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Appointments for 2005-2006 term

IEEE Transactions on Very Large Scale Integration (VLSI) Systems 2005年第7期13卷 773-782页

作者： Ranganathan, Nagarajan Agrawal, Vishwani D. Chakradhar, Srimat T. Chakrabarty, Krishnendu Courtois, Bernard DeMara, Ronald Hu, Xiaobo Sharon Ismail, Yehea I. Jha, Niraj K. John, Lizy Kurian Ker, Ming-Dou Koren, Israel Liu, Bin-Da Marculescu, Diana Marculescu, Radu Narayanan, Vijaykrishnan Nassif, Sani R. Nowick, Steven M. Sapatnekar, Sachin S. Sherlekar, Sunil Sylvester, Dennis Vemuri, Ranga Pham, Michael Department of Computer Science and Engineering University of South Florida Tampa FL 33620 United States Department of Computer Science and Engineering Nanomaterials and Nanomanufacturing Research Center University of South Florida Tampa United States IEEE United States Systems United States Department of Electrical and Computer Engineering Rutgers University New Brunswick NJ United States IETE India ACM NEC Laboratories America Inc. Princeton NJ United States Duke University Durham NC United States ACM SIGDA Sigma Xi United States Laboratory of Techniques of Informatics and Microelectronics for Computer Architectecture ASME IMAPS IEEE Computer Society University of Central Florida Orlando United States Computer Engineering Program SEECS Department of Computer Science and Engineering University of Notre Dame Notre Dame IN United States Northwestern University Evanston IL United States Department of Electrical Engineering Princeton University Princeton NJ United States Association for Computing Machinery Austin United States UT Austin Engineering Foundation United States Department of Electronics Engineering National Chiao-Tung University Taiwan Department of Electrical and Computer Engineering University of Massachusetts Amherst United States Department of Electrical Engineering Department of Electrical and Computer Engineering Carnegie Mellon University Pittsburgh PA United States Electrical and Computer Engineering Faculty Carnegie Mellon University Pittsburgh PA United States Computer Science and Engineering Department Pennsylvania State University University Park United States IBM Austin Research Laboratory Austin TX United States Columbia University New York NY United States Department of Electrical and Computer Engineering University of Minnesota Minneapolis United States Tata Consultancy Services Centre of Excellence for Embedded Systems India Department of Electrical Engineering IIT Bombay India Department of Electrical Engineering Uni

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A comparative evaluation of competitive learning algorithms for edge detection enhancement

A comparative evaluation of competitive learning algorithms ...

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European Signal Processing Conference (EUSIPCO)

作者： Tuba Sirin Mehmet Izzet Saglam Isin Erer Muhittin Gokmen Okan Ersoy Informatics Institute Computer Science and Engineering Informatics Institute Satellite Communication and Remote Sensing Program Faculty of Electrical and Electronic Engineering Electronics and Communication Department Faculty of Electrical and Electronic Engineering Istanbul Technical University Maslak Istanbul TURKEY Purdue University School of Electrical and Computer Engineering West Lafayette Indiana USA

Most edge detection algorithms include three main stages: smoothing, differentiation, and labeling. In this paper, we evaluate the performance of algorithms in which competitive learning is applied first to enhance edges, followed by an edge detector to locate the edges. In this way, more detailed and relatively more unbroken edges can be found as compared to the results when an edge detector is applied alone. The algorithms compared are K-Means, SOM and SOGR for clustering, and Canny and GED for edge detection. Perceptionally, best results were obtained with the GED-SOGR algorithm. The SOGR is also considerably simpler and faster than the SOM algorithm.

关键词： Image edge detection Image segmentation Vectors Abstracts Filtering algorithms Erbium Training

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A Submission Model for Use in the Indexing, Searching, and Retrieval of Distributed Pathology Case and Tissue Specimens 11

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11th World Congress on Medical informatics, MEDINFO 2004

作者： Namini, Ahmad H. Berkowicz, David A. Kohane, Isaac S. Chueh, Henry Laboratory of Computer Science Massachusetts General Hospital BostonMA United States Children's Hospital Informatics Program Harvard-Partners Center for Genetics and Genomics BostonMA United States

ISBN: (纸本)1586034448

This paper describes the Shared Pathology informatics Network (SPIN) submission model for uploading de-identified XML annotations of pathology case and specimen information to a distributed peer-to-peer network architecture. SPIN use cases, architecture, and technologies, as well as pathology information design is described. With the architecture currently in use by six member institutions, SPIN appears to be a viable, secure methodology to submit pathology information for query and specimen retrieval by investigators. © 2004 IMIA. All rights reserved.

