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Adaptive smooth multicast protocol for multimedia data transmission

Adaptive smooth multicast protocol for multimedia data trans...

引用

International Symposium on Performance Evaluation of computer & Telecommunication Systems SPECTS

作者： Christos Bouras Apostolos Gkamas Georgios Kioumourtzis Research Academic Computer Technology Institute University of Patras Rion Greece Research Unit 6 Research Academic Computer Technology Institute Patras Greece Department of Telecommunications Science and Technology of Peloponnesus University of Greece Rion Greece Computer Engineering and Informatics Department University of Patras Rion Greece

ISBN: (纸本)9781424434497

We introduce Adaptive Smooth Multicast Protocol (ASMP), for multimedia transmission over best-effort networks. The smoothness lays in the calculation and adaptation of the transmission rate, which is based on dynamic estimation of protocol parameters and dynamic adjustment of the ldquosmoothness factorrdquo. ASMP key attributes are: (a) adaptive scalability to large sets of receivers, (b) TCP-friendly behavior, (c) high bandwidth utilization, and finally (d) smooth transmission rates, which are suitable for multimedia applications. We evaluate the performance of ASMP and investigate its behavior under various network conditions through extensive simulations, conducted with the network simulator software (ns2).

关键词： Multicast protocols Data communication Bandwidth Scalability Transport protocols Telecommunication computing Application software informatics Paper technology Streaming media

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New architectures for optical packet switching using QD-SOAs for multi-wavelength buffering

New architectures for optical packet switching using QD-SOAs...

引用

IEEE Workshop on High Performance Switching and Routing

作者： Kyriakos Vlachos Wojciech Kabacinski Slawomir Weclewski LComputer Engineering & Informatics Department and Research Academic Computer Technology Institute University of Patras Rio Greece Poznan University of Technology Poland

We present two architectures for implementing optical buffers. Both use multi-wavelength selective elements like quantum dot semiconductor optical amplifiers (QD-SOAs) as multi-wavelength converters and fixed-length delay lines that are combined to form both an output queuing and a parallel buffer switch design. The output queuing buffer design requires less active devices (QD-SOA) when implementing large buffers, but the parallel buffer design becomes more profitable, when the number of wavelength channels that can be simultaneously processed by the wavelength selective switches (QD-SOAs) increases. This is because the number of active devices depends only on the buffer size. We also proposed scheduling algorithm to resolve packet contention in parallel buffer architecture and carried out a simulation considering mean packet delay, maximum buffer occupancy and packet loss probability.

关键词： Optical packet switching Optical buffering Optical switches Delay lines Optical wavelength conversion Feedforward systems Dairy products Optical fiber networks Quantum dots Scheduling algorithm

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The effect of background knowledge in graph-based learning in the chemoinformatics domain

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作者： Karunaratne, Thashmee Boström, Henrik Department of Computer and Systems Sciences Stockholm University Royal Institute of Technology SE-164 40 Kista Sweden Skövde Cognition and Artificial Intelligence Lab School of Humanities and Informatics University of Skövde SE-541 28 Skövde Sweden

ISBN: (纸本)9780387749341

Typical machine learning systems often use a set of previous experiences (examples) to learn concepts, patterns, or relations hidden within the data [1]. Current machine learning approaches are challenged by the growing size of the data repositories and the growing complexity of those data [1, 2]. In order to accommodate the requirement of being able to learn from complex data, several methods have been introduced in the field of machine learning [2]. Based on the way the input and resulting hypotheses are represented, two main categories of such methods exist, namely, logic-based and graph-based methods [3]. The demarcation line between logic- and graph-based methods lies in the differences of their data representation methods, hypothesis formation, and testing as well as the form of the output produced. The main purpose of our study is toinvestigate the effect of incorporating background knowledge into graph learning methods. The ability of graph learning methods to obtain accurate theories with a minimum of background knowledge is of course a desirable property, but not being able to effectively utilize additional knowledge that is available and has been proven important is clearly a disadvantage. Therefore we examine how far additional, already available, background knowledge can be effectively used for increasing the performance of a graph learner. Another contribution of our study is that it establishes a neutral ground to compare classiffication accuracies of the two closely related approaches, making it possible to study whether graph learning methods actually would outperform ILP methods if the same background knowledge were utilized [9]. The rest of this chapter is organized as follows. The next section discusses related work concerning the contribution of background knowledge when learning from complex data. Section 10.3 provides a description of the graph learning method that is used in our study. The experimental setup, empirical evaluation, and the res

关键词： Learning systems

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Fuzzy Fusion for Affective State Assessment in Distance Learning Based on Image Detection

Fuzzy Fusion for Affective State Assessment in Distance Lear...

