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International Conference on Network Protocols

作者： Chiping Tang P.K. McKinley Software Engineering and Network Systems Laboratory Department of Computer Science and Engineering Michigan State University East Lansing MI USA

Path probing is essential to maintaining an efficient overlay network topology. However, the cost of a full-scale probing is as high as O(n/sup 2/), which is prohibitive in large-scale overlay networks. Several methods have been proposed to reduce probing overhead, although at a cost in terms of probing completeness. In this paper, an orthogonal solution is proposed that trades probing overhead for estimation accuracy in sparse networks such as the Internet. The proposed solution uses network-level path composition information (for example, as provided by a topology server) to infer path quality without full-scale probing. The inference metrics include latency, loss rate and available bandwidth. This approach is used to design several probing algorithms, which are evaluated through analysis and simulation. The results show that the proposed method can significantly reduce probing overhead while providing hounded quality estimations for all n /spl times/ (n - 1) overlay paths. The solution is well suited to medium-scale overlay networks in the Internet. In other environments, it can be combined with extant probing algorithms to further improve performance.

关键词： Network topology Costs IP networks Algorithm design and analysis Large-scale systems Network servers Web server Delay Bandwidth Inference algorithms

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Architecture and operation of an adaptable communication substrate

Architecture and operation of an adaptable communication sub...

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IEEE Workshop on Future Trends of Distributed Computing systems

作者： S.M. Sadjadi P.K. McKinley E.P. Kasten Software Engineering and Network Systems Laboratory Department of Computer Science and Engineering Michigan State University East Lansing MI USA

This paper describes the internal architecture and operation of an adaptable communication component called the MetaSocket. MetaSockets are created using Adaptive Java, a reflective extension to Java that enables a component's internal architecture and behavior to be adapted at run time in response to external stimuli. This paper describes how adaptive behavior is implemented in MetaSockets, as well as how MetaSockets interact with other adaptive components, such as decision makers and event mediators. Results of experiments on a mobile computing testbed demonstrate how MetaSockets respond to dynamic wireless channel conditions in order to improve the quality of interactive audio streams delivered to iPAQ handheld computers.

关键词： Java computer architecture Handheld computers Application software Military computing computer languages Middleware Sockets Time factors Streaming media

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Enhancing the fault-tolerance of nonmasking programs

Enhancing the fault-tolerance of nonmasking programs

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International Conference on Distributed Computing systems

作者： S.S. Kulkarni A. Ebnenasir Department of Computer Science and Engineering Software Engineering and Network Systems Laboratory Michigan State University East Lansing MI USA

In this paper we focus on automated techniques to enhance the fault-tolerance of a nonmasking fault-tolerant program to masking. A masking program continually satisfies its specification even if faults occur. By contrast, a nonmasking program merely guarantees that after faults stop occurring, the program recovers to states from where it continually satisfies its specification. Until the recovery is complete, however a nonmasking program can violate its (safety) specification. Thus, the problem of enhancing fault-tolerance from nonmasking to masking requires that safety be added and recovery be preserved. We focus on this enhancement problem for high atomicity programs-where each process can read all variables-and for distributed programs-where restrictions are imposed on what processes can read and write. We present a sound and complete algorithm for high atomicity programs and a sound algorithm for distributed programs. We also argue that our algorithms are simpler than previous algorithms, where masking fault-tolerance is added to a fault-intolerant program. Hence, these algorithms can partially reap the benefits of automation when the cost of adding masking fault-tolerance to a fault-intolerant program is high. To illustrate these algorithms, we show how the masking fault-tolerant programs for triple modular redundancy and Byzantine agreement can be obtained by enhancing the fault-tolerance of the corresponding nonmasking versions. We also discuss how the derivation of these programs is simplified when we begin with a nonmasking fault-tolerant program.

关键词： Fault tolerance Safety Fault tolerant systems software engineering Laboratories computer science Automation Costs Redundancy engineering profession

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Attribute reduction of rough sets in mining market value functions

Attribute reduction of rough sets in mining market value fun...

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IEEE/WIC International Conference on Web Intelligence, WI 2003

作者： Huang, Jiajin Liu, Chunnian Ou, Chuangxin Yao, Y.Y. Zhong, N. Mutimedia and Intelligent Software Technology Beijing Municipal Key Laboratory Beijing University of Technology Beijing China Department of Computer Science University of Regina ReginaSKS4S 0A2 Canada Department of Information Engineering Macbashi Institute of Technology Maebashi-City371-0816 Japan

ISBN: (纸本)0769519326

The linear model of market value functions is a new method for direct marketing. Just like other methods in direct marketing, attribute reduction is very important to deal with large databases. We apply the algorithm of attribute reduction, which is based on the combination of rough set theory with the boosting algorithm, to the linear model of market value functions. Experimental results compared with the ELSA/ANN model show that the proposed algorithms can be used effectively in the linear model of market value functions. © 2003 IEEE.

关键词： Data mining

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Ensemble neural network methods for satellite-derived estimation of chlorophyll /spl alpha/

Ensemble neural network methods for satellite-derived estima...

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International Joint Conference on Neural Networks (IJCNN)

作者： W.H. Slade R.L. Miller H. Ressom P. Natarajan Department of Electrical and Computer Engineering Intelligent Systems Laboratory University of Maine Orono ME USA Earth Science Applications Directorate Stennis Space Centet NASA MS USA

In this paper, neural network-based methods incorporating ensemble learning techniques are presented that estimate chlorophyll /spl alpha/ (chl /spl alpha/) concentration in the coastal waters of the Gulf of Maine (GOM). A dataset was constructed consisting of in situ chl measurements from the GOM matched with satellite data from the sea-viewing wide-field-of-view sensor (SeaWiFS). These data were used to develop models using diverse neural network ensembles for estimation of chl /spl alpha/ concentration from satellite-retrieved ocean reflectances. Results indicate that the models are able to generalize across geographical and temporal variation, and are resilient to uncertainty such as that introduced by poor atmospheric correction, or radiance contributions from non-chl /spl alpha/ components in case 2 waters.

