbonylnaphthalenyl (m/z 155) and the naphthalenyl (m/z 127) moieties. Once developed and optimized, the analytical procedure was validated in term of sensitivity (lower limits of detection in the range of 0.1-0.5 ng mL(-1)), specificity (no interference was detected at the retention times of the analytes under investigation), recovery (higher than 65% with a satisfactory repeatability: CV% lower than 10), matrix effect (lower than 30% for all the biological specimens tested), repeatability of the retention times (CV% lower than 0.1), robustness, and carry over (the positive

  6. Early Detection of Alzheimer's Disease Based on the Patient's Creative Drawing Process: First Results with a Novel Neuropsychological Testing Method.

    Science.gov (United States)

    Heymann, Petra; Gienger, Regine; Hett, Andreas; Müller, Stephan; Laske, Christoph; Robens, Sibylle; Ostermann, Thomas; Elbing, Ulrich

    2018-01-01

    Based on the knowledge of art therapy, we developed a new neuropsychological drawing test in order to identify individuals with mild cognitive impairment (MCI) as well as dementia patients and healthy controls (HC). By observing a variety of drawing characteristics of 92 participants with a mean age of 67.7, art therapy and dementia experts discriminate HC from MCI, early dementia of the Alzheimer-type (eDAT), and moderate dementia of the Alzheimer-type (mDAT) by the process analysis of tree drawings on a digitizing tablet. The art therapist's average categorical rating of healthy and MCI or demented individuals matched the clinical diagnosis by 88%. In a first small study, we analyzed interrater reliability, sensitivity, specificity, negative and positive predicted values of our tree drawing test (TDT) in comparison with the clock drawing test (CDT). Similar values of moderate interrater reliability were found for the TDT (0.56) as well as for the CDT (0.54). A significant high sensitivity of 0.9 within this binary impairment scale (HC versus impaired or demented) can be demonstrated. Substantial values for the specificity (0.67) could be obtained that however remain under a perfect value of the CDT (1.0). Considering 31 individuals that received the clinical diagnosis "impaired or demented" the TDT shows a higher recognition rate for the MCI group than the CDT. Furthermore in 8 of 12 borderline cases of clinical diagnosis, the outcome of the TDT diagnosis was consistent with the final clinical result.

  7. Material detection method and device

    International Nuclear Information System (INIS)

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

    1994-01-01

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

  8. Computer-aided diagnostic scheme for the detection of lung nodules on chest radiographs: Localized search method based on anatomical classification

    International Nuclear Information System (INIS)

    Shiraishi, Junji; Li Qiang; Suzuki, Kenji; Engelmann, Roger; Doi, Kunio

    2006-01-01

    We developed an advanced computer-aided diagnostic (CAD) scheme for the detection of various types of lung nodules on chest radiographs intended for implementation in clinical situations. We used 924 digitized chest images (992 noncalcified nodules) which had a 500x500 matrix size with a 1024 gray scale. The images were divided randomly into two sets which were used for training and testing of the computerized scheme. In this scheme, the lung field was first segmented by use of a ribcage detection technique, and then a large search area (448x448 matrix size) within the chest image was automatically determined by taking into account the locations of a midline and a top edge of the segmented ribcage. In order to detect lung nodule candidates based on a localized search method, we divided the entire search area into 7x7 regions of interest (ROIs: 64x64 matrix size). In the next step, each ROI was classified anatomically into apical, peripheral, hilar, and diaphragm/heart regions by use of its image features. Identification of lung nodule candidates and extraction of image features were applied for each localized region (128x128 matrix size), each having its central part (64x64 matrix size) located at a position corresponding to a ROI that was classified anatomically in the previous step. Initial candidates were identified by use of the nodule-enhanced image obtained with the average radial-gradient filtering technique, in which the filter size was varied adaptively depending on the location and the anatomical classification of the ROI. We extracted 57 image features from the original and nodule-enhanced images based on geometric, gray-level, background structure, and edge-gradient features. In addition, 14 image features were obtained from the corresponding locations in the contralateral subtraction image. A total of 71 image features were employed for three sequential artificial neural networks (ANNs) in order to reduce the number of false-positive candidates. All

  9. Improved GLR method to instrument failure detection

    International Nuclear Information System (INIS)

    Jeong, Hak Yeoung; Chang, Soon Heung

    1985-01-01

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

  10. A Method to Detect AAC Audio Forgery

    Directory of Open Access Journals (Sweden)

    Qingzhong Liu

    2015-08-01

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

  11. In silico and experimental evaluation of DNA-based detection methods for the ability to discriminate almond from other Prunus spp.

