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2009 WRI World Congress on computer Science and Information engineering, CSIE 2009

作者： Wang, Jhing-Fa Chang, Gung-Ming Wang, Jia-Ching Lin, Shun-Chieh Department of Electrical Engineering National Cheng Kung University Tainan Taiwan Department of Electrical and Computer Engineering University of Wisconsin-Madison United States Home Network Technology Centre Industrial Technology Research Institute/South Taiwan

ISBN: (纸本)9780769535074

A stress detection based on multi-class probabilistic support vector machines (MCP-SVMs) is proposed for classifying speech into following categories - no stress, primary stress, and secondary stress. The stress classifier is performed with a feature set including perceptual features, MFCC, delta-MFCC and delta-delta-MFCC. To observe that speakers from the same accent regions had similar tendencies in mispronunciations including word stress, this work uses English Across Taiwan (EAT) to represent Taiwanese-accented English speech corpora. The overall performance in the experimental results achieves about 84% classification of accuracy. © 2008 IEEE.

关键词： Stresses

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Rural Wireless Mesh networking in Africa: An experiential study

Rural Wireless Mesh Networking in Africa: An experiential st...

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24th International Conference on computers and Their Applications 2009, CATA 2009

作者： Backens, Jonathan Song, Min Engels, Lutz Department of Electrical and Computer Engineering Old Dominion University Norfolk VA 23529 United States Network Infrastructure Design Zuyd University Heerlen Netherlands

ISBN: (纸本)9781615670147

Connecting the rural communities of the developing world remains a huge task in both the areas of adequate technology and local implementation. With widely varying topography and demographics, rural communities provide a unique challenge in connectivity that wireless communication seems destined to meet. Specifically the ubiquitous nature of wireless mesh networks (WMN) presents a theoretically plausible solution to these varying difficulties. There has been a growing interest in these unique challenges with several recent research publications on long distance links in WMN, channel allocation schemes and performance. However the current analysis and simulation based research that is the focus in most technical literature lacks the proof of concept that comes from an actual implementation. Therefore a novel approach to rural wireless connectivity is presented from an actual test case in the rural village of Macha, Zambia. Its indoor to indoor mesh network follows a realistic deployment instead of planned logical deployment strategy yet is highly functional. Areas of research arising from an actual implementation are presented with performance results of the resulting network presented.

关键词： Mesh generation

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A new fuzzing technique for software vulnerability mining

A new fuzzing technique for software vulnerability mining

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International Conference on Software engineering, CONSEG 2009

作者： Wu, Zhiyong Atwood, J. William Zhu, Xueyong Network Information Center University of Science and Technology of China Hefei Anhui China Department of Computer Science and Software Engineering Concordia University Montreal QC Canada

Test case mutation and generation (m&g) based on data samples is a n effective way to generate test cases for Knowledge-based fuzzing, but present m&g technique is only capable of one-dimensional m&g at a time based on a data sample and thus it is impossible to find a vulnