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检索条件"机构=Multimedia Information Systems and Advanced Computing Laboratory"

共 503 条记录，以下是351-360 订阅

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Particle swarm optimization for support vector clustering Separating hyper-plane of unlabeled data

Particle swarm optimization for support vector clustering Se...

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International Conference on Modeling, Simulation and Applied Optimization

作者： Souad CHAABOUNI Salma JAMMOUSSI Yassine BENAYED Multimedia InfoRmation systems and Advanced Computing Laboratory MIRACL. SFAX University

ISBN: (纸本)9781467358125

The objective of this work is to design a new method to solve the problem of integrating the Vapnik theory, as regards support vector machines, in the field of clustering data. For this we turned to bio-inspired meta-heuristics. Bio-inspired approaches aim to develop models resolving a class of problems by drawing on patterns of behavior developed in ethology. For instance, the Particle Swarm Optimization (PSO) is one of the latest and widely used methods in this regard. Inspired by this paradigm we propose a new method for clustering. The proposed method PSvmC ensures the best separation of the unlabeled data sets into two groups. It aims specifically to explore the basic principles of SVM and to combine it with the meta-heuristic of particle swarm optimization to resolve the clustering problem. Indeed, it makes a contribution in the field of analysis of multivariate data. Obtained results present groups as homogeneous as possible. Indeed, the intra-class value is more efficient when comparing it to those obtained by Hierarchical clustering, Simple K-means and EM algorithms for different database of benchmark.

关键词： Support Vector Machines Clustering Particle Swarm Optimization

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Translating verbs between MSA and arabic dialects through deep morphological analysis 20

Translating verbs between MSA and arabic dialects through de...

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20e Conference Traitement Automatique des Langues Naturelles et la 15e Rencontres des Etudiants Chercheurs en Informatique pour le Traitement Automatique des Langues, TALN-RECITAL 2013 - 20th Conference on Automatic Natural Language Processing and the 15th Meeting of Computer Science Student Researchers for Natural Language Processing, TALN-RECITAL 2013

作者： Hamdi, Ahmed Boujelbane, Rahma Habash, Nizar Nasr, Alexis Laboratoire d'Informatique Fondamentale de Marseille CNRS UMR 7279 Université Aix Marseille France Multimedia InfoRmation Systems and Advanced Computing Laboratory Sfax3021 Tunisia Center for Computational Learning Systems Columbia University New York NY10115 United States

The developpment of NLP tools for dialects faces the severe problem of lack of resources for such dialects. In the case of diglossia, as in arabic, a variant of arabic, Modern Standard Arabic, exists, for which many resources have been developped which can be used to build NLP tools. Taking advantage of the closeness of MSA and dialects, one way to solve the problem consist in performing a surfacic translation of the dialect into MSA in order to use the tools developped for MSA. We describe in this paper an achitecture for such a translation and we evaluate it on arabic verbs. © ATALA.

关键词： Natural language processing systems

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Arabic text to speech synthesis based on neural networks for MFCC estimation

Arabic text to speech synthesis based on neural networks for...

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World Congress on Computer and information Technology (WCCIT)

作者： Ilyes Rebai Yassine BenAyed Multimedia Information system and Advanced Computing Laboratory Sfax University Sfax Tunisia

ISBN: (纸本)9781479904617

With the increasing number of users of text to speech applications, high quality speech synthesis is required. However, only few researches concern Arabic text to speech applications. Compared with other languages such as English and French the quality of Arabic synthesis speech is still poor. For these reasons, we propose in this paper an Arabic text to speech synthesis system based on statistical parametric synthesis. Mel Frequency Cepstral Coefficients (MFCC), energy and pitch are predicted using back propagation artificial neural networks and then transformed into speech using Mel Log Spectrum Approximation filter. Often, in Arabic written text, the short vowels called diacritic marks are omitted. So, a diacritization system is proposed to resolve this problem. Different unit sizes are considered in speech database which are phoneme, diphone and triphone. MFCC neural network architecture and an objective evaluation with the MFCC distortion measure are given in this paper.

关键词： Speech Feature extraction Speech synthesis Mel frequency cepstral coefficient Artificial neural networks Databases Biological neural networks

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A WAN-optimized live storage migration mechanism toward virtual machine evacuation upon severe disasters

A WAN-optimized live storage migration mechanism toward virt...

