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Construction of time-stamped mobility map for path tracking via smith-waterman measurement matching

Mathematical Problems in engineering 2014年第1期2014卷

作者： Zhou, Mu Tian, Zengshan Xu, Kunjie Wu, Haibo Pu, Qiaolin Yu, Xiang Chongqing Key Lab of Mobile Communications Technology Chongqing University of Posts and Telecommunications Chongqing 400065 China Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Hong Kong Hong Kong Graduate Telecommunications and Networking Program University of Pittsburgh Pittsburgh PA 15260 United States China Internet Research Lab Computer Network Information Center Chinese Academy of Sciences Beijing 100190 China

Path tracking in wireless and mobile environments is a fundamental technology for ubiquitous location-based services (LBSs). In particular, it is very challenging to develop highly accurate and cost-efficient tracking systems applied to the anonymous areas where the floor plans are not available for security and privacy reasons. This paper proposes a novel path tracking approach for large Wi-Fi areas based on the time-stamped unlabeled mobility map which is constructed from Smith-Waterman received signal strength (RSS) measurement matching. Instead of conventional location fingerprinting, we construct mobility map with the technique of dimension reduction from the raw measurement space into a low-dimensional embedded manifold. The feasibility of our proposed approach is verified by the real-world experiments in the HKUST campus Wi-Fi networks, sMobileNet. The experimental results prove that our approach is adaptive and capable of achieving an adequate precision level in path tracking. © 2014 Mu Zhou et al.

关键词： Wi-Fi

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Development and evaluation of a hospital-wide healthcare-associated surgical site infection detection algorithm

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Journal of Microbiology, Immunology and Infection 2015年第2期48卷 S43-S43页

作者： Yi-Ju Tseng Bo-Chiang Huang Hui-Chi Lin Ming-Yuan Chen Rung-Ji Shang Wang-Huei Sheng Yee-Chun Chen Feipei Lai Shan-Chwen Chang Children's Hospital Informatics Program Boston Children's Hospital Boston MA USA Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University Taiwan Center for Infection Control National Taiwan University Hospital (NTUH) Taiwan Information Systems Office NTUH Taipei Taiwan Department of Internal Medicine NTUH and College of Medicine Taiwan National Institute of Infectious Diseases and Vaccinology National Health Research Institutes Taiwan Department of Computer Science and Information Engineering National Taiwan University Taiwan

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Dirichlet tessellation for high-dimensional RSS clustering in Wi-Fi environment

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ICIC Express Letters 2014年第7期8卷 2043-2048页

作者： Zhou, Mu Tian, Zengshan Xu, Kunjie Tang, Xiaomou Chongqing Key Lab of Mobile Communications Technology Chongqing University of Posts and Telecommunications No. 2 Chongwen Road Nanan District Chongqing 400065 China Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Clear Water Bay Kowloon Hong Kong Graduate Telecommunication and Networking Program School of Information Science University of Pittsburgh PA 15260 United States

The received signal strength (RSS) clustering has played a significant role in site surveying and data pre-processing for the location tracking in Wi-Fi environment. To this end, this paper presents a novel clustering algorithm to cluster the raw RSS vectors with large similarities in both the RSS and physical locations together. The clusters of RSS vectors are determined by the cells which are generated by the Dirichlet tessellation in a transformed low-dimensional space. Our algorithm consists of two steps. We first use the Laplacian embedding to transform the raw measurements into a low-dimensional space, while preserving the RSS and location neighborhood relations. Second, after the seeds of cells are carefully selected, we will tessellate the low-dimensional space by the Dirichlet cells to obtain the clustering results. The experiments conducted in an actual public Wi-Fi environment prove that our algorithm can achieve the smallest cluster scattering in both the RSS and locations compared with the existing affinity propagation clustering, K-means clustering and binary support vector classifier (SVC) algorithms. © 2014 ISSN 1881-803X.

关键词： Wi-Fi

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Cross-camera vehicle tracking via affine invariant object matching for video forensics applications

Cross-camera vehicle tracking via affine invariant object ma...