关键词： Pathology

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Causal Discovery Using A Bayesian Local Causal Discovery Algorithm

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11th World Congress on Medical informatics, MEDINFO 2004

作者： Mani, Subramani Cooper, Gregory F. Center for Biomedical Informatics The Intelligent Systems Program University of Pittsburgh PA15213 United States Department of Computer Science University of Wisconsin-Milwaukee MilwaukeeWI53201 United States

ISBN: (纸本)1586034448

This study focused on the development and application of an efficient algorithm to induce causal relationships from observational data. The algorithm, called BLCD, is based on a causal Bayesian network framework BLCD initially uses heuristic greedy search to derive the Markov Blanket (MB) of a node that serves as the "locality "for the identification of pair-wise causal relationships. BLCD takes as input a dataset and outputs potential causes of the form variable X causally influences variable Y. Identification of the causal factors of diseases and outcomes, can help formulate better management, prevention and control strategies for the improvement of health care. In this study we focused on investigating factors that may contribute causally to infant mortality in the United States. We used the U.S. Linked Birth/Infant Death dataset for 1991 with more than four million records and about 200 variables for each record. Our sample consisted of 41,155 records randomly selected from the whole dataset. Each record had maternal, paternal and child factors and the outcome at the end of the first year-whether the infant survived or not. Using the infant birth and death dataset as input, BLCD output six purported causal relationships. Three out of the six relationships seem plausible. Even though we have not yet discovered a clinically novel causal link, we plan to look for novel causal pathways using the full sample. © 2004 IMIA. All rights reserved.

关键词： Bayesian networks

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Causal discovery using a Bayesian local causal discovery algorithm

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Studies in Health Technology and informatics 2004年第PT 1期107卷 731-735页

作者： Mani, Subramani Cooper, Gregory F. Center for Biomedical Informatics Intelligent Systems Program University of Pittsburgh PA 15213 United States Department of Computer Science University of Wisconsin Milwaukee Milwaukee WI 53201 United States

This study focused on the development and application of an efficient algorithm to induce causal relationships from observational data. The algorithm, called BLCD, is based on a causal Bayesian network framework. BLCD initially uses heuristic greedy search to derive the Markov Blanket (MB) of a node that serves as the 'locality' for the identification of pair-wise causal relationships. BLCD takes as input a dataset and outputs potential causes of the form variable X causally influences variable Y. Identification of the causal factors of diseases and outcomes, can help formulate better management, prevention and control strategies for the improvement of health care. In this study we focused on investigating factors that may contribute causally to infant mortality in the United States. We used the U.S. Linked Birth/Infant Death dataset for 1991 with more than four million records and about 200 variables for each record. Our sample consisted of 41,155 records randomly selected from the whole dataset. Each record had maternal, paternal and child factors and the outcome at the end of the first year-whether the infant survived or not. Using the infant birth and death dataset as input, BLCD output six purported causal relationships. Three out of the six relationships seem plausible. Even though we have not yet discovered a clinically novel causal link, we plan to look for novel causal pathways using the full sample. © 2004 IMIA. All rights reserved.

关键词： Bayesian networks

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End-to-end layered multicast of streaming media in heterogeneous networks

End-to-end layered multicast of streaming media in heterogen...

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IEEE International Conference on Performance, Computing and Communications (IPCCC)

作者： C. Nagaraj M. Nguyen L. Pezeshkmehr M. Moh Department of Computer Science San Jose State University San Jose CA USA Department of Computer Science San Jose State University Foundation San Jose CA USA CSU PERB (Program of Education and Research in Bio-informatics) and SJSU Lottery Grant

There has been a growing demand for streaming media distribution over the Internet, which consists of heterogeneous end hosts with different capabilities and using various last-mile network connections. To provide end-to-end differentiated services of streaming media among heterogeneous users, an application-layer multicasting of layered encoded streams is presented. The proposed basic scheme incorporates the existing NICE protocol proposed by Banerjee el al. (2002) with layered multicasting similar to receiver-driven layered multicast (RLM) proposed by McCanne et al. (1996). The resulting protocol is further enhanced with an improved cluster-leader selection process and prioritized control packet treatments. By applying cumulative video encoding scheme, the enhanced protocol provides service differentiation among end hosts of different capabilities, allowing them to receive different video qualities corresponding to one or more layers of encoded streams. When compared with the basic scheme via simulation, the enhanced protocol provides better video quality, higher bandwidth usage, and lower loss rate.

关键词： Streaming media Intelligent networks Encoding Bandwidth Multicast protocols Internet computer science IP networks Process control Business

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A framework for assessing HMIS in developing countries: Latvia as a case study

A framework for assessing HMIS in developing countries: Latv...