    Science.gov (United States)

    Brežná, Barbara; Šmíd, Jiří; Costa, Joana; Radvanszky, Jan; Mafra, Isabel; Kuchta, Tomáš

    2015-04-01

    Ten published DNA-based analytical methods aiming at detecting material of almond (Prunus dulcis) were in silico evaluated for potential cross-reactivity with other stone fruits (Prunus spp.), including peach, apricot, plum, cherry, sour cherry and Sargent cherry. For most assays, the analysis of nucleotide databases suggested none or insufficient discrimination of at least some stone fruits. On the other hand, the assay targeting non-specific lipid transfer protein (Röder et al., 2011, Anal Chim Acta 685:74-83) was sufficiently discriminative, judging from nucleotide alignments. Empirical evaluation was performed for three of the published methods, one modification of a commercial kit (SureFood allergen almond) and one attempted novel method targeting thaumatin-like protein gene. Samples of leaves and kernels were used in the experiments. The empirical results were favourable for the method from Röder et al. (2011) and a modification of SureFood allergen almond kit, both showing cross-reactivity <10(-3) compared to the model almond. Copyright © 2014 Elsevier Ltd. All rights reserved.

  12. Feasibility of a molecular screening method for detection of Salmonella enterica and Campylobacter jejuni in a routine community-based clinical microbiology laboratory

    NARCIS (Netherlands)

    Schuurman, T.; de Boer, R. F.; van Zanten, E.; van Slochteren, K. R.; Scheper, H. R.; Dijk-Alberts, B. G.; Moller, A. V. M.; Kooistra-Smid, A. M. D.

    Conventional diagnostic methods for the detection of Salmonella enterica and Campylobacter jejuni are laborious and time-consuming procedures, resulting in final results, for the majority of specimens, only after 3 to 4 days. Molecular detection can improve the time to reporting of the final results

  13. Supersonic wave detection method and supersonic detection device

    International Nuclear Information System (INIS)

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

    1996-01-01

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

  14. GC ‘Multi-Analyte’ Detection Method

    Energy Technology Data Exchange (ETDEWEB)

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

    2009-07-15

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

  15. Power Consumption Based Android Malware Detection

    OpenAIRE

    Hongyu Yang; Ruiwen Tang

    2016-01-01

    In order to solve the problem that Android platform’s sand-box mechanism prevents security protection software from accessing effective information to detect malware, this paper proposes a malicious software detection method based on power consumption. Firstly, the mobile battery consumption status information was obtained, and the Gaussian mixture model (GMM) was built by using Mel frequency cepstral coefficients (MFCC). Then, the GMM was used to analyze power consumption; malicious software...

  16. Real-time PCR-based method for the rapid detection of extended RAS mutations using bridged nucleic acids in colorectal cancer.

    Science.gov (United States)

    Iida, Takao; Mizuno, Yukie; Kaizaki, Yasuharu

    2017-10-27

    Mutations in RAS and BRAF are predictors of the efficacy of anti-epidermal growth factor receptor (EGFR) therapy in patients with metastatic colorectal cancer (mCRC). Therefore, simple, rapid, cost-effective methods to detect these mutations in the clinical setting are greatly needed. In the present study, we evaluated BNA Real-time PCR Mutation Detection Kit Extended RAS (BNA Real-time PCR), a real-time PCR method that uses bridged nucleic acid clamping technology to rapidly detect mutations in RAS exons 2-4 and BRAF exon 15. Genomic DNA was extracted from 54 formalin-fixed paraffin-embedded (FFPE) tissue samples obtained from mCRC patients. Among the 54 FFPE samples, BNA Real-time PCR detected 21 RAS mutations (38.9%) and 5 BRAF mutations (9.3%), and the reference assay (KRAS Mutation Detection Kit and MEBGEN™ RASKET KIT) detected 22 RAS mutations (40.7%). The concordance rate of detected RAS mutations between the BNA Real-time PCR assay and the reference assays was 98.2% (53/54). The BNA Real-time PCR assay proved to be a more simple, rapid, and cost-effective method for detecting KRAS and RAS mutations compared with existing assays. These findings suggest that BNA Real-time PCR is a valuable tool for predicting the efficacy of early anti-EGFR therapy in mCRC patients. Copyright © 2017 Elsevier B.V. All rights reserved.