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2013 IEEE International Conference on Multimedia and Expo, ICME 2013

作者： Hsu, Chao-Yung Kang, Li-Wei Mark Liao, Hong-Yuan Institute of Information Science Academia Sinica Taipei Taiwan Graduate School of Engineering Science and Technology-Doctoral Program Department of Computer Science and Information Engineering National Yunlin University of Science and Technology Yunlin Taiwan

ISBN: (纸本)9781479900152

The recent deployment of very large-scale camera networks consisting of fixed/moving surveillance cameras and vehicle video recorders, has led to a novel field in object tracking problem. The major goal is to detect and track each vehicle within a large area, which can be applied to video forensics. For example, a suspected vehicle can be automatically identified for mining digital criminal evidences from a large amount of video data. In this paper, we propose an efficient cross-camera vehicle tracking technique via affine invariant object matching. More specifically, we formulate the problem as invariant image feature matching among different viewpoints of cameras. To achieve vehicle matching, we first extract invariant image feature based on ASIFT (affine and scale-invariant feature transform) for each detected vehicle in a camera network. Then, to improve the accuracy of ASIFT feature matching between images from different viewpoints, we propose to efficiently match feature points based on our observed spatially invariant property of ASIFT, as well as the min-hash technique. As a result, cross-camera vehicle tracking can be efficiently and accurately achieved. Experimental results demonstrate the efficacy of the proposed algorithm and the feasibility to video forensics applications. © 2013 IEEE.

关键词： Tracking (position)

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Haze effect removal from image via haze density estimation in optical model

Haze effect removal from image via haze density estimation i...

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作者： Yeh, Chia-Hung Kang, Li-Wei Lee, Ming-Sui Lin, Cheng-Yang Department of Electrical Engineering National Sun Yat-sen University 804 Taiwan Graduate School of Engineering Science and Technology-Doctoral Program Department of Computer Science and Information Engineering National Yunlin University of Science and Technology Yunlin 640 Taiwan Graduate Institute of Networking and Multimedia Department of Computer Science and Information Engineering National Taiwan University Taipei 106 Taiwan

Images/videos captured from optical devices are usually degraded by turbid media such as haze, smoke, fog, rain and snow. Haze is the most common problem in outdoor scenes because of the atmosphere conditions. This paper proposes a novel single image-based dehazing framework to remove haze artifacts from images, where we propose two novel image priors, called the pixel-based dark channel prior and the pixel-based bright channel prior. Based on the two priors with the haze optical model, we propose to estimate atmospheric light via haze density analysis. We can then estimate transmission map, followed by refining it via the bilateral filter. As a result, high-quality haze-free images can be recovered with lower computational complexity compared with the state-of-the-art approach based on patch-based dark channel prior. ©2013 Optical Society of America.

关键词： Pixels

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Error analysis for RADAR neighbor matching localization in linear logarithmic strength varying Wi-Fi environment

The Scientific World Journal

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The Scientific World Journal 2014年第1期2014卷 647370页

作者： Zhou, Mu Tian, Zengshan Xu, Kunjie Yu, Xiang Wu, Haibo Chongqing Key Lab of Mobile Communications Technology Chongqing University of Posts and Telecommunications Chongqing 400065 China Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Kowloon Hong Kong Graduate Telecommunications and Networking Program University of Pittsburgh Pittsburgh PA 15260 United States China Internet Research Lab Computer Network Information Center Chinese Academy of Sciences Beijing 100190 China

This paper studies the statistical errors for the fingerprint-based RADAR neighbor matching localization with the linearly calibrated reference points (RPs) in logarithmic received signal strength (RSS) varying Wi-Fi environment. To the best of our knowledge, little comprehensive analysis work has appeared on the error performance of neighbor matching localization with respect to the deployment of RPs. However, in order to achieve the efficient and reliable location-based services (LBSs) as well as the ubiquitous context-awareness in Wi-Fi environment, much attention has to be paid to the highly accurate and cost-efficient localization systems. To this end, the statistical errors by the widely used neighbor matching localization are significantly discussed in this paper to examine the inherent mathematical relations between the localization errors and the locations of RPs by using a basic linear logarithmic strength varying model. Furthermore, based on the mathematical demonstrations and some testing results, the closed-form solutions to the statistical errors by RADAR neighbor matching localization can be an effective tool to explore alternative deployment of fingerprint-based neighbor matching localization systems in the future. © 2014 Mu Zhou et al.