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作者： Hirofuchi, Takahiro Tsugawa, Maurido Nakada, Hidemoto Kudoh, Tomohiro Itoh, Satoshi Information Technology Research Insti-tute National Institute of Science Technology Tsukuba-shi Japan Advanced Computing Information Systems Laboratory University of Florida Gainesville FL 32611 United States

Wide-area VM migration is a technology with potential to aid IT services recovery since it can be used to evacuate virtualized servers to safe locations upon a critical disaster. However, the amount of data in-volved in a wide-area VM migration is substantially larger compared to VM migrations within LAN due to the need to transfer virtualized storage in addition to memory and CPU states. This increase of data makes it chal-lenging to relocate VMs under a limited time window with electrical power. In this paper, we propose a mechanism to improve live storage migration across WAN. The key idea is to reduce the amount of data to be trans-ferred by proactively caching virtual disk blocks to a backup site during regular VM operation. As a result of pre-cached disk blocks, the proposed mechanism can dramatically reduce the amount of data and consequently the time required to live migrate the entire VM state. The mechanism was evaluated using a prototype implementation under different workloads and network conditions, and we confirmed that it dramatically reduces the time to complete a VM live migration. By using the proposed mechanism, it is possible to relocate a VM from Japan to the United States in just under 40 seconds. This relocation would otherwise take over 1500 seconds, demon-strating that the proposed mechanism was able to reduce the migration time by 97.5%. © 2013 The Institute of Electronics, information and Communication Engineers.

关键词： Virtual machine

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Weighted committee-based structure learning for microarray data

Weighted committee-based structure learning for microarray d...

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IEEE Symposium on Bioinformatics and Bioengineering (BIBE)

作者： Hasna Njah Salma Jamoussi Multimedia InfoRmation Systems and Advanced Computer Laboratory (MIRACL) Sfax University Tunisia

Bayesian networks (BN) are considered to be one of the strongest modeling techniques of gene regulatory networks (GRN) thanks to their ability to present features and relations between them in a causal and probabilistic way. Learning the structure of those models needs a large training dataset in order to avoid over-fitting. However, biological data, especially microarray data, suffer from the presence of only few instances. Some recent approaches tried to face this challenge by applying committee based methods. We use this principle in order to suggest a new method supported by a double-weight-assignment technique. We show that our approach has succeeded to learn benchmark structures.

关键词： Bayes methods Training Weight measurement Benchmark testing Evolutionary computation Genetics

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Hybrid SVM/HMM model for the recognition of Arabic triphones-based continuous speech

Hybrid SVM/HMM model for the recognition of Arabic triphones...

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IEEE SSD International Multi-Conference on systems, Signals and Devices

作者： Elyes Zarrouk Yassine Benayed Faïez Gargouri MIRACL Multimedia InfoRmation system and Advanced Computing Laboratory Higher Institute of Computer Science and Multimedia ISIMS University of Sfax Tunisia

ISBN: (纸本)9781467364591

Even if the progress of Hidden Markov Models (HMM) is huge, those models lack a discriminatory ability especially on speech recognition. In order to ameliorate the results of recognition systems, we apply Support Vectors Machine (SVM) as an estimator of posterior probabilities since they are characterized by a high predictive power and discrimination. Moreover, they are based on a structural risk minimization (SRM) where the aim is to set up a classifier that minimizes a bound on the expected risk, rather than the empirical risk. In this paper, we describe the use of the hybrid model SVM/HMM for Arabic triphones-based continuous speech. Furthermore, our work incorporates the stage of preparing language models. It consists in a novel approach for automatic labeling with respect to syntax and grammar rules of the Arabic language. The best results are obtained with the proposed system SVM/HMM when we achieve 76.96% as the best recognition rate of a tested speaker. The speech recognizer was evaluated with ARABIC_DB corpus and performs at 11.42% WER as compared to 13.32% with triphones mixture-Gaussian HMM system.

关键词： Hidden Markov models Support vector machines Speech recognition Speech Acoustics Labeling Kernel

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Particle Swarm Optimization based method for Bayesian Network Structure Learning

Particle Swarm Optimization based method for Bayesian Networ...

