WorldWideScience

Sample records for multi-oriented text detection

  1. Rotation-invariant features for multi-oriented text detection in natural images.

    Directory of Open Access Journals (Sweden)

    Cong Yao

    Full Text Available Texts in natural scenes carry rich semantic information, which can be used to assist a wide range of applications, such as object recognition, image/video retrieval, mapping/navigation, and human computer interaction. However, most existing systems are designed to detect and recognize horizontal (or near-horizontal texts. Due to the increasing popularity of mobile-computing devices and applications, detecting texts of varying orientations from natural images under less controlled conditions has become an important but challenging task. In this paper, we propose a new algorithm to detect texts of varying orientations. Our algorithm is based on a two-level classification scheme and two sets of features specially designed for capturing the intrinsic characteristics of texts. To better evaluate the proposed method and compare it with the competing algorithms, we generate a comprehensive dataset with various types of texts in diverse real-world scenes. We also propose a new evaluation protocol, which is more suitable for benchmarking algorithms for detecting texts in varying orientations. Experiments on benchmark datasets demonstrate that our system compares favorably with the state-of-the-art algorithms when handling horizontal texts and achieves significantly enhanced performance on variant texts in complex natural scenes.

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

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    Y. Jia

    2016-06-01

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

  3. Structural damage detection-oriented multi-type sensor placement with multi-objective optimization

    Science.gov (United States)

    Lin, Jian-Fu; Xu, You-Lin; Law, Siu-Seong

    2018-05-01

    A structural damage detection-oriented multi-type sensor placement method with multi-objective optimization is developed in this study. The multi-type response covariance sensitivity-based damage detection method is first introduced. Two objective functions for optimal sensor placement are then introduced in terms of the response covariance sensitivity and the response independence. The multi-objective optimization problem is formed by using the two objective functions, and the non-dominated sorting genetic algorithm (NSGA)-II is adopted to find the solution for the optimal multi-type sensor placement to achieve the best structural damage detection. The proposed method is finally applied to a nine-bay three-dimensional frame structure. Numerical results show that the optimal multi-type sensor placement determined by the proposed method can avoid redundant sensors and provide satisfactory results for structural damage detection. The restriction on the number of each type of sensors in the optimization can reduce the searching space in the optimization to make the proposed method more effective. Moreover, how to select a most optimal sensor placement from the Pareto solutions via the utility function and the knee point method is demonstrated in the case study.

  4. Scene text detection by leveraging multi-channel information and local context

    Science.gov (United States)

    Wang, Runmin; Qian, Shengyou; Yang, Jianfeng; Gao, Changxin

    2018-03-01

    As an important information carrier, texts play significant roles in many applications. However, text detection in unconstrained scenes is a challenging problem due to cluttered backgrounds, various appearances, uneven illumination, etc.. In this paper, an approach based on multi-channel information and local context is proposed to detect texts in natural scenes. According to character candidate detection plays a vital role in text detection system, Maximally Stable Extremal Regions(MSERs) and Graph-cut based method are integrated to obtain the character candidates by leveraging the multi-channel image information. A cascaded false positive elimination mechanism are constructed from the perspective of the character and the text line respectively. Since the local context information is very valuable for us, these information is utilized to retrieve the missing characters for boosting the text detection performance. Experimental results on two benchmark datasets, i.e., the ICDAR 2011 dataset and the ICDAR 2013 dataset, demonstrate that the proposed method have achieved the state-of-the-art performance.

  5. OBLIQUE MULTI-CAMERA SYSTEMS – ORIENTATION AND DENSE MATCHING ISSUES

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    E. Rupnik

    2014-03-01

    Full Text Available The use of oblique imagery has become a standard for many civil and mapping applications, thanks to the development of airborne digital multi-camera systems, as proposed by many companies (Blomoblique, IGI, Leica, Midas, Pictometry, Vexcel/Microsoft, VisionMap, etc.. The indisputable virtue of oblique photography lies in its simplicity of interpretation and understanding for inexperienced users allowing their use of oblique images in very different applications, such as building detection and reconstruction, building structural damage classification, road land updating and administration services, etc. The paper reports an overview of the actual oblique commercial systems and presents a workflow for the automated orientation and dense matching of large image blocks. Perspectives, potentialities, pitfalls and suggestions for achieving satisfactory results are given. Tests performed on two datasets acquired with two multi-camera systems over urban areas are also reported.

  6. Multi-detector row CT colonography: effect of collimation, pitch, and orientation on polyp detection in a human colectomy specimen.

    Science.gov (United States)

    Taylor, Stuart A; Halligan, Steve; Bartram, Clive I; Morgan, Paul R; Talbot, Ian C; Fry, Nicola; Saunders, Brian P; Khosraviani, Kirosh; Atkin, Wendy

    2003-10-01

    To investigate the effects of orientation, collimation, pitch, and tube current setting on polyp detection at multi-detector row computed tomographic (CT) colonography and to determine the optimal combination of scanning parameters for screening. A colectomy specimen containing 117 polyps of different sizes was insufflated and imaged with a multi-detector row CT scanner at various collimation (1.25 and 2.5 mm), pitch (3 and 6), and tube current (50, 100, and 150 mA) settings. Two-dimensional multiplanar reformatted images and three-dimensional endoluminal surface renderings from the 12 resultant data sets were examined by one observer for the presence and conspicuity of polyps. The results were analyzed with Poisson regression and logistic regression to determine the effects of scanning parameters and of specimen orientation on polyp detection. The percentage of polyps that were detected significantly increased when collimation (P =.008) and table feed (P =.03) were decreased. Increased tube current resulted in improved detection only of polyps with a diameter of less than 5 mm. Polyps of less than 5 mm were optimally depicted with a collimation of 1.25 mm, a pitch of 3, and a tube current setting of 150 mA; polyps with a diameter greater than 5 mm were adequately depicted with 1.25-mm collimation and with either pitch setting and any of the three tube current settings. Small polyps in the transverse segment (positioned at a 90 degrees angle to the z axis of scanning) were significantly less visible than those in parallel or oblique orientations (P detector row CT is highly dependent on collimation, pitch, and, to a lesser extent, tube current. Collimation of 1.25 mm, combined with pitch of 6 and tube current of 50 mA, provides for reliable detection of polyps 5 mm or larger while limiting the effective radiation dose. Polyps smaller than 5 mm, however, may be poorly depicted with use of these settings in the transverse colon. Copyright RSNA, 2003

  7. Multi-scale and multi-orientation medical image analysis

    NARCIS (Netherlands)

    Haar Romenij, ter B.M.; Deserno, T.M.

    2011-01-01

    Inspired by multi-scale and multi-orientation mechanisms recognized in the first stages of our visual system, this chapter gives a tutorial overview of the basic principles. Images are discrete, measured data. The optimal aperture for an observation with as little artefacts as possible, is derived

  8. Detecting text in natural scenes with multi-level MSER and SWT

    Science.gov (United States)

    Lu, Tongwei; Liu, Renjun

    2018-04-01

    The detection of the characters in the natural scene is susceptible to factors such as complex background, variable viewing angle and diverse forms of language, which leads to poor detection results. Aiming at these problems, a new text detection method was proposed, which consisted of two main stages, candidate region extraction and text region detection. At first stage, the method used multiple scale transformations of original image and multiple thresholds of maximally stable extremal regions (MSER) to detect the text regions which could detect character regions comprehensively. At second stage, obtained SWT maps by using the stroke width transform (SWT) algorithm to compute the candidate regions, then using cascaded classifiers to propose non-text regions. The proposed method was evaluated on the standard benchmark datasets of ICDAR2011 and the datasets that we made our own data sets. The experiment results showed that the proposed method have greatly improved that compared to other text detection methods.

  9. Immobilization of ruthenium phthalocyanine on silica-coated multi-wall partially oriented carbon nanotubes: Electrochemical detection of fenitrothion pesticide

    Energy Technology Data Exchange (ETDEWEB)

    Canevari, Thiago C., E-mail: tccanevari@gmail.com [Engineering School, Mackenzie Presbyterian University, 01302-907 São Paulo, SP (Brazil); Prado, Thiago M.; Cincotto, Fernando H.; Machado, Sergio A.S. [Institute of Chemistry, State University of São Paulo, P.O. Box 780, 13560-970 São Carlos, SP (Brazil)

    2016-04-15

    Highlights: • Hybrid material, SiO{sub 2}/MWCNTs containing ruthenium phthalocyanine (RuPc) synthesized in situ. • Silica containing multi-walled carbon nanotube partially oriented. • Determination of pesticide fenitrothion in orange juice. - Abstract: This paper reports on the determination of the pesticide fenitrothion using a glassy carbon electrode modified with silica-coated, multi-walled, partially oriented carbon nanotubes, SiO{sub 2}/MWCNTs, containing ruthenium phthalocyanine (RuPc) synthesized in situ. The hybrid SiO{sub 2}/MWCNTs/RuPc material was characterized by UV–vis absorption spectroscopy, X-ray photoelectron spectroscopy (XPS), scanning electron microscopy (SEM), high-resolution transmission electron microscopy (HR-TEM) and differential pulse voltammetry. The modified electrode showed well-defined peaks in the presence of fenitrothion in acetate buffer, pH 4.5, with a sensitivity of 0.0822 μA μM{sup −1} mm{sup −2} and a detection limit of 0.45 ppm. Notably, the modified SiO{sub 2}/MWCNTs/RuPc electrodes with did not suffer from significant influences in the presence of other organophosphorus pesticides during the determination of the fenitrothion pesticide. Moreover, this modified electrode showed excellent performance in the determination of fenitrothion in orange juice.

  10. Text and ideology: text-oriented discourse analysis

    Directory of Open Access Journals (Sweden)

    Maria Eduarda Gonçalves Peixoto

    2018-04-01

    Full Text Available The article aims to contribute to the understanding of the connection between text and ideology articulated by the text-oriented analysis of discourse (ADTO. Based on the reflections of Fairclough (1989, 2001, 2003 and Fairclough and Chouliaraki (1999, the debate presents the social ontology that ADTO uses to base its conception of social life as an open system and textually mediated; the article then explains the chronological-narrative development of the main critical theories of ideology, by virtue of which ADTO organizes the assumptions that underpin the particular use it makes of the term. Finally, the discussion presents the main aspects of the connection between text and ideology, offering a conceptual framework that can contribute to the domain of the theme according to a critical discourse analysis approach.

  11. Orienting task effects on text recall in adulthood.

    Science.gov (United States)

    Simon, E W; Dixon, R A; Nowak, C A; Hultsch, D F

    1982-09-01

    This investigation examined the effects of orienting task-controlled processing on the text recall of younger (18 to 32 years), middle-aged (39 to 51 years), and older (59 to 76 years) adults. The participants were presented with a 500-word narrative text. Three groups performed orienting tasks (syntactic, stylistic, advice) within an incidental memory paradigm. A fourth group was asked for intentional recall. Analysis indicated a significant age by orienting task interaction. Younger adults recalled more propositions when recall was intentional or when it was preceded by a deep-orienting task than when it was preceded by a shallow-orienting task. Middle-aged and older adults recalled more propositions when recall was intentional than when it was incidental, regardless of the depth of the orienting task. There were no significant differences in intentional recall. In addition, a significant age x orienting task x propositional level interaction indicated that younger adults recalled more of the main ideas of the text following deep processing, whereas the middle-aged and older adults recalled more of these ideas following intentional processing.

  12. Oriented Edge-Based Feature Descriptor for Multi-Sensor Image Alignment and Enhancement

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    Myung-Ho Ju

    2013-10-01

    Full Text Available In this paper, we present an efficient image alignment and enhancement method for multi-sensor images. The shape of the object captured in a multi-sensor images can be determined by comparing variability of contrast using corresponding edges across multi-sensor image. Using this cue, we construct a robust feature descriptor based on the magnitudes of the oriented edges. Our proposed method enables fast image alignment by identifying matching features in multi-sensor images. We enhance the aligned multi-sensor images through the fusion of the salient regions from each image. The results of stitching the multi-sensor images and their enhancement demonstrate that our proposed method can align and enhance multi-sensor images more efficiently than previous methods.

  13. Far-Infrared Based Pedestrian Detection for Driver-Assistance Systems Based on Candidate Filters, Gradient-Based Feature and Multi-Frame Approval Matching

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    Guohua Wang

    2015-12-01

    Full Text Available Far-infrared pedestrian detection approaches for advanced driver-assistance systems based on high-dimensional features fail to simultaneously achieve robust and real-time detection. We propose a robust and real-time pedestrian detection system characterized by novel candidate filters, novel pedestrian features and multi-frame approval matching in a coarse-to-fine fashion. Firstly, we design two filters based on the pedestrians’ head and the road to select the candidates after applying a pedestrian segmentation algorithm to reduce false alarms. Secondly, we propose a novel feature encapsulating both the relationship of oriented gradient distribution and the code of oriented gradient to deal with the enormous variance in pedestrians’ size and appearance. Thirdly, we introduce a multi-frame approval matching approach utilizing the spatiotemporal continuity of pedestrians to increase the detection rate. Large-scale experiments indicate that the system works in real time and the accuracy has improved about 9% compared with approaches based on high-dimensional features only.

  14. Oblique Multi-Camera Systems - Orientation and Dense Matching Issues

    Science.gov (United States)

    Rupnik, E.; Nex, F.; Remondino, F.

    2014-03-01

    The use of oblique imagery has become a standard for many civil and mapping applications, thanks to the development of airborne digital multi-camera systems, as proposed by many companies (Blomoblique, IGI, Leica, Midas, Pictometry, Vexcel/Microsoft, VisionMap, etc.). The indisputable virtue of oblique photography lies in its simplicity of interpretation and understanding for inexperienced users allowing their use of oblique images in very different applications, such as building detection and reconstruction, building structural damage classification, road land updating and administration services, etc. The paper reports an overview of the actual oblique commercial systems and presents a workflow for the automated orientation and dense matching of large image blocks. Perspectives, potentialities, pitfalls and suggestions for achieving satisfactory results are given. Tests performed on two datasets acquired with two multi-camera systems over urban areas are also reported.

  15. Service orientation in holonic and multi agent manufacturing and robotics

    CERN Document Server

    Thomas, Andre; Trentesaux, Damien

    2013-01-01

    The book covers four research domains representing a trend for modern manufacturing control: Holonic and Multi-agent technologies for industrial systems; Intelligent Product and Product-driven Automation; Service Orientation of Enterprise’s strategic and technical processes; and Distributed Intelligent Automation Systems. These evolution lines have in common concepts related to service orientation derived from the Service Oriented Architecture (SOA) paradigm.     The service-oriented multi-agent systems approach discussed in the book is characterized by the use of a set of distributed autonomous and cooperative agents, embedded in smart components that use the SOA principles, being oriented by offer and request of services, in order to fulfil production systems and value chain goals.   A new integrated vision combining emergent technologies is offered, to create control structures with distributed intelligence supporting the vertical and horizontal enterprise integration and running in truly distributed ...

  16. Service orientation in holonic and multi-agent manufacturing

    CERN Document Server

    Thomas, André; Trentesaux, Damien

    2015-01-01

    This volume gathers the peer reviewed papers presented at the 4th edition of the International Workshop “Service Orientation in Holonic and Multi-agent Manufacturing – SOHOMA’14” organized and hosted on November 5-6, 2014 by the University of Lorraine, France in collaboration with the CIMR Research Centre of the University Politehnica of Bucharest and the TEMPO Laboratory of the University of Valenciennes and Hainaut-Cambrésis.   The book is structured in six parts, each one covering a specific research line which represents a trend in future manufacturing: (1) Holonic and Agent-based Industrial Automation Systems; (2) Service-oriented Management and Control of Manufacturing Systems; (3) Distributed Modelling for Safety and Security in Industrial Systems; (4) Complexity, Big Data and Virtualization in Computing-oriented Manufacturing; (5) Adaptive, Bio-inspired and Self-organizing Multi-Agent Systems for Manufacturing, and (6) Physical Internet Simulation, Modelling and Control.   There is a clear ...

  17. Benchmarking and performance enhancement framework for multi-staging object-oriented languages

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    Ahmed H. Yousef

    2013-06-01

    Full Text Available This paper focuses on verifying the readiness, feasibility, generality and usefulness of multi-staging programming in software applications. We present a benchmark designed to evaluate the performance gain of different multi-staging programming (MSP languages implementations of object oriented languages. The benchmarks in this suite cover different tests that range from classic simple examples (like matrix algebra to advanced examples (like encryption and image processing. The benchmark is applied to compare the performance gain of two different MSP implementations (Mint and Metaphor that are built on object oriented languages (Java and C# respectively. The results concerning the application of this benchmark on these languages are presented and analysed. The measurement technique used in benchmarking leads to the development of a language independent performance enhancement framework that allows the programmer to select which code segments need staging. The framework also enables the programmer to verify the effectiveness of staging on the application performance. The framework is applied to a real case study. The case study results showed the effectiveness of the framework to achieve significant performance enhancement.

  18. Enhanced Biosensor Platforms for Detecting the Atherosclerotic Biomarker VCAM1 Based on Bioconjugation with Uniformly Oriented VCAM1-Targeting Nanobodies

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    Duy Tien Ta

    2016-07-01

    Full Text Available Surface bioconjugation of biomolecules has gained enormous attention for developing advanced biomaterials including biosensors. While conventional immobilization (by physisorption or covalent couplings using the functional groups of the endogenous amino acids usually results in surfaces with low activity, reproducibility and reusability, the application of methods that allow for a covalent and uniformly oriented coupling can circumvent these limitations. In this study, the nanobody targeting Vascular Cell Adhesion Molecule-1 (NbVCAM1, an atherosclerotic biomarker, is engineered with a C-terminal alkyne function via Expressed Protein Ligation (EPL. Conjugation of this nanobody to azidified silicon wafers and Biacore™ C1 sensor chips is achieved via Copper(I-catalyzed azide-alkyne cycloaddition (CuAAC “click” chemistry to detect VCAM1 binding via ellipsometry and surface plasmon resonance (SPR, respectively. The resulting surfaces, covered with uniformly oriented nanobodies, clearly show an increased antigen binding affinity, sensitivity, detection limit, quantitation limit and reusability as compared to surfaces prepared by random conjugation. These findings demonstrate the added value of a combined EPL and CuAAC approach as it results in strong control over the surface orientation of the nanobodies and an improved detecting power of their targets—a must for the development of advanced miniaturized, multi-biomarker biosensor platforms.

  19. 6th Workshop on Service Orientation in Holonic and Multi-Agent Manufacturing

    CERN Document Server

    Trentesaux, Damien; Thomas, André; Leitão, Paulo; Oliveira, José

    2017-01-01

    The book offers an integrated vision on Cloud and HPC, Big Data, Analytics and virtualization in computing-oriented manufacturing, combining information and communication technologies, service-oriented control of holonic architectures as well as enterprise integration solutions based on SOA principles. It is structured in eight parts, each one grouping research and trends in digital manufacturing and service oriented manufacturing control: Cloud and Cyber-Physical Systems for Smart Manufacturing, Reconfigurable and Self-organized Multi-Agent Systems for Industry and Service, Sustainability Issues in Intelligent Manufacturing Systems, Holonic and Multi-agent System Design for Industry and Service, Should Intelligent Manufacturing Systems be Dependable and Safe?, Service-oriented Management and Control of Manufacturing Systems, Engineering and Human Integration in Flexible and Reconfigurable Industrial Systems,Virtualization and Simulation in Computing-oriented Industry and Service.

  20. Task-oriented control of Single-Master Multi-Slave Manipulator System

    International Nuclear Information System (INIS)

    Kosuge, Kazuhiro; Ishikawa, Jun; Furuta, Katsuhisa; Hariki, Kazuo; Sakai, Masaru.

    1994-01-01

    A master-slave manipulator system, in general, consists of a master arm manipulated by a human and a slave arm used for real tasks. Some tasks, such as manipulation of a heavy object, etc., require two or more slave arms operated simultaneously. A Single-Master Multi-Slave Manipulator System consists of a master arm with six degrees of freedom and two or more slave arms, each of which has six or more degrees of freedom. In this system, a master arm controls the task-oriented variables using Virtual Internal Model (VIM) based on the concept of 'Task-Oriented Control'. VIM is a reference model driven by sensory information and used to describe the desired relation between the motion of a master arm and task-oriented variables. The motion of slave arms are controlled based on the task oriented variables generated by VIM and tailors the system to meet specific tasks. A single-master multi-slave manipulator system, having two slave arms, is experimentally developed and illustrates the concept. (author)

  1. SmartMal: A Service-Oriented Behavioral Malware Detection Framework for Mobile Devices

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    Chao Wang

    2014-01-01

    Full Text Available This paper presents SmartMal—a novel service-oriented behavioral malware detection framework for vehicular and mobile devices. The highlight of SmartMal is to introduce service-oriented architecture (SOA concepts and behavior analysis into the malware detection paradigms. The proposed framework relies on client-server architecture, the client continuously extracts various features and transfers them to the server, and the server’s main task is to detect anomalies using state-of-art detection algorithms. Multiple distributed servers simultaneously analyze the feature vector using various detectors and information fusion is used to concatenate the results of detectors. We also propose a cycle-based statistical approach for mobile device anomaly detection. We accomplish this by analyzing the users’ regular usage patterns. Empirical results suggest that the proposed framework and novel anomaly detection algorithm are highly effective in detecting malware on Android devices.

  2. Multi-view Face Detection Using Deep Convolutional Neural Networks

    OpenAIRE

    Farfade, Sachin Sudhakar; Saberian, Mohammad; Li, Li-Jia

    2015-01-01

    In this paper we consider the problem of multi-view face detection. While there has been significant research on this problem, current state-of-the-art approaches for this task require annotation of facial landmarks, e.g. TSM [25], or annotation of face poses [28, 22]. They also require training dozens of models to fully capture faces in all orientations, e.g. 22 models in HeadHunter method [22]. In this paper we propose Deep Dense Face Detector (DDFD), a method that does not require pose/lan...

  3. Determining fast orientation changes of multi-spectral line cameras from the primary images

    Science.gov (United States)

    Wohlfeil, Jürgen

    2012-01-01

    Fast orientation changes of airborne and spaceborne line cameras cannot always be avoided. In such cases it is essential to measure them with high accuracy to ensure a good quality of the resulting imagery products. Several approaches exist to support the orientation measurement by using optical information received through the main objective/telescope. In this article an approach is proposed that allows the determination of non-systematic orientation changes between every captured line. It does not require any additional camera hardware or onboard processing capabilities but the payload images and a rough estimate of the camera's trajectory. The approach takes advantage of the typical geometry of multi-spectral line cameras with a set of linear sensor arrays for different spectral bands on the focal plane. First, homologous points are detected within the heavily distorted images of different spectral bands. With their help a connected network of geometrical correspondences can be built up. This network is used to calculate the orientation changes of the camera with the temporal and angular resolution of the camera. The approach was tested with an extensive set of aerial surveys covering a wide range of different conditions and achieved precise and reliable results.

  4. Land Cover Change Detection in Urban Lake Areas Using Multi-Temporary Very High Spatial Resolution Aerial Images

    Directory of Open Access Journals (Sweden)

    Wenyuan Zhang

    2018-01-01

    Full Text Available The availability of very high spatial resolution (VHR remote sensing imagery provides unique opportunities to exploit meaningful change information in detail with object-oriented image analysis. This study investigated land cover (LC changes in Shahu Lake of Wuhan using multi-temporal VHR aerial images in the years 1978, 1981, 1989, 1995, 2003, and 2011. A multi-resolution segmentation algorithm and CART (classification and regression trees classifier were employed to perform highly accurate LC classification of the individual images, while a post-classification comparison method was used to detect changes. The experiments demonstrated that significant changes in LC occurred along with the rapid urbanization during 1978–2011. The dominant changes that took place in the study area were lake and vegetation shrinking, replaced by high density buildings and roads. The total area of Shahu Lake decreased from ~7.64 km2 to ~3.60 km2 during the past 33 years, where 52.91% of its original area was lost. The presented results also indicated that urban expansion and inadequate legislative protection are the main factors in Shahu Lake’s shrinking. The object-oriented change detection schema presented in this manuscript enables us to better understand the specific spatial changes of Shahu Lake, which can be used to make reasonable decisions for lake protection and urban development.

  5. The effectiveness of multi modal representation text books to improve student's scientific literacy of senior high school students

    Science.gov (United States)

    Zakiya, Hanifah; Sinaga, Parlindungan; Hamidah, Ida

    2017-05-01

    The results of field studies showed the ability of science literacy of students was still low. One root of the problem lies in the books used in learning is not oriented toward science literacy component. This study focused on the effectiveness of the use of textbook-oriented provisioning capability science literacy by using multi modal representation. The text books development method used Design Representational Approach Learning to Write (DRALW). Textbook design which was applied to the topic of "Kinetic Theory of Gases" is implemented in XI grade students of high school learning. Effectiveness is determined by consideration of the effect and the normalized percentage gain value, while the hypothesis was tested using Independent T-test. The results showed that the textbooks which were developed using multi-mode representation science can improve the literacy skills of students. Based on the size of the effect size textbooks developed with representation multi modal was found effective in improving students' science literacy skills. The improvement was occurred in all the competence and knowledge of scientific literacy. The hypothesis testing showed that there was a significant difference on the ability of science literacy between class that uses textbooks with multi modal representation and the class that uses the regular textbook used in schools.

  6. Management of Multi-projects In a Process oriented Organization

    OpenAIRE

    Macheridis, Nikos; Nilsson, Carl-Henrik

    2006-01-01

    When projects are used as an organisational platform to conduct business, a project can be the only project in the organisation or one amongst several others. The latter case is called multi-project organisation. Usually an organization with a multi-project environment has a base organisation, which can be functional, matrix structure or another. The purpose of this article is to develop a model based on a process oriented organization as a complement to functional or matrix organizational st...

  7. No apparent influence of psychometrically-defined schizotypy on orientation-dependent contextual modulation of visual contrast detection

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    Damien J. Mannion

    2017-01-01

    Full Text Available We investigated the relationship between psychometrically-defined schizotypy and the ability to detect a visual target pattern. Target detection is typically impaired by a surrounding pattern (context with an orientation that is parallel to the target, relative to a surrounding pattern with an orientation that is orthogonal to the target (orientation-dependent contextual modulation. Based on reports that this effect is reduced in those with schizophrenia, we hypothesised that there would be a negative relationship between the relative score on psychometrically-defined schizotypy and the relative effect of orientation-dependent contextual modulation. We measured visual contrast detection thresholds and scores on the Oxford-Liverpool Inventory of Feelings and Experiences (O-LIFE from a non-clinical sample (N = 100. Contrary to our hypothesis, we find an absence of a monotonic relationship between the relative magnitude of orientation-dependent contextual modulation of visual contrast detection and the relative score on any of the subscales of the O-LIFE. The apparent difference of this result with previous reports on those with schizophrenia suggests that orientation-dependent contextual modulation may be an informative condition in which schizophrenia and psychometrically-defined schizotypy are dissociated. However, further research is also required to clarify the strength of orientation-dependent contextual modulation in those with schizophrenia.

  8. Real-time detection with AdaBoost-svm combination in various face orientation

    Science.gov (United States)

    Fhonna, R. P.; Nasution, M. K. M.; Tulus

    2018-03-01

    Most of the research has used algorithm AdaBoost-SVM for face detection. However, to our knowledge so far there is no research has been facing detection on real-time data with various orientations using the combination of AdaBoost and Support Vector Machine (SVM). Characteristics of complex and diverse face variations and real-time data in various orientations, and with a very complex application will slow down the performance of the face detection system this becomes a challenge in this research. Face orientation performed on the detection system, that is 900, 450, 00, -450, and -900. This combination method is expected to be an effective and efficient solution in various face orientations. The results showed that the highest average detection rate is on the face detection oriented 00 and the lowest detection rate is in the face orientation 900.

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

    Science.gov (United States)

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

    2015-03-01

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

  10. Flexible feature-space-construction architecture and its VLSI implementation for multi-scale object detection

    Science.gov (United States)

    Luo, Aiwen; An, Fengwei; Zhang, Xiangyu; Chen, Lei; Huang, Zunkai; Jürgen Mattausch, Hans

    2018-04-01

    Feature extraction techniques are a cornerstone of object detection in computer-vision-based applications. The detection performance of vison-based detection systems is often degraded by, e.g., changes in the illumination intensity of the light source, foreground-background contrast variations or automatic gain control from the camera. In order to avoid such degradation effects, we present a block-based L1-norm-circuit architecture which is configurable for different image-cell sizes, cell-based feature descriptors and image resolutions according to customization parameters from the circuit input. The incorporated flexibility in both the image resolution and the cell size for multi-scale image pyramids leads to lower computational complexity and power consumption. Additionally, an object-detection prototype for performance evaluation in 65 nm CMOS implements the proposed L1-norm circuit together with a histogram of oriented gradients (HOG) descriptor and a support vector machine (SVM) classifier. The proposed parallel architecture with high hardware efficiency enables real-time processing, high detection robustness, small chip-core area as well as low power consumption for multi-scale object detection.

  11. Multi-sample immunoassay inside optical fiber capillary enabled by evanescent wave detection

    Directory of Open Access Journals (Sweden)

    Chun-Wei Wang

    2016-03-01

    Full Text Available A novel evanescent wave-based (EW microfluidic capillary fiber-optic biosensor (MCFOB has been developed using capillaries as a transducer embedded in a multichannel device to enhance the collection efficiency of the fluorescence signal. The capillary serves dual roles as a waveguide and a container, enabling more straightforward, consistent, and compact biosensor packaging compared to conventional optical fiber biosensors and microfluidic systems. In order to detect multiple samples in one device, the biosensor incorporates a polydimethysiloxane (PDMS multi-channel device, which also serves as cladding for the biosensor. In addition, this biosensor only consumes 10 μl of a sample and does not require hydrofluoric acid etching in the fabrication process. The orientation for signal collection is optimized by comparing the lateral and normal signal directions for detected glyceraldehyde 3-phosphate dehydrogenase (GAPDH. C-reactive protein (CRP is used to validate the MCFOB, and the limit of detection (LOD for CRP in the MCFOB is 1.94 ng/ml (74 pM. Moreover, the real-time measurement is demonstrated to verify that the evanescent wave is the only exciting light source in the MCFOB, which gives the potential for real-time measurement applications. Keywords: C-reactive protein, Capillary, Fiber-optic, Microfluidic, Evanescent wave, Immunoassay

  12. Far-Infrared Based Pedestrian Detection for Driver-Assistance Systems Based on Candidate Filters, Gradient-Based Feature and Multi-Frame Approval Matching.

    Science.gov (United States)

    Wang, Guohua; Liu, Qiong

    2015-12-21

    Far-infrared pedestrian detection approaches for advanced driver-assistance systems based on high-dimensional features fail to simultaneously achieve robust and real-time detection. We propose a robust and real-time pedestrian detection system characterized by novel candidate filters, novel pedestrian features and multi-frame approval matching in a coarse-to-fine fashion. Firstly, we design two filters based on the pedestrians' head and the road to select the candidates after applying a pedestrian segmentation algorithm to reduce false alarms. Secondly, we propose a novel feature encapsulating both the relationship of oriented gradient distribution and the code of oriented gradient to deal with the enormous variance in pedestrians' size and appearance. Thirdly, we introduce a multi-frame approval matching approach utilizing the spatiotemporal continuity of pedestrians to increase the detection rate. Large-scale experiments indicate that the system works in real time and the accuracy has improved about 9% compared with approaches based on high-dimensional features only.

  13. A face detection bias for horizontal orientations develops in middle childhood

    Directory of Open Access Journals (Sweden)

    Benjamin J Balas

    2015-06-01

    Full Text Available Faces are complex stimuli that can be described via intuitive facial features like the eyes, nose, and mouth, configural features like the distances between facial landmarks, and features that correspond to computations performed in the early visual system (e.g. oriented edges. With regard to this latter category of descriptors, adult face recognition relies disproportionately on information in specific spatial frequency and orientation bands: Many recognition tasks are performed more accurately when adults have access to mid-range spatial frequencies (8-16 cycles/face and horizontal orientations (Dakin & Watt, 2009. In the current study, we examined how this information bias develops in middle childhood. We recruited children between the ages of 5-10 years old to participate in a simple categorization task that required them to label images according to whether they depicted a face or a house. Critically, children were presented with face and house images comprised either of primarily horizontal orientation energy, primarily vertical orientation energy, or both horizontal and vertical orientation energy. We predicted that any bias favoring horizontal information over vertical should be more evident in faces than in houses, and also that older children would be more likely to show such a bias than younger children. We designed our categorization task to be sufficiently easy that children would perform at near-ceiling accuracy levels, but with variation in response times that would reflect how they rely on different orientations as a function of age and object category. We found that horizontal bias for face detection (but not house detection correlated significantly with age, suggesting an emergent category-specific bias for horizontal orientation energy that develops during middle childhood. These results thus suggest that the tuning of high-level recognition to specific low-level visual features takes take place over several years of visual

  14. Text Line Detection from Rectangle Traffic Panels of Natural Scene

    Science.gov (United States)

    Wang, Shiyuan; Huang, Linlin; Hu, Jian

    2018-01-01

    Traffic sign detection and recognition is very important for Intelligent Transportation. Among traffic signs, traffic panel contains rich information. However, due to low resolution and blur in the rectangular traffic panel, it is difficult to extract the character and symbols. In this paper, we propose a coarse-to-fine method to detect the Chinese character on traffic panels from natural scenes. Given a traffic panel Color Quantization is applied to extract candidate regions of Chinese characters. Second, a multi-stage filter based on learning is applied to discard the non-character regions. Third, we aggregate the characters for text lines by Distance Metric Learning method. Experimental results on real traffic images from Baidu Street View demonstrate the effectiveness of the proposed method.

  15. Horizontal and vertical combination of multi-tenancy patterns in service-oriented applications

    Science.gov (United States)

    Mietzner, Ralph; Leymann, Frank; Unger, Tobias

    2011-02-01

    Software as a service (SaaS) providers exploit economies of scale by offering the same instance of an application to multiple customers typically in a single-instance multi-tenant architecture model. Therefore the applications must be scalable, multi-tenant aware and configurable. In this article, we show how the services in a service-oriented SaaS application can be deployed using different multi-tenancy patterns. We describe how services in different multi-tenancy patterns can be composed on the application level. In addition to that, we also describe how these multi-tenancy patterns can be applied to middleware and hardware components. We then show with some real world examples how the different multi-tenancy patterns can be combined.

  16. Oriented antibodies as versatile detection element in biosensors

    NARCIS (Netherlands)

    Trilling, A.K.

    2013-01-01

    The aim of this thesis is to explore orientation of detection elements on biosensor

    surfaces. To this end, different strategies were combined such as surface chemistry and protein functionalization, with the aim to generate a platform for oriented immobilization of antibodies

    in

  17. Multi-Model Estimation Based Moving Object Detection for Aerial Video

    Directory of Open Access Journals (Sweden)

    Yanning Zhang

    2015-04-01

    Full Text Available With the wide development of UAV (Unmanned Aerial Vehicle technology, moving target detection for aerial video has become a popular research topic in the computer field. Most of the existing methods are under the registration-detection framework and can only deal with simple background scenes. They tend to go wrong in the complex multi background scenarios, such as viaducts, buildings and trees. In this paper, we break through the single background constraint and perceive the complex scene accurately by automatic estimation of multiple background models. First, we segment the scene into several color blocks and estimate the dense optical flow. Then, we calculate an affine transformation model for each block with large area and merge the consistent models. Finally, we calculate subordinate degree to multi-background models pixel to pixel for all small area blocks. Moving objects are segmented by means of energy optimization method solved via Graph Cuts. The extensive experimental results on public aerial videos show that, due to multi background models estimation, analyzing each pixel’s subordinate relationship to multi models by energy minimization, our method can effectively remove buildings, trees and other false alarms and detect moving objects correctly.

  18. Pedagogical Factors Stimulating the Self-Development of Students' Multi-Dimensional Thinking in Terms of Subject-Oriented Teaching

    Science.gov (United States)

    Andreev, Valentin I.

    2014-01-01

    The main aim of this research is to disclose the essence of students' multi-dimensional thinking, also to reveal the rating of factors which stimulate the raising of effectiveness of self-development of students' multi-dimensional thinking in terms of subject-oriented teaching. Subject-oriented learning is characterized as a type of learning where…

  19. Multi-scale structural similarity index for motion detection

    Directory of Open Access Journals (Sweden)

    M. Abdel-Salam Nasr

    2017-07-01

    Full Text Available The most recent approach for measuring the image quality is the structural similarity index (SSI. This paper presents a novel algorithm based on the multi-scale structural similarity index for motion detection (MS-SSIM in videos. The MS-SSIM approach is based on modeling of image luminance, contrast and structure at multiple scales. The MS-SSIM has resulted in much better performance than the single scale SSI approach but at the cost of relatively lower processing speed. The major advantages of the presented algorithm are both: the higher detection accuracy and the quasi real-time processing speed.

  20. Text-analytic Measurement of Effectuation and Causation Orientations among Small and Global Business Managers

    DEFF Research Database (Denmark)

    Mattsson, Jan; Helmersson, Helge

    2012-01-01

    We demonstrate how one can measure overall quality in texts gathered from interviews by means of PERTEX text analytic method. We compare text analytic measures and content for locally active Scandinavian small business managers and globally operating Indian IT managers when recapitulating......-components we are also able to display the degree of fragmentation, focus and integration in the text. We show how AFFI measures differ between managers with a causation or effectuation orientation irrespective of their role as small business manager or as an established global manager. Hence, we posit...... that effectuation and causation orientations may be generic characteristic of managers in general....

  1. Who multi-tasks and why? Multi-tasking ability, perceived multi-tasking ability, impulsivity, and sensation seeking.

    Directory of Open Access Journals (Sweden)

    David M Sanbonmatsu

    Full Text Available The present study examined the relationship between personality and individual differences in multi-tasking ability. Participants enrolled at the University of Utah completed measures of multi-tasking activity, perceived multi-tasking ability, impulsivity, and sensation seeking. In addition, they performed the Operation Span in order to assess their executive control and actual multi-tasking ability. The findings indicate that the persons who are most capable of multi-tasking effectively are not the persons who are most likely to engage in multiple tasks simultaneously. To the contrary, multi-tasking activity as measured by the Media Multitasking Inventory and self-reported cell phone usage while driving were negatively correlated with actual multi-tasking ability. Multi-tasking was positively correlated with participants' perceived ability to multi-task ability which was found to be significantly inflated. Participants with a strong approach orientation and a weak avoidance orientation--high levels of impulsivity and sensation seeking--reported greater multi-tasking behavior. Finally, the findings suggest that people often engage in multi-tasking because they are less able to block out distractions and focus on a singular task. Participants with less executive control--low scorers on the Operation Span task and persons high in impulsivity--tended to report higher levels of multi-tasking activity.

  2. Multi-shelled q-ball imaging. Moment-based orientation distribution function

    International Nuclear Information System (INIS)

    Umezawa, Eizou; Yamaguchi, Kojiro; Yoshikawa, Mayo; Ohno, Kana; Yoshikawa, Emi

    2010-01-01

    q-ball imaging (QBI) reconstructs the orientation distribution function (ODF) that describes the probability for a spin to diffuse in a given direction, and it is capable of identifying intravoxel multiple fiber orientations. The local maxima of ODF are assumed to indicate fiber orientations, but there is a mismatch between the orientation of a fiber crossing and the local maxima. We propose a novel method, multi-shelled QBI (MS-QBI), that gives a new ODF based on the moment of the probability density function of diffusion displacement. We test the accuracy of the fiber orientation indicated by the new ODF and test fiber tracking using the new ODF. We performed tests using numerical simulation. To test the accuracy of fiber orientation, we assumed that 2 fibers cross and evaluated the deviation of the measured crossing angle from the actual angle. To test the fiber tracking, we used a numerical phantom of the cerebral hemisphere containing the corpus callosum, projection fibers, and superior longitudinal fasciculus. In the tests, we compared the results between MS-QBI and conventional QBI under the condition of approximately equal total numbers of diffusion signal samplings between the 2 methods and chose the interpolation parameter such that the stabilities of the results of the angular deviation for the 2 methods were the same. The absolute value of the mean angular deviation was smaller in MS-QBI than in conventional QBI. Using the moment-based ODF improved the accuracy of fiber pathways in fiber tracking but maintained the stability of the results. MS-QBI can more accurately identify intravoxel multiple fiber orientations than can QBI, without increasing sampling number. The high accuracy of MS-QBI will contribute to the improved tractography. (author)

  3. Edge and line oriented contour detection : State of the art

    NARCIS (Netherlands)

    Papari, Giuseppe; Petkov, Nicolai

    We present an overview of various edge and line oriented approaches to contour detection that have been proposed in the last two decades. By edge and line oriented we mean methods that do not rely on segmentation. Distinction is made between edges and contours. Contour detectors are divided in local

  4. Financial Statement Fraud Detection using Text Mining

    OpenAIRE

    Rajan Gupta; Nasib Singh Gill

    2013-01-01

    Data mining techniques have been used enormously by the researchers’ community in detecting financial statement fraud. Most of the research in this direction has used the numbers (quantitative information) i.e. financial ratios present in the financial statements for detecting fraud. There is very little or no research on the analysis of text such as auditor’s comments or notes present in published reports. In this study we propose a text mining approach for detecting financial statement frau...

  5. Educational MOO: Text-Based Virtual Reality for Learning in Community. ERIC Digest.

    Science.gov (United States)

    Turbee, Lonnie

    MOO stands for "Multi-user domain, Object-Oriented." Early multi-user domains, or "MUDs," began as net-based dungeons-and-dragons type games, but MOOs have evolved from these origins to become some of cyberspace's most fascinating and engaging online communities. MOOs are social environments in a text-based virtual reality…

  6. Cloud Detection by Fusing Multi-Scale Convolutional Features

    Science.gov (United States)

    Li, Zhiwei; Shen, Huanfeng; Wei, Yancong; Cheng, Qing; Yuan, Qiangqiang

    2018-04-01

    Clouds detection is an important pre-processing step for accurate application of optical satellite imagery. Recent studies indicate that deep learning achieves best performance in image segmentation tasks. Aiming at boosting the accuracy of cloud detection for multispectral imagery, especially for those that contain only visible and near infrared bands, in this paper, we proposed a deep learning based cloud detection method termed MSCN (multi-scale cloud net), which segments cloud by fusing multi-scale convolutional features. MSCN was trained on a global cloud cover validation collection, and was tested in more than ten types of optical images with different resolution. Experiment results show that MSCN has obvious advantages over the traditional multi-feature combined cloud detection method in accuracy, especially when in snow and other areas covered by bright non-cloud objects. Besides, MSCN produced more detailed cloud masks than the compared deep cloud detection convolution network. The effectiveness of MSCN make it promising for practical application in multiple kinds of optical imagery.

  7. Multi-image screening technique applied to a general orientation training program

    International Nuclear Information System (INIS)

    Hajek, B.K.; Campbell, T.O.; Evans, A.D.; Hickey, J.M.

    1979-01-01

    A general orientation and training program is a prerequisite for personnel to have unescorted access to various site locations at a nuclear power plant. A new general orientation and training program is being developed for the Toledo Edison Company to be used at the Davis-Besse Nuclear Power Station. The program is presented in a multi-image and stereo sound format that has the unique capability to present the magnitude and scale of the plant, to arouse and maintain the interest of the viewer, and to instill in him a feeling of importance and pride about his job. Satisfactory completion of the program by individuals is assessed and certified by a machine scored test that is administered as an integral part of the presentation

  8. Multi-User Identification-Based Eye-Tracking Algorithm Using Position Estimation

    Directory of Open Access Journals (Sweden)

    Suk-Ju Kang

    2016-12-01

    Full Text Available This paper proposes a new multi-user eye-tracking algorithm using position estimation. Conventional eye-tracking algorithms are typically suitable only for a single user, and thereby cannot be used for a multi-user system. Even though they can be used to track the eyes of multiple users, their detection accuracy is low and they cannot identify multiple users individually. The proposed algorithm solves these problems and enhances the detection accuracy. Specifically, the proposed algorithm adopts a classifier to detect faces for the red, green, and blue (RGB and depth images. Then, it calculates features based on the histogram of the oriented gradient for the detected facial region to identify multiple users, and selects the template that best matches the users from a pre-determined face database. Finally, the proposed algorithm extracts the final eye positions based on anatomical proportions. Simulation results show that the proposed algorithm improved the average F1 score by up to 0.490, compared with benchmark algorithms.

  9. Contrast, size, and orientation-invariant target detection in infrared imagery

    Science.gov (United States)

    Zhou, Yi-Tong; Crawshaw, Richard D.

    1991-08-01

    Automatic target detection in IR imagery is a very difficult task due to variations in target brightness, shape, size, and orientation. In this paper, the authors present a contrast, size, and orientation invariant algorithm based on Gabor functions for detecting targets from a single IR image frame. The algorithms consists of three steps. First, it locates potential targets by using low-resolution Gabor functions which resist noise and background clutter effects, then, it removes false targets and eliminates redundant target points based on a similarity measure. These two steps mimic human vision processing but are different from Zeevi's Foveating Vision System. Finally, it uses both low- and high-resolution Gabor functions to verify target existence. This algorithm has been successfully tested on several IR images that contain multiple examples of military vehicles with different size and brightness in various background scenes and orientations.

  10. Inelastic x-ray study of plasmons in oriented single and multi-walled carbon nanotubes

    International Nuclear Information System (INIS)

    Casa, D.M.; Upton, M.H.; Gog, T.; Misewich, J.; Hill, J.P.; Lowndes, D.; Eres, G.

    2006-01-01

    Carbon nanotubes (CNT) have a wide variety of interesting properties and a large number of potential aplications in electronic and optical devices. In this study we concentrate on one important aspect of their electronic stucture: the plasmon dispersions in both single- and multi-wall CNTs and their relation to those in graphite. For the first time inelastic X-ray scattering is used to study these collective electronic excitations in oriented CNT samples. The experiments were performed on the IXS instrument at beamline 9ID CMC-XOR, APS, ANL. The incident energy was defined by a Si(333) monochromator, a spherically bent Ge(733) diced analyzer at the end of a 1-m arm focused the incident radiation onto a solid-state detector. The overall resolution was ∼300 meV FWHM. The incident photons were linearly polarized perpendicular to the scattering plane. Energy loss scans were taken by varying the incident energy while keeping the exit energy fixed at 8.9805 keV. The momentum transfer was kept along the nanotubes axis. Spectra were taken at room temperature. The samples were oriented CNTs (both single- and multi-wall) grown on a Si substrate. The samples referred to as 'single-wall' were in fact a few walls at most (1-5) while the multi-walled ones had ∼12 walls. Fig. 1. shows the inelastic spectra for the single-, multi-wall, and highly oriented pyrolithic graphite (HOPG) from top to bottom. Momentum transfer was Q = 0.79 (angstrom) -1 in all cases, its direction was along the tubes for the first two samples or parallel to the sheets for graphite. The peaks at ∼10 and ∼30 eV are known as the π and σ + π plasmons respectively. Fig. 2. shows the complete dispersion curves for both plasmon modes as a function of momentum transfer for all three samples.

  11. Image Fusion-Based Land Cover Change Detection Using Multi-Temporal High-Resolution Satellite Images

    Directory of Open Access Journals (Sweden)

    Biao Wang

    2017-08-01

    Full Text Available Change detection is usually treated as a problem of explicitly detecting land cover transitions in satellite images obtained at different times, and helps with emergency response and government management. This study presents an unsupervised change detection method based on the image fusion of multi-temporal images. The main objective of this study is to improve the accuracy of unsupervised change detection from high-resolution multi-temporal images. Our method effectively reduces change detection errors, since spatial displacement and spectral differences between multi-temporal images are evaluated. To this end, a total of four cross-fused images are generated with multi-temporal images, and the iteratively reweighted multivariate alteration detection (IR-MAD method—a measure for the spectral distortion of change information—is applied to the fused images. In this experiment, the land cover change maps were extracted using multi-temporal IKONOS-2, WorldView-3, and GF-1 satellite images. The effectiveness of the proposed method compared with other unsupervised change detection methods is demonstrated through experimentation. The proposed method achieved an overall accuracy of 80.51% and 97.87% for cases 1 and 2, respectively. Moreover, the proposed method performed better when differentiating the water area from the vegetation area compared to the existing change detection methods. Although the water area beneath moderate and sparse vegetation canopy was captured, vegetation cover and paved regions of the water body were the main sources of omission error, and commission errors occurred primarily in pixels of mixed land use and along the water body edge. Nevertheless, the proposed method, in conjunction with high-resolution satellite imagery, offers a robust and flexible approach to land cover change mapping that requires no ancillary data for rapid implementation.

  12. Detection of sexual orientation ("gaydar") by homosexual and heterosexual women.

    Science.gov (United States)

    Lyons, Minna; Lynch, Aoife; Brewer, Gayle; Bruno, Davide

    2014-02-01

    Although there has been considerable research investigating the ability to identify sexual orientation from static images, or "gaydar," few studies have considered the role of female sexual orientation or sexual interest (for example, sociosexual orientation) in judgment accuracy. In two studies, we investigated the sexuality detection ability, and masculinity and femininity as cues used in judgment. In Study 1, we recruited heterosexual (N = 55) and homosexual (N = 71) women to rate the sexual orientation of homosexual and heterosexual male and female targets (N = 80: 20 heterosexual men, 20 homosexual men, 20 heterosexual women, and 20 homosexual women). We found that detection accuracy was better than chance levels for both male and female targets and that male targets were more likely to be falsely labeled as homosexual than female targets were. Overall, female faces were more accurately identified as heterosexual or homosexual than male faces and homosexual female raters were biased towards labeling targets as homosexual. Sociosexuality did not influence the accuracy with which targets were identified as heterosexual or homosexual. In Study 2, 100 heterosexual and 20 homosexual women rated the stimulus for masculinity and femininity. Heterosexual women were rated as more feminine and less masculine than homosexual women and homosexual men were rated as more feminine and less masculine than heterosexual men. Sexual orientation of the judges did not affect the ratings. The results were discussed with a reference to evolutionary and cultural influences affecting sexual orientation judgment accuracy.

  13. SmartMal: a service-oriented behavioral malware detection framework for mobile devices.

    Science.gov (United States)

    Wang, Chao; Wu, Zhizhong; Li, Xi; Zhou, Xuehai; Wang, Aili; Hung, Patrick C K

    2014-01-01

    This paper presents SmartMal--a novel service-oriented behavioral malware detection framework for vehicular and mobile devices. The highlight of SmartMal is to introduce service-oriented architecture (SOA) concepts and behavior analysis into the malware detection paradigms. The proposed framework relies on client-server architecture, the client continuously extracts various features and transfers them to the server, and the server's main task is to detect anomalies using state-of-art detection algorithms. Multiple distributed servers simultaneously analyze the feature vector using various detectors and information fusion is used to concatenate the results of detectors. We also propose a cycle-based statistical approach for mobile device anomaly detection. We accomplish this by analyzing the users' regular usage patterns. Empirical results suggest that the proposed framework and novel anomaly detection algorithm are highly effective in detecting malware on Android devices.

  14. Ship Detection Using Transfer Learned Single Shot Multi Box Detector

    Directory of Open Access Journals (Sweden)

    Nie Gu-Hong

    2017-01-01

    Full Text Available Ship detection in satellite images is a challenging task. In this paper, we introduce a transfer learned Single Shot MultiBox Detector (SSD for ship detection. To this end, a state-of-the-art object detection model pre-trained from a large number of natural images was transfer learned for ship detection with limited labeled satellite images. To the best of our knowledge, this could be one of the first studies which introduce SSD into ship detection on satellite images. Experiments demonstrated that our method could achieve 87.9% AP at 47 FPS using NVIDIA TITAN X. In comparison with Faster R-CNN, 6.7% AP improvement could be achieved. Effects of the observation resolution has also been studied with the changing input sizes among 300 × 300, 600 × 600 and 900 × 900. It has been noted that the detection accuracy declined sharply with the decreasing resolution that is mainly caused by the missing small ships.

  15. 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)

  16. Segmentation and object-oriented classification of wetlands in a karst Florida landscape using multi-season Landsat-7 ETM+ Imagery

    Science.gov (United States)

    Segmentation and object-oriented processing of single-season and multi-season Landsat-7 ETM+ data was utilized for the classification of wetlands in a 1560 km2 study area of north central Florida. This segmentation and object-oriented classification outperformed the traditional ...

  17. Success probability orientated optimization model for resource allocation of the technological innovation multi-project system

    Institute of Scientific and Technical Information of China (English)

    Weixu Dai; Weiwei Wu; Bo Yu; Yunhao Zhu

    2016-01-01

    A success probability orientated optimization model for resource al ocation of the technological innovation multi-project system is studied. Based on the definition of the technological in-novation multi-project system, the leveling optimization of cost and success probability is set as the objective of resource al ocation. The cost function and the probability function of the optimization model are constructed. Then the objective function of the model is constructed and the solving process is explained. The model is applied to the resource al ocation of an enterprise’s technological innovation multi-project system. The results show that the pro-posed model is more effective in rational resource al ocation, and is more applicable in maximizing the utility of the technological innovation multi-project system.

  18. Predicting Teacher Emotional Labour Based on Multi-Frame Leadership Orientations: A Case from Turkey

    Science.gov (United States)

    Özdemir, Murat; Koçak, Seval

    2018-01-01

    Human behaviours in organisations are closely associated with leadership styles. The main purpose of this study is to find out the relationship between teachers' perception about multi-frame leadership orientations of principals and teachers' emotional labour. The study is based on Bolman and Deal's Four Frames Model, and, therefore, the…

  19. Multi-board concept - a scenario based approach for supporting product quality and life cycle oriented design

    DEFF Research Database (Denmark)

    Robotham, Antony John; Hertzum, Morten

    2000-01-01

    This paper will describe the multi-board concept, which is a working approach for supporting life cycle oriented design and product quality. Aspects of this concept include construction of a common working environment where multiple display boards depict scenarios of the product life cycle...... to believe that the multi-board concept promises to be a useful means of communication amongst the design team. We be-lieve that it fosters a thorough understanding of life cycle events, which, in turn, inspires the design of innovative products of the highest quality......., creating a shared quality mindset amongst design-ers, and developing creativity and synthesis in product design. The appropriateness of scenarios for supporting life cycle oriented design will be ar-gued and preliminary results from early experi-mentation will be presented.Initial results lead us...

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

    Science.gov (United States)

    McGlone, Thomas D. (Inventor)

    2017-01-01

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

  1. Detection of plane, poorly oriented wide flaws using focused transducers

    International Nuclear Information System (INIS)

    Vadder, D. de; Azou, P.; Bastien, P.; Saglio, R.

    1976-01-01

    The detection of plane, poorly oriented, wide flaws by ultrasonic non destructive testing is distinctly improved when using focused transducers. An increased echo can be obtained crossing the defect limit [fr

  2. OBTAINING APPROXIMATE VALUES OF EXTERIOR ORIENTATION ELEMENTS OF MULTI-INTERSECTION IMAGES USING PARTICLE SWARM OPTIMIZATION

    Directory of Open Access Journals (Sweden)

    X. Li

    2012-07-01

    Full Text Available In this paper, an efficient global optimization algorithm in the field of artificial intelligence, named Particle Swarm Optimization (PSO, is introduced into close range photogrammetric data processing. PSO can be applied to obtain the approximate values of exterior orientation elements under the condition that multi-intersection photography and a small portable plane control frame are used. PSO, put forward by an American social psychologist J. Kennedy and an electrical engineer R.C. Eberhart, is a stochastic global optimization method based on swarm intelligence, which was inspired by social behavior of bird flocking or fish schooling. The strategy of obtaining the approximate values of exterior orientation elements using PSO is as follows: in terms of image coordinate observed values and space coordinates of few control points, the equations of calculating the image coordinate residual errors can be given. The sum of absolute value of each image coordinate is minimized to be the objective function. The difference between image coordinate observed value and the image coordinate computed through collinear condition equation is defined as the image coordinate residual error. Firstly a gross area of exterior orientation elements is given, and then the adjustment of other parameters is made to get the particles fly in the gross area. After iterative computation for certain times, the satisfied approximate values of exterior orientation elements are obtained. By doing so, the procedures like positioning and measuring space control points in close range photogrammetry can be avoided. Obviously, this method can improve the surveying efficiency greatly and at the same time can decrease the surveying cost. And during such a process, only one small portable control frame with a couple of control points is employed, and there are no strict requirements for the space distribution of control points. In order to verify the effectiveness of this algorithm

  3. Robust Automated Image Co-Registration of Optical Multi-Sensor Time Series Data: Database Generation for Multi-Temporal Landslide Detection

    Directory of Open Access Journals (Sweden)

    Robert Behling

    2014-03-01

    Full Text Available Reliable multi-temporal landslide detection over longer periods of time requires multi-sensor time series data characterized by high internal geometric stability, as well as high relative and absolute accuracy. For this purpose, a new methodology for fully automated co-registration has been developed allowing efficient and robust spatial alignment of standard orthorectified data products originating from a multitude of optical satellite remote sensing data of varying spatial resolution. Correlation-based co-registration uses world-wide available terrain corrected Landsat Level 1T time series data as the spatial reference, ensuring global applicability. The developed approach has been applied to a multi-sensor time series of 592 remote sensing datasets covering an approximately 12,000 km2 area in Southern Kyrgyzstan (Central Asia strongly affected by landslides. The database contains images acquired during the last 26 years by Landsat (ETM, ASTER, SPOT and RapidEye sensors. Analysis of the spatial shifts obtained from co-registration has revealed sensor-specific alignments ranging between 5 m and more than 400 m. Overall accuracy assessment of these alignments has resulted in a high relative image-to-image accuracy of 17 m (RMSE and a high absolute accuracy of 23 m (RMSE for the whole co-registered database, making it suitable for multi-temporal landslide detection at a regional scale in Southern Kyrgyzstan.

  4. A Software Module for High-Accuracy Calibration of Rings and Cylinders on CMM using Multi-Orientation Techniques (Multi-Step and Reversal methods)

    DEFF Research Database (Denmark)

    Tosello, Guido; De Chiffre, Leonardo

    . The Centre for Geometrical Metrology (CGM) at the Technical University of Denmark takes care of free form measurements, in collaboration with DIMEG, University of Padova, Italy. The present report describes a software module, ROUNDCAL, to be used for high-accuracy calibration of rings and cylinders....... The purpose of the software is to calculate the form error and the least square circle of rings and cylinders by mean of average of pontwise measuring results becoming from so-called multi-orientation techniques (both reversal and multi-step methods) in order to eliminate systematic errors of CMM ....

  5. FULLY AUTOMATED IMAGE ORIENTATION IN THE ABSENCE OF TARGETS

    Directory of Open Access Journals (Sweden)

    C. Stamatopoulos

    2012-07-01

    Full Text Available Automated close-range photogrammetric network orientation has traditionally been associated with the use of coded targets in the object space to allow for an initial relative orientation (RO and subsequent spatial resection of the images. Over the past decade, automated orientation via feature-based matching (FBM techniques has attracted renewed research attention in both the photogrammetry and computer vision (CV communities. This is largely due to advances made towards the goal of automated relative orientation of multi-image networks covering untargetted (markerless objects. There are now a number of CV-based algorithms, with accompanying open-source software, that can achieve multi-image orientation within narrow-baseline networks. From a photogrammetric standpoint, the results are typically disappointing as the metric integrity of the resulting models is generally poor, or even unknown, while the number of outliers within the image matching and triangulation is large, and generally too large to allow relative orientation (RO via the commonly used coplanarity equations. On the other hand, there are few examples within the photogrammetric research field of automated markerless camera calibration to metric tolerances, and these too are restricted to narrow-baseline, low-convergence imaging geometry. The objective addressed in this paper is markerless automatic multi-image orientation, maintaining metric integrity, within networks that incorporate wide-baseline imagery. By wide-baseline we imply convergent multi-image configurations with convergence angles of up to around 90°. An associated aim is provision of a fast, fully automated process, which can be performed without user intervention. For this purpose, various algorithms require optimisation to allow parallel processing utilising multiple PC cores and graphics processing units (GPUs.

  6. Adaptive multi-resolution Modularity for detecting communities in networks

    Science.gov (United States)

    Chen, Shi; Wang, Zhi-Zhong; Bao, Mei-Hua; Tang, Liang; Zhou, Ji; Xiang, Ju; Li, Jian-Ming; Yi, Chen-He

    2018-02-01

    Community structure is a common topological property of complex networks, which attracted much attention from various fields. Optimizing quality functions for community structures is a kind of popular strategy for community detection, such as Modularity optimization. Here, we introduce a general definition of Modularity, by which several classical (multi-resolution) Modularity can be derived, and then propose a kind of adaptive (multi-resolution) Modularity that can combine the advantages of different Modularity. By applying the Modularity to various synthetic and real-world networks, we study the behaviors of the methods, showing the validity and advantages of the multi-resolution Modularity in community detection. The adaptive Modularity, as a kind of multi-resolution method, can naturally solve the first-type limit of Modularity and detect communities at different scales; it can quicken the disconnecting of communities and delay the breakup of communities in heterogeneous networks; and thus it is expected to generate the stable community structures in networks more effectively and have stronger tolerance against the second-type limit of Modularity.

  7. SU-E-J-15: Automatically Detect Patient Treatment Position and Orientation in KV Portal Images

    International Nuclear Information System (INIS)

    Qiu, J; Yang, D

    2015-01-01

    Purpose: In the course of radiation therapy, the complex information processing workflow will Result in potential errors, such as incorrect or inaccurate patient setups. With automatic image check and patient identification, such errors could be effectively reduced. For this purpose, we developed a simple and rapid image processing method, to automatically detect the patient position and orientation in 2D portal images, so to allow automatic check of positions and orientations for patient daily RT treatments. Methods: Based on the principle of portal image formation, a set of whole body DRR images were reconstructed from multiple whole body CT volume datasets, and fused together to be used as the matching template. To identify the patient setup position and orientation shown in a 2D portal image, the 2D portal image was preprocessed (contrast enhancement, down-sampling and couch table detection), then matched to the template image so to identify the laterality (left or right), position, orientation and treatment site. Results: Five day’s clinical qualified portal images were gathered randomly, then were processed by the automatic detection and matching method without any additional information. The detection results were visually checked by physicists. 182 images were correct detection in a total of 200kV portal images. The correct rate was 91%. Conclusion: The proposed method can detect patient setup and orientation quickly and automatically. It only requires the image intensity information in KV portal images. This method can be useful in the framework of Electronic Chart Check (ECCK) to reduce the potential errors in workflow of radiation therapy and so to improve patient safety. In addition, the auto-detection results, as the patient treatment site position and patient orientation, could be useful to guide the sequential image processing procedures, e.g. verification of patient daily setup accuracy. This work was partially supported by research grant from

  8. SU-E-J-15: Automatically Detect Patient Treatment Position and Orientation in KV Portal Images

    Energy Technology Data Exchange (ETDEWEB)

    Qiu, J [Washington University in St Louis, Taian, Shandong (China); Yang, D [Washington University School of Medicine, St Louis, MO (United States)

    2015-06-15

    Purpose: In the course of radiation therapy, the complex information processing workflow will Result in potential errors, such as incorrect or inaccurate patient setups. With automatic image check and patient identification, such errors could be effectively reduced. For this purpose, we developed a simple and rapid image processing method, to automatically detect the patient position and orientation in 2D portal images, so to allow automatic check of positions and orientations for patient daily RT treatments. Methods: Based on the principle of portal image formation, a set of whole body DRR images were reconstructed from multiple whole body CT volume datasets, and fused together to be used as the matching template. To identify the patient setup position and orientation shown in a 2D portal image, the 2D portal image was preprocessed (contrast enhancement, down-sampling and couch table detection), then matched to the template image so to identify the laterality (left or right), position, orientation and treatment site. Results: Five day’s clinical qualified portal images were gathered randomly, then were processed by the automatic detection and matching method without any additional information. The detection results were visually checked by physicists. 182 images were correct detection in a total of 200kV portal images. The correct rate was 91%. Conclusion: The proposed method can detect patient setup and orientation quickly and automatically. It only requires the image intensity information in KV portal images. This method can be useful in the framework of Electronic Chart Check (ECCK) to reduce the potential errors in workflow of radiation therapy and so to improve patient safety. In addition, the auto-detection results, as the patient treatment site position and patient orientation, could be useful to guide the sequential image processing procedures, e.g. verification of patient daily setup accuracy. This work was partially supported by research grant from

  9. Object-Oriented Query Language For Events Detection From Images Sequences

    Science.gov (United States)

    Ganea, Ion Eugen

    2015-09-01

    In this paper is presented a method to represent the events extracted from images sequences and the query language used for events detection. Using an object oriented model the spatial and temporal relationships between salient objects and also between events are stored and queried. This works aims to unify the storing and querying phases for video events processing. The object oriented language syntax used for events processing allow the instantiation of the indexes classes in order to improve the accuracy of the query results. The experiments were performed on images sequences provided from sport domain and it shows the reliability and the robustness of the proposed language. To extend the language will be added a specific syntax for constructing the templates for abnormal events and for detection of the incidents as the final goal of the research.