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A case study on effectively identifying technical debt 13

A case study on effectively identifying technical debt

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17th International Conference on Evaluation and Assessment in Software engineering, EASE 2013

作者： Zazworka, Nico Spínola, Rodrigo O. Vetro, Antonio Shull, Forrest Seaman, Carolyn Fraunhofer USA Center for Experimental Software Engineering College Park United States Graduate Program in Systems and Computer UNIFACS Salvador Brazil Dept. of Control and Computer Engineering Politecnico di Torino Torino Italy Department of Information Systems UMBC Baltimore United States Elsevier Information Systems GmbH Frankfurt Germany

ISBN: (纸本)9781450318488

Context: The technical debt (TD) concept describes a tradeoff between short-term and long-term goals in software development. While it is highly useful as a metaphor, it has utility beyond the facilitation of discussion, to inspire a useful set of methods and tools that support the identification, measurement, monitoring, management, and payment of TD. Objective: This study focuses on the identification of TD. We evaluate human elicitation of TD and compare it to automated identification. Method: We asked a development team to identify TD items in artifacts from a software project on which they were working. We provided the participants with a TD template and a short questionnaire. In addition, we also collected the output of three tools to automatically identify TD and compared it to the results of human elicitation. Results: There is little overlap between the TD reported by different developers, so aggregation, rather than consensus, is an appropriate way to combine TD reported by multiple developers. The tools used are especially useful for identifying defect debt but cannot help in identifying many other types of debt, so involving humans in the identification process is necessary. Conclusion: We have conducted a case study that focuses on the practical identification of TD, one area that could be facilitated by tools and techniques. It contributes to the TD landscape, which depicts an understanding of relationships between different types of debt and how they are best discovered. Copyright 2013 ACM.

关键词： Software design

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Erratum to: The whole genome sequence of the Mediterranean fruit fly, Ceratitis capitata (Wiedemann), reveals insights into the biology and adaptive evolution of a highly invasive pest species

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Genome biology 2017年第1期18卷 11页

作者： Alexie Papanicolaou Marc F Schetelig Peter Arensburger Peter W Atkinson Joshua B Benoit Kostas Bourtzis Pedro Castañera John P Cavanaugh Hsu Chao Christopher Childers Ingrid Curril Huyen Dinh HarshaVardhan Doddapaneni Amanda Dolan Shannon Dugan Markus Friedrich Giuliano Gasperi Scott Geib Georgios Georgakilas Richard A Gibbs Sarah D Giers Ludvik M Gomulski Miguel González-Guzmán Ana Guillem-Amat Yi Han Artemis G Hatzigeorgiou Pedro Hernández-Crespo Daniel S T Hughes Jeffery W Jones Dimitra Karagkouni Panagiota Koskinioti Sandra L Lee Anna R Malacrida Mosè Manni Kostas Mathiopoulos Angela Meccariello Monica Munoz-Torres Shwetha C Murali Terence D Murphy Donna M Muzny Georg Oberhofer Félix Ortego Maria D Paraskevopoulou Monica Poelchau Jiaxin Qu Martin Reczko Hugh M Robertson Andrew J Rosendale Andrew E Rosselot Giuseppe Saccone Marco Salvemini Grazia Savini Patrick Schreiner Francesca Scolari Paolo Siciliano Sheina B Sim George Tsiamis Enric Ureña Ioannis S Vlachos John H Werren Ernst A Wimmer Kim C Worley Antigone Zacharopoulou Stephen Richards Alfred M Handler Hawkesbury Institute for the Environment Western Sydney University Sydney Australia. Justus-Liebig-University Giessen Institute for Insect Biotechnology 35394 Giessen Germany. Department of Biological Sciences Cal Poly Pomona Pomona CA 91768 USA. Department of Entomology and Center for Disease Vector Research University of California Riverside Riverside CA 92521 USA. Interdepartmental Graduate Program in Genetics Genomics & Bioinformatics University of California Riverside Riverside CA 92521 USA. Department of Biological Sciences University of Cincinnati Cincinnati OH 45221 USA. Insect Pest Control Laboratory Joint FAO/IAEA Programme of Nuclear Techniques in Food and Agriculture Seibersdorf Vienna Austria. Department of Environmental and Natural Resources Management University of Patras Agrinio Greece. Department of Environmental Biology Centro de Investigaciones Biológicas CSIC 28040 Madrid Spain. Human Genome Sequencing Center Department of Human and Molecular Genetics Baylor College of Medicine 77030 Houston TX USA. National Agricultural Library USDA 20705 Beltsville MD USA. Georg-August-Universität Göttingen Johann-Friedrich-Blumenbach-Institut für Zoologie und Anthropologie 37077 Göttingen Germany. Department of Biology University of Rochester 14627 Rochester NY USA. Department of Biological Sciences Wayne State University 48202 Detroit MI USA. Department of Biology and Biotechnology University of Pavia 27100 Pavia Italy. USDA-ARS Pacific Basin Agricultural Research Center 96720 Hilo HI USA. DIANA-Lab Department of Electrical & Computer Engineering University of Thessaly 382 21 Volos Greece and Hellenic Pasteur Institute 11521 Athens Greece. Department of Entomology University of Illinois at Urbana-Champaign 61801 Urbana IL USA. Department of Biological Sciences Oakland University 48309 Rochester MI USA. Department of Biochemistry and Biotechnology University of Thessaly Larissa Greece. Department of Biology Univer