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Annual Hawaii International Conference on System sciences (HICSS)

作者： D.S. Haazen D.J. Streveler Senior Health Specialist Health Program Team Leader World Bank Europe and Central Asia Region Riga Latvia Medical Informatics Department of Information and Computer Science University of Hawai Honolulu HI USA

The health systems in many developing countries lag seriously behind the developed world in the use of health management information systems (HMIS). The World Bank, like other international donor organizations, is increasingly called upon to provide technical and financial assistance in this area, but success stories remain rare. Because HMIS are critical to developing and improving health systems delivery and finance, the bank must find ways to increase effectiveness of the interventions it supports. This paper attempts to contribute to this process by proposing a new conceptual framework for the assessment of HMIS interventions, and then demonstrating the framework by applying it to an existing project to support national health insurance in Latvia. The paper documents the key characteristics of the HMIS project, discusses successes and failures to date, and presents lessons learned that may be applicable to other HMIS projects in developing countries. The case study focuses on a functional classification of the HMIS implementation, and critical success factors that have emerged with regard to systems implementation in developed countries.

关键词： computer aided software engineering Management information systems Europe Asia Insurance Environmental management Project management Biomedical informatics computer science Finance

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A Factorized High Dimensional Model Representation on the Partitioned Random Discrete Data

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Applied Numerical Analysis & Computational Mathematics 2004年第1期1卷

作者： M. Alper Tunga Metin Demiralp Department of Computer Science and Engineering Engineering Faculty Işįk University Maslak 34398 İstanbul Turkey Computational Science and Engineering Program Informatics Institute İstanbul Technical University Maslak 80626 İstanbul Turkey Phone: +90 212 285 70 82 Fax: +90 212 285 70 73

The main purpose of this work is to obtain the general structure of a product type of multivariate function when the values of the function are given randomly at the nodes of a hyperprism. When the dimensionality of multivariate interpolation and the number of the data sets increase unboundedly, many problems can be encountered in the standard numerical methods. Factorized High Dimensional Model Representation (FHDMR) is used to obtain the general structure of this given multivariate function. The components of FHDMR are determined by using the components of the Generalized High Dimensional Model Representation (GHDMR).The given random discrete data is partitioned by GHDMR method. This partitioned data produces a structure for the multivariate function by using single variable Lagrange interpolation formula including only the constant term and the univariate terms of the GHDMR components. Finally, a general structure is obtained via FHMDR by using these components. By this way, the multidimensionality of a multivariate interpolation is approximated by lower dimensional interpolations like univariate ones. (© 2004 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)

关键词： Multivariate functions multivariate representations approximation factor analysis interpolation multidimensional problems

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A rule-based XML access control model

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in computer science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2003年 2876卷 35-48页

作者： Anutariya, Chutiporn Chatvichienchai, Somchai Iwiahara, Mizuho Wuwongse, Vilas Kambayashi, Yahiko Computer Science Program Shinawatra University Pathumthani Thailand Department of Social Informatics Graduate School of Informatics Kyoto University Kyoto Japan Computer Science and Information Management Program Asian Institute of Technology Pathumthani Thailand

Due to a widely use of XML language in various application domains, a well-established mechanism for the definition and enforcement of security controls on specific accesses to XML documents is demanded, in order to ensure that only authorized entities can perform certain actions on the protected data. The proposed rule-based, declarative approach supports definition of (possibly implicit and complex) authorization rules on particular nodes within a document as well as enforcement of multiple user-defined policies, specifying selected mechanisms to resolve conflicts or to apply default authorization. Moreover, by founded on both RDF and XDD theory, the developed approach yields a simple yet flexible and interchangeable XML access control model with well-defined declarative semantics. © Springer-Verlag Berlin Heidelberg 2003.

关键词： Access control models

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Humanoid Arm Motion Planning using Stereo Vision and RRT Search

Humanoid Arm Motion Planning using Stereo Vision and RRT Sea...

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2003 IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Kagami, Satoshi Kuffner, James J. Nishiwaki, Koichi Okada, Kei Inaba, Masayuki Inoue, Hirochika Digital Human Lab. Natl. Inst. of Adv. Sci./Technology CREST Program Japan Sci./Technology Corporation School of Computer Science Carnegie Mellon University Dept. of Mechano-Informatics Sch. of Info. Science and Technology Univ. of Tokyo

This paper describes an experimental stereo vision based motion planning system for humanoid robots. The goal is to automatically generate arm trajectories that avoid obstacles in unknown environments from high-level task commands. Our system consists of three components: 1) environment sensing using stereo vision with disparity map generation and online consistency checking, 2) probabilistic mesh modeling in order to accumulate continuous vision input, and 3) motion planning for the robot arm using RRTs (Rapidly exploring Random Trees). We demonstrate results from experiments using an implementation designed for the humanoid robot H7.

关键词： Intelligent robots

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