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15th International Conference on Information Fusion, FUSION 2012

作者： Schikora, Marek Gning, Amadou Mihaylova, Lyudmila Cremers, Daniel Koch, Wolfgang Dept. Sensor Data and Information Fusion Fraunhofer FKIE Wachtberg Germany Dept. of Computer Science University College London United Kingdom School of Computing and Communications University of Lancaster United Kingdom Dept. Computer Science Technical University of Munich Germany

ISBN: (纸本)9780982443859

This paper develops a novel approach for multitarget tracking, called box-particle probability hypothesis density filter (box-PHD filter). The approach is able to track multiple targets and estimates the unknown number of targets. Furthermore, it is capable to deal with three sources of uncertainty: stochastic, set-theoretic and data association uncertainty. The box-PHD filter reduces the number of particles significantly, which improves the runtime considerably. The small particle number makes this approach attractive for distributed computing. A box-particle is a random sample that occupies a small and controllable rectangular region of non-zero volume. Manipulation of boxes utilizes methods from the field of interval analysis. The theoretical derivation of the box-PHD filter is presented followed by a comparative analysis with a standard sequential Monte Carlo (SMC) version of the PHD filter. To measure the performance objectively three measures are used: inclusion, volume and the optimum subpattern assignment metric. Our studies suggest that the box-PHD filter reaches similar accuracy results, like a SMC-PHD filter but with much considerably less computational costs. Furthermore, we can show that in the presence of strongly biased measurement the box-PHD filter even outperforms the classical SMC-PHD filter. © 2012 ISIF (Intl Society of Information Fusi).

关键词： Distributed computer systems

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Foundations of Relational Similarity-Based Query Language RESIQL

Foundations of Relational Similarity-Based Query Language RE...

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IEEE Symposium on Foundations of Computational Intelligence

作者： Petr Krajca Vilem Vychodil Data Analysis and Modeling Lab (DAMOL) Dept. Computer Science Palacky University Olomouc 17. listopadu 12 CZ–77146 Olomouc Czech Republic

ISBN: (纸本)9781467359009

We present a query language for similarity-based relational model of data with support of ordinal ranking and imperfect matches. The model utilized in this paper results from Codd's model of data by considering general residuated partially ordered scales of degrees of satisfaction in place of the twoelement Boolean scale implicitly used in the Codd model. As a result, we look at the traditional relational model of data from the perspective of general scales allowing us to represent partial matches of relational queries. From the data representation point of view, the basic structures representing both the stored data and results of queries are so-called ranked data tables, generalizing the ordinary data tables (relations). Compared to other approaches dealing with ranking and imperfect matches, ours has several benefits: (i) it is based on solid logical foundations-we do not introduce an additional ranking module on top of the Codd model but have all the necessary concepts as an integral part of the model, (ii) the model is very general and several ranking procedures introduced in the past can be shown to be particular cases of our model, (iii) the model is not oriented just to query answering, it allows to handle similarity-based data dependencies, approximate constraints and other issues that cannot be properly formalized in the classic Codd model, (iv) despite of its generality, query execution in the model is tractable. In this paper, we present logical foundations of the query language and show how it implements the underlying similarity-based model of data.

关键词： model twoelement relational

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Gesture spotting for controlling a mobile assistance system for service and maintenance 42

Gesture spotting for controlling a mobile assistance system ...

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42. Jahrestagung der Gesellschaft fur Informatik e.V. ,GI, Informatik 2012 - 42nd Annual Meeting of the German Informatics Society (GI), Informatics 2012

作者： Hein, Albert Low, Thomas Hensch, Maximilian Kirste, Thomas Nürnberger, Andreas Dept. of Computer Science University of Rostock Germany Data and Knowledge Engineering Group Otto-von-Guericke University Magdeburg Germany

ISBN: (纸本)9783885796022

As information technology interweaves with our daily environment, new modes of interaction will be required. In this paper, we suggest a gesture-based approach and present a prototypical case study for a gesture controlled mobile assistant system for an industrial application domain. We discuss a number of design requirements, that are common to gesture-based interaction techniques, describe the resulting system architecture, as well as the training and recognition process, and an experimental evaluation. We will show that even without too much effort such a system can be realized with standard hardware and algorithms, and still achieve very robust recognition results. © 2012 Gesellschaft fur Informatik (GI). All rights reserved.

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Advanced high-adaptive image coding for frame memory reduction in LCD overdrive

Advanced high-adaptive image coding for frame memory reducti...