  17. Thermoluminescence method for detection of irradiated food

    International Nuclear Information System (INIS)

    Pinnioja, S.

    1998-01-01

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

  18. Thermoluminescence method for detection of irradiated food

    Energy Technology Data Exchange (ETDEWEB)

    Pinnioja, S

    1998-12-31

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

  19. Leukemia and colon tumor detection based on microarray data classification using momentum backpropagation and genetic algorithm as a feature selection method

    Science.gov (United States)

    Wisesty, Untari N.; Warastri, Riris S.; Puspitasari, Shinta Y.

    2018-03-01

    Cancer is one of the major causes of mordibility and mortality problems in the worldwide. Therefore, the need of a system that can analyze and identify a person suffering from a cancer by using microarray data derived from the patient’s Deoxyribonucleic Acid (DNA). But on microarray data has thousands of attributes, thus making the challenges in data processing. This is often referred to as the curse of dimensionality. Therefore, in this study built a system capable of detecting a patient whether contracted cancer or not. The algorithm used is Genetic Algorithm as feature selection and Momentum Backpropagation Neural Network as a classification method, with data used from the Kent Ridge Bio-medical Dataset. Based on system testing that has been done, the system can detect Leukemia and Colon Tumor with best accuracy equal to 98.33% for colon tumor data and 100% for leukimia data. Genetic Algorithm as feature selection algorithm can improve system accuracy, which is from 64.52% to 98.33% for colon tumor data and 65.28% to 100% for leukemia data, and the use of momentum parameters can accelerate the convergence of the system in the training process of Neural Network.

  20. Novel liquid chromatography method based on linear weighted regression for the fast determination of isoprostane isomers in plasma samples using sensitive tandem mass spectrometry detection.

    Science.gov (United States)

    Aszyk, Justyna; Kot, Jacek; Tkachenko, Yurii; Woźniak, Michał; Bogucka-Kocka, Anna; Kot-Wasik, Agata

    2017-04-15

    A simple, fast, sensitive and accurate methodology based on a LLE followed by liquid chromatography-tandem mass spectrometry for simultaneous determination of four regioisomers (8-iso prostaglandin F 2α , 8-iso-15(R)-prostaglandin F 2α , 11β-prostaglandin F 2α , 15(R)-prostaglandin F 2α ) in routine analysis of human plasma samples was developed. Isoprostanes are stable products of arachidonic acid peroxidation and are regarded as the most reliable markers of oxidative stress in vivo. Validation of method was performed by evaluation of the key analytical parameters such as: matrix effect, analytical curve, trueness, precision, limits of detection and limits of quantification. As a homoscedasticity was not met for analytical data, weighted linear regression was applied in order to improve the accuracy at the lower end points of calibration curve. The detection limits (LODs) ranged from 1.0 to 2.1pg/mL. For plasma samples spiked with the isoprostanes at the level of 50pg/mL, intra-and interday repeatability ranged from 2.1 to 3.5% and 0.1 to 5.1%, respectively. The applicability of the proposed approach has been verified by monitoring of isoprostane isomers level in plasma samples collected from young patients (n=8) subjected to hyperbaric hyperoxia (100% oxygen at 280kPa(a) for 30min) in a multiplace hyperbaric chamber. Copyright © 2017 Elsevier B.V. All rights reserved.

  1. A Simulation-Based Study on the Comparison of Statistical and Time Series Forecasting Methods for Early Detection of Infectious Disease Outbreaks.

    Science.gov (United States)

    Yang, Eunjoo; Park, Hyun Woo; Choi, Yeon Hwa; Kim, Jusim; Munkhdalai, Lkhagvadorj; Musa, Ibrahim; Ryu, Keun Ho

    2018-05-11

    Early detection of infectious disease outbreaks is one of the important and significant issues in syndromic surveillance systems. It helps to provide a rapid epidemiological response and reduce morbidity and mortality. In order to upgrade the current system at the Korea Centers for Disease Control and Prevention (KCDC), a comparative study of state-of-the-art techniques is required. We compared four different temporal outbreak detection algorithms: the CUmulative SUM (CUSUM), the Early Aberration Reporting System (EARS), the autoregressive integrated moving average (ARIMA), and the Holt-Winters algorithm. The comparison was performed based on not only 42 different time series generated taking into account trends, seasonality, and randomly occurring outbreaks, but also real-world daily and weekly data related to diarrhea infection. The algorithms were evaluated using different metrics. These were namely, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), F1 score, symmetric mean absolute percent error (sMAPE), root-mean-square error (RMSE), and mean absolute deviation (MAD). Although the comparison results showed better performance for the EARS C3 method with respect to the other algorithms, despite the characteristics of the underlying time series data, Holt⁻Winters showed better performance when the baseline frequency and the dispersion parameter values were both less than 1.5 and 2, respectively.

