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Advances in Intelligent and Soft Computing 2012年 151 AISC卷 V-VI页

作者： Omatu, Sigeru De Paz Santana, Juan F. González, Sara Rodríguez Molina, Jose M. Bernardos, Ana M. Rodríguez, Juan M. Corchado Graduate School of Engineering Osaka Prefecture University Sakai Osaka Japan Department of Computer Science Faculty of Science University of Salamanca Salamanca Spain Applied Artificial Intelligence Group Universidad Carlos III de Madrid Colmenarejo Madrid Spain Data Processing and Simulation Group ETSI. Telecomunicación Universidad Politécnica de Madrid Madrid Spain

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A semantic infrastructure for a knowledge driven sensor web

A semantic infrastructure for a knowledge driven sensor web

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4th International Workshop on Semantic Sensor Networks 2011, SSN 2011 - A 10th International Semantic Web Conference, ISWC 2011

作者： Moodley, Deshendran Tapamo, Jules Raymond School of Computer Science University of KwaZulu-Natal Durban South Africa School of Electrical Electronic and Computer Engineering University of KwaZulu-Natal Durban South Africa CSIR Meraka Centre for Artificial Intelligence Research University of KwaZulu-Natal South Africa

Sensor Web researchers are currently investigating middleware to aid in the dynamic discovery, integration and analysis of vast quantities of high quality, but distributed and heterogeneous earth observation data. Key challenges being investigated include dynamic data integration and analysis, service discovery and semantic interoperability. However, few efforts deal with the management of both knowledge and system dynamism. Two emerging technologies that have shown promise in dealing with these issues are ontologies and software agents. This paper introduces the idea and identifies key requirements for a Knowledge Driven Sensor Web and presents our efforts towards developing an associated semantic infrastructure within the Sensor Web Agent Platform.

关键词： Multi agent systems

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Meeting Report: BioSharing at ISMB 2010

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Standards in genomic sciences 2010年第3期3卷 254-8页

作者： Dawn Field Susanna Sansone Edward F Delong Peter Sterk Iddo Friedberg Pascale Gaudet Susanna Lewis Renzo Kottmann Lynette Hirschman George Garrity Guy Cochrane John Wooley Folker Meyer Sarah Hunter Owen White Brian Bramlett Susan Gregurick Hilmar Lapp Sandra Orchard Philippe Rocca-Serra Alan Ruttenberg Nigam Shah Chris Taylor Anne Thessen Centre for Ecology & Hydrology Wallingford UK Oxford e-Research Centre University of Oxford Oxford UK Department of Biological Engineering Massachusetts Institue of Technology Cambridge USA Department of Microbiology Miami University Oxford USA Department of Computer Science and Software Engineering Miami University Oxford USA Swiss Institute of Bioinformatics Geneva 4 Switzerland Lawrence Berkeley National Laboratory Berkeley USA Microbial Genomics Group Max Planck Institute for Marine Microbiology & Jacobs University Bremen Bremen Germany Information Technology Center The MITRE Corporation Bedford USA Department of Microbiology and Molecular Genetics Michigan State University East Lansing USA European Molecular Biology Laboratory (EMBL) Outstation European Bioinformatics Institute (EBI) Cambridge UK University of California San Diego La Jolla USA Argonne National Laboratory Argonne USA Institute for Genome Sciences University of Maryland School of Medicine Baltimore USA Lux Bio Group Portland USA Biological Systems Science Division Department of Energy Washington DC USA National Evolutionary Synthesis Center (NESCent) Durham USA Science Commons c/o Massachusetts Institute of Technology Computer Science and Artificial Intelligence Laboratory Cambridge USA Stanford Center for Biomedical Informatics Research Stanford USA Marine Biological Laboratory USA

This report summarizes the proceedings of the one day BioSharing meeting held at the Intelligent Systems for Molecular Biology (ISMB) 2010 conference in Boston, MA, USA This inaugural BioSharing event was hosted by the Genomic Standards Consortium as part of its M3 & BioSharing special interest group (SIG) workshop. The BioSharing event included invited talks from a range of community leaders and a panel discussion at the end of the day. The panel session led to the formal agreement among community leaders to join together to promote cross-community knowledge exchange and collaborations. A key focus of the newly formed Biosharing community will be linking up resources to promote real-world data sharing (virtuous cycle of data) and supporting compliance with data policies through the creation of a one-stop-portal of information. Further information about the newly established BioSharing effort can be found at http://***.