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2012 9th IEEE RIVF International Conference on Computing and Communication Technologies, Research, Innovation, and Vision for the Future, RIVF 2012

作者： Huu, Tai Nguyen Thi, Hoang-Lan Nguyen Dept. of Information Technology Hue Univ. Hanoi Univ. of Science and Technology Hue Viet Nam Dept. of Data Communications and Computer Networks Hanoi Univ. of Science and Technology Hanoi Viet Nam

ISBN: (纸本)9781467303088

In this paper, Advanced High-Adaptive Image Coding (AHAIC) is proposed to increase compression performance for Frame Memory Reduction in LCD Overdrive. The AHAIC contains a new technique to improve the quality of decompressed images. It is a Content-based Bit Distribution Technique (CBBDT) which improves the image quality while preserving fixed word length compression feature. Experimental results show that, compared with other coding methods used in the same type of application, AHAIC has outperforming feature. ©2012 IEEE.

关键词： Image coding

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A science cloud for data intensive sciences

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data science Journal 2013年 12卷 WDS139-WDS146页

作者： Murata, Ken T. Watari, Shinichi Nagatsuma, Tsutomu Kunitake, Manabu Watanabe, Hidenobu Yamamoto, Kazunori Kubota, Yasufumi Kato, Hisao Tsugawa, Takuya Ukawa, Kentaro Muranaga, Kazuya Kimura, Eizen Tatebe, Osamu Fukazawa, Keiichiro Murayama, Yasuhiro 4-2-1 Nukui-kita Koganei Tokyo 184-8795 Japan Systems Engineering Consultants Co. Ltd. 4-10-1 Yoga Setagaya Tokyo 158-0097 Japan Dept. Medical Informatics of Medical School of Ehime Univ. Situkawa Toon City Ehime 791-0295 Japan Dept. Computer Science Univ. of Tsukuba Tenoudai 1-1-1 Tsukuba Science City Ibaraki 305-8573 Japan Research Institute for Information Technology Kyushu University 6-10-1 Hakozaki Higashi-Ku Fukuoka 812-8581 Japan Integrated Science Data System Research Lab NICT 4-2-1 Nukui-kita Koganei Tokyo 184-8795 Japan

It is often discussed that the fourth methodology for science research is "informatics". The first methodology is a theoretic approach, the second one is observation and/or experiment, and the third one is computer simulation. Informatics is a new methodology for data intensive science, which is a new concept based on the fact that most scientific data are digitalized and the amount of data is huge. The facilities to support informatics are cloud systems. Herein we propose a cloud system especially designed for science. The basic concepts, design, resources, implementation, and applications of the NICT science cloud are discussed.

关键词： Digital storage

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A quantitative evaluation of techniques for detection of abnormal change events in blogs. 12

A quantitative evaluation of techniques for detection of abn...

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12th ACM/IEEE-CS Joint Conference on Digital Libraries, JCDL '12

作者： Bogen II, Paul L. Furuta, Richard Shipman, Frank Intelligent Computing Research Team Computational Data Analytics Group Oak Ridge National Laboratory Oak Ridge TN United States Center for the Study of Digital Libraries Dept. of Computer Science and Engineering Texas A and M University College Station TX 77843 United States

ISBN: (纸本)9781450311540

While most digital collections have limited forms of change - primarily creation and deletion of additional resources - there exists a class of digital collections that undergoes additional kinds of change. These collections are made up of resources that are distributed across the Internet and brought together into a collection via hyperlinking. Resources in these collections can be expected to change as time goes on. Part of the difficulty in maintaining these collections is determining if a changed page is still a valid member of the collection. Others have tried to address this problem by measuring change and defining a maximum allowed threshold of change, however, these methods treat all change as a potential problem and treat web content as a static document despite its intrinsically dynamic nature. Instead, we approach the significance of change on the web as a normal part of a web document's life-cycle and determine the difference between what a maintainer expects a page to do and what it actually does. In this work we evaluate the different options for extractors and analyzers in order to determine the best options from a suite of techniques. The evaluation used a human-generated ground-truth set of blog changes. The results of this work showed a statistically significant improvement over a range of traditional threshold techniques when applied to our collection of tagged blog changes. © 2012 ACM.

关键词： Pattern recognition

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The Demeter Framework for model and data interoperability

The Demeter Framework for model and data interoperability

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6th Biennial Meeting of the International Environmental Modelling and Software Society: Managing Resources of a Limited Planet, iEMSs 2012

作者： Fritzinger, Eric Dascalu, Sergiu M. Ames, Daniel P. Benedict, Karl Gibbs, Ivan McMahon Jr., Michael J. Harris Jr., Frederick C. Dept. of Computer Science and Engineering University of Nevada Reno United States Department of Geosciences Idaho State University United States Earth Data Analysis Center University of New Mexico United States