  2. A combined approach based on MAF analysis and AHP method to fault detection mapping: A case study from a gas field, southwest of Iran

    Science.gov (United States)

    Shakiba, Sima; Asghari, Omid; Khah, Nasser Keshavarz Faraj

    2018-01-01

    A combined geostatitical methodology based on Min/Max Auto-correlation Factor (MAF) analysis and Analytical Hierarchy Process (AHP) is presented to generate a suitable Fault Detection Map (FDM) through seismic attributes. Five seismic attributes derived from a 2D time slice obtained from data related to a gas field located in southwest of Iran are used including instantaneous amplitude, similarity, energy, frequency, and Fault Enhancement Filter (FEF). The MAF analysis is implemented to reduce dimension of input variables, and then AHP method is applied on three obtained de-correlated MAF factors as evidential layer. Three Decision Makers (DMs) are used to construct PCMs for determining weights of selected evidential layer. Finally, weights obtained by AHP were multiplied in normalized valued of each alternative (MAF layers) and the concluded weighted layers were integrated in order to prepare final FDM. Results proved that applying algorithm proposed in this study generate a map more acceptable than the each individual attribute and sharpen the non-surface discontinuities as well as enhancing continuity of detected faults.

  3. Odour detection methods: olfactometry and chemical sensors.

    Science.gov (United States)

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

    2011-01-01

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

  4. Odour Detection Methods: Olfactometry and Chemical Sensors

    Directory of Open Access Journals (Sweden)

    Sara Lovascio

    2011-05-01

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

  5. An accurate, specific, sensitive, high-throughput method based on a microsphere immunoassay for multiplex detection of three viruses and bacterial fruit blotch bacterium in cucurbits.

    Science.gov (United States)

    Charlermroj, Ratthaphol; Makornwattana, Manlika; Himananto, Orawan; Seepiban, Channarong; Phuengwas, Sudtida; Warin, Nuchnard; Gajanandana, Oraprapai; Karoonuthaisiri, Nitsara

    2017-09-01

    To employ a microsphere immunoassay (MIA) to simultaneously detect multiple plant pathogens (potyviruses, Watermelon silver mottle virus, Melon yellow spot virus, and Acidovorax avenae subsp. citrulli) in actual plant samples, several factors need to be optimized and rigorously validated. Here, a simple extraction method using a single extraction buffer was successfully selected to detect the four pathogens in various cucurbit samples (cucumber, cantaloupe, melon, and watermelon). The extraction method and assay performance were validated with inoculated and field cucurbit samples. The MIA showed 98-99% relative accuracy, 97-100% relative specificity and 92-100% relative sensitivity when compared to commercial ELISA kits and reverse transcription PCR. In addition, the MIA was also able to accurately detect multiple-infected field samples. The results demonstrate that one common extraction method for all tested cucurbit samples could be applied to detect multiple pathogens; avoiding the need for multiple protocols to be employed. This multiplex method can therefore be instrumental for high-throughput screening of multiple plant pathogens with many advantages such as a shorter assay time (2.5h) with single assay format, a lower cost of detection ($5 vs $19.7 for 4 pathogens/sample) and less labor requirement. Its multiplex capacity can also be expanded to detect up to 50 different pathogens upon the availability of specific antibodies. Copyright © 2017 Elsevier B.V. All rights reserved.

  6. Validation of a PCR-based method for the detection of various rendered materials in feedstuffs using a forensic DNA extraction kit.

    Science.gov (United States)

    Myers, Michael J; Yancy, Haile F; Araneta, Michael; Armour, Jennifer; Derr, Janice; Hoostelaere, Lawrence A D; Farmer, Doris; Jackson, Falana; Kiessling, William M; Koch, Henry; Lin, Huahua; Liu, Yan; Mowlds, Gabrielle; Pinero, David; Riter, Ken L; Sedwick, John; Shen, Yuelian; Wetherington, June; Younkins, Ronsha

    2006-01-01