  10. Western Image of the Orient and Oriental in Agatha Christie’s Death on the Nile: A Postcolonial Reading

    Directory of Open Access Journals (Sweden)

    Mevlüde ZENGİN

    2016-12-01

    Full Text Available This paper attempts to read Agatha Christie’s Death on the Nile (1937, a Hercule Poirot detective novel from a postcolonial stand in general but in particular it seeks traces of Orientalism in it. Expertly plotted and set in Egypt, an exotic background, Death on the Nile is analyzed in this study, through Edward W. Said’s critique of Orientalism, to detect the novel’s projection of the Orient and oriental. Orientalism is defined by Edward Said in his groundbreaking book Orientalism (1978 as a scholarly discipline involving the negative portrayal of the East and eastern people, values and culture by westerners and as western construction of the Orient in occidental discourse through western perspective. Composed of two sections the essay begins with a brief introduction to postcolonial criticism and the critique of Orientalism. Next Death on the Nile is analyzed in the light of the criticism of Orientalism in the second section. The projection of the Orient and oriental people, places, values, concepts and so forth detected in the novel are presented in two subsections of this part. The study concludes that Death on the Nilebeing a detective novel has an orientalist quality when it comes to the reflection of the Orient and oriental though Christie does not foreground this quality of the novel. Another conclusion reached at the end of this study is that for Christie, the Queen of detective fiction has been considered to be a best-selling novelist of all time, her novel, Death on the Nile with its orientalist attitude to the East and easterner, must have contributed to the construction of a negative and false image of the Orient in western mind and discourse

  11. Multi-beam synchronous measurement based on PSD phase detection using frequency-domain multiplexing

    Science.gov (United States)

    Duan, Ying; Qin, Lan; Xue, Lian; Xi, Feng; Mao, Jiubing

    2013-10-01

    According to the principle of centroid measurement, position-sensitive detectors (PSD) are commonly used for micro displacement detection. However, single-beam detection method cannot satisfy such tasks as multi-dimension position measurement, three dimension vision reconstruction, and robot precision positioning, which require synchronous measurement of multiple light beams. Consequently, we designed PSD phase detection method using frequency-domain multiplexing for synchronous detection of multiple modulated light beams. Compared to previous PSD amplitude detection method, the phase detection method using FDM has advantages of simplified measuring system, low cost, high capability of resistance to light interference as well as improved resolution. The feasibility of multi-beam synchronous measurement based on PSD phase detection using FDM was validated by multi-beam measuring experiments. The maximum non-linearity error of the multi-beam synchronous measurement is 6.62%.

  12. Alignment of crystal orientations of the multi-domain photonic crystals in Parides sesostris wing scales

    Science.gov (United States)

    Yoshioka, S.; Fujita, H.; Kinoshita, S.; Matsuhana, B.

    2014-01-01

    It is known that the wing scales of the emerald-patched cattleheart butterfly, Parides sesostris, contain gyroid-type photonic crystals, which produce a green structural colour. However, the photonic crystal is not a single crystal that spreads over the entire scale, but it is separated into many small domains with different crystal orientations. As a photonic crystal generally has band gaps at different frequencies depending on the direction of light propagation, it seems mysterious that the scale is observed to be uniformly green under an optical microscope despite the multi-domain structure. In this study, we have carefully investigated the structure of the wing scale and discovered that the crystal orientations of different domains are not perfectly random, but there is a preferred crystal orientation that is aligned along the surface normal of the scale. This finding suggests that there is an additional factor during the developmental process of the microstructure that regulates the crystal orientation. PMID:24352678

  13. Multi-User Domain Object Oriented (MOO) as a High School Procedure for Foreign Language Acquisition.

    Science.gov (United States)

    Backer, James A.

    Foreign language students experience added difficulty when they are isolated from native speakers and from the culture of the target language. It has been posited that MOO (Multi-User Domain Object Oriented) may help overcome the geographical isolation of these students. MOOs are Internet-based virtual worlds in which people from all over the real…

  14. Using adversary text to detect adversary phase changes.

    Energy Technology Data Exchange (ETDEWEB)

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

    2009-05-01

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

  15. Sustainability-Oriented Financial Resource Allocation in a Project Portfolio through Multi-Criteria Decision-Making

    Directory of Open Access Journals (Sweden)

    Nomeda Dobrovolskienė

    2016-05-01

    Full Text Available Modern portfolio theory attempts to maximize the expected return of a portfolio for a given level of portfolio risk, or equivalently minimize risk for a given level of expected return. The reality, however, shows that, when selecting projects to a portfolio and allocating resources in the portfolio, an increasing number of organizations take into account other aspects as well. As a result of the sole purpose (risk-return, it offers only a partial solution for a sustainable organization. Existing project portfolio selection and resource allocation methods and models do not consider sustainability. Therefore, the aim of this article is to develop a sustainability-oriented model of financial resource allocation in a project portfolio by integrating a composite sustainability index of a project into Markowitz’s classical risk-return scheme (mean-variance model. The model was developed by applying multi-criteria decision-making methods. The practicability of the model was tested by an empirical study in a selected construction company. The proposed sustainability-oriented financial resource allocation model could be used in allocating financial resources in any type of business. The use of the model would not only help organisations to manage risk and achieve higher return but would also allow carrying out sustainable projects, thereby promoting greater environmental responsibility and giving more consideration to the wellbeing of future generations. Moreover, the model allows quantifying the impact of the integration of sustainability into financial resource allocation on the return of a portfolio.

  16. Intrusion detection model using fusion of chi-square feature selection and multi class SVM

    Directory of Open Access Journals (Sweden)

    Ikram Sumaiya Thaseen

    2017-10-01

    Full Text Available Intrusion detection is a promising area of research in the domain of security with the rapid development of internet in everyday life. Many intrusion detection systems (IDS employ a sole classifier algorithm for classifying network traffic as normal or abnormal. Due to the large amount of data, these sole classifier models fail to achieve a high attack detection rate with reduced false alarm rate. However by applying dimensionality reduction, data can be efficiently reduced to an optimal set of attributes without loss of information and then classified accurately using a multi class modeling technique for identifying the different network attacks. In this paper, we propose an intrusion detection model using chi-square feature selection and multi class support vector machine (SVM. A parameter tuning technique is adopted for optimization of Radial Basis Function kernel parameter namely gamma represented by ‘ϒ’ and over fitting constant ‘C’. These are the two important parameters required for the SVM model. The main idea behind this model is to construct a multi class SVM which has not been adopted for IDS so far to decrease the training and testing time and increase the individual classification accuracy of the network attacks. The investigational results on NSL-KDD dataset which is an enhanced version of KDDCup 1999 dataset shows that our proposed approach results in a better detection rate and reduced false alarm rate. An experimentation on the computational time required for training and testing is also carried out for usage in time critical applications.

  17. MixDroid: A multi-features and multi-classifiers bagging system for Android malware detection

    Science.gov (United States)

    Huang, Weiqing; Hou, Erhang; Zheng, Liang; Feng, Weimiao

    2018-05-01

    In the past decade, Android platform has rapidly taken over the mobile market for its superior convenience and open source characteristics. However, with the popularity of Android, malwares targeting on Android devices are increasing rapidly, while the conventional rule-based and expert-experienced approaches are no longer able to handle such explosive growth. In this paper, combining with the theory of natural language processing and machine learning, we not only implement the basic feature extraction of permission application features, but also propose two innovative schemes of feature extraction: Dalvik opcode features and malicious code image, and implement an automatic Android malware detection system MixDroid which is based on multi-features and multi-classifiers. According to our experiment results on 20,000 Android applications, detection accuracy of MixDroid is 98.1%, which proves our schemes' effectiveness in Android malware detection.

  18. Service-oriented multi-agent systems: architecture for the sensor web

    CSIR Research Space (South Africa)

    Terhorst, AL

    2006-03-01

    Full Text Available Understanding the behaviour of ecosystems requires persistent and multi-modal observation. Advances in sensor technology and distributed computing, coupled with the development of open standards that facilitate sensor/sensor network interoperability...

  19. Detecting Hotspot Information Using Multi-Attribute Based Topic Model.

    Directory of Open Access Journals (Sweden)

    Jing Wang

    Full Text Available Microblogging as a kind of social network has become more and more important in our daily lives. Enormous amounts of information are produced and shared on a daily basis. Detecting hot topics in the mountains of information can help people get to the essential information more quickly. However, due to short and sparse features, a large number of meaningless tweets and other characteristics of microblogs, traditional topic detection methods are often ineffective in detecting hot topics. In this paper, we propose a new topic model named multi-attribute latent dirichlet allocation (MA-LDA, in which the time and hashtag attributes of microblogs are incorporated into LDA model. By introducing time attribute, MA-LDA model can decide whether a word should appear in hot topics or not. Meanwhile, compared with the traditional LDA model, applying hashtag attribute in MA-LDA model gives the core words an artificially high ranking in results meaning the expressiveness of outcomes can be improved. Empirical evaluations on real data sets demonstrate that our method is able to detect hot topics more accurately and efficiently compared with several baselines. Our method provides strong evidence of the importance of the temporal factor in extracting hot topics.

  20. Utilizing Multi-Field Text Features for Efficient Email Spam Filtering

    Directory of Open Access Journals (Sweden)

    Wuying Liu

    2012-06-01

    Full Text Available Large-scale spam emails cause a serious waste of time and resources. This paper investigates the text features of email documents and the feature noises among multi-field texts, resulting in an observation of a power law distribution of feature strings within each text field. According to the observation, we propose an efficient filtering approach including a compound weight method and a lightweight field text classification algorithm. The compound weight method considers both the historical classifying ability of each field classifier and the classifying contribution of each text field in the current classified email. The lightweight field text classification algorithm straightforwardly calculates the arithmetical average of multiple conditional probabilities predicted from feature strings according to a string-frequency index for labeled emails storing. The string-frequency index structure has a random-sampling-based compressible property owing to the power law distribution and can largely reduce the storage space. The experimental results in the TREC spam track show that the proposed approach can complete the filtering task in low space cost and high speed, whose overall performance 1-ROCA exceeds the best one among the participators at the trec07p evaluation.

  1. Distributed Fault Detection and Isolation for Flocking in a Multi-robot System with Imperfect Communication

    Directory of Open Access Journals (Sweden)

    Shao Shiliang

    2014-06-01

    Full Text Available In this paper, we focus on distributed fault detection and isolation (FDI for a multi-robot system where multiple robots execute a flocking task. Firstly, we propose a fault detection method based on the local-information-exchange and sensor-measurement technologies to cover cases of both perfect communication and imperfect communication. The two detection technologies can be adaptively selected according to the packet loss rate (PLR. Secondly, we design a fault isolation method, considering a situation in which faulty robots still influence the behaviours of other robots. Finally, a complete FDI scheme, based on the proposed detection and isolation methods, is simulated in various scenarios. The results demonstrate that our FDI scheme is effective.

  2. An Amperometric Immunosensor Based on Graphene Composite Film and Protein a for Chlorpyrifos Detection

    Directory of Open Access Journals (Sweden)

    Xiangyou Wang

    2014-09-01

    Full Text Available In this paper, an immunosensor was designed for chlorpyrifos detection, which was based on graphene-multi-walled carbon nanotubes-gold nanoparticle-chitosan (GR-MWCNTs-AuNPs- CHIT nanocomposite film. Protein A (SPA can combine with gold nanoparticles, which made anti- chlorpyrifos antibody immobilized orientedly, eventually the modified immunosensor was developed for the detection of chlorpyrifos residues. Under the optimized conditions, a regression equation: y=9.5676 lgC (ng/mL +18.164 (R2=0.9976 was obtained with a detection limit as low as 0.037 ng/mL. The proposed chlorpyrifos immunosensor exhibited high reproducibility, stability, and good selectivity and regeneration, it has the potential of real sample detection.

  3. Analysis of Oriented Texture - with application to the Detection of Architectural Distortion in Mammograms with Application to the Detection of Architectural Distortion in Mammograms

    CERN Document Server

    Ayres, Fabio; Desautels, JE Leo

    2011-01-01

    The presence of oriented features in images often conveys important information about the scene or the objects contained; the analysis of oriented patterns is an important task in the general framework of image understanding. As in many other applications of computer vision, the general framework for the understanding of oriented features in images can be divided into low- and high-level analysis. In the context of the study of oriented features, low-level analysis includes the detection of oriented features in images; a measure of the local magnitude and orientation of oriented features over

  4. Deep Space Detection of Oriented Ice Crystals

    Science.gov (United States)

    Marshak, A.; Varnai, T.; Kostinski, A. B.

    2017-12-01

    The deep space climate observatory (DSCOVR) spacecraft resides at the first Lagrangian point about one million miles from Earth. A polychromatic imaging camera onboard delivers nearly hourly observations of the entire sun-lit face of the Earth. Many images contain unexpected bright flashes of light over both ocean and land. We constructed a yearlong time series of flash latitudes, scattering angles and oxygen absorption to demonstrate conclusively that the flashes over land are specular reflections off tiny ice crystals floating in the air nearly horizontally. Such deep space detection of tropospheric ice can be used to constrain the likelihood of oriented crystals and their contribution to Earth albedo.

  5. Case-Based Multi-Sensor Intrusion Detection

    Science.gov (United States)

    Schwartz, Daniel G.; Long, Jidong

    2009-08-01

    Multi-sensor intrusion detection systems (IDSs) combine the alerts raised by individual IDSs and possibly other kinds of devices such as firewalls and antivirus software. A critical issue in building a multi-sensor IDS is alert-correlation, i.e., determining which alerts are caused by the same attack. This paper explores a novel approach to alert correlation using case-based reasoning (CBR). Each case in the CBR system's library contains a pattern of alerts raised by some known attack type, together with the identity of the attack. Then during run time, the alert streams gleaned from the sensors are compared with the patterns in the cases, and a match indicates that the attack described by that case has occurred. For this purpose the design of a fast and accurate matching algorithm is imperative. Two such algorithms were explored: (i) the well-known Hungarian algorithm, and (ii) an order-preserving matching of our own device. Tests were conducted using the DARPA Grand Challenge Problem attack simulator. These showed that the both matching algorithms are effective in detecting attacks; but the Hungarian algorithm is inefficient; whereas the order-preserving one is very efficient, in fact runs in linear time.

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

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg

    2005-01-01

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

  7. Detecting bots using multi-level traffic analysis

    DEFF Research Database (Denmark)

    Stevanovic, Matija; Pedersen, Jens Myrup

    2016-01-01

    introduces a novel multi-level botnet detection approach that performs network traffic analysis of three protocols widely considered as the main carriers of botnet Command and Control (C&C) and attack traffic, i.e. TCP, UDP and DNS. The proposed method relies on supervised machine learning for identifying...

  8. A Cost Effective Multi-Spectral Scanner for Natural Gas Detection

    Energy Technology Data Exchange (ETDEWEB)

    Yudaya Sivathanu; Jongmook Lim; Vinoo Narayanan; Seonghyeon Park

    2005-12-07

    The objective of this project is to design, fabricate and demonstrate a cost effective, multi-spectral scanner for natural gas leak detection in transmission and distribution pipelines. During the first year of the project, a laboratory version of the multi-spectral scanner was designed, fabricated, and tested at EnUrga Inc. The multi-spectral scanner was also evaluated using a blind Department of Energy study at the Rocky Mountain Oilfield Testing Center. The performance of the scanner was inconsistent during the blind study. However, most of the leaks were outside the view of the multi-spectral scanner that was developed during the first year of the project. Therefore, a definite evaluation of the capability of the scanner was not obtained. Despite the results, sufficient number of plumes was detected fully confirming the feasibility of the multi-spectral scanner. During the second year, the optical design of the scanner was changed to improve the sensitivity of the system. Laboratory tests show that the system can reliably detect small leaks (20 SCFH) at 30 to 50 feet. A prototype scanner was built and evaluated during the second year of the project. Only laboratory evaluations were completed during the second year. The laboratory evaluations show the feasibility of using the scanner to determine natural gas pipeline leaks. Further field evaluations and optimization of the scanner are required before commercialization of the scanner can be initiated.

  9. An improved reconstruction algorithm based on multi-user detection for uplink grant-free NOMA

    Directory of Open Access Journals (Sweden)

    Hou Chengyan

    2017-01-01

    Full Text Available For the traditional orthogonal matching pursuit(OMP algorithm in multi-user detection(MUD for uplink grant-free NOMA, here is a poor BER performance, so in this paper we propose an temporal-correlation orthogonal matching pursuit algorithm(TOMP to realize muli-user detection. The core idea of the TOMP is to use the time correlation of the active user sets to achieve user activity and data detection in a number of continuous time slots. We use the estimated active user set in the current time slot as a priori information to estimate the active user sets for the next slot. By maintaining the active user set Tˆl of size K(K is the number of users, but modified in each iteration. Specifically, active user set is believed to be reliable in one iteration but shown error in another iteration, can be added to the set path delay Tˆl or removed from it. Theoretical analysis of the improved algorithm provide a guarantee that the multi-user can be successfully detected with a high probability. The simulation results show that the proposed scheme can achieve better bit error rate (BER performance in the uplink grant-free NOMA system.

  10. Ship Detection in Optical Remote Sensing Images Based on Wavelet Transform and Multi-Level False Alarm Identification

    Directory of Open Access Journals (Sweden)

    Fang Xu

    2017-09-01

    Full Text Available Ship detection by Unmanned Airborne Vehicles (UAVs and satellites plays an important role in a spectrum of related military and civil applications. To improve the detection efficiency, accuracy, and speed, a novel ship detection method from coarse to fine is presented. Ship targets are viewed as uncommon regions in the sea background caused by the differences in colors, textures, shapes, or other factors. Inspired by this fact, a global saliency model is constructed based on high-frequency coefficients of the multi-scale and multi-direction wavelet decomposition, which can characterize different feature information from edge to texture of the input image. To further reduce the false alarms, a new and effective multi-level discrimination method is designed based on the improved entropy and pixel distribution, which is robust against the interferences introduced by islands, coastlines, clouds, and shadows. The experimental results on optical remote sensing images validate that the presented saliency model outperforms the comparative models in terms of the area under the receiver operating characteristic curves core and the accuracy in the images with different sizes. After the target identification, the locations and the number of the ships in various sizes and colors can be detected accurately and fast with high robustness.

  11. Multi-Modal Detection and Mapping of Static and Dynamic Obstacles in Agriculture for Process Evaluation

    Directory of Open Access Journals (Sweden)

    Timo Korthals

    2018-03-01

    Full Text Available Today, agricultural vehicles are available that can automatically perform tasks such as weed detection and spraying, mowing, and sowing while being steered automatically. However, for such systems to be fully autonomous and self-driven, not only their specific agricultural tasks must be automated. An accurate and robust perception system automatically detecting and avoiding all obstacles must also be realized to ensure safety of humans, animals, and other surroundings. In this paper, we present a multi-modal obstacle and environment detection and recognition approach for process evaluation in agricultural fields. The proposed pipeline detects and maps static and dynamic obstacles globally, while providing process-relevant information along the traversed trajectory. Detection algorithms are introduced for a variety of sensor technologies, including range sensors (lidar and radar and cameras (stereo and thermal. Detection information is mapped globally into semantical occupancy grid maps and fused across all sensors with late fusion, resulting in accurate traversability assessment and semantical mapping of process-relevant categories (e.g., crop, ground, and obstacles. Finally, a decoding step uses a Hidden Markov model to extract relevant process-specific parameters along the trajectory of the vehicle, thus informing a potential control system of unexpected structures in the planned path. The method is evaluated on a public dataset for multi-modal obstacle detection in agricultural fields. Results show that a combination of multiple sensor modalities increases detection performance and that different fusion strategies must be applied between algorithms detecting similar and dissimilar classes.

  12. Multi-Branch Fully Convolutional Network for Face Detection

    KAUST Repository

    Bai, Yancheng; Ghanem, Bernard

    2017-01-01

    Face detection is a fundamental problem in computer vision. It is still a challenging task in unconstrained conditions due to significant variations in scale, pose, expressions, and occlusion. In this paper, we propose a multi-branch fully

  13. A study of earthquake-induced building detection by object oriented classification approach

    Science.gov (United States)

    Sabuncu, Asli; Damla Uca Avci, Zehra; Sunar, Filiz

    2017-04-01

    Among the natural hazards, earthquakes are the most destructive disasters and cause huge loss of lives, heavily infrastructure damages and great financial losses every year all around the world. According to the statistics about the earthquakes, more than a million earthquakes occur which is equal to two earthquakes per minute in the world. Natural disasters have brought more than 780.000 deaths approximately % 60 of all mortality is due to the earthquakes after 2001. A great earthquake took place at 38.75 N 43.36 E in the eastern part of Turkey in Van Province on On October 23th, 2011. 604 people died and about 4000 buildings seriously damaged and collapsed after this earthquake. In recent years, the use of object oriented classification approach based on different object features, such as spectral, textural, shape and spatial information, has gained importance and became widespread for the classification of high-resolution satellite images and orthophotos. The motivation of this study is to detect the collapsed buildings and debris areas after the earthquake by using very high-resolution satellite images and orthophotos with the object oriented classification and also see how well remote sensing technology was carried out in determining the collapsed buildings. In this study, two different land surfaces were selected as homogenous and heterogeneous case study areas. In the first step of application, multi-resolution segmentation was applied and optimum parameters were selected to obtain the objects in each area after testing different color/shape and compactness/smoothness values. In the next step, two different classification approaches, namely "supervised" and "unsupervised" approaches were applied and their classification performances were compared. Object-based Image Analysis (OBIA) was performed using e-Cognition software.

  14. SPEEDY RECOVERY OF DAMAGED DIGITAL PHOTOGRAPHS USING MULTI STRUCTURE MORPHOLOGY

    Directory of Open Access Journals (Sweden)

    D. Jemi Florinabel

    2011-11-01

    Full Text Available A speedy recovery of damaged digitized photographs based on orientation driven multi structure morphology is proposed. The recovery order plays an important factor for human visualization and hence it is guided by the orientation of edges at the surrounding known regions of the missing domain. The image is edge detected by thresholding the image gradient along the eight possible orientations. These eight edge images are represented as eight edge planes. The edge-plane-sliced information is used twice manifold for reconstructing the regions within the missing part, as well as for guiding the integration that follows. The damaged regions are morphologically eroded using the structuring elements of corresponding orientations dictated by the edge-planes. The resultant filled image is obtained using local isotopic driven integration. The novelty of our approach is to explicitly specify the direction of filling herby ensuring ease in convergence in different orientations and then streamlining the process to guarantee complete and natural look. By implementing region-filling through morphological erosion, several pixels instead of one can be restored at every inpainting step, making the method faster than many traditional texture synthesis inpainting algorithms and successfully recovers images with better Peak Signal to Noise ratios even for massive damages.

  15. A performance-oriented power transformer design methodology using multi-objective evolutionary optimization.

    Science.gov (United States)

    Adly, Amr A; Abd-El-Hafiz, Salwa K

    2015-05-01

    Transformers are regarded as crucial components in power systems. Due to market globalization, power transformer manufacturers are facing an increasingly competitive environment that mandates the adoption of design strategies yielding better performance at lower costs. In this paper, a power transformer design methodology using multi-objective evolutionary optimization is proposed. Using this methodology, which is tailored to be target performance design-oriented, quick rough estimation of transformer design specifics may be inferred. Testing of the suggested approach revealed significant qualitative and quantitative match with measured design and performance values. Details of the proposed methodology as well as sample design results are reported in the paper.

  16. Evaluating spatial- and temporal-oriented multi-dimensional visualization techniques

    Directory of Open Access Journals (Sweden)

    Chong Ho Yu

    2003-07-01

    Full Text Available Visualization tools are said to be helpful for researchers to unveil hidden patterns and..relationships among variables, and also for teachers to present abstract statistical concepts and..complicated data structures in a concrete manner. However, higher-dimension visualization..techniques can be confusing and even misleading, especially when human-instrument interface..and cognitive issues are under-applied. In this article, the efficacy of function-based, datadriven,..spatial-oriented, and temporal-oriented visualization techniques are discussed based..upon extensive review. Readers can find practical implications for both research and..instructional practices. For research purposes, the spatial-based graphs, such as Trellis displays..in S-Plus, are preferable over the temporal-based displays, such as the 3D animated plot in..SAS/Insight. For teaching purposes, the temporal-based displays, such as the 3D animation plot..in Maple, seem to have advantages over the spatial-based graphs, such as the 3D triangular..coordinate plot in SyStat.

  17. Layer-oriented multigrid wavefront reconstruction algorithms for multi-conjugate adaptive optics

    Science.gov (United States)

    Gilles, Luc; Ellerbroek, Brent L.; Vogel, Curtis R.

    2003-02-01

    Multi-conjugate adaptive optics (MCAO) systems with 104-105 degrees of freedom have been proposed for future giant telescopes. Using standard matrix methods to compute, optimize, and implement wavefront control algorithms for these systems is impractical, since the number of calculations required to compute and apply the reconstruction matrix scales respectively with the cube and the square of the number of AO degrees of freedom. In this paper, we develop an iterative sparse matrix implementation of minimum variance wavefront reconstruction for telescope diameters up to 32m with more than 104 actuators. The basic approach is the preconditioned conjugate gradient method, using a multigrid preconditioner incorporating a layer-oriented (block) symmetric Gauss-Seidel iterative smoothing operator. We present open-loop numerical simulation results to illustrate algorithm convergence.

  18. Secure Distributed Detection under Energy Constraint in IoT-Oriented Sensor Networks

    Directory of Open Access Journals (Sweden)

    Guomei Zhang

    2016-12-01

    Full Text Available We study the secure distributed detection problems under energy constraint for IoT-oriented sensor networks. The conventional channel-aware encryption (CAE is an efficient physical-layer secure distributed detection scheme in light of its energy efficiency, good scalability and robustness over diverse eavesdropping scenarios. However, in the CAE scheme, it remains an open problem of how to optimize the key thresholds for the estimated channel gain, which are used to determine the sensor’s reporting action. Moreover, the CAE scheme does not jointly consider the accuracy of local detection results in determining whether to stay dormant for a sensor. To solve these problems, we first analyze the error probability and derive the optimal thresholds in the CAE scheme under a specified energy constraint. These results build a convenient mathematic framework for our further innovative design. Under this framework, we propose a hybrid secure distributed detection scheme. Our proposal can satisfy the energy constraint by keeping some sensors inactive according to the local detection confidence level, which is characterized by likelihood ratio. In the meanwhile, the security is guaranteed through randomly flipping the local decisions forwarded to the fusion center based on the channel amplitude. We further optimize the key parameters of our hybrid scheme, including two local decision thresholds and one channel comparison threshold. Performance evaluation results demonstrate that our hybrid scheme outperforms the CAE under stringent energy constraints, especially in the high signal-to-noise ratio scenario, while the security is still assured.

  19. Reliability-oriented multi-objective optimal decision-making approach for uncertainty-based watershed load reduction

    International Nuclear Information System (INIS)

    Dong, Feifei; Liu, Yong; Su, Han; Zou, Rui; Guo, Huaicheng

    2015-01-01

    Water quality management and load reduction are subject to inherent uncertainties in watershed systems and competing decision objectives. Therefore, optimal decision-making modeling in watershed load reduction is suffering due to the following challenges: (a) it is difficult to obtain absolutely “optimal” solutions, and (b) decision schemes may be vulnerable to failure. The probability that solutions are feasible under uncertainties is defined as reliability. A reliability-oriented multi-objective (ROMO) decision-making approach was proposed in this study for optimal decision making with stochastic parameters and multiple decision reliability objectives. Lake Dianchi, one of the three most eutrophic lakes in China, was examined as a case study for optimal watershed nutrient load reduction to restore lake water quality. This study aimed to maximize reliability levels from considerations of cost and load reductions. The Pareto solutions of the ROMO optimization model were generated with the multi-objective evolutionary algorithm, demonstrating schemes representing different biases towards reliability. The Pareto fronts of six maximum allowable emission (MAE) scenarios were obtained, which indicated that decisions may be unreliable under unpractical load reduction requirements. A decision scheme identification process was conducted using the back propagation neural network (BPNN) method to provide a shortcut for identifying schemes at specific reliability levels for decision makers. The model results indicated that the ROMO approach can offer decision makers great insights into reliability tradeoffs and can thus help them to avoid ineffective decisions. - Highlights: • Reliability-oriented multi-objective (ROMO) optimal decision approach was proposed. • The approach can avoid specifying reliability levels prior to optimization modeling. • Multiple reliability objectives can be systematically balanced using Pareto fronts. • Neural network model was used to

  20. Reliability-oriented multi-objective optimal decision-making approach for uncertainty-based watershed load reduction

    Energy Technology Data Exchange (ETDEWEB)

    Dong, Feifei [College of Environmental Science and Engineering, Key Laboratory of Water and Sediment Sciences (MOE), Peking University, Beijing 100871 (China); Liu, Yong, E-mail: yongliu@pku.edu.cn [College of Environmental Science and Engineering, Key Laboratory of Water and Sediment Sciences (MOE), Peking University, Beijing 100871 (China); Institute of Water Sciences, Peking University, Beijing 100871 (China); Su, Han [College of Environmental Science and Engineering, Key Laboratory of Water and Sediment Sciences (MOE), Peking University, Beijing 100871 (China); Zou, Rui [Tetra Tech, Inc., 10306 Eaton Place, Ste 340, Fairfax, VA 22030 (United States); Yunnan Key Laboratory of Pollution Process and Management of Plateau Lake-Watershed, Kunming 650034 (China); Guo, Huaicheng [College of Environmental Science and Engineering, Key Laboratory of Water and Sediment Sciences (MOE), Peking University, Beijing 100871 (China)

    2015-05-15

    Water quality management and load reduction are subject to inherent uncertainties in watershed systems and competing decision objectives. Therefore, optimal decision-making modeling in watershed load reduction is suffering due to the following challenges: (a) it is difficult to obtain absolutely “optimal” solutions, and (b) decision schemes may be vulnerable to failure. The probability that solutions are feasible under uncertainties is defined as reliability. A reliability-oriented multi-objective (ROMO) decision-making approach was proposed in this study for optimal decision making with stochastic parameters and multiple decision reliability objectives. Lake Dianchi, one of the three most eutrophic lakes in China, was examined as a case study for optimal watershed nutrient load reduction to restore lake water quality. This study aimed to maximize reliability levels from considerations of cost and load reductions. The Pareto solutions of the ROMO optimization model were generated with the multi-objective evolutionary algorithm, demonstrating schemes representing different biases towards reliability. The Pareto fronts of six maximum allowable emission (MAE) scenarios were obtained, which indicated that decisions may be unreliable under unpractical load reduction requirements. A decision scheme identification process was conducted using the back propagation neural network (BPNN) method to provide a shortcut for identifying schemes at specific reliability levels for decision makers. The model results indicated that the ROMO approach can offer decision makers great insights into reliability tradeoffs and can thus help them to avoid ineffective decisions. - Highlights: • Reliability-oriented multi-objective (ROMO) optimal decision approach was proposed. • The approach can avoid specifying reliability levels prior to optimization modeling. • Multiple reliability objectives can be systematically balanced using Pareto fronts. • Neural network model was used to

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

    Science.gov (United States)

    Zhang, Li; He, Rongjun

    2018-03-01

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

  2. Action detection by double hierarchical multi-structure space-time statistical matching model

    Science.gov (United States)

    Han, Jing; Zhu, Junwei; Cui, Yiyin; Bai, Lianfa; Yue, Jiang

    2018-03-01

    Aimed at the complex information in videos and low detection efficiency, an actions detection model based on neighboring Gaussian structure and 3D LARK features is put forward. We exploit a double hierarchical multi-structure space-time statistical matching model (DMSM) in temporal action localization. First, a neighboring Gaussian structure is presented to describe the multi-scale structural relationship. Then, a space-time statistical matching method is proposed to achieve two similarity matrices on both large and small scales, which combines double hierarchical structural constraints in model by both the neighboring Gaussian structure and the 3D LARK local structure. Finally, the double hierarchical similarity is fused and analyzed to detect actions. Besides, the multi-scale composite template extends the model application into multi-view. Experimental results of DMSM on the complex visual tracker benchmark data sets and THUMOS 2014 data sets show the promising performance. Compared with other state-of-the-art algorithm, DMSM achieves superior performances.

  3. Packer Detection for Multi-Layer Executables Using Entropy Analysis

    Directory of Open Access Journals (Sweden)

    Munkhbayar Bat-Erdene

    2017-03-01

    Full Text Available Packing algorithms are broadly used to avoid anti-malware systems, and the proportion of packed malware has been growing rapidly. However, just a few studies have been conducted on detection various types of packing algorithms in a systemic way. Following this understanding, we elaborate a method to classify packing algorithms of a given executable into three categories: single-layer packing, re-packing, or multi-layer packing. We convert entropy values of the executable file loaded into memory into symbolic representations, for which we used SAX (Symbolic Aggregate Approximation. Based on experiments of 2196 programs and 19 packing algorithms, we identify that precision (97.7%, accuracy (97.5%, and recall ( 96.8% of our method are respectively high to confirm that entropy analysis is applicable in identifying packing algorithms.

  4. Aircraft Detection from VHR Images Based on Circle-Frequency Filter and Multilevel Features

    Directory of Open Access Journals (Sweden)

    Feng Gao

    2013-01-01

    Full Text Available Aircraft automatic detection from very high-resolution (VHR images plays an important role in a wide variety of applications. This paper proposes a novel detector for aircraft detection from very high-resolution (VHR remote sensing images. To accurately distinguish aircrafts from background, a circle-frequency filter (CF-filter is used to extract the candidate locations of aircrafts from a large size image. A multi-level feature model is then employed to represent both local appearance and spatial layout of aircrafts by means of Robust Hue Descriptor and Histogram of Oriented Gradients. The experimental results demonstrate the superior performance of the proposed method.

  5. Broader visual orientation tuning in patients with schizophrenia

    Directory of Open Access Journals (Sweden)

    Ariel eRokem

    2011-11-01

    Full Text Available Reduced gamma-aminobutyric acid (GABA levels in cerebral cortex are thought to contribute to information processing deficits in patients with schizophrenia (SZ, and we have previously reported lower in vivo GABA levels in the visual cortex of patients with SZ. GABA-mediated inhibition plays a role in sharpening orientation tuning of visual cortical neurons. Therefore, we predicted that tuning for visual stimulus orientation would be wider in SZ. We measured orientation tuning with a psychophysical procedure in which subjects performed a target detection task of a low-contrast oriented grating, following adaptation to a high-contrast grating. Contrast detection thresholds were determined for a range of adapter-target orientation offsets. For both SZ and healthy controls, contrast thresholds decreased as orientation offset increased, suggesting that this tuning curve reflects the selectivity of visual cortical neurons for stimulus orientation. After accounting for generalized deficits in task performance in SZ, there was no difference between patients and controls for detection of target stimuli having either the same orientation as the adapter or orientations far from the adapter. However, patients’ thresholds were significantly higher for intermediate adapter-target offsets. In addition, the mean width parameter of a Gaussian fit to the psychophysical orientation tuning curves was significantly larger for the patient group. We also present preliminary data relating visual cortical GABA levels, as measured with magnetic resonance spectroscopy, and orientation tuning width. These results suggest that our finding of broader orientation tuning in SZ may be due to diminished visual cortical GABA levels.

  6. Multi-scale analysis of the European airspace using network community detection.

    Directory of Open Access Journals (Sweden)

    Gérald Gurtner

    Full Text Available We show that the European airspace can be represented as a multi-scale traffic network whose nodes are airports, sectors, or navigation points and links are defined and weighted according to the traffic of flights between the nodes. By using a unique database of the air traffic in the European airspace, we investigate the architecture of these networks with a special emphasis on their community structure. We propose that unsupervised network community detection algorithms can be used to monitor the current use of the airspace and improve it by guiding the design of new ones. Specifically, we compare the performance of several community detection algorithms, both with fixed and variable resolution, and also by using a null model which takes into account the spatial distance between nodes, and we discuss their ability to find communities that could be used to define new control units of the airspace.

  7. Measuring the purpose of firms' customer and competitor-oriented activities

    DEFF Research Database (Denmark)

    Sørensen, Hans Eibe

    Traditional empirical market orientation research predominantly focuses on the presence of firms' market-oriented activities. This paper empirically explores a novel structure of four multi-indicator measures assessing the purpose of firms' customer and competitor-oriented activities. The operati......Traditional empirical market orientation research predominantly focuses on the presence of firms' market-oriented activities. This paper empirically explores a novel structure of four multi-indicator measures assessing the purpose of firms' customer and competitor-oriented activities...

  8. Detection of preferential particle orientation in the atmosphere: Development of an alternative polarization lidar system

    International Nuclear Information System (INIS)

    Geier, Manfred; Arienti, Marco

    2014-01-01

    Increasing interest in polarimetric characterization of atmospheric aerosols has led to the development of complete sample-measuring (Mueller) polarimeters that are capable of measuring the entire backscattering phase matrix of a probed volume. These Mueller polarimeters consist of several moving parts, which limit measurement rates and complicate data analysis. In this paper, we present the concept of a less complex polarization lidar setup for detection of preferential orientation of atmospheric particulates. On the basis of theoretical considerations of data inversion stability and propagation of measurement uncertainties, an optimum optical configuration is established for two modes of operation (with either a linear or a circular polarized incident laser beam). The conceptualized setup falls in the category of incomplete sample-measuring polarimeters and uses four detection channels for simultaneous measurement of the backscattered light. The expected performance characteristics are discussed through an example of a typical aerosol with a small fraction of particles oriented in a preferred direction. The theoretical analysis suggests that achievable accuracies in backscatter cross-sections and depolarization ratios are similar to those with conventional two-channel configurations, while in addition preferential orientation can be detected with the proposed four-channel system for a wide range of conditions. - Highlights: • A theoretical study of a new four-channel lidar concept is offered. • Preferential particle orientation detection could be realized with minor device modifications. • The proposed configuration is optimized to balance inversion uncertainties. • Circular polarized beam is demonstrated to provide the best noise performance. • Operation with ultra-short pulses is proposed to quantify particle number density

  9. Visual Saliency Models for Text Detection in Real World.

    Directory of Open Access Journals (Sweden)

    Renwu Gao

    Full Text Available This paper evaluates the degree of saliency of texts in natural scenes using visual saliency models. A large scale scene image database with pixel level ground truth is created for this purpose. Using this scene image database and five state-of-the-art models, visual saliency maps that represent the degree of saliency of the objects are calculated. The receiver operating characteristic curve is employed in order to evaluate the saliency of scene texts, which is calculated by visual saliency models. A visualization of the distribution of scene texts and non-texts in the space constructed by three kinds of saliency maps, which are calculated using Itti's visual saliency model with intensity, color and orientation features, is given. This visualization of distribution indicates that text characters are more salient than their non-text neighbors, and can be captured from the background. Therefore, scene texts can be extracted from the scene images. With this in mind, a new visual saliency architecture, named hierarchical visual saliency model, is proposed. Hierarchical visual saliency model is based on Itti's model and consists of two stages. In the first stage, Itti's model is used to calculate the saliency map, and Otsu's global thresholding algorithm is applied to extract the salient region that we are interested in. In the second stage, Itti's model is applied to the salient region to calculate the final saliency map. An experimental evaluation demonstrates that the proposed model outperforms Itti's model in terms of captured scene texts.

  10. Agent-Oriented Embedded Control System Design and Development of a Vision-Based Automated Guided Vehicle

    Directory of Open Access Journals (Sweden)

    Wu Xing

    2012-07-01

    Full Text Available This paper presents a control system design and development approach for a vision-based automated guided vehicle (AGV based on the multi-agent system (MAS methodology and embedded system resources. A three-phase agent-oriented design methodology Prometheus is used to analyse system functions, construct operation scenarios, define agent types and design the MAS coordination mechanism. The control system is then developed in an embedded implementation containing a digital signal processor (DSP and an advanced RISC machine (ARM by using the multitasking processing capacity of multiple microprocessors and system services of a real-time operating system (RTOS. As a paradigm, an onboard embedded controller is designed and developed for the AGV with a camera detecting guiding landmarks, and the entire procedure has a high efficiency and a clear hierarchy. A vision guidance experiment for our AGV is carried out in a space-limited laboratory environment to verify the perception capacity and the onboard intelligence of the agent-oriented embedded control system.

  11. Low-temperature nuclear orientation

    International Nuclear Information System (INIS)

    Stone, N.J.; Postma, H.

    1986-01-01

    This book comprehensively surveys the many aspects of the low temperature nuclear orientation method. The angular distribution of radioactive emissions from nuclei oriented by hyperfine interactions in solids, is treated experimentally and theoretically. A general introductory chapter is followed by formal development of the theory of the orientation process and the anisotropic emission of decay products from oriented nuclei, applied to radioactive decay and to reactions. Five chapters on applications to nuclear physics cover experimental studies of alpha, beta and gamma emission, nuclear moment measurement and level structure information. Nuclear orientation studies of parity non-conservation and time reversal asymmetry are fully described. Seven chapters cover aspects of hyperfine interactions, magnetic and electric, in metals, alloys and insulating crystals, including ordered systems. Relaxation phenomena and the combined technique of NMR detection using oriented nuclei are treated at length. Chapters on the major recent development of on-line facilities, giving access to short lived nuclei far from stability, on the use of nuclear orientation for thermometry below 1 Kelvin and on technical aspects of the method complete the main text. Extensive appendices, table of relevant parameters and over 1000 references are included to assist the design of future experiments. (Auth.)

  12. A study on multi-data source fusion method for petroleum pipeline leak detection

    Energy Technology Data Exchange (ETDEWEB)

    Liang, Wei; Zhang, Laibin [Research Center of Oil and Gas Safety Engineering Technology, China University of Petroleum, Beijing, (China)

    2010-07-01

    The detection of leaks on petroleum pipeline is a very important safety issue. Several studies were commissioned to develop new monitoring procedures for leakage detection. This paper sets out a new leak detection process. The approach developed took into consideration steady and transient states. The study investigated leak diagnosis problems in product pipelines using multi-sensor measurements (pressure, flux, density and temperature). The information collected from each sensor was considered as pieces of evidence that describe the operational conditions of the pipeline. The Dempster-Shafer (D-S) theory is used to associate multi-sensor data to pipe health indices. Experimental pressure and flow rate data were recorded using a Pipeline Leak Detection System (PLDS) acquisition card and used to verify the accuracy and reliability of this new detection method. The results showed that the degree of credibility was a high as 0.877. It was also found that multi-feature information fusion improves recognition of pipeline conditions.

  13. NHL and RCGA Based Multi-Relational Fuzzy Cognitive Map Modeling for Complex Systems

    Directory of Open Access Journals (Sweden)

    Zhen Peng

    2015-11-01

    Full Text Available In order to model multi-dimensions and multi-granularities oriented complex systems, this paper firstly proposes a kind of multi-relational Fuzzy Cognitive Map (FCM to simulate the multi-relational system and its auto construct algorithm integrating Nonlinear Hebbian Learning (NHL and Real Code Genetic Algorithm (RCGA. The multi-relational FCM fits to model the complex system with multi-dimensions and multi-granularities. The auto construct algorithm can learn the multi-relational FCM from multi-relational data resources to eliminate human intervention. The Multi-Relational Data Mining (MRDM algorithm integrates multi-instance oriented NHL and RCGA of FCM. NHL is extended to mine the causal relationships between coarse-granularity concept and its fined-granularity concepts driven by multi-instances in the multi-relational system. RCGA is used to establish high-quality high-level FCM driven by data. The multi-relational FCM and the integrating algorithm have been applied in complex system of Mutagenesis. The experiment demonstrates not only that they get better classification accuracy, but it also shows the causal relationships among the concepts of the system.

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

    Science.gov (United States)

    Bohan, Jason; Filik, Ruth

    2018-01-01

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

  15. Fall detection in walking robots by multi-way principal component analysis

    NARCIS (Netherlands)

    Karssen, J.G.; Wisse, M.

    2008-01-01

    Large disturbances can cause a biped to fall. If an upcoming fall can be detected, damage can be minimized or the fall can be prevented. We introduce the multi-way principal component analysis (MPCA) method for the detection of upcoming falls. We study the detection capability of the MPCA method in

  16. Variations on agent-oriented programming

    Directory of Open Access Journals (Sweden)

    Dalia Baziukė

    2017-12-01

    Full Text Available Occurrence of the agent paradigm and its further applications have stimulated the emergence of new concepts and methodologies in computer science. Today terms like multi-agent system, agent-oriented methodology, and agent-oriented programming (AOP are widely used. The aim of this paper is to clarify the validity of usage of the terms AOP and AOP language. This is disclosed in two phases of an analysis process. Determining to which concepts, terms like agent, programming, object-oriented analysis and design, object-oriented programming, and agent-oriented analysis and design correspond is accomplished in the first phase. Analysis of several known agent system engineering methodologies in terms of key concepts used, final resulting artifacts, and their relationship with known programming paradigms and modern tools for agent system development is performed in the second phase. The research shows that in most cases in the final phase of agent system design and in the coding stage, the main artifact is an object, defined according to the rules of the object-oriented paradigm. Hence, we say that the computing society still does not have AOP owing to the lack of an AOP language. Thus, the term AOP is very often incorrectly assigned to agent system development frameworks that in most cases, transform agents into objects.DOI: 10.15181/csat.v5i1.1361

  17. Texture orientation-based algorithm for detecting infrared maritime targets.

    Science.gov (United States)

    Wang, Bin; Dong, Lili; Zhao, Ming; Wu, Houde; Xu, Wenhai

    2015-05-20

    Infrared maritime target detection is a key technology for maritime target searching systems. However, in infrared maritime images (IMIs) taken under complicated sea conditions, background clutters, such as ocean waves, clouds or sea fog, usually have high intensity that can easily overwhelm the brightness of real targets, which is difficult for traditional target detection algorithms to deal with. To mitigate this problem, this paper proposes a novel target detection algorithm based on texture orientation. This algorithm first extracts suspected targets by analyzing the intersubband correlation between horizontal and vertical wavelet subbands of the original IMI on the first scale. Then the self-adaptive wavelet threshold denoising and local singularity analysis of the original IMI is combined to remove false alarms further. Experiments show that compared with traditional algorithms, this algorithm can suppress background clutter much better and realize better single-frame detection for infrared maritime targets. Besides, in order to guarantee accurate target extraction further, the pipeline-filtering algorithm is adopted to eliminate residual false alarms. The high practical value and applicability of this proposed strategy is backed strongly by experimental data acquired under different environmental conditions.

  18. Plant trait detection with multi-scale spectrometry

    Science.gov (United States)

    Gamon, J. A.; Wang, R.

    2017-12-01

    Proximal and remote sensing using imaging spectrometry offers new opportunities for detecting plant traits, with benefits for phenotyping, productivity estimation, stress detection, and biodiversity studies. Using proximal and airborne spectrometry, we evaluated variation in plant optical properties at various spatial and spectral scales with the goal of identifying optimal scales for distinguishing plant traits related to photosynthetic function. Using directed approaches based on physiological vegetation indices, and statistical approaches based on spectral information content, we explored alternate ways of distinguishing plant traits with imaging spectrometry. With both leaf traits and canopy structure contributing to the signals, results exhibit a strong scale dependence. Our results demonstrate the benefits of multi-scale experimental approaches within a clear conceptual framework when applying remote sensing methods to plant trait detection for phenotyping, productivity, and biodiversity studies.

  19. An object-oriented and quadrilateral-mesh based solution adaptive algorithm for compressible multi-fluid flows

    Science.gov (United States)

    Zheng, H. W.; Shu, C.; Chew, Y. T.

    2008-07-01

    In this paper, an object-oriented and quadrilateral-mesh based solution adaptive algorithm for the simulation of compressible multi-fluid flows is presented. The HLLC scheme (Harten, Lax and van Leer approximate Riemann solver with the Contact wave restored) is extended to adaptively solve the compressible multi-fluid flows under complex geometry on unstructured mesh. It is also extended to the second-order of accuracy by using MUSCL extrapolation. The node, edge and cell are arranged in such an object-oriented manner that each of them inherits from a basic object. A home-made double link list is designed to manage these objects so that the inserting of new objects and removing of the existing objects (nodes, edges and cells) are independent of the number of objects and only of the complexity of O( 1). In addition, the cells with different levels are further stored in different lists. This avoids the recursive calculation of solution of mother (non-leaf) cells. Thus, high efficiency is obtained due to these features. Besides, as compared to other cell-edge adaptive methods, the separation of nodes would reduce the memory requirement of redundant nodes, especially in the cases where the level number is large or the space dimension is three. Five two-dimensional examples are used to examine its performance. These examples include vortex evolution problem, interface only problem under structured mesh and unstructured mesh, bubble explosion under the water, bubble-shock interaction, and shock-interface interaction inside the cylindrical vessel. Numerical results indicate that there is no oscillation of pressure and velocity across the interface and it is feasible to apply it to solve compressible multi-fluid flows with large density ratio (1000) and strong shock wave (the pressure ratio is 10,000) interaction with the interface.

  20. Penalized likelihood and multi-objective spatial scans for the detection and inference of irregular clusters

    Directory of Open Access Journals (Sweden)

    Fonseca Carlos M

    2010-10-01

    Full Text Available Abstract Background Irregularly shaped spatial clusters are difficult to delineate. A cluster found by an algorithm often spreads through large portions of the map, impacting its geographical meaning. Penalized likelihood methods for Kulldorff's spatial scan statistics have been used to control the excessive freedom of the shape of clusters. Penalty functions based on cluster geometry and non-connectivity have been proposed recently. Another approach involves the use of a multi-objective algorithm to maximize two objectives: the spatial scan statistics and the geometric penalty function. Results & Discussion We present a novel scan statistic algorithm employing a function based on the graph topology to penalize the presence of under-populated disconnection nodes in candidate clusters, the disconnection nodes cohesion function. A disconnection node is defined as a region within a cluster, such that its removal disconnects the cluster. By applying this function, the most geographically meaningful clusters are sifted through the immense set of possible irregularly shaped candidate cluster solutions. To evaluate the statistical significance of solutions for multi-objective scans, a statistical approach based on the concept of attainment function is used. In this paper we compared different penalized likelihoods employing the geometric and non-connectivity regularity functions and the novel disconnection nodes cohesion function. We also build multi-objective scans using those three functions and compare them with the previous penalized likelihood scans. An application is presented using comprehensive state-wide data for Chagas' disease in puerperal women in Minas Gerais state, Brazil. Conclusions We show that, compared to the other single-objective algorithms, multi-objective scans present better performance, regarding power, sensitivity and positive predicted value. The multi-objective non-connectivity scan is faster and better suited for the

  1. CAI System with Multi-Media Text Through Web Browser for NC Lathe Programming

    Science.gov (United States)

    Mizugaki, Yoshio; Kikkawa, Koichi; Mizui, Masahiko; Kamijo, Keisuke

    A new Computer Aided Instruction (CAI) system for NC lathe programming has been developed with use of multi-media texts including movies, animations, pictures, sound and texts through Web browser. Although many CAI systems developed previously for NC programming consist of text-based instructions, it is difficult for beginners to learn NC programming with use of them. In the developed CAI system, multi-media texts are adopted for the help of users' understanding, and it is available through Web browser anytime and anywhere. Also the error log is automatically recorded for the future references. According to the NC programming coded by a user, the movement of the NC lathe is animated and shown in the monitor screen in front of the user. If its movement causes the collision between a cutting tool and the lathe, some sound and the caution remark are generated. If the user makes mistakes some times at a certain stage in learning NC, the corresponding suggestion is shown in the form of movies, animations, and so forth. By using the multimedia texts, users' attention is kept concentrated during a training course. In this paper, the configuration of the CAI system is explained and the actual procedures for users to learn the NC programming are also explained too. Some beginners tested this CAI system and their results are illustrated and discussed from the viewpoint of the efficiency and usefulness of this CAI system. A brief conclusion is also mentioned.

  2. Error detection in GPS observations by means of Multi-process models

    DEFF Research Database (Denmark)

    Thomsen, Henrik F.

    2001-01-01

    The main purpose of this article is to present the idea of using Multi-process models as a method of detecting errors in GPS observations. The theory behind Multi-process models, and double differenced phase observations in GPS is presented shortly. It is shown how to model cycle slips in the Mul...

  3. Multi-Perspective Vehicle Detection and Tracking

    DEFF Research Database (Denmark)

    Dueholm, Jacob Velling; Kristoffersen, Miklas Strøm; Satzoda, Ravi K.

    2016-01-01

    this dataset is introduced along with its challenges and evaluation metrics. A vision-based multi-perspective dataset is presented, containing a full panoramic view from a moving platform driving on U.S. highways capturing 2704x1440 resolution images at 12 frames per second. The dataset serves multiple......The research community has shown significant improvements in both vision-based detection and tracking of vehicles, working towards a high level understanding of on-road maneuvers. Behaviors of surrounding vehicles in a highway environment is found as an interesting starting point, of why...... purposes to be used as traditional detection and tracking, together with tracking of vehicles across perspectives. Each of the four perspectives have been annotated, resulting in more than 4000 bounding boxes in order to evaluate and compare novel methods....

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

    Directory of Open Access Journals (Sweden)

    Jinqi Zhao

    2017-12-01

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

  5. Obtaining Approximate Values of Exterior Orientation Elements of Multi-Intersection Images Using Particle Swarm Optimization

    Science.gov (United States)

    Li, X.; Li, S. W.

    2012-07-01

    In this paper, an efficient global optimization algorithm in the field of artificial intelligence, named Particle Swarm Optimization (PSO), is introduced into close range photogrammetric data processing. PSO can be applied to obtain the approximate values of exterior orientation elements under the condition that multi-intersection photography and a small portable plane control frame are used. PSO, put forward by an American social psychologist J. Kennedy and an electrical engineer R.C. Eberhart, is a stochastic global optimization method based on swarm intelligence, which was inspired by social behavior of bird flocking or fish schooling. The strategy of obtaining the approximate values of exterior orientation elements using PSO is as follows: in terms of image coordinate observed values and space coordinates of few control points, the equations of calculating the image coordinate residual errors can be given. The sum of absolute value of each image coordinate is minimized to be the objective function. The difference between image coordinate observed value and the image coordinate computed through collinear condition equation is defined as the image coordinate residual error. Firstly a gross area of exterior orientation elements is given, and then the adjustment of other parameters is made to get the particles fly in the gross area. After iterative computation for certain times, the satisfied approximate values of exterior orientation elements are obtained. By doing so, the procedures like positioning and measuring space control points in close range photogrammetry can be avoided. Obviously, this method can improve the surveying efficiency greatly and at the same time can decrease the surveying cost. And during such a process, only one small portable control frame with a couple of control points is employed, and there are no strict requirements for the space distribution of control points. In order to verify the effectiveness of this algorithm, two experiments are

  6. Religion Education Teaching in Zimbabwe Secondary Schools: The Search for an Authentic Values-Oriented Multi-Faith Religion Education Pedagogical Model

    Science.gov (United States)

    Ndlovu, Lovemore

    2014-01-01

    Religion Education teaching in post-independence Zimbabwe has remained bible-oriented and confessional at a time when most Religion Education stakeholders expect an "open", plural and authentic multi-faith Religion Education curriculum. Despite curriculum innovation initiatives aimed at introducing new approaches such as experiential…

  7. Exploiting physical constraints for multi-spectral exo-planet detection

    Science.gov (United States)

    Thiébaut, Éric; Devaney, Nicholas; Langlois, Maud; Hanley, Kenneth

    2016-07-01

    We derive a physical model of the on-axis PSF for a high contrast imaging system such as GPI or SPHERE. This model is based on a multi-spectral Taylor series expansion of the diffraction pattern and predicts that the speckles should be a combination of spatial modes with deterministic chromatic magnification and weighting. We propose to remove most of the residuals by fitting this model on a set of images at multiple wavelengths and times. On simulated data, we demonstrate that our approach achieves very good speckle suppression without additional heuristic parameters. The residual speckles1, 2 set the most serious limitation in the detection of exo-planets in high contrast coronographic images provided by instruments such as SPHERE3 at the VLT, GPI4, 5 at Gemini, or SCExAO6 at Subaru. A number of post-processing methods have been proposed to remove as much as possible of the residual speckles while preserving the signal from the planets. These methods exploit the fact that the speckles and the planetary signal have different temporal and spectral behaviors. Some methods like LOCI7 are based on angular differential imaging8 (ADI), spectral differential imaging9, 10 (SDI), or on a combination of ADI and SDI.11 Instead of working on image differences, we propose to tackle the exo-planet detection as an inverse problem where a model of the residual speckles is fit on the set of multi-spectral images and, possibly, multiple exposures. In order to reduce the number of degrees of freedom, we impose specific constraints on the spatio-spectral distribution of stellar speckles. These constraints are deduced from a multi-spectral Taylor series expansion of the diffraction pattern for an on-axis source which implies that the speckles are a combination of spatial modes with deterministic chromatic magnification and weighting. Using simulated data, the efficiency of speckle removal by fitting the proposed multi-spectral model is compared to the result of using an approximation

  8. Multi-Task Vehicle Detection with Region-of-Interest Voting.

    Science.gov (United States)

    Chu, Wenqing; Liu, Yao; Shen, Chen; Cai, Deng; Hua, Xian-Sheng

    2017-10-12

    Vehicle detection is a challenging problem in autonomous driving systems, due to its large structural and appearance variations. In this paper, we propose a novel vehicle detection scheme based on multi-task deep convolutional neural networks (CNN) and region-of-interest (RoI) voting. In the design of CNN architecture, we enrich the supervised information with subcategory, region overlap, bounding-box regression and category of each training RoI as a multi-task learning framework. This design allows the CNN model to share visual knowledge among different vehicle attributes simultaneously, thus detection robustness can be effectively improved. In addition, most existing methods consider each RoI independently, ignoring the clues from its neighboring RoIs. In our approach, we utilize the CNN model to predict the offset direction of each RoI boundary towards the corresponding ground truth. Then each RoI can vote those suitable adjacent bounding boxes which are consistent with this additional information. The voting results are combined with the score of each RoI itself to find a more accurate location from a large number of candidates. Experimental results on the real-world computer vision benchmarks KITTI and the PASCAL2007 vehicle dataset show that our approach achieves superior performance in vehicle detection compared with other existing published works.

  9. Signal Detection Framework Using Semantic Text Mining Techniques

    Science.gov (United States)

    Sudarsan, Sithu D.

    2009-01-01

    Signal detection is a challenging task for regulatory and intelligence agencies. Subject matter experts in those agencies analyze documents, generally containing narrative text in a time bound manner for signals by identification, evaluation and confirmation, leading to follow-up action e.g., recalling a defective product or public advisory for…

  10. Detection of Heterogeneous Small Inclusions by a Multi-Step MUSIC Method

    Science.gov (United States)

    Solimene, Raffaele; Dell'Aversano, Angela; Leone, Giovanni

    2014-05-01

    In this contribution the problem of detecting and localizing scatterers with small (in terms of wavelength) cross sections by collecting their scattered field is addressed. The problem is dealt with for a two-dimensional and scalar configuration where the background is given as a two-layered cylindrical medium. More in detail, while scattered field data are taken in the outermost layer, inclusions are embedded within the inner layer. Moreover, the case of heterogeneous inclusions (i.e., having different scattering coefficients) is addressed. As a pertinent applicative context we identify the problem of diagnose concrete pillars in order to detect and locate rebars, ducts and other small in-homogeneities that can populate the interior of the pillar. The nature of inclusions influences the scattering coefficients. For example, the field scattered by rebars is stronger than the one due to ducts. Accordingly, it is expected that the more weakly scattering inclusions can be difficult to be detected as their scattered fields tend to be overwhelmed by those of strong scatterers. In order to circumvent this problem, in this contribution a multi-step MUltiple SIgnal Classification (MUSIC) detection algorithm is adopted [1]. In particular, the first stage aims at detecting rebars. Once rebars have been detected, their positions are exploited to update the Green's function and to subtract the scattered field due to their presence. The procedure is repeated until all the inclusions are detected. The analysis is conducted by numerical experiments for a multi-view/multi-static single-frequency configuration and the synthetic data are generated by a FDTD forward solver. Acknowledgement This work benefited from networking activities carried out within the EU funded COST Action TU1208 "Civil Engineering Applications of Ground Penetrating Radar." [1] R. Solimene, A. Dell'Aversano and G. Leone, "MUSIC algorithms for rebar detection," J. of Geophysics and Engineering, vol. 10, pp. 1

  11. Multi-layer hierarchical array fabricated with diatom frustules for highly sensitive bio-detection applications

    International Nuclear Information System (INIS)

    Li, Aobo; Cai, Jun; Pan, Junfeng; Wang, Yu; Yue, Yue; Zhang, Deyuan

    2014-01-01

    Diatoms have delicate porous structures which are very beneficial in improving the absorbing ability in the bio-detection field. In this study, multi-layered hierarchical arrays were fabricated by packing Nitzschia soratensis (N. soratensis) frustules into Cosinodiscus argus (C. argus) frustules to achieve advanced sensitivity in bio-detection chips. Photolithographic patterning was used to obtain N. soratensis frustule arrays, and the floating behavior of C. argus frustules was employed to control their postures for packing N. soratensis frustule array spots. The morphology of the multi-layer C. argus–N. soratensis package array was investigated by scanning electron microscopy, demonstrating that the overall and sub-structures of the diatom frustules were retained. The signal enhancing effect of multi-layer C. argus–N. soratensis packages was demonstrated by fluorescent antibody test results. The mechanism of the enhancement was also analyzed, indicating that both complex hierarchical frustule structures and optimized posture of C. argus frustules were important for improving bio-detection sensitivities. The technique for fabricating multi-layer diatom frustules arrays is also useful for making multi-functional biochips and controllable drug delivery systems. (paper)

  12. Data fusion of multi-scale representations for structural damage detection

    Science.gov (United States)

    Guo, Tian; Xu, Zili

    2018-01-01

    Despite extensive researches into structural health monitoring (SHM) in the past decades, there are few methods that can detect multiple slight damage in noisy environments. Here, we introduce a new hybrid method that utilizes multi-scale space theory and data fusion approach for multiple damage detection in beams and plates. A cascade filtering approach provides multi-scale space for noisy mode shapes and filters the fluctuations caused by measurement noise. In multi-scale space, a series of amplification and data fusion algorithms are utilized to search the damage features across all possible scales. We verify the effectiveness of the method by numerical simulation using damaged beams and plates with various types of boundary conditions. Monte Carlo simulations are conducted to illustrate the effectiveness and noise immunity of the proposed method. The applicability is further validated via laboratory cases studies focusing on different damage scenarios. Both results demonstrate that the proposed method has a superior noise tolerant ability, as well as damage sensitivity, without knowing material properties or boundary conditions.