引用

2008 International Conference on Audio，Language and Image Processing(2008国际声音、语言、图像过程大会)

作者： Kuoan Hwang Chiahao Yang Department of Computer Science and Information Engineering & Graduate Institute of Networking and Co Graduate Institute of Informatics Doctoral program Chaoyang University of Technology

Distance learning is a learning style that can overcome the limitation of time and space. Because of the distance, teachers can not handle the student's learning situation, and they do not know whether the student is attentive, drowsy or absent. If teachers can know the student's affective state, they can overcome the difficult. The research applies the image recognition technologies to capture the face images of students when they are learning and analyzes their face features to evaluate the student's affective state by Fuzzy Integral. Finally, teachers can monitor the student's behavior by the detection results on the system interface.

关键词： Distance learning Skin computers Distance measurement Face Image color analysis Education

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Performance study of the Mobile IPv6 protocol and its variations

Performance study of the Mobile IPv6 protocol and its variat...

引用

International Symposium on Communication Systems, Networks and Digital Signal Processing, CNSDSP

作者： George Aristomenopoulos Christos Bouras Kostas Stamos Computer Engineering and Informatics Department University슠of슠Patras Greece Computer Engineering and Informatics Department University of Patras Patras Greece Research Academic Computer Technology Institute N.Kazantzaki Str. Patras Univ. GR-26500 Rion Greece

In this paper, we use the OMNET++ simulator in order to evaluate the performance of the basic mobile IPv6 protocol and some of its proposed variations. The most important metric we are interested in is the handover latency, which is measured for various combinations of the proposed mobile IPv6 variations and then this metric is used, combined with factors such as the complexity of the implementation, in order to evaluate and identify the best possible configuration for the operation of the protocol.

关键词： Mobile communication Manganese Protocols Mobile computing Internet Force Object oriented modeling

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Local peculiarity factor and its application in outlier detection

Local peculiarity factor and its application in outlier dete...

引用

14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2008

作者： Yang, Jian Zhong, Ning Yao, Yiyu Wang, Jue International WIC Institute Key Laboratory of Multimedia and Intelligent Software Beijing University of Technology Beijing 100124 China Department of Life Science and Informatics Maebashi Institute of Technology Maebashi-City 371-0816 Japan Department of Computer Science University of Regina Regina S4S 0A2 Canada Institute of Automation Chinese Academy of Sciences Beijing 100196 China

ISBN: (纸本)9781605581934

Peculiarity oriented mining (POM), aiming to discover peculiarity rules hidden in a dataset, is a new data mining method. In the past few years, many results and applications on POM have been reported. However, there is still a lack of theoretical analysis. In this paper, we prove that the peculiarity factor (PF), one of the most important concepts in POM, can accurately characterize the peculiarity of data with respect to the probability density function of a normal distribution, but is unsuitable for more general distributions. Thus, we propose the concept of local peculiarity factor (LPF). It is proved that the LPF has the same ability as the PF for a normal distribution and is the so-called ν-sensitive peculiarity description for general distributions. To demonstrate the effectiveness of the LPF, we apply it to outlier detection problems and give a new outlier detection algorithm called LPF-Outlier. Experimental results show that LPF-Outlier is an effective outlier detection algorithm. © 2008 ACM.

关键词： Data mining

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biTemporal Session Reconstruction for Visited Sessions Retrieval

biTemporal Session Reconstruction for Visited Sessions Retri...