关键词： Community Leader Funding Agency Special Interest Group Panel Discussion Standardization Effort

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An interactive decision support system based on consistency criteria

An interactive decision support system based on consistency ...

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作者： Alonso, S. Cabrerizo, F.J. Chiclana, F. Herrera, F. Herrera-Viedma, E. Department of Software Engineering University of Granada 18071 Granada Spain Centre for Computational Intelligence School of Computing De Montfort University Leicester LEI 9BH United Kingdom Department of Computer Science and Artificial Intelligence University of Granada 18071 Granada Spain

To achieve consistent solutions is an important goal in group decision making problems. However, the expression of preferences is often a very difficult task for the experts, specially in decision problems with a high number of alternatives and when experts use fuzzy preference relations to provide their opinions. This usually leads to situations where experts are not able to properly express all their preferences in a consistent way, that is, without contradiction. In this paper, to overcome this problem, we present a decision support system based on consistency criteria to aid experts to express their fuzzy preference relations in a more consistent way. The system works interactively with the expert by providing him/her recommendations on the preference values that he/she has not yet expressed. These recommendations are computed trying to maintain the expert's consistency level as high as possible. ©2008 Old City Publishing, Inc.

关键词： Decision support systems

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Fast lane detection with Randomized Hough Transform

Fast lane detection with Randomized Hough Transform

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International Symposium on Information Technology, ITSim

作者： Azali Saudi Jason Teo Mohd Hanafi Ahmad Hijazi Jumat Sulaiman Centre for Artificial Intelligence Computer Science Program School of Engineering & Information Technology Universiti Malaysia Sabah Kota Kinabalu Malaysia Computer Graphics Program School of Science & Technology Universiti Malaysia Sabah Kota Kinabalu Malaysia

Lane detection is an essential component of autonomous mobile robot applications. Any lane detection method has to deal with the varying conditions of the lane and surrounding that the robot would encounter while moving. Lane detection procedure can provide estimates for the position and orientation of the robot within the lane and also can provide a reference system for locating other obstacles in the path of the robot. In this paper we present a method for lane detection in video frames of a camera mounted on top of the mobile robot. Given video input from the camera, the gradient of the current lane in the near field of view are automatically detected. Randomized Hough Transform is used for extracting parametric curves from the images acquired. A priori knowledge of the lane position is assumed for better accuracy of lane detection.

关键词： Transforms Roads Pixel Robustness Image edge detection Vehicles Equations

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IMPLEMENTATION OF A LOCALIZATION-ORIENTED HRI FOR WALKING ROBOTS IN THE ROBOCUP ENVIRONMENT

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International Journal of Information Acquisition 2008年第4期5卷 331-347页

作者： RENATO SAMPERIO HUOSHENG HU DONGBING GU Logistics and Production Robotics German Research Centre for Artificial Intelligence Robert-Hooke-Str. 5 28359 Bremen Germany School of Computer Science and Electronic Engineering University of Essex Wivenhoe Park Colchester CO4 3SQ United Kingdom

This paper presents the design and implementation of a human–robot interface capable of evaluating robot localization performance and maintaining full control of robot behaviors in the RoboCup domain. The system consists of legged robots, behavior modules, an overhead visual tracking system, and a graphic user interface. A human–robot communication framework is designed for executing cooperative and competitive processing tasks between users and robots by using object oriented and modularized software architecture, operability, and functionality. Some experimental results are presented to show the performance of the proposed system based on simulated and real-time information.

