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检索条件"机构=Multimedia InfoRmation System and Advanced Computing Laboratory"

共 259 条记录，以下是251-260 订阅

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Parallel Multi-Objective Evolutionary Algorithm with Multi-Front Equitable Distribution

Parallel Multi-Objective Evolutionary Algorithm with Multi-F...

引用

International Conference on Grid and Cooperative computing (GCC)

作者： Abdelbasset Essabri Mariem Gzara Taicir Loukil Laboratoire de Gestion Industrielle et d’Aide à la Décision (GIAD) Sfax Tunisia Multimedia Information Systems and Advanced Computing Laboratory Sfax Tunisia

In multi-objective context, the evolutionary approach offers specific mechanisms such as Pareto selection, elitism and diversification. These techniques are proved to be efficient to characterize the Pareto front. However, their high computing time constitutes a major handicap for their expansion. The parallelization of multi-objective evolutionary algorithms (MOEAs) may be an efficient way to overcome this problem. This parallelization aims not only to achieve time saving by distributing the computational effort but also to get benefit from the algorithmic aspect by the cooperation between different populations and evolutionary schemes. In this paper we propose a new parallel multi-objective evolutionary algorithm with multi-front equitable distribution which is based on an elitist technique. Every population evolves differently on a processor and cooperates with the others to preserve genetic diversity and to obtain a set of diversified non dominated solutions

关键词： Evolutionary computation Genetic algorithms Concurrent computing Master-slave Distributed computing Parallel processing Computer industry multimedia systems multimedia computing information systems

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A Tamper-resistance Key Pre-distribution Scheme for Wireless Sensor Networks

A Tamper-resistance Key Pre-distribution Scheme for Wireless...

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International Conference on Grid and Cooperative computing Workshops (GCCW)

作者： Lei Xie Hongsong Zhu Yongjun Xu Yuefei Zhu Institute of Information Engineering Information and Engineering University Zhengzhou China Advanced Test Technology Laboratory Key Laboratory of Computer System and Architecture Institute of Computing Technology Chinese Academy and Sciences Beijing China

Wireless sensor network (WSN), which is integrated with many technologies such as sensor, embedded computing, wireless communication and distributed information processing etc., is becoming an important branch of ubiquitous computing research. WSN is composed of a large number of distributed sensor nodes, so to ensure the sensor nodes dependable is essential to security of whole network. By introducing a lightweight tamper-resistance design based on security co-processor into sensor nodes, this paper loosens up the security assumptions of WSN, and redefines the objectives of WSN security. Based on such secure infrastructure, the paper also proposes a concise and effective key pre-distribution scheme, in which each node needs to send only one cluster key announcement message and cluster key net can be set up within neighborhood

关键词： Wireless sensor networks Pervasive computing Ubiquitous computing information security Computer networks Computer architecture Sensor arrays Design engineering Laboratories Embedded computing

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Collateral Representative Subspace Projection Modeling for Supervised Classification

Collateral Representative Subspace Projection Modeling for S...

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International Conference on Tools for Artificial Intelligence (ICTAI)

作者： Thiago Quirino Zongxing Xie Mei-ling Shyu Shu-ching Chen Liwu Chang Department of Electrical and Computer Engineering University of Miami Coral Gables FL USA Distributed Multimedia Information System Laboratory School of Computing and Information Sciences Florida International University Miami FL USA Naval Research Laboratory Center for High Assurance Computer Systems Washington D.C. USA

In this paper, a novel supervised classification approach called collateral representative subspace projection modeling (C-RSPM) is presented. C-RSPM facilitates schemes for collateral class modeling, class-ambiguity solving, and classification, resulting a multi-class supervised classifier with high detection rate and various operational benefits including low training and classification times and low processing power and memory requirements. In addition, C-RSPM is capable of adaptively selecting nonconsecutive principal dimensions from the statistical information of the training data set to achieve an accurate modeling of a representative subspace. Experimental results have shown that the proposed C-RSPM approach outperforms other supervised classification methods such as SIMCA, C4.5 decision tree, decision table (DT), nearest neighbor (NN), KNN, support vector machine (SVM), I-NN best warping window DTW, I-NN DTW with no warping window, and the well-known classifier boosting method AdaBoost with SVM

关键词： Principal component analysis Support vector machines Support vector machine classification Intrusion detection Training data Classification tree analysis Bayesian methods Laboratories Distributed computing Power system modeling

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An Integrated and Interactive Video Retrieval Framework with Hierarchical Learning Models and Semantic Clustering Strategy

An Integrated and Interactive Video Retrieval Framework with...

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IEEE International Conference on information Reuse and Integration (IRI)

作者： Na Zhao Shu-ching Chen Mei-ling Shyu Stuart H. Rubin Distributed Multimedia Information System Laboratory School of Computing and Information Sciences Florida International University Miami FL USA Department of Electrical and Computer Engineering University of Miami Coral Gables FL USA Space and Naval Warfare Systems Command San Diego CA USA

In this research, we propose an integrated and interactive framework to manage and retrieve large scale video archives. The video data are modeled by a hierarchical learning mechanism called HMMM (hierarchical Markov model mediator) and indexed by an innovative semantic video database clustering strategy. The cumulated user feedbacks are reused to update the affinity relationships of the video objects as well as their initial state probabilities. Correspondingly, both the high level semantics and user perceptions are employed in the video clustering strategy. The clustered video database is capable of providing appealing multimedia experience to the users because the modeled multimedia database system can learn the user's preferences and interests interactively

关键词： multimedia databases Hidden Markov models information retrieval multimedia systems Large scale integration Learning systems Clustering methods Clustering algorithms Feedback Content based retrieval

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UNPCC: A Novel Unsupervised Classification Scheme for Network Intrusion Detection

UNPCC: A Novel Unsupervised Classification Scheme for Networ...