关键词： Neural networks Oceans Biomedical optical imaging Optical network units Optical sensors Sea measurements Atmospheric modeling Uncertainty Water Sea surface

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Online recommendation based on customer shopping model in e-commerce 03

Online recommendation based on customer shopping model in e-...

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IEEE WIC ACM International Conference on Web Intelligence (WI)

作者： Junzhong Ji Zhiqiang Sha Chunnian Liu Ning Zhong College of Computer Science and Technology Beijing Municipal Key Laboratory of Multimedia and Intelligent Software Technology Beijing University of Technology Beijing China Department of Information Engineering Maebashi Institute of Technology Maebashi Japan

ISBN: (纸本)0769519326

As e-commerce developing rapidly, it is becoming a research focus about how to capture or find customer's behavior patterns and realize commerce intelligence by use of Web mining technology. Recommendation system in electronic commerce is one of the successful applications that are based on such mechanism. We present a new framework in recommendation system by finding customer model from business data. This framework formalizes the recommending process as knowledge representation of the customer shopping information and uncertainty knowledge inference process. In our approach, we firstly build a customer model based on Bayesian network by learning from customer shopping history data, then we present a recommendation algorithm based on probability inference in combination with the last shopping action of the customer, which can effectively and in real time generate a recommendation set of commodity.

关键词： Data mining Business Knowledge representation Collaboration Web mining Uncertainty Bayesian methods History Inference algorithms Filtering

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XML and the semantic web: What is the future?

Proceedings of the 36th Annual Hawaii International Conferen...

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Proceedings of the 36th Annual Hawaii International Conference on System sciences, HICSS 2003 2003年 123-124页

作者： Chen, P. Bryan, George Vouk, Mladen Potok, Thomas E. Elmore, Mark Department of Computer Science Louisiana State University United States Centre for Advanced Systems Engineering University of Western Sydney Australia Department of Computer Science North Carolina State University United States Applied Software Engineering Research Group Oak Ridge National Laboratory United States

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An optimization framework for dynamic, distributed real-time systems

An optimization framework for dynamic, distributed real-time...

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International Symposium on Parallel and Distributed Processing (IPDPS)

作者： K. Ecker D. Juedes L. Welch D. Chelberg C. Bruggeman F. Drews D. Fleeman D. Parrott B. Pfarr Department of Computer Science Technical University of Clausthal-Zellerfeld Clausthal-Zellerfeld Germany Center for Intelligent Distributed and Dependable Systems School of Electrical Engineering and Computer Science Ohio University Athens OH USA Real-Time Software Engineering Branch NASA Goddard Space Flight Center Baltimore MD USA

The paper presents a model that is useful for developing resource allocation algorithms for distributed real-time systems that operate in dynamic environments. Interesting aspects of the model include dynamic environments, utility and service levels, which provide a means for graceful degradation in resource-constrained situations and support optimization of the allocation of resources. The paper also provides an allocation algorithm that illustrates how to use the model for producing feasible, optimal resource allocations.

关键词： Real time systems Resource management NASA Satellites computer networks Space technology Geoscience computer science Sensor arrays Instruments

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Attribute reduction of rough sets in mining market value functions 03

Attribute reduction of rough sets in mining market value fun...

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IEEE WIC ACM International Conference on Web Intelligence (WI)

作者： Jiajin Huang Chunnian Liu Chuangxin Ou Y.Y. Yao N. Zhong Mutimedia and Intelligent Software Technology Beijing Municipal Key Laboratory Beijing University of Technology Beijing China Department of Computer Science University of Regina Regina SAS Canada Department of Information Engineering Macbashi Institute of Technology Maebashi Japan

ISBN: (纸本)9780769519326

关键词： Rough sets Set theory Databases Entropy Laboratories computer science Boosting Internet Data mining Predictive models

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Automatic face region tracking for highly accurate face recognition in unconstrained environments

Automatic face region tracking for highly accurate face reco...

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IEEE Conference on Advanced Video and Signal Based Surveillance (AVSS)

作者： Y.-O. Kim J. Paik Jingu Heo A. Koschan B. Abidi M. Abidi Korea Electronics and Technology Institute Puchon Gyeonggi South Korea Image Processing Laboratory Department of Image Engineering Graduate School of Advanced Imaging Science Multimedia and Film Chung-Ang University Seoul South Korea Imaging Robotics and Intelligent Systems Laboratory Department of Electrical and Computer Engineering University of Tennessee Knoxville USA

We present a combined real-time face region tracking and highly accurate face recognition technique for an intelligent surveillance system. High-resolution face images are very important to achieving accurate identification of a human face. Conventional surveillance or security systems, however, usually provide poor image quality because they use only fixed cameras to record scenes passively. We have implemented a real-time surveillance system that tracks a moving face using four pan-tilt-zoom (PTZ) cameras. While tracking, the region-of-interest (ROI) can be obtained by using a low-pass filter and background subtraction with the PTZ. Color information in the ROI is updated to extract features for optimal tracking and zooming. FaceIt/sup /spl reg//, which is one of the most popular face recognition software packages, is evaluated and then used to recognize the faces from the video signal. Experimentation with real human faces showed highly acceptable results in the sense of both accuracy and computational efficiency.

关键词： Face recognition Surveillance Real time systems Humans Cameras intelligent systems Security Image quality Layout Low pass filters

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