引用

International Conference on Information Visualisation (IV)

作者： Ahmed Aburodes Assaid Elkilany Ilias Petrounias Department of Computer Science Sebha University Sebha Libya School of Informatics University of Manchester Institute of Science and Technology Manchester UK

Web mining is an intensive task which may yield significant insights that may revolutionise business and marketing by using effective information distribution, entertainment and communication techniques. For instance, corporations can optimise their eCommerce Websites to maximize impact and personalise the online content of their Websites. Corporations can use Web mining techniques for better understanding about their customers and thus will gain competitive edge by delivering the right information and services. This paper concentrates on reconstruction of visited session which was recorded in a Web log server. Existing approaches for reconstruction of users' session deal only with the time when a user accesses every page, whereas, in this paper, each visited page is incorporated with a pair of ordered time points, which we call biTemporal. Re-produced sessions can be used latter in different ways such as personalization, sequential pattern discovery, etc.

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Gait authentication using distributed source coding

Gait authentication using distributed source coding

引用

IEEE International Conference on Image Processing

作者： S. Argyropoulos D. Tzovaras D. Ioannidis M. G. Strintzis Informatics and Telematics Institute Centre for Research and Technology Hellas Greece Department of Electrical and Computer Engineering Aristotle University of Thessaloniki Greece

A novel gait authentication scheme based on distributed source coding principles is proposed. Biometric recognition is formulated as a coding problem with noisy side information at the decoder and error correcting codes are employed for user authentication. The effective exploitation of the noise channel statistics in the decoding process improves performance. It is also shown that the proposed method increases the security of the stored biometric templates. Gait recognition is based on the extraction of depth data from human silhouettes and a set of discriminative features. The experimental results demonstrate the validity of the proposed method.

关键词： Authentication Source coding Biometrics Decoding Error correction codes Statistical distributions Data security Information security Data mining Humans

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Steganalysis of multi-class JPEG images based on expanded Markov features and polynomial fitting

Steganalysis of multi-class JPEG images based on expanded Ma...

引用

International Joint Conference on Neural Networks (IJCNN)

作者： Qingzhong Liu Andrew H. Sung Bernardete M. Ribeiro Rita Ferreira Computer Science Department of New Mexico Institute of Mining and Technology Institute for Complex Additive Systems Analysis USA Computer Science Department of New Mexico Institute of Mining and Technology Institute for Complex Additive Systems Analysis Socorro NM USA Department of Informatics Engineering University of Coimbra Portugal

In this article, based on the Markov approach proposed by shi et al. , we expand it to the inter-blocks of the DCT domain, calculate the difference of the expanded Markov features between the testing image and the calibrated version, and combine these difference features and the polynomial fitting features on the histogram of the DCT coefficients as detectors. We reasonably improve the detection performance in multi-class JPEG images. We also compare the steganalysis performance among the feature reduction/selection methods based on principal component analysis, singular value decomposition, and Fisherpsilas linear discriminant.

关键词： Feature extraction Transform coding Discrete cosine transforms Testing Polynomials Kernel Artificial neural networks

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Building resilient classifiers for LSB matching steganography

Building resilient classifiers for LSB matching steganograph...

引用

International Joint Conference on Neural Networks (IJCNN)

作者： Rita Ferreira Bernardete Ribeiro Catarina Silva Qingzhong Liu Andrew H. Sung Department of Informatics Engineering CISUC University of Coimbra Portugal School of Technology and Management Polytechnic Institute of Leiria Portugal Department of Computer Science New Mexico Technology USA

One of the Internetpsilas hallmark is the rapid spread of the use of information and communication technology. This has boosted methods for hiding stego information inside digital cover content images which is a concerning issue in information security. On the other hand, attack of steganographic schemes has leveraged methods for steganalysis which is a challenging problem. In this paper, first we look at the design of classifiers, such as, support vector machines (SVM) and neural networks (RBF and MLP) which are able to detect the presence of least significant bit (LSB) matching steganography of gray scale images. Second, by combining with feature ranking methods (SVM-recursive feature elimination, Kruskal Wallis) and reduction techniques (PCA) pattern classification of stego is successfully achieved. It is of utmost importance to look at the large set of features extracted from images and find ranking methods able, namely, to exclude correlated and redundant features, avoid the curse of dimensionality or circumvent the need of the steganalyzer to be re-designed. Results show that desirable properties of robustness and resilience are attained by designing classifiers able to deal with redundancy and noise. Moreover, comparison of classifiers performance emphasizes the chosen model for the steganalyser.

关键词： Support vector machines Complexity theory Principal component analysis Artificial neural networks Feature extraction Kernel Training

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