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International Conference on Tools for Artificial Intelligence (ICTAI)

作者： Zongxing Xie Thiago Quirino Mei-ling Shyu Shu-ching Chen Liwu Chang Department of Electrical and Computer Engineering University of Miami Coral Gables FL USA Distributed Multimedia Information System Laboratory School of Computing and Information Sciences Florida International University Miami FL USA Center for High Assurance Computer Systems Naval Research Laboratory Washington D.C. DC USA

The development of effective classification techniques, particularly unsupervised classification, is important for real-world applications since information about the training data before classification is relatively unknown. In this paper, a novel unsupervised classification algorithm is proposed to meet the increasing demand in the domain of network intrusion detection. Our proposed UNPCC (unsupervised principal component classifier) algorithm is a multiclass unsupervised classifier with absolutely no requirements for any a priori class related data information (e.g., the number of classes and the maximum number of instances belonging to each class), and an inherently natural supervised classification scheme, both which present high detection rates and several operational advantages (e.g., lower training time, lower classification time, lower processing power requirement, and lower memory requirement). Experiments have been conducted with the KDD Cup 99 data and network traffic data simulated from our private network testbed, and the promising results demonstrate that our UNPCC algorithm outperforms several well-known supervised and unsupervised classification algorithms

关键词： Intrusion detection Classification algorithms Clustering algorithms Computer networks Distributed computing Laboratories Training data Traffic control Testing Machine learning algorithms

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Hybrid Evolutionary Algorithm With Insertion Heuristics For The Flexible Job Shop Problem

Hybrid Evolutionary Algorithm With Insertion Heuristics For ...

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International Conference on Services systems and Services Management, ICSSSM

作者： Fredj Neifar Mariem Gzara Aziz Moukrim Taicir Loukil Multimedia Information Systems and Advanced Computing Laboratory Sfax Tunisia Centre de Recherches de Royallieu UTC Laboratoire Heudiasyc Compiegne France Laboratoire de Gestion industrielle et Aide à la Décision (GIAD) Sfax Tunisia

This paper presents a hybrid evolutionary algorithm for the flexible job shop problem. We developed and tested new genetic operators. Insertion heuristics have been incorporated into crossover and mutation operators in order to enhance the performance of the genetic search. The approach is tested on a set of standard instances taken from the literature. The empirical experiments are promising and validate the effectiveness of the proposed algorithm

关键词： Evolutionary computation Job shop scheduling Testing information systems Laboratories Computer industry Genetic mutations NP-hard problem Constitution

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Neural network based framework for goal event detection in soccer videos

Neural network based framework for goal event detection in s...

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Seventh IEEE International Symposium on multimedia, ISM 2005

作者： Wickramaratna, Kasun Chen, Min Chen, Shu-Ching Shyu, Mei-Ling Distributed Multimedia Information System Laboratory School of Computing and Information Sciences Florida International University Miami FL 33199 United States Department of Electrical and Computer Engineering University of Miami Coral Gables FL 33124 United States

ISBN: (纸本)0769524893

In this paper, a neural network based framework for semantic event detection in soccer videos is proposed. The framework provides a robust solution for soccer goal event detection by combining the strength of multimodal analysis and the ability of neural network ensembles to reduce the generalization error. Due to the rareness of the goal events, the bootstrapped sampling method on the training set is utilized to enhance the recall of goal event detection. Then a group of component networks are trained using all the available training data. The precision of the detection is greatly improved via the following two steps. First, a pre-filtering step is employed on the test set to reduce the noisy and inconsistent data, and then an advanced weighting scheme is proposed to intelligently traverse and combine the component network predictions by taking into consideration the prediction performance of each network. A set of experiments are designed to compare the performance of different bootstrapped sampling schemes, to present the strength of the proposed weighting scheme in event detection, and to demonstrate the effectiveness of our framework for soccer goal event detection. © 2005 IEEE.

关键词： multimedia systems

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Neural network based framework for goal event detection in soccer videos

Neural network based framework for goal event detection in s...

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IEEE International Symposium on multimedia

作者： K. Wickramaratna Min Chen Shu-Ching Chen Mei-Ling Shyu Distributed Multimedia Information System Laboratory School of Computing and Information Sciences Florida International University Miami FL USA Department of Electrical and Computer Engineering University of Miami Coral Gables FL USA

关键词： Neural networks Event detection Intelligent networks Videos Hidden Markov models Robustness Sampling methods Feature extraction multimedia systems multimedia computing

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Web-Age information Management 1

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丛书名： Lecture Notes in Computer Science

1000年

作者： Yunjun Gao Kyuseok Shim Zhiming Ding Peiquan Jin Zujie Ren Yingyuan Xiao An Liu Shaojie Qiao

ISBN: (数字)9783642395277

ISBN: (纸本)9783642395260

This book constitutes the refereed proceedings of six workshops of the 14th International Conference on Web-Age information Management, WAIM 2013, held in Beidaihe, China, June 2013. The 37 revised full papers are organized in topical sections on the six following workshops: The International Workshop on Big Data Management on Emerging Hardware (HardBD 2013), the Second International Workshop on Massive Data Storage and Processing (MDSP 2013), the First International Workshop on Emergency Management in Big Data Age (BigEM 2013), the International Workshop on Trajectory Mining in Social Networks (TMSN 2013), the First International Workshop on Location-based Query Processing in Mobile Environments (LQPM 2013), and the First International Workshop on Big Data Management and Service (BDMS 2013).

关键词： information Storage and Retrieval information systems Applications (incl. Internet) Data Mining and Knowledge Discovery Database Management Computer Communication Networks Algorithm Analysis and Problem Complexity

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