  13. Who multi-tasks and why? Multi-tasking ability, perceived multi-tasking ability, impulsivity, and sensation seeking.

    Science.gov (United States)

    Sanbonmatsu, David M; Strayer, David L; Medeiros-Ward, Nathan; Watson, Jason M

    2013-01-01

    The present study examined the relationship between personality and individual differences in multi-tasking ability. Participants enrolled at the University of Utah completed measures of multi-tasking activity, perceived multi-tasking ability, impulsivity, and sensation seeking. In addition, they performed the Operation Span in order to assess their executive control and actual multi-tasking ability. The findings indicate that the persons who are most capable of multi-tasking effectively are not the persons who are most likely to engage in multiple tasks simultaneously. To the contrary, multi-tasking activity as measured by the Media Multitasking Inventory and self-reported cell phone usage while driving were negatively correlated with actual multi-tasking ability. Multi-tasking was positively correlated with participants' perceived ability to multi-task ability which was found to be significantly inflated. Participants with a strong approach orientation and a weak avoidance orientation--high levels of impulsivity and sensation seeking--reported greater multi-tasking behavior. Finally, the findings suggest that people often engage in multi-tasking because they are less able to block out distractions and focus on a singular task. Participants with less executive control--low scorers on the Operation Span task and persons high in impulsivity--tended to report higher levels of multi-tasking activity.

  14. Who Multi-Tasks and Why? Multi-Tasking Ability, Perceived Multi-Tasking Ability, Impulsivity, and Sensation Seeking

    Science.gov (United States)

    Sanbonmatsu, David M.; Strayer, David L.; Medeiros-Ward, Nathan; Watson, Jason M.

    2013-01-01

    The present study examined the relationship between personality and individual differences in multi-tasking ability. Participants enrolled at the University of Utah completed measures of multi-tasking activity, perceived multi-tasking ability, impulsivity, and sensation seeking. In addition, they performed the Operation Span in order to assess their executive control and actual multi-tasking ability. The findings indicate that the persons who are most capable of multi-tasking effectively are not the persons who are most likely to engage in multiple tasks simultaneously. To the contrary, multi-tasking activity as measured by the Media Multitasking Inventory and self-reported cell phone usage while driving were negatively correlated with actual multi-tasking ability. Multi-tasking was positively correlated with participants’ perceived ability to multi-task ability which was found to be significantly inflated. Participants with a strong approach orientation and a weak avoidance orientation – high levels of impulsivity and sensation seeking – reported greater multi-tasking behavior. Finally, the findings suggest that people often engage in multi-tasking because they are less able to block out distractions and focus on a singular task. Participants with less executive control - low scorers on the Operation Span task and persons high in impulsivity - tended to report higher levels of multi-tasking activity. PMID:23372720

  15. Multi-Level Anomaly Detection on Time-Varying Graph Data

    Energy Technology Data Exchange (ETDEWEB)

    Bridges, Robert A [ORNL; Collins, John P [ORNL; Ferragut, Erik M [ORNL; Laska, Jason A [ORNL; Sullivan, Blair D [ORNL

    2015-01-01

    This work presents a novel modeling and analysis framework for graph sequences which addresses the challenge of detecting and contextualizing anomalies in labelled, streaming graph data. We introduce a generalization of the BTER model of Seshadhri et al. by adding flexibility to community structure, and use this model to perform multi-scale graph anomaly detection. Specifically, probability models describing coarse subgraphs are built by aggregating probabilities at finer levels, and these closely related hierarchical models simultaneously detect deviations from expectation. This technique provides insight into a graph's structure and internal context that may shed light on a detected event. Additionally, this multi-scale analysis facilitates intuitive visualizations by allowing users to narrow focus from an anomalous graph to particular subgraphs or nodes causing the anomaly. For evaluation, two hierarchical anomaly detectors are tested against a baseline Gaussian method on a series of sampled graphs. We demonstrate that our graph statistics-based approach outperforms both a distribution-based detector and the baseline in a labeled setting with community structure, and it accurately detects anomalies in synthetic and real-world datasets at the node, subgraph, and graph levels. To illustrate the accessibility of information made possible via this technique, the anomaly detector and an associated interactive visualization tool are tested on NCAA football data, where teams and conferences that moved within the league are identified with perfect recall, and precision greater than 0.786.

  16. Detective text of post-modernism: precedential phenomena as linguacultural markers of intertexuality

    Directory of Open Access Journals (Sweden)

    Tuova Ruzana Hamedovna

    2015-12-01

    Full Text Available Detective postmodern text is characterized by active functioning of gaming modality, which is partly responsible for its inclusion in the semantic space of precedent phenomena. Precedential phenomena mark elements of linguaculture and intertextuality as one of the important features of the postmodern age. Dual transformation, which is subjected to precedent phenomena determines ultimately receptive-interpretive activity of the reader: producing text simulates certain perception through the signs of the text of the addresser and the recipient creates a new text according to their own ideas about the text-addresser and the author’s vision. Polyfunctionality of postmodern text is determined by the presence in it of precedent phenomena and polyvariety of interpretations of detective texts due to the interaction with the case genre that is reflected in the author’s game with meanings. Game modality focused on comic effect by binding the text and contrasting concepts, which helps the recipient to render artistic images, characters and plot situations, strengthening the vitality of precedent phenomena. In detective novels by Boris Akunin texts and precedent names are widely used, provoking the reader to intellectual activity and, thus, involving in the interpretation of the text of its common cultural postmodern experience.

  17. Cognitive diffusion model with user-oriented context-to-text recognition for learning to promote high level cognitive processes

    Directory of Open Access Journals (Sweden)

    Wu-Yuin Hwang

    2014-03-01

    Full Text Available There is a large number of studies on how to promote students’ cognitive processes and learning achievements through various learning activities supported by advanced learning technologies. However, not many of them focus on applying the knowledge that students learn in school to solve authentic daily life problems. This study aims to propose a cognitive diffusion model called User-oriented Context-to-Text Recognition for Learning (U-CTRL to facilitate and improve students’ learning and cognitive processes from lower levels (i.e., Remember and Understand to higher levels (i.e., Apply and above through an innovative approach, called User-Oriented Context-to-Text Recognition for Learning (U-CTRL. With U-CTRL, students participate in learning activities in which they capture the learning context that can be scanned and recognized by a computer application as text. Furthermore, this study proposes the use of an innovative model, called Cognitive Diffusion Model, to investigate the diffusion and transition of students’ cognitive processes in different learning stages including pre-schooling, after-schooling, crossing the chasm, and higher cognitive processing. Finally, two cases are presented to demonstrate how the U-CTRL approach can be used to facilitate student cognition in their learning of English and Natural science.

  18. Multi-spectral imager

    CSIR Research Space (South Africa)

    Stolper, R

    2006-02-01

    Full Text Available channel are boresighted with two beamsplitter windows; and • The IR system is boresighted. APPLICATION High-voltage environment • Detecting loose strands, bolts and nuts; • Detecting Corona discharges on insulator discs; • Detecting... and locating spark gaps; • Detecting and locating RIV sources; • Audit sub-stations and transmission lines for audio noise and Corona activities. RECORDINGS / APPLICATIONS REPORTING TOOL: MultiSOFT • Image handling software for grabbing, processing...

  19. Data fusion for QRS complex detection in multi-lead electrocardiogram recordings

    Science.gov (United States)

    Ledezma, Carlos A.; Perpiñan, Gilberto; Severeyn, Erika; Altuve, Miguel

    2015-12-01

    Heart diseases are the main cause of death worldwide. The first step in the diagnose of these diseases is the analysis of the electrocardiographic (ECG) signal. In turn, the ECG analysis begins with the detection of the QRS complex, which is the one with the most energy in the cardiac cycle. Numerous methods have been proposed in the bibliography for QRS complex detection, but few authors have analyzed the possibility of taking advantage of the information redundancy present in multiple ECG leads (simultaneously acquired) to produce accurate QRS detection. In our previous work we presented such an approach, proposing various data fusion techniques to combine the detections made by an algorithm on multiple ECG leads. In this paper we present further studies that show the advantages of this multi-lead detection approach, analyzing how many leads are necessary in order to observe an improvement in the detection performance. A well known QRS detection algorithm was used to test the fusion techniques on the St. Petersburg Institute of Cardiological Technics database. Results show improvement in the detection performance with as little as three leads, but the reliability of these results becomes interesting only after using seven or more leads. Results were evaluated using the detection error rate (DER). The multi-lead detection approach allows an improvement from DER = 3:04% to DER = 1:88%. Further works are to be made in order to improve the detection performance by implementing further fusion steps.

  20. Dataset: Multi Sensor-Orientation Movement Data of Goats

    NARCIS (Netherlands)

    Kamminga, Jacob Wilhelm

    2018-01-01

    This is a labeled dataset. Motion data were collected from six sensor nodes that were fixed with different orientations to a collar around the neck of goats. These six sensor nodes simultaneously, with different orientations, recorded various activities performed by the goat. We recorded the

  1. Multi-Domain Modeling Based on Modelica

    Directory of Open Access Journals (Sweden)

    Liu Jun

    2016-01-01

    Full Text Available With the application of simulation technology in large-scale and multi-field problems, multi-domain unified modeling become an effective way to solve these problems. This paper introduces several basic methods and advantages of the multidisciplinary model, and focuses on the simulation based on Modelica language. The Modelica/Mworks is a newly developed simulation software with features of an object-oriented and non-casual language for modeling of the large, multi-domain system, which makes the model easier to grasp, develop and maintain.It This article shows the single degree of freedom mechanical vibration system based on Modelica language special connection mechanism in Mworks. This method that multi-domain modeling has simple and feasible, high reusability. it closer to the physical system, and many other advantages.

  2. Full-text automated detection of surgical site infections secondary to neurosurgery in Rennes, France.

    Science.gov (United States)

    Campillo-Gimenez, Boris; Garcelon, Nicolas; Jarno, Pascal; Chapplain, Jean Marc; Cuggia, Marc

    2013-01-01

    The surveillance of Surgical Site Infections (SSI) contributes to the management of risk in French hospitals. Manual identification of infections is costly, time-consuming and limits the promotion of preventive procedures by the dedicated teams. The introduction of alternative methods using automated detection strategies is promising to improve this surveillance. The present study describes an automated detection strategy for SSI in neurosurgery, based on textual analysis of medical reports stored in a clinical data warehouse. The method consists firstly, of enrichment and concept extraction from full-text reports using NOMINDEX, and secondly, text similarity measurement using a vector space model. The text detection was compared to the conventional strategy based on self-declaration and to the automated detection using the diagnosis-related group database. The text-mining approach showed the best detection accuracy, with recall and precision equal to 92% and 40% respectively, and confirmed the interest of reusing full-text medical reports to perform automated detection of SSI.

  3. International Workshop on Service Orientation in Holonic and Multi-Agent Manufacturing

    CERN Document Server

    Trentesaux, Damien; Thomas, André; McFarlane, Duncan

    2016-01-01

    This volume gathers the peer reviewed papers which were presented at the 5th edition of the International Workshop “Service Orientation in Holonic and Multi-agent Man-ufacturing – SOHOMA’15” organized in November 5-6, 2015 by the Institute for Manufacturing (IfM) of the University of Cambridge, UK in collaboration with the CIMR Research Centre in Computer Integrated Manufacturing and Robotics of the University Politehnica of Bucharest, Romania, the LAMIH Laboratory of Industrial and Human Automation Control, Mechanical Engineering and Computer Science of the University of Valenciennes and Hainaut-Cambrésis, France and the CRAN Re-search Centre for Automatic Control, Nancy of the University of Lorraine, France. The book is structured in seven parts, each one grouping a number of chapters de-scribing research in actual domains of the digital transformation in manufacturing and trends in future manufacturing control: (1) Applications of Intelligent Products; (2) Advances in Control of Physical Internet ...

  4. A FRAMEWORK OF CHANGE DETECTION BASED ON COMBINED MORPHOLOGICA FEATURES AND MULTI-INDEX CLASSIFICATION

    Directory of Open Access Journals (Sweden)

    S. Li

    2017-09-01

    Full Text Available Remote sensing images are particularly well suited for analysis of land cover change. In this paper, we present a new framework for detection of changing land cover using satellite imagery. Morphological features and a multi-index are used to extract typical objects from the imagery, including vegetation, water, bare land, buildings, and roads. Our method, based on connected domains, is different from traditional methods; it uses image segmentation to extract morphological features, while the enhanced vegetation index (EVI, the differential water index (NDWI are used to extract vegetation and water, and a fragmentation index is used to the correct extraction results of water. HSV transformation and threshold segmentation extract and remove the effects of shadows on extraction results. Change detection is performed on these results. One of the advantages of the proposed framework is that semantic information is extracted automatically using low-level morphological features and indexes. Another advantage is that the proposed method detects specific types of change without any training samples. A test on ZY-3 images demonstrates that our framework has a promising capability to detect change.

  5. The Application of KINECT Motion Sensing Technology in Game-Oriented Study

    Directory of Open Access Journals (Sweden)

    Hui Yu Yang

    2014-03-01

    Full Text Available The learning environment based on the KINECT Motion Sensing technology is able to fully mobilize the learners' multi-sensory organs, closely combine study with sports and enhance human-computer interactions, which can be conducive to the learners' health, greatly increase the relishes of learning and promote effective learning in the game, and finally compensate for the shortage of human-computer interactions in the traditional mouse and keyboard mode. The article elaborates on the KINECT Motion Sensing Technology and its educational applications status by analyzing its effective supports for game-oriented studying environment, based on which the article establishes a game-oriented learning environment. Eventually the article reveals an applicable case of game-oriented teaching and learning as a reference for related researches.

  6. Single- and multi-frequency detection of surface displacements via scanning probe microscopy.

    Science.gov (United States)

    Romanyuk, Konstantin; Luchkin, Sergey Yu; Ivanov, Maxim; Kalinin, Arseny; Kholkin, Andrei L

    2015-02-01

    Piezoresponse force microscopy (PFM) provides a novel opportunity to detect picometer-level displacements induced by an electric field applied through a conducting tip of an atomic force microscope (AFM). Recently, it was discovered that superb vertical sensitivity provided by PFM is high enough to monitor electric-field-induced ionic displacements in solids, the technique being referred to as electrochemical strain microscopy (ESM). ESM has been implemented only in multi-frequency detection modes such as dual AC resonance tracking (DART) and band excitation, where the response is recorded within a finite frequency range, typically around the first contact resonance. In this paper, we analyze and compare signal-to-noise ratios of the conventional single-frequency method with multi-frequency regimes of measuring surface displacements. Single-frequency detection ESM is demonstrated using a commercial AFM.

  7. Improving Anomaly Detection for Text-Based Protocols by Exploiting Message Structures

    Directory of Open Access Journals (Sweden)

    Christian M. Mueller

    2010-12-01

    Full Text Available Service platforms using text-based protocols need to be protected against attacks. Machine-learning algorithms with pattern matching can be used to detect even previously unknown attacks. In this paper, we present an extension to known Support Vector Machine (SVM based anomaly detection algorithms for the Session Initiation Protocol (SIP. Our contribution is to extend the amount of different features used for classification (feature space by exploiting the structure of SIP messages, which reduces the false positive rate. Additionally, we show how combining our approach with attribute reduction significantly improves throughput.

  8. A validity study of self-reported daily texting frequency, cell phone characteristics, and texting styles among young adults.

    Science.gov (United States)

    Gold, Judith E; Rauscher, Kimberly J; Zhu, Motao

    2015-04-02

    Texting is associated with adverse health effects including musculoskeletal disorders, sleep disturbances, and traffic crashes. Many studies have relied on self-reported texting frequency, yet the validity of self-reports is unknown. Our objective was to provide some of the first data on the validity of self-reported texting frequency, cell phone characteristics including input device (e.g. touchscreen), key configuration (e.g., QWERTY), and texting styles including phone orientation (e.g., horizontal) and hands holding the phone while texting. Data were collected using a self-administered questionnaire and observation of a texting task among college students ages 18 to 24. To gauge agreement between self-reported and phone bill-derived categorical number of daily text messages sent, we calculated percent of agreement, Spearman correlation coefficient, and a linear weighted kappa statistic. For agreement between self-reported and observed cell phone characteristics and texting styles we calculated percentages of agreement. We used chi-square tests to detect significant differences (α = 0.05) by gender and study protocol. There were 106 participants; 87 of which had complete data for texting frequency analyses. Among these 87, there was 26% (95% CI: 21-31) agreement between self-reported and phone bill-derived number of daily text messages sent with a Spearman's rho of 0.48 and a weighted kappa of 0.17 (95% CI: 0.06-0.27). Among those who did not accurately report the number of daily texts sent, 81% overestimated this number. Among the full sample (n = 106), there was high agreement between self-reported and observed texting input device (96%, 95% CI: 91-99), key configuration (89%, 95% CI: 81-94), and phone orientation while texting (93%, 95% CI: 86-97). No differences were found by gender or study protocol among any items. While young adults correctly reported their cell phone's characteristics and phone orientation while texting, most incorrectly

  9. Compact Gaussian quantum computation by multi-pixel homodyne detection

    International Nuclear Information System (INIS)

    Ferrini, G; Fabre, C; Treps, N; Gazeau, J P; Coudreau, T

    2013-01-01

    We study the possibility of producing and detecting continuous variable cluster states in an extremely compact optical setup. This method is based on a multi-pixel homodyne detection system recently demonstrated experimentally, which includes classical data post-processing. It allows the incorporation of the linear optics network, usually employed in standard experiments for the production of cluster states, in the stage of the measurement. After giving an example of cluster state generation by this method, we further study how this procedure can be generalized to perform Gaussian quantum computation. (paper)

  10. Improving package structure of object-oriented software using multi-objective optimization and weighted class connections

    Directory of Open Access Journals (Sweden)

    Amarjeet

    2017-07-01

    Full Text Available The software maintenance activities performed without following the original design decisions about the package structure usually deteriorate the quality of software modularization, leading to decay of the quality of the system. One of the main reasons for such structural deterioration is inappropriate grouping of source code classes in software packages. To improve such grouping/modular-structure, previous researchers formulated the software remodularization problem as an optimization problem and solved it using search-based meta-heuristic techniques. These optimization approaches aimed at improving the quality metrics values of the structure without considering the original package design decisions, often resulting into a totally new software modularization. The entirely changed software modularization becomes costly to realize as well as difficult to understand for the developers/maintainers. To alleviate this issue, we propose a multi-objective optimization approach to improve the modularization quality of an object-oriented system with minimum possible movement of classes between existing packages of original software modularization. The optimization is performed using NSGA-II, a widely-accepted multi-objective evolutionary algorithm. In order to ensure minimum modification of original package structure, a new approach of computing class relations using weighted strengths has been proposed here. The weights of relations among different classes are computed on the basis of the original package structure. A new objective function has been formulated using these weighted class relations. This objective function drives the optimization process toward better modularization quality simultaneously ensuring preservation of original structure. To evaluate the results of the proposed approach, a series of experiments are conducted over four real-worlds and two random software applications. The experimental results clearly indicate the effectiveness

  11. Object-oriented crop mapping and monitoring using multi-temporal polarimetric RADARSAT-2 data

    Science.gov (United States)

    Jiao, Xianfeng; Kovacs, John M.; Shang, Jiali; McNairn, Heather; Walters, Dan; Ma, Baoluo; Geng, Xiaoyuan

    2014-10-01

    The aim of this paper is to assess the accuracy of an object-oriented classification of polarimetric Synthetic Aperture Radar (PolSAR) data to map and monitor crops using 19 RADARSAT-2 fine beam polarimetric (FQ) images of an agricultural area in North-eastern Ontario, Canada. Polarimetric images and field data were acquired during the 2011 and 2012 growing seasons. The classification and field data collection focused on the main crop types grown in the region, which include: wheat, oat, soybean, canola and forage. The polarimetric parameters were extracted with PolSAR analysis using both the Cloude-Pottier and Freeman-Durden decompositions. The object-oriented classification, with a single date of PolSAR data, was able to classify all five crop types with an accuracy of 95% and Kappa of 0.93; a 6% improvement in comparison with linear-polarization only classification. However, the time of acquisition is crucial. The larger biomass crops of canola and soybean were most accurately mapped, whereas the identification of oat and wheat were more variable. The multi-temporal data using the Cloude-Pottier decomposition parameters provided the best classification accuracy compared to the linear polarizations and the Freeman-Durden decomposition parameters. In general, the object-oriented classifications were able to accurately map crop types by reducing the noise inherent in the SAR data. Furthermore, using the crop classification maps we were able to monitor crop growth stage based on a trend analysis of the radar response. Based on field data from canola crops, there was a strong relationship between the phenological growth stage based on the BBCH scale, and the HV backscatter and entropy.

  12. Complex Event Detection via Multi Source Video Attributes (Open Access)

    Science.gov (United States)

    2013-10-03

    Complex Event Detection via Multi-Source Video Attributes Zhigang Ma† Yi Yang‡ Zhongwen Xu‡§ Shuicheng Yan Nicu Sebe† Alexander G. Hauptmann...under its International Research Centre @ Singapore Fund- ing Initiative and administered by the IDM Programme Of- fice, and the Intelligence Advanced

  13. AUTOMATIC ORIENTATION OF LARGE BLOCKS OF OBLIQUE IMAGES

    Directory of Open Access Journals (Sweden)

    E. Rupnik

    2013-05-01

    Full Text Available Nowadays, multi-camera platforms combining nadir and oblique cameras are experiencing a revival. Due to their advantages such as ease of interpretation, completeness through mitigation of occluding areas, as well as system accessibility, they have found their place in numerous civil applications. However, automatic post-processing of such imagery still remains a topic of research. Configuration of cameras poses a challenge on the traditional photogrammetric pipeline used in commercial software and manual measurements are inevitable. For large image blocks it is certainly an impediment. Within theoretical part of the work we review three common least square adjustment methods and recap on possible ways for a multi-camera system orientation. In the practical part we present an approach that successfully oriented a block of 550 images acquired with an imaging system composed of 5 cameras (Canon Eos 1D Mark III with different focal lengths. Oblique cameras are rotated in the four looking directions (forward, backward, left and right by 45° with respect to the nadir camera. The workflow relies only upon open-source software: a developed tool to analyse image connectivity and Apero to orient the image block. The benefits of the connectivity tool are twofold: in terms of computational time and success of Bundle Block Adjustment. It exploits the georeferenced information provided by the Applanix system in constraining feature point extraction to relevant images only, and guides the concatenation of images during the relative orientation. Ultimately an absolute transformation is performed resulting in mean re-projection residuals equal to 0.6 pix.

  14. A Service-Oriented Approach for Dynamic Chaining of Virtual Network Functions over Multi-Provider Software-Defined Networks

    Directory of Open Access Journals (Sweden)

    Barbara Martini

    2016-06-01

    Full Text Available Emerging technologies such as Software-Defined Networks (SDN and Network Function Virtualization (NFV promise to address cost reduction and flexibility in network operation while enabling innovative network service delivery models. However, operational network service delivery solutions still need to be developed that actually exploit these technologies, especially at the multi-provider level. Indeed, the implementation of network functions as software running over a virtualized infrastructure and provisioned on a service basis let one envisage an ecosystem of network services that are dynamically and flexibly assembled by orchestrating Virtual Network Functions even across different provider domains, thereby coping with changeable user and service requirements and context conditions. In this paper we propose an approach that adopts Service-Oriented Architecture (SOA technology-agnostic architectural guidelines in the design of a solution for orchestrating and dynamically chaining Virtual Network Functions. We discuss how SOA, NFV, and SDN may complement each other in realizing dynamic network function chaining through service composition specification, service selection, service delivery, and placement tasks. Then, we describe the architecture of a SOA-inspired NFV orchestrator, which leverages SDN-based network control capabilities to address an effective delivery of elastic chains of Virtual Network Functions. Preliminary results of prototype implementation and testing activities are also presented. The benefits for Network Service Providers are also described that derive from the adaptive network service provisioning in a multi-provider environment through the orchestration of computing and networking services to provide end users with an enhanced service experience.

  15. ROBUST AND ACCURATE IMAGE-BASED GEOREFERENCING EXPLOITING RELATIVE ORIENTATION CONSTRAINTS

    Directory of Open Access Journals (Sweden)

    S. Cavegn

    2018-05-01

    Full Text Available Urban environments with extended areas of poor GNSS coverage as well as indoor spaces that often rely on real-time SLAM algorithms for camera pose estimation require sophisticated georeferencing in order to fulfill our high requirements of a few centimeters for absolute 3D point measurement accuracies. Since we focus on image-based mobile mapping, we extended the structure-from-motion pipeline COLMAP with georeferencing capabilities by integrating exterior orientation parameters from direct sensor orientation or SLAM as well as ground control points into bundle adjustment. Furthermore, we exploit constraints for relative orientation parameters among all cameras in bundle adjustment, which leads to a significant robustness and accuracy increase especially by incorporating highly redundant multi-view image sequences. We evaluated our integrated georeferencing approach on two data sets, one captured outdoors by a vehicle-based multi-stereo mobile mapping system and the other captured indoors by a portable panoramic mobile mapping system. We obtained mean RMSE values for check point residuals between image-based georeferencing and tachymetry of 2 cm in an indoor area, and 3 cm in an urban environment where the measurement distances are a multiple compared to indoors. Moreover, in comparison to a solely image-based procedure, our integrated georeferencing approach showed a consistent accuracy increase by a factor of 2–3 at our outdoor test site. Due to pre-calibrated relative orientation parameters, images of all camera heads were oriented correctly in our challenging indoor environment. By performing self-calibration of relative orientation parameters among respective cameras of our vehicle-based mobile mapping system, remaining inaccuracies from suboptimal test field calibration were successfully compensated.

  16. Staying with the Text: The Contribution of Gender, Achievement Orientations, and Interest to Students' Performance on a Literacy Task

    Science.gov (United States)

    Graham, Jedda; Tisher, Ruth; Ainley, Mary; Kennedy, Gregor

    2008-01-01

    This study addresses concerns about boys' underperformance on literacy tasks compared to girls, by investigating male and females students' responses to narrative texts. Participants were 142 Grade 9 and 10 students. Achievement orientations, including goals, self-efficacy, and self-handicapping, were measured and approach and avoidance factors…

  17. Pattern-oriented modelling: a 'multi-scope' for predictive systems ecology.

    Science.gov (United States)

    Grimm, Volker; Railsback, Steven F

    2012-01-19

    Modern ecology recognizes that modelling systems across scales and at multiple levels-especially to link population and ecosystem dynamics to individual adaptive behaviour-is essential for making the science predictive. 'Pattern-oriented modelling' (POM) is a strategy for doing just this. POM is the multi-criteria design, selection and calibration of models of complex systems. POM starts with identifying a set of patterns observed at multiple scales and levels that characterize a system with respect to the particular problem being modelled; a model from which the patterns emerge should contain the right mechanisms to address the problem. These patterns are then used to (i) determine what scales, entities, variables and processes the model needs, (ii) test and select submodels to represent key low-level processes such as adaptive behaviour, and (iii) find useful parameter values during calibration. Patterns are already often used in these ways, but a mini-review of applications of POM confirms that making the selection and use of patterns more explicit and rigorous can facilitate the development of models with the right level of complexity to understand ecological systems and predict their response to novel conditions.

  18. Multi-bits error detection and fast recovery in RISC cores

    International Nuclear Information System (INIS)

    Wang Jing; Yang Xing; Zhang Weigong; Shen Jiao; Qiu Keni; Zhao Yuanfu

    2015-01-01

    The particles-induced soft errors are a major threat to the reliability of microprocessors. Even worse, multi-bits upsets (MBUs) are ever-increased due to the rapidly shrinking feature size of the IC on a chip. Several architecture-level mechanisms have been proposed to protect microprocessors from soft errors, such as dual and triple modular redundancies (DMR and TMR). However, most of them are inefficient to combat the growing multi-bits errors or cannot well balance the critical paths delay, area and power penalty. This paper proposes a novel architecture, self-recovery dual-pipeline (SRDP), to effectively provide soft error detection and recovery with low cost for general RISC structures. We focus on the following three aspects. First, an advanced DMR pipeline is devised to detect soft error, especially MBU. Second, SEU/MBU errors can be located by enhancing self-checking logic into pipelines stage registers. Third, a recovery scheme is proposed with a recovery cost of 1 or 5 clock cycles. Our evaluation of a prototype implementation exhibits that the SRDP can successfully detect particle-induced soft errors up to 100% and recovery is nearly 95%, the other 5% will inter a specific trap. (paper)

  19. Multi-bits error detection and fast recovery in RISC cores

    Science.gov (United States)

    Jing, Wang; Xing, Yang; Yuanfu, Zhao; Weigong, Zhang; Jiao, Shen; Keni, Qiu

    2015-11-01

    The particles-induced soft errors are a major threat to the reliability of microprocessors. Even worse, multi-bits upsets (MBUs) are ever-increased due to the rapidly shrinking feature size of the IC on a chip. Several architecture-level mechanisms have been proposed to protect microprocessors from soft errors, such as dual and triple modular redundancies (DMR and TMR). However, most of them are inefficient to combat the growing multi-bits errors or cannot well balance the critical paths delay, area and power penalty. This paper proposes a novel architecture, self-recovery dual-pipeline (SRDP), to effectively provide soft error detection and recovery with low cost for general RISC structures. We focus on the following three aspects. First, an advanced DMR pipeline is devised to detect soft error, especially MBU. Second, SEU/MBU errors can be located by enhancing self-checking logic into pipelines stage registers. Third, a recovery scheme is proposed with a recovery cost of 1 or 5 clock cycles. Our evaluation of a prototype implementation exhibits that the SRDP can successfully detect particle-induced soft errors up to 100% and recovery is nearly 95%, the other 5% will inter a specific trap.

  20. Evaluating and Improving Automatic Sleep Spindle Detection by Using Multi-Objective Evolutionary Algorithms

    Directory of Open Access Journals (Sweden)

    Min-Yin Liu

    2017-05-01

    Full Text Available Sleep spindles are brief bursts of brain activity in the sigma frequency range (11–16 Hz measured by electroencephalography (EEG mostly during non-rapid eye movement (NREM stage 2 sleep. These oscillations are of great biological and clinical interests because they potentially play an important role in identifying and characterizing the processes of various neurological disorders. Conventionally, sleep spindles are identified by expert sleep clinicians via visual inspection of EEG signals. The process is laborious and the results are inconsistent among different experts. To resolve the problem, numerous computerized methods have been developed to automate the process of sleep spindle identification. Still, the performance of these automated sleep spindle detection methods varies inconsistently from study to study. There are two reasons: (1 the lack of common benchmark databases, and (2 the lack of commonly accepted evaluation metrics. In this study, we focus on tackling the second problem by proposing to evaluate the performance of a spindle detector in a multi-objective optimization context and hypothesize that using the resultant Pareto fronts for deriving evaluation metrics will improve automatic sleep spindle detection. We use a popular multi-objective evolutionary algorithm (MOEA, the Strength Pareto Evolutionary Algorithm (SPEA2, to optimize six existing frequency-based sleep spindle detection algorithms. They include three Fourier, one continuous wavelet transform (CWT, and two Hilbert-Huang transform (HHT based algorithms. We also explore three hybrid approaches. Trained and tested on open-access DREAMS and MASS databases, two new hybrid methods of combining Fourier with HHT algorithms show significant performance improvement with F1-scores of 0.726–0.737.

  1. Automated multi-lesion detection for referable diabetic retinopathy in indigenous health care.

    Directory of Open Access Journals (Sweden)

    Ramon Pires

    Full Text Available Diabetic Retinopathy (DR is a complication of diabetes mellitus that affects more than one-quarter of the population with diabetes, and can lead to blindness if not discovered in time. An automated screening enables the identification of patients who need further medical attention. This study aimed to classify retinal images of Aboriginal and Torres Strait Islander peoples utilizing an automated computer-based multi-lesion eye screening program for diabetic retinopathy. The multi-lesion classifier was trained on 1,014 images from the São Paulo Eye Hospital and tested on retinal images containing no DR-related lesion, single lesions, or multiple types of lesions from the Inala Aboriginal and Torres Strait Islander health care centre. The automated multi-lesion classifier has the potential to enhance the efficiency of clinical practice delivering diabetic retinopathy screening. Our program does not necessitate image samples for training from any specific ethnic group or population being assessed and is independent of image pre- or post-processing to identify retinal lesions. In this Aboriginal and Torres Strait Islander population, the program achieved 100% sensitivity and 88.9% specificity in identifying bright lesions, while detection of red lesions achieved a sensitivity of 67% and specificity of 95%. When both bright and red lesions were present, 100% sensitivity with 88.9% specificity was obtained. All results obtained with this automated screening program meet WHO standards for diabetic retinopathy screening.

  2. Automated detection of follow-up appointments using text mining of discharge records.

    Science.gov (United States)

    Ruud, Kari L; Johnson, Matthew G; Liesinger, Juliette T; Grafft, Carrie A; Naessens, James M

    2010-06-01

    To determine whether text mining can accurately detect specific follow-up appointment criteria in free-text hospital discharge records. Cross-sectional study. Mayo Clinic Rochester hospitals. Inpatients discharged from general medicine services in 2006 (n = 6481). Textual hospital dismissal summaries were manually reviewed to determine whether the records contained specific follow-up appointment arrangement elements: date, time and either physician or location for an appointment. The data set was evaluated for the same criteria using SAS Text Miner software. The two assessments were compared to determine the accuracy of text mining for detecting records containing follow-up appointment arrangements. Agreement of text-mined appointment findings with gold standard (manual abstraction) including sensitivity, specificity, positive predictive and negative predictive values (PPV and NPV). About 55.2% (3576) of discharge records contained all criteria for follow-up appointment arrangements according to the manual review, 3.2% (113) of which were missed through text mining. Text mining incorrectly identified 3.7% (107) follow-up appointments that were not considered valid through manual review. Therefore, the text mining analysis concurred with the manual review in 96.6% of the appointment findings. Overall sensitivity and specificity were 96.8 and 96.3%, respectively; and PPV and NPV were 97.0 and 96.1%, respectively. of individual appointment criteria resulted in accuracy rates of 93.5% for date, 97.4% for time, 97.5% for physician and 82.9% for location. Text mining of unstructured hospital dismissal summaries can accurately detect documentation of follow-up appointment arrangement elements, thus saving considerable resources for performance assessment and quality-related research.

  3. Detection of hepatocellular carcinoma with multi-slice spiral CT by ...

    African Journals Online (AJOL)

    STORAGESEVER

    2010-06-07

    Jun 7, 2010 ... The purpose of the study is to evaluate the effect of iodine concentration of contrast material on detection of hepatocellular carcinoma with multi-slice spiral computed tomography (CT) by using double-arterial phase and portal venous phase enhanced scanning. Ninety-four (94) patients with hepatocellular ...

  4. Layout-aware text extraction from full-text PDF of scientific articles

    Directory of Open Access Journals (Sweden)

    Ramakrishnan Cartic

    2012-05-01

    Full Text Available Abstract Background The Portable Document Format (PDF is the most commonly used file format for online scientific publications. The absence of effective means to extract text from these PDF files in a layout-aware manner presents a significant challenge for developers of biomedical text mining or biocuration informatics systems that use published literature as an information source. In this paper we introduce the ‘Layout-Aware PDF Text Extraction’ (LA-PDFText system to facilitate accurate extraction of text from PDF files of research articles for use in text mining applications. Results Our paper describes the construction and performance of an open source system that extracts text blocks from PDF-formatted full-text research articles and classifies them into logical units based on rules that characterize specific sections. The LA-PDFText system focuses only on the textual content of the research articles and is meant as a baseline for further experiments into more advanced extraction methods that handle multi-modal content, such as images and graphs. The system works in a three-stage process: (1 Detecting contiguous text blocks using spatial layout processing to locate and identify blocks of contiguous text, (2 Classifying text blocks into rhetorical categories using a rule-based method and (3 Stitching classified text blocks together in the correct order resulting in the extraction of text from section-wise grouped blocks. We show that our system can identify text blocks and classify them into rhetorical categories with Precision1 = 0.96% Recall = 0.89% and F1 = 0.91%. We also present an evaluation of the accuracy of the block detection algorithm used in step 2. Additionally, we have compared the accuracy of the text extracted by LA-PDFText to the text from the Open Access subset of PubMed Central. We then compared this accuracy with that of the text extracted by the PDF2Text system, 2commonly used to extract text from PDF

  5. 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.

  6. Layout-aware text extraction from full-text PDF of scientific articles.

    Science.gov (United States)

    Ramakrishnan, Cartic; Patnia, Abhishek; Hovy, Eduard; Burns, Gully Apc

    2012-05-28

    The Portable Document Format (PDF) is the most commonly used file format for online scientific publications. The absence of effective means to extract text from these PDF files in a layout-aware manner presents a significant challenge for developers of biomedical text mining or biocuration informatics systems that use published literature as an information source. In this paper we introduce the 'Layout-Aware PDF Text Extraction' (LA-PDFText) system to facilitate accurate extraction of text from PDF files of research articles for use in text mining applications. Our paper describes the construction and performance of an open source system that extracts text blocks from PDF-formatted full-text research articles and classifies them into logical units based on rules that characterize specific sections. The LA-PDFText system focuses only on the textual content of the research articles and is meant as a baseline for further experiments into more advanced extraction methods that handle multi-modal content, such as images and graphs. The system works in a three-stage process: (1) Detecting contiguous text blocks using spatial layout processing to locate and identify blocks of contiguous text, (2) Classifying text blocks into rhetorical categories using a rule-based method and (3) Stitching classified text blocks together in the correct order resulting in the extraction of text from section-wise grouped blocks. We show that our system can identify text blocks and classify them into rhetorical categories with Precision1 = 0.96% Recall = 0.89% and F1 = 0.91%. We also present an evaluation of the accuracy of the block detection algorithm used in step 2. Additionally, we have compared the accuracy of the text extracted by LA-PDFText to the text from the Open Access subset of PubMed Central. We then compared this accuracy with that of the text extracted by the PDF2Text system, 2commonly used to extract text from PDF. Finally, we discuss preliminary error analysis for

  7. Advanced concepts in multi-dimensional radiation detection and imaging

    International Nuclear Information System (INIS)

    Vetter, Kai; Barnowski, Ross; Pavlovsky, Ryan; Haefner, Andy; Torii, Tatsuo; Shikaze, Yoshiaki; Sanada, Yukihisa

    2016-01-01

    Recent developments in the detector fabrication, signal readout, and data processing enable new concepts in radiation detection that are relevant for applications ranging from fundamental physics to medicine as well as nuclear security and safety. We present recent progress in multi-dimensional radiation detection and imaging in the Berkeley Applied Nuclear Physics program. It is based on the ability to reconstruct scenes in three dimensions and fuse it with gamma-ray image information. We are using the High-Efficiency Multimode Imager HEMI in its Compton imaging mode and combining it with contextual sensors such as the Microsoft Kinect or visual cameras. This new concept of volumetric imaging or scene data fusion provides unprecedented capabilities in radiation detection and imaging relevant for the detection and mapping of radiological and nuclear materials. This concept brings us one step closer to the seeing the world with gamma-ray eyes. (author)

  8. Multi-sensor radiation detector system

    International Nuclear Information System (INIS)

    Foster, R.G.; Cyboron, R.D.

    1975-01-01

    The invention is a multi-sensor radiation detection system including a self-powered detector and an ion or fission chamber, preferably joined as a unitary structure, for removable insertion into a nuclear reactor. The detector and chamber are connected electrically in parallel, requiring but two conductors extending out of the reactor to external electrical circuitry which includes a load impedance, a voltage source, and switch means. The switch means are employed to alternately connect the detector and chamber either with th load impedance or with the load impedance and the voltage source. In the former orientation, current through the load impedance indicates flux intensity at the self-powered detector and in the latter orientation, the current indicates flux intensity at the detector and fission chamber, though almost all of the current is contributed by the fission chamber. (auth)

  9. Toward Vision Oriented Organization through Foresight Capability Development

    Directory of Open Access Journals (Sweden)

    Gianita BLEOJU

    2014-11-01

    Full Text Available Dealing with complexity is becoming increasingly difficult for organizations, due to limited replicable abilities, once management performance was remunerated by successful decisions on the marketplace. The competitive advantage, based upon current documented organizational management expertise, deployed into patterns of competitive behavior, prove to be unsustainable. Therefore, we assist to a relative emergency of strategic intelligence adjustment framework, to channel the managerial capability mechanisms, from current detective orientation capabilities toward anticipatory ones. Based upon exploitation of an organizational profiling database, we try our contribution to this challenging debate, by formulating recommendations for strategic adjustment and prototype testing of the potential solutions, through a designed transition matrix from market oriented to vision oriented organizations.

  10. Text Detection and Pose Estimation for a Reading Robot

    OpenAIRE

    Bulacu, Marius; Ezaki, Nobuo; Schomaker, Lambert

    2008-01-01

    One very important advantage of using CoCos for text detection is that they naturally allow the analysis to take place across scales. In this approach, scale does not represent such a problematic issue because the CoCo extraction process is scale independent. CoCos give a prompt, but rather imperfect, hold to the structures present in the image and CoCo selection

  11. Diagnostic value of multi-tumor markers protein biochip detection for primary pulmonary cancer

    International Nuclear Information System (INIS)

    Xu Fengpo; Wu Yiwei; Li Qingru; Fa Yihua

    2005-01-01

    To evaluate the diagnostic value of multi-tumor markers protein biochip detection for primary pulmonary cancer, 12 tumor markers including AFP, CEA, NSE, CA125, CA15-3, CA242, CA19-9, PSA, f-PSA, FER, β-HCG and HGH were measured by the protein biochip in the serum of 45 primary pulmonary cancer patients. Positive rate of tumor markers was FER (42.2%), CEA (35.6%), CA125 (24.4%), CA15-3 (17.8%), CA242 (13.3%), CA19-9 (11.1%), β-HCG(8.9%), HGH(6.7%), NSE(4.4%), AFP (0), f-PSA (0) and PSA (0), respectively. The rate of patients with one abnorma indicator was 57.8% except FER. The positive rate using multi-tumor markers protein biochip detection was significantly higher than that of single tumor marker detective method, and this detection can be used for the diagnosis of patients with primary pulmonary cancer. (authors)

  12. Representation of Block-Based Image Features in a Multi-Scale Framework for Built-Up Area Detection

    Directory of Open Access Journals (Sweden)

    Zhongwen Hu

    2016-02-01

    Full Text Available The accurate extraction and mapping of built-up areas play an important role in many social, economic, and environmental studies. In this paper, we propose a novel approach for built-up area detection from high spatial resolution remote sensing images, using a block-based multi-scale feature representation framework. First, an image is divided into small blocks, in which the spectral, textural, and structural features are extracted and represented using a multi-scale framework; a set of refined Harris corner points is then used to select blocks as training samples; finally, a built-up index image is obtained by minimizing the normalized spectral, textural, and structural distances to the training samples, and a built-up area map is obtained by thresholding the index image. Experiments confirm that the proposed approach is effective for high-resolution optical and synthetic aperture radar images, with different scenes and different spatial resolutions.

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

    Science.gov (United States)

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

    2018-04-01

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

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

    Directory of Open Access Journals (Sweden)

    Omar E. Mora

    2018-01-01

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

  15. Integrating physically based simulators with Event Detection Systems: Multi-site detection approach.

    Science.gov (United States)

    Housh, Mashor; Ohar, Ziv

    2017-03-01

    The Fault Detection (FD) Problem in control theory concerns of monitoring a system to identify when a fault has occurred. Two approaches can be distinguished for the FD: Signal processing based FD and Model-based FD. The former concerns of developing algorithms to directly infer faults from sensors' readings, while the latter uses a simulation model of the real-system to analyze the discrepancy between sensors' readings and expected values from the simulation model. Most contamination Event Detection Systems (EDSs) for water distribution systems have followed the signal processing based FD, which relies on analyzing the signals from monitoring stations independently of each other, rather than evaluating all stations simultaneously within an integrated network. In this study, we show that a model-based EDS which utilizes a physically based water quality and hydraulics simulation models, can outperform the signal processing based EDS. We also show that the model-based EDS can facilitate the development of a Multi-Site EDS (MSEDS), which analyzes the data from all the monitoring stations simultaneously within an integrated network. The advantage of the joint analysis in the MSEDS is expressed by increased detection accuracy (higher true positive alarms and fewer false alarms) and shorter detection time. Copyright © 2016 Elsevier Ltd. All rights reserved.

  16. Particle detection from oriented nuclei

    International Nuclear Information System (INIS)

    Wouters, J.; Moor, P. de; Schuurmans, P.; Severijns, N.; Vanderpoorten, W.; Vanneste, L.

    1992-01-01

    A survey is given of particle emission from nuclei that have been spin oriented by cryogenical means. Experiments and recent developments with detectors in the low temperature environment and their on-line application are reviewed. The most recent results are mentioned. Some phenomena to be unraveled in future studies are pointed out. (orig.)

  17. Saharan dust detection using multi-sensor satellite measurements

    Directory of Open Access Journals (Sweden)

    Sriharsha Madhavan

    2017-02-01

    Full Text Available Contemporary scientists have vested interest in trying to understand the climatology of the North Atlantic Basin since this region is considered as the genesis for hurricane formation that eventually get shipped to the tropical Atlantic region and the Caribbean. The effects of atmospheric water cycle and the climate of West Africa and the Atlantic basin are hugely impacted by the radiative forcing of Saharan dust. The focus area in this paper would be to improve the dust detection schemes by employing the use of multi sensor measurements in the thermal emissive wavelengths using legacy sensors such as Terra (T and Aqua (A MODerate-resolution Imaging Spectroradiometer (MODIS, fusing with Ozone Monitoring Instrument (OMI. Previous work by Hao and Qu (2007 had considered a limited number of thermal infrared channels which led to a correlation coefficient R2 value of 0.765 between the Aerosol Optical Thickness (AOT at 550 nm and the modeled dust index. In this work, we extend the thermal infrared based dust detection by employing additional channels: the 8.55 μm which has shown high sensitivity to the Saharan dust, along with water vapor channel of 7.1 μm and cloud top channel of 13.1 μm. Also, the dust pixels were clearly identified using the OMI based aerosol types. The dust pixels were cleanly segregated from the other aerosol types such as sulfates, biomass, and other carbonaceous aerosols. These improvements led to a much higher correlation coefficient R2 value of 0.85 between the modified dust index and the AOT in comparison to the previous work. The key limitations from the current AOT products based on MODIS and were put to test by validating the improved dust detection algorithm. Two improvements were noted. First, the dust measurement radiometry using MODIS is significantly improved by at least an order of 2. Second the spatial measurements are enhanced by a factor of at least 10.

  18. Detecting Slums from Quick Bird Data in Pune Using AN Object Oriented Approach

    Science.gov (United States)

    Shekhar, S.

    2012-07-01

    We have been witnessing a gradual and steady transformation from a pre dominantly rural society to an urban society in India and by 2030, it will have more people living in urban than rural areas. Slums formed an integral part of Indian urbanisation as most of the Indian cities lack in basic needs of an acceptable life. Many efforts are being taken to improve their conditions. To carry out slum renewal programs and monitor its implementation, slum settlements should be recorded to obtain an adequate spatial data base. This can be only achieved through the analysis of remote sensing data with very high spatial resolution. Regarding the occurrences of settlement areas in the remote sensing data pixel-based approach on a high resolution image is unable to represent the heterogeneity of complex urban environments. Hence there is a need for sophisticated method and data for slum analysis. An attempt has been made to detect and discriminate the slums of Pune city by describing typical characteristics of these settlements, by using eCognition software from quick bird data on the basis of object oriented approach. Based on multi resolution segmentation, initial objects were created and further depend on texture, geometry and contextual characteristics of the image objects, they were classified into slums and non-slums. The developed rule base allowed the description of knowledge about phenomena clearly and easily using fuzzy membership functions and the described knowledge stored in the classification rule base led to the best classification with more than 80% accuracy.

  19. Verifying the model of predicting entrepreneurial intention among students of business and non-business orientation

    Directory of Open Access Journals (Sweden)

    Zoran Sušanj

    2015-01-01

    Full Text Available This study aims to verify whether certain entrepreneurial characteristics, like entrepreneurial potential and entrepreneurial propensity, affect the level of entrepreneurial self-efficacy and desirability of entrepreneurship, and further have direct and indirect effect on entrepreneurial intentions. Furthermore, this study seeks to compare the strength of the relationship between these variables among groups of students who receive some entrepreneurship education and students outside the business sphere. Data was collected from a sample of undergraduate students of business and non-business orientation and analyzed with multi-group analysis within SEM. Results of the multi-group analysis indicate that indeed, the strength of the relationship among tested variables is more pronounced when it comes to business students. That is, mediating effect of perceived entrepreneurial self-efficacy and desirability of entrepreneurship in the relationship between entrepreneurial characteristics and intent, is significantly stronger for the business-oriented groups, in comparison to non-business orientation group. The amount of explained variance of all constructs (except entrepreneurial propensity is also larger in business students in comparison to non-business students. Educational implications of obtained results are discussed.

  20. Detection of surface cracking in steel pipes based on vibration data using a multi-class support vector machine classifier

    Science.gov (United States)

    Mustapha, S.; Braytee, A.; Ye, L.

    2017-04-01

    In this study, we focused at the development and verification of a robust framework for surface crack detection in steel pipes using measured vibration responses; with the presence of multiple progressive damage occurring in different locations within the structure. Feature selection, dimensionality reduction, and multi-class support vector machine were established for this purpose. Nine damage cases, at different locations, orientations and length, were introduced into the pipe structure. The pipe was impacted 300 times using an impact hammer, after each damage case, the vibration data were collected using 3 PZT wafers which were installed on the outer surface of the pipe. At first, damage sensitive features were extracted using the frequency response function approach followed by recursive feature elimination for dimensionality reduction. Then, a multi-class support vector machine learning algorithm was employed to train the data and generate a statistical model. Once the model is established, decision values and distances from the hyper-plane were generated for the new collected data using the trained model. This process was repeated on the data collected from each sensor. Overall, using a single sensor for training and testing led to a very high accuracy reaching 98% in the assessment of the 9 damage cases used in this study.

  1. Multi-valued logic in breast cancer detection.

    Science.gov (United States)

    Boiculese, L V; Dimitriu, G

    2003-01-01

    The aim of this paper is to determine the type of the breast cancer disease. The two classes of separation are malignant respectively benign. A multi-valued logic system (fuzzy system) was develop and applied in this classification. The system uses nine attributes as inputs that were scaled with an integer value in the range between 1 and 10. The attributes represent: 1. Clump Thickness, 2. Uniformity of Cell Size, 3. Uniformity of Cell Shape, 4. Marginal Adhesion, 5. Single Epithelial Cell Size, 6. Bare Nuclei, 7. Bland Chromatin, 8. Normal Nucleoli, 9. Mitoses. After training the system managed to get a good detection with an error less than 5%.

  2. Automatic multi-modal intelligent seizure acquisition (MISA) system for detection of motor seizures from electromyographic data and motion data

    DEFF Research Database (Denmark)

    Conradsen, Isa; Beniczky, Sándor; Wolf, Peter

    2012-01-01

    measures of reconstructed sub-bands from the discrete wavelet transformation (DWT) and the wavelet packet transformation (WPT). Based on the extracted features all data segments were classified using a support vector machine (SVM) algorithm as simulated seizure or normal activity. A case study...... of the seizure from the patient showed that the simulated seizures were visually similar to the epileptic one. The multi-modal intelligent seizure acquisition (MISA) system showed high sensitivity, short detection latency and low false detection rate. The results showed superiority of the multi- modal detection...... system compared to the uni-modal one. The presented system has a promising potential for seizure detection based on multi-modal data....

  3. Pattern-oriented modelling: a ‘multi-scope’ for predictive systems ecology

    Science.gov (United States)

    Grimm, Volker; Railsback, Steven F.

    2012-01-01

    Modern ecology recognizes that modelling systems across scales and at multiple levels—especially to link population and ecosystem dynamics to individual adaptive behaviour—is essential for making the science predictive. ‘Pattern-oriented modelling’ (POM) is a strategy for doing just this. POM is the multi-criteria design, selection and calibration of models of complex systems. POM starts with identifying a set of patterns observed at multiple scales and levels that characterize a system with respect to the particular problem being modelled; a model from which the patterns emerge should contain the right mechanisms to address the problem. These patterns are then used to (i) determine what scales, entities, variables and processes the model needs, (ii) test and select submodels to represent key low-level processes such as adaptive behaviour, and (iii) find useful parameter values during calibration. Patterns are already often used in these ways, but a mini-review of applications of POM confirms that making the selection and use of patterns more explicit and rigorous can facilitate the development of models with the right level of complexity to understand ecological systems and predict their response to novel conditions. PMID:22144392

  4. Performance of serum biomarkers for the early detection of invasive aspergillosis in febrile, neutropenic patients: a multi-state model.

    Directory of Open Access Journals (Sweden)

    Michaël Schwarzinger

    Full Text Available The performance of serum biomarkers for the early detection of invasive aspergillosis expectedly depends on the timing of test results relative to the empirical administration of antifungal therapy during neutropenia, although a dynamic evaluation framework is lacking.We developed a multi-state model describing simultaneously the likelihood of empirical antifungal therapy and the risk of invasive aspergillosis during neutropenia. We evaluated whether the first positive test result with a biomarker is an independent predictor of invasive aspergillosis when both diagnostic information used to treat and risk factors of developing invasive aspergillosis are taken into account over time. We applied the multi-state model to a homogeneous cohort of 185 high-risk patients with acute myeloid leukemia. Patients were prospectively screened for galactomannan antigenemia twice a week for immediate treatment decision; 2,214 serum samples were collected on the same days and blindly assessed for (1->3- β-D-glucan antigenemia and a quantitative PCR assay targeting a mitochondrial locus.The usual evaluation framework of biomarker performance was unable to distinguish clinical benefits of β-glucan or PCR assays. The multi-state model evidenced that the risk of invasive aspergillosis is a complex time function of neutropenia duration and risk management. The quantitative PCR assay accelerated the early detection of invasive aspergillosis (P = .010, independently of other diagnostic information used to treat, while β-glucan assay did not (P = .53.The performance of serum biomarkers for the early detection of invasive aspergillosis is better apprehended by the evaluation of time-varying predictors in a multi-state model. Our results provide strong rationale for prospective studies testing a preemptive antifungal therapy, guided by clinical, radiological, and bi-weekly blood screening with galactomannan antigenemia and a standardized quantitative PCR assay.

  5. Service Orientation in Holonic and Multi-Agent Manufacturing Control

    CERN Document Server

    Thomas, André; Trentesaux, Damien

    2012-01-01

    Service orientation is emerging nowadays at multiple organizational levels in enterprise business, and it leverages technology in response to the growing need for greater business integration, flexibility and agility of manufacturing enterprises. This book gathers contributions from scientists, researchers and industrialists on concepts, methods, frameworks and implementing issues addressing trends in the service orientation of control technology and management applied to manufacturing enterprise. It analyzes a Service Oriented Architecture (SOA) representing a technical architecture, a business modelling concept, a type of infrastructure, an integration source and a new way of viewing units of automation within the enterprise. The presents how SOA aligns the business world with the world of information technology in a way that makes both more effective.  

  6. [A cloud detection algorithm for MODIS images combining Kmeans clustering and multi-spectral threshold method].

    Science.gov (United States)

    Wang, Wei; Song, Wei-Guo; Liu, Shi-Xing; Zhang, Yong-Ming; Zheng, Hong-Yang; Tian, Wei

    2011-04-01

    An improved method for detecting cloud combining Kmeans clustering and the multi-spectral threshold approach is described. On the basis of landmark spectrum analysis, MODIS data is categorized into two major types initially by Kmeans method. The first class includes clouds, smoke and snow, and the second class includes vegetation, water and land. Then a multi-spectral threshold detection is applied to eliminate interference such as smoke and snow for the first class. The method is tested with MODIS data at different time under different underlying surface conditions. By visual method to test the performance of the algorithm, it was found that the algorithm can effectively detect smaller area of cloud pixels and exclude the interference of underlying surface, which provides a good foundation for the next fire detection approach.

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

    Science.gov (United States)

    Beer, N. Reginald; Paglieroni, David W.

    2015-07-21

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

  8. Multi-Branch Fully Convolutional Network for Face Detection

    KAUST Repository

    Bai, Yancheng

    2017-07-20

    Face detection is a fundamental problem in computer vision. It is still a challenging task in unconstrained conditions due to significant variations in scale, pose, expressions, and occlusion. In this paper, we propose a multi-branch fully convolutional network (MB-FCN) for face detection, which considers both efficiency and effectiveness in the design process. Our MB-FCN detector can deal with faces at all scale ranges with only a single pass through the backbone network. As such, our MB-FCN model saves computation and thus is more efficient, compared to previous methods that make multiple passes. For each branch, the specific skip connections of the convolutional feature maps at different layers are exploited to represent faces in specific scale ranges. Specifically, small faces can be represented with both shallow fine-grained and deep powerful coarse features. With this representation, superior improvement in performance is registered for the task of detecting small faces. We test our MB-FCN detector on two public face detection benchmarks, including FDDB and WIDER FACE. Extensive experiments show that our detector outperforms state-of-the-art methods on all these datasets in general and by a substantial margin on the most challenging among them (e.g. WIDER FACE Hard subset). Also, MB-FCN runs at 15 FPS on a GPU for images of size 640 x 480 with no assumption on the minimum detectable face size.

  9. Statistical text classifier to detect specific type of medical incidents.

    Science.gov (United States)

    Wong, Zoie Shui-Yee; Akiyama, Masanori

    2013-01-01

    WHO Patient Safety has put focus to increase the coherence and expressiveness of patient safety classification with the foundation of International Classification for Patient Safety (ICPS). Text classification and statistical approaches has showed to be successful to identifysafety problems in the Aviation industryusing incident text information. It has been challenging to comprehend the taxonomy of medical incidents in a structured manner. Independent reporting mechanisms for patient safety incidents have been established in the UK, Canada, Australia, Japan, Hong Kong etc. This research demonstrates the potential to construct statistical text classifiers to detect specific type of medical incidents using incident text data. An illustrative example for classifying look-alike sound-alike (LASA) medication incidents using structured text from 227 advisories related to medication errors from Global Patient Safety Alerts (GPSA) is shown in this poster presentation. The classifier was built using logistic regression model. ROC curve and the AUC value indicated that this is a satisfactory good model.

  10. Detection of cosmic ray tracks using scintillating fibers and position sensitive multi-anode photomultipliers

    International Nuclear Information System (INIS)

    Atac, M.; Streets, J.; Wilcer, N.

    1998-02-01

    This experiment demonstrates detection of cosmic ray tracks by using Scintillating fiber planes and multi-anode photomultipliers (MA-PMTs). In a laboratory like this, cosmic rays provide a natural source of high-energy charged particles which can be detected with high efficiency and with nanosecond time resolution

  11. Image-Based Multi-Target Tracking through Multi-Bernoulli Filtering with Interactive Likelihoods

    Directory of Open Access Journals (Sweden)

    Anthony Hoak

    2017-03-01

    Full Text Available We develop an interactive likelihood (ILH for sequential Monte Carlo (SMC methods for image-based multiple target tracking applications. The purpose of the ILH is to improve tracking accuracy by reducing the need for data association. In addition, we integrate a recently developed deep neural network for pedestrian detection along with the ILH with a multi-Bernoulli filter. We evaluate the performance of the multi-Bernoulli filter with the ILH and the pedestrian detector in a number of publicly available datasets (2003 PETS INMOVE, Australian Rules Football League (AFL and TUD-Stadtmitte using standard, well-known multi-target tracking metrics (optimal sub-pattern assignment (OSPA and classification of events, activities and relationships for multi-object trackers (CLEAR MOT. In all datasets, the ILH term increases the tracking accuracy of the multi-Bernoulli filter.

  12. Synthesis of a multi-functional DNA nanosphere barcode system for direct cell detection.

    Science.gov (United States)

    Han, Sangwoo; Lee, Jae Sung; Lee, Jong Bum

    2017-09-28

    Nucleic acid-based technologies have been applied to numerous biomedical applications. As a novel material for target detection, DNA has been used to construct a barcode system with a range of structures. This paper reports multi-functionalized DNA nanospheres (DNANSs) by rolling circle amplification (RCA) with several functionalized nucleotides. DNANSs with a barcode system were designed to exhibit fluorescence for coding enhanced signals and contain biotin for more functionalities, including targeting through the biotin-streptavidin (biotin-STA) interaction. Functionalized deoxynucleotide triphosphates (dNTPs) were mixed in the RCA process and functional moieties can be expressed on the DNANSs. The anti-epidermal growth factor receptor antibodies (anti-EGFR Abs) can be conjugated on DNANSs for targeting cancer cells specifically. As a proof of concept, the potential of the multi-functional DNANS barcode was demonstrated by direct cell detection as a simple detection method. The DNANS barcode provides a new route for the simple and rapid selective recognition of cancer cells.

  13. Multi-arrhythmias detection with an XML rule-based system from 12-Lead Electrocardiogram.

    Science.gov (United States)

    Khelassi, Abdeldjalil; Yelles-Chaouche, Sarra-Nassira; Benais, Faiza

    2017-05-01

    The computer-aided detection of cardiac arrhythmias stills a crucial application in medical technologies. The rule based systems RBS ensure a high level of transparency and interpretability of the obtained results. To facilitate the diagnosis of the cardiologists and to reduce the uncertainty made in this diagnosis. In this research article, we have realized a classification and automatic recognition of cardiac arrhythmias, by using XML rules that represent the cardiologist knowledge. Thirteen experiments with different knowledge bases were realized for improving the performance of the used method in the detection of 13 cardiac arrhythmias. In the first 12 experiments, we have designed a specialized knowledge base for each cardiac arrhythmia, which contains just one arrhythmia detection rule. In the last experiment, we applied the knowledge base which contains rules of 12 arrhythmias. We used, for the experiments, an international data set with 279 features and 452 records characterizing 12 leads of ECG signal and social information of patients. The data sets were constructed and published at Bilkent University of Ankara, Turkey. In addition, the second version of the self-developed software "XMLRULE" was used; the software can infer more than one class and facilitate the interpretability of the obtained results. The 12 first experiments give 82.80% of correct detection as the mean of all experiments, the results were between 19% and 100% with a low rate in just one experiment. The last experiment in which all arrhythmias are considered, the results of correct detection was 38.33% with 90.55% of sensibility and 46.24% of specificity. It was clearly show that in these results the good choice of the classification model is very beneficial in terms of performance. The obtained results were better than the published results with other computational methods for the mono class detection, but it was less in multi-class detection. The RBS is the most transparent method for

  14. Detecting causality from online psychiatric texts using inter-sentential language patterns

    Directory of Open Access Journals (Sweden)

    Wu Jheng-Long

    2012-07-01

    Full Text Available Abstract Background Online psychiatric texts are natural language texts expressing depressive problems, published by Internet users via community-based web services such as web forums, message boards and blogs. Understanding the cause-effect relations embedded in these psychiatric texts can provide insight into the authors’ problems, thus increasing the effectiveness of online psychiatric services. Methods Previous studies have proposed the use of word pairs extracted from a set of sentence pairs to identify cause-effect relations between sentences. A word pair is made up of two words, with one coming from the cause text span and the other from the effect text span. Analysis of the relationship between these words can be used to capture individual word associations between cause and effect sentences. For instance, (broke up, life and (boyfriend, meaningless are two word pairs extracted from the sentence pair: “I broke up with my boyfriend. Life is now meaningless to me”. The major limitation of word pairs is that individual words in sentences usually cannot reflect the exact meaning of the cause and effect events, and thus may produce semantically incomplete word pairs, as the previous examples show. Therefore, this study proposes the use of inter-sentential language patterns such as ≪broke up, boyfriend>, Results Performance was evaluated on a corpus of texts collected from PsychPark (http://www.psychpark.org, a virtual psychiatric clinic maintained by a group of volunteer professionals from the Taiwan Association of Mental Health Informatics. Experimental results show that the use of inter-sentential language patterns outperformed the use of word pairs proposed in previous studies. Conclusions This study demonstrates the acquisition of inter-sentential language patterns for causality detection from online psychiatric texts. Such semantically more complete and precise features can improve causality detection performance.