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Investigating technical debt folklore: Shedding some light on technical debt opinion

Investigating technical debt folklore: Shedding some light o...

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2013 4th International Workshop on Managing Technical Debt, MTD 2013

作者： Spínola, Rodrigo O. Vetrò, Antonio Zazworka, Nico Seaman, Carolyn Shull, Forrest Graduate Program in Systems and Computer Universidade Salvador UNIFACS Salvador BA Brazil Dept. of Control and Computer Engineering Politecnico di Torino Torino Italy Elsevier Information Systems GmbH Frankfurt Germany Department of Information Systems UMBC Baltimore MD United States Fraunhofer USA Center for Experimental Software Engineering College Park United States

ISBN: (纸本)9781467364430

We identified and organized a number of statements about technical debt (TD Folklore list) expressed by practitioners in online websites, blogs and published papers. We chose 14 statements and we evaluated them through two surveys (37 practitioners answered the questionnaires), ranking them by agreement and consensus. The statements most agreed with show that TD is an important factor in software project management and not simply another term for 'bad code'. This study will help the research community in identifying folklore that can be translated into research questions to be investigated, thus targeting attempts to provide a scientific basis for TD management. © 2013 IEEE.

关键词： Surveys

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Cross-camera complementary vehicle matching via feature expandsion for video forensics

Cross-camera complementary vehicle matching via feature expa...

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IEEE International Symposium on Consumer Electronics (ISCE)

作者： Chao-Yung Hsu Chih-Yang Lin Li-Wei Kang Hong-Yuan Mark Liao Institute of Information Science Academia Sinica Taipei Taiwan Department of Computer Science and Information Engineering Asia University Taichung Taiwan Graduate School of Engineering Science and Technology-Doctoral Program and Department of Computer Science and Information Engineering National Yunlin University of Science and Technology Yunlin Taiwan

ISBN: (纸本)9781467361989

In this paper, we will investigate a more challenging vehicle matching problem. The problem is formulated as invariant image feature matching among opposite viewpoints of cameras, i.e. complementary object matching. For example, a front vehicle object may be given as a query to retrieve a rear vehicle object of the same vehicle. To solve the complementary object matching, invariant image feature is first extracted based on ASIFT (affine and scale-invariant feature transform) for each detected vehicle in a camera network. Then, the ASIFT feature is expanded via a special vehicle database. As a result, cross-camera vehicle matching with the help of complementary part can be greatly improved. Experimental results demonstrate the effectiveness of the proposed algorithm and the feasibility to video forensics applications.

关键词： Vehicles Cameras Databases Feature extraction Visualization Digital forensics

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