关键词： Human–robot interface GUI walking robots

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Visualizing Consensus in Group Decision Making Situations

Visualizing Consensus in Group Decision Making Situations

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IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

作者： S. Alonso E. Herrera-Viedma F.J. Cabrerizo F. Chiclana F. Herrera Software Engineering Department University of Granada Spain Computer Science and Artificial Intelligence Department University of Granada Spain Centre for Computational Intelligence School of Computing De Montfort University Leicester UK

In the resolution of group decision making problems the consensus process, that is, the process where experts discuss about the alternatives to narrow their differences, is usually held with all the experts gathered together in a place where they can speak and discuss about the alternatives in the problem. However, in situations where it is not possible to bring them all together it is usually difficult for the experts to identify the closeness of the opinions of the rest of the experts, and thus, it can be difficult to have a clear view of the current state of the consensus process. In this paper we present a tool that creates consensus diagrams that help experts to easily comprehend the current consensus state in the decision problem. This tool is based on several consistency, consensus and similarity measures and with the application of a clustering algorithm, it identifies and represents the different groups of experts with similar opinions, identifies a possible candidate for spokesperson for each group and easily depicts the consistency level expressed by each one of the experts.

关键词： Visualization Decision making Clustering algorithms Software engineering computer science artificial intelligence Computational intelligence Communications technology Videoconference Electronic mail

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Looseness Controlled Crossover in GP for Object Recognition

Looseness Controlled Crossover in GP for Object Recognition

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Congress on Evolutionary Computation

作者： Mengjie Zhang Xiaoying Gao Weijun Lou School of Mathematics Statistics and Computer Science Victoria University of Wellington Wellington New Zealand Artificial Intelligence Research Centre College of Mechanical and Electrical Engineering Agricultural University of Hebei China

This paper describes an approach to improving the crossover operator in genetic programming for object recognition particularly object classification problems. In this approach, instead of randomly choosing the crossover points as in the standard crossover operator, we use a measure called looseness to guide the selection of crossover points. Rather than using the genetic beam search only, this approach uses a hybrid beam-hill climbing search scheme in the evolutionary process. This approach is examined and compared with the standard crossover operator and the headless chicken crossover method on a sequence of object classification problems. The results suggest that this approach outperforms both the headless chicken crossover and the standard crossover on all of these problems.

关键词： Object recognition Genetic programming Face detection Genetic algorithms Automatic programming Mathematics Statistics computer science Measurement standards Face recognition

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Background subtraction under varying illumination

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Systems and computers in Japan 2006年第4期37卷 77-88页

作者： Matsuyama, Takashi Wada, Toshikazu Habe, Hitoshi Tanahashi, Kazuya Graduate School of Informatics Kyoto University Kyoto 606-8501 Japan Mitsubishi Electric Corporation NTT Data Corporation Department of Intelligence Science and Technology Graduate School of Informatics Kyoto University International Association for Pattern Recognition IEICE Information Processing Society of Japan Japanese Society for Artificial Intelligence IEEE Computer Society Department of Computer and Communication Sciences Faculty of Systems Engineering Wakayama University IEEE

Background subtraction is widely used as an effective method for detecting moving objects in a video image. However, background subtraction requires a prerequisite in that image variation cannot be observed, and the range of application is limited. Proposed in this research paper is a method for detecting moving objects by using background subtraction that can be applied to cases in which the image has varied due to varying illumination. This method is based on two object detection methods that are based on different lines of thinking. One method compares the background image and the observed image using invariant features of illumination. The other method estimates the illumination conditions of the observed image and normalizes the brightness before carrying out background subtraction. These two methods are complementary, and highly precise detection results can be obtained by ultimately integrating the detection results of both methods. © 2006 Wiley Periodicals, Inc.

关键词： Lighting

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Dissertation abstracts

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Machine Vision and Applications 1989年第2期2卷 117-120页

作者： Tanimoto, Steven L. Srihari, Sargur N. Levine, Martin D. Seering, Warren P. Nevatia, R. Department of Computer Science FR-35 University of Washington Seattle USA Technical Report 88-08 Department of Computer Science SUNY at Buffalo Buffalo USA Technical Report 88-22 Department of Computer Science SUNY at Buffalo Buffalo USA Research Centre for Intelligent Machines McGill University Montréal Canada Publications Department Technical Report 932 MIT Artificial Intelligence Laboratory Cambridge USA Institute for Robotics and Intelligent Systems University of Southern California School of Engineering Los Angeles USA

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