  15. The Effects of Strategic Orientations and Perceived Environment on Firm Performance

    Directory of Open Access Journals (Sweden)

    Farkas Gergely

    2016-03-01

    Full Text Available Among micro, small, and medium-sized firms located in Hungary, I conducted a survey examining the effects of entrepreneurial and learning orientations, and that of perceived environment on firm performance. I studied the perceptions of environmental turbulence and environmental hostility. Three dimensions were examined both in the case of entrepreneurial orientation (i.e., innovativeness, proactiveness, and risk taking and in the case of learning orientation (i.e., commitment to learning, shared visions, and open-mindedness. The effects of such dimensions on firm performance were analyzed with the path analysis (PLS-SEM method. In the course of the research, firm performance was divided into three dimensions: efficiency, growth, and profit. The possible effect of available financial resources was also taken into consideration. Results show that the availability of financial resources is relatively important, although it is connected only to the growth dimension of performance. Strategic orientations should be interpreted as multi-dimensional, and they have an effect on different performance dimensions. The research was cross-sectional and has implications for long-term strategic decisions.

  16. POTENTIAL OF MULTI-TEMPORAL OBLIQUE AIRBORNE IMAGERY FOR STRUCTURAL DAMAGE ASSESSMENT

    Directory of Open Access Journals (Sweden)

    A. Vetrivel

    2016-06-01

    Full Text Available Quick post-disaster actions demand automated, rapid and detailed building damage assessment. Among the available technologies, post-event oblique airborne images have already shown their potential for this task. However, existing methods usually compensate the lack of pre-event information with aprioristic assumptions of building shapes and textures that can lead to uncertainties and misdetections. However, oblique images have been already captured over many cities of the world, and the exploitation of pre- and post-event data as inputs to damage assessment is readily feasible in urban areas. In this paper, we investigate the potential of multi-temporal oblique imagery for detailed damage assessment focusing on two methodologies: the first method aims at detecting severe structural damages related to geometrical deformation by combining the complementary information provided by photogrammetric point clouds and oblique images. The developed method detected 87% of damaged elements. The failed detections are due to varying noise levels within the point cloud which hindered the recognition of some structural elements. We observed, in general that the façade regions are very noisy in point clouds. To address this, we propose our second method which aims to detect damages to building façades using the oriented oblique images. The results show that the proposed methodology can effectively differentiate among the three proposed categories: collapsed/highly damaged, lower levels of damage and undamaged buildings, using a computationally light-weight approach. We describe the implementations of the above mentioned methods in detail and present the promising results achieved using multi-temporal oblique imagery over the city of L’Aquila (Italy.

  17. Water Orientation at Ceramide/Water Interfaces Studied by Heterodyne-Detected Vibrational Sum Frequency Generation Spectroscopy and Molecular Dynamics Simulation

    KAUST Repository

    Adhikari, Aniruddha

    2016-10-10

    Lipid/water interaction is essential for many biological processes. The water structure at the nonionic lipid interface remains little known, and there is no scope of a priori prediction of water orientation at nonionic interfaces, either. Here, we report our study combining advanced nonlinear spectroscopy and molecular dynamics simulation on the water orientation at the ceramide/water interface. We measured χ spectrum in the OH stretch region of ceramide/isotopically diluted water interface using heterodyne-detected vibrational sum-frequency generation spectroscopy and found that the interfacial water prefers an overall hydrogen-up orientation. Molecular dynamics simulation indicates that this preferred hydrogen-up orientation of water is determined by a delicate balance between hydrogen-up and hydrogen-down orientation induced by lipid-water and intralipid hydrogen bonds. This mechanism also suggests that water orientation at neutral lipid interfaces depends highly on the chemical structure of the lipid headgroup, in contrast to the charged lipid interfaces where the net water orientation is determined solely by the charge of the lipid headgroup.

  18. Research on engineering-oriented constraints conflict detection in collaborative design of wire harness technology

    Institute of Scientific and Technical Information of China (English)

    LIU Xiaoping; HE Honglin; XU Benzhu

    2012-01-01

    Engineering-oriented constraint of harness technology has much information and project information presents progressive changes along with the design. Therefore, how to handle conflict resolution quickly is a problem to be solved. Process model of con- flict detection is put forward according to characteristics of harness technology design engineering-oriented constraint, and then two problems of how to conduct conflict positioning and judgment of constraint rules are introduced in this paper. Afterwards in this pa- per, constraint information directed acyclic graph is established by classified project constraint information to solve the conflict posi- tioning problem; solution of constraint satisfaction problem is applied to realize judgment problem of constraint rules. Finally, exam- ple is used to analyze the method in this paper to further verify the correctness and effectiveness of this method.

  19. Automatic Fabric Defect Detection with a Multi-Scale Convolutional Denoising Autoencoder Network Model

    Directory of Open Access Journals (Sweden)

    Shuang Mei

    2018-04-01

    Full Text Available Fabric defect detection is a necessary and essential step of quality control in the textile manufacturing industry. Traditional fabric inspections are usually performed by manual visual methods, which are low in efficiency and poor in precision for long-term industrial applications. In this paper, we propose an unsupervised learning-based automated approach to detect and localize fabric defects without any manual intervention. This approach is used to reconstruct image patches with a convolutional denoising autoencoder network at multiple Gaussian pyramid levels and to synthesize detection results from the corresponding resolution channels. The reconstruction residual of each image patch is used as the indicator for direct pixel-wise prediction. By segmenting and synthesizing the reconstruction residual map at each resolution level, the final inspection result can be generated. This newly developed method has several prominent advantages for fabric defect detection. First, it can be trained with only a small amount of defect-free samples. This is especially important for situations in which collecting large amounts of defective samples is difficult and impracticable. Second, owing to the multi-modal integration strategy, it is relatively more robust and accurate compared to general inspection methods (the results at each resolution level can be viewed as a modality. Third, according to our results, it can address multiple types of textile fabrics, from simple to more complex. Experimental results demonstrate that the proposed model is robust and yields good overall performance with high precision and acceptable recall rates.

  20. Emotion detection from text

    Science.gov (United States)

    Ramalingam, V. V.; Pandian, A.; Jaiswal, Abhijeet; Bhatia, Nikhar

    2018-04-01

    This paper presents a novel method based on concept of Machine Learning for Emotion Detection using various algorithms of Support Vector Machine and major emotions described are linked to the Word-Net for enhanced accuracy. The approach proposed plays a promising role to augment the Artificial Intelligence in the near future and could be vital in optimization of Human-Machine Interface.

  1. A high-throughput method for GMO multi-detection using a microfluidic dynamic array.

    Science.gov (United States)

    Brod, Fábio Cristiano Angonesi; van Dijk, Jeroen P; Voorhuijzen, Marleen M; Dinon, Andréia Zilio; Guimarães, Luis Henrique S; Scholtens, Ingrid M J; Arisi, Ana Carolina Maisonnave; Kok, Esther J

    2014-02-01

    The ever-increasing production of genetically modified crops generates a demand for high-throughput DNA-based methods for the enforcement of genetically modified organisms (GMO) labelling requirements. The application of standard real-time PCR will become increasingly costly with the growth of the number of GMOs that is potentially present in an individual sample. The present work presents the results of an innovative approach in genetically modified crops analysis by DNA based methods, which is the use of a microfluidic dynamic array as a high throughput multi-detection system. In order to evaluate the system, six test samples with an increasing degree of complexity were prepared, preamplified and subsequently analysed in the Fluidigm system. Twenty-eight assays targeting different DNA elements, GM events and species-specific reference genes were used in the experiment. The large majority of the assays tested presented expected results. The power of low level detection was assessed and elements present at concentrations as low as 0.06 % were successfully detected. The approach proposed in this work presents the Fluidigm system as a suitable and promising platform for GMO multi-detection.

  2. Multi-layer cube sampling for liver boundary detection in PET-CT images.

    Science.gov (United States)

    Liu, Xinxin; Yang, Jian; Song, Shuang; Song, Hong; Ai, Danni; Zhu, Jianjun; Jiang, Yurong; Wang, Yongtian

    2018-06-01

    Liver metabolic information is considered as a crucial diagnostic marker for the diagnosis of fever of unknown origin, and liver recognition is the basis of automatic diagnosis of metabolic information extraction. However, the poor quality of PET and CT images is a challenge for information extraction and target recognition in PET-CT images. The existing detection method cannot meet the requirement of liver recognition in PET-CT images, which is the key problem in the big data analysis of PET-CT images. A novel texture feature descriptor called multi-layer cube sampling (MLCS) is developed for liver boundary detection in low-dose CT and PET images. The cube sampling feature is proposed for extracting more texture information, which uses a bi-centric voxel strategy. Neighbour voxels are divided into three regions by the centre voxel and the reference voxel in the histogram, and the voxel distribution information is statistically classified as texture feature. Multi-layer texture features are also used to improve the ability and adaptability of target recognition in volume data. The proposed feature is tested on the PET and CT images for liver boundary detection. For the liver in the volume data, mean detection rate (DR) and mean error rate (ER) reached 95.15 and 7.81% in low-quality PET images, and 83.10 and 21.08% in low-contrast CT images. The experimental results demonstrated that the proposed method is effective and robust for liver boundary detection.

  3. Detecting Damaged Building Regions Based on Semantic Scene Change from Multi-Temporal High-Resolution Remote Sensing Images

    Directory of Open Access Journals (Sweden)

    Jihui Tu

    2017-04-01

    Full Text Available The detection of damaged building regions is crucial to emergency response actions and rescue work after a disaster. Change detection methods using multi-temporal remote sensing images are widely used for this purpose. Differing from traditional methods based on change detection for damaged building regions, semantic scene change can provide a new point of view since it can indicate the land-use variation at the semantic level. In this paper, a novel method is proposed for detecting damaged building regions based on semantic scene change in a visual Bag-of-Words model. Pre- and post-disaster scene change in building regions are represented by a uniform visual codebook frequency. The scene change of damaged and non-damaged building regions is discriminated using the Support Vector Machine (SVM classifier. An evaluation of experimental results, for a selected study site of the Longtou hill town of Yunnan, China, which was heavily damaged in the Ludian earthquake of 14 March 2013, shows that this method is feasible and effective for detecting damaged building regions. For the experiments, WorldView-2 optical imagery and aerial imagery is used.

  4. MODEL OF IMPROVING ENVIRONMENTAL MANAGEMENT SYSTEM BY MULTI - SOFTWARE

    Directory of Open Access Journals (Sweden)

    Jelena Jovanovic

    2009-03-01

    Full Text Available This paper is based on doctoral dissertation which is oriented on improving environmental management system using multi - software. In this doctoral dissertation will be used key results of master thesis which is oriented on quantification environmental aspects and impacts by artificial neural network in organizations. This paper recommend improving environmental management system in organization using Balanced scorecard model and MCDM method - AHP (Analytic hierarchy process based on group decision. BSC would be spread with elements of Environmental management system and used in area of strategic management system in organization and AHP would be used in area of checking results getting by quantification environmental aspects and impacts.

  5. Stability Analysis for a Multi-Camera Photogrammetric System

    Directory of Open Access Journals (Sweden)

    Ayman Habib

    2014-08-01

    Full Text Available Consumer-grade digital cameras suffer from geometrical instability that may cause problems when used in photogrammetric applications. This paper provides a comprehensive review of this issue of interior orientation parameter variation over time, it explains the common ways used for coping with the issue, and describes the existing methods for performing stability analysis for a single camera. The paper then points out the lack of coverage of stability analysis for multi-camera systems, suggests a modification of the collinearity model to be used for the calibration of an entire photogrammetric system, and proposes three methods for system stability analysis. The proposed methods explore the impact of the changes in interior orientation and relative orientation/mounting parameters on the reconstruction process. Rather than relying on ground truth in real datasets to check the system calibration stability, the proposed methods are simulation-based. Experiment results are shown, where a multi-camera photogrammetric system was calibrated three times, and stability analysis was performed on the system calibration parameters from the three sessions. The proposed simulation-based methods provided results that were compatible with a real-data based approach for evaluating the impact of changes in the system calibration parameters on the three-dimensional reconstruction.

  6. Assigning Main Orientation to an EOH Descriptor on Multispectral Images

    Directory of Open Access Journals (Sweden)

    Yong Li

    2015-07-01

    Full Text Available This paper proposes an approach to compute an EOH (edge-oriented histogram descriptor with main orientation. EOH has a better matching ability than SIFT (scale-invariant feature transform on multispectral images, but does not assign a main orientation to keypoints. Alternatively, it tends to assign the same main orientation to every keypoint, e.g., zero degrees. This limits EOH to matching keypoints between images of translation misalignment only. Observing this limitation, we propose assigning to keypoints the main orientation that is computed with PIIFD (partial intensity invariant feature descriptor. In the proposed method, SIFT keypoints are detected from images as the extrema of difference of Gaussians, and every keypoint is assigned to the main orientation computed with PIIFD. Then, EOH is computed for every keypoint with respect to its main orientation. In addition, an implementation variant is proposed for fast computation of the EOH descriptor. Experimental results show that the proposed approach performs more robustly than the original EOH on image pairs that have a rotation misalignment.

  7. Modulation of orientation-selective neurons by motion: when additive, when multiplicative?

    Directory of Open Access Journals (Sweden)

    Torsten eLüdge

    2014-06-01

    Full Text Available The recurrent interaction among orientation-selective neurons in the primary visual cortex (V1 is suited to enhance contours in a noisy visual scene. Motion is known to have a strong pop-up effect in perceiving contours, but how motion-sensitive neurons in V1 support contour detection remains vastly elusive. Here we suggest how the various types of motion-sensitive neurons observed in V1 should be wired together in a micro-circuitry to optimally extract contours in the visual scene. Motion-sensitive neurons can be selective about the direction of motion occurring at some spot or respond equally to all directions (pandirectional. We show that, in the light of figure-ground segregation, direction-selective motion neurons should additively modulate the corresponding orientation-selective neurons with preferred orientation orthogonal to the motion direction. In turn, to maximally enhance contours, pandirectional motion neurons should multiplicatively modulate all orientation-selective neurons with co-localized receptive fields. This multiplicative modulation amplifies the local V1-circuitry among co-aligned orientation-selective neurons for detecting elongated contours. We suggest that the additive modulation by direction- specific motion neurons is achieved through synaptic projections to the somatic region, and the multiplicative modulation by pandirectional motion neurons through projections to the apical region of orientation-specific pyramidal neurons. For the purpose of contour detection, the V1- intrinsic integration of motion information is advantageous over a downstream integration as it exploits the recurrent V1-circuitry designed for that task.

  8. Chip-Oriented Fluorimeter Design and Detection System Development for DNA Quantification in Nano-Liter Volumes

    Directory of Open Access Journals (Sweden)

    Da-Sheng Lee

    2009-12-01

    Full Text Available The chip-based polymerase chain reaction (PCR system has been developed in recent years to achieve DNA quantification. Using a microstructure and miniature chip, the volume consumption for a PCR can be reduced to a nano-liter. With high speed cycling and a low reaction volume, the time consumption of one PCR cycle performed on a chip can be reduced. However, most of the presented prototypes employ commercial fluorimeters which are not optimized for fluorescence detection of such a small quantity sample. This limits the performance of DNA quantification, especially low experiment reproducibility. This study discusses the concept of a chip-oriented fluorimeter design. Using the analytical model, the current study analyzes the sensitivity and dynamic range of the fluorimeter to fit the requirements for detecting fluorescence in nano-liter volumes. Through the optimized processes, a real-time PCR on a chip system with only one nano-liter volume test sample is as sensitive as the commercial real-time PCR machine using the sample with twenty micro-liter volumes. The signal to noise (S/N ratio of a chip system for DNA quantification with hepatitis B virus (HBV plasmid samples is 3 dB higher. DNA quantification by the miniature chip shows higher reproducibility compared to the commercial machine with respect to samples of initial concentrations from 103 to 105 copies per reaction.

  9. Aesthetic Judgement of Orientation in Modern Art

    Directory of Open Access Journals (Sweden)

    George Mather

    2012-01-01

    Full Text Available When creating an artwork, the artist makes a decision regarding the orientation at which the work is to be hung based on their aesthetic judgement and the message conveyed by the piece. Is the impact or aesthetic appeal of a work diminished when it is hung at an incorrect orientation? To investigate this question, Experiment 1 asked whether naïve observers can appreciate the correct orientation (as defined by the artist of 40 modern artworks, some of which are entirely abstract. Eighteen participants were shown 40 paintings in a series of trials. Each trial presented all four cardinal orientations on a computer screen, and the participant was asked to select the orientation that was most attractive or meaningful. Results showed that the correct orientation was selected in 48% of trials on average, significantly above the 25% chance level, but well below perfect performance. A second experiment investigated the extent to which the 40 paintings contained recognisable content, which may have mediated orientation judgements. Recognition rates varied from 0% for seven of the paintings to 100% for five paintings. Orientation judgements in Experiment 1 correlated significantly with “meaningful” content judgements in Experiment 2: 42% of the variance in orientation judgements in Experiment 1 was shared with recognition of meaningful content in Experiment 2. For the seven paintings in which no meaningful content at all was detected, 41% of the variance in orientation judgements was shared with variance in a physical measure of image content, Fourier amplitude spectrum slope. For some paintings, orientation judgements were quite consistent, despite a lack of meaningful content. The origin of these orientation judgements remains to be identified.

  10. Waveguide-integrated single- and multi-photon detection at telecom wavelengths using superconducting nanowires

    International Nuclear Information System (INIS)

    Ferrari, Simone; Kahl, Oliver; Kovalyuk, Vadim; Goltsman, Gregory N.; Korneev, Alexander; Pernice, Wolfram H. P.

    2015-01-01

    We investigate single- and multi-photon detection regimes of superconducting nanowire detectors embedded in silicon nitride nanophotonic circuits. At near-infrared wavelengths, simultaneous detection of up to three photons is observed for 120 nm wide nanowires biased far from the critical current, while narrow nanowires below 100 nm provide efficient single photon detection. A theoretical model is proposed to determine the different detection regimes and to calculate the corresponding internal quantum efficiency. The predicted saturation of the internal quantum efficiency in the single photon regime agrees well with plateau behavior observed at high bias currents

  11. Waveguide-integrated single- and multi-photon detection at telecom wavelengths using superconducting nanowires

    Energy Technology Data Exchange (ETDEWEB)

    Ferrari, Simone; Kahl, Oliver [Institute of Nanotechnology, Karlsruhe Institute of Technology, Karlsruhe 76132 (Germany); Kovalyuk, Vadim [Institute of Nanotechnology, Karlsruhe Institute of Technology, Karlsruhe 76132 (Germany); Department of Physics, Moscow State Pedagogical University, Moscow 119992 (Russian Federation); Goltsman, Gregory N. [Department of Physics, Moscow State Pedagogical University, Moscow 119992 (Russian Federation); National Research University Higher School of Economics, 20 Myasnitskaya Ulitsa, Moscow 101000 (Russian Federation); Korneev, Alexander [Department of Physics, Moscow State Pedagogical University, Moscow 119992 (Russian Federation); Moscow Institute of Physics and Technology (State University), Moscow 141700 (Russian Federation); Pernice, Wolfram H. P., E-mail: wolfram.pernice@kit.edu [Institute of Nanotechnology, Karlsruhe Institute of Technology, Karlsruhe 76132 (Germany); Department of Physics, University of Münster, 48149 Münster (Germany)

    2015-04-13

    We investigate single- and multi-photon detection regimes of superconducting nanowire detectors embedded in silicon nitride nanophotonic circuits. At near-infrared wavelengths, simultaneous detection of up to three photons is observed for 120 nm wide nanowires biased far from the critical current, while narrow nanowires below 100 nm provide efficient single photon detection. A theoretical model is proposed to determine the different detection regimes and to calculate the corresponding internal quantum efficiency. The predicted saturation of the internal quantum efficiency in the single photon regime agrees well with plateau behavior observed at high bias currents.

  12. Oriented cluster perforating technology and its application in horizontal wells

    Directory of Open Access Journals (Sweden)

    Huabin Chen

    2016-11-01

    Full Text Available An oriented cluster perforating technology, which integrates both advantages of cluster and oriented perforating, will help solve a series of technical complexities in horizontal well drilling. For realizing its better application in oil and gas development, a series of technologies were developed including perforator self-weight eccentricity, matching of the electronic selective module codes with the surface program control, axial centralized contact signal transmission, and post-perforation intercluster sealing insulation. In this way, the following functions could be realized, such as cable-transmission horizontal well perforator self-weight orientation, dynamic signal transmission, reliable addressing & selective perforation and post-perforation intercluster sealing. The combined perforation and bridge plug or the multi-cluster perforation can be fulfilled in one trip of perforation string. As a result, the horizontal-well oriented cluster perforating technology based on cable conveying was developed. This technology was successfully applied in unconventional gas reservoir exploitation, such as shale gas and coalbed methane, with accurate orientation, reliable selective perforation and satisfactory inter-cluster sealing. The horizontal-well oriented cluster perforating technology benefits the orientation of horizontal well drilling with a definite target and direction, which provides a powerful support for the subsequent reservoir stimulation. It also promotes the fracturing fluid to sweep the principal pay zones to the maximum extent. Moreover, it is conductive to the formation of complex fracture networks in the reservoirs, making quality and efficient development of unconventional gas reservoirs possible.

  13. Link between Work-Related Prosocial Orientation and Professional Capability of Employees: A Preliminary Exploratory Investigation

    Directory of Open Access Journals (Sweden)

    Małgorzata Adamska-Chudzińska

    2015-05-01

    Full Text Available The paper explores the link between work-related prosocial orientation of organizations and professional capabilities of employees suggesting that the prosocial orientation impacts the level of professional capability and proactive engagement. The article applies three main methods: literature studies, in-depth questionnaire surveys and multi-person method of assessment. The applied sub-measures for both leading constructs were formed and collinearity was tested using linear correlation coefficient. In prosocial environments psychological predispositions as essential aspects of personality and determinants of human behaviour, activate and stimulate professional activity. The implementation of a prosocial orientation leads to significant growth in professional capability and can influence employees’ entrepreneurial behaviour. An important aspect of employee proactive behaviour is building an internal policy based on prosocial mechanisms. Effective stimulation of prosocial and proactive attitudes and actions requires the creation of an environment where activities are realized alongside social values and with respect for individual personal determinants of activity. Considerations and findings presented in the paper contribute to the area of determinants of effective and lasting proactive employee development. The use of the multi-person method can be considered valuable in behavioural research in entrepreneurship.

  14. MULTIDIRECTIONAL BUILDING DETECTION IN AERIAL IMAGES WITHOUT SHAPE TEMPLATES

    Directory of Open Access Journals (Sweden)

    A. Manno-Kovacs

    2013-05-01

    Full Text Available The aim of this paper is to exploit orientation information of an urban area for extracting building contours without shape templates. Unlike using shape templates, these given contours describe more variability and reveal the fine details of the building outlines, resulting in a more accurate detection process, which is beneficial for many tasks, like map updating and city planning. According to our assumption, orientation of the closely located buildings is coherent, it is related to the road network, therefore adaptation of this information can lead to more efficient building detection results. The introduced method first extracts feature points for representing the urban area. Orientation information in the feature point neighborhoods is analyzed to define main orientations. Based on orientation information, the urban area is classified into different directional clusters. The edges of the classified building groups are then emphasized with shearlet based edge detection method, which is able to detect edges only in the main directions, resulting in an efficient connectivity map. In the last step, with the fusion of the feature points and connectivity map, building contours are detected with a non-parametric active contour method.

  15. Detection of Multi-Layer and Vertically-Extended Clouds Using A-Train Sensors

    Science.gov (United States)

    Joiner, J.; Vasilkov, A. P.; Bhartia, P. K.; Wind, G.; Platnick, S.; Menzel, W. P.

    2010-01-01

    The detection of mUltiple cloud layers using satellite observations is important for retrieval algorithms as well as climate applications. In this paper, we describe a relatively simple algorithm to detect multiple cloud layers and distinguish them from vertically-extended clouds. The algorithm can be applied to coincident passive sensors that derive both cloud-top pressure from the thermal infrared observations and an estimate of solar photon pathlength from UV, visible, or near-IR measurements. Here, we use data from the A-train afternoon constellation of satellites: cloud-top pressure, cloud optical thickness, the multi-layer flag from the Aqua MODerate-resolution Imaging Spectroradiometer (MODIS) and the optical centroid cloud pressure from the Aura Ozone Monitoring Instrument (OMI). For the first time, we use data from the CloudSat radar to evaluate the results of a multi-layer cloud detection scheme. The cloud classification algorithms applied with different passive sensor configurations compare well with each other as well as with data from CloudSat. We compute monthly mean fractions of pixels containing multi-layer and vertically-extended clouds for January and July 2007 at the OMI spatial resolution (l2kmx24km at nadir) and at the 5kmx5km MODIS resolution used for infrared cloud retrievals. There are seasonal variations in the spatial distribution of the different cloud types. The fraction of cloudy pixels containing distinct multi-layer cloud is a strong function of the pixel size. Globally averaged, these fractions are approximately 20% and 10% for OMI and MODIS, respectively. These fractions may be significantly higher or lower depending upon location. There is a much smaller resolution dependence for fractions of pixels containing vertically-extended clouds (approx.20% for OMI and slightly less for MODIS globally), suggesting larger spatial scales for these clouds. We also find higher fractions of vertically-extended clouds over land as compared with

  16. Detection of License Plate using Sliding Window, Histogram of Oriented Gradient, and Support Vector Machines Method

    Science.gov (United States)

    Astawa, INGA; Gusti Ngurah Bagus Caturbawa, I.; Made Sajayasa, I.; Dwi Suta Atmaja, I. Made Ari

    2018-01-01

    The license plate recognition usually used as part of system such as parking system. License plate detection considered as the most important step in the license plate recognition system. We propose methods that can be used to detect the vehicle plate on mobile phone. In this paper, we used Sliding Window, Histogram of Oriented Gradient (HOG), and Support Vector Machines (SVM) method to license plate detection so it will increase the detection level even though the image is not in a good quality. The image proceed by Sliding Window method in order to find plate position. Feature extraction in every window movement had been done by HOG and SVM method. Good result had shown in this research, which is 96% of accuracy.

  17. Multi-vehicle detection with identity awareness using cascade Adaboost and Adaptive Kalman filter for driver assistant system.

    Directory of Open Access Journals (Sweden)

    Baofeng Wang

    Full Text Available Vision-based vehicle detection is an important issue for advanced driver assistance systems. In this paper, we presented an improved multi-vehicle detection and tracking method using cascade Adaboost and Adaptive Kalman filter(AKF with target identity awareness. A cascade Adaboost classifier using Haar-like features was built for vehicle detection, followed by a more comprehensive verification process which could refine the vehicle hypothesis in terms of both location and dimension. In vehicle tracking, each vehicle was tracked with independent identity by an Adaptive Kalman filter in collaboration with a data association approach. The AKF adaptively adjusted the measurement and process noise covariance through on-line stochastic modelling to compensate the dynamics changes. The data association correctly assigned different detections with tracks using global nearest neighbour(GNN algorithm while considering the local validation. During tracking, a temporal context based track management was proposed to decide whether to initiate, maintain or terminate the tracks of different objects, thus suppressing the sparse false alarms and compensating the temporary detection failures. Finally, the proposed method was tested on various challenging real roads, and the experimental results showed that the vehicle detection performance was greatly improved with higher accuracy and robustness.

  18. Multi-class geospatial object detection based on a position-sensitive balancing framework for high spatial resolution remote sensing imagery

    Science.gov (United States)

    Zhong, Yanfei; Han, Xiaobing; Zhang, Liangpei

    2018-04-01

    Multi-class geospatial object detection from high spatial resolution (HSR) remote sensing imagery is attracting increasing attention in a wide range of object-related civil and engineering applications. However, the distribution of objects in HSR remote sensing imagery is location-variable and complicated, and how to accurately detect the objects in HSR remote sensing imagery is a critical problem. Due to the powerful feature extraction and representation capability of deep learning, the deep learning based region proposal generation and object detection integrated framework has greatly promoted the performance of multi-class geospatial object detection for HSR remote sensing imagery. However, due to the translation caused by the convolution operation in the convolutional neural network (CNN), although the performance of the classification stage is seldom influenced, the localization accuracies of the predicted bounding boxes in the detection stage are easily influenced. The dilemma between translation-invariance in the classification stage and translation-variance in the object detection stage has not been addressed for HSR remote sensing imagery, and causes position accuracy problems for multi-class geospatial object detection with region proposal generation and object detection. In order to further improve the performance of the region proposal generation and object detection integrated framework for HSR remote sensing imagery object detection, a position-sensitive balancing (PSB) framework is proposed in this paper for multi-class geospatial object detection from HSR remote sensing imagery. The proposed PSB framework takes full advantage of the fully convolutional network (FCN), on the basis of a residual network, and adopts the PSB framework to solve the dilemma between translation-invariance in the classification stage and translation-variance in the object detection stage. In addition, a pre-training mechanism is utilized to accelerate the training procedure

  19. Text mining to detect indications of fraud in annual reports worldwide

    NARCIS (Netherlands)

    Fissette, Marcia Valentine Maria

    2017-01-01

    The research described in this thesis examined the contribution of text analysis to detecting indications of fraud in the annual reports of companies worldwide. A total of 1,727 annual reports have been collected, of which 402 are of the years and companies in which fraudulent activities took place,

  20. Feasibility on fiber orientation detection on unidirectional CFRP composite laminates using nondestructive evaluation techniques

    Science.gov (United States)

    Yang, In-Young; Kim, Ji-Hoon; Cha, Cheon-Seok; Lee, Kil-Sung; Hsu, David K.; Im, Kwang-Hee

    2007-07-01

    In particular, CFRP (carbon fiber reinforced plastics) composite materials have found wide applicability because of their inherent design flexibility and improved material properties. CFRP composites were manufactured from uni-direction prepreg sheet in this paper. It is important to assess fiber orientation, material properties and part defect in order to ensure product quality and structural integrity of CFRP because strength and stiffness of composites depend on fiber orientation. It is desirable to perform nondestructive evaluation which is very beneficial. An new method for nondestructively determining the fiber orientation in a composite laminate is presented. A one-sided pitch-catch setup was used in the detection and evaluation of flaws and material anomalies in the unidirectional CFRP composite laminates. Two Rayleigh wave transducers were joined head-to-head and used in the pitch-catch mode on the surface of the composites. The pitch-catch signal was found to be more sensitive than normal incidence backwall echo of longitudinal wave to subtle flaw conditions in the composite. Especially, ultrasonic waves were extensively characterized in the CFRP composite laminates both normal to fiber and along to fiber with using a one-sided direction of Rayleigh wave transducers. Also, one-sided ultrasonic measurement was made with using a Rayleigh wave transducers and a conventional scanner was used in an immersion tank for extracting fiber orientation information from the ultrasonic reflection in the unidirectional laminate. Therefore, it is thought that the proposed method is useful to evaluate integrity of CFRP laminates.

  1. The Fermilab Advanced Computer Program multi-array processor system (ACPMAPS): A site oriented supercomputer for theoretical physics

    International Nuclear Information System (INIS)

    Nash, T.; Areti, H.; Atac, R.

    1988-08-01

    The ACP Multi-Array Processor System (ACPMAPS) is a highly cost effective, local memory parallel computer designed for floating point intensive grid based problems. The processing nodes of the system are single board array processors based on the FORTRAN and C programmable Weitek XL chip set. The nodes are connected by a network of very high bandwidth 16 port crossbar switches. The architecture is designed to achieve the highest possible cost effectiveness while maintaining a high level of programmability. The primary application of the machine at Fermilab will be lattice gauge theory. The hardware is supported by a transparent site oriented software system called CANOPY which shields theorist users from the underlying node structure. 4 refs., 2 figs

  2. MULTI-LEVEL SAMPLING APPROACH FOR CONTINOUS LOSS DETECTION USING ITERATIVE WINDOW AND STATISTICAL MODEL

    OpenAIRE

    Mohd Fo'ad Rohani; Mohd Aizaini Maarof; Ali Selamat; Houssain Kettani

    2010-01-01

    This paper proposes a Multi-Level Sampling (MLS) approach for continuous Loss of Self-Similarity (LoSS) detection using iterative window. The method defines LoSS based on Second Order Self-Similarity (SOSS) statistical model. The Optimization Method (OM) is used to estimate self-similarity parameter since it is fast and more accurate in comparison with other estimation methods known in the literature. Probability of LoSS detection is introduced to measure continuous LoSS detection performance...

  3. Multi-scale Fully Convolutional Network for Face Detection in the Wild

    KAUST Repository

    Bai, Yancheng

    2017-08-24

    Face detection is a classical problem in computer vision. It is still a difficult task due to many nuisances that naturally occur in the wild. In this paper, we propose a multi-scale fully convolutional network for face detection. To reduce computation, the intermediate convolutional feature maps (conv) are shared by every scale model. We up-sample and down-sample the final conv map to approximate K levels of a feature pyramid, leading to a wide range of face scales that can be detected. At each feature pyramid level, a FCN is trained end-to-end to deal with faces in a small range of scale change. Because of the up-sampling, our method can detect very small faces (10×10 pixels). We test our MS-FCN detector on four public face detection datasets, including FDDB, WIDER FACE, AFW and PASCAL FACE. Extensive experiments show that it outperforms state-of-the-art methods. Also, MS-FCN runs at 23 FPS on a GPU for images of size 640×480 with no assumption on the minimum detectable face size.

  4. Network module detection: Affinity search technique with the multi-node topological overlap measure.

    Science.gov (United States)

    Li, Ai; Horvath, Steve

    2009-07-20

    Many clustering procedures only allow the user to input a pairwise dissimilarity or distance measure between objects. We propose a clustering method that can input a multi-point dissimilarity measure d(i1, i2, ..., iP) where the number of points P can be larger than 2. The work is motivated by gene network analysis where clusters correspond to modules of highly interconnected nodes. Here, we define modules as clusters of network nodes with high multi-node topological overlap. The topological overlap measure is a robust measure of interconnectedness which is based on shared network neighbors. In previous work, we have shown that the multi-node topological overlap measure yields biologically meaningful results when used as input of network neighborhood analysis. We adapt network neighborhood analysis for the use of module detection. We propose the Module Affinity Search Technique (MAST), which is a generalized version of the Cluster Affinity Search Technique (CAST). MAST can accommodate a multi-node dissimilarity measure. Clusters grow around user-defined or automatically chosen seeds (e.g. hub nodes). We propose both local and global cluster growth stopping rules. We use several simulations and a gene co-expression network application to argue that the MAST approach leads to biologically meaningful results. We compare MAST with hierarchical clustering and partitioning around medoid clustering. Our flexible module detection method is implemented in the MTOM software which can be downloaded from the following webpage: http://www.genetics.ucla.edu/labs/horvath/MTOM/

  5. Flow Oriented Channel Assignment for Multi-radio Wireless Mesh Networks

    Directory of Open Access Journals (Sweden)

    Niu Zhisheng

    2010-01-01

    Full Text Available We investigate channel assignment for a multichannel wireless mesh network backbone, where each router is equipped with multiple interfaces. Of particular interest is the development of channel assignment heuristics for multiple flows. We present an optimization formulation and then propose two iterative flow oriented heuristics for the conflict-free and interference-aware cases, respectively. To maximize the aggregate useful end-to-end flow rates, both algorithms identify and resolve congestion at instantaneous bottleneck link in each iteration. Then the link rate is optimally allocated among contending flows that share this link by solving a linear programming (LP problem. A thorough performance evaluation is undertaken as a function of the number of channels and interfaces/node and the number of contending flows. The performance of our algorithm is shown to be significantly superior to best known algorithm in its class in multichannel limited radio scenarios.

  6. Secure Distributed Detection under Energy Constraint in IoT-Oriented Sensor Networks.

    Science.gov (United States)

    Zhang, Guomei; Sun, Hao

    2016-12-16

    We study the secure distributed detection problems under energy constraint for IoT-oriented sensor networks. The conventional channel-aware encryption (CAE) is an efficient physical-layer secure distributed detection scheme in light of its energy efficiency, good scalability and robustness over diverse eavesdropping scenarios. However, in the CAE scheme, it remains an open problem of how to optimize the key thresholds for the estimated channel gain, which are used to determine the sensor's reporting action. Moreover, the CAE scheme does not jointly consider the accuracy of local detection results in determining whether to stay dormant for a sensor. To solve these problems, we first analyze the error probability and derive the optimal thresholds in the CAE scheme under a specified energy constraint. These results build a convenient mathematic framework for our further innovative design. Under this framework, we propose a hybrid secure distributed detection scheme. Our proposal can satisfy the energy constraint by keeping some sensors inactive according to the local detection confidence level, which is characterized by likelihood ratio. In the meanwhile, the security is guaranteed through randomly flipping the local decisions forwarded to the fusion center based on the channel amplitude. We further optimize the key parameters of our hybrid scheme, including two local decision thresholds and one channel comparison threshold. Performance evaluation results demonstrate that our hybrid scheme outperforms the CAE under stringent energy constraints, especially in the high signal-to-noise ratio scenario, while the security is still assured.

  7. Localization of Wheeled Mobile Robot Based on Extended Kalman Filtering

    Directory of Open Access Journals (Sweden)

    Li Guangxu

    2015-01-01

    Full Text Available A mobile robot localization method which combines relative positioning with absolute orientation is presented. The code salver and gyroscope are used for relative positioning, and the laser radar is used to detect absolute orientation. In this paper, we established environmental map, multi-sensor information fusion model, sensors and robot motion model. The Extended Kalman Filtering (EKF is adopted as multi-sensor data fusion technology to realize the precise localization of wheeled mobile robot.

  8. Detection of Quinoline in G. boninense-Infected Plants Using Functionalized Multi-Walled Carbon Nanotubes: A Field Study

    Directory of Open Access Journals (Sweden)

    Fowotade Sulayman Akanbi

    2017-07-01

    Full Text Available Carbon nanotubes (CNTs reinforced with gold nanoparticles (AuNPs and chitosan nanoparticles (CTSNPs were anchored on a screen-printed electrode to fabricate a multi-walled structure for the detection of quinoline. The surface morphology of the nanocomposites and the modified electrode was examined by an ultra-high resolution field emission scanning electron microscope (FESEM, and Fourier-transform infrared (FT-IR spectroscopy was used to confirm the presence of specific functional groups on the multi-walled carbon nanotubes MWCNTs. Cyclic voltammetry (CV and linear sweep voltammetry (LSV were used to monitor the layer-by-layer assembly of ultra-thin films of nanocomposites on the surface of the electrode and other electrochemical characterizations. Under optimized conditions, the novel sensor displayed outstanding electrochemical reactivity towards the electro-oxidation of quinoline. The linear range was fixed between 0.0004 and 1.0 μM, with a limit of detection (LOD of 3.75 nM. The fabricated electrode exhibited high stability with excellent sensitivity and selectivity, specifically attributable to the salient characteristics of AuNPs, CTSNPs, and MWCNTs and the synergistic inter-relationship between them. The newly developed electrode was tested in the field. The Ipa increased with an increase in the amount of quinoline solution added, and the peak potential deviated minimally, depicting the real capability of the newly fabricated electrode.

  9. A SIMULTANEOUS MULTI-PROBE DETECTION LABEL-FREE OPTICAL-RESOLUTION PHOTOACOUSTIC MICROSCOPY TECHNIQUE BASED ON MICROCAVITY TRANSDUCER

    Directory of Open Access Journals (Sweden)

    YONGBO WU

    2013-07-01

    Full Text Available We demonstrate the feasibility of simultaneous multi-probe detection for an optical-resolution photoacoustic microscopy (OR-PAM system. OR-PAM has elicited the attention of biomedical imaging researchers because of its optical absorption contrast and high spatial resolution with great imaging depth. OR-PAM allows label-free and noninvasive imaging by maximizing the optical absorption of endogenous biomolecules. However, given the inadequate absorption of some biomolecules, detection sensitivity at the same incident intensity requires improvement. In this study, a modulated continuous wave with power density less than 3 mW/cm2 (1/4 of the ANSI safety limit excited the weak photoacoustic (PA signals of biological cells. A microcavity transducer is developed based on the bulk modulus of gas five orders of magnitude lower than that of solid; air pressure variation is inversely proportional to cavity volume at the same temperature increase. Considering that a PA wave expands in various directions, detecting PA signals from different positions and adding them together can increase detection sensitivity and signal-to-noise ratio. Therefore, we employ four detectors to acquire tiny PA signals simultaneously. Experimental results show that the developed OR-PAM system allows the label-free imaging of cells with weak optical absorption.

  10. Detecting Hotspot Information Using Multi-Attribute Based Topic Model

    Science.gov (United States)

    Wang, Jing; Li, Li; Tan, Feng; Zhu, Ying; Feng, Weisi

    2015-01-01

    Microblogging as a kind of social network has become more and more important in our daily lives. Enormous amounts of information are produced and shared on a daily basis. Detecting hot topics in the mountains of information can help people get to the essential information more quickly. However, due to short and sparse features, a large number of meaningless tweets and other characteristics of microblogs, traditional topic detection methods are often ineffective in detecting hot topics. In this paper, we propose a new topic model named multi-attribute latent dirichlet allocation (MA-LDA), in which the time and hashtag attributes of microblogs are incorporated into LDA model. By introducing time attribute, MA-LDA model can decide whether a word should appear in hot topics or not. Meanwhile, compared with the traditional LDA model, applying hashtag attribute in MA-LDA model gives the core words an artificially high ranking in results meaning the expressiveness of outcomes can be improved. Empirical evaluations on real data sets demonstrate that our method is able to detect hot topics more accurately and efficiently compared with several baselines. Our method provides strong evidence of the importance of the temporal factor in extracting hot topics. PMID:26496635

  11. Text Detection in Natural Scene Images by Stroke Gabor Words.

    Science.gov (United States)

    Yi, Chucai; Tian, Yingli

    2011-01-01

    In this paper, we propose a novel algorithm, based on stroke components and descriptive Gabor filters, to detect text regions in natural scene images. Text characters and strings are constructed by stroke components as basic units. Gabor filters are used to describe and analyze the stroke components in text characters or strings. We define a suitability measurement to analyze the confidence of Gabor filters in describing stroke component and the suitability of Gabor filters on an image window. From the training set, we compute a set of Gabor filters that can describe principle stroke components of text by their parameters. Then a K -means algorithm is applied to cluster the descriptive Gabor filters. The clustering centers are defined as Stroke Gabor Words (SGWs) to provide a universal description of stroke components. By suitability evaluation on positive and negative training samples respectively, each SGW generates a pair of characteristic distributions of suitability measurements. On a testing natural scene image, heuristic layout analysis is applied first to extract candidate image windows. Then we compute the principle SGWs for each image window to describe its principle stroke components. Characteristic distributions generated by principle SGWs are used to classify text or nontext windows. Experimental results on benchmark datasets demonstrate that our algorithm can handle complex backgrounds and variant text patterns (font, color, scale, etc.).

  12. How does the closure of interorganizational relationships affect entrepreneurial orientation?

    Directory of Open Access Journals (Sweden)

    María José Ruiz-Ortega

    2017-07-01

    Full Text Available This study delves in the controversy about the nature and the sign of the effect of interorganizational relationships on entrepreneurial orientation. The paper analyses the effects of networks of interorganizational relationships at firm level. Specifically, we study the influence of closure of interorganizational relationships in entrepreneurial orientation and the mediating role of dynamic capabilities. The empirical analysis was developed on a sample of 292 Spanish agri-food firms. We detect a positive mediating effect of the closure of interorganizational relationships, mainly cooperative relationships, on entrepreneurial orientation through dynamic capabilities. It highlights the emergence of a suppression effect uncovering the dark side of closed interorganizational relationships in several dimensions of entrepreneurial orientation – proactiveness, autonomy and risk-taking –. This paper contributes to link three theoretical approaches – social capital, entrepreneurship and dynamic capabilities – to probe further into the implications of interorganizational relationships.

  13. A Depth Video-based Human Detection and Activity Recognition using Multi-features and Embedded Hidden Markov Models for Health Care Monitoring Systems

    Directory of Open Access Journals (Sweden)

    Ahmad Jalal

    2017-08-01

    Full Text Available Increase in number of elderly people who are living independently needs especial care in the form of healthcare monitoring systems. Recent advancements in depth video technologies have made human activity recognition (HAR realizable for elderly healthcare applications. In this paper, a depth video-based novel method for HAR is presented using robust multi-features and embedded Hidden Markov Models (HMMs to recognize daily life activities of elderly people living alone in indoor environment such as smart homes. In the proposed HAR framework, initially, depth maps are analyzed by temporal motion identification method to segment human silhouettes from noisy background and compute depth silhouette area for each activity to track human movements in a scene. Several representative features, including invariant, multi-view differentiation and spatiotemporal body joints features were fused together to explore gradient orientation change, intensity differentiation, temporal variation and local motion of specific body parts. Then, these features are processed by the dynamics of their respective class and learned, modeled, trained and recognized with specific embedded HMM having active feature values. Furthermore, we construct a new online human activity dataset by a depth sensor to evaluate the proposed features. Our experiments on three depth datasets demonstrated that the proposed multi-features are efficient and robust over the state of the art features for human action and activity recognition.

  14. Evaluation of outbreak detection performance using multi-stream syndromic surveillance for influenza-like illness in rural Hubei Province, China: a temporal simulation model based on healthcare-seeking behaviors.

    Directory of Open Access Journals (Sweden)

    Yunzhou Fan

    Full Text Available BACKGROUND: Syndromic surveillance promotes the early detection of diseases outbreaks. Although syndromic surveillance has increased in developing countries, performance on outbreak detection, particularly in cases of multi-stream surveillance, has scarcely been evaluated in rural areas. OBJECTIVE: This study introduces a temporal simulation model based on healthcare-seeking behaviors to evaluate the performance of multi-stream syndromic surveillance for influenza-like illness. METHODS: Data were obtained in six towns of rural Hubei Province, China, from April 2012 to June 2013. A Susceptible-Exposed-Infectious-Recovered model generated 27 scenarios of simulated influenza A (H1N1 outbreaks, which were converted into corresponding simulated syndromic datasets through the healthcare-behaviors model. We then superimposed converted syndromic datasets onto the baselines obtained to create the testing datasets. Outbreak performance of single-stream surveillance of clinic visit, frequency of over the counter drug purchases, school absenteeism, and multi-stream surveillance of their combinations were evaluated using receiver operating characteristic curves and activity monitoring operation curves. RESULTS: In the six towns examined, clinic visit surveillance and school absenteeism surveillance exhibited superior performances of outbreak detection than over the counter drug purchase frequency surveillance; the performance of multi-stream surveillance was preferable to signal-stream surveillance, particularly at low specificity (Sp <90%. CONCLUSIONS: The temporal simulation model based on healthcare-seeking behaviors offers an accessible method for evaluating the performance of multi-stream surveillance.

  15. Service-oriented workflow to efficiently and automatically fulfill products in a highly individualized web and mobile environment

    Science.gov (United States)

    Qiao, Mu

    2015-03-01

    Service Oriented Architecture1 (SOA) is widely used in building flexible and scalable web sites and services. In most of the web or mobile photo book and gifting business space, the products ordered are highly variable without a standard template that one can substitute texts or images from similar to that of commercial variable data printing. In this paper, the author describes a SOA workflow in a multi-sites, multi-product lines fulfillment system where three major challenges are addressed: utilization of hardware and equipment, highly automation with fault recovery, and highly scalable and flexible with order volume fluctuation.

  16. Two-motor single-inverter field-oriented induction machine drive ...

    Indian Academy of Sciences (India)

    Multi-machine, single-inverter induction motor drives are attractive in situations in which all machines are of similar ratings, and operate at approximately the same load torques. The advantages include small size compared to multi-inverter system, lower weight and overall cost. However, field oriented control of such drives ...

  17. Computerized detection of breast lesions in multi-centre and multi-instrument DCE-MR data using 3D principal component maps and template matching

    Science.gov (United States)

    Ertas, Gokhan; Doran, Simon; Leach, Martin O.

    2011-12-01

    In this study, we introduce a novel, robust and accurate computerized algorithm based on volumetric principal component maps and template matching that facilitates lesion detection on dynamic contrast-enhanced MR. The study dataset comprises 24 204 contrast-enhanced breast MR images corresponding to 4034 axial slices from 47 women in the UK multi-centre study of MRI screening for breast cancer and categorized as high risk. The scans analysed here were performed on six different models of scanner from three commercial vendors, sited in 13 clinics around the UK. 1952 slices from this dataset, containing 15 benign and 13 malignant lesions, were used for training. The remaining 2082 slices, with 14 benign and 12 malignant lesions, were used for test purposes. To prevent false positives being detected from other tissues and regions of the body, breast volumes are segmented from pre-contrast images using a fast semi-automated algorithm. Principal component analysis is applied to the centred intensity vectors formed from the dynamic contrast-enhanced T1-weighted images of the segmented breasts, followed by automatic thresholding to eliminate fatty tissues and slowly enhancing normal parenchyma and a convolution and filtering process to minimize artefacts from moderately enhanced normal parenchyma and blood vessels. Finally, suspicious lesions are identified through a volumetric sixfold neighbourhood connectivity search and calculation of two morphological features: volume and volumetric eccentricity, to exclude highly enhanced blood vessels, nipples and normal parenchyma and to localize lesions. This provides satisfactory lesion localization. For a detection sensitivity of 100%, the overall false-positive detection rate of the system is 1.02/lesion, 1.17/case and 0.08/slice, comparing favourably with previous studies. This approach may facilitate detection of lesions in multi-centre and multi-instrument dynamic contrast-enhanced breast MR data.

  18. Effects of multi-state links in network community detection

    International Nuclear Information System (INIS)

    Rocco, Claudio M.; Moronta, José; Ramirez-Marquez, José E.; Barker, Kash

    2017-01-01

    A community is defined as a group of nodes of a network that are densely interconnected with each other but only sparsely connected with the rest of the network. The set of communities (i.e., the network partition) and their inter-community links could be derived using special algorithms account for the topology of the network and, in certain cases, the possible weights associated to the links. In general, the set of weights represents some characteristic as capacity, flow and reliability, among others. The effects of considering weights could be translated to obtain a different partition. In many real situations, particularly when modeling infrastructure systems, networks must be modeled as multi-state networks (e.g., electric power networks). In such networks, each link is characterized by a vector of known random capacities (i.e., the weight on each link could vary according to a known probability distribution). In this paper a simple Monte Carlo approach is proposed to evaluate the effects of multi-state links on community detection as well as on the performance of the network. The approach is illustrated with the topology of an electric power system. - Highlights: • Identify network communities when considering multi-state links. • Identified how effects of considering weights translate to different partition. • Identified importance of Inter-Community Links and changes with respect to community. • Preamble to performing a resilience assessment able to mimic the evolution of the state of each community.

  19. Detecting coordinated regulation of multi-protein complexes using logic analysis of gene expression

    Directory of Open Access Journals (Sweden)

    Yeates Todd O

    2009-12-01

    Full Text Available Abstract Background Many of the functional units in cells are multi-protein complexes such as RNA polymerase, the ribosome, and the proteasome. For such units to work together, one might expect a high level of regulation to enable co-appearance or repression of sets of complexes at the required time. However, this type of coordinated regulation between whole complexes is difficult to detect by existing methods for analyzing mRNA co-expression. We propose a new methodology that is able to detect such higher order relationships. Results We detect coordinated regulation of multiple protein complexes using logic analysis of gene expression data. Specifically, we identify gene triplets composed of genes whose expression profiles are found to be related by various types of logic functions. In order to focus on complexes, we associate the members of a gene triplet with the distinct protein complexes to which they belong. In this way, we identify complexes related by specific kinds of regulatory relationships. For example, we may find that the transcription of complex C is increased only if the transcription of both complex A AND complex B is repressed. We identify hundreds of examples of coordinated regulation among complexes under various stress conditions. Many of these examples involve the ribosome. Some of our examples have been previously identified in the literature, while others are novel. One notable example is the relationship between the transcription of the ribosome, RNA polymerase and mannosyltransferase II, which is involved in N-linked glycan processing in the Golgi. Conclusions The analysis proposed here focuses on relationships among triplets of genes that are not evident when genes are examined in a pairwise fashion as in typical clustering methods. By grouping gene triplets, we are able to decipher coordinated regulation among sets of three complexes. Moreover, using all triplets that involve coordinated regulation with the ribosome

  20. 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.

  1. Performance comparison of multi-detector detection statistics in targeted compact binary coalescence GW search

    OpenAIRE

    Haris, K; Pai, Archana

    2016-01-01

    Global network of advanced Interferometric gravitational wave (GW) detectors are expected to be on-line soon. Coherent observation of GW from a distant compact binary coalescence (CBC) with a network of interferometers located in different continents give crucial information about the source such as source location and polarization information. In this paper we compare different multi-detector network detection statistics for CBC search. In maximum likelihood ratio (MLR) based detection appro...

  2. Rapid islanding detection using multi-level inverter for grid-interactive PV system

    International Nuclear Information System (INIS)

    Tsang, K.M.; Chan, W.L.

    2014-01-01

    Graphical abstract: - Highlights: • Novel reference signal is used to form an islanding detection scheme for PV system. • Supply fixed magnitude sinusoidal signal even if utility grid is disconnected. • Seamless transfer between grid-connected and stand-alone modes is possible. - Abstract: A novel reference signal generator is combined with a multi-level inverter to form a rapid islanding detection scheme for grid-interactive PV system. The reference signal generator can easily be synchronized with the utility grid signal and produced a fixed magnitude and very low total harmonic distortion (THD) sinusoidal signal which is in phase with the utility grid signal. Unlike conventional phase-locked loop (PLL) circuitry, the reference signal generator can also provide a fixed magnitude sinusoidal signal even if the utility grid is disconnected and automatically re-synchronous with the grid rapidly. Consequently, seamless transfer between grid-connected and stand-alone modes could easily be achieved if anti-islanding protection is not required. If a saturation element is applied to the raw reference signal followed by the synthesis of the truncated signal using a multi-level inverter, the distinct flat-top feature of the synthesized signal can quickly and easily be identified if the network is in islanding mode at the point of common coupling. Experimental results are included to demonstrate the effectiveness of the proposed detection scheme

  3. Effect of Multi-condition Training and Speech Enhancement Methods on Spoofing Detection

    DEFF Research Database (Denmark)

    Yu, Hong; Sarkar, Achintya Kumar; Thomsen, Dennis Alexander Lehmann

    2016-01-01

    enhancement methods on a state of-the-art spoofing detection system based on the dynamic linear frequency cepstral coefficients (LFCC) feature and a Gaussian mixture model maximum-likelihood (GMM-ML) classifier. In the experiment part we consider three additive noise types, Cantine, Babble and white Gaussian......Many researchers have demonstrated the good performance of spoofing detection systems under clean training and testing conditions. However, it is well known that the performance of speaker and speech recognition systems significantly degrades in noisy conditions. Therefore, it is of great interest...... to investigate the effect of noise on the performance of spoofing detection systems. In this paper, we investigate a multi-conditional training method where spoofing detection models are trained with a mix of clean and noisy data. In addition, we study the effect of different noise types as well as speech...

  4. Multi-emotion detection in user-generated reviews

    NARCIS (Netherlands)

    Buitinck, L.; van Amerongen, J.; Tan, E.; de Rijke, M.; Hanbury, A.; Kazai, G.; Rauber, A.; Fuhr, N.

    2015-01-01

    Expressions of emotion abound in user-generated content, whether it be in blogs, reviews, or on social media. Much work has been devoted to detecting and classifying these emotions, but little of it has acknowledged the fact that emotionally charged text may express multiple emotions at the same

  5. Health-related hot topic detection in online communities using text clustering.

    Directory of Open Access Journals (Sweden)

    Yingjie Lu

    Full Text Available Recently, health-related social media services, especially online health communities, have rapidly emerged. Patients with various health conditions participate in online health communities to share their experiences and exchange healthcare knowledge. Exploring hot topics in online health communities helps us better understand patients' needs and interest in health-related knowledge. However, the statistical topic analysis employed in previous studies is becoming impractical for processing the rapidly increasing amount of online data. Automatic topic detection based on document clustering is an alternative approach for extracting health-related hot topics in online communities. In addition to the keyword-based features used in traditional text clustering, we integrate medical domain-specific features to represent the messages posted in online health communities. Three disease discussion boards, including boards devoted to lung cancer, breast cancer and diabetes, from an online health community are used to test the effectiveness of topic detection. Experiment results demonstrate that health-related hot topics primarily include symptoms, examinations, drugs, procedures and complications. Further analysis reveals that there also exist some significant differences among the hot topics discussed on different types of disease discussion boards.

  6. Entrepreneurial Orientation and Business Internationalisation Process: The Theoretical Foundations of International Entrepreneurship

    Directory of Open Access Journals (Sweden)

    Krzysztof Wach

    2015-06-01

    Full Text Available The main goal of the article is to discuss and elaborate on the basics of international entrepreneurial orientation (IEO, its fundamentals and principles. The paper reviews these three important terms by trying to link them and suggests a holistic framework. The article is of descriptive character, thus it is based on literature review and its constructive critics. The article is an attempted synthesis of the concept of international entrepreneurial orientation. It focuses on IEO as the implementation of one of the most important research theme in the theory of entrepreneurship, which is entrepreneurial orientation (EO into the studies of international entrepreneurship (IE. Findings: Firstly, international entrepreneurial process was discussed from the international entrepreneurship perspective. Secondly, the paper introduces the conceptualisation of entrepreneurial orientation from both three- and multidimensional perspectives. Thirdly, IEO is conceptualised and operationalised from the perspective of entrepreneurial internationalisation of firms. Implications & Recommendations: IEO is a multi-dimensional concept. IEO can be considered both an individual and firm-level construct. IEO enables business to identify and exploit internationalisation opportunities. IEO reflects the firms overall proactiveness and aggressiveness in its pursuit of international markets.

  7. BRIDGE CRACK DETECTION USING MULTI-ROTARY UAV AND OBJECT-BASE IMAGE ANALYSIS

    Directory of Open Access Journals (Sweden)

    J. Y. Rau

    2017-08-01

    Full Text Available Bridge is an important infrastructure for human life. Thus, the bridge safety monitoring and maintaining is an important issue to the government. Conventionally, bridge inspection were conducted by human in-situ visual examination. This procedure sometimes require under bridge inspection vehicle or climbing under the bridge personally. Thus, its cost and risk is high as well as labor intensive and time consuming. Particularly, its documentation procedure is subjective without 3D spatial information. In order cope with these challenges, this paper propose the use of a multi-rotary UAV that equipped with a SONY A7r2 high resolution digital camera, 50 mm fixed focus length lens, 135 degrees up-down rotating gimbal. The target bridge contains three spans with a total of 60 meters long, 20 meters width and 8 meters height above the water level. In the end, we took about 10,000 images, but some of them were acquired by hand held method taken on the ground using a pole with 2–8 meters long. Those images were processed by Agisoft PhotoscanPro to obtain exterior and interior orientation parameters. A local coordinate system was defined by using 12 ground control points measured by a total station. After triangulation and camera self-calibration, the RMS of control points is less than 3 cm. A 3D CAD model that describe the bridge surface geometry was manually measured by PhotoscanPro. They were composed of planar polygons and will be used for searching related UAV images. Additionally, a photorealistic 3D model can be produced for 3D visualization. In order to detect cracks on the bridge surface, we utilize object-based image analysis (OBIA technique to segment the image into objects. Later, we derive several object features, such as density, area/bounding box ratio, length/width ratio, length, etc. Then, we can setup a classification rule set to distinguish cracks. Further, we apply semi-global-matching (SGM to obtain 3D crack information and based

  8. Molecular approaches for detection of the multi-drug resistant tuberculosis (MDR-TB in Bangladesh.

    Directory of Open Access Journals (Sweden)

    Tafsina Haque Aurin

    Full Text Available The principal obstacles in the treatment of tuberculosis (TB are delayed and inaccurate diagnosis which often leads to the onset of the drug resistant TB cases. To avail the appropriate treatment of the patients and to hinder the transmission of drug-resistant TB, accurate and rapid detection of resistant isolates is critical. Present study was designed to demonstrate the efficacy of molecular techniques inclusive of line probe assay (LPA and GeneXpert MTB/RIF methods for the detection of multi-drug resistant (MDR TB. Sputum samples from 300 different categories of treated and new TB cases were tested for the detection of possible mutation in the resistance specific genes (rpoB, inhA and katG through Genotype MTBDRplus assay or LPA and GeneXpert MTB/RIF tests. Culture based conventional drug susceptibility test (DST was also carried out to measure the efficacy of the molecular methods employed. Among 300 samples, 191 (63.7% and 193 (64.3% cases were found to be resistant against rifampicin in LPA and GeneXpert methods, respectively; while 189 (63% cases of rifampicin resistance were detected by conventional DST methods. On the other hand, 196 (65.3% and 191 (63.7% isolates showed isoniazid resistance as detected by LPA and conventional drug susceptibility test (DST, respectively. Among the drug resistant isolates (collectively 198 in LPA and 193 in conventional DST, 189 (95.6% and 187 (96.9% were considered to be MDR as examined by LPA and conventional DST, respectively. Category-II and -IV patients encountered higher frequency of drug resistance compared to those from category-I and new cases. Considering the higher sensitivity, specificity and accuracy along with the required time to results significantly shorter, our study supports the adoption of LPA and GeneXpert assay as efficient tools in detecting drug resistant TB in Bangladesh.

  9. Multi-Scale Peak and Trough Detection Optimised for Periodic and Quasi-Periodic Neuroscience Data.

    Science.gov (United States)

    Bishop, Steven M; Ercole, Ari

    2018-01-01

    The reliable detection of peaks and troughs in physiological signals is essential to many investigative techniques in medicine and computational biology. Analysis of the intracranial pressure (ICP) waveform is a particular challenge due to multi-scale features, a changing morphology over time and signal-to-noise limitations. Here we present an efficient peak and trough detection algorithm that extends the scalogram approach of Scholkmann et al., and results in greatly improved algorithm runtime performance. Our improved algorithm (modified Scholkmann) was developed and analysed in MATLAB R2015b. Synthesised waveforms (periodic, quasi-periodic and chirp sinusoids) were degraded with white Gaussian noise to achieve signal-to-noise ratios down to 5 dB and were used to compare the performance of the original Scholkmann and modified Scholkmann algorithms. The modified Scholkmann algorithm has false-positive (0%) and false-negative (0%) detection rates identical to the original Scholkmann when applied to our test suite. Actual compute time for a 200-run Monte Carlo simulation over a multicomponent noisy test signal was 40.96 ± 0.020 s (mean ± 95%CI) for the original Scholkmann and 1.81 ± 0.003 s (mean ± 95%CI) for the modified Scholkmann, demonstrating the expected improvement in runtime complexity from [Formula: see text] to [Formula: see text]. The accurate interpretation of waveform data to identify peaks and troughs is crucial in signal parameterisation, feature extraction and waveform identification tasks. Modification of a standard scalogram technique has produced a robust algorithm with linear computational complexity that is particularly suited to the challenges presented by large, noisy physiological datasets. The algorithm is optimised through a single parameter and can identify sub-waveform features with minimal additional overhead, and is easily adapted to run in real time on commodity hardware.