ISBN: (纸本)9788890357428

This paper presents an overview of the Demeter Framework being developed at the University of Nevada, Reno as part of the Nevada Climate Change Portal. The Demeter Framework proposes a new solution to the model coupling problem by taking a component-based approach that allows almost any standard or type of component to be integrated within the system. For example, the DotSpatial toolbox from Idaho State University is currently being integrated into the Demeter Framework to handle complex geospatial processing, and can then be linked with components from many different sources. The Demeter Framework utilizes flow control and automated data conversions to help manage the issues that arise with non-homogenous component standards. It also encourages usergenerated content that can expand the functionality and availability of components, and as a result will also allow researchers to share their work freely and with very few logistical hindrances. The framework also relies on web service-based components to not only enable access to high-powered computing resources but also to help transcend the programming language and operating system barriers that many software frameworks encounter. The paper provides details on the key architectural concepts and components (activities, translators, channels, and data format converters) that make model and data interoperability possible with Demeter, presents the framework's Silverlight-based "Persephone" interface designed for user-friendly scenario configuration and execution, describes the workflow runtime web-service being developed, and, finally, provides examples of integration involving WaterOneFlow web services as data sources and DotSpatial toolset items as computational components.

关键词： Web services

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Box-particle intensity filter

Box-particle intensity filter

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9th IET data Fusion and Target Tracking Conference: Algorithms and Applications, DF and TT 2012

作者： Schikora, M. Gning, A. Mihaylova, L. Cremers, D. Koch, W. Streit, R. Fraunhofer FKIE Dept. Sensor Data and Information Fusion Wachtberg Germany University of Lancaster School of Computing and Communications United Kingdom University College London Department of Computer Science United Kingdom Technical University of Munich Department of Computer Science Germany Metron Inc. Reston VA United States

ISBN: (纸本)9781849196246

This paper develops a novel approach for multi-target tracking, called box-particle intensity filter (box-iFilter). The approach is able to cope with unknown clutter, false alarms and estimates the unknown number of targets. Furthermore, it is capable of dealing with three sources of uncertainty: stochastic, set-theoretic and data association uncertainty. The box-iFilter reduces the number of particles significantly, which improves the runtime considerably. The low particle number enables this approach to be used for distributed computing. A box-particle is a random sample that occupies a small and controllable rectangular region of non-zero volume. Manipulation of boxes utilizes the methods from the field of interval analysis. Our studies suggest that the box-iFilter reaches an accuracy similar to a sequential Monte Carlo (SMC) iFilter but with much less computational costs.

关键词： Distributed computer systems

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Caricature system using moving least squares based on Justin

International Journal of Multimedia and Ubiquitous Engineeri...

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International Journal of Multimedia and Ubiquitous Engineering 2012年第3期7卷 69-78页

作者： Lee, Jiye Byun, Hae Won Dept. of Computer Science Sungshin Women's University Korea Republic of LOTTE Data Communication Company Korea Republic of

In this paper, we propose a new automatically generation system of caricature which emphasizes the unique characteristics of the input images. This system can create the cartoon character similar to user's features by using set rules adopted a particular artist's technique. Input image is transformed by using MLS(Moving Least Squares) approximation[1] based on a predefined cartoon character's image. The unique characteristics of user can be detected by comparing the information between the mean face feature and the input face feature extracted by AAM(Active Appearance Model) [2]. In this paper, to exaggerate the detected unique characteristics, we set-up the exaggeration rules using the technique of Justin[10] who is caricature artist. In addition, during the cartooning process, user's hairs and accessories are applied to the deformed image to make a close resemblance. Reliable and matured caricature can be represented through the exaggeration rules of the actual caricature artist's techniques. From this study, we can easily create a cartoon caricature appearing user's feature by combining a caricature with existing cartoon researches.

关键词： Caricature Cartoon Image deformation Justin MLS

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InCaToMi: Integrative causal topic miner between textual and non-textual time series data 12

InCaToMi: Integrative causal topic miner between textual and...

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21st ACM International Conference on Information and Knowledge Management, CIKM 2012

作者： Kim, Hyun Duk Zhai, ChengXiang Rietz, Thomas A. Diermeier, Daniel Hsu, Meichun Castellanos, Malu Ceja Limon, Carlos A. Dept. of Computer Science University of Illinois at Urbana-Champaign Urbana IL United States Dept. of Finance University of Iowa Iowa City IA United States Kellogg School of Management Northwestern University Evanston IL United States Information Analytics Lab. HP Laboratories Palo Alto CA United States HP Laboratories Guadalajara Mexico

ISBN: (纸本)9781450311564

Topic modeling is popular for text mining tasks. Recently, topic modeling has been combined with time lines when textual data is related to external non-textual time series data such as stock prices. However, no previous work has used the external non-textual time series data in the process of topic modeling. In this paper, we describe a novel text mining system, Integrative Causal Topic Miner (InCaToMi) that integrates textual and non-textual time series data. InCaToMi automatically finds causal relationships and topics using text data and external non-textual time series data using Granger Testing. Moreover, InCaToMi considers the non-textual time series data in the topic modeling process, using the time series data to iteratively improve modeling results through interactions between it and the textual data at both topic and word levels. © 2012 Authors.

关键词： Time series

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