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International Conference on Modeling, Simulation and Applied Optimization

作者： Saoussen Aouay Salma Jamoussi Yassine Ben Ayed MIRACL Multimedia InfoRmation system and Advanced Computing Laboratory Higher Institute of Computer Science and Multimedia Sfax BP 1030 - Tunisia

ISBN: (纸本)9781467358125

Bayesian Networks (BNs) are good tools for representing knowledge and reasoning under conditions of uncertainty. In general, learning Bayesian Network structure from a data-set is considered a NP-hard problem, due to the search space complexity. A novel structure-learning method, based on PSO (Particle Swarm Optimization) and the K2 algorithm, is presented in this paper. To learn the structure of a bayesian network, PSO here is used for searching in the space of orderings. Then the fitness of each ordering is calculated by running the K2 algorithm and returning the score of the network consistent with it. The experimental results demonstrate that our approach produces better performance compared to others BN structure learning algorithms.

关键词： Bayesian Networks Particle Swarm Optimization K2 Algorithm Structure Learning

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A multidimensional heuristic for social routing in peer-to-peer networks

A multidimensional heuristic for social routing in peer-to-p...

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Consumer Communications and Networking Conference, CCNC IEEE

作者： Shuo Jia Pierre St Juste Renato J. Figueiredo Advanced Computing and Information Systems Laboratory University of Florida Gainesville FL USA

A fundamental problem encountered in designing decentralized social applications is the issue of efficiently locating target nodes in social peer-to-peer networks based on local information only. The unique “small-world” phenomenon of social networks shows that a typical pair of nodes is connected by very short chains of intermediate friends, and individuals are able to collectively discover such short paths. In this paper, we propose a decentralized algorithm that exploits this “small-world” phenomenon to discover efficient routes to reach target nodes in unstructured social overlays. In order to test the performance of this algorithm, we simulate it on a real-world social graph dataset crawled from a large online social networking website (LiveJournal). Compared with other related works, the simulation results show that our proposed decentralized social routing algorithm not only shortens the median length of the search path, but also increases the success rate of finding such routes between arbitrary pair of nodes in the LiveJournal social graph.

关键词： Routing Peer-to-peer computing Social network services Cities and towns Algorithm design and analysis Electronic mail

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Enabling decentralized microblogging through P2PVPNs

Enabling decentralized microblogging through P2PVPNs

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Consumer Communications and Networking Conference, CCNC IEEE

作者： Pierre St Juste Heungsik Eom Kyungyong Lee Renato J. Figueiredo Advanced Computing and Information Systems Laboratory University of Florida Gainesville FL USA

In the past few years, many peer-to-peer microblogging solutions have been proposed and/or implemented utilizing various technologies such as DHTs, multicast trees, and/or gossip protocols. These previous works address the issue of privacy and performance in a variety of ways including the use of session keys for message encryption or direct connections for low latency communication. We propose a decentralized microblogging service which takes advantage of available peer-to-peer virtual private networking (P2PVPN) technologies which provide privacy and low-latency communication in the common case of P2P messaging among social peers. Leveraging the private IP connectivity of P2PVPNs, our design utilizes both IP multicasting and random walks to ensure that peers are able to publish messages with varying degree of scope (i.e. friends, friends of friends, and/or the public). We study the implications of our data dissemination mechanism for a decentralized microblogging service through simulation-based analysis based on synthetic social graphs. Overall, our experimental results show that peers can effectively follow each other's updates with acceptable overhead. Through the use of our pseudo-random-walk algorithm, we estimate that, in a 900K social graph, with a TTL of 100, a user can retreive updates from anyone in the social graph 55% of the time, but by increasing the TTL to 400 that hit rate increases to 95%.

关键词： Peer-to-peer computing IP networks Multicast communication Internet Bandwidth Availability Cryptography

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A peer-to-peer microblogging service based on IP multicast and social virtual private networking

A peer-to-peer microblogging service based on IP multicast a...

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Consumer Communications and Networking Conference, CCNC IEEE

作者： Pierre St Juste Renato J. Figueiredo Advanced Computing and Information Systems Laboratory University of Florida Gainesville FL USA

Microblogging services such as Twitter have become an indispensable communication tool on the Internet. However, due to their centralized nature, microblogging services have been susceptible to blocking by governments and powerful groups. To address this issue, we present a peer-to-peer microblogging service that is resistant to government intrusions and censorship. The strength of our design lies in the fact that we leverage trusted, peer-to-peer connections for the dissemination of information. Our proposed design consists mainly of two key components: a microblogging service which uses UDP and IP multicasting to push and pull updates, and a peer-to-peer VPN (SocialVPN) which enable IP multicasting over the Internet and provide direct IP connectivity among social peers. We also implemented and deployed a prototype to show the feasibility of our approach.

关键词： IP networks Peer-to-peer computing Multicast communication Internet Virtual private networks Government Unicast

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