  10. Detection of Abnormal Events via Optical Flow Feature Analysis

    Directory of Open Access Journals (Sweden)

    Tian Wang

    2015-03-01

    Full Text Available In this paper, a novel algorithm is proposed to detect abnormal events in video streams. The algorithm is based on the histogram of the optical flow orientation descriptor and the classification method. The details of the histogram of the optical flow orientation descriptor are illustrated for describing movement information of the global video frame or foreground frame. By combining one-class support vector machine and kernel principal component analysis methods, the abnormal events in the current frame can be detected after a learning period characterizing normal behaviors. The difference abnormal detection results are analyzed and explained. The proposed detection method is tested on benchmark datasets, then the experimental results show the effectiveness of the algorithm.

  11. Improved anomaly detection using multi-scale PLS and generalized likelihood ratio test

    KAUST Repository

    Madakyaru, Muddu

    2017-02-16

    Process monitoring has a central role in the process industry to enhance productivity, efficiency, and safety, and to avoid expensive maintenance. In this paper, a statistical approach that exploit the advantages of multiscale PLS models (MSPLS) and those of a generalized likelihood ratio (GLR) test to better detect anomalies is proposed. Specifically, to consider the multivariate and multi-scale nature of process dynamics, a MSPLS algorithm combining PLS and wavelet analysis is used as modeling framework. Then, GLR hypothesis testing is applied using the uncorrelated residuals obtained from MSPLS model to improve the anomaly detection abilities of these latent variable based fault detection methods even further. Applications to a simulated distillation column data are used to evaluate the proposed MSPLS-GLR algorithm.

  12. Improved anomaly detection using multi-scale PLS and generalized likelihood ratio test

    KAUST Repository

    Madakyaru, Muddu; Harrou, Fouzi; Sun, Ying

    2017-01-01

    Process monitoring has a central role in the process industry to enhance productivity, efficiency, and safety, and to avoid expensive maintenance. In this paper, a statistical approach that exploit the advantages of multiscale PLS models (MSPLS) and those of a generalized likelihood ratio (GLR) test to better detect anomalies is proposed. Specifically, to consider the multivariate and multi-scale nature of process dynamics, a MSPLS algorithm combining PLS and wavelet analysis is used as modeling framework. Then, GLR hypothesis testing is applied using the uncorrelated residuals obtained from MSPLS model to improve the anomaly detection abilities of these latent variable based fault detection methods even further. Applications to a simulated distillation column data are used to evaluate the proposed MSPLS-GLR algorithm.

  13. Damping Oriented Design of Thin-Walled Mechanical Components by Means of Multi-Layer Coating Technology

    Directory of Open Access Journals (Sweden)

    Giuseppe Catania

    2018-02-01

    Full Text Available The damping behaviour of multi-layer composite mechanical components, shown by recent research and application papers, is analyzed. A local dissipation mechanism, acting at the interface between any two different layers of the composite component, is taken into account, and a beam model, to be used for validating the known experimental results, is proposed. Multi-layer prismatic beams, consisting of a metal substrate and of some thin coated layers exhibiting variable stiffness and adherence properties, are considered in order to make it possible to study and validate this assumption. A dynamical model, based on a simple beam geometry but taking into account the previously introduced local dissipation mechanism and distributed visco-elastic constraints, is proposed. Some different application examples of specific multi-layer beams are considered, and some numerical examples concerning the beam free and forced response are described. The influence of the multilayer system parameters on the damping behaviour of the free and forced response of the composite beam is investigated by means of the definition of some damping estimators. Some effective multi-coating configurations, giving a relevant increase of the damping estimators of the coated structure with respect to the same uncoated structure, are obtained from the model simulation, and the results are critically discussed.

  14. Multi-component and multi-array TEM detection in karst tunnels

    International Nuclear Information System (INIS)

    Sun, Huaifeng; Li, Shucai; Su, Maoxin; Xue, Yiguo; Li, Xiu; Qi, Zhipeng

    2012-01-01

    Emerging applications of transient electromagnetic methods (TEM) in tunnelling require higher resolution on the distributions and shapes of low resistivity bodies, such as karst water and karst pipes, using multi-component and multi-array receivers. However, there are no apparent resistivity definitions for both vertical and horizontal components with offsets inside the loop. Although the raw field can show the differences of the earth electric structure, it is not straightforward. Apparent resistivity is very convenient and easy for engineers. We have developed a method for multi-component and multi-array TEM which can be applied in tunnelling and defined the expressions of apparent resistivity. This method takes advantage of the difference in resolution among components. A homogeneous half-space model and four typical three-layered models are used to test the effectiveness of the new definition. A field case history is carried out and analysed to demonstrate the viability of this technique. The results suggest that it is feasible to use the technique in tunnelling, especially for identifying the spatial distribution of karst water and karst pipes. (paper)

  15. A comparison study on algorithms of detecting long forms for short forms in biomedical text

    Directory of Open Access Journals (Sweden)

    Wu Cathy H

    2007-11-01

    Full Text Available Abstract Motivation With more and more research dedicated to literature mining in the biomedical domain, more and more systems are available for people to choose from when building literature mining applications. In this study, we focus on one specific kind of literature mining task, i.e., detecting definitions of acronyms, abbreviations, and symbols in biomedical text. We denote acronyms, abbreviations, and symbols as short forms (SFs and their corresponding definitions as long forms (LFs. The study was designed to answer the following questions; i how well a system performs in detecting LFs from novel text, ii what the coverage is for various terminological knowledge bases in including SFs as synonyms of their LFs, and iii how to combine results from various SF knowledge bases. Method We evaluated the following three publicly available detection systems in detecting LFs for SFs: i a handcrafted pattern/rule based system by Ao and Takagi, ALICE, ii a machine learning system by Chang et al., and iii a simple alignment-based program by Schwartz and Hearst. In addition, we investigated the conceptual coverage of two terminological knowledge bases: i the UMLS (the Unified Medical Language System, and ii the BioThesaurus (a thesaurus of names for all UniProt protein records. We also implemented a web interface that provides a virtual integration of various SF knowledge bases. Results We found that detection systems agree with each other on most cases, and the existing terminological knowledge bases have a good coverage of synonymous relationship for frequently defined LFs. The web interface allows people to detect SF definitions from text and to search several SF knowledge bases. Availability The web site is http://gauss.dbb.georgetown.edu/liblab/SFThesaurus.

  16. Detection of Text Lines of Handwritten Arabic Manuscripts using Markov Decision Processes

    Directory of Open Access Journals (Sweden)

    Youssef Boulid

    2016-09-01

    Full Text Available In a character recognition systems, the segmentation phase is critical since the accuracy of the recognition depend strongly on it. In this paper we present an approach based on Markov Decision Processes to extract text lines from binary images of Arabic handwritten documents. The proposed approach detects the connected components belonging to the same line by making use of knowledge about features and arrangement of those components. The initial results show that the system is promising for extracting Arabic handwritten lines.

  17. Detecting New Words from Chinese Text Using Latent Semi-CRF Models

    Science.gov (United States)

    Sun, Xiao; Huang, Degen; Ren, Fuji

    Chinese new words and their part-of-speech (POS) are particularly problematic in Chinese natural language processing. With the fast development of internet and information technology, it is impossible to get a complete system dictionary for Chinese natural language processing, as new words out of the basic system dictionary are always being created. A latent semi-CRF model, which combines the strengths of LDCRF (Latent-Dynamic Conditional Random Field) and semi-CRF, is proposed to detect the new words together with their POS synchronously regardless of the types of the new words from the Chinese text without being pre-segmented. Unlike the original semi-CRF, the LDCRF is applied to generate the candidate entities for training and testing the latent semi-CRF, which accelerates the training speed and decreases the computation cost. The complexity of the latent semi-CRF could be further adjusted by tuning the number of hidden variables in LDCRF and the number of the candidate entities from the Nbest outputs of the LDCRF. A new-words-generating framework is proposed for model training and testing, under which the definitions and distributions of the new words conform to the ones existing in real text. Specific features called “Global Fragment Information” for new word detection and POS tagging are adopted in the model training and testing. The experimental results show that the proposed method is capable of detecting even low frequency new words together with their POS tags. The proposed model is found to be performing competitively with the state-of-the-art models presented.

  18. Object-oriented Method of Hierarchical Urban Building Extraction from High-resolution Remote-Sensing Imagery

    Directory of Open Access Journals (Sweden)

    TAO Chao

    2016-02-01

    Full Text Available An automatic urban building extraction method for high-resolution remote-sensing imagery,which combines building segmentation based on neighbor total variations with object-oriented analysis,is presented in this paper. Aimed at different extraction complexity from various buildings in the segmented image,a hierarchical building extraction strategy with multi-feature fusion is adopted. Firstly,we extract some rectangle buildings which remain intact after segmentation through shape analysis. Secondly,in order to ensure each candidate building target to be independent,multidirectional morphological road-filtering algorithm is designed which can separate buildings from the neighboring roads with similar spectrum. Finally,we take the extracted buildings and the excluded non-buildings as samples to establish probability model respectively,and Bayesian discriminating classifier is used for making judgment of the other candidate building objects to get the ultimate extraction result. The experimental results have shown that the approach is able to detect buildings with different structure and spectral features in the same image. The results of performance evaluation also support the robustness and precision of the approach developed.

  19. Intrusion detection on oil pipeline right of way using monogenic signal representation

    Science.gov (United States)

    Nair, Binu M.; Santhaseelan, Varun; Cui, Chen; Asari, Vijayan K.

    2013-05-01

    We present an object detection algorithm to automatically detect and identify possible intrusions such as construction vehicles and equipment on the regions designated as the pipeline right-of-way (ROW) from high resolution aerial imagery. The pipeline industry has buried millions of miles of oil pipelines throughout the country and these regions are under constant threat of unauthorized construction activities. We propose a multi-stage framework which uses a pyramidal template matching scheme in the local phase domain by taking a single high resolution training image to classify a construction vehicle. The proposed detection algorithm makes use of the monogenic signal representation to extract the local phase information. Computing the monogenic signal from a two dimensional object region enables us to separate out the local phase information (structural details) from the local energy (contrast) thereby achieving illumination invariance. The first stage involves the local phase based template matching using only a single high resolution training image in a local region at multiple scales. Then, using the local phase histogram matching, the orientation of the detected region is determined and a voting scheme gives a certain weightage to the resulting clusters. The final stage involves the selection of clusters based on the number of votes attained and using the histogram of oriented phase feature descriptor, the object is located at the correct orientation and scale. The algorithm is successfully tested on four different datasets containing imagery with varying image resolution and object orientation.

  20. EQUIP Healthcare: An overview of a multi-component intervention to enhance equity-oriented care in primary health care settings.

    Science.gov (United States)

    Browne, Annette J; Varcoe, Colleen; Ford-Gilboe, Marilyn; Wathen, C Nadine

    2015-12-14

    The primary health care (PHC) sector is increasingly relevant as a site for population health interventions, particularly in relation to marginalized groups, where the greatest gains in health status can be achieved. The purpose of this paper is to provide an overview of an innovative multi-component, organizational-level intervention designed to enhance the capacity of PHC clinics to provide equity-oriented care, particularly for marginalized populations. The intervention, known as EQUIP, is being implemented in Canada in four diverse PHC clinics serving populations who are impacted by structural inequities. These PHC clinics serve as case studies for the implementation and evaluation of the EQUIP intervention. We discuss the evidence and theory that provide the basis for the intervention, describe the intervention components, and discuss the methods used to evaluate the implementation and impact of the intervention in diverse contexts. Research and theory related to equity-oriented care, and complexity theory, are central to the design of the EQUIP intervention. The intervention aims to enhance capacity for equity-oriented care at the staff level, and at the organizational level (i.e., policy and operations) and is novel in its dual focus on: (a) Staff education: using standardized educational models and integration strategies to enhance staff knowledge, attitudes and practices related to equity-oriented care in general, and cultural safety, and trauma- and violence-informed care in particular, and; (b) Organizational integration and tailoring: using a participatory approach, practice facilitation, and catalyst grants to foster shifts in organizational structures, practices and policies to enhance the capacity to deliver equity-oriented care, improve processes of care, and shift key client outcomes. Using a mixed methods, multiple case-study design, we are examining the impact of the intervention in enhancing staff knowledge, attitudes and practices; improving

  1. Modeling of Agile Intelligent Manufacturing-oriented Production Scheduling System

    Institute of Scientific and Technical Information of China (English)

    Zhong-Qi Sheng; Chang-Ping Tang; Ci-Xing Lv

    2010-01-01

    Agile intelligent manufacturing is one of the new manufacturing paradigms that adapt to the fierce globalizing market competition and meet the survival needs of the enterprises, in which the management and control of the production system have surpassed the scope of individual enterprise and embodied some new features including complexity, dynamicity, distributivity, and compatibility. The agile intelligent manufacturing paradigm calls for a production scheduling system that can support the cooperation among various production sectors, the distribution of various resources to achieve rational organization, scheduling and management of production activities. This paper uses multi-agents technology to build an agile intelligent manufacturing-oriented production scheduling system. Using the hybrid modeling method, the resources and functions of production system are encapsulated, and the agent-based production system model is established. A production scheduling-oriented multi-agents architecture is constructed and a multi-agents reference model is given in this paper.

  2. Multi-slice spiral CT detects spread of small laryngeal tumors

    International Nuclear Information System (INIS)

    Bruening, R.; Schoepf, U.; Becker, C.; Reiser, M.; Hong, C.; Sturm, C.; Wollenberg, B.

    1999-01-01

    The purpose of the study was to preoperatively investigate small laryngeal carcinomas using multi-slice spiral CT (MSCT) and subsequent multiplanar reconstructions (MPR) and to compare the results to the detailed spread found a surgery and histology. Nine patients with small (T1, T2) laryngeal cancer were investigated on a MSCT scanner (Siemens plus 4 Volume Zoom, Siemens). A 4x1 mm collimation, 120 kV, 200 mAs and a 0.5 seconds rotation time were used, allowing a coverage of the entire larynx in approximately 10 seconds within a single breathhold. Multiplanar reconstruction's (MPR) in sagittal and coronal plane were reconstructed in all patients and rated in consensus reading. In 8 of nine patients, the glottic spread was detected by MSCT, in one case of a supraglottic tumor a glottic invasion was excluded. The infiltration of the anterior commissure, the infiltration into the subglottic space and the extension into the hypo-pharynx was correctly assessed in all patients. MSCT was not able to predict infiltration of the arythnoids in two patients. The use of multi-slice CT for the preoperative assessment of small laryngeal tumors shows great promise. The detection or exclusion of subtle spread of these tumors into the supra- or subglottic space and along the glottic level was possible with high accuracy. As the examination time is short, artifacts are rare and multiplanar reconstructions gain in clinical importance. (orig.) [de

  3. Electrocatalytic Detection of Amitrole on the Multi-Walled Carbon Nanotube – Iron (II tetra-aminophthalocyanine Platform

    Directory of Open Access Journals (Sweden)

    Tebello Nyokong

    2008-08-01

    Full Text Available It is shown that iron(II tetra-aminophthalocyanine complex electropolymerized onto a multi-walled carbon nanotube-modified basal plane pyrolytic graphite electrode greatly enhanced the electrocatalytic detetion of amitrole (a toxic herbicide, resulting in a very low detection limit (0.5 nM and excellent sensitivity of 8.80±0.44 μA/nM, compared to any known work reported so far. The electrocatalytic detection of amitrole at this electrode occurred at less positive potential (~0.3 V vs Ag|ACl and also revealed a typical coupled chemical reaction. The mechanism for this response is proposed. The electrode gave satisfactory selectivity to amitrole in the presence of other potential interfering pesticides in aqueous solutions.

  4. Magnetic-Field-Orientation Dependent Magnetoelectric Effect in FeBSiC/PZT/FeBSiC Composites

    Directory of Open Access Journals (Sweden)

    Jun-Xian Ye

    2014-01-01

    Full Text Available We investigate the magnetic-field-orientation dependent magnetoelectric (ME effect in the FeBSiC/Pb(Zr,TiO3(PZT/FeBSiC laminates. It is shown that, by only using the bias-magnetic-field dependent ME response measured with the magnetic-field parallel to the surface plane of PZT slab, the magnetic-field-orientation dependent ME coefficient upon magnetic-fields of various amplitudes can be obtained via computer simulations. The simulation results match well the experimental measurements, demonstrating the applicability of the ME laminates-based sensors in detecting magnetic-fields with uncertain amplitudes and/or orientations in environment.

  5. Combining orthogonal polarization for elongated target detection with GPR

    International Nuclear Information System (INIS)

    Lualdi, Maurizio; Lombardi, Federico

    2014-01-01

    For an accurate imaging of ground penetrating radar data the polarization characteristics of the propagating electromagnetic (EM) wavefield and wave amplitude variations with antenna pattern orientation must be taken into account. For objects that show some directionality feature and cylindrical shape any misalignment between transmitter and target can strongly modify the polarization state of the backscattered wavefield, thus conditioning the detection capability of the system. Hints on the depolarization can be used to design the optimal GPR antenna survey to avoid omissions and pitfalls during data processing. This research addresses the issue of elongated target detection through a multi azimuth (or multi polarization) approach based on the combination of mutually orthogonal GPR data. Results from the analysis of the formal scattering problem demonstrate how this strategy can reach a scalar formulation of the scattering matrix and achieve a rotational invariant quantity. The effectiveness of the algorithm is then evaluated with a detailed field example showing results closely proximal to those obtained under the optimal alignment condition: detection is significantly improved and the risk of target missing is reduced. (paper)

  6. Feature-based attentional modulation of orientation perception in somatosensation

    Directory of Open Access Journals (Sweden)

    Meike Annika Schweisfurth

    2014-07-01

    Full Text Available In a reaction time study of human tactile orientation detection the effects of spatial attention and feature-based attention were investigated. Subjects had to give speeded responses to target orientations (parallel and orthogonal to the finger axis in a random stream of oblique tactile distractor orientations presented to their index and ring fingers. Before each block of trials, subjects received a tactile cue at one finger. By manipulating the validity of this cue with respect to its location and orientation (feature, we provided an incentive to subjects to attend spatially to the cued location and only there to the cued orientation. Subjects showed quicker responses to parallel compared to orthogonal targets, pointing to an orientation anisotropy in sensory processing. Also, faster reaction times were observed in location-matched trials, i.e. when targets appeared on the cued finger, representing a perceptual benefit of spatial attention. Most importantly, reaction times were shorter to orientations matching the cue, both at the cued and at the uncued location, documenting a global enhancement of tactile sensation by feature-based attention. This is the first report of a perceptual benefit of feature-based attention outside the spatial focus of attention in somatosensory perception. The similarity to effects of feature-based attention in visual perception supports the notion of matching attentional mechanisms across sensory domains.

  7. Contextual Multi-Scale Region Convolutional 3D Network for Activity Detection

    KAUST Repository

    Bai, Yancheng

    2018-01-28

    Activity detection is a fundamental problem in computer vision. Detecting activities of different temporal scales is particularly challenging. In this paper, we propose the contextual multi-scale region convolutional 3D network (CMS-RC3D) for activity detection. To deal with the inherent temporal scale variability of activity instances, the temporal feature pyramid is used to represent activities of different temporal scales. On each level of the temporal feature pyramid, an activity proposal detector and an activity classifier are learned to detect activities of specific temporal scales. Temporal contextual information is fused into activity classifiers for better recognition. More importantly, the entire model at all levels can be trained end-to-end. Our CMS-RC3D detector can deal with activities at all temporal scale ranges with only a single pass through the backbone network. We test our detector on two public activity detection benchmarks, THUMOS14 and ActivityNet. Extensive experiments show that the proposed CMS-RC3D detector outperforms state-of-the-art methods on THUMOS14 by a substantial margin and achieves comparable results on ActivityNet despite using a shallow feature extractor.

  8. A software framework for real-time multi-modal detection of microsleeps.

    Science.gov (United States)

    Knopp, Simon J; Bones, Philip J; Weddell, Stephen J; Jones, Richard D

    2017-09-01

    A software framework is described which was designed to process EEG, video of one eye, and head movement in real time, towards achieving early detection of microsleeps for prevention of fatal accidents, particularly in transport sectors. The framework is based around a pipeline structure with user-replaceable signal processing modules. This structure can encapsulate a wide variety of feature extraction and classification techniques and can be applied to detecting a variety of aspects of cognitive state. Users of the framework can implement signal processing plugins in C++ or Python. The framework also provides a graphical user interface and the ability to save and load data to and from arbitrary file formats. Two small studies are reported which demonstrate the capabilities of the framework in typical applications: monitoring eye closure and detecting simulated microsleeps. While specifically designed for microsleep detection/prediction, the software framework can be just as appropriately applied to (i) other measures of cognitive state and (ii) development of biomedical instruments for multi-modal real-time physiological monitoring and event detection in intensive care, anaesthesiology, cardiology, neurosurgery, etc. The software framework has been made freely available for researchers to use and modify under an open source licence.

  9. Contextual Multi-Scale Region Convolutional 3D Network for Activity Detection

    KAUST Repository

    Bai, Yancheng; Xu, Huijuan; Saenko, Kate; Ghanem, Bernard

    2018-01-01

    Activity detection is a fundamental problem in computer vision. Detecting activities of different temporal scales is particularly challenging. In this paper, we propose the contextual multi-scale region convolutional 3D network (CMS-RC3D) for activity detection. To deal with the inherent temporal scale variability of activity instances, the temporal feature pyramid is used to represent activities of different temporal scales. On each level of the temporal feature pyramid, an activity proposal detector and an activity classifier are learned to detect activities of specific temporal scales. Temporal contextual information is fused into activity classifiers for better recognition. More importantly, the entire model at all levels can be trained end-to-end. Our CMS-RC3D detector can deal with activities at all temporal scale ranges with only a single pass through the backbone network. We test our detector on two public activity detection benchmarks, THUMOS14 and ActivityNet. Extensive experiments show that the proposed CMS-RC3D detector outperforms state-of-the-art methods on THUMOS14 by a substantial margin and achieves comparable results on ActivityNet despite using a shallow feature extractor.

  10. Defect detection in industrial radiography: a multi-scale approach; Detection de defauts en radiographie industrielle: approches multiechelles

    Energy Technology Data Exchange (ETDEWEB)

    Lefevre, M

    1995-10-01

    Radiography is used by Electricite de France for pipe inspection in nuclear power plant in order to detect defects. For several years, the RD Division of EDF has undertaken research to define image processing methods well adapted to radiographic images. The main issues raised by these images are their low contrast, their high level of noise, the presence of a trend and the variable size of the defects. A data base of digitized radiographs of pipes has been gathered and the statistical, topological and geometrical properties of all of these images have been analyzed. From this study, a global indicator of the presence of defects and local features, leading to a classification of images into areas with or without defects, have been extracted. The defect localisation problem has been considered in a multi-scale framework based on the creation of a family of images with increasing regularity and defined as a solution of a partial differential equation. From a choice of axioms, a set of equations may be deduced which define various multi-scale analyses. The survey of the properties of such analysed, when applied to images altered with different types of noise, has lead to the selection of the digitized radiographs best adapted multi-scale analysis. The segmentation process, uses the geodesic information attached to defects via connection cost concept. The final decision is based on a summary of the information extracted at several scales. A fuzzy logic approach has been proposed to solve this part. We then developed methods and tools for expertise guidance and validated them on a complete data base of images. Some global indicators have been extracted and a detection and localisation process has been achieved for large defects. (author). 117 refs., 73 figs.

  11. Red orientalism: Mikhail Pavlovich and Marxist Oriental studies in early Soviet Russia

    NARCIS (Netherlands)

    Kemper, M.

    2010-01-01

    Marxist Oriental Studies in early Soviet Russia emerged in opposition to the 'bourgeois' Russian tradition of classical Oriental scholarship; rather than studying texts and history, Bolshevik Orientalists saw their task in providing the Soviet government with the necessary political and

  12. Development of a large-solid-angle and multi-device detection system for elemental analysis

    International Nuclear Information System (INIS)

    Satoh, T.; Ishii, K.; Kamiya, T.; Sakai, T.; Oikawa, M.; Arakawa, K.; Matsuyama, S.; Yamazaki, H.

    2003-01-01

    A new detection apparatus for both low energy X-rays like 1 keV and back scattered protons of MeV energy was developed. The detection apparatus consists of a large-solid-angle multi-device Si detector and a data acquisition system. The detector has 45 detection devices which are arranged in the shape of a pentagonal pyramid and fully cover a sample. A micro-beam irradiates the sample through the center of the pentagonal pyramid and X-rays emitted from the sample are detected in a solid angle of about 1.0 sr. This novel detection setup has about five times higher sensitivity than a conventional micro-PIXE camera. In addition, not only X-rays but back scattered protons can be detected, since the counting rate of back scattered protons per detection device is small despite lack of a passive absorber

  13. Automatic detection of adverse events to predict drug label changes using text and data mining techniques.

    Science.gov (United States)

    Gurulingappa, Harsha; Toldo, Luca; Rajput, Abdul Mateen; Kors, Jan A; Taweel, Adel; Tayrouz, Yorki

    2013-11-01

    The aim of this study was to assess the impact of automatically detected adverse event signals from text and open-source data on the prediction of drug label changes. Open-source adverse effect data were collected from FAERS, Yellow Cards and SIDER databases. A shallow linguistic relation extraction system (JSRE) was applied for extraction of adverse effects from MEDLINE case reports. Statistical approach was applied on the extracted datasets for signal detection and subsequent prediction of label changes issued for 29 drugs by the UK Regulatory Authority in 2009. 76% of drug label changes were automatically predicted. Out of these, 6% of drug label changes were detected only by text mining. JSRE enabled precise identification of four adverse drug events from MEDLINE that were undetectable otherwise. Changes in drug labels can be predicted automatically using data and text mining techniques. Text mining technology is mature and well-placed to support the pharmacovigilance tasks. Copyright © 2013 John Wiley & Sons, Ltd.

  14. Performance improvement of developed program by using multi-thread technique

    Directory of Open Access Journals (Sweden)

    Surasak Jabal

    2015-03-01

    Full Text Available This research presented how to use a multi-thread programming technique to improve the performance of a program written by Windows Presentation Foundation (WPF. The Computer Assisted Instruction (CAI software, named GAME24, was selected to use as a case study. This study composed of two main parts. The first part was about design and modification of the program structure upon the Object Oriented Programing (OOP approach. The second part was about coding the program using the multi-thread technique which the number of threads were based on the calculated Catalan number. The result showed that the multi-thread programming technique increased the performance of the program 44%-88% compared to the single-thread technique. In addition, it has been found that the number of cores in the CPU also increase the performance of multithreaded program proportionally.

  15. Prognosis Essay Scoring and Article Relevancy Using Multi-Text Features and Machine Learning

    Directory of Open Access Journals (Sweden)

    Arif Mehmood

    2017-01-01

    Full Text Available This study develops a model for essay scoring and article relevancy. Essay scoring is a costly process when we consider the time spent by an evaluator. It may lead to inequalities of the effort by various evaluators to apply the same evaluation criteria. Bibliometric research uses the evaluation criteria to find relevancy of articles instead. Researchers mostly face relevancy issues while searching articles. Therefore, they classify the articles manually. However, manual classification is burdensome due to time needed for evaluation. The proposed model performs automatic essay evaluation using multi-text features and ensemble machine learning. The proposed method is implemented in two data sets: a Kaggle short answer data set for essay scoring that includes four ranges of disciplines (Science, Biology, English, and English language Arts, and a bibliometric data set having IoT (Internet of Things and non-IoT classes. The efficacy of the model is measured against the Tandalla and AutoP approach using Cohen’s kappa. The model achieves kappa values of 0.80 and 0.83 for the first and second data sets, respectively. Kappa values show that the proposed model has better performance than those of earlier approaches.

  16. Effects of Text Messaging on Academic Performance

    OpenAIRE

    Barks Amanda; Searight H. Russell; Ratwik Susan

    2011-01-01

    University students frequently send and receive cellular phone text messages during classroominstruction. Cognitive psychology research indicates that multi-tasking is frequently associatedwith performance cost. However, university students often have considerable experience withelectronic multi-tasking and may believe that they can devote necessary attention to a classroomlecture while sending and receiving text messages. In the current study, university students whoused text messaging were ...

  17. Results on the Coherent Interaction of High Energy Electrons and Photons in Oriented Single Crystals

    CERN Document Server

    Apyan, A.; Badelek, B.; Ballestrero, S.; Biino, C.; Birol, I.; Cenci, P.; Connell, S.H.; Eichblatt, S.; Fonseca, T.; Freund, A.; Gorini, B.; Groess, R.; Ispirian, K.; Ketel, T.J.; Kononets, Yu.V.; Lopez, A.; Mangiarotti, A.; van Rens, B.; Sellschop, J.P.F.; Shieh, M.; Sona, P.; Strakhovenko, V.; Uggerhoj, E.; Uggerhj, Ulrik Ingerslev; Unel, G.; Velasco, M.; Vilakazi, Z.Z.; Wessely, O.; Kononets, Yu.V.

    2005-01-01

    The CERN-NA-59 experiment examined a wide range of electromagnetic processes for multi-GeV electrons and photons interacting with oriented single crystals. The various types of crystals and their orientations were used for producing photon beams and for converting and measuring their polarisation. The radiation emitted by 178 GeV unpolarised electrons incident on a 1.5 cm thick Si crystal oriented in the Coherent Bremsstrahlung (CB) and the String-of-Strings (SOS) modes was used to obtain multi-GeV linearly polarised photon beams. A new crystal polarimetry technique was established for measuring the linear polarisation of the photon beam. The polarimeter is based on the dependence of the Coherent Pair Production (CPP) cross section in oriented single crystals on the direction of the photon polarisation with respect to the crystal plane. Both a 1 mm thick single crystal of Germanium and a 4 mm thick multi-tile set of synthetic Diamond crystals were used as analyzers of the linear polarisation. A birefringence ...

  18. On multi-fingerprint detection and attribution of greenhouse gas- and aerosol forced climate change

    Energy Technology Data Exchange (ETDEWEB)

    Hegerl, G C [Max-Planck-Institut fuer Meteorologie, Hamburg (Germany); Hasselmann, K [Max-Planck-Institut fuer Meteorologie, Hamburg (Germany); Cubasch, U [Deutsches Klimarechenzentrum (DKRZ), Hamburg (Germany); Mitchell, J F.B. [Hadley Centre for Climate Prediction and Research, Bracknell (United Kingdom). Meteorological Office; Roeckner, E [Max-Planck-Institut fuer Meteorologie, Hamburg (Germany); Voss, R [Deutsches Klimarechenzentrum (DKRZ), Hamburg (Germany); Waszkewitz, J [Deutsches Klimarechenzentrum (DKRZ), Hamburg (Germany)

    1996-07-01

    A multi-fingerprint analysis is applied to the detection and attribution of anthropogenic climate change. While a single fingerprint, as applied in a previous paper by Hegerl et al. (1996), is optimal for detecting a significant climate change, the simultaneous use of several fingerprints allows one to investigate additionally the consistency between observations and model predicted climate change signals for competing candidate forcing mechanisms. Thus the multi-fingerprint method is a particularly useful technique for attributing an observed climate change to a proposed cause. Different model-predicted climate change signals are derived from three global warming simulations for the period 1880 to 2049. In one simulation, the forcing was by greenhouse gases only, while in the remaining two simulations the influence of aerosols was also included. The two dominant climate change signals derived from these simulations are optimized statistically by weighting the model-predicted climate change pattern towards low-noise directions. These optimized fingerprints are then applied to observed near surface temperature trends. The space-time structure of natural climate variability (needed to determine the signal-to-noise ratio) is estimated from several multi-century control simulations with different CGCMs and from instrumental data over the last 134 years. (orig.)

  19. Multi-Dimensional Damage Detection for Surfaces and Structures

    Science.gov (United States)

    Williams, Martha; Lewis, Mark; Roberson, Luke; Medelius, Pedro; Gibson, Tracy; Parks, Steen; Snyder, Sarah

    2013-01-01

    Current designs for inflatable or semi-rigidized structures for habitats and space applications use a multiple-layer construction, alternating thin layers with thicker, stronger layers, which produces a layered composite structure that is much better at resisting damage. Even though such composite structures or layered systems are robust, they can still be susceptible to penetration damage. The ability to detect damage to surfaces of inflatable or semi-rigid habitat structures is of great interest to NASA. Damage caused by impacts of foreign objects such as micrometeorites can rupture the shell of these structures, causing loss of critical hardware and/or the life of the crew. While not all impacts will have a catastrophic result, it will be very important to identify and locate areas of the exterior shell that have been damaged by impacts so that repairs (or other provisions) can be made to reduce the probability of shell wall rupture. This disclosure describes a system that will provide real-time data regarding the health of the inflatable shell or rigidized structures, and information related to the location and depth of impact damage. The innovation described here is a method of determining the size, location, and direction of damage in a multilayered structure. In the multi-dimensional damage detection system, layers of two-dimensional thin film detection layers are used to form a layered composite, with non-detection layers separating the detection layers. The non-detection layers may be either thicker or thinner than the detection layers. The thin-film damage detection layers are thin films of materials with a conductive grid or striped pattern. The conductive pattern may be applied by several methods, including printing, plating, sputtering, photolithography, and etching, and can include as many detection layers that are necessary for the structure construction or to afford the detection detail level required. The damage is detected using a detector or

  20. Multi-gene detection and identification of mosquito-borne RNA viruses using an oligonucleotide microarray.

    Directory of Open Access Journals (Sweden)

    Nathan D Grubaugh

    Full Text Available BACKGROUND: Arthropod-borne viruses are important emerging pathogens world-wide. Viruses transmitted by mosquitoes, such as dengue, yellow fever, and Japanese encephalitis viruses, infect hundreds of millions of people and animals each year. Global surveillance of these viruses in mosquito vectors using molecular based assays is critical for prevention and control of the associated diseases. Here, we report an oligonucleotide DNA microarray design, termed ArboChip5.1, for multi-gene detection and identification of mosquito-borne RNA viruses from the genera Flavivirus (family Flaviviridae, Alphavirus (Togaviridae, Orthobunyavirus (Bunyaviridae, and Phlebovirus (Bunyaviridae. METHODOLOGY/PRINCIPAL FINDINGS: The assay utilizes targeted PCR amplification of three genes from each virus genus for electrochemical detection on a portable, field-tested microarray platform. Fifty-two viruses propagated in cell-culture were used to evaluate the specificity of the PCR primer sets and the ArboChip5.1 microarray capture probes. The microarray detected all of the tested viruses and differentiated between many closely related viruses such as members of the dengue, Japanese encephalitis, and Semliki Forest virus clades. Laboratory infected mosquitoes were used to simulate field samples and to determine the limits of detection. Additionally, we identified dengue virus type 3, Japanese encephalitis virus, Tembusu virus, Culex flavivirus, and a Quang Binh-like virus from mosquitoes collected in Thailand in 2011 and 2012. CONCLUSIONS/SIGNIFICANCE: We demonstrated that the described assay can be utilized in a comprehensive field surveillance program by the broad-range amplification and specific identification of arboviruses from infected mosquitoes. Furthermore, the microarray platform can be deployed in the field and viral RNA extraction to data analysis can occur in as little as 12 h. The information derived from the ArboChip5.1 microarray can help to establish

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

    Directory of Open Access Journals (Sweden)

    Vernon Lawhern

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

  2. Multi-Frequency VLBA Polarimetry and the Twin-Jet Quasar 0850+581

    Directory of Open Access Journals (Sweden)

    Evgeniya Kravchenko

    2017-11-01

    Full Text Available We present the first multi-frequency VLBA study of the quasar 0850+581 which appears to have a two-sided relativistic jet. Apparent velocity in the approaching jet changes from 3.4c to 7c with the separation from the core. The jet-to-counter-jet ratio of about 5 and apparent superluminal velocities suggest that the observing angle of the inner jet is ≤ 17 ∘ . It is likely that this orientation significantly changes downstream due to an interaction of the jet with the surrounding medium; signs of this are seen in polarization. A dense inhomogeneous Faraday screen is detected in the innermost regions of this quasar. We suggest that there is a presence of ionized gas in its nucleus, which might be responsible for the free-free absorption of the synchrotron emission in the jet and counter-jet at frequencies below 8.4 GHz. The experiment makes use of slowly varying instrumental polarisation factors (polarization leakage or D-terms in time. We report application of the “D-term connection” technique for the calibration of an absolute orientation of electric vector position angle (EVPA observed by VLBA at 4.6, 5.0, 8.1, 8.4, 15.4, 22.3, and 43.3 GHz bands during the 2007–2011.

  3. Development of uniform eddy current multi-probe for flaw detection on complex shape part

    International Nuclear Information System (INIS)

    Fukuoka, Katsuhiro; Hashimoto, Mitsuo

    2007-01-01

    The establishment of the technology that inspects plant structures nondestructive is requested, because the occurrence of cracks is reported in the structures of nuclear power plants. In this research, a uniform eddy current multi-probe that is able to be applied to the complex structure and inspected the cracks at the high speed was developed. Exciting coils of the uniform eddy current multi-probe were designed the shape that agreed with the complex shape part, and so that the eddy current flows uniformly in the part of pick-up coils. The pick-up coils were arranged on a flexible printed circuit board as it was possible to correspond to the complex shape. The detection characteristics of EDM (electro-discharge machining) slits provided on the complex shape part were evaluated. The clear signals for the EDM slits provided on the curvature surface of 25 mm in radius were obtained by this probe. We confirmed that the crack shape was able to be estimated by the detection signals. (author)

  4. Preference Bias of Head Orientation in Choosing between Two Non-durables

    Directory of Open Access Journals (Sweden)

    Hiroyuki eFunaya

    2015-06-01

    Full Text Available The goal of this study is to investigate how customers’ gaze, head and body orientations reflect their choices. Although the relationship between human choice and gaze behavior has been well studied, other behaviors such as head and body are unknown. We conducted a two-alternatives-forced-choice task to examine (1 whether preference bias, i.e. a positional bias in gaze, head and body toward the item that was later chosen, exists in choice, (2 when preference bias is observed and when prediction of the resulting choice becomes possible (3 whether human choice is affected when the body orientations are manipulated. We used real non-durable products (cheap snacks and clothing on a shopping shelf. The results showed that there was a significant preference bias in head orientation at the beginning one second when the subjects stood straight toward the shelf, and that the head orientation was more biased toward the selected item than the gaze and the center of pressure at the ending one second. Manipulating body orientation did not affect the result of choice. The preference bias detected by observing the head orientation would be useful in marketing science for predicting customers’ choice.

  5. An Intelligent Fleet Condition-Based Maintenance Decision Making Method Based on Multi-Agent

    Directory of Open Access Journals (Sweden)

    Bo Sun

    2012-01-01

    Full Text Available According to the demand for condition-based maintenance online decision making among a mission oriented fleet, an intelligent maintenance decision making method based on Multi-agent and heuristic rules is proposed. The process of condition-based maintenance within an aircraft fleet (each containing one or more Line Replaceable Modules based on multiple maintenance thresholds is analyzed. Then the process is abstracted into a Multi-Agent Model, a 2-layer model structure containing host negotiation and independent negotiation is established, and the heuristic rules applied to global and local maintenance decision making is proposed. Based on Contract Net Protocol and the heuristic rules, the maintenance decision making algorithm is put forward. Finally, a fleet consisting of 10 aircrafts on a 3-wave continuous mission is illustrated to verify this method. Simulation results indicate that this method can improve the availability of the fleet, meet mission demands, rationalize the utilization of support resources and provide support for online maintenance decision making among a mission oriented fleet.

  6. BioC-compatible full-text passage detection for protein-protein interactions using extended dependency graph.

    Science.gov (United States)

    Peng, Yifan; Arighi, Cecilia; Wu, Cathy H; Vijay-Shanker, K

    2016-01-01

    There has been a large growth in the number of biomedical publications that report experimental results. Many of these results concern detection of protein-protein interactions (PPI). In BioCreative V, we participated in the BioC task and developed a PPI system to detect text passages with PPIs in the full-text articles. By adopting the BioC format, the output of the system can be seamlessly added to the biocuration pipeline with little effort required for the system integration. A distinctive feature of our PPI system is that it utilizes extended dependency graph, an intermediate level of representation that attempts to abstract away syntactic variations in text. As a result, we are able to use only a limited set of rules to extract PPI pairs in the sentences, and additional rules to detect additional passages for PPI pairs. For evaluation, we used the 95 articles that were provided for the BioC annotation task. We retrieved the unique PPIs from the BioGRID database for these articles and show that our system achieves a recall of 83.5%. In order to evaluate the detection of passages with PPIs, we further annotated Abstract and Results sections of 20 documents from the dataset and show that an f-value of 80.5% was obtained. To evaluate the generalizability of the system, we also conducted experiments on AIMed, a well-known PPI corpus. We achieved an f-value of 76.1% for sentence detection and an f-value of 64.7% for unique PPI detection.Database URL: http://proteininformationresource.org/iprolink/corpora. © The Author(s) 2016. Published by Oxford University Press.

  7. Detection of pulmonary nodules on lung X-ray images. Studies on multi-resolutional filter and energy subtraction images

    International Nuclear Information System (INIS)

    Sawada, Akira; Sato, Yoshinobu; Kido, Shoji; Tamura, Shinichi

    1999-01-01

    The purpose of this work is to prove the effectiveness of an energy subtraction image for the detection of pulmonary nodules and the effectiveness of multi-resolutional filter on an energy subtraction image to detect pulmonary nodules. Also we study influential factors to the accuracy of detection of pulmonary nodules from viewpoints of types of images, types of digital filters and types of evaluation methods. As one type of images, we select an energy subtraction image, which removes bones such as ribs from the conventional X-ray image by utilizing the difference of X-ray absorption ratios at different energy between bones and soft tissue. Ribs and vessels are major causes of CAD errors in detection of pulmonary nodules and many researches have tried to solve this problem. So we select conventional X-ray images and energy subtraction X-ray images as types of images, and at the same time select ∇ 2 G (Laplacian of Guassian) filter, Min-DD (Minimum Directional Difference) filter and our multi-resolutional filter as types of digital filters. Also we select two evaluation methods and prove the effectiveness of an energy subtraction image, the effectiveness of Min-DD filter on a conventional X-ray image and the effectiveness of multi-resolutional filter on an energy subtraction image. (author)

  8. Object Attention Patches for Text Detection and Recognition in Scene Images using SIFT

    NARCIS (Netherlands)

    Sriman, Bowornrat; Schomaker, Lambertus; De Marsico, Maria; Figueiredo, Mário; Fred, Ana

    2015-01-01

    Natural urban scene images contain many problems for character recognition such as luminance noise, varying font styles or cluttered backgrounds. Detecting and recognizing text in a natural scene is a difficult problem. Several techniques have been proposed to overcome these problems. These are,

  9. Trauma and Pain in Family-Orientated Societies

    Directory of Open Access Journals (Sweden)

    Jan Ilhan Kizilhan

    2017-12-01

    Full Text Available People from family-oriented societies in particular, in addition to having a post-traumatic stress disorder (PTSD suffer from chronic pain and physical complaints. Such people have a different understanding of physical illness and pain and, compared to patients from western societies, have different ideas on healing, even when confronted with the therapist. Hitherto, these factors have not been sufficiently taken into account in modern, multi-module therapy approaches. Trauma can be perceived via pain and physical complaints, whereby the pain is not restricted to one part of the body but is seen as covering the body as a whole. Therefore, in the treatment and above all in the patient-therapist relationship, it is necessary to understand what importance is attached to the perceived pain in relation to the trauma. The afflicted body expresses the trauma in the shape of its further-reaching consequences such as the patient’s social, collective, economic and cultural sensitivity. Therefore, for the effective treatment of trauma and chronic pain, it is necessary to use a multi-modal, interdisciplinary, and culture-sensitive approach when treating patients from traditional cultural backgrounds.

  10. Exploiting Higher Order and Multi-modal Features for 3D Object Detection

    DEFF Research Database (Denmark)

    Kiforenko, Lilita

    that describe object visual appearance such as shape, colour, texture etc. This thesis focuses on robust object detection and pose estimation of rigid objects using 3D information. The thesis main contributions are novel feature descriptors together with object detection and pose estimation algorithms....... The initial work introduces a feature descriptor that uses edge categorisation in combination with a local multi-modal histogram descriptor in order to detect objects with little or no texture or surface variation. The comparison is performed with a state-of-the-art method, which is outperformed...... of the methods work well for one type of objects in a specific scenario, in another scenario or with different objects they might fail, therefore more robust solutions are required. The typical problem solution is the design of robust feature descriptors, where feature descriptors contain information...

  11. Using temporal orientation, category fluency, and word recall for detecting cognitive impairment: the 10-point cognitive screener (10-CS).

    Science.gov (United States)

    Apolinario, Daniel; Lichtenthaler, Daniel Gomes; Magaldi, Regina Miksian; Soares, Aline Thomaz; Busse, Alexandre Leopold; Amaral, Jose Renato das Gracas; Jacob-Filho, Wilson; Brucki, Sonia Maria Dozzi

    2016-01-01

    A screening strategy composed of three-item temporal orientation and three-word recall has been increasingly used for detecting cognitive impairment. However, the intervening task administered between presentation and recall has varied. We evaluated six brief tasks that could be useful as intervening distractors and possibly provide incremental accuracy: serial subtraction, clock drawing, category fluency, letter fluency, timed visual detection, and digits backwards. Older adults (n = 230) consecutively referred for suspected cognitive impairment underwent a comprehensive assessment for gold-standard diagnosis, of whom 56 (24%) presented cognitive impairment not dementia and 68 (30%) presented dementia. Among those with dementia, 87% presented very mild or mild stages (Clinical Dementia Rating 0.5 or 1). The incremental value of each candidate intervening task in a model already containing orientation and word recall was assessed. Category fluency (animal naming) presented the highest incremental value among the six candidate intervening tasks. Reclassification analyses revealed a net gain of 12% among cognitively impaired and 17% among normal participants. A four-point scaled score of the animal naming task was added to three-item temporal orientation and three-word recall to compose the 10-point Cognitive Screener. The education-adjusted 10-point Cognitive Screener outperformed the longer Mini-Mental State Examination for detecting both cognitive impairment (area under the curve 0.85 vs 0.77; p = 0.027) and dementia (area under the curve 0.90 vs 0.83; p = 0.015). Based on empirical data, we have developed a brief and easy-to-use screening strategy with higher accuracy and some practical advantages compared with commonly used tools. Copyright © 2015 John Wiley & Sons, Ltd.

  12. Unified Modeling Language description of the object-oriented multi-scale adaptive finite element method for Step-and-Flash Imprint Lithography Simulations

    International Nuclear Information System (INIS)

    Paszynski, Maciej; Gurgul, Piotr; Sieniek, Marcin; Pardo, David

    2010-01-01

    In the first part of the paper we present the multi-scale simulation of the Step-and-Flash Imprint Lithography (SFIL), a modern patterning process. The simulation utilizes the hp adaptive Finite Element Method (hp-FEM) coupled with Molecular Statics (MS) model. Thus, we consider the multi-scale problem, with molecular statics applied in the areas of the mesh where the highest accuracy is required, and the continuous linear elasticity with thermal expansion coefficient applied in the remaining part of the domain. The degrees of freedom from macro-scale element's nodes located on the macro-scale side of the interface have been identified with particles from nano-scale elements located on the nano-scale side of the interface. In the second part of the paper we present Unified Modeling Language (UML) description of the resulting multi-scale application (hp-FEM coupled with MS). We investigated classical, procedural codes from the point of view of the object-oriented (O-O) programming paradigm. The discovered hierarchical structure of classes and algorithms makes the UML project as independent on the spatial dimension of the problem as possible. The O-O UML project was defined at an abstract level, independent on the programming language used.

  13. Computation Reduction Oriented Circular Scanning SAR Raw Data Simulation on Multi-GPUs

    Directory of Open Access Journals (Sweden)

    Hu Chen

    2016-08-01

    Full Text Available As a special working mode, the circular scanning Synthetic Aperture Radar (SAR is widely used in the earth observation. With the increase of resolution and swath width, the simulation data has a massive increase, which boosts the new requirements of efficiency. Through analyzing the redundancy in the raw data simulation based on Graphics Processing Unit (GPU, a fast simulation method considering reduction of redundant computation is realized by the multi-GPUs and Message Passing Interface (MPI. The results show that the efficiency of 4-GPUs increases 2 times through the redundant reduction, and the hardware cost decreases by 50%, thus the overall speedup achieves 350 times than the traditional CPU simulation.

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

    Directory of Open Access Journals (Sweden)

    Miaole Hou

    2016-05-01

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

  15. Novelty detection of foreign objects in food using multi-modal X-ray imaging

    DEFF Research Database (Denmark)

    Einarsdottir, Hildur; Emerson, Monica Jane; Clemmensen, Line Katrine Harder

    2016-01-01

    In this paper we demonstrate a method for novelty detection of foreign objects in food products using grating-based multimodal X-ray imaging. With this imaging technique three modalities are available with pixel correspondence, enhancing organic materials such as wood chips, insects and soft...... plastics not detectable by conventional X-ray absorption radiography. We conduct experiments, where several food products are imaged with common foreign objects typically found in the food processing industry. To evaluate the benefit from using this multi-contrast X-ray technique over conventional X......-ray absorption imaging, a novelty detection scheme based on well known image- and statistical analysis techniques is proposed. The results show that the presented method gives superior recognition results and highlights the advantage of grating-based imaging....

  16. A Portable Wireless Communication Platform Based on a Multi-Material Fiber Sensor for Real-Time Breath Detection

    Directory of Open Access Journals (Sweden)

    Mourad Roudjane

    2018-03-01

    Full Text Available In this paper, we present a new mobile wireless communication platform for real-time monitoring of an individual’s breathing rate. The platform takes the form of a wearable stretching T-shirt featuring a sensor and a detection base station. The sensor is formed by a spiral-shaped antenna made from a multi-material fiber connected to a compact transmitter. Based on the resonance frequency of the antenna at approximately 2.4 GHz, the breathing sensor relies on its Bluetooth transmitter. The contactless and non-invasive sensor is designed without compromising the user’s comfort. The sensing mechanism of the system is based on the detection of the signal amplitude transmitted wirelessly by the sensor, which is found to be sensitive to strain. We demonstrate the capability of the platform to detect the breathing rates of four male volunteers who are not in movement. The breathing pattern is obtained through the received signal strength indicator (RSSI which is filtered and analyzed with home-made algorithms in the portable system. Numerical simulations of human breath are performed to support the experimental detection, and both results are in a good agreement. Slow, fast, regular, irregular, and shallow breathing types are successfully recorded within a frequency interval of 0.16–1.2 Hz, leading to a breathing rate varying from 10 to 72 breaths per minute.

  17. Synthesised model of market orientation-business performance relationship

    Directory of Open Access Journals (Sweden)

    G. Nwokah

    2006-12-01

    Full Text Available Purpose: The purpose of this paper is to assess the impact of market orientation on the performance of the organisation. While much empirical works have centered on market orientation, the generalisability of its impact on performance of the Food and Beverages organisations in the Nigeria context has been under-researched. Design/Methodology/Approach: The study adopted a triangulation methodology (quantitative and qualitative approach. Data was collected from key informants using a research instrument. Returned instruments were analyzed using nonparametric correlation through the use of the Statistical Package for Social Sciences (SPSS version 10. Findings: The study validated the earlier instruments but did not find any strong association between market orientation and business performance in the Nigerian context using the food and beverages organisations for the study. The reasons underlying the weak relationship between market orientation and business performance of the Food and Beverages organisations is government policies, new product development, diversification, innovation and devaluation of the Nigerian currency. One important finding of this study is that market orientation leads to business performance through some moderating variables. Implications: The study recommends that Nigerian Government should ensure a stable economy and make economic policies that will enhance existing business development in the country. Also, organisations should have performance measurement systems to detect the impact of investment on market orientation with the aim of knowing how the organisation works. Originality/Value: This study significantly refines the body of knowledge concerning the impact of market orientation on the performance of the organisation, and thereby offers a model of market orientation and business performance in the Nigerian context for marketing scholars and practitioners. This model will, no doubt, contribute to the body of

  18. Time-aware multi-viewpoint summarization of multilingual social text streams

    NARCIS (Netherlands)

    Ren, Zhaochun; Inel, Oana; Aroyo, Lora; De Rijke, Maarten

    2016-01-01

    A viewpoint is a triple consisting of an entity, a topic related to this entity and sentiment towards this topic. In time-aware multi-viewpoint summarization one monitors viewpoints for a running topic and selects a small set of informative documents. In this paper, we focus on time-aware

  19. Characteristics of transitory multi-charged molecular ions produced by an intense femtosecond laser impulse; Etats electroniques des ions moleculaires multicharges transitoires produits par une impulsion laser femtoseconde intense

    Energy Technology Data Exchange (ETDEWEB)

    Quaglia, L

    2001-12-01

    The study of the molecular multi-ionization is narrowly linked to the dynamics of excitation and fragmentation for which the experimental observables rest on the characteristics of the fragmentation products, these characteristics are: intern energy, kinetic energy and charge states. The first chapter sets the problem. The second chapter presents the experimental tools used and developed in this work, the technologies of the detection of ions or of fluorescence are also described. The chapter 3 gathers the theoretical aspects: quantum chemistry and CASSCF (complete active space self consistent field) methods have been used to compute the potential energy curves of multi-charged ions, the two-dimensional hydrodynamic model derived from the Thomas-Fermi model is introduced to tackle the molecular re-orientation. The chapter 4 presents the experimental study of highly excited states by using fluorescence detection methods. The chapter 5 is dedicated to the study of low excited states by measuring kinetic energy spectra and by comparison with potential energy curves of molecular multi-charged ions. The chapter 6 presents experiments with 2 impulses and the results given by the Thomas-Fermi model applied to the re-orientation of the N{sub 2}O molecule. (A.C.)

  20. Faraday cage-type electrochemiluminescence immunosensor for ultrasensitive detection of Vibrio vulnificus based on multi-functionalized graphene oxide.

    Science.gov (United States)

    Guo, Zhiyong; Sha, Yuhong; Hu, Yufang; Yu, Zhongqing; Tao, Yingying; Wu, Yanjie; Zeng, Min; Wang, Sui; Li, Xing; Zhou, Jun; Su, Xiurong

    2016-10-01

    A novel Faraday cage-type electrochemiluminescence (ECL) immunosensor devoted to the detection of Vibrio vulnificus (VV) was fabricated. The sensing strategy was presented by a unique Faraday cage-type immunocomplex based on immunomagnetic beads (IMBs) and multi-functionalized graphene oxide (GO) labeled with (2,2'-bipyridine)(5-aminophenanthroline)ruthenium (Ru-NH2). The multi-functionalized GO could sit on the electrode surface directly due to the large surface area, abundant functional groups, and good electronic transport property. It ensures that more Ru-NH2 is entirely caged and become "effective," thus improving sensitivity significantly, which resembles extending the outer Helmholtz plane (OHP) of the electrode. Under optimal conditions, the developed immunosensor achieves a limit of detection as low as 1 CFU/mL. Additionally, the proposed immunosensor with high sensitivity and selectivity can be used for the detection of real samples. The novel Faraday cage-type method has shown potential application for the diagnosis of VV and opens up a new avenue in ECL immunoassay. Graphical abstract Faraday cage-type immunoassay mode for ultrasensitive detection by extending OHP.

  1. Programming paradigms in an object-oriented multi-media standard

    NARCIS (Netherlands)

    D.J. Duke; I. Herman (Ivan)

    1997-01-01

    textabstractOf the various programming paradigms in use today, object-orientation is probably the most successful in terms of industrial take-up and application, particularly in the field of multimedia. It is therefore unsurprising that this technology has been adopted by ISO/IEC JTC1/SC24 as the

  2. The multi-stage proportional chamber in the detection of Cherenkov rings for particle recognition

    International Nuclear Information System (INIS)

    Sauli, F.

    1979-01-01

    The multi-stage proportional chamber enables very high gains of 10 6 or more to be reached in gaseous mixtures offering a very good quantum efficiency in the far ultra-violet range. This makes it an ideal instrument for detecting and locating the photons emitted by Cerenkov effect in appropriate radiators [fr

  3. Molecular orientation of individual LCP particles in injection-moulded PPS/LCP blends

    Directory of Open Access Journals (Sweden)

    Kestenbach H.-J.

    2003-01-01

    Full Text Available Polarized light microscopy was used to investigate the presence of preferred molecular orientation in the LCP phase of PPS/LCP blends after injection moulding. Normal birefringence effects appeared to be complicated by artifacts due to sample preparation and by the complex nature of polarized light transmission through a multicomponent sample. It was found, however, that, during low-temperature cutting of optically transparent thin sections on a standard microtome, individual LCP particles could be separated from the PPS matrix, and their birefringence analyzed separately. Preferred orientation was detected only in LCP fibrils which dominated in skin regions, but not in droplet-shaped particles which had formed in core regions. Quantitative measurements indicated that the molecular orientation of the fibrils increased linearly with their length-to-diameter aspect ratios which ranged from 15 to 50. Even for the highest aspect ratios, however, the degree of orientation was always less than that which could easily be introduced into pure LCP thin-film samples by manual shearing.

  4. Anomaly Detection with Text Mining

    Data.gov (United States)

    National Aeronautics and Space Administration — Many existing complex space systems have a significant amount of historical maintenance and problem data bases that are stored in unstructured text forms. The...

  5. THE EARLY DETECTION OF THE EMERALD ASH BORER (EAB USING MULTI-SOURCE REMOTELY SENSED DATA

    Directory of Open Access Journals (Sweden)

    B. Hu

    2018-04-01

    Full Text Available The objectives of this study were to exploit the synergy of hyperspectral imagery, Light Detection And Ranging (LiDAR and high spatial resolution data and their synergy in the early detection of the EAB (Emerald Ash Borer presence in trees within urban areas and to develop a framework to combine information extracted from multiple data sources. To achieve these, an object-oriented framework was developed to combine information derived from available data sets to characterize ash trees. Within this framework, an advanced individual tree delineation method was developed to delineate individual trees using the combined high-spatial resolution worldview-3 imagery was used together with LiDAR data. Individual trees were then classified to ash and non-ash trees using spectral and spatial information. In order to characterize the health state of individual ash trees, leaves from ash trees with various health states were sampled and measured using a field spectrometer. Based on the field measurements, the best indices that sensitive to leaf chlorophyll content were selected. The developed framework and methods were tested using worldview-3, airborne LiDAR data over the Keele campus of York University Toronto Canada. Satisfactory results in terms of individual tree crown delineation, ash tree identification and characterization of the health state of individual ash trees. Quantitative evaluations is being carried out.

  6. Multi-stage identification scheme for detecting damage in structures under ambient excitations

    International Nuclear Information System (INIS)

    Bao, Chunxiao; Li, Zhong-Xian; Hao, Hong

    2013-01-01

    Structural damage identification methods are critical to the successful application of structural health monitoring (SHM) systems to civil engineering structures. The dynamic response of civil engineering structures is usually characterized by high nonlinearity and non-stationarity. Accordingly, an improved Hilbert–Huang transform (HHT) method which is adaptive, output-only and applicable to system identification of in-service structures under ambient excitations is developed in this study. Based on this method, a multi-stage damage detection scheme including the detection of damage occurrence, damage existence, damage location and the estimation of damage severity is developed. In this scheme, the improved HHT method is used to analyse the structural acceleration response, the obtained instantaneous frequency detects the instant of damage occurrence, the instantaneous phase is sensitive to minor damage and provides reliable damage indication, and the damage indicator developed based on statistical analysis of the Hilbert marginal spectrum detects damage locations. Finally, the response sampled at the detected damage location is continuously analysed to estimate the damage severity. Numerical and experimental studies of frame structures under ambient excitations are performed. The results demonstrate that this scheme accomplishes the above damage detection functions within one flow. It is robust, time efficient, simply implemented and applicable to the real-time SHM of in-service structures. (paper)

  7. Low-Cost Resonant Cavity Raman Gas Probe for Multi-Gas Detection

    Science.gov (United States)

    Thorstensen, J.; Haugholt, K. H.; Ferber, A.; Bakke, K. A. H.; Tschudi, J.

    2014-12-01

    Raman based gas sensing can be attractive in several industrial applications, due to its multi-gas sensing capabilities and its ability to detect O_2 and N_2. In this article, we have built a Raman gas probe, based on low-cost components, which has shown an estimated detection limit of 0.5 % for 30 second measurements of N_2 and O_2. While this detection limit is higher than that of commercially available equipment, our estimated component cost is approximately one tenth of the price of commercially available equipment. The use of a resonant Fabry-Pérot cavity increases the scattered signal, and hence the sensitivity, by a factor of 50. The cavity is kept in resonance using a piezo-actuated mirror and a photodiode in a feedback loop. The system described in this article was made with minimum-cost components to demonstrate the low-cost principle. However, it is possible to decrease the detection limit using a higher-powered (but still low-cost) laser and improving the collection optics. By applying these improvements, the detection limit and estimated measurement precision will be sufficient for e.g. the monitoring of input gases in combustion processes, such as e.g. (bio-)gas power plants. In these processes, knowledge about gas compositions with 0.1 % (absolute) precision can help regulate and optimize process conditions. The system has the potential to provide a low-cost, industrial Raman sensor that is optimized for specific gas-detection applications.

  8. Detecting Multi-scale Structures in Chandra Images of Centaurus A

    Science.gov (United States)

    Karovska, M.; Fabbiano, G.; Elvis, M. S.; Evans, I. N.; Kim, D. W.; Prestwich, A. H.; Schwartz, D. A.; Murray, S. S.; Forman, W.; Jones, C.; Kraft, R. P.; Isobe, T.; Cui, W.; Schreier, E. J.

    1999-12-01

    Centaurus A (NGC 5128) is a giant early-type galaxy with a merger history, containing the nearest radio-bright AGN. Recent Chandra High Resolution Camera (HRC) observations of Cen A reveal X-ray multi-scale structures in this object with unprecedented detail and clarity. We show the results of an analysis of the Chandra data with smoothing and edge enhancement techniques that allow us to enhance and quantify the multi-scale structures present in the HRC images. These techniques include an adaptive smoothing algorithm (Ebeling et al 1999), and a multi-directional gradient detection algorithm (Karovska et al 1994). The Ebeling et al adaptive smoothing algorithm, which is incorporated in the CXC analysis s/w package, is a powerful tool for smoothing images containing complex structures at various spatial scales. The adaptively smoothed images of Centaurus A show simultaneously the high-angular resolution bright structures at scales as small as an arcsecond and the extended faint structures as large as several arc minutes. The large scale structures suggest complex symmetry, including a component possibly associated with the inner radio lobes (as suggested by the ROSAT HRI data, Dobereiner et al 1996), and a separate component with an orthogonal symmetry that may be associated with the galaxy as a whole. The dust lane and the x-ray ridges are very clearly visible. The adaptively smoothed images and the edge-enhanced images also suggest several filamentary features including a large filament-like structure extending as far as about 5 arcminutes to North-West.

  9. Fast Detection of Airports on Remote Sensing Images with Single Shot MultiBox Detector

    Science.gov (United States)

    Xia, Fei; Li, HuiZhou

    2018-01-01

    This paper introduces a method for fast airport detection on remote sensing images (RSIs) using Single Shot MultiBox Detector (SSD). To our knowledge, this could be the first study which introduces an end-to-end detection model into airport detection on RSIs. Based on the common low-level features between natural images and RSIs, a convolution neural network trained on large amounts of natural images was transferred to tackle the airport detection problem with limited annotated data. To deal with the specific characteristics of RSIs, some related parameters in the SSD, such as the scales and layers, were modified for more accurate and rapider detection. The experiments show that the proposed method could achieve 83.5% Average Recall at 8 FPS on RSIs with the size of 1024*1024. In contrast to Faster R-CNN, an improvement on AP and speed could be obtained.

  10. market orientation and firm performance in ghana's pharmaceutical

    African Journals Online (AJOL)

    User

    1Department of Marketing and Corporate Strategy, School of Business, KNUST, ... The study examined the relationship between market orientation and performance in the phar- ... economy context and in a multi-strata approach. ... ented organization experiences superior per- ... compatibility with customer needs (Appiah-.

  11. Sustainability Orientation and Entrepreneurship Orientation: Is There a Tradeoff Relationship between Them?

    Directory of Open Access Journals (Sweden)

    Chang Soo Sung

    2018-02-01

    Full Text Available Sustainability and entrepreneurship are often regarded as binary concepts that have a tradeoff relationship, meaning that the higher the social and environmental consideration, the lower the private and economic benefits. The purpose of this study is to investigate the effect of individual sustainability orientation on opportunity recognition and sustainable entrepreneurship intention, and examine whether it has a tradeoff relationship with entrepreneurship orientation. The result of this study shows that sustainability orientation has a positive relationship with opportunity recognition and entrepreneurship intention related to sustainability. Analysis of the moderating effects of entrepreneurship orientation reveals the positive effect with sustainability orientation but negative effect with opportunity recognition on sustainable entrepreneurship intention. This study would suggest implications to entrepreneurs on how to balance sustainability and entrepreneurship and promote sustainability entrepreneurship.

  12. Detecting Neolithic Burial Mounds from LiDAR-Derived Elevation Data Using a Multi-Scale Approach and Machine Learning Techniques

    Directory of Open Access Journals (Sweden)

    Alexandre Guyot

    2018-02-01

    Full Text Available Airborne LiDAR technology is widely used in archaeology and over the past decade has emerged as an accurate tool to describe anthropomorphic landforms. Archaeological features are traditionally emphasised on a LiDAR-derived Digital Terrain Model (DTM using multiple Visualisation Techniques (VTs, and occasionally aided by automated feature detection or classification techniques. Such an approach offers limited results when applied to heterogeneous structures (different sizes, morphologies, which is often the case for archaeological remains that have been altered throughout the ages. This study proposes to overcome these limitations by developing a multi-scale analysis of topographic position combined with supervised machine learning algorithms (Random Forest. Rather than highlighting individual topographic anomalies, the multi-scalar approach allows archaeological features to be examined not only as individual objects, but within their broader spatial context. This innovative and straightforward method provides two levels of results: a composite image of topographic surface structure and a probability map of the presence of archaeological structures. The method was developed to detect and characterise megalithic funeral structures in the region of Carnac, the Bay of Quiberon, and the Gulf of Morbihan (France, which is currently considered for inclusion on the UNESCO World Heritage List. As a result, known archaeological sites have successfully been geo-referenced with a greater accuracy than before (even when located under dense vegetation and a ground-check confirmed the identification of a previously unknown Neolithic burial mound in the commune of Carnac.

  13. Detecting the multi-spin interaction of an XY spin chain by the geometric phase of a coupled qubit

    International Nuclear Information System (INIS)

    Zhang, Xiu-xing; Zhang, Ai-ping; Li, Fu-li

    2012-01-01

    We investigate geometric phase (GP) of a qubit symmetrically coupled to a XY spin chain with three-spin interaction in a transverse magnetic field. An analytical expression for the GP is found in the weak coupling limit. It is shown that the GP displays a sharp peak or dip around the quantum phase transition point of the spin chain. Without the three-spin interaction, the GP has a peak or dip around the critical point λ=1. If the three-spin interaction exists, the peak or dip position is obviously shifted away from the original position. This result reveals that the GP may be taken as an observable to detect both the existence and strength of multi-spin interaction in a spin chain. -- Highlights: ► Analytical expression for geometric phase (GP) of a qubit coupled to a spin chain is obtained. ► Relation between GP and multi-spin interaction is investigated. ► Detection of multi-spin interaction by means of GP is proposed.

  14. Reviewing Microgrids from a Multi-Agent Systems Perspective

    Directory of Open Access Journals (Sweden)

    Jorge J. Gomez-Sanz

    2014-05-01

    Full Text Available The construction of Smart Grids leads to the main question of what kind of intelligence such grids require and how to build it. Some authors choose an agent based solution to realize this intelligence. However, there may be some misunderstandings in the way this technology is being applied. This paper exposes some considerations of this subject, focusing on the Microgrid level, and shows a practical example through INGENIAS methodology, which is a methodology for the development of Agent Oriented systems that applies Model Driven Development techniques to produce fully functional Multi-Agent Systems.

  15. Multi-detection of preservatives in cheeses by liquid chromatography-tandem mass spectrometry.

    Science.gov (United States)

    Fuselli, Fabio; Guarino, Chiara; La Mantia, Alessandro; Longo, Lucia; Faberi, Angelo; Marianella, Rosa Maria

    2012-10-01

    The incorrect use of preservatives in cheeses may compromise food safety and damage consumers. According to the law, more than one preservative may be contemporarily used in cheeses. So a method for their contemporary detection may be useful for both manufacturers and control agencies quality control. In this research a liquid chromatography-tandem mass spectrometric with electrospray ionization method for the multi-determination of seven preservatives (benzoic acid, citric acid, hexamethylenetetramine, lysozyme, natamycin, nisin and sorbic acid) in cheese was developed. The preservatives were contemporarily extracted from cheese by a single procedure, and analyzed by RP-LC/ESI-MS/MS (Ion Trap) in positive ionization mode, with single reaction monitoring (SRM) acquisition. Three sample types (hard, pasta filata and fresh cheese) were used for method evaluation. Recoveries were mostly higher than 90%; MDLs ranged from 0.02 to 0.26 mgkg(-1), and MQLs were included between 0.07 and 0.88 mgkg(-1). Due to matrix effect, quantitation was performed by referring to a matrix matched calibration curve, for each cheese typology. This method was also applied to commercial cheese samples, with good results. It appears fast, reliable and suitable for both screening and confirmation of the presence and quantitation of the preservatives in a single, multi-detection analysis. Copyright © 2012 Elsevier B.V. All rights reserved.

  16. A Multi-Model Stereo Similarity Function Based on Monogenic Signal Analysis in Poisson Scale Space

    Directory of Open Access Journals (Sweden)

    Jinjun Li

    2011-01-01

    Full Text Available A stereo similarity function based on local multi-model monogenic image feature descriptors (LMFD is proposed to match interest points and estimate disparity map for stereo images. Local multi-model monogenic image features include local orientation and instantaneous phase of the gray monogenic signal, local color phase of the color monogenic signal, and local mean colors in the multiscale color monogenic signal framework. The gray monogenic signal, which is the extension of analytic signal to gray level image using Dirac operator and Laplace equation, consists of local amplitude, local orientation, and instantaneous phase of 2D image signal. The color monogenic signal is the extension of monogenic signal to color image based on Clifford algebras. The local color phase can be estimated by computing geometric product between the color monogenic signal and a unit reference vector in RGB color space. Experiment results on the synthetic and natural stereo images show the performance of the proposed approach.

  17. Multi-compartment microscopic diffusion imaging

    OpenAIRE

    Kaden, Enrico; Kelm, Nathaniel D.; Carson, Robert P.; Does, Mark D.; Alexander, Daniel C.

    2016-01-01

    This paper introduces a multi-compartment model for microscopic diffusion anisotropy imaging. The aim is to estimate microscopic features specific to the intra- and extra-neurite compartments in nervous tissue unconfounded by the effects of fibre crossings and orientation dispersion, which are ubiquitous in the brain. The proposed MRI method is based on the Spherical Mean Technique (SMT), which factors out the neurite orientation distribution and thus provides direct estimates of the microsco...

  18. Investigations for a multi-marker RT-PCR to improve sensitivity of disseminated tumor cell detection.

    NARCIS (Netherlands)

    Vlems, F.A.; Diepstra, J.H.S.; Cornelissen, I.M.; Ligtenberg, M.J.L.; Wobbes, Th.; Punt, C.J.A.; Krieken, J.H.J.M. van; Ruers, T.J.M.; Muijen, G.N.P. van

    2003-01-01

    BACKGROUND: In order to develop a multi-marker RT-PCR, which as such may be more sensitive than a single marker assay for the detection of disseminated tumor cells, we evaluated six RT-PCR markers: cytokeratin 20 (CK20), carcinoembryonic antigen (CEA), guanylyl cyclase C (GCC), epidermal growth

  19. Investigations for a multi-marker RT-PCR to improve sensitivity of disseminated tumor cell detection

    NARCIS (Netherlands)

    Vlems, F. A.; Diepstra, J. H. S.; Cornelissen, I. M. H. A.; Ligtenberg, M. J. L.; Wobbes, Th; Punt, C. J. A.; van Krieken, J. H. J. M.; Ruers, T. J. M.; van Muijen, G. N. P.

    2003-01-01

    In order to develop a multi-marker RT-PCR, which as such may be more sensitive than a single marker assay for the detection of disseminated tumor cells, we evaluated six RT-PCR markers: cytokeratin 20 (CK20), carcinoembryonic antigen (CEA), guanylyl cyclase C (GCC), epidermal growth factor receptor

  20. Suitability of magnetic single- and multi-core nanoparticles to detect protein binding with dynamic magnetic measurement techniques

    International Nuclear Information System (INIS)

    Remmer, Hilke; Dieckhoff, Jan; Schilling, Meinhard; Ludwig, Frank

    2015-01-01

    We investigated the binding of biotinylated proteins to various streptavidin functionalized magnetic nanoparticles with different dynamic magnetic measurement techniques to examine their potential for homogeneous bioassays. As particle systems, single-core nanoparticles with a nominal core diameter of 30 nm as well as multi-core nanoparticles with hydrodynamic sizes varying between nominally 60 nm and 100 nm were chosen. As experimental techniques, fluxgate magnetorelaxometry (MRX), complex ac susceptibility (ACS) and measurements of the phase lag between rotating field and sample magnetization are applied. MRX measurements are only suited for the detection of small analytes if the multivalency of functionalized nanoparticles and analytes causes cross-linking, thus forming larger aggregates. ACS measurements showed for all nanoparticle systems a shift of the imaginary part's maximum towards small frequencies. In rotating field measurements only the single-core nanoparticle systems with dominating Brownian mechanism exhibit an increase of the phase lag upon binding in the investigated frequency range. The coexistence of Brownian and Néel relaxation processes can cause a more complex phase lag change behavior, as demonstrated for multi-core nanoparticle systems. - Highlights: • Cealization of homogeneous magnetic bioassays using different magnetic techniques. • Comparison of single- and multi-core nanoparticle systems. • ac Susceptibility favorable for detection of small analytes. • Magnetorelaxometry favorable for detection of large analytes or cross-linking assays

  1. Fast Multi-Symbol Based Iterative Detectors for UWB Communications

    Directory of Open Access Journals (Sweden)

    Lottici Vincenzo

    2010-01-01

    Full Text Available Ultra-wideband (UWB impulse radios have shown great potential in wireless local area networks for localization, coexistence with other services, and low probability of interception and detection. However, low transmission power and high multipath effect make the detection of UWB signals challenging. Recently, multi-symbol based detection has caught attention for UWB communications because it provides good performance and does not require explicit channel estimation. Most of the existing multi-symbol based methods incur a higher computational cost than can be afforded in the envisioned UWB systems. In this paper, we propose an iterative multi-symbol based method that has low complexity and provides near optimal performance. Our method uses only one initial symbol to start and applies a decision directed approach to iteratively update a filter template and information symbols. Simulations show that our method converges in only a few iterations (less than 5, and that when the number of symbols increases, the performance of our method approaches that of the ideal Rake receiver.

  2. DataToText: A Consumer-Oriented Approach to Data Analysis

    Science.gov (United States)

    Kenny, David A.

    2010-01-01

    DataToText is a project developed where the user communicates the relevant information for an analysis and DataToText computer routine produces text output that describes in words, tables, and figures the results from the analyses. Two extended examples are given, one an example of a moderator analysis and the other an example of a dyadic data…

  3. A Multi-Agent Framework for Anomalies Detection on Distributed Firewalls Using Data Mining Techniques

    Science.gov (United States)

    Karoui, Kamel; Ftima, Fakher Ben; Ghezala, Henda Ben

    The Agents and Data Mining integration has emerged as a promising area for disributed problems solving. Applying this integration on distributed firewalls will facilitate the anomalies detection process. In this chapter, we present a set of algorithms and mining techniques to analyse, manage and detect anomalies on distributed firewalls' policy rules using the multi-agent approach; first, for each firewall, a static agent will execute a set of data mining techniques to generate a new set of efficient firewall policy rules. Then, a mobile agent will exploit these sets of optimized rules to detect eventual anomalies on a specific firewall (intra-firewalls anomalies) or between firewalls (inter-firewalls anomalies). An experimental case study will be presented to demonstrate the usefulness of our approach.

  4. Analysis of pharmaceutical impurities using multi-heartcutting 2D LC coupled with UV-charged aerosol MS detection.

    Science.gov (United States)

    Zhang, Kelly; Li, Yi; Tsang, Midco; Chetwyn, Nik P

    2013-09-01

    To overcome challenges in HPLC impurity analysis of pharmaceuticals, we developed an automated online multi-heartcutting 2D HPLC system with hyphenated UV-charged aerosol MS detection. The first dimension has a primary column and the second dimension has six orthogonal columns to enhance flexibility and selectivity. The two dimensions were interfaced by a pair of switching valves equipped with six trapping loops that allow multi-heartcutting of peaks of interest in the first dimension and also allow "peak parking." The hyphenated UV-charged aerosol MS detection provides comprehensive detection for compounds with and without UV chromophores, organics, and inorganics. It also provides structural information for impurity identification. A hidden degradation product that co-eluted with the drug main peak was revealed by RP × RP separation and thus enabled the stability-indicating method development. A poorly retained polar component with no UV chromophores was analyzed by RP × hydrophilic interaction liquid chromatography separation with charged aerosol detection. Furthermore, using this system, the structures of low-level impurities separated by a method using nonvolatile phosphate buffer were identified and tracked by MS in the second dimension. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  5. Developing Agent-Oriented Video Surveillance System through Agent-Oriented Methodology (AOM

    Directory of Open Access Journals (Sweden)

    Cheah Wai Shiang

    2016-12-01

    Full Text Available Agent-oriented methodology (AOM is a comprehensive and unified agent methodology for agent-oriented software development. Although AOM is claimed to be able to cope with a complex system development, it is still not yet determined up to what extent this may be true. Therefore, it is vital to conduct an investigation to validate this methodology. This paper presents the adoption of AOM in developing an agent-oriented video surveillance system (VSS. An intruder handling scenario is designed and implemented through AOM. AOM provides an alternative method to engineer a distributed security system in a systematic manner. It presents the security system at a holistic view; provides a better conceptualization of agent-oriented security system and supports rapid prototyping as well as simulation of video surveillance system.

  6. Multi-Unmanned Aerial Vehicle (UAV) Cooperative Fault Detection Employing Differential Global Positioning (DGPS), Inertial and Vision Sensors.

    Science.gov (United States)

    Heredia, Guillermo; Caballero, Fernando; Maza, Iván; Merino, Luis; Viguria, Antidio; Ollero, Aníbal

    2009-01-01

    This paper presents a method to increase the reliability of Unmanned Aerial Vehicle (UAV) sensor Fault Detection and Identification (FDI) in a multi-UAV context. Differential Global Positioning System (DGPS) and inertial sensors are used for sensor FDI in each UAV. The method uses additional position estimations that augment individual UAV FDI system. These additional estimations are obtained using images from the same planar scene taken from two different UAVs. Since accuracy and noise level of the estimation depends on several factors, dynamic replanning of the multi-UAV team can be used to obtain a better estimation in case of faults caused by slow growing errors of absolute position estimation that cannot be detected by using local FDI in the UAVs. Experimental results with data from two real UAVs are also presented.

  7. Massively Multi-core Acceleration of a Document-Similarity Classifier to Detect Web Attacks

    Energy Technology Data Exchange (ETDEWEB)

    Ulmer, C; Gokhale, M; Top, P; Gallagher, B; Eliassi-Rad, T

    2010-01-14

    This paper describes our approach to adapting a text document similarity classifier based on the Term Frequency Inverse Document Frequency (TFIDF) metric to two massively multi-core hardware platforms. The TFIDF classifier is used to detect web attacks in HTTP data. In our parallel hardware approaches, we design streaming, real time classifiers by simplifying the sequential algorithm and manipulating the classifier's model to allow decision information to be represented compactly. Parallel implementations on the Tilera 64-core System on Chip and the Xilinx Virtex 5-LX FPGA are presented. For the Tilera, we employ a reduced state machine to recognize dictionary terms without requiring explicit tokenization, and achieve throughput of 37MB/s at slightly reduced accuracy. For the FPGA, we have developed a set of software tools to help automate the process of converting training data to synthesizable hardware and to provide a means of trading off between accuracy and resource utilization. The Xilinx Virtex 5-LX implementation requires 0.2% of the memory used by the original algorithm. At 166MB/s (80X the software) the hardware implementation is able to achieve Gigabit network throughput at the same accuracy as the original algorithm.

  8. Exterior orientation of CBERS-2B imagery using multi-feature control and orbital data

    Science.gov (United States)

    Marcato Junior, J.; Tommaselli, A. M. G.

    2013-05-01

    The major contribution of this paper relates to the practical advantages of combining Ground Control Points (GCPs), Ground Control Lines (GCLs) and orbital data to estimate the exterior orientation parameters of images collected by CBERS-2B (China-Brazil Earth Resources Satellite) HRC (High-resolution Camera) and CCD (High-resolution CCD Camera) sensors. Although the CBERS-2B is no longer operational, its images are still being used in Brazil, and the next generations of the CBERS satellite will have sensors with similar technical features, which motivates the study presented in this paper. The mathematical models that relate the object and image spaces are based on collinearity (for points) and coplanarity (for lines) conditions. These models were created in an in-house developed software package called TMS (Triangulation with Multiple Sensors) with multi-feature control (GCPs and GCLs). Experiments on a block of four CBERS-2B HRC images and on one CBERS-2B CCD image were performed using both models. It was observed that the combination of GCPs and GCLs provided better bundle block adjustment results than conventional bundle adjustment using only GCPs. The results also demonstrate the advantages of using primarily orbital data when the number of control entities is reduced.

  9. An automated multi-scale network-based scheme for detection and location of seismic sources

    Science.gov (United States)

    Poiata, N.; Aden-Antoniow, F.; Satriano, C.; Bernard, P.; Vilotte, J. P.; Obara, K.

    2017-12-01

    We present a recently developed method - BackTrackBB (Poiata et al. 2016) - allowing to image energy radiation from different seismic sources (e.g., earthquakes, LFEs, tremors) in different tectonic environments using continuous seismic records. The method exploits multi-scale frequency-selective coherence in the wave field, recorded by regional seismic networks or local arrays. The detection and location scheme is based on space-time reconstruction of the seismic sources through an imaging function built from the sum of station-pair time-delay likelihood functions, projected onto theoretical 3D time-delay grids. This imaging function is interpreted as the location likelihood of the seismic source. A signal pre-processing step constructs a multi-band statistical representation of the non stationary signal, i.e. time series, by means of higher-order statistics or energy envelope characteristic functions. Such signal-processing is designed to detect in time signal transients - of different scales and a priori unknown predominant frequency - potentially associated with a variety of sources (e.g., earthquakes, LFE, tremors), and to improve the performance and the robustness of the detection-and-location location step. The initial detection-location, based on a single phase analysis with the P- or S-phase only, can then be improved recursively in a station selection scheme. This scheme - exploiting the 3-component records - makes use of P- and S-phase characteristic functions, extracted after a polarization analysis of the event waveforms, and combines the single phase imaging functions with the S-P differential imaging functions. The performance of the method is demonstrated here in different tectonic environments: (1) analysis of the one year long precursory phase of 2014 Iquique earthquake in Chile; (2) detection and location of tectonic tremor sources and low-frequency earthquakes during the multiple episodes of tectonic tremor activity in southwestern Japan.

  10. A bio-image sensor for simultaneous detection of multi-neurotransmitters.

    Science.gov (United States)

    Lee, You-Na; Okumura, Koichi; Horio, Tomoko; Iwata, Tatsuya; Takahashi, Kazuhiro; Hattori, Toshiaki; Sawada, Kazuaki

    2018-03-01

    We report here a new bio-image sensor for simultaneous detection of spatial and temporal distribution of multi-neurotransmitters. It consists of multiple enzyme-immobilized membranes on a 128 × 128 pixel array with read-out circuit. Apyrase and acetylcholinesterase (AChE), as selective elements, are used to recognize adenosine 5'-triphosphate (ATP) and acetylcholine (ACh), respectively. To enhance the spatial resolution, hydrogen ion (H + ) diffusion barrier layers are deposited on top of the bio-image sensor and demonstrated their prevention capability. The results are used to design the space among enzyme-immobilized pixels and the null H + sensor to minimize the undesired signal overlap by H + diffusion. Using this bio-image sensor, we can obtain H + diffusion-independent imaging of concentration gradients of ATP and ACh in real-time. The sensing characteristics, such as sensitivity and detection of limit, are determined experimentally. With the proposed bio-image sensor the possibility exists for customizable monitoring of the activities of various neurochemicals by using different kinds of proton-consuming or generating enzymes. Copyright © 2017 Elsevier B.V. All rights reserved.

  11. The Development of Citizen Oriented Informatics

    Directory of Open Access Journals (Sweden)

    Ion IVAN

    2010-01-01

    Full Text Available We define the concept of citizen-oriented computer application. Quality characteristics are set for computer applications developed in the conditions of citizen-oriented computing and outline the development cycle for these applications. It defines the conditions of existence for citizen-oriented applications. Average and long-term strategies are elaborated.

  12. Algorithm for detecting violations of traffic rules based on computer vision approaches

    Directory of Open Access Journals (Sweden)

    Ibadov Samir

    2017-01-01

    Full Text Available We propose a new algorithm for automatic detect violations of traffic rules for improving the people safety on the unregulated pedestrian crossing. The algorithm uses multi-step proceedings. They are zebra detection, cars detection, and pedestrian detection. For car detection, we use faster R-CNN deep learning tool. The algorithm shows promising results in the detection violations of traffic rules.

  13. Anomalous Signal Detection in ELF Band Electromagnetic Wave using Multi-layer Neural Network with Wavelet Decomposition

    Science.gov (United States)

    Itai, Akitoshi; Yasukawa, Hiroshi; Takumi, Ichi; Hata, Masayasu

    It is well known that electromagnetic waves radiated from the earth's crust are useful for predicting earthquakes. We analyze the electromagnetic waves received at the extremely low frequency band of 223Hz. These observed signals contain the seismic radiation from the earth's crust, but also include several undesired signals. Our research focuses on the signal detection technique to identify an anomalous signal corresponding to the seismic radiation in the observed signal. Conventional anomalous signal detections lack a wide applicability due to their assumptions, e.g. the digital data have to be observed at the same time or the same sensor. In order to overcome the limitation related to the observed signal, we proposed the anomalous signals detection based on a multi-layer neural network which is trained by digital data observed during a span of a day. In the neural network approach, training data do not need to be recorded at the same place or the same time. However, some noises, which have a large amplitude, are detected as the anomalous signal. This paper develops a multi-layer neural network to decrease the false detection of the anomalous signal from the electromagnetic wave. The training data for the proposed network is the decomposed signal of the observed signal during several days, since the seismic radiations are often recorded from several days to a couple of weeks. Results show that the proposed neural network is useful to achieve the accurate detection of the anomalous signal that indicates seismic activity.

  14. From drafting guideline to error detection: Automating style checking for legislative texts

    OpenAIRE

    Höfler Stefan; Sugisaki Kyoko

    2012-01-01

    This paper reports on the development of methods for the automated detection of violations of style guidelines for legislative texts, and their implementation in a prototypical tool. To this aim, the approach of error modelling employed in automated style checkers for technical writing is enhanced to meet the requirements of legislative editing. The paper identifies and discusses the two main sets of challenges that have to be tackled in this process: (i) the provision of domain-specific NLP ...

  15. Multi-slice ultrasound image calibration of an intelligent skin-marker for soft tissue artefact compensation.

    Science.gov (United States)

    Masum, M A; Pickering, M R; Lambert, A J; Scarvell, J M; Smith, P N

    2017-09-06

    In this paper, a novel multi-slice ultrasound (US) image calibration of an intelligent skin-marker used for soft tissue artefact compensation is proposed to align and orient image slices in an exact H-shaped pattern. Multi-slice calibration is complex, however, in the proposed method, a phantom based visual alignment followed by transform parameters estimation greatly reduces the complexity and provides sufficient accuracy. In this approach, the Hough Transform (HT) is used to further enhance the image features which originate from the image feature enhancing elements integrated into the physical phantom model, thus reducing feature detection uncertainty. In this framework, slice by slice image alignment and calibration are carried out and this provides manual ease and convenience. Copyright © 2016 Elsevier Ltd. All rights reserved.

  16. Multi-channel polarized thermal emitter

    Science.gov (United States)

    Lee, Jae-Hwang; Ho, Kai-Ming; Constant, Kristen P

    2013-07-16

    A multi-channel polarized thermal emitter (PTE) is presented. The multi-channel PTE can emit polarized thermal radiation without using a polarizer at normal emergence. The multi-channel PTE consists of two layers of metallic gratings on a monolithic and homogeneous metallic plate. It can be fabricated by a low-cost soft lithography technique called two-polymer microtransfer molding. The spectral positions of the mid-infrared (MIR) radiation peaks can be tuned by changing the periodicity of the gratings and the spectral separation between peaks are tuned by changing the mutual angle between the orientations of the two gratings.

  17. Four-spacecraft determination of magnetopause orientation, motion and thickness: comparison with results from single-spacecraft methods

    Directory of Open Access Journals (Sweden)

    S. E. Haaland

    2004-04-01

    Full Text Available In this paper, we use Cluster data from one magnetopause event on 5 July 2001 to compare predictions from various methods for determination of the velocity, orientation, and thickness of the magnetopause current layer. We employ established as well as new multi-spacecraft techniques, in which time differences between the crossings by the four spacecraft, along with the duration of each crossing, are used to calculate magnetopause speed, normal vector, and width. The timing is based on data from either the Cluster Magnetic Field Experiment (FGM or the Electric Field Experiment (EFW instruments. The multi-spacecraft results are compared with those derived from various single-spacecraft techniques, including minimum-variance analysis of the magnetic field and deHoffmann-Teller, as well as Minimum-Faraday-Residue analysis of plasma velocities and magnetic fields measured during the crossings. In order to improve the overall consistency between multi- and single-spacecraft results, we have also explored the use of hybrid techniques, in which timing information from the four spacecraft is combined with certain limited results from single-spacecraft methods, the remaining results being left for consistency checks. The results show good agreement between magnetopause orientations derived from appropriately chosen single-spacecraft techniques and those obtained from multi-spacecraft timing. The agreement between magnetopause speeds derived from single- and multi-spacecraft methods is quantitatively somewhat less good but it is evident that the speed can change substantially from one crossing to the next within an event. The magnetopause thickness varied substantially from one crossing to the next, within an event. It ranged from 5 to 10 ion gyroradii. The density profile was sharper than the magnetic profile: most of the density change occured in the earthward half of the magnetopause.

    Key words. Magnetospheric physics (magnetopause, cusp and

  18. Multi-state autonomous drilling for lunar exploration

    Directory of Open Access Journals (Sweden)

    Chen Chongbin

    2016-10-01

    Full Text Available Due to the lack of information of subsurface lunar regolith stratification which varies along depth, the drilling device may encounter lunar soil and lunar rock randomly in the drilling process. To meet the load safety requirements of unmanned sampling mission under limited orbital resources, the control strategy of autonomous drilling should adapt to the indeterminable lunar environments. Based on the analysis of two types of typical drilling media (i.e., lunar soil and lunar rock, this paper proposes a multi-state control strategy for autonomous lunar drilling. To represent the working circumstances in the lunar subsurface and reduce the complexity of the control algorithm, lunar drilling process was categorized into three drilling states: the interface detection, initiation of drilling parameters for recognition and drilling medium recognition. Support vector machine (SVM and continuous wavelet transform were employed for the online recognition of drilling media and interface, respectively. Finite state machine was utilized to control the transition among different drilling states. To verify the effectiveness of the multi-state control strategy, drilling experiments were implemented with multi-layered drilling media constructed by lunar soil simulant and lunar rock simulant. The results reveal that the multi-state control method is capable of detecting drilling state variation and adjusting drilling parameters timely under vibration interferences. The multi-state control method provides a feasible reference for the control of extraterrestrial autonomous drilling.

  19. The Survey of Relationship Between Religious Orientation and Happiness Among the Elderly Man and Woman in Tehran

    Directory of Open Access Journals (Sweden)

    Dawood Ghaderi

    2011-01-01

    Full Text Available Objectives: The aim of this study was to survey relationship between religious orientation and happiness in elderly man and woman in Tehran. Methods & Materials: The present study was descriptive and causal- Comparative. In order to survey the relationship between religious orientation and happiness among the elderly men and women in Tehran 389 aged people above 60 years including 247 men and 142 women were selected by multi stage cluster sampling. The research instruments were Allport religion orientation questionnaire and happiness inventory of Oxford. Results: The result showed that religion orientation and happiness in elderly man and woman (P<0/01 have significant positive relationship. The amount of happiness among these who had religion internal orientation were further that who had external religions orientation (P<0.01. The relationship between religion external orientation and happiness in both elderly men and women was not significant. The amount of happiness among old women was significantly further that old men (P<0.01. The elderly woman in two internal and external religion orientation in general earn higher markers than elderly men (P<0.01. Conclusion: The result shows that there is positive relationship between religion orientation and happiness among elderly men and women. We conclude that people with internal religion orientation were happier in both genders. On the confirm of most studies in the field of religion psychology we could conclude that the elderly women are more religious than elderly men. More research in the field of studied varieties can represent brighter data.

  20. Accuracy assessment of tree crown detection using local maxima and multi-resolution segmentation

    International Nuclear Information System (INIS)

    Khalid, N; Hamid, J R A; Latif, Z A

    2014-01-01

    Diversity of trees forms an important component in the forest ecosystems and needs proper inventories to assist the forest personnel in their daily activities. However, tree parameter measurements are often constrained by physical inaccessibility to site locations, high costs, and time. With the advancement in remote sensing technology, such as the provision of higher spatial and spectral resolution of imagery, a number of developed algorithms fulfil the needs of accurate tree inventories information in a cost effective and timely manner over larger forest areas. This study intends to generate tree distribution map in Ampang Forest Reserve using the Local Maxima and Multi-Resolution image segmentation algorithm. The utilization of recent worldview-2 imagery with Local Maxima and Multi-Resolution image segmentation proves to be capable of detecting and delineating the tree crown in its accurate standing position

  1. Learning history by composing synthesis texts: Effects of an instructional programme on learning, reading and writing processes, and text quality

    NARCIS (Netherlands)

    Martínez, I.; Mateos, M.; Martín, E.; Rijlaarsdam, G.

    2015-01-01

    The aim of the present study was to improve learning from texts via strategies that train students how to process synthesis texts. Processing such texts requires goal-oriented interaction between reading and writing activities. The participants were 62 sixth-grade students, 33 in the experimental

  2. Visual search of illusory contours: Shape and orientation effects

    Directory of Open Access Journals (Sweden)

    Gvozdenović Vasilije

    2008-01-01

    Full Text Available Illusory contours are specific class of visual stimuli that represent stimuli configurations perceived as integral irrespective of the fact that they are given in fragmented uncompleted wholes. Due to their specific features, illusory contours gained much attention in last decade representing prototype of stimuli used in investigations focused on binding problem. On the other side, investigations of illusory contours are related to problem of the level of their visual processing. Neurophysiologic studies show that processing of illusory contours proceed relatively early, on the V2 level, on the other hand most of experimental studies claim that illusory contours are perceived with engagement of visual attention, binding their elements to whole percept. This research is focused on two experiments in which visual search of illusory contours are based on shape and orientation. The main experimental procedure evolved the task proposed by Bravo and Nakayama where instead of detection, subjects were performing identification of one among two possible targets. In the first experiment subjects detected the presence of illusory square or illusory triangle, while in the second experiment subject were detecting two different orientations of illusory triangle. The results are interpreted in terms of visual search and feature integration theory. Beside the type of visual search task, search type proved to be dependent of specific features of illusory shapes which further complicate theoretical interpretation of the level of their perception.

  3. Contribution to the detection of changes in multi-modal 3D MRI sequences

    International Nuclear Information System (INIS)

    Bosc, Marcel

    2003-01-01

    This research thesis reports the study of automatic techniques for the detection of changes in image sequences of brain magnetic resonance imagery (MRI), and more particularly the study of localised intensity changes occurring during pathological evolutions such as evolutions of lesions into multiple sclerosis. Thus, this work focused on the development of image processing tools allowing to decide whether changes are statistically significant or not. The author developed automatic techniques of identification and correction of the main artefacts (position, deformations, intensity variation, and so on), and proposes an original technique for cortex segmentation which introduced anatomic information for an improved automatic detection. The developed change detection system has been assessed within the frame of the study of the evolution of lesions of multiple sclerosis. Performance have been determined on a large number of multi-modal images, and the automatic system has shown better performance than a human expert [fr

  4. Performance improvement of multi-class detection using greedy algorithm for Viola-Jones cascade selection

    Science.gov (United States)

    Tereshin, Alexander A.; Usilin, Sergey A.; Arlazarov, Vladimir V.

    2018-04-01

    This paper aims to study the problem of multi-class object detection in video stream with Viola-Jones cascades. An adaptive algorithm for selecting Viola-Jones cascade based on greedy choice strategy in solution of the N-armed bandit problem is proposed. The efficiency of the algorithm on the problem of detection and recognition of the bank card logos in the video stream is shown. The proposed algorithm can be effectively used in documents localization and identification, recognition of road scene elements, localization and tracking of the lengthy objects , and for solving other problems of rigid object detection in a heterogeneous data flows. The computational efficiency of the algorithm makes it possible to use it both on personal computers and on mobile devices based on processors with low power consumption.

  5. Computational simulation of biomolecules transport with multi-physics near microchannel surface for development of biomolecules-detection devices.

    Science.gov (United States)

    Suzuki, Yuma; Shimizu, Tetsuhide; Yang, Ming

    2017-01-01

    The quantitative evaluation of the biomolecules transport with multi-physics in nano/micro scale is demanded in order to optimize the design of microfluidics device for the biomolecules detection with high detection sensitivity and rapid diagnosis. This paper aimed to investigate the effectivity of the computational simulation using the numerical model of the biomolecules transport with multi-physics near a microchannel surface on the development of biomolecules-detection devices. The biomolecules transport with fluid drag force, electric double layer (EDL) force, and van der Waals force was modeled by Newtonian Equation of motion. The model validity was verified in the influence of ion strength and flow velocity on biomolecules distribution near the surface compared with experimental results of previous studies. The influence of acting forces on its distribution near the surface was investigated by the simulation. The trend of its distribution to ion strength and flow velocity was agreement with the experimental result by the combination of all acting forces. Furthermore, EDL force dominantly influenced its distribution near its surface compared with fluid drag force except for the case of high velocity and low ion strength. The knowledges from the simulation might be useful for the design of biomolecules-detection devices and the simulation can be expected to be applied on its development as the design tool for high detection sensitivity and rapid diagnosis in the future.

  6. Multi-person localization and orientation estimation in volumetric scene reconstructions

    NARCIS (Netherlands)

    Liem, M.C.

    2014-01-01

    Accurate localization of persons and estimation of their pose are important topics in current-day computer vision research. As part of the pose estimation, estimating the body orientation of a person (i.e. rotation around torso major axis) conveys important information about the person's current

  7. Radiographic film orientation in radiotherapy dosimetry

    International Nuclear Information System (INIS)

    Suchowerska, N.; Davison, A.; Drew, J.; Metcalfe, P.

    1996-01-01

    Since the discovery of x-rays, film has been used as a detection medium for radiation. More recently radiographic film has become established as a practical tool for the measurement of dose distribution in radiotherapy. The accuracy and reproducibility of film dosimetry depends on photon energy, processing conditions and film plane orientation. The relationship between photon energy, processing conditions and film dosimetry accuracy has been studied. The role of film plane orientation is still controversial. The current work aims to clarify the effects film plane orientation has on film dosimetry. Poster 205. (author)

  8. Probe Sensor Using Nanostructured Multi-Walled Carbon Nanotube Yarn for Selective and Sensitive Detection of Dopamine

    Directory of Open Access Journals (Sweden)

    Wed Al-Graiti

    2017-04-01

    Full Text Available The demands for electrochemical sensor materials with high strength and durability in physiological conditions continue to grow and novel approaches are being enabled by the advent of new electromaterials and novel fabrication technologies. Herein, we demonstrate a probe-style electrochemical sensor using highly flexible and conductive multi-walled carbon nanotubes (MWNT yarns. The MWNT yarn-based sensors can be fabricated onto micro Pt-wire with a controlled diameter varying from 100 to 300 µm, and then further modified with Nafion via a dip-coating approach. The fabricated micro-sized sensors were characterized by electron microscopy, Raman, FTIR, electrical, and electrochemical measurements. For the first time, the MWNT/Nafion yarn-based probe sensors have been assembled and assessed for high-performance dopamine sensing, showing a significant improvement in both sensitivity and selectivity in dopamine detection in presence of ascorbic acid and uric acid. It offers the potential to be further developed as implantable probe sensors.

  9. Detection of pneumonia using free-text radiology reports in the BioSense system.

    Science.gov (United States)

    Asatryan, Armenak; Benoit, Stephen; Ma, Haobo; English, Roseanne; Elkin, Peter; Tokars, Jerome

    2011-01-01

    Near real-time disease detection using electronic data sources is a public health priority. Detecting pneumonia is particularly important because it is the manifesting disease of several bioterrorism agents as well as a complication of influenza, including avian and novel H1N1 strains. Text radiology reports are available earlier than physician diagnoses and so could be integral to rapid detection of pneumonia. We performed a pilot study to determine which keywords present in text radiology reports are most highly associated with pneumonia diagnosis. Electronic radiology text reports from 11 hospitals from February 1, 2006 through December 31, 2007 were used. We created a computerized algorithm that searched for selected keywords ("airspace disease", "consolidation", "density", "infiltrate", "opacity", and "pneumonia"), differentiated between clinical history and radiographic findings, and accounted for negations and double negations; this algorithm was tested on a sample of 350 radiology reports. We used the algorithm to study 189,246 chest radiographs, searching for the keywords and determining their association with a final International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) diagnosis of pneumonia. Performance of the search algorithm in finding keywords, and association of the keywords with a pneumonia diagnosis. In the sample of 350 radiographs, the search algorithm was highly successful in identifying the selected keywords (sensitivity 98.5%, specificity 100%). Analysis of the 189,246 radiographs showed that the keyword "pneumonia" was the strongest predictor of an ICD-9-CM diagnosis of pneumonia (adjusted odds ratio 11.8) while "density" was the weakest (adjusted odds ratio 1.5). In general, the most highly associated keyword present in the report, regardless of whether a less highly associated keyword was also present, was the best predictor of a diagnosis of pneumonia. Empirical methods may assist in finding radiology

  10. DESIGN of MICRO CANTILEVER BEAM for VAPOUR DETECTION USING COMSOL MULTI PHYSICS SOFTWARE

    OpenAIRE

    Sivacoumar R; Parvathy JM; Pratishtha Deep

    2015-01-01

    This paper gives an overview of micro cantilever beam of various shapes and materials for vapour detection. The design of micro cantilever beam, analysis and simulation is done for each shape. The simulation is done using COMSOL Multi physics software using structural mechanics and chemical module. The simulation results of applied force and resulting Eigen frequencies will be analyzed for different beam structures. The vapour analysis is done using flow cell that consists of chemical pill...

  11. Robust and Accurate Image-Based Georeferencing Exploiting Relative Orientation Constraints

    Science.gov (United States)

    Cavegn, S.; Blaser, S.; Nebiker, S.; Haala, N.

    2018-05-01

    Urban environments with extended areas of poor GNSS coverage as well as indoor spaces that often rely on real-time SLAM algorithms for camera pose estimation require sophisticated georeferencing in order to fulfill our high requirements of a few centimeters for absolute 3D point measurement accuracies. Since we focus on image-based mobile mapping, we extended the structure-from-motion pipeline COLMAP with georeferencing capabilities by integrating exterior orientation parameters from direct sensor orientation or SLAM as well as ground control points into bundle adjustment. Furthermore, we exploit constraints for relative orientation parameters among all cameras in bundle adjustment, which leads to a significant robustness and accuracy increase especially by incorporating highly redundant multi-view image sequences. We evaluated our integrated georeferencing approach on two data sets, one captured outdoors by a vehicle-based multi-stereo mobile mapping system and the other captured indoors by a portable panoramic mobile mapping system. We obtained mean RMSE values for check point residuals between image-based georeferencing and tachymetry of 2 cm in an indoor area, and 3 cm in an urban environment where the measurement distances are a multiple compared to indoors. Moreover, in comparison to a solely image-based procedure, our integrated georeferencing approach showed a consistent accuracy increase by a factor of 2-3 at our outdoor test site. Due to pre-calibrated relative orientation parameters, images of all camera heads were oriented correctly in our challenging indoor environment. By performing self-calibration of relative orientation parameters among respective cameras of our vehicle-based mobile mapping system, remaining inaccuracies from suboptimal test field calibration were successfully compensated.

  12. Automated multi-lesion detection for referable diabetic retinopathy in indigenous health care.

    Science.gov (United States)

    Pires, Ramon; Carvalho, Tiago; Spurling, Geoffrey; Goldenstein, Siome; Wainer, Jacques; Luckie, Alan; Jelinek, Herbert F; Rocha, Anderson

    2015-01-01

    Diabetic Retinopathy (DR) is a complication of diabetes mellitus that affects more than one-quarter of the population with diabetes, and can lead to blindness if not discovered in time. An automated screening enables the identification of patients who need further medical attention. This study aimed to classify retinal images of Aboriginal and Torres Strait Islander peoples utilizing an automated computer-based multi-lesion eye screening program for diabetic retinopathy. The multi-lesion classifier was trained on 1,014 images from the São Paulo Eye Hospital and tested on retinal images containing no DR-related lesion, single lesions, or multiple types of lesions from the Inala Aboriginal and Torres Strait Islander health care centre. The automated multi-lesion classifier has the potential to enhance the efficiency of clinical practice delivering diabetic retinopathy screening. Our program does not necessitate image samples for training from any specific ethnic group or population being assessed and is independent of image pre- or post-processing to identify retinal lesions. In this Aboriginal and Torres Strait Islander population, the program achieved 100% sensitivity and 88.9% specificity in identifying bright lesions, while detection of red lesions achieved a sensitivity of 67% and specificity of 95%. When both bright and red lesions were present, 100% sensitivity with 88.9% specificity was obtained. All results obtained with this automated screening program meet WHO standards for diabetic retinopathy screening.

  13. Detecting Multi-layered Forest Stands Using High Density Airborne LiDAR Data. GI_Forum|GI_Forum 2015 – Geospatial Minds for Society|

    OpenAIRE

    Schultz, Alfred; Mund, Jan-Peter; Körner, Michael; Wilke, Robert

    2016-01-01

    Since two decades, the use of terrestrial laser scanning (TLS) and Airborne Light Detection and Ranging (LIDAR) has become very prominent in analysing 3D forest structures (AKAY et al. 2009). The potential of full waveform analysis of high density Airborne LiDAR data (ALS) for the detection and structural analysis of multi-layered forest stands is not yet well investigated (JASKIERNIAK et al. 2011), although ALS data provide exact information on tree heights of multi-layered forest stands usi...

  14. TeraSCREEN: multi-frequency multi-mode Terahertz screening for border checks

    Science.gov (United States)

    Alexander, Naomi E.; Alderman, Byron; Allona, Fernando; Frijlink, Peter; Gonzalo, Ramón; Hägelen, Manfred; Ibáñez, Asier; Krozer, Viktor; Langford, Marian L.; Limiti, Ernesto; Platt, Duncan; Schikora, Marek; Wang, Hui; Weber, Marc Andree

    2014-06-01

    The challenge for any security screening system is to identify potentially harmful objects such as weapons and explosives concealed under clothing. Classical border and security checkpoints are no longer capable of fulfilling the demands of today's ever growing security requirements, especially with respect to the high throughput generally required which entails a high detection rate of threat material and a low false alarm rate. TeraSCREEN proposes to develop an innovative concept of multi-frequency multi-mode Terahertz and millimeter-wave detection with new automatic detection and classification functionalities. The system developed will demonstrate, at a live control point, the safe automatic detection and classification of objects concealed under clothing, whilst respecting privacy and increasing current throughput rates. This innovative screening system will combine multi-frequency, multi-mode images taken by passive and active subsystems which will scan the subjects and obtain complementary spatial and spectral information, thus allowing for automatic threat recognition. The TeraSCREEN project, which will run from 2013 to 2016, has received funding from the European Union's Seventh Framework Programme under the Security Call. This paper will describe the project objectives and approach.

  15. Multi-branched gold nanostars with fractal structure for SERS detection of the pesticide thiram

    Science.gov (United States)

    Zhu, Jian; Liu, Mei-Jin; Li, Jian-Jun; Li, Xin; Zhao, Jun-Wu

    2018-01-01

    The surface-enhanced Raman scattering (SERS) activity of multi-branched gold nanostars with fractal structure has been investigated for trace detection of pesticide thiram. Raman spectrum results show that the gold nanostars substrate can produce about 102 fold stronger signal than the thiram alone with the thiram concentration increase of 103 times and 1.4 fold stronger signal than the gold nanostars without fractal feature. In the detection procedure, the most prominent SERS peak at 1376 cm- 1 has been chosen to characterize and quantify the concentration of thiram. Experimental results indicate this Raman substrate based on fractal gold nanostars exhibits excellent selective probing performance for thiram with a detection limit as low as 10- 10 M in solution and 0.24 ng/cm2 in apple peels. Interference experiment results show that the effects from the interfering pesticides could be neglected in the detection procedure. Therefore, the gold nanostars as a SERS substrate have excellent sensitivity and selectivity.

  16. Absolute distance measurement by dual-comb interferometry with multi-channel digital lock-in phase detection

    International Nuclear Information System (INIS)

    Yang, Ruitao; Pollinger, Florian; Meiners-Hagen, Karl; Krystek, Michael; Bosse, Harald; Tan, Jiubin

    2015-01-01

    We present a dual-comb-based heterodyne multi-wavelength absolute interferometer capable of long distance measurements. The phase information of the various comb modes is extracted in parallel by a multi-channel digital lock-in phase detection scheme. Several synthetic wavelengths of the same order are constructed and the corresponding phases are averaged to deduce the absolute lengths with significantly reduced uncertainty. Comparison experiments with an incremental HeNe reference interferometer show a combined relative measurement uncertainty of 5.3 × 10 −7 at a measurement distance of 20 m. Combining the advantage of synthetic wavelength interferometry and dual-comb interferometry, our compact and simple approach provides sufficient precision for many industrial applications. (paper)

  17. Absolute distance measurement by dual-comb interferometry with multi-channel digital lock-in phase detection

    Science.gov (United States)

    Yang, Ruitao; Pollinger, Florian; Meiners-Hagen, Karl; Krystek, Michael; Tan, Jiubin; Bosse, Harald

    2015-08-01

    We present a dual-comb-based heterodyne multi-wavelength absolute interferometer capable of long distance measurements. The phase information of the various comb modes is extracted in parallel by a multi-channel digital lock-in phase detection scheme. Several synthetic wavelengths of the same order are constructed and the corresponding phases are averaged to deduce the absolute lengths with significantly reduced uncertainty. Comparison experiments with an incremental HeNe reference interferometer show a combined relative measurement uncertainty of 5.3 × 10-7 at a measurement distance of 20 m. Combining the advantage of synthetic wavelength interferometry and dual-comb interferometry, our compact and simple approach provides sufficient precision for many industrial applications.

  18. Application of multi-step excitation schemes for detection of actinides and lanthanides in solutions by luminescence/chemiluminescence laser spectroscopy

    Energy Technology Data Exchange (ETDEWEB)

    Izosimov, I. [Joint Institute for Nuclear Research, Joliot Curie 6, Dubna 141980 (Russian Federation)

    2016-07-01

    The use of laser radiation with tunable wavelength allows the selective excitation of actinide/lanthanide species with subsequent registration of luminescence/chemiluminescence for their detection. This work is devoted to applications of the time-resolved laser-induced luminescence spectroscopy and time-resolved laser-induced chemiluminescence spectroscopy for the detection of lanthanides and actinides. Results of the experiments on U, Eu, and Sm detection by TRLIF (Time Resolved Laser Induced Fluorescence) method in blood plasma and urine are presented. Data on luminol chemiluminescence in solutions containing Sm(III), U(IV), and Pu(IV) are analyzed. It is shown that appropriate selectivity of lanthanide/actinide detection can be reached when chemiluminescence is initiated by transitions within 4f- or 5f-electron shell of lanthanide/actinide ions corresponding to the visible spectral range. In this case chemiluminescence of chemiluminogen (luminol) arises when the ion of f element is excited by multi-quantum absorption of visible light. The multi-photon scheme of chemiluminescence excitation makes chemiluminescence not only a highly sensitive but also a highly selective tool for the detection of lanthanide/actinide species in solutions. (author)

  19. Harnessing the Power of Text Mining for the Detection of Abusive Content in Social Media

    OpenAIRE

    Chen, Hao; McKeever, Susan; Delany, Sarah Jane

    2016-01-01

    Abstract The issues of cyberbullying and online harassment have gained considerable coverage in the last number of years. Social media providers need to be able to detect abusive content both accurately and efficiently in order to protect their users. Our aim is to investigate the application of core text mining techniques for the automatic detection of abusive content across a range of social media sources include blogs, forums, media-sharing, Q&A and chat - using datasets from Twitter, YouT...

  20. Handheld Multi-Gas Meters Assessment Report

    Energy Technology Data Exchange (ETDEWEB)

    Williams, Gustavious [Brigham Young Univ., Provo, UT (United States); Wald-Hopkins, Mark David [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Obrey, Stephen J. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Akhadov, Valida Dushdurova [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2016-06-27

    Handheld multi-gas meters (MGMs) are equipped with sensors to monitor oxygen (O2) levels and additional sensors to detect the presence of combustible or toxic gases in the environment. This report is limited to operational response-type MGMs that include at least four different sensors. These sensors can vary by type and by the monitored chemical. In real time, the sensors report the concentration of monitored gases in the atmosphere near the MGM. In April 2016 the System Assessment and Validation for Emergency Responders (SAVER) Program conducted an operationally-oriented assessment of MGMs. Five MGMs were assessed by emergency responders. The criteria and scenarios used in this assessment were derived from the results of a focus group of emergency responders with experience in using MGMs. The assessment addressed 16 evaluation criteria in four SAVER categories: Usability, Capability, Maintainability, and Deployability.

  1. Data Rods: High Speed, Time-Series Analysis of Massive Cryospheric Data Sets Using Object-Oriented Database Methods

    Science.gov (United States)

    Liang, Y.; Gallaher, D. W.; Grant, G.; Lv, Q.

    2011-12-01

    Change over time, is the central driver of climate change detection. The goal is to diagnose the underlying causes, and make projections into the future. In an effort to optimize this process we have developed the Data Rod model, an object-oriented approach that provides the ability to query grid cell changes and their relationships to neighboring grid cells through time. The time series data is organized in time-centric structures called "data rods." A single data rod can be pictured as the multi-spectral data history at one grid cell: a vertical column of data through time. This resolves the long-standing problem of managing time-series data and opens new possibilities for temporal data analysis. This structure enables rapid time- centric analysis at any grid cell across multiple sensors and satellite platforms. Collections of data rods can be spatially and temporally filtered, statistically analyzed, and aggregated for use with pattern matching algorithms. Likewise, individual image pixels can be extracted to generate multi-spectral imagery at any spatial and temporal location. The Data Rods project has created a series of prototype databases to store and analyze massive datasets containing multi-modality remote sensing data. Using object-oriented technology, this method overcomes the operational limitations of traditional relational databases. To demonstrate the speed and efficiency of time-centric analysis using the Data Rods model, we have developed a sea ice detection algorithm. This application determines the concentration of sea ice in a small spatial region across a long temporal window. If performed using traditional analytical techniques, this task would typically require extensive data downloads and spatial filtering. Using Data Rods databases, the exact spatio-temporal data set is immediately available No extraneous data is downloaded, and all selected data querying occurs transparently on the server side. Moreover, fundamental statistical

  2. SAW Classification Algorithm for Chinese Text Classification

    OpenAIRE

    Xiaoli Guo; Huiyu Sun; Tiehua Zhou; Ling Wang; Zhaoyang Qu; Jiannan Zang

    2015-01-01

    Considering the explosive growth of data, the increased amount of text data’s effect on the performance of text categorization forward the need for higher requirements, such that the existing classification method cannot be satisfied. Based on the study of existing text classification technology and semantics, this paper puts forward a kind of Chinese text classification oriented SAW (Structural Auxiliary Word) algorithm. The algorithm uses the special space effect of Chinese text where words...

  3. Towards aspect-oriented functional–structural plant modelling

    Science.gov (United States)

    Cieslak, Mikolaj; Seleznyova, Alla N.; Prusinkiewicz, Przemyslaw; Hanan, Jim

    2011-01-01

    Background and Aims Functional–structural plant models (FSPMs) are used to integrate knowledge and test hypotheses of plant behaviour, and to aid in the development of decision support systems. A significant amount of effort is being put into providing a sound methodology for building them. Standard techniques, such as procedural or object-oriented programming, are not suited for clearly separating aspects of plant function that criss-cross between different components of plant structure, which makes it difficult to reuse and share their implementations. The aim of this paper is to present an aspect-oriented programming approach that helps to overcome this difficulty. Methods The L-system-based plant modelling language L+C was used to develop an aspect-oriented approach to plant modelling based on multi-modules. Each element of the plant structure was represented by a sequence of L-system modules (rather than a single module), with each module representing an aspect of the element's function. Separate sets of productions were used for modelling each aspect, with context-sensitive rules facilitated by local lists of modules to consider/ignore. Aspect weaving or communication between aspects was made possible through the use of pseudo-L-systems, where the strict-predecessor of a production rule was specified as a multi-module. Key Results The new approach was used to integrate previously modelled aspects of carbon dynamics, apical dominance and biomechanics with a model of a developing kiwifruit shoot. These aspects were specified independently and their implementation was based on source code provided by the original authors without major changes. Conclusions This new aspect-oriented approach to plant modelling is well suited for studying complex phenomena in plant science, because it can be used to integrate separate models of individual aspects of plant development and function, both previously constructed and new, into clearly organized, comprehensive FSPMs. In

  4. Towards aspect-oriented functional--structural plant modelling.

    Science.gov (United States)

    Cieslak, Mikolaj; Seleznyova, Alla N; Prusinkiewicz, Przemyslaw; Hanan, Jim

    2011-10-01

    Functional-structural plant models (FSPMs) are used to integrate knowledge and test hypotheses of plant behaviour, and to aid in the development of decision support systems. A significant amount of effort is being put into providing a sound methodology for building them. Standard techniques, such as procedural or object-oriented programming, are not suited for clearly separating aspects of plant function that criss-cross between different components of plant structure, which makes it difficult to reuse and share their implementations. The aim of this paper is to present an aspect-oriented programming approach that helps to overcome this difficulty. The L-system-based plant modelling language L+C was used to develop an aspect-oriented approach to plant modelling based on multi-modules. Each element of the plant structure was represented by a sequence of L-system modules (rather than a single module), with each module representing an aspect of the element's function. Separate sets of productions were used for modelling each aspect, with context-sensitive rules facilitated by local lists of modules to consider/ignore. Aspect weaving or communication between aspects was made possible through the use of pseudo-L-systems, where the strict-predecessor of a production rule was specified as a multi-module. The new approach was used to integrate previously modelled aspects of carbon dynamics, apical dominance and biomechanics with a model of a developing kiwifruit shoot. These aspects were specified independently and their implementation was based on source code provided by the original authors without major changes. This new aspect-oriented approach to plant modelling is well suited for studying complex phenomena in plant science, because it can be used to integrate separate models of individual aspects of plant development and function, both previously constructed and new, into clearly organized, comprehensive FSPMs. In a future work, this approach could be further

  5. Multi-Feature Based Multiple Landmine Detection Using Ground Penetration Radar

    Directory of Open Access Journals (Sweden)

    S. Park

    2014-06-01

    Full Text Available This paper presents a novel method for detection of multiple landmines using a ground penetrating radar (GPR. Conventional algorithms mainly focus on detection of a single landmine, which cannot linearly extend to the multiple landmine case. The proposed algorithm is composed of four steps; estimation of the number of multiple objects buried in the ground, isolation of each object, feature extraction and detection of landmines. The number of objects in the GPR signal is estimated by using the energy projection method. Then signals for the objects are extracted by using the symmetry filtering method. Each signal is then processed for features, which are given as input to the support vector machine (SVM for landmine detection. Three landmines buried in various ground conditions are considered for the test of the proposed method. They demonstrate that the proposed method can successfully detect multiple landmines.

  6. AUTOMATIC CLOUD DETECTION FROM MULTI-TEMPORAL SATELLITE IMAGES: TOWARDS THE USE OF PLÉIADES TIME SERIES

    Directory of Open Access Journals (Sweden)

    N. Champion

    2012-08-01

    Full Text Available Contrary to aerial images, satellite images are often affected by the presence of clouds. Identifying and removing these clouds is one of the primary steps to perform when processing satellite images, as they may alter subsequent procedures such as atmospheric corrections, DSM production or land cover classification. The main goal of this paper is to present the cloud detection approach, developed at the French Mapping agency. Our approach is based on the availability of multi-temporal satellite images (i.e. time series that generally contain between 5 and 10 images and is based on a region-growing procedure. Seeds (corresponding to clouds are firstly extracted through a pixel-to-pixel comparison between the images contained in time series (the presence of a cloud is here assumed to be related to a high variation of reflectance between two images. Clouds are then delineated finely using a dedicated region-growing algorithm. The method, originally designed for panchromatic SPOT5-HRS images, is tested in this paper using time series with 9 multi-temporal satellite images. Our preliminary experiments show the good performances of our method. In a near future, the method will be applied to Pléiades images, acquired during the in-flight commissioning phase of the satellite (launched at the end of 2011. In that context, this is a particular goal of this paper to show to which extent and in which way our method can be adapted to this kind of imagery.

  7. Multi-channel non-invasive fetal electrocardiography detection using wavelet decomposition

    Science.gov (United States)

    Almeida, Javier; Ruano, Josué; Corredor, Germán.; Romo-Bucheli, David; Navarro-Vargas, José Ricardo; Romero, Eduardo

    2017-11-01

    Non-invasive fetal electrocardiography (fECG) has attracted the medical community because of the importance of fetal monitoring. However, its implementation in clinical practice is challenging: the fetal signal has a low Signal- to-Noise-Ratio and several signal sources are present in the maternal abdominal electrocardiography (AECG). This paper presents a novel method to detect the fetal signal from a multi-channel maternal AECG. The method begins by applying filters and signal detrending the AECG signals. Afterwards, the maternal QRS complexes are identified and subtracted. The residual signals are used to detect the fetal QRS complex. Intervals of these signals are analyzed by using a wavelet decomposition. The resulting representation feds a previously trained Random Forest (RF) classifier that identifies signal intervals associated to fetal QRS complex. The method was evaluated on a public available dataset: the Physionet2013 challenge. A set of 50 maternal AECG records were used to train the RF classifier. The evaluation was carried out in signals intervals extracted from additional 25 maternal AECG. The proposed method yielded an 83:77% accuracy in the fetal QRS complex classification task.

  8. From university research to innovation: Detecting knowledge transfer via text mining

    Energy Technology Data Exchange (ETDEWEB)

    Woltmann, S.; Clemmensen, L.; Alkærsig, L

    2016-07-01

    Knowledge transfer by universities is a top priority in innovation policy and a primary purpose for public research funding, due to being an important driver of technical change and innovation. Current empirical research on the impact of university research relies mainly on formal databases and indicators such as patents, collaborative publications and license agreements, to assess the contribution to the socioeconomic surrounding of universities. In this study, we present an extension of the current empirical framework by applying new computational methods, namely text mining and pattern recognition. Text samples for this purpose can include files containing social media contents, company websites and annual reports. The empirical focus in the present study is on the technical sciences and in particular on the case of the Technical University of Denmark (DTU). We generated two independent text collections (corpora) to identify correlations of university publications and company webpages. One corpus representing the company sites, serving as sample of the private economy and a second corpus, providing the reference to the university research, containing relevant publications. We associated the former with the latter to obtain insights into possible text and semantic relatedness. The text mining methods are extrapolating the correlations, semantic patterns and content comparison of the two corpora to define the document relatedness. We expect the development of a novel tool using contemporary techniques for the measurement of public research impact. The approach aims to be applicable across universities and thus enable a more holistic comparable assessment. This rely less on formal databases, which is certainly beneficial in terms of the data reliability. We seek to provide a supplementary perspective for the detection of the dissemination of university research and hereby enable policy makers to gain additional insights of (informal) contributions of knowledge

  9. A multi-wavelength (u.v. to visible) laser system for early detection of oral cancer

    Science.gov (United States)

    Najda, S. P.; Perlin, P.; Leszczyński, M.; Slight, T. J.; Meredith, W.; Schemmann, M.; Moseley, H.; Woods, J. A.; Valentine, R.; Kalra, S.; Mossey, P.; Theaker, E.; Macluskey, M.; Mimnagh, G.; Mimnagh, W.

    2015-03-01

    A multi-wavelength (360nm - 440nm), real-time Photonic Cancer Detector (PCD) optical system based on GaN semiconductor laser technology is outlined. A proof of concept using blue laser technology for early detection of cancer has already been tested and proven for esophageal cancer. This concept is expanded to consider a wider range of wavelengths and the PCD will initially be used for early diagnosis of oral cancers. The PCD creates an image of the oral cavity (broad field white light detection) and maps within the oral cavity any suspicious lesions with high sensitivity using a narrow field tunable detector.

  10. Multi-Sensor Mud Detection

    Science.gov (United States)

    Rankin, Arturo L.; Matthies, Larry H.

    2010-01-01

    Robust mud detection is a critical perception requirement for Unmanned Ground Vehicle (UGV) autonomous offroad navigation. A military UGV stuck in a mud body during a mission may have to be sacrificed or rescued, both of which are unattractive options. There are several characteristics of mud that may be detectable with appropriate UGV-mounted sensors. For example, mud only occurs on the ground surface, is cooler than surrounding dry soil during the daytime under nominal weather conditions, is generally darker than surrounding dry soil in visible imagery, and is highly polarized. However, none of these cues are definitive on their own. Dry soil also occurs on the ground surface, shadows, snow, ice, and water can also be cooler than surrounding dry soil, shadows are also darker than surrounding dry soil in visible imagery, and cars, water, and some vegetation are also highly polarized. Shadows, snow, ice, water, cars, and vegetation can all be disambiguated from mud by using a suite of sensors that span multiple bands in the electromagnetic spectrum. Because there are military operations when it is imperative for UGV's to operate without emitting strong, detectable electromagnetic signals, passive sensors are desirable. JPL has developed a daytime mud detection capability using multiple passive imaging sensors. Cues for mud from multiple passive imaging sensors are fused into a single mud detection image using a rule base, and the resultant mud detection is localized in a terrain map using range data generated from a stereo pair of color cameras.

  11. Effect of alignment on adsorption characteristics of self-oriented multi-walled carbon nanotube arrays

    International Nuclear Information System (INIS)

    Zilli, D; Bonelli, P R; Cukierman, A L

    2006-01-01

    The adsorption characteristics of self-oriented multi-walled carbon nanotube (MWCNT) arrays are examined from N 2 (-196 deg. C) adsorption measurements. The arrays were synthesized in a laboratory by in situ chemical vapour deposition of iron or cobalt phthalocyanines at 880 and 950 deg. C, under otherwise constant conditions, in an attempt to obtain different morphological structures. For both precursors, increasing the temperature leads to MWCNT arrays with lower Brunauer-Emmett-Teller (BET) surface area and total pore volume, though the effect is more pronounced for those arising from the iron-based compound. Despite this, precursor yields of individual nanotubes of larger diameter, higher BET area and total pore volume characterize the resulting arrays compared to those arising from cobalt phthalocyanine for the same temperatures. As evidenced by SEM and TEM images, the arrays synthesized from iron phthalocyanine at 880 deg. C show better vertical alignment and denser structures than those obtained from this compound at 950 deg. C, and also from cobalt phthalocyanine at both temperatures. Further ultrasonication of the arrays produced from the iron compound brings about a significant reduction in their adsorption capacity, attributable to the pronounced disarrangement of the resulting structures. The present results demonstrate that the alignment of MWCNT arrays plays a crucial role in their N 2 adsorption characteristics

  12. Cooperative fusion for multi-obstacles detection with use of stereovision and laser scanner

    OpenAIRE

    LABAYRADE, R; ROYERE, C; GRUYER, D; AUBERT, D

    2003-01-01

    The authors propose in this paper a new cooperative fusion approach between stereovision and laser scanner in order to take advantage of the best features of these two sensors to perform robust, accurate and real-time detection of multi-obstacles in the automotive context. The proposed system is able to estimate the position and the height, width and depth of generic obstacles at video frame rate (25 frames per second). The vehicle pitch, estimated by stereovision, is used to filter laser sca...

  13. Cooperative fusion for multi-obstacles detection with use of stereovision and laser scanner

    OpenAIRE

    LABAYRADE, R; ROYERE, C; GRUYER, D; AUBERT, D

    2005-01-01

    We propose a new cooperative fusion approach between stereovision and laser scanner in order to take advantage of the best features and cope with the drawbacks of these two sensors to perform robust, accurate and real time-detection of multi-obstacles in the automotive context. The proposed system is able to estimate the position and the height, width and depth of generic obstacles at video frame rate (25 frames per second). The vehicle pitch, estimated by stereovision, is used to filter lase...

  14. LINE-BASED MULTI-IMAGE MATCHING FOR FAÇADE RECONSTRUCTION

    Directory of Open Access Journals (Sweden)

    T. A. Teo

    2012-07-01

    Full Text Available This research integrates existing LOD 2 building models and multiple close-range images for façade structural lines extraction. The major works are orientation determination and multiple image matching. In the orientation determination, Speeded Up Robust Features (SURF is applied to extract tie points automatically. Then, tie points and control points are combined for block adjustment. An object-based multi-images matching is proposed to extract the façade structural lines. The 2D lines in image space are extracted by Canny operator followed by Hough transform. The role of LOD 2 building models is to correct the tilt displacement of image from different views. The wall of LOD 2 model is also used to generate hypothesis planes for similarity measurement. Finally, average normalized cross correlation is calculated to obtain the best location in object space. The test images are acquired by a nonmetric camera Nikon D2X. The total number of image is 33. The experimental results indicate that the accuracy of orientation determination is about 1 pixel from 2515 tie points and 4 control points. It also indicates that line-based matching is more flexible than point-based matching.

  15. Multirapid Serial Visual Presentation Framework for EEG-Based Target Detection

    Directory of Open Access Journals (Sweden)

    Zhimin Lin

    2017-01-01

    Full Text Available Target image detection based on a rapid serial visual presentation (RSVP paradigm is a typical brain-computer interface system with various applications, such as image retrieval. In an RSVP paradigm, a P300 component is detected to determine target images. This strategy requires high-precision single-trial P300 detection methods. However, the performance of single-trial detection methods is relatively lower than that of multitrial P300 detection methods. Image retrieval based on multitrial P300 is a new research direction. In this paper, we propose a triple-RSVP paradigm with three images being presented simultaneously and a target image appearing three times. Thus, multitrial P300 classification methods can be used to improve detection accuracy. In this study, these mechanisms were extended and validated, and the characteristics of the multi-RSVP framework were further explored. Two different P300 detection algorithms were also utilized in multi-RSVP to demonstrate that the scheme is universally applicable. Results revealed that the detection accuracy of the multi-RSVP paradigm was higher than that of the standard RSVP paradigm. The results validate the effectiveness of the proposed method, and this method can provide a whole new idea in the field of EEG-based target detection.

  16. Multi-biometric Liveness Detection – A New Perspective

    African Journals Online (AJOL)

    2016-12-01

    Dec 1, 2016 ... Basic Multi-biometric Authentication System was thought to have sealed the vulnerabilities ..... action of a real physical human being and not from a pattern ... of authentication is referred to as multi-biometric fusion, and such a ...

  17. Automated Extraction of Substance Use Information from Clinical Texts.

    Science.gov (United States)

    Wang, Yan; Chen, Elizabeth S; Pakhomov, Serguei; Arsoniadis, Elliot; Carter, Elizabeth W; Lindemann, Elizabeth; Sarkar, Indra Neil; Melton, Genevieve B

    2015-01-01

    Within clinical discourse, social history (SH) includes important information about substance use (alcohol, drug, and nicotine use) as key risk factors for disease, disability, and mortality. In this study, we developed and evaluated a natural language processing (NLP) system for automated detection of substance use statements and extraction of substance use attributes (e.g., temporal and status) based on Stanford Typed Dependencies. The developed NLP system leveraged linguistic resources and domain knowledge from a multi-site social history study, Propbank and the MiPACQ corpus. The system attained F-scores of 89.8, 84.6 and 89.4 respectively for alcohol, drug, and nicotine use statement detection, as well as average F-scores of 82.1, 90.3, 80.8, 88.7, 96.6, and 74.5 respectively for extraction of attributes. Our results suggest that NLP systems can achieve good performance when augmented with linguistic resources and domain knowledge when applied to a wide breadth of substance use free text clinical notes.

  18. BILINGUAL MULTIMODAL SYSTEM FOR TEXT-TO-AUDIOVISUAL SPEECH AND SIGN LANGUAGE SYNTHESIS

    Directory of Open Access Journals (Sweden)

    A. A. Karpov

    2014-09-01

    Full Text Available We present a conceptual model, architecture and software of a multimodal system for audio-visual speech and sign language synthesis by the input text. The main components of the developed multimodal synthesis system (signing avatar are: automatic text processor for input text analysis; simulation 3D model of human's head; computer text-to-speech synthesizer; a system for audio-visual speech synthesis; simulation 3D model of human’s hands and upper body; multimodal user interface integrating all the components for generation of audio, visual and signed speech. The proposed system performs automatic translation of input textual information into speech (audio information and gestures (video information, information fusion and its output in the form of multimedia information. A user can input any grammatically correct text in Russian or Czech languages to the system; it is analyzed by the text processor to detect sentences, words and characters. Then this textual information is converted into symbols of the sign language notation. We apply international «Hamburg Notation System» - HamNoSys, which describes the main differential features of each manual sign: hand shape, hand orientation, place and type of movement. On their basis the 3D signing avatar displays the elements of the sign language. The virtual 3D model of human’s head and upper body has been created using VRML virtual reality modeling language, and it is controlled by the software based on OpenGL graphical library. The developed multimodal synthesis system is a universal one since it is oriented for both regular users and disabled people (in particular, for the hard-of-hearing and visually impaired, and it serves for multimedia output (by audio and visual modalities of input textual information.

  19. Building Multi-Agent Systems Using Jason

    DEFF Research Database (Denmark)

    Boss, Niklas Skamriis; Jensen, Andreas Schmidt; Villadsen, Jørgen

    2010-01-01

    We provide a detailed description of the Jason-DTU system, including the used methodology, tools as well as team strategy. We also discuss the experience gathered in the contest. In spring 2009 the course “Artificial Intelligence and Multi- Agent Systems” was held for the first time...... on the Technical University of Denmark (DTU). A part of this course was a short introduction to the multi-agent framework Jason, which is an interpreter for AgentSpeak, an agent-oriented programming language. As the final project in this course a solution to the Multi-Agent Programming Contest from 2007, the Gold...

  20. OOAspectZ and aspect-oriented UML class diagrams for Aspect-oriented software modelling (AOSM

    Directory of Open Access Journals (Sweden)

    Cristian Vidal Silva

    2013-09-01

    Full Text Available Regarding modularised software development, Aspect-oriented programming (AOP identifies and represents individually crosscutting concerns during the software development cycle’s programming stage. This article proposes and applies OOAspectZ to formal Aspect-oriented requirement specifications for prior stages of the software development cycle. It particularly concerns requirement specification and the structural design of data and behaviour, along with describing and applying Aspect-oriented UML class diagrams to designing classes, aspects and associations among classes and aspects during Aspect-oriented software development (AOSD.OOAspectZ is a language integrating both Object-Z and AspectZ formal languages whereas Aspect-oriented UML class diagrams represent AOP code, object class and crosscutting concern class structure by means of stereotypes. This article shows and applies the main OOAspectZ and AO UML class diagram characteristics to Aspect-oriented software modelling (AOSM using a classic example of AOP. Ideas for future work concerning an actual AOP version are also indicated.

  1. Archives: Orient Journal of Medicine

    African Journals Online (AJOL)

    Items 1 - 26 of 26 ... Archives: Orient Journal of Medicine. Journal Home > Archives: Orient Journal of Medicine. Log in or Register to get access to full text downloads. Username, Password, Remember me, or Register · Journal Home · ABOUT THIS JOURNAL · Advanced Search · Current Issue · Archives. 1 - 26 of 26 Items ...

  2. Object-Oriented Type Systems

    DEFF Research Database (Denmark)

    Schwartzbach, Michael Ignatieff; Palsberg, Jens

    a type system that generalizes and explains them. The theory is based on an idealized object-oriented language called BOPL (Basic Object Programming Language), containing common features of the above languages. A type system, type inference algorithm, and typings of inheritance and genericity......Object-Oriented Type Systems Jens Palsberg and Michael I. Schwartzbach Aarhus University, Denmark Type systems are required to ensure reliability and efficiency of software. For object-oriented languages, typing is an especially challenging problem because of inheritance, assignment, and late...... are provided for BOPL. Throughout, the results are related to the languages on which BOPL is based. This text offers advanced undergraduates and professional software developers a sound understanding of the key aspects of object-oriented type systems. All algorithms are implemented in a freely available...

  3. Performance of UWB Array-Based Radar Sensor in a Multi-Sensor Vehicle-Based Suit for Landmine Detection

    NARCIS (Netherlands)

    Yarovoy, A.; Savelyev, T.; Zhuge, X.; Aubry, P.; Ligthart, L.; Schavemaker, J.G.M.; Tettelaar, P.; Breejen, E. de

    2008-01-01

    In this paper, integration of an UWB array-based timedomain radar sensor in a vehicle-mounted multi-sensor system for landmine detection is described. Dedicated real-time signal processing algorithms are developed to compute the radar sensor confidence map which is used for sensor fusion.

  4. Study of molecular orientations in Langmuir-Blodgett films

    International Nuclear Information System (INIS)

    Lesieur, Pierre

    1986-01-01

    This research thesis reports the characterization of Langmuir-Blodgett films by electric paramagnetic resonance and by resonant Raman diffusion in polarized light. Films are made of mixed or alternated multi-layers of amphiphilic porphyrins and docosenoic acid. The author more particularly studied the orientation of porphyrinic macro-cycles with respect to the layer substrate [fr

  5. Text Character Extraction Implementation from Captured Handwritten Image to Text Conversionusing Template Matching Technique

    Directory of Open Access Journals (Sweden)

    Barate Seema

    2016-01-01

    Full Text Available Images contain various types of useful information that should be extracted whenever required. A various algorithms and methods are proposed to extract text from the given image, and by using that user will be able to access the text from any image. Variations in text may occur because of differences in size, style,orientation, alignment of text, and low image contrast, composite backgrounds make the problem during extraction of text. If we develop an application that extracts and recognizes those texts accurately in real time, then it can be applied to many important applications like document analysis, vehicle license plate extraction, text- based image indexing, etc and many applications have become realities in recent years. To overcome the above problems we develop such application that will convert the image into text by using algorithms, such as bounding box, HSV model, blob analysis,template matching, template generation.

  6. Programming in an object-oriented environment

    CERN Document Server

    Ege, Raimund K

    1992-01-01

    Programming in an Object-Oriented Environment provides an in-depth look at the concepts behind the technology of object-oriented programming.This book explains why object-oriented programming has the potential to vastly improve the productivity of programmers and how to apply this technology in a practical environment. Many programming examples are included, focusing on how different programming languages support the core of object-oriented concepts. C++ is used as the main sample language throughout this text.This monograph consists of two major parts. Part I provides an introduction to objec

  7. Real-time flight conflict detection and release based on Multi-Agent system

    Science.gov (United States)

    Zhang, Yifan; Zhang, Ming; Yu, Jue

    2018-01-01

    This paper defines two-aircrafts, multi-aircrafts and fleet conflict mode, sets up space-time conflict reservation on the basis of safety interval and conflict warning time in three-dimension. Detect real-time flight conflicts combined with predicted flight trajectory of other aircrafts in the same airspace, and put forward rescue resolutions for the three modes respectively. When accorded with the flight conflict conditions, determine the conflict situation, and enter the corresponding conflict resolution procedures, so as to avoid the conflict independently, as well as ensure the flight safety of aimed aircraft. Lastly, the correctness of model is verified with numerical simulation comparison.

  8. Detecting and Analyzing Cybercrime in Text-Based Communication of Cybercriminal Networks through Computational Linguistic and Psycholinguistic Feature Modeling

    Science.gov (United States)

    Mbaziira, Alex Vincent

    2017-01-01

    Cybercriminals are increasingly using Internet-based text messaging applications to exploit their victims. Incidents of deceptive cybercrime in text-based communication are increasing and include fraud, scams, as well as favorable and unfavorable fake reviews. In this work, we use a text-based deception detection approach to train models for…

  9. Faint Object Detection in Multi-Epoch Observations via Catalog Data Fusion

    Energy Technology Data Exchange (ETDEWEB)

    Budavári, Tamás; Szalay, Alexander S. [Department of Physics and Astronomy, The Johns Hopkins University, 3400 North Charles Street, Baltimore, MD 21218 (United States); Loredo, Thomas J. [Cornell Center for Astrophysics and Planetary Science, Cornell University, Ithaca, NY 14853 (United States)

    2017-03-20

    Astronomy in the time-domain era faces several new challenges. One of them is the efficient use of observations obtained at multiple epochs. The work presented here addresses faint object detection and describes an incremental strategy for separating real objects from artifacts in ongoing surveys. The idea is to produce low-threshold single-epoch catalogs and to accumulate information across epochs. This is in contrast to more conventional strategies based on co-added or stacked images. We adopt a Bayesian approach, addressing object detection by calculating the marginal likelihoods for hypotheses asserting that there is no object or one object in a small image patch containing at most one cataloged source at each epoch. The object-present hypothesis interprets the sources in a patch at different epochs as arising from a genuine object; the no-object hypothesis interprets candidate sources as spurious, arising from noise peaks. We study the detection probability for constant-flux objects in a Gaussian noise setting, comparing results based on single and stacked exposures to results based on a series of single-epoch catalog summaries. Our procedure amounts to generalized cross-matching: it is the product of a factor accounting for the matching of the estimated fluxes of the candidate sources and a factor accounting for the matching of their estimated directions. We find that probabilistic fusion of multi-epoch catalogs can detect sources with similar sensitivity and selectivity compared to stacking. The probabilistic cross-matching framework underlying our approach plays an important role in maintaining detection sensitivity and points toward generalizations that could accommodate variability and complex object structure.

  10. Faint Object Detection in Multi-Epoch Observations via Catalog Data Fusion

    International Nuclear Information System (INIS)

    Budavári, Tamás; Szalay, Alexander S.; Loredo, Thomas J.

    2017-01-01

    Astronomy in the time-domain era faces several new challenges. One of them is the efficient use of observations obtained at multiple epochs. The work presented here addresses faint object detection and describes an incremental strategy for separating real objects from artifacts in ongoing surveys. The idea is to produce low-threshold single-epoch catalogs and to accumulate information across epochs. This is in contrast to more conventional strategies based on co-added or stacked images. We adopt a Bayesian approach, addressing object detection by calculating the marginal likelihoods for hypotheses asserting that there is no object or one object in a small image patch containing at most one cataloged source at each epoch. The object-present hypothesis interprets the sources in a patch at different epochs as arising from a genuine object; the no-object hypothesis interprets candidate sources as spurious, arising from noise peaks. We study the detection probability for constant-flux objects in a Gaussian noise setting, comparing results based on single and stacked exposures to results based on a series of single-epoch catalog summaries. Our procedure amounts to generalized cross-matching: it is the product of a factor accounting for the matching of the estimated fluxes of the candidate sources and a factor accounting for the matching of their estimated directions. We find that probabilistic fusion of multi-epoch catalogs can detect sources with similar sensitivity and selectivity compared to stacking. The probabilistic cross-matching framework underlying our approach plays an important role in maintaining detection sensitivity and points toward generalizations that could accommodate variability and complex object structure.

  11. Kinetics of oriented crystallization of polymers in the linear stress-orientation range in the series expansion approach

    Directory of Open Access Journals (Sweden)

    L. Jarecki

    2018-04-01

    Full Text Available An analytical formula is derived for the oriented crystallization coefficient governing kinetics of oriented crystallization under uniaxial amorphous orientation in the entire temperature range. A series expansion approach is applied to the free energy of crystallization in the Hoffman-Lauritzen kinetic model of crystallization at accounting for the entropy of orientation of the amorphous chains. The series expansion coefficients are calculated for systems of Gaussian chains in linear stress-orientation range. Oriented crystallization rate functions are determined basing on the ‘proportional expansion’ approach proposed by Ziabicki in the steady-state limit. Crystallization kinetics controlled by separate predetermined and sporadic primary nucleation is considered, as well as the kinetics involving both nucleation mechanisms potentially present in oriented systems. The involvement of sporadic nucleation in the transformation kinetics is predicted to increase with increasing amorphous orientation. Example computations illustrate the dependence of the calculated functions on temperature and amorphous orientation, as well as qualitative agreement of the calculations with experimental results.

  12. Globalisation, Mergers and "Inadvertent Multi-Campus Universities": Reflections from Wales

    Science.gov (United States)

    Zeeman, Nadine; Benneworth, Paul

    2017-01-01

    Multi-site universities face the challenge of integrating campuses that may have different profiles and orientations arising from place-specific attachments. Multi-campus universities created via mergers seeking to ensure long-term financial sustainability, and increasing their attractiveness to students, create a tension in campuses' purposes. We…

  13. ANALYSIS OF MOBILE LASER SCANNING DATA AND MULTI-VIEW IMAGE RECONSTRUCTION

    Directory of Open Access Journals (Sweden)

    C. Briese

    2012-07-01

    Full Text Available The combination of laser scanning (LS, active, direct 3D measurement of the object surface and photogrammetry (high geometric and radiometric resolution is widely applied for object reconstruction (e.g. architecture, topography, monitoring, archaeology. Usually the results are a coloured point cloud or a textured mesh. The geometry is typically generated from the laser scanning point cloud and the radiometric information is the result of image acquisition. In the last years, next to significant developments in static (terrestrial LS and kinematic LS (airborne and mobile LS hardware and software, research in computer vision and photogrammetry lead to advanced automated procedures in image orientation and image matching. These methods allow a highly automated generation of 3D geometry just based on image data. Founded on advanced feature detector techniques (like SIFT (Scale Invariant Feature Transform very robust techniques for image orientation were established (cf. Bundler. In a subsequent step, dense multi-view stereo reconstruction algorithms allow the generation of very dense 3D point clouds that represent the scene geometry (cf. Patch-based Multi-View Stereo (PMVS2. Within this paper the usage of mobile laser scanning (MLS and simultaneously acquired image data for an advanced integrated scene reconstruction is studied. For the analysis the geometry of a scene is generated by both techniques independently. Then, the paper focuses on the quality assessment of both techniques. This includes a quality analysis of the individual surface models and a comparison of the direct georeferencing of the images using positional and orientation data of the on board GNSS-INS system and the indirect georeferencing of the imagery by automatic image orientation. For the practical evaluation a dataset from an archaeological monument is utilised. Based on the gained knowledge a discussion of the results is provided and a future strategy for the integration of

  14. Game of Objects: vicarious causation and multi-modal media

    Directory of Open Access Journals (Sweden)

    Aaron Pedinotti

    2013-09-01

    Full Text Available This paper applies philosopher Graham Harman's object-oriented theory of "vicarious causation" to an analysis of the multi-modal media phenomenon known as "Game of Thrones." Examining the manner in which George R.R. Martin's best-selling series of fantasy novels has been adapted into a board game, a video game, and a hit HBO television series, it uses the changes entailed by these processes to trace the contours of vicariously generative relations. In the course of the resulting analysis, it provides new suggestions concerning the eidetic dimensions of Harman's causal model, particularly with regard to causation in linear networks and in differing types of game systems.

  15. Detection of Asian Dust Storm Using MODIS Measurements

    Directory of Open Access Journals (Sweden)

    Yong Xie

    2017-08-01

    Full Text Available Every year, a large number of aerosols are released from dust storms into the atmosphere, which may have potential impacts on the climate, environment, and air quality. Detecting dust aerosols and monitoring their movements and evolutions in a timely manner is a very significant task. Satellite remote sensing has been demonstrated as an effective means for observing dust aerosols. In this paper, an algorithm based on the multi-spectral technique for detecting dust aerosols was developed by combining measurements of moderate resolution imaging spectroradiometer (MODIS reflective solar bands and thermal emissive bands. Data from dust events that occurred during the past several years were collected as training data for spectral and statistical analyses. According to the spectral curves of various scene types, a series of spectral bands was selected individually or jointly, and corresponding thresholds were defined for step-by-step scene classification. The multi-spectral algorithm was applied mainly to detect dust storms in Asia. The detection results were validated not only visually with MODIS true color images, but also quantitatively with products of Ozone Monitoring Instrument (OMI and Cloud Aerosol Lidar with Orthogonal Polarization (CALIOP. The validations showed that this multi-spectral detection algorithm was suitable to monitor dust aerosols in the selected study areas.

  16. Multi-Channel Amplifier-Discriminator for Highly Time-Resolved Detection

    CERN Document Server

    Despeisse, M; Lapington, J; Jarron, P

    2011-01-01

    A low-power multi-channel amplifier-discriminator was developed for application in highly time-resolved detection systems. The proposed circuit architecture, so-called Nino, is based on a time-over-threshold approach and shows a high potential for time-resolved readout of solid-state photo-detectors and of detectors based on vacuum technologies. The Irpics circuit was designed in a 250 nm CMOS technology, implementing 32 channels of a Nino version optimized to achieve high-time resolution on the output low-voltage differential signals (LVDS) while keeping a low power consumption of 10 mW per channel. Electrical characterizations of the circuit demonstrate a very low intrinsic time jitter on the output pulse leading edge, measured below 10 ps rms for each channel for high input signal charges (100 fC) and below 25 ps rms for low input signal charges (20-100 fC). The read-out architecture moreover permits to retrieve the input signal charge from the timing measurements, while a calibration procedure was develop...

  17. AUTOMATIC ROAD GAP DETECTION USING FUZZY INFERENCE SYSTEM

    Directory of Open Access Journals (Sweden)

    S. Hashemi

    2012-09-01

    Full Text Available Automatic feature extraction from aerial and satellite images is a high-level data processing which is still one of the most important research topics of the field. In this area, most of the researches are focused on the early step of road detection, where road tracking methods, morphological analysis, dynamic programming and snakes, multi-scale and multi-resolution methods, stereoscopic and multi-temporal analysis, hyper spectral experiments, are some of the mature methods in this field. Although most researches are focused on detection algorithms, none of them can extract road network perfectly. On the other hand, post processing algorithms accentuated on the refining of road detection results, are not developed as well. In this article, the main is to design an intelligent method to detect and compensate road gaps remained on the early result of road detection algorithms. The proposed algorithm consists of five main steps as follow: 1 Short gap coverage: In this step, a multi-scale morphological is designed that covers short gaps in a hierarchical scheme. 2 Long gap detection: In this step, the long gaps, could not be covered in the previous stage, are detected using a fuzzy inference system. for this reason, a knowledge base consisting of some expert rules are designed which are fired on some gap candidates of the road detection results. 3 Long gap coverage: In this stage, detected long gaps are compensated by two strategies of linear and polynomials for this reason, shorter gaps are filled by line fitting while longer ones are compensated by polynomials.4 Accuracy assessment: In order to evaluate the obtained results, some accuracy assessment criteria are proposed. These criteria are obtained by comparing the obtained results with truly compensated ones produced by a human expert. The complete evaluation of the obtained results whit their technical discussions are the materials of the full paper.

  18. A New Multi-Sensor Track Fusion Architecture for Multi-Sensor Information Integration

    National Research Council Canada - National Science Library

    Jean, Buddy H; Younker, John; Hung, Chih-Cheng

    2004-01-01

    .... This new technology will integrate multi-sensor information and extract integrated multi-sensor information to detect, track and identify multiple targets at any time, in any place under all weather conditions...

  19. Applications of Multi-Agent Technology to Power Systems

    Science.gov (United States)

    Nagata, Takeshi

    Currently, agents are focus of intense on many sub-fields of computer science and artificial intelligence. Agents are being used in an increasingly wide variety of applications. Many important computing applications such as planning, process control, communication networks and concurrent systems will benefit from using multi-agent system approach. A multi-agent system is a structure given by an environment together with a set of artificial agents capable to act on this environment. Multi-agent models are oriented towards interactions, collaborative phenomena, and autonomy. This article presents the applications of multi-agent technology to the power systems.

  20. a Framework of Change Detection Based on Combined Morphologica Features and Multi-Index Classification

    Science.gov (United States)

    Li, S.; Zhang, S.; Yang, D.

    2017-09-01

    Remote sensing images are particularly well suited for analysis of land cover change. In this paper, we present a new framework for detection of changing land cover using satellite imagery. Morphological features and a multi-index are used to extract typical objects from the imagery, including vegetation, water, bare land, buildings, and roads. Our method, based on connected domains, is different from traditional methods; it uses image segmentation to extract morphological features, while the enhanced vegetation index (EVI), the differential water index (NDWI) are used to extract vegetation and water, and a fragmentation index is used to the correct extraction results of water. HSV transformation and threshold segmentation extract and remove the effects of shadows on extraction results. Change detection is performed on these results. One of the advantages of the proposed framework is that semantic information is extracted automatically using low-level morphological features and indexes. Another advantage is that the proposed method detects specific types of change without any training samples. A test on ZY-3 images demonstrates that our framework has a promising capability to detect change.

  1. Flow-cytometric identification of vinegars using a multi-parameter analysis optical detection module

    Science.gov (United States)

    Verschooten, T.; Ottevaere, H.; Vervaeke, M.; Van Erps, J.; Callewaert, M.; De Malsche, W.; Thienpont, H.

    2015-09-01

    We show a proof-of-concept demonstration of a multi-parameter analysis low-cost optical detection system for the flowcytometric identification of vinegars. This multi-parameter analysis system can simultaneously measure laser induced fluorescence, absorption and scattering excited by two time-multiplexed lasers of different wavelengths. To our knowledge no other polymer optofluidic chip based system offers more simultaneous measurements. The design of the optofluidic channels is aimed at countering the effects that viscous fingering, air bubbles, and emulsion samples can have on the correct operation of such a detection system. Unpredictable variations in viscosity and refractive index of the channel content can be turned into a source of information. The sample is excited by two laser diodes that are driven by custom made low-cost laser drivers. The optofluidic chip is built to be robust and easy to handle and is reproducible using hot embossing. We show a custom optomechanical holder for the optofluidic chip that ensures correct alignment and automatic connection to the external fluidic system. We show an experiment in which 92 samples of vinegar are measured. We are able to identify 9 different kinds of vinegar with an accuracy of 94%. Thus we show an alternative approach to the classic optical spectroscopy solution at a lowered. Furthermore, we have shown the possibility of predicting the viscosity and turbidity of vinegars with a goodness-of-fit R2 over 0.947.

  2. Moessbauer effects on oriented nuclei

    International Nuclear Information System (INIS)

    Sayouti, E.H.

    1984-01-01

    Standard nuclear orientation methods (not sensitive to the polarization) do not give information on the sign of the magnetic moment. Mossbauer effect separates right-hand and left-hand circularly polarized components, thus its detection on oriented nuclei (T approximately 10 mK) gives the sign of the magnetic moment of oriented state. In this thesis we applied this method to study the 3/2 - ground states of 191 Pt and 193 Os, which are in the prolate-oblate transition region, where assignement of experimental levels to theoretical states is often umbiguous. We show that for those nuclei the sign of the magnetic moment is the signature of the configuration, and its determination establishes the correspondance between experimental and theoretical levels [fr

  3. Control-oriented model of a membrane humidifier for fuel cell applications

    International Nuclear Information System (INIS)

    Solsona, Miguel; Kunusch, Cristian; Ocampo-Martinez, Carlos

    2017-01-01

    Highlights: • A control-oriented model of a Nafion® membrane gas humidifier has been developed. • The control-oriented model has been experimentally validated. • A non-linear control strategy has been used to test its suitability for control purposes. - Abstract: Improving the humidification of polymer electrolyte membrane fuel-cells (PEMFC) is essential to optimize its performance and stability. Therefore, this paper presents an experimentally validated model of a low temperature PEMFC cathode humidifier for control/observation design purposes. A multi-input/multi-output non-linear fourth order model is derived, based on the mass and heat dynamics of circulating air. In order to validate the proposed model and methodology, experimental results are provided. Finally, a non-linear control strategy based on second order sliding mode is designed and analyzed in order to show suitability and usefulness of the approach.

  4. Location and orientation of panel on the screen as a structural visual element to highlight text displayed

    Science.gov (United States)

    Léger, Laure; Chevalier, Aline

    2017-07-01

    Searching for information on the internet has become a daily activity. It is considered to be a complex cognitive activity that involves visual attention. Many studies have demonstrated that users' information search are affected both by the spatial configuration of words and the elements displayed on the screen: elements that are used to structure web pages. One of these elements, the web panel, contains information. Web panel is a rectangular area with a colored background that was used to highlighting content presented in this specific rectangular area. Our general hypothesis was that the presence of a panel on a web page would affect the structure of a word display, as a result, information search accuracy. We carried out an experiment in which we manipulated the presence vs. the absence of a panel, as well as its orientation on the screen (vertical vs. horizontal). Twenty participants were asked to answer questions while their eye movements were recorded. Results showed that the presence of a panel resulted in reduced accuracy and shorter response times. Panel orientation affected scanpaths, especially when they were orientated vertically. We discuss these findings and suggest ways in which this research could be developed further in future.

  5. Postdictive modulation of visual orientation.

    Directory of Open Access Journals (Sweden)

    Takahiro Kawabe

    Full Text Available The present study investigated how visual orientation is modulated by subsequent orientation inputs. Observers were presented a near-vertical Gabor patch as a target, followed by a left- or right-tilted second Gabor patch as a distracter in the spatial vicinity of the target. The task of the observers was to judge whether the target was right- or left-tilted (Experiment 1 or whether the target was vertical or not (Supplementary experiment. The judgment was biased toward the orientation of the distracter (the postdictive modulation of visual orientation. The judgment bias peaked when the target and distracter were temporally separated by 100 ms, indicating a specific temporal mechanism for this phenomenon. However, when the visibility of the distracter was reduced via backward masking, the judgment bias disappeared. On the other hand, the low-visibility distracter could still cause a simultaneous orientation contrast, indicating that the distracter orientation is still processed in the visual system (Experiment 2. Our results suggest that the postdictive modulation of visual orientation stems from spatiotemporal integration of visual orientation on the basis of a slow feature matching process.

  6. The equivalent internal orientation and position noise for contour integration.

    Science.gov (United States)

    Baldwin, Alex S; Fu, Minnie; Farivar, Reza; Hess, Robert F

    2017-10-12

    Contour integration is the joining-up of local responses to parts of a contour into a continuous percept. In typical studies observers detect contours formed of discrete wavelets, presented against a background of random wavelets. This measures performance for detecting contours in the limiting external noise that background provides. Our novel task measures contour integration without requiring any background noise. This allowed us to perform noise-masking experiments using orientation and position noise. From these we measure the equivalent internal noise for contour integration. We found an orientation noise of 6° and position noise of 3 arcmin. Orientation noise was 2.6x higher in contour integration compared to an orientation discrimination control task. Comparing against a position discrimination task found position noise in contours to be 2.4x lower. This suggests contour integration involves intermediate processing that enhances the quality of element position representation at the expense of element orientation. Efficiency relative to the ideal observer was lower for the contour tasks (36% in orientation noise, 21% in position noise) compared to the controls (54% and 57%).

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

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg

    2007-01-01

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

  8. Vehicle Color Recognition with Vehicle-Color Saliency Detection and Dual-Orientational Dimensionality Reduction of CNN Deep Features

    Science.gov (United States)

    Zhang, Qiang; Li, Jiafeng; Zhuo, Li; Zhang, Hui; Li, Xiaoguang

    2017-12-01

    Color is one of the most stable attributes of vehicles and often used as a valuable cue in some important applications. Various complex environmental factors, such as illumination, weather, noise and etc., result in the visual characteristics of the vehicle color being obvious diversity. Vehicle color recognition in complex environments has been a challenging task. The state-of-the-arts methods roughly take the whole image for color recognition, but many parts of the images such as car windows; wheels and background contain no color information, which will have negative impact on the recognition accuracy. In this paper, a novel vehicle color recognition method using local vehicle-color saliency detection and dual-orientational dimensionality reduction of convolutional neural network (CNN) deep features has been proposed. The novelty of the proposed method includes two parts: (1) a local vehicle-color saliency detection method has been proposed to determine the vehicle color region of the vehicle image and exclude the influence of non-color regions on the recognition accuracy; (2) dual-orientational dimensionality reduction strategy has been designed to greatly reduce the dimensionality of deep features that are learnt from CNN, which will greatly mitigate the storage and computational burden of the subsequent processing, while improving the recognition accuracy. Furthermore, linear support vector machine is adopted as the classifier to train the dimensionality reduced features to obtain the recognition model. The experimental results on public dataset demonstrate that the proposed method can achieve superior recognition performance over the state-of-the-arts methods.

  9. Model observer for assessing digital breast tomosynthesis for multi-lesion detection in the presence of anatomical noise

    Science.gov (United States)

    Wen, Gezheng; Markey, Mia K.; Miner Haygood, Tamara; Park, Subok

    2018-02-01

    Model observers are widely used in task-based assessments of medical image quality. The presence of multiple abnormalities in a single set of images, such as in multifocal multicentric breast cancer (MFMC), has an immense clinical impact on treatment planning and survival outcomes. Detecting multiple breast tumors is challenging as MFMC is relatively uncommon, and human observers do not know the number or locations of tumors a priori. Digital breast tomosynthesis (DBT), in which an x-ray beam sweeps over a limited angular range across the breast, has the potential to improve the detection of multiple tumors. However, prior studies of DBT image quality all focus on unifocal breast cancers. In this study, we extended our 2D multi-lesion (ML) channelized Hotelling observer (CHO) into a 3D ML-CHO that detects multiple lesions from volumetric imaging data. Then we employed the 3D ML-CHO to identify optimal DBT acquisition geometries for detection of MFMC. Digital breast phantoms with multiple embedded synthetic lesions were scanned by simulated DBT scanners of different geometries (wide/narrow angular span, different number of projections per scan) to simulate MFMC cases. With new implementations of 3D partial least squares (PLS) and modified Laguerre-Gauss (LG) channels, the 3D ML-CHO made detection decisions based upon the overall information from individual DBT slices and their correlations. Our evaluation results show that: (1) the 3D ML-CHO could achieve good detection performance with a small number of channels, and 3D PLS channels on average outperform the counterpart LG channels; (2) incorporating locally varying anatomical backgrounds and their correlations as in the 3D ML-CHO is essential for multi-lesion detection; (3) the most effective DBT geometry for detection of MFMC may vary when the task of clinical interest changes, and a given DBT geometry may not yield images that are equally informative for detecting MF, MC, and unifocal cancers.

  10. Automatic facial pore analysis system using multi-scale pore detection.

    Science.gov (United States)

    Sun, J Y; Kim, S W; Lee, S H; Choi, J E; Ko, S J

    2017-08-01

    As facial pore widening and its treatments have become common concerns in the beauty care field, the necessity for an objective pore-analyzing system has been increased. Conventional apparatuses lack in usability requiring strong light sources and a cumbersome photographing process, and they often yield unsatisfactory analysis results. This study was conducted to develop an image processing technique for automatic facial pore analysis. The proposed method detects facial pores using multi-scale detection and optimal scale selection scheme and then extracts pore-related features such as total area, average size, depth, and the number of pores. Facial photographs of 50 subjects were graded by two expert dermatologists, and correlation analyses between the features and clinical grading were conducted. We also compared our analysis result with those of conventional pore-analyzing devices. The number of large pores and the average pore size were highly correlated with the severity of pore enlargement. In comparison with the conventional devices, the proposed analysis system achieved better performance showing stronger correlation with the clinical grading. The proposed system is highly accurate and reliable for measuring the severity of skin pore enlargement. It can be suitably used for objective assessment of the pore tightening treatments. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  11. Faults detection approach using PCA and SOM algorithm in PMSG-WT system

    Directory of Open Access Journals (Sweden)

    Mohamed Lamine FADDA

    2016-07-01

    Full Text Available In this paper, a new approach for faults detection in observable data system wind turbine - permanent magnet synchronous generator (WT-PMSG, the studying objective, illustrate the combination (SOM-PCA to build Multi-local-PCA models faults detection in system (WT-PMSG, the performance of the method suggested to faults detection in system data, finding good results in simulation experiment.

  12. Market Orientation and Innovators’ Success: an Exploration of the Influence of Customer and Competitor Orientation

    Directory of Open Access Journals (Sweden)

    Michael Lewrick

    2011-08-01

    Full Text Available The concepts of market orientation and innovation and their interrelationship with business success have been explored from a number of perspectives. However, research in this area has not explored the differences between start-up and mature companies. The research study acquired data from over two hundred Chief Operating Officers (CEO’s and Managing Directors from both start-up and mature companies. The results illustrate the differences in both types of company and reveals new insights with regard to market orientation and its constituent elements and its relationship with both incremental and radical innovations. Key research results are that strong competitor orientation, a key ingredient of market orientation, has positive relationship to incremental innovation for start-up companies but it is contra productive for mature companies. In mature organizations a strong customer orientation is associated with radical innovation.

  13. Text Mining the History of Medicine.

    Science.gov (United States)

    Thompson, Paul; Batista-Navarro, Riza Theresa; Kontonatsios, Georgios; Carter, Jacob; Toon, Elizabeth; McNaught, John; Timmermann, Carsten; Worboys, Michael; Ananiadou, Sophia

    2016-01-01

    Historical text archives constitute a rich and diverse source of information, which is becoming increasingly readily accessible, due to large-scale digitisation efforts. However, it can be difficult for researchers to explore and search such large volumes of data in an efficient manner. Text mining (TM) methods can help, through their ability to recognise various types of semantic information automatically, e.g., instances of concepts (places, medical conditions, drugs, etc.), synonyms/variant forms of concepts, and relationships holding between concepts (which drugs are used to treat which medical conditions, etc.). TM analysis allows search systems to incorporate functionality such as automatic suggestions of synonyms of user-entered query terms, exploration of different concepts mentioned within search results or isolation of documents in which concepts are related in specific ways. However, applying TM methods to historical text can be challenging, according to differences and evolutions in vocabulary, terminology, language structure and style, compared to more modern text. In this article, we present our efforts to overcome the various challenges faced in the semantic analysis of published historical medical text dating back to the mid 19th century. Firstly, we used evidence from diverse historical medical documents from different periods to develop new resources that provide accounts of the multiple, evolving ways in which concepts, their variants and relationships amongst them may be expressed. These resources were employed to support the development of a modular processing pipeline of TM tools for the robust detection of semantic information in historical medical documents with varying characteristics. We applied the pipeline to two large-scale medical document archives covering wide temporal ranges as the basis for the development of a publicly accessible semantically-oriented search system. The novel resources are available for research purposes, while

  14. Research on the new type of multi-functional satellite system for space debris detection

    Science.gov (United States)

    Guo, Linghua; Fu, Qiang; Jiang, Huilin; Xu, Xihe

    2017-05-01

    With the rapid development of space exploration and utilization, orbital debris increases dramatically, leading to great threat to human space activities and spacecraft security. In this paper, a new type of multi-functional space debris satellite system (MSDS) was put forward, which shared main optical system, and possessed functions of multidimensional information detection, polarized remote sensing and high rate transmission. The MSDS system can meet the requirements of detection and identification for the small orbital debris which is 1000km faraway, as well as the requirements of the data transmission by 50 Mbps to 2.5 Gbps@200-1000 km. At the same time, by the method of satellite orbital maneuver and attitude adjusting, the orbital debris information that is real-time, complex and refined, allweather can be acquired and transmitted by the new system. Such new type of multifunctional satellite system can provide important and effective technology for international orbital debris detection.

  15. An Approach for Automatic Orientation of Big Point Clouds from the Stationary Scanners Based on the Spherical Targets

    Directory of Open Access Journals (Sweden)

    YAO Jili

    2015-04-01

    Full Text Available Terrestrial laser scanning (TLS technology has high speed of data acquisition, large amount of point cloud, long distance of measuring. However, there are some disadvantages such as distance limitation in target detecting, hysteresis in point clouds processing, low automation and weaknesses of adapting long-distance topographic survey. In this case, we put forward a method on long-range targets detecting in big point clouds orientation. The method firstly searches point cloud rings that contain targets according to their engineering coordinate system. Then the detected rings are divided into sectors to detect targets in a very short time so as to obtain central coordinates of these targets. Finally, the position and orientation parameters of scanner are calculated and point clouds in scanner's own coordinate system(SOCS are converted into engineering coordinate system. The method is able to be applied in ordinary computers for long distance topographic(the distance between scanner and targets ranges from 180 to 700 m survey in mountainous areas with targets radius of 0.162m.

  16. Multi-channel integrated circuits for the detection and measurement of ionizing radiation

    International Nuclear Information System (INIS)

    Engel, G.L.; Duggireddi, N.; Vangapally, V.; Elson, J.M.; Sobotka, L.G.; Charity, R.J.

    2011-01-01

    The Integrated Circuits (IC) Design Research Laboratory at Southern Illinois University Edwardsville (SIUE) has collaborated with the Nuclear Reactions Group at Washington University (WU) to develop a family of multi-channel integrated circuits. To date, the collaboration has successfully produced two micro-chips. The first was an analog shaped and peak sensing chip with on-board constant-fraction discriminators and sparsified readout. This chip is known as Heavy-Ion Nuclear Physics-16 Channel (HINP16C). The second chip, christened PSD8C, was designed to logically complement (in terms of detector types) the HINP16C chip. Pulse Shape Discrimination-8 Channel (PSD8C), featuring three settable charge integration windows per channel, performs pulse shape discrimination (PSD). This paper summarizes the design, capabilities, and features of the HINP16C and PSD8C ICs. It proceeds to discuss the modifications, made to the ICs and their associated systems, which have attempted to improve ease of use, increase performance, and extend capabilities. The paper concludes with a brief discussion of what may be the next chip (employing a multi-sampling scheme) to be added to our CMOS ASIC 'tool box' for radiation detection instrumentation.

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

    Directory of Open Access Journals (Sweden)

    S. Makuti

    2018-05-01

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

  18. Anisotropy model for modern grain oriented electrical steel based on orientation distribution function

    Directory of Open Access Journals (Sweden)

    Fan Jiang

    2018-05-01

    Full Text Available Accurately modeling the anisotropic behavior of electrical steel is mandatory in order to perform good end simulations. Several approaches can be found in the literature for that purpose but the more often those methods are not able to deal with grain oriented electrical steel. In this paper, a method based on orientation distribution function is applied to modern grain oriented laminations. In particular, two solutions are proposed in order to increase the results accuracy. The first one consists in increasing the decomposition number of the cosine series on which the method is based. The second one consists in modifying the determination method of the terms belonging to this cosine series.

  19. Effects of Text Messaging on Academic Performance

    Directory of Open Access Journals (Sweden)

    Barks Amanda

    2011-12-01

    Full Text Available University students frequently send and receive cellular phone text messages during classroominstruction. Cognitive psychology research indicates that multi-tasking is frequently associatedwith performance cost. However, university students often have considerable experience withelectronic multi-tasking and may believe that they can devote necessary attention to a classroomlecture while sending and receiving text messages. In the current study, university students whoused text messaging were randomly assigned to one of two conditions: 1. a group that sent andreceived text messages during a lecture or, 2. a group that did not engage in text messagingduring the lecture. Participants who engaged in text messaging demonstrated significantlypoorer performance on a test covering lecture content compared with the group that did notsend and receive text messages. Participants exhibiting higher levels of text messaging skill hadsignificantly lower test scores than participants who were less proficient at text messaging. It ishypothesized that in terms of retention of lecture material, more frequent task shifting by thosewith greater text messaging proficiency contributed to poorer performance. Overall, the findingsdo not support the view, held by many university students, that this form of multitasking has littleeffect on the acquisition of lecture content. Results provide empirical support for teachers andprofessors who ban text messaging in the classroom.

  20. Multi-channel motor evoked potential monitoring during anterior cervical discectomy and fusion

    Directory of Open Access Journals (Sweden)

    Dong-Gun Kim

    Full Text Available Objectives: Anterior cervical discectomy and fusion (ACDF surgery is the most common surgical procedure for the cervical spine with low complication rate. Despite the potential prognostic benefit, intraoperative neurophysiological monitoring (IONM, a method for detecting impending neurological compromise, is not routinely used in ACDF surgery. The present study aimed to identify the potential benefits of monitoring multi-channel motor evoked potentials (MEPs during ACDF surgery. Methods: We retrospectively reviewed 200 consecutive patients who received IONM with multi-channel MEPs and somatosensory evoked potentials (SSEPs. On average, 9.2 muscles per patient were evaluated under MEP monitoring. Results: The rate of MEP change during surgery in the multi-level ACDF group was significantly higher than the single-level group. Two patients from the single-level ACDF group (1.7% and four patients from the multi-level ACDF group (4.9% experienced post-operative motor deficits. Multi-channel MEPs monitoring during single and multi-level ACDF surgery demonstrated higher sensitivity, specificity, positive predictive and negative predictive value than SSEP monitoring. Conclusions: Multi-channel MEP monitoring might be beneficial for the detection of segmental injury as well as long tract injury during single- and multi-level ACDF surgery. Significance: This is first large scale study to identify the usefulness of multi-channel MEPs in monitoring ACDF surgery. Keywords: Disc disease, Somatosensory evoked potentials, Intraoperative neurophysiological monitoring, Motor evoked potentials, Anterior cervical discectomy and fusion

  1. Novel images extraction model using improved delay vector variance feature extraction and multi-kernel neural network for EEG detection and prediction.

    Science.gov (United States)

    Ge, Jing; Zhang, Guoping

    2015-01-01

    Advanced intelligent methodologies could help detect and predict diseases from the EEG signals in cases the manual analysis is inefficient available, for instance, the epileptic seizures detection and prediction. This is because the diversity and the evolution of the epileptic seizures make it very difficult in detecting and identifying the undergoing disease. Fortunately, the determinism and nonlinearity in a time series could characterize the state changes. Literature review indicates that the Delay Vector Variance (DVV) could examine the nonlinearity to gain insight into the EEG signals but very limited work has been done to address the quantitative DVV approach. Hence, the outcomes of the quantitative DVV should be evaluated to detect the epileptic seizures. To develop a new epileptic seizure detection method based on quantitative DVV. This new epileptic seizure detection method employed an improved delay vector variance (IDVV) to extract the nonlinearity value as a distinct feature. Then a multi-kernel functions strategy was proposed in the extreme learning machine (ELM) network to provide precise disease detection and prediction. The nonlinearity is more sensitive than the energy and entropy. 87.5% overall accuracy of recognition and 75.0% overall accuracy of forecasting were achieved. The proposed IDVV and multi-kernel ELM based method was feasible and effective for epileptic EEG detection. Hence, the newly proposed method has importance for practical applications.

  2. MULTI-TEMPORAL AND MULTI-SENSOR IMAGE MATCHING BASED ON LOCAL FREQUENCY INFORMATION

    Directory of Open Access Journals (Sweden)

    X. Liu

    2012-08-01

    Full Text Available Image Matching is often one of the first tasks in many Photogrammetry and Remote Sensing applications. This paper presents an efficient approach to automated multi-temporal and multi-sensor image matching based on local frequency information. Two new independent image representations, Local Average Phase (LAP and Local Weighted Amplitude (LWA, are presented to emphasize the common scene information, while suppressing the non-common illumination and sensor-dependent information. In order to get the two representations, local frequency information is firstly obtained from Log-Gabor wavelet transformation, which is similar to that of the human visual system; then the outputs of odd and even symmetric filters are used to construct the LAP and LWA. The LAP and LWA emphasize on the phase and amplitude information respectively. As these two representations are both derivative-free and threshold-free, they are robust to noise and can keep as much of the image details as possible. A new Compositional Similarity Measure (CSM is also presented to combine the LAP and LWA with the same weight for measuring the similarity of multi-temporal and multi-sensor images. The CSM can make the LAP and LWA compensate for each other and can make full use of the amplitude and phase of local frequency information. In many image matching applications, the template is usually selected without consideration of its matching robustness and accuracy. In order to overcome this problem, a local best matching point detection is presented to detect the best matching template. In the detection method, we employ self-similarity analysis to identify the template with the highest matching robustness and accuracy. Experimental results using some real images and simulation images demonstrate that the presented approach is effective for matching image pairs with significant scene and illumination changes and that it has advantages over other state-of-the-art approaches, which include: the

  3. Extraction of the 3D local orientation of myocytes in human cardiac tissue using X-ray phase-contrast micro-tomography and multi-scale analysis.

    Science.gov (United States)

    Varray, François; Mirea, Iulia; Langer, Max; Peyrin, Françoise; Fanton, Laurent; Magnin, Isabelle E

    2017-05-01

    This paper presents a methodology to access the 3D local myocyte arrangements in fresh human post-mortem heart samples. We investigated the cardiac micro-structure at a high and isotropic resolution of 3.5 µm in three dimensions using X-ray phase micro-tomography at the European Synchrotron Radiation Facility. We then processed the reconstructed volumes to extract the 3D local orientation of the myocytes using a multi-scale approach with no segmentation. We created a simplified 3D model of tissue sample made of simulated myocytes with known size and orientations, to evaluate our orientation extraction method. Afterwards, we applied it to 2D histological cuts and to eight 3D left ventricular (LV) cardiac tissue samples. Then, the variation of the helix angles, from the endocardium to the epicardium, was computed at several spatial resolutions ranging from 3.6 3  mm 3 to 112 3  µm 3 . We measure an increased range of 20° to 30° from the coarsest resolution level to the finest level in the experimental samples. This result is in line with the higher values measured from histology. The displayed tractography demonstrates a rather smooth evolution of the transmural helix angle in six LV samples and a sudden discontinuity of the helix angle in two septum samples. These measurements bring a new vision of the human heart architecture from macro- to micro-scale. Copyright © 2017 Elsevier B.V. All rights reserved.

  4. Basic Test Framework for the Evaluation of Text Line Segmentation and Text Parameter Extraction

    Directory of Open Access Journals (Sweden)

    Darko Brodić

    2010-05-01

    Full Text Available Text line segmentation is an essential stage in off-line optical character recognition (OCR systems. It is a key because inaccurately segmented text lines will lead to OCR failure. Text line segmentation of handwritten documents is a complex and diverse problem, complicated by the nature of handwriting. Hence, text line segmentation is a leading challenge in handwritten document image processing. Due to inconsistencies in measurement and evaluation of text segmentation algorithm quality, some basic set of measurement methods is required. Currently, there is no commonly accepted one and all algorithm evaluation is custom oriented. In this paper, a basic test framework for the evaluation of text feature extraction algorithms is proposed. This test framework consists of a few experiments primarily linked to text line segmentation, skew rate and reference text line evaluation. Although they are mutually independent, the results obtained are strongly cross linked. In the end, its suitability for different types of letters and languages as well as its adaptability are its main advantages. Thus, the paper presents an efficient evaluation method for text analysis algorithms.

  5. SIMULASI TEKNIK POWER CONTROL DAN MULTI USER DETECTION PADA SISTEM KOMUNIKASI DS-CDMA

    Directory of Open Access Journals (Sweden)

    Yuli Christyono

    2012-02-01

    Full Text Available CDMA is interference limited multiple access system. Because all users transmit on the same frequency,internal interference generated by the system is the most significant factor in determining system capacity andcall quality. The transmit power for each user must be reduced to limit interference, however, the power shouldbe enough to maintain the required Eb/No (signal to noise ratio for a satisfactory call quality. Maximumcapacity is achieved when Eb/No of every user is at the minimum level needed for the acceptable channelperformance. As the MS moves around, the RF environment continuously changes due to fast and slow fading,external interference, shadowing , and other factors. The aim of the dynamic power control is to limittransmitted power on both the links while maintaining link quality under all conditions. Additional advantagesare longer mobile battery life and longer life span of BTS power amplifiers.In this research will be made a sumulation of power control and multi user detection to avoid the interferencebetween MS.Observations show that the increasing number of users will decrease the value of Signal to Interfrence Ratio(SIR / SIR below the target. To cope the growing number of users increases can be done by iteration / updatingpower transmit so the convergence computation can be reached and target value SIR can be achieved. Inaddition, to reduce interference can also be done by extending the number of chips.

  6. P1-30: Axis Orientation Effects on Interaction between Color-Selective Symmetry Detectors

    Directory of Open Access Journals (Sweden)

    Chia-Ching Wu

    2012-10-01

    Full Text Available We used a noise masking paradigm to examine the interaction between color-selective symmetry detection mechanisms in the visual system. We used a 2AFC paradigm in which a random dot noise mask was presented in both intervals. One interval contained a target, while the other, a random dot control. The target consisted of a red and a green symmetric pattern with the same (both were 45° or −45° or orthogonal (one 45°and the other −45° orientation. The observers were to determine which interval contained the symmetric target. We measured the target density threshold at various noise densities. For all conditions, the target density threshold increased with noise density with a slope 0.96 on log-log coordinates. The threshold for the same-orientation condition was lower than that for the orthogonal condition at all noise densities. We fit our data with a divisive inhibition model for symmetry pattern detection (Chen & Tyler, 2010 PLOS One, in which the response of a symmetry detector is the excitation of a linear symmetry operator raised to a power and then divided by the divisive inhibition from all relevant symmetry operators. The best fit showed that the mutual inhibition between symmetry detectors in the same-orientation condition was only 13% of that in the orthogonal condition. Hence, instead of a strong same-orientation inhibition commonly observed in experiments using Gabor patches, it is actually easier for the visual system to integrate symmetric patterns of the same symmetric axis.

  7. Subjective impression of differences in realism, source width, and orientation between auralizations created from multi-channel anechoic recordings

    DEFF Research Database (Denmark)

    Vigeant, Michelle C.; Wang, Lily M.; Rindel, Jens Holger

    2005-01-01

    in realism and source width. Auralizations were made using three different types of musical instruments: woodwinds (flute), brass (trombone) and strings (violin). Subjects were asked to rate each musical track on a seven-point scale for the degree of realism and source width. An analysis of variance (ANOVA......) was carried out to determine the differences between the number of channels and the effect of instrument. A second test was conducted to assess the degree of difficulty in detecting source orientation (facing the audience or facing the stage wall) depending on the number of channels (one, four or thirteen......) and the amount of absorption in the room. [Work supported by the National Science Foundation.]...

  8. An Adaptive Orientation Estimation Method for Magnetic and Inertial Sensors in the Presence of Magnetic Disturbances

    Directory of Open Access Journals (Sweden)

    Bingfei Fan

    2017-05-01

    Full Text Available Magnetic and inertial sensors have been widely used to estimate the orientation of human segments due to their low cost, compact size and light weight. However, the accuracy of the estimated orientation is easily affected by external factors, especially when the sensor is used in an environment with magnetic disturbances. In this paper, we propose an adaptive method to improve the accuracy of orientation estimations in the presence of magnetic disturbances. The method is based on existing gradient descent algorithms, and it is performed prior to sensor fusion algorithms. The proposed method includes stationary state detection and magnetic disturbance severity determination. The stationary state detection makes this method immune to magnetic disturbances in stationary state, while the magnetic disturbance severity determination helps to determine the credibility of magnetometer data under dynamic conditions, so as to mitigate the negative effect of the magnetic disturbances. The proposed method was validated through experiments performed on a customized three-axis instrumented gimbal with known orientations. The error of the proposed method and the original gradient descent algorithms were calculated and compared. Experimental results demonstrate that in stationary state, the proposed method is completely immune to magnetic disturbances, and in dynamic conditions, the error caused by magnetic disturbance is reduced by 51.2% compared with original MIMU gradient descent algorithm.

  9. Multi-Cultural Competency-Based Vocational Curricula. Food Service. Multi-Cultural Competency-Based Vocational/Technical Curricula Series.

    Science.gov (United States)

    Hepburn, Larry; Shin, Masako

    This document, one of eight in a multi-cultural competency-based vocational/technical curricula series, is on food service. This program is designed to run 24 weeks and cover 15 instructional areas: orientation, sanitation, management/planning, preparing food for cooking, preparing beverages, cooking eggs, cooking meat, cooking vegetables,…

  10. Effect of multi-layered bottom electrodes on the orientation of strontium-doped lead zirconate titanate thin films

    Energy Technology Data Exchange (ETDEWEB)

    Bhaskaran, M. [Microelectronics and Materials Technology Centre, School of Electrical and Computer Engineering, RMIT University, GPO Box 2476V, Melbourne, Victoria 3001 (Australia)], E-mail: madhu.bhaskaran@gmail.com; Sriram, S. [Microelectronics and Materials Technology Centre, School of Electrical and Computer Engineering, RMIT University, GPO Box 2476V, Melbourne, Victoria 3001 (Australia); Mitchell, D.R.G.; Short, K.T. [Institute of Materials Engineering, Australian Nuclear Science and Technology Organisation (ANSTO), PMB 1, Menai, New South Wales 2234 (Australia); Holland, A.S. [Microelectronics and Materials Technology Centre, School of Electrical and Computer Engineering, RMIT University, GPO Box 2476V, Melbourne, Victoria 3001 (Australia)

    2008-09-30

    This article discusses the results from X-ray diffraction (XRD) analysis of piezoelectric strontium-doped lead zirconate titanate (PSZT) thin films deposited on multi-layer coatings on silicon. The films were deposited by RF magnetron sputtering on a metal coated substrate. The aim was to exploit the pronounced piezoelectric effect that is theoretically expected normal to the substrate. This work highlighted the influence that the bottom electrode architecture exerts on the final crystalline orientation of the deposited thin films. A number of bottom electrode architectures were used, with the uppermost metal layer on which PSZT was deposited being gold or platinum. The XRD analysis revealed that the unit cell of the PSZT thin films deposited on gold and on platinum were deformed, relative to expected unit cell dimensions. Experimental results have been used to estimate the unit cell parameters. The XRD results were then indexed based on these unit cell parameters. The choice and the thickness of the intermediate adhesion layers influenced the relative intensity, and in some cases, the presence of perovskite peaks. In some cases, undesirable reactions between the bottom electrode layers were observed, and layer architectures to overcome these reactions are also discussed.

  11. THE USE OF COMPUTER VISION ALGORITHMS FOR AUTOMATIC ORIENTATION OF TERRESTRIAL LASER SCANNING DATA

    Directory of Open Access Journals (Sweden)

    J. S. Markiewicz

    2016-06-01

    Full Text Available The paper presents analysis of the orientation of terrestrial laser scanning (TLS data. In the proposed data processing methodology, point clouds are considered as panoramic images enriched by the depth map. Computer vision (CV algorithms are used for orientation, which are applied for testing the correctness of the detection of tie points and time of computations, and for assessing difficulties in their implementation. The BRISK, FASRT, MSER, SIFT, SURF, ASIFT and CenSurE algorithms are used to search for key-points. The source data are point clouds acquired using a Z+F 5006h terrestrial laser scanner on the ruins of Iłża Castle, Poland. Algorithms allowing combination of the photogrammetric and CV approaches are also presented.

  12. Hand Proximity Differentially Affects Visual Working Memory for Color and Orientation in a Binding Task

    Directory of Open Access Journals (Sweden)

    Shane P. Kelly

    2014-04-01

    Full Text Available Observers determined whether two sequentially presented arrays of six lines were the same or different. Differences, when present, involved either a swap in the color of two lines or a swap in the orientation of two lines. Thus, accurate change detection required the binding of color and orientation information for each line within visual working memory. Holding viewing distance constant, the proximity of the arrays to the hands was manipulated. Placing the hands near the to-be-remembered array decreased participants’ ability to remember color information, but increased their ability to remember orientation information. This pair of results indicates that hand proximity differentially affects the processing of various types of visual information, a conclusion broadly consistent with functional and anatomical differences in the magnocellular and parvocellular pathways. It further indicates that hand proximity affects the likelihood that various object features will be encoded into integrated object files.

  13. Co-Labeling for Multi-View Weakly Labeled Learning.

    Science.gov (United States)

    Xu, Xinxing; Li, Wen; Xu, Dong; Tsang, Ivor W

    2016-06-01

    It is often expensive and time consuming to collect labeled training samples in many real-world applications. To reduce human effort on annotating training samples, many machine learning techniques (e.g., semi-supervised learning (SSL), multi-instance learning (MIL), etc.) have been studied to exploit weakly labeled training samples. Meanwhile, when the training data is represented with multiple types of features, many multi-view learning methods have shown that classifiers trained on different views can help each other to better utilize the unlabeled training samples for the SSL task. In this paper, we study a new learning problem called multi-view weakly labeled learning, in which we aim to develop a unified approach to learn robust classifiers by effectively utilizing different types of weakly labeled multi-view data from a broad range of tasks including SSL, MIL and relative outlier detection (ROD). We propose an effective approach called co-labeling to solve the multi-view weakly labeled learning problem. Specifically, we model the learning problem on each view as a weakly labeled learning problem, which aims to learn an optimal classifier from a set of pseudo-label vectors generated by using the classifiers trained from other views. Unlike traditional co-training approaches using a single pseudo-label vector for training each classifier, our co-labeling approach explores different strategies to utilize the predictions from different views, biases and iterations for generating the pseudo-label vectors, making our approach more robust for real-world applications. Moreover, to further improve the weakly labeled learning on each view, we also exploit the inherent group structure in the pseudo-label vectors generated from different strategies, which leads to a new multi-layer multiple kernel learning problem. Promising results for text-based image retrieval on the NUS-WIDE dataset as well as news classification and text categorization on several real-world multi

  14. Wind-related orientation patterns in diurnal, crepuscular and nocturnal high-altitude insect migrants

    Directory of Open Access Journals (Sweden)

    Gao eHu

    2016-02-01

    Full Text Available Most insect migrants fly at considerable altitudes (hundreds of meters above the ground where they utilize fast-flowing winds to achieve rapid and comparatively long-distance transport. The nocturnal aerial migrant fauna has been well studied with entomological radars, and many studies have demonstrated that flight orientations are frequently grouped around a common direction in a range of nocturnal insect migrants. Common orientation typically occurs close to the downwind direction (thus ensuring that a large component of the insects’ self-powered speed is directed downstream, and in nocturnal insects at least, the downwind headings are seemingly maintained by direct detection of wind-related turbulent cues. Despite being far more abundant and speciose, the day-flying windborne migrant fauna has been much less studied by radar; thus the frequency of wind-related common orientation patterns and the sensory mechanisms involved in their formation remain to be established. Here we analyze a large dataset of >600,000 radar-detected ‘medium-sized’ windborne insect migrants (body mass from 10 to 70 mg, flying hundreds of meters above southern UK, during the afternoon, in the period around sunset, and in the middle of the night. We found that wind-related common orientation was almost ubiquitous during the day (present in 97% of all ‘migration events’ analyzed, and was also frequent at sunset (85% and at night (81%. Headings were systematically offset to the right of the flow at night-time (as predicted from the use of turbulence cues for flow assessment, but there was no directional bias in the offsets during the day or at sunset. Orientation ‘performance’ significantly increased with increasing flight altitude throughout the day and night. We conclude by discussing sensory mechanisms which most likely play a role in the selection and maintenance of wind-related flight headings.

  15. Decision algorithms in fire detection systems

    Directory of Open Access Journals (Sweden)

    Ristić Jovan D.

    2011-01-01

    Full Text Available Analogue (and addressable fire detection systems enables a new quality in improving sensitivity to real fires and reducing susceptibility to nuisance alarm sources. Different decision algorithms types were developed with intention to improve sensitivity and reduce false alarm occurrence. At the beginning, it was free alarm level adjustment based on preset level. Majority of multi-criteria decision work was based on multi-sensor (multi-signature decision algorithms - using different type of sensors on the same location or, rather, using different aspects (level and rise of one sensor measured value. Our idea is to improve sensitivity and reduce false alarm occurrence by forming groups of sensors that work in similar conditions (same world side in the building, same or similar technology or working time. Original multi-criteria decision algorithms based on level, rise and difference of level and rise from group average are discussed in this paper.

  16. Low seroprevalence of bartonella species in danish elite orienteers

    DEFF Research Database (Denmark)

    Schiellerup, Peter; Dyhr, Thomas; Rolain, Jean Marc

    2004-01-01

    participants were tested for antibodies against B. henselae, B. quintana and B. elizabethae using immunofluorescent antibody tests. Surprisingly, Bartonella antibodies were only detected in sera from 5 persons: B. henselae from 1 elite orienteer, 1 handball player and 1 blood donor. B. elizabethae antibodies...... were detected in 1 handball player and 1 basketball player. We found no association between elite orienteers and the prevalence of Bartonella antibody positivity. This is in contrast to the Swedish study, and might be explained by the use of different serological methods in the 2 studies; to determine...

  17. HPLC ‘Multi-Analyte’ Detection Method

    Energy Technology Data Exchange (ETDEWEB)

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

    2009-07-15

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

  18. Multi-flux-transformer MRI detection with an atomic magnetometer.

    Science.gov (United States)

    Savukov, Igor; Karaulanov, Todor

    2014-12-01

    Recently, anatomical ultra-low field (ULF) MRI has been demonstrated with an atomic magnetometer (AM). A flux-transformer (FT) has been used for decoupling MRI fields and gradients to avoid their negative effects on AM performance. The field of view (FOV) was limited because of the need to compromise between the size of the FT input coil and MRI sensitivity per voxel. Multi-channel acquisition is a well-known solution to increase FOV without significantly reducing sensitivity. In this paper, we demonstrate twofold FOV increase with the use of three FT input coils. We also show that it is possible to use a single atomic magnetometer and single acquisition channel to acquire three independent MRI signals by applying a frequency-encoding gradient along the direction of the detection array span. The approach can be generalized to more channels and can be critical for imaging applications of non-cryogenic ULF MRI where FOV needs to be large, including head, hand, spine, and whole-body imaging. Copyright © 2014 Elsevier Inc. All rights reserved.

  19. Competition Between Endogenous and Exogenous Orienting of Visual Attention

    Science.gov (United States)

    Berger, Andrea; Henik, Avishai; Rafal, Robert

    2005-01-01

    The relation between reflexive and voluntary orienting of visual attention was investigated with 4 experiments: a simple detection task, a localization task, a saccade toward the target task, and a target identification task in which discrimination difficulty was manipulated. Endogenous and exogenous orienting cues were presented in each trial and…

  20. Multi-stage classification method oriented to aerial image based on low-rank recovery and multi-feature fusion sparse representation.

    Science.gov (United States)

    Ma, Xu; Cheng, Yongmei; Hao, Shuai

    2016-12-10

    Automatic classification of terrain surfaces from an aerial image is essential for an autonomous unmanned aerial vehicle (UAV) landing at an unprepared site by using vision. Diverse terrain surfaces may show similar spectral properties due to the illumination and noise that easily cause poor classification performance. To address this issue, a multi-stage classification algorithm based on low-rank recovery and multi-feature fusion sparse representation is proposed. First, color moments and Gabor texture feature are extracted from training data and stacked as column vectors of a dictionary. Then we perform low-rank matrix recovery for the dictionary by using augmented Lagrange multipliers and construct a multi-stage terrain classifier. Experimental results on an aerial map database that we prepared verify the classification accuracy and robustness of the proposed method.

  1. Multi-Angle Snowflake Camera Instrument Handbook

    Energy Technology Data Exchange (ETDEWEB)

    Stuefer, Martin [Univ. of Alaska, Fairbanks, AK (United States); Bailey, J. [Univ. of Alaska, Fairbanks, AK (United States)

    2016-07-01

    The Multi-Angle Snowflake Camera (MASC) takes 9- to 37-micron resolution stereographic photographs of free-falling hydrometers from three angles, while simultaneously measuring their fall speed. Information about hydrometeor size, shape orientation, and aspect ratio is derived from MASC photographs. The instrument consists of three commercial cameras separated by angles of 36º. Each camera field of view is aligned to have a common single focus point about 10 cm distant from the cameras. Two near-infrared emitter pairs are aligned with the camera’s field of view within a 10-angular ring and detect hydrometeor passage, with the lower emitters configured to trigger the MASC cameras. The sensitive IR motion sensors are designed to filter out slow variations in ambient light. Fall speed is derived from successive triggers along the fall path. The camera exposure times are extremely short, in the range of 1/25,000th of a second, enabling the MASC to capture snowflake sizes ranging from 30 micrometers to 3 cm.

  2. Falling-incident detection and throughput enhancement in a multi-camera video-surveillance system.

    Science.gov (United States)

    Shieh, Wann-Yun; Huang, Ju-Chin

    2012-09-01

    For most elderly, unpredictable falling incidents may occur at the corner of stairs or a long corridor due to body frailty. If we delay to rescue a falling elder who is likely fainting, more serious consequent injury may occur. Traditional secure or video surveillance systems need caregivers to monitor a centralized screen continuously, or need an elder to wear sensors to detect falling incidents, which explicitly waste much human power or cause inconvenience for elders. In this paper, we propose an automatic falling-detection algorithm and implement this algorithm in a multi-camera video surveillance system. The algorithm uses each camera to fetch the images from the regions required to be monitored. It then uses a falling-pattern recognition algorithm to determine if a falling incident has occurred. If yes, system will send short messages to someone needs to be noticed. The algorithm has been implemented in a DSP-based hardware acceleration board for functionality proof. Simulation results show that the accuracy of falling detection can achieve at least 90% and the throughput of a four-camera surveillance system can be improved by about 2.1 times. Copyright © 2011 IPEM. Published by Elsevier Ltd. All rights reserved.

  3. Multiplex TaqMan® detection of pathogenic and multi-drug resistant Salmonella.

    Science.gov (United States)

    Singh, Prashant; Mustapha, Azlin

    2013-09-02

    Overuse of antibiotics in the medical and animal industries is one of the major causes for the development of multi-drug-resistant (MDR) food pathogens that are often difficult to treat. In the past few years, higher incidences of outbreaks caused by MDR Salmonella have been increasingly documented. The objective of this study was to develop a rapid multiplex real-time polymerase chain reaction (PCR) assay for simultaneous detection of pathogenic and MDR Salmonella spp. A multiplex TaqMan®real-time PCR was designed by targeting the invasin virulence gene (invA), and four commonly found antibiotic resistance genes, viz. ampicillin, chloramphenicol, streptomycin and tetracycline. To avoid false negative results and to increase the reliability of the assay, an internal amplification control (IAC) was added which was detected using a locked nucleic acid (LNA) probe. In serially diluted (5 ng-50 fg) DNA samples, the assay was able to detect 100 genomic equivalents of Salmonella, while in a multiplex format, the sensitivity was 1000 genomic equivalents. The assay performed equally well on artificially contaminated samples of beef trim, ground beef of different fat contents (73:27, 80:20, 85:15 and 93:7), chicken rinse, ground chicken, ground turkey, egg, spinach and tomato. While the detection limit for un-enriched inoculated food samples was 10(4) CFU/g, this was improved to 10 CFU/g after a 12-h enrichment in buffered peptone water, with 100% reproducibility. The multiplex real-time assay developed in this study can be used as a valuable tool to detect MDR virulent Salmonella, thus enhancing the safety of food. © 2013.

  4. Role of Computer Aided Diagnosis (CAD in the detection of pulmonary nodules on 64 row multi detector computed tomography

    Directory of Open Access Journals (Sweden)

    K Prakashini

    2016-01-01

    Full Text Available Aims and Objectives: To determine the overall performance of an existing CAD algorithm with thin-section computed tomography (CT in the detection of pulmonary nodules and to evaluate detection sensitivity at a varying range of nodule density, size, and location. Materials and Methods: A cross-sectional prospective study was conducted on 20 patients with 322 suspected nodules who underwent diagnostic chest imaging using 64-row multi-detector CT. The examinations were evaluated on reconstructed images of 1.4 mm thickness and 0.7 mm interval. Detection of pulmonary nodules, initially by a radiologist of 2 years experience (RAD and later by CAD lung nodule software was assessed. Then, CAD nodule candidates were accepted or rejected accordingly. Detected nodules were classified based on their size, density, and location. The performance of the RAD and CAD system was compared with the gold standard that is true nodules confirmed by consensus of senior RAD and CAD together. The overall sensitivity and false-positive (FP rate of CAD software was calculated. Observations and Results: Of the 322 suspected nodules, 221 were classified as true nodules on the consensus of senior RAD and CAD together. Of the true nodules, the RAD detected 206 (93.2% and 202 (91.4% by the CAD. CAD and RAD together picked up more number of nodules than either CAD or RAD alone. Overall sensitivity for nodule detection with the CAD program was 91.4%, and FP detection per patient was 5.5%. The CAD showed comparatively higher sensitivity for nodules of size 4-10 mm (93.4% and nodules in hilar (100% and central (96.5% location when compared to RAD′s performance. Conclusion: CAD performance was high in detecting pulmonary nodules including the small size and low-density nodules. CAD even with relatively high FP rate, assists and improves RAD′s performance as a second reader, especially for nodules located in the central and hilar region and for small nodules by saving RADs time.

  5. A New Approach to Performing Bundle Adjustment for Time Series UAV Images 3D Building Change Detection

    Directory of Open Access Journals (Sweden)

    Wenzhuo Li

    2017-06-01

    Full Text Available Successful change detection in multi-temporal images relies on high spatial co-registration accuracy. However, co-registration accuracy alone cannot meet the needs of change detection when using several ground control points to separately geo-reference multi-temporal images from unmanned aerial vehicles (UAVs. This letter reports on a new approach to perform bundle adjustment—named united bundle adjustment (UBA—to solve this co-registration problem for change detection in multi-temporal UAV images. In UBA, multi-temporal UAV images are matched with each other to construct a unified tie point net. One single bundle adjustment process is performed on the unified tie point net, placing every image into the same coordinate system and thus automatically accomplishing spatial co-registration. We then perform change detection using both orthophotos and three-dimensional height information derived from dense image matching techniques. Experimental results show that UBA co-registration accuracy is higher than the accuracy of commonly-used approaches for multi-temporal UAV images. Our proposed preprocessing method extends the capacities of consumer-level UAVs so they can eventually meet the growing need for automatic building change detection and dynamic monitoring using only RGB band images.

  6. Watch out! Magnetoencephalographic evidence for early modulation of attention orienting by fearful gaze cueing.

    Directory of Open Access Journals (Sweden)

    Fanny Lachat

    Full Text Available Others' gaze and emotional facial expression are important cues for the process of attention orienting. Here, we investigated with magnetoencephalography (MEG whether the combination of averted gaze and fearful expression may elicit a selectively early effect of attention orienting on the brain responses to targets. We used the direction of gaze of centrally presented fearful and happy faces as the spatial attention orienting cue in a Posner-like paradigm where the subjects had to detect a target checkerboard presented at gazed-at (valid trials or non gazed-at (invalid trials locations of the screen. We showed that the combination of averted gaze and fearful expression resulted in a very early attention orienting effect in the form of additional parietal activity between 55 and 70 ms for the valid versus invalid targets following fearful gaze cues. No such effect was obtained for the targets following happy gaze cues. This early cue-target validity effect selective of fearful gaze cues involved the left superior parietal region and the left lateral middle occipital region. These findings provide the first evidence for an effect of attention orienting induced by fearful gaze in the time range of C1. In doing so, they demonstrate the selective impact of combined gaze and fearful expression cues in the process of attention orienting.

  7. Dynamic Task Allocation in Multi-Hop Multimedia Wireless Sensor Networks with Low Mobility

    Directory of Open Access Journals (Sweden)

    Klaus Moessner

    2013-10-01

    Full Text Available This paper presents a task allocation-oriented framework to enable efficient in-network processing and cost-effective multi-hop resource sharing for dynamic multi-hop multimedia wireless sensor networks with low node mobility, e.g., pedestrian speeds. The proposed system incorporates a fast task reallocation algorithm to quickly recover from possible network service disruptions, such as node or link failures. An evolutional self-learning mechanism based on a genetic algorithm continuously adapts the system parameters in order to meet the desired application delay requirements, while also achieving a sufficiently long network lifetime. Since the algorithm runtime incurs considerable time delay while updating task assignments, we introduce an adaptive window size to limit the delay periods and ensure an up-to-date solution based on node mobility patterns and device processing capabilities. To the best of our knowledge, this is the first study that yields multi-objective task allocation in a mobile multi-hop wireless environment under dynamic conditions. Simulations are performed in various settings, and the results show considerable performance improvement in extending network lifetime compared to heuristic mechanisms. Furthermore, the proposed framework provides noticeable reduction in the frequency of missing application deadlines.

  8. Generation and Detection of Alignments in Gabor Patterns

    Directory of Open Access Journals (Sweden)

    Samy Blusseau

    2016-11-01

    Full Text Available This paper presents a method to be used in psychophysical experiments to compare directly visual perception to an a contrario algorithm, on a straight patterns detection task. The method is composed of two parts. The first part consists in building a stimulus, namely an array of oriented elements, in which an alignment is present with variable salience. The second part focuses on a detection algorithm, based on the a contrario theory, which is designed to predict which alignment will be considered as the most salient in a given stimulus.

  9. EDITORIAL: Optical orientation Optical orientation

    Science.gov (United States)

    SAME ADDRESS *, Yuri; Landwehr, Gottfried

    2008-11-01

    priority of the discovery in the literature, which was partly caused by the existence of the Iron Curtain. I had already enjoyed contact with Boris in the 1980s when the two volumes of Landau Level Spectroscopy were being prepared [2]. He was one of the pioneers of magneto-optics in semiconductors. In the 1950s the band structure of germanium and silicon was investigated by magneto-optical methods, mainly in the United States. No excitonic effects were observed and the band structure parameters were determined without taking account of excitons. However, working with cuprous oxide, which is a direct semiconductor with a relative large energy gap, Zakharchenya and his co-worker Seysan showed that in order to obtain correct band structure parameters, it is necessary to take excitons into account [3]. About 1970 Boris started work on optical orientation. Early work by Hanle in Germany in the 1920s on the depolarization of luminescence in mercury vapour by a transverse magnetic field was not appreciated for a long time. Only in the late 1940s did Kastler and co-workers in Paris begin a systematic study of optical pumping, which led to the award of a Nobel prize. The ideas of optical pumping were first applied by Georges Lampel to solid state physics in 1968. He demonstrated optical orientation of free carriers in silicon. The detection method was nuclear magnetic resonance; optically oriented free electrons dynamically polarized the 29Si nuclei of the host lattice. The first optical detection of spin orientation was demonstrated by with the III-V semiconductor GaSb by Parsons. Due to the various interaction mechanisms of spins with their environment, the effects occurring in semiconductors are naturally more complex than those in atoms. Optical detection is now the preferred method to detect spin alignment in semiconductors. The orientation of spins in crystals pumped with circularly polarized light is deduced from the degree of circular polarization of the recombination

  10. The impact of inverted text on visual word processing: An fMRI study.

    Science.gov (United States)

    Sussman, Bethany L; Reddigari, Samir; Newman, Sharlene D

    2018-06-01

    Visual word recognition has been studied for decades. One question that has received limited attention is how different text presentation orientations disrupt word recognition. By examining how word recognition processes may be disrupted by different text orientations it is hoped that new insights can be gained concerning the process. Here, we examined the impact of rotating and inverting text on the neural network responsible for visual word recognition focusing primarily on a region of the occipto-temporal cortex referred to as the visual word form area (VWFA). A lexical decision task was employed in which words and pseudowords were presented in one of three orientations (upright, rotated or inverted). The results demonstrate that inversion caused the greatest disruption of visual word recognition processes. Both rotated and inverted text elicited increased activation in spatial attention regions within the right parietal cortex. However, inverted text recruited phonological and articulatory processing regions within the left inferior frontal and left inferior parietal cortices. Finally, the VWFA was found to not behave similarly to the fusiform face area in that unusual text orientations resulted in increased activation and not decreased activation. It is hypothesized here that the VWFA activation is modulated by feedback from linguistic processes. Copyright © 2018 Elsevier Inc. All rights reserved.

  11. APPLYING PROFESSIONALLY ORIENTED PROBLEMS OF MATHEMATICAL MODELING IN TEACHING STUDENTS OF ENGINEERING DEPARTMENTS

    Directory of Open Access Journals (Sweden)

    Natal’ya Yur’evna Gorbunova

    2017-06-01

    Full Text Available We described several aspects of organizing student research work, as well as solving a number of mathematical modeling problems: professionally-oriented, multi-stage, etc. We underlined the importance of their economic content. Samples of using such problems in teaching Mathematics at agricultural university were given. Several questions connected with information material selection and peculiarities of research problems application were described. Purpose. The author aims to show the possibility and necessity of using professionally-oriented problems of mathematical modeling in teaching Mathematics at agricultural university. The subject of analysis is including such problems into educational process. Methodology. The main research method is dialectical method of obtaining knowledge of finding approaches to selection, writing and using mathematical modeling and professionally-oriented problems in educational process; the methodology is study of these methods of obtaining knowledge. Results. As a result of analysis of literature, students opinions, observation of students work, and taking into account personal teaching experience, it is possible to make conclusion about importance of using mathematical modeling problems, as it helps to systemize theoretical knowledge, apply it to practice, raise students study motivation in engineering sphere. Practical implications. Results of the research can be of interest for teachers of Mathematics in preparing Bachelor and Master students of engineering departments of agricultural university both for theoretical research and for modernization of study courses.

  12. Multi-Sensor Integration to Map Odor Distribution for the Detection of Chemical Sources

    Directory of Open Access Journals (Sweden)

    Xiang Gao

    2016-07-01

    Full Text Available This paper addresses the problem of mapping odor distribution derived from a chemical source using multi-sensor integration and reasoning system design. Odor localization is the problem of finding the source of an odor or other volatile chemical. Most localization methods require a mobile vehicle to follow an odor plume along its entire path, which is time consuming and may be especially difficult in a cluttered environment. To solve both of the above challenges, this paper proposes a novel algorithm that combines data from odor and anemometer sensors, and combine sensors’ data at different positions. Initially, a multi-sensor integration method, together with the path of airflow was used to map the pattern of odor particle movement. Then, more sensors are introduced at specific regions to determine the probable location of the odor source. Finally, the results of odor source location simulation and a real experiment are presented.

  13. Research of ddi based on multi-label conditional random field

    Directory of Open Access Journals (Sweden)

    Yu Yangzhi

    2017-01-01

    Full Text Available The detection of drug name and drug-drug interaction(DDI is considered as a sequence labeling task in this paper. We present the multi-label CRF method to complete it. Compared to the traditional method, our method can not only identify drug names, but also can identify drug-drug interaction. According to the characteristics of medical texts, this paper extracts the good features of the description of DDI. The proposed method has good performance in DDIExtraction 2013 evaluation corpus.

  14. A preliminary approach to creating an overview of lactoferrin multi-functionality utilizing a text mining method.

    Science.gov (United States)

    Shimazaki, Kei-ichi; Kushida, Tatsuya

    2010-06-01

    Lactoferrin is a multi-functional metal-binding glycoprotein that exhibits many biological functions of interest to many researchers from the fields of clinical medicine, dentistry, pharmacology, veterinary medicine, nutrition and milk science. To date, a number of academic reports concerning the biological activities of lactoferrin have been published and are easily accessible through public data repositories. However, as the literature is expanding daily, this presents challenges in understanding the larger picture of lactoferrin function and mechanisms. In order to overcome the "analysis paralysis" associated with lactoferrin information, we attempted to apply a text mining method to the accumulated lactoferrin literature. To this end, we used the information extraction system GENPAC (provided by Nalapro Technologies Inc., Tokyo). This information extraction system uses natural language processing and text mining technology. This system analyzes the sentences and titles from abstracts stored in the PubMed database, and can automatically extract binary relations that consist of interactions between genes/proteins, chemicals and diseases/functions. We expect that such information visualization analysis will be useful in determining novel relationships among a multitude of lactoferrin functions and mechanisms. We have demonstrated the utilization of this method to find pathways of lactoferrin participation in neovascularization, Helicobacter pylori attack on gastric mucosa, atopic dermatitis and lipid metabolism.

  15. Multi-core parallelism in a column-store

    NARCIS (Netherlands)

    Gawade, M.M.

    2017-01-01

    The research reported in this thesis addresses several challenges of improving the efficiency and effectiveness of parallel processing of analytical database queries on modern multi- and many-core systems, using an open-source column-oriented analytical database management system, MonetDB, for

  16. Robust fault detection for the dynamics of high-speed train with multi-source finite frequency interference.

    Science.gov (United States)

    Bai, Weiqi; Dong, Hairong; Yao, Xiuming; Ning, Bin

    2018-04-01

    This paper proposes a composite fault detection scheme for the dynamics of high-speed train (HST), using an unknown input observer-like (UIO-like) fault detection filter, in the presence of wind gust and operating noises which are modeled as disturbance generated by exogenous system and unknown multi-source disturbance within finite frequency domain. Using system input and system output measurements, the fault detection filter is designed to generate the needed residual signals. In order to decouple disturbance from residual signals without truncating the influence of faults, this paper proposes a method to partition the disturbance into two parts. One subset of the disturbance does not appear in residual dynamics, and the influence of the other subset is constrained by H ∞ performance index in a finite frequency domain. A set of detection subspaces are defined, and every different fault is assigned to its own detection subspace to guarantee the residual signals are diagonally affected promptly by the faults. Simulations are conducted to demonstrate the effectiveness and merits of the proposed method. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

  17. Stochastic multi-period multi-product multi-objective Aggregate Production Planning model in multi-echelon supply chain

    Directory of Open Access Journals (Sweden)

    Kaveh Khalili-Damghani

    2017-07-01

    Full Text Available In this paper a multi-period multi-product multi-objective aggregate production planning (APP model is proposed for an uncertain multi-echelon supply chain considering financial risk, customer satisfaction, and human resource training. Three conflictive objective functions and several sets of real constraints are considered concurrently in the proposed APP model. Some parameters of the proposed model are assumed to be uncertain and handled through a two-stage stochastic programming (TSSP approach. The proposed TSSP is solved using three multi-objective solution procedures, i.e., the goal attainment technique, the modified ε-constraint method, and STEM method. The whole procedure is applied in an automotive resin and oil supply chain as a real case study wherein the efficacy and applicability of the proposed approaches are illustrated in comparison with existing experimental production planning method.

  18. Combination of Morphological Operations with Structure based Partitioning and grouping for Text String detection from Natural Scenes

    OpenAIRE

    Vyankatesh V. Rampurkar; Gyankamal J. Chhajed

    2014-01-01

    Text information in natural scene images serves as important clues for many image-based applications such as scene perceptive, content-based image retrieval, assistive direction-finding and automatic geocoding. Now days different approaches like countours based, Image binarization and enhancement based, Gradient based and colour reduction based techniques can be used for the text detection from natural scenes. In this paper the combination of morphological operations with structure based part...

  19. From text to intertext: Intertextuality as a paradigm for reading Matthew

    Directory of Open Access Journals (Sweden)

    Stefan Alkier

    2005-10-01

    Full Text Available In this article intertextuality is introduced as one important part of a theory of the semiotics of biblical texts. Intertextuality is an essential factor for the generation of the meanings of a text in the acts of the production and reception of a text. It opens the internal structure of a text with regard to its relations to other texts. The semiotic concept of intertextuality distinguishes three ways of intertextual readings: production-oriented intertextuality, reception-oriented intertextuality and experimental intertextuality. This wide but differentiated concept of intertextuality can serve as a theory and helpful method for investigations of the history of biblical texts as well as for reflected school lessons, sermons and poetics in today’s times. An intertextual reading of the first chapter of Matthew provides a test case of this semiotic concept of intertextuality.

  20. Research on segmentation based on multi-atlas in brain MR image

    Science.gov (United States)

    Qian, Yuejing

    2018-03-01

    Accurate segmentation of specific tissues in brain MR image can be effectively achieved with the multi-atlas-based segmentation method, and the accuracy mainly depends on the image registration accuracy and fusion scheme. This paper proposes an automatic segmentation method based on the multi-atlas for brain MR image. Firstly, to improve the registration accuracy in the area to be segmented, we employ a target-oriented image registration method for the refinement. Then In the label fusion, we proposed a new algorithm to detect the abnormal sparse patch and simultaneously abandon the corresponding abnormal sparse coefficients, this method is made based on the remaining sparse coefficients combined with the multipoint label estimator strategy. The performance of the proposed method was compared with those of the nonlocal patch-based label fusion method (Nonlocal-PBM), the sparse patch-based label fusion method (Sparse-PBM) and majority voting method (MV). Based on our experimental results, the proposed method is efficient in the brain MR images segmentation compared with MV, Nonlocal-PBM, and Sparse-PBM methods.

  1. Pedestrian detection based on redundant wavelet transform

    Science.gov (United States)

    Huang, Lin; Ji, Liping; Hu, Ping; Yang, Tiejun

    2016-10-01

    Intelligent video surveillance is to analysis video or image sequences captured by a fixed or mobile surveillance camera, including moving object detection, segmentation and recognition. By using it, we can be notified immediately in an abnormal situation. Pedestrian detection plays an important role in an intelligent video surveillance system, and it is also a key technology in the field of intelligent vehicle. So pedestrian detection has very vital significance in traffic management optimization, security early warn and abnormal behavior detection. Generally, pedestrian detection can be summarized as: first to estimate moving areas; then to extract features of region of interest; finally to classify using a classifier. Redundant wavelet transform (RWT) overcomes the deficiency of shift variant of discrete wavelet transform, and it has better performance in motion estimation when compared to discrete wavelet transform. Addressing the problem of the detection of multi-pedestrian with different speed, we present an algorithm of pedestrian detection based on motion estimation using RWT, combining histogram of oriented gradients (HOG) and support vector machine (SVM). Firstly, three intensities of movement (IoM) are estimated using RWT and the corresponding areas are segmented. According to the different IoM, a region proposal (RP) is generated. Then, the features of a RP is extracted using HOG. Finally, the features are fed into a SVM trained by pedestrian databases and the final detection results are gained. Experiments show that the proposed algorithm can detect pedestrians accurately and efficiently.

  2. Service Outsourcing Character Oriented Privacy Conflict Detection Method in Cloud Computing

    Directory of Open Access Journals (Sweden)

    Changbo Ke

    2014-01-01

    Full Text Available Cloud computing has provided services for users as a software paradigm. However, it is difficult to ensure privacy information security because of its opening, virtualization, and service outsourcing features. Therefore how to protect user privacy information has become a research focus. In this paper, firstly, we model service privacy policy and user privacy preference with description logic. Secondly, we use the pellet reasonor to verify the consistency and satisfiability, so as to detect the privacy conflict between services and user. Thirdly, we present the algorithm of detecting privacy conflict in the process of cloud service composition and prove the correctness and feasibility of this method by case study and experiment analysis. Our method can reduce the risk of user sensitive privacy information being illegally used and propagated by outsourcing services. In the meantime, the method avoids the exception in the process of service composition by the privacy conflict, and improves the trust degree of cloud service providers.

  3. Versatile single-molecule multi-color excitation and detection fluorescence setup for studying biomolecular dynamics

    KAUST Repository

    Sobhy, M. A.

    2011-11-07

    Single-molecule fluorescence imaging is at the forefront of tools applied to study biomolecular dynamics both in vitro and in vivo. The ability of the single-molecule fluorescence microscope to conduct simultaneous multi-color excitation and detection is a key experimental feature that is under continuous development. In this paper, we describe in detail the design and the construction of a sophisticated and versatile multi-color excitation and emission fluorescence instrument for studying biomolecular dynamics at the single-molecule level. The setup is novel, economical and compact, where two inverted microscopes share a laser combiner module with six individual laser sources that extend from 400 to 640 nm. Nonetheless, each microscope can independently and in a flexible manner select the combinations, sequences, and intensities of the excitation wavelengths. This high flexibility is achieved by the replacement of conventional mechanical shutters with acousto-optic tunable filter (AOTF). The use of AOTF provides major advancement by controlling the intensities, duration, and selection of up to eight different wavelengths with microsecond alternation time in a transparent and easy manner for the end user. To our knowledge this is the first time AOTF is applied to wide-field total internal reflection fluorescence (TIRF) microscopy even though it has been commonly used in multi-wavelength confocal microscopy. The laser outputs from the combiner module are coupled to the microscopes by two sets of four single-mode optic fibers in order to allow for the optimization of the TIRF angle for each wavelength independently. The emission is split into two or four spectral channels to allow for the simultaneous detection of up to four different fluorophores of wide selection and using many possible excitation and photoactivation schemes. We demonstrate the performance of this new setup by conducting two-color alternating excitation single-molecule fluorescence resonance energy

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

    Directory of Open Access Journals (Sweden)

    Haobo Lyu

    2016-06-01

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

  5. P2-18: Temporal and Featural Separation of Memory Items Play Little Role for VSTM-Based Change Detection

    Directory of Open Access Journals (Sweden)

    Dae-Gyu Kim

    2012-10-01

    Full Text Available Classic studies of visual short-term memory (VSTM found that presenting memory items either sequentially or simultaneously does not affect recognition accuracy of the remembered items. Other studies also suggest that capacity of VSTM benefits from formation of bound object-based representations leading to no cost of remembering multi-feature items. According to these ideas, we aimed to examine the role of temporal and featural separation of memory items in VSTM change detection, (1 if sample items are separated across different temporal moments and (2 if across different feature dimensions. In a series of change detection experiments, we asked participants to report a change between a sample and a test display with a brief delay in between. In experiment 1, the sample items were split into two sets with a different onset time. In experiment 2, the sample items were split across two different feature dimensions (e.g., half color and half orientation. The change detection accuracy in Experiment 1 showed no substantial drop when the memory items were separated into two onset groups compared to simultaneous onset. The accuracy did not drop either when the features of sample items were split across two different feature groups compared to when were not split. The results indicate that temporal and featural separation of VWM items does not play a significant role for VSTM-based change detection.

  6. Flexible Method for the Automated Offline-Detection of Artifacts in Multi-Channel Electroencephalogram Recordings

    DEFF Research Database (Denmark)

    Waser, Markus; Garn, Heinrich; Benke, Thomas

    2017-01-01

    . However, these preprocessing steps do not allow for complete artifact correction. We propose a method for the automated offline-detection of remaining artifacts after preprocessing in multi-channel EEG recordings. In contrast to existing methods it requires neither adaptive parameters varying between...... recordings nor a topography template. It is suited for short EEG segments and is flexible with regard to target applications. The algorithm was developed and tested on 60 clinical EEG samples of 20 seconds each that were recorded both in resting state and during cognitive activation to gain a realistic...

  7. Toward automated face detection in thermal and polarimetric thermal imagery

    Science.gov (United States)

    Gordon, Christopher; Acosta, Mark; Short, Nathan; Hu, Shuowen; Chan, Alex L.

    2016-05-01

    Visible spectrum face detection algorithms perform pretty reliably under controlled lighting conditions. However, variations in illumination and application of cosmetics can distort the features used by common face detectors, thereby degrade their detection performance. Thermal and polarimetric thermal facial imaging are relatively invariant to illumination and robust to the application of makeup, due to their measurement of emitted radiation instead of reflected light signals. The objective of this work is to evaluate a government off-the-shelf wavelet based naïve-Bayes face detection algorithm and a commercial off-the-shelf Viola-Jones cascade face detection algorithm on face imagery acquired in different spectral bands. New classifiers were trained using the Viola-Jones cascade object detection framework with preprocessed facial imagery. Preprocessing using Difference of Gaussians (DoG) filtering reduces the modality gap between facial signatures across the different spectral bands, thus enabling more correlated histogram of oriented gradients (HOG) features to be extracted from the preprocessed thermal and visible face images. Since the availability of training data is much more limited in the thermal spectrum than in the visible spectrum, it is not feasible to train a robust multi-modal face detector using thermal imagery alone. A large training dataset was constituted with DoG filtered visible and thermal imagery, which was subsequently used to generate a custom trained Viola-Jones detector. A 40% increase in face detection rate was achieved on a testing dataset, as compared to the performance of a pre-trained/baseline face detector. Insights gained in this research are valuable in the development of more robust multi-modal face detectors.

  8. Network Communication as a Service-Oriented Capability

    Energy Technology Data Exchange (ETDEWEB)

    Johnston, William; Johnston, William; Metzger, Joe; Collins, Michael; Burrescia, Joseph; Dart, Eli; Gagliardi, Jim; Guok, Chin; Oberman, Kevin; O' Conner, Mike

    2008-01-08

    In widely distributed systems generally, and in science-oriented Grids in particular, software, CPU time, storage, etc., are treated as"services" -- they can be allocated and used with service guarantees that allows them to be integrated into systems that perform complex tasks. Network communication is currently not a service -- it is provided, in general, as a"best effort" capability with no guarantees and only statistical predictability. In order for Grids (and most types of systems with widely distributed components) to be successful in performing the sustained, complex tasks of large-scale science -- e.g., the multi-disciplinary simulation of next generation climate modeling and management and analysis of the petabytes of data that will come from the next generation of scientific instrument (which is very soon for the LHC at CERN) -- networks must provide communication capability that is service-oriented: That is it must be configurable, schedulable, predictable, and reliable. In order to accomplish this, the research and education network community is undertaking a strategy that involves changes in network architecture to support multiple classes of service; development and deployment of service-oriented communication services, and; monitoring and reporting in a form that is directly useful to the application-oriented system so that it may adapt to communications failures. In this paper we describe ESnet's approach to each of these -- an approach that is part of an international community effort to have intra-distributed system communication be based on a service-oriented capability.

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

    Directory of Open Access Journals (Sweden)

    P. Duncan

    2012-08-01

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

  10. Multi-Layer Approach for the Detection of Selective Forwarding Attacks

    Directory of Open Access Journals (Sweden)

    Naser Alajmi

    2015-11-01

    Full Text Available Security breaches are a major threat in wireless sensor networks (WSNs. WSNs are increasingly used due to their broad range of important applications in both military and civilian domains. WSNs are prone to several types of security attacks. Sensor nodes have limited capacities and are often deployed in dangerous locations; therefore, they are vulnerable to different types of attacks, including wormhole, sinkhole, and selective forwarding attacks. Security attacks are classified as data traffic and routing attacks. These security attacks could affect the most significant applications of WSNs, namely, military surveillance, traffic monitoring, and healthcare. Therefore, there are different approaches to detecting security attacks on the network layer in WSNs. Reliability, energy efficiency, and scalability are strong constraints on sensor nodes that affect the security of WSNs. Because sensor nodes have limited capabilities in most of these areas, selective forwarding attacks cannot be easily detected in networks. In this paper, we propose an approach to selective forwarding detection (SFD. The approach has three layers: MAC pool IDs, rule-based processing, and anomaly detection. It maintains the safety of data transmission between a source node and base station while detecting selective forwarding attacks. Furthermore, the approach is reliable, energy efficient, and scalable.

  11. X-ray diffraction studies of the structure and orientations of thiophene and fluorenone based molecule

    International Nuclear Information System (INIS)

    Porzio, William; Pasini, Mariacecilia; Destri, Silvia; Giovanella, Umberto; Fontaine, Philippe

    2006-01-01

    The crystal structure of a conjugated molecule containing thiophene and fluorenone residues has been determined from powder X-ray diffraction (XRD). Thin films ( -5 Pa) onto oxidized silicon substrates, are oriented along with different crystallographic directions. A comparison of XRD in both Grazing Incidence and Bragg-Brentano geometries allowed to perform a quantitative analysis of the various orientations. This approach is generally applicable in the case of multi-oriented films. The results fully account for the poor performance of this molecule in p-type field effect transistor devices

  12. Proposal for Implementing Multi-User Database (MUD) Technology in an Academic Library.

    Science.gov (United States)

    Filby, A. M. Iliana

    1996-01-01

    Explores the use of MOO (multi-user object oriented) virtual environments in academic libraries to enhance reference services. Highlights include the development of multi-user database (MUD) technology from gaming to non-recreational settings; programming issues; collaborative MOOs; MOOs as distinguished from other types of virtual reality; audio…

  13. Bridge Crack Detection Using Multi-Rotary Uav and Object-Base Image Analysis

    Science.gov (United States)

    Rau, J. Y.; Hsiao, K. W.; Jhan, J. P.; Wang, S. H.; Fang, W. C.; Wang, J. L.

    2017-08-01

    Bridge is an important infrastructure for human life. Thus, the bridge safety monitoring and maintaining is an important issue to the government. Conventionally, bridge inspection were conducted by human in-situ visual examination. This procedure sometimes require under bridge inspection vehicle or climbing under the bridge personally. Thus, its cost and risk is high as well as labor intensive and time consuming. Particularly, its documentation procedure is subjective without 3D spatial information. In order cope with these challenges, this paper propose the use of a multi-rotary UAV that equipped with a SONY A7r2 high resolution digital camera, 50 mm fixed focus length lens, 135 degrees up-down rotating gimbal. The target bridge contains three spans with a total of 60 meters long, 20 meters width and 8 meters height above the water level. In the end, we took about 10,000 images, but some of them were acquired by hand held method taken on the ground using a pole with 2-8 meters long. Those images were processed by Agisoft PhotoscanPro to obtain exterior and interior orientation parameters. A local coordinate system was defined by using 12 ground control points measured by a total station. After triangulation and camera self-calibration, the RMS of control points is less than 3 cm. A 3D CAD model that describe the bridge surface geometry was manually measured by PhotoscanPro. They were composed of planar polygons and will be used for searching related UAV images. Additionally, a photorealistic 3D model can be produced for 3D visualization. In order to detect cracks on the bridge surface, we utilize object-based image analysis (OBIA) technique to segment the image into objects. Later, we derive several object features, such as density, area/bounding box ratio, length/width ratio, length, etc. Then, we can setup a classification rule set to distinguish cracks. Further, we apply semi-global-matching (SGM) to obtain 3D crack information and based on image scale we

  14. Multi-sensor explosive detection system

    International Nuclear Information System (INIS)

    Gozani, T.; Shea, P.M.; Sawa, Z.P.

    1992-01-01

    This patent describes an explosive detection system. It comprises a source of neutrons; a detector array comprising a plurality of gamma ray detectors, each of the gamma ray detectors providing a detection signal in the event a gamma ray is captured by the detector, and at least one neutron detector, the neutron detector providing a neutron detection signal in the event a neutron is captured by the neutron detector; means for irradiating an object being examined with neutrons from the neutron source and for positioning the detector array relative to the object so that gamma rays emitted from the elements within the object as a result of the neutron irradiation are detected by the gamma ray detectors of the detector array; and parallel distributed processing means responsive to the detection signals of the detector array for discriminating between objects carrying explosives and objects not carrying explosives, the parallel distributed processing means including an artificial neural system (ANS), the ANS having a parallel network of processors, each processor of the parallel network of processors, each processor of the parallel network of processors including means for receiving at least one input signal, and means for generating an output signal as a function of the at least one input signal

  15. Testing Object-Oriented Programs using Dynamic Aspects and Non-Determinism

    DEFF Research Database (Denmark)

    Achenbach, Michael; Ostermann, Klaus

    2010-01-01

    decisions exposing private data. We present an approach that both improves the expressiveness of test cases using non-deterministic choice and reduces design modifications using dynamic aspect-oriented programming techniques. Non-deterministic choice facilitates local definitions of multiple executions...... without parameterization or generation of tests. It also eases modelling naturally non-deterministic program features like IO or multi-threading in integration tests. Dynamic AOP facilitates powerful design adaptations without exposing test features, keeping the scope of these adaptations local to each...... test. We also combine non-determinism and dynamic aspects in a new approach to testing multi-threaded programs using co-routines....

  16. Area–Oriented Technology Mapping for LUT–Based Logic Blocks

    Directory of Open Access Journals (Sweden)

    Kubica Marcin

    2017-03-01

    Full Text Available One of the main aspects of logic synthesis dedicated to FPGA is the problem of technology mapping, which is directly associated with the logic decomposition technique. This paper focuses on using configurable properties of CLBs in the process of logic decomposition and technology mapping. A novel theory and a set of efficient techniques for logic decomposition based on a BDD are proposed. The paper shows that logic optimization can be efficiently carried out by using multiple decomposition. The essence of the proposed synthesis method is multiple cutting of a BDD. A new diagram form called an SMTBDD is proposed. Moreover, techniques that allow finding the best technology mapping oriented to configurability of CLBs are presented. In the experimental section, the presented method (MultiDec is compared with academic and commercial tools. The experimental results show that the proposed technology mapping strategy leads to good results in terms of the number of CLBs.

  17. The influence of market orientation on innovation strategies

    OpenAIRE

    Newman, Alexander; Prajogo, Daniel; Atherton, Andrew

    2016-01-01

    Purpose This study examines the effects of market orientation on exploratory and exploitative innovation, and the moderating effects of family ownership on these relationships. Design/methodology/approach This study utilizes multi-group path analysis and confirmatory factor analysis in LISREL on data from 228 firms in the Australian service sector. Findings This study establishes that both customer and competitor innovation are positively related to exploitative and exploratory innovation. Ho...

  18. Landslide mapping with multi-scale object-based image analysis – a case study in the Baichi watershed, Taiwan

    Directory of Open Access Journals (Sweden)

    T. Lahousse

    2011-10-01

    Full Text Available We developed a multi-scale OBIA (object-based image analysis landslide detection technique to map shallow landslides in the Baichi watershed, Taiwan, after the 2004 Typhoon Aere event. Our semi-automated detection method selected multiple scales through landslide size statistics analysis for successive classification rounds. The detection performance achieved a modified success rate (MSR of 86.5% with the training dataset and 86% with the validation dataset. This performance level was due to the multi-scale aspect of our methodology, as the MSR for single scale classification was substantially lower, even after spectral difference segmentation, with a maximum of 74%. Our multi-scale technique was capable of detecting landslides of varying sizes, including very small landslides, up to 95 m2. The method presented certain limitations: the thresholds we established for classification were specific to the study area, to the landslide type in the study area, and to the spectral characteristics of the satellite image. Because updating site-specific and image-specific classification thresholds is easy with OBIA software, our multi-scale technique is expected to be useful for mapping shallow landslides at watershed level.

  19. Deficient prepulse inhibition in schizophrenia detected by the multi-site COGS.

    Science.gov (United States)

    Swerdlow, Neal R; Light, Gregory A; Sprock, Joyce; Calkins, Monica E; Green, Michael F; Greenwood, Tiffany A; Gur, Raquel E; Gur, Ruben C; Lazzeroni, Laura C; Nuechterlein, Keith H; Radant, Allen D; Ray, Amrita; Seidman, Larry J; Siever, Larry J; Silverman, Jeremy M; Stone, William S; Sugar, Catherine A; Tsuang, Debby W; Tsuang, Ming T; Turetsky, Bruce I; Braff, David L

    2014-02-01

    Startle inhibition by weak prepulses (PPI) is studied to understand the biology of information processing in schizophrenia patients and healthy comparison subjects (HCS). The Consortium on the Genetics of Schizophrenia (COGS) identified associations between PPI and single nucleotide polymorphisms in schizophrenia probands and unaffected relatives, and linkage analyses extended evidence for the genetics of PPI deficits in schizophrenia in the COGS-1 family study. These findings are being extended in a 5-site "COGS-2" study of 1800 patients and 1200 unrelated HCS to facilitate genetic analyses. We describe a planned interim analysis of COGS-2 PPI data. Eyeblink startle was measured in carefully screened HCS and schizophrenia patients (n=1402). Planned analyses of PPI (60 ms intervals) assessed effects of diagnosis, sex and test site, PPI-modifying effects of medications and smoking, and relationships between PPI and neurocognitive measures. 884 subjects met strict inclusion criteria. ANOVA of PPI revealed significant effects of diagnosis (p=0.0005) and sex (pschizophrenia PPI differences were greatest among patients not taking 2nd generation antipsychotics, and were independent of smoking status. Modest but significant relationships were detected between PPI and performance in specific neurocognitive measures. The COGS-2 multi-site study detects schizophrenia-related PPI deficits reported in single-site studies, including patterns related to diagnosis, prepulse interval, sex, medication and other neurocognitive measures. Site differences were detected and explored. The target COGS-2 schizophrenia "endophenotype" of reduced PPI should prove valuable for identifying and confirming schizophrenia risk genes in future analyses. Copyright © 2013 Elsevier B.V. All rights reserved.

  20. Muddy Learning: Evaluating Learning in Multi-User Computer-Based Environments

    National Research Council Canada - National Science Library

    McArthur, David

    1998-01-01

    ... (Multiple User Synthetic Environments), and MOOs (Multi-User Object Oriented), enables users to create new "rooms" in virtual worlds, define their own personnaes, and engage visitors in rich dialogues...

  1. Multi-Input Convolutional Neural Network for Flower Grading

    Directory of Open Access Journals (Sweden)

    Yu Sun

    2017-01-01

    Full Text Available Flower grading is a significant task because it is extremely convenient for managing the flowers in greenhouse and market. With the development of computer vision, flower grading has become an interdisciplinary focus in both botany and computer vision. A new dataset named BjfuGloxinia contains three quality grades; each grade consists of 107 samples and 321 images. A multi-input convolutional neural network is designed for large scale flower grading. Multi-input CNN achieves a satisfactory accuracy of 89.6% on the BjfuGloxinia after data augmentation. Compared with a single-input CNN, the accuracy of multi-input CNN is increased by 5% on average, demonstrating that multi-input convolutional neural network is a promising model for flower grading. Although data augmentation contributes to the model, the accuracy is still limited by lack of samples diversity. Majority of misclassification is derived from the medium class. The image processing based bud detection is useful for reducing the misclassification, increasing the accuracy of flower grading to approximately 93.9%.

  2. Multi-Functional Sensor System for Heart Rate, Body Position and Movement Intensity Analysis

    Directory of Open Access Journals (Sweden)

    Michael MAO

    2008-12-01

    Full Text Available A novel multi-functional wearable sensor has been developed with multi-axis accelerometer, disposable hydro-gel electrodes, and analog filtering components. This novel sensor implementation can be used for detecting common body positions, movement intensity, and measures bio-potential signals for ECG and heart rate analysis. Based on the novel sensor principle, a prototype combines position detection, heart rate detection, and motion intensity level detection together in a handheld device that records the physiological information and wirelessly transmits the signals through Bluetooth to a mobile phone. Static body positions such as standing/sitting, lying supine, prone, and on the sides have been detected with high accuracy (97.7 % during the subject tests. Further, an algorithm that detects body movement intensity that can potentially be applied in real-time monitoring physical activity level is proposed based on average variance values. Motion intensity results show variance values increase and exercise intensity increases for almost all of the cases. A clear relation between movement intensity level shown by an increase in frequency and/or speed of exercise increases the variance values detected in all three spatial axes.

  3. Negative emotion provides cues for orienting auditory spatial attention

    Directory of Open Access Journals (Sweden)

    Erkin eAsutay

    2015-05-01

    Full Text Available The auditory stimuli provide information about the objects and events around us. They can also carry biologically significant emotional information (such as unseen dangers and conspecific vocalizations, which provides cues for allocation of attention and mental resources. Here, we investigated whether task-irrelevant auditory emotional information can provide cues for orientation of auditory spatial attention. We employed a covert spatial orienting task: the dot-probe task. In each trial, two task irrelevant auditory cues were simultaneously presented at two separate locations (left-right or front-back. Environmental sounds were selected to form emotional vs. neutral, emotional vs. emotional, and neutral vs. neutral cue pairs. The participants’ task was to detect the location of an acoustic target that was presented immediately after the task-irrelevant auditory cues. The target was presented at the same location as one of the auditory cues. The results indicated that participants were significantly faster to locate the target when it replaced the negative cue compared to when it replaced the neutral cue. The positive cues did not produce a clear attentional bias. Further, same valence pairs (emotional-emotional or neutral-neutral did not modulate reaction times due to a lack of spatial attention capture by one cue in the pair. Taken together, the results indicate that negative affect can provide cues for the orientation of spatial attention in the auditory domain.

  4. Breaking the color barrier - a multi-selective antibody reporter offers innovative strategies of fluorescence detection.

    Science.gov (United States)

    Gallo, Eugenio; Jarvik, Jonathan W

    2017-08-01

    A novel bi-partite fluorescence platform exploits the high affinity and selectivity of antibody scaffolds to capture and activate small-molecule fluorogens. In this report, we investigated the property of multi-selectivity activation by a single antibody against diverse cyanine family fluorogens. Our fluorescence screen identified three cell-impermeant fluorogens, each with unique emission spectra (blue, green and red) and nanomolar affinities. Most importantly, as a protein fusion tag to G-protein-coupled receptors, the antibody biosensor retained full activity - displaying bright fluorogen signals with minimal background on live cells. Because fluorogen-activating antibodies interact with their target ligands via non-covalent interactions, we were able to perform advanced multi-color detection strategies on live cells, previously difficult or impossible with conventional reporters. We found that by fine-tuning the concentrations of the different color fluorogen molecules in solution, a user may interchange the fluorescence signal (onset versus offset), execute real-time signal exchange via fluorogen competition, measure multi-channel fluorescence via co-labeling, and assess real-time cell surface receptor traffic via pulse-chase experiments. Thus, here we inform of an innovative reporter technology based on tri-color signal that allows user-defined fluorescence tuning in live-cell applications. © 2017. Published by The Company of Biologists Ltd.

  5. Dynamics of molecular stereochemistry via oriented molecule scattering

    International Nuclear Information System (INIS)

    Parker, D.H.; Jalink, H.; Stolte, S.

    1987-01-01

    Crossed-beam reactive scattering experiments employing electrostatic hexapole fields to control the initial collision geometry of chemical reactions are described. New results are presented on the reactions of oriented NO with ozone and oriented N 2 O with Ba. Preliminary results are also given for the oriented CH 3 F + Ca* → CaF* + CH 3 reaction. Recent technical advances in state selection and product detection are detailed. They discuss the effects of rotational coupling and nonzero impact parameters in changing the molecular precollisions orientation selected by the hexapole fields to a different in-collision orientation at the moment of impact with the reaction partner. Uncoupling of l doubling in N 2 O at strong orientation fields is demonstrated via the observed reactive anisotropy. Steric effects are found to govern many aspects of the reactions investigated thus far. Strong correlations are observed of the reactivity, product recoil, and rotational angular momentum distributions with the collisional orientation. These correlations ultimately provide information on the anisotropic part of the reaction potential energy surface. They conclude with a brief outline of possible future directions in oriented molecule scattering

  6. Three-dimensional analysis of relationship between relative orientation and motion modes

    Directory of Open Access Journals (Sweden)

    Fan Shijie

    2014-12-01

    Full Text Available Target motion modes have a close relationship with the relative orientation of missile-to-target in three-dimensional highly maneuvering target interception. From the perspective of relationship between the sensor coordinate system and the target body coordinate system, a basic model of sensor is stated and the definition of relative angular velocity between the two coordinate systems is introduced firstly. Then, the three-dimensional analytic expressions of relative angular velocity for different motion modes are derived and simplified by analyzing the influences of target centroid motion, rotation around centroid and relative motion. Finally, the relationships of the relative angular velocity directions and values with motion modes are discussed. Simulation results validate the rationality of the theoretical analysis. It is demonstrated that there are significant differences of the relative orientation in different motion modes which include luxuriant information about motion modes. The conclusions are significant for the research of motion mode identification, maneuver detection, maneuvering target tracking and interception using target signatures.

  7. Modelling multi-pulse population dynamics from ultrafast spectroscopy.

    Directory of Open Access Journals (Sweden)

    Luuk J G W van Wilderen

    2011-03-01

    Full Text Available Current advanced laser, optics and electronics technology allows sensitive recording of molecular dynamics, from single resonance to multi-colour and multi-pulse experiments. Extracting the occurring (bio- physical relevant pathways via global analysis of experimental data requires a systematic investigation of connectivity schemes. Here we present a Matlab-based toolbox for this purpose. The toolbox has a graphical user interface which facilitates the application of different reaction models to the data to generate the coupled differential equations. Any time-dependent dataset can be analysed to extract time-independent correlations of the observables by using gradient or direct search methods. Specific capabilities (i.e. chirp and instrument response function for the analysis of ultrafast pump-probe spectroscopic data are included. The inclusion of an extra pulse that interacts with a transient phase can help to disentangle complex interdependent pathways. The modelling of pathways is therefore extended by new theory (which is included in the toolbox that describes the finite bleach (orientation effect of single and multiple intense polarised femtosecond pulses on an ensemble of randomly oriented particles in the presence of population decay. For instance, the generally assumed flat-top multimode beam profile is adapted to a more realistic Gaussian shape, exposing the need for several corrections for accurate anisotropy measurements. In addition, the (selective excitation (photoselection and anisotropy of populations that interact with single or multiple intense polarised laser pulses is demonstrated as function of power density and beam profile. Using example values of real world experiments it is calculated to what extent this effectively orients the ensemble of particles. Finally, the implementation includes the interaction with multiple pulses in addition to depth averaging in optically dense samples. In summary, we show that mathematical

  8. Automatic Detection of Cyberbullying in Social Media Text

    NARCIS (Netherlands)

    Van Hee, Cynthia; Jacobs, Gilles; Emmery, Chris; Desmet, Bart; Lefever, Els; Verhoeven, Ben; De Pauw, Guy; Daelemans, W.M.P.; Hoste, Veronique

    2018-01-01

    While social media offer great communication opportunities, they also increase the vulnerability of young people to threatening situations online. Recent studies report that cyberbullying constitutes a growing problem among youngsters. Successful prevention depends on the adequate detection of

  9. The influence of marketing orientation on organizational ...

    African Journals Online (AJOL)

    The influence of marketing orientation on organizational performance: a case study in Terengganu. ... of relationship marketing in the hotel industry performance regarding Permai Hotel ... EMAIL FREE FULL TEXT EMAIL FREE FULL TEXT

  10. Report made on behalf of the parity mixed commission in charge of proposing a text about the dispositions of the project of energy orientation law remaining to be discussed; Rapport fait au nom de la commission mixte paritaire (1) chargee de proposer un texte sur les dispositions restant en discussion du projet de loi d'orientation sur l'energie

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2005-07-01

    The project of energy orientation law aims at fixing the main principles of the French energy policy for the next decades. It foresees: the re-launching of the French nuclear program (building of an experimental European pressurized reactor (EPR)), the reinforcement of the mastery of energy demand (3% per year, creation of energy saving certificates and reinforcement of buildings energy efficiency rules), and the sustain of renewable energies development. This document presents, first, a direct comparison, article by article, of the text adopted in second lecture by the House of Commons, with the text adopted in second lecture by the Senate. Then, a text is proposed for the last dispositions that remained to be discussed and is presented in the second part of the report. (J.S.)

  11. An Improved Algorithm Based on Minimum Spanning Tree for Multi-scale Segmentation of Remote Sensing Imagery

    Directory of Open Access Journals (Sweden)

    LI Hui

    2015-07-01

    Full Text Available As the basis of object-oriented information extraction from remote sensing imagery,image segmentation using multiple image features,exploiting spatial context information, and by a multi-scale approach are currently the research focuses. Using an optimization approach of the graph theory, an improved multi-scale image segmentation method is proposed. In this method, the image is applied with a coherent enhancement anisotropic diffusion filter followed by a minimum spanning tree segmentation approach, and the resulting segments are merged with reference to a minimum heterogeneity criterion.The heterogeneity criterion is defined as a function of the spectral characteristics and shape parameters of segments. The purpose of the merging step is to realize the multi-scale image segmentation. Tested on two images, the proposed method was visually and quantitatively compared with the segmentation method employed in the eCognition software. The results show that the proposed method is effective and outperforms the latter on areas with subtle spectral differences.

  12. A hybrid approach for efficient anomaly detection using metaheuristic methods

    Directory of Open Access Journals (Sweden)

    Tamer F. Ghanem

    2015-07-01

    Full Text Available Network intrusion detection based on anomaly detection techniques has a significant role in protecting networks and systems against harmful activities. Different metaheuristic techniques have been used for anomaly detector generation. Yet, reported literature has not studied the use of the multi-start metaheuristic method for detector generation. This paper proposes a hybrid approach for anomaly detection in large scale datasets using detectors generated based on multi-start metaheuristic method and genetic algorithms. The proposed approach has taken some inspiration of negative selection-based detector generation. The evaluation of this approach is performed using NSL-KDD dataset which is a modified version of the widely used KDD CUP 99 dataset. The results show its effectiveness in generating a suitable number of detectors with an accuracy of 96.1% compared to other competitors of machine learning algorithms.

  13. Market Orientation Practices and Effects on Organizational Performance

    Directory of Open Access Journals (Sweden)

    Haim Hilman

    2014-09-01

    Full Text Available Today’s organizations need market orientation practices to strive and generate superior performance and competitive advantage in the modern turbulent marketplace. Thus, this research inspects the respective links between the dimensions of (a competitor orientation and (b customer orientation and performance in the context of hotels in Malaysia. Data were gathered through self-administrated mail questionnaires directed to the top- and middle-level managers of three- to five-star-rated hotels in Malaysia. The findings indicated that hotels in Malaysia practiced competitor orientation and customer orientation as their core marketing strategy. Specifically, both competitor orientation and customer orientation positively linked to organizational performance. Few studies have investigated the practices and effects of market orientation on performance in the Malaysian hotel setting. Therefore, this study provided new insights into the understanding of market orientation practices in the hotel industry, particularly in Malaysia. In addition, the significance of this study, potential limitations, and future examination directions are highlighted.

  14. Living Diversity: Developing a Typology of Consumer Cultural Orientations in Culturally Diverse Marketplaces

    DEFF Research Database (Denmark)

    Kipnis, Eva; Emontspool, Julie; Broderick, Amanda J.

    2012-01-01

    -cultural orientations and use these orientations as informants of their consumption choices. Our findings suggest that the study of consumption implications of cultural diversity should be extended beyond mainstream/migrant differentiation which loses its significance in today’s globalized world...... framework for ethnic consumption and subsequently apply it in an empirical study. The findings indicate that through differential deployment of local, global and foreign cultures affinities for identity negotiation, mainstream and migrant consumers alike can develop or maintain uni-, bi- and multi...

  15. Scanning Electron Microscope Calibration Using a Multi-Image Non-Linear Minimization Process

    Science.gov (United States)

    Cui, Le; Marchand, Éric

    2015-04-01

    A scanning electron microscope (SEM) calibrating approach based on non-linear minimization procedure is presented in this article. A part of this article has been published in IEEE International Conference on Robotics and Automation (ICRA), 2014. . Both the intrinsic parameters and the extrinsic parameters estimations are achieved simultaneously by minimizing the registration error. The proposed approach considers multi-images of a multi-scale calibration pattern view from different positions and orientations. Since the projection geometry of the scanning electron microscope is different from that of a classical optical sensor, the perspective projection model and the parallel projection model are considered and compared with distortion models. Experiments are realized by varying the position and the orientation of a multi-scale chessboard calibration pattern from 300× to 10,000×. The experimental results show the efficiency and the accuracy of this approach.

  16. Seizure Onset Detection based on a Uni- or Multi-modal Intelligent Seizure Acquisition (UISA/MISA) System

    DEFF Research Database (Denmark)

    Conradsen, Isa; Beniczky, Sándor; Wolf, Peter

    2010-01-01

    An automatic Uni- or Multi-modal Inteligent Seizure Acquisition (UISA/MISA) system is highly applicable for onset detection of epileptic seizures based on motion data. The modalities used are surface electromyography (sEMG), acceleration (ACC) and angular velocity (ANG). The new proposed automatic...... algorithm on motion data is extracting features as “log-sum” measures of discrete wavelet components. Classification into the two groups “seizure” versus “nonseizure” is made based on the support vector machine (SVM) algorithm. The algorithm performs with a sensitivity of 91-100%, a median latency of 1...... second and a specificity of 100% on multi-modal data from five healthy subjects simulating seizures. The uni-modal algorithm based on sEMG data from the subjects and patients performs satisfactorily in some cases. As expected, our results clearly show superiority of the multimodal approach, as compared...

  17. BAMUD Features Demonstration by System View

    Directory of Open Access Journals (Sweden)

    D. Kocur

    2004-09-01

    Full Text Available Direct-sequence code-division multiple access (DS-CDMA is afrequently used wireless technology in DS-CDMA communications. Theconventional DS-CDMA detector follows a single-user detection strategyin which each user is detected separately without regard for the otherusers. The better strategy is multi-user detection (MUD, whereinformation about multiple users is used to improve detection of eachindividual user. This paper presents an adaptive multi-user detectorconverging (for any initialization to the minimum mean square error(MMSE detector without requiring training sequences. This blindmulti-user detector (BAMUD requires no more knowledge than does theconventional single-user detector. The structure of adaptive blinddetector is simulated by the system design tool SystemView. The aimfocus is to verify theoretical knowledge of BAMUD structure usinghardware-oriented PC-based model in SystemView.

  18. An ultrasonic methodology to non-destructively estimate the grain orientation in an anisotropic weld

    Directory of Open Access Journals (Sweden)

    Wirdelius Håkan

    2014-06-01

    Full Text Available The initial step towards a non-destructive technique that estimates grain orientation in an anisotropic weld is presented in this paper. The purpose is to aid future forward simulations of ultrasonic NDT of this kind of weld to achieve a better result. A forward model that consists of a weld model, a transmitter model, a receiver model and a 2D ray tracing algorithm is introduced. An inversion based on a multi-objective genetic algorithm is also presented. Experiments are conducted for both P and SV waves in order to collect enough data used in the inversion. Calculation is conducted to fulfil the estimation with both the synthetic data and the experimental data. Concluding remarks are presented at the end of the paper.

  19. An Efficient VLSI Architecture for Multi-Channel Spike Sorting Using a Generalized Hebbian Algorithm

    Directory of Open Access Journals (Sweden)

    Ying-Lun Chen

    2015-08-01

    Full Text Available A novel VLSI architecture for multi-channel online spike sorting is presented in this paper. In the architecture, the spike detection is based on nonlinear energy operator (NEO, and the feature extraction is carried out by the generalized Hebbian algorithm (GHA. To lower the power consumption and area costs of the circuits, all of the channels share the same core for spike detection and feature extraction operations. Each channel has dedicated buffers for storing the detected spikes and the principal components of that channel. The proposed circuit also contains a clock gating system supplying the clock to only the buffers of channels currently using the computation core to further reduce the power consumption. The architecture has been implemented by an application-specific integrated circuit (ASIC with 90-nm technology. Comparisons to the existing works show that the proposed architecture has lower power consumption and hardware area costs for real-time multi-channel spike detection and feature extraction.

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

    Science.gov (United States)

    Ewald, Melanie; Fechner, Peter; Gauglitz, Günter

    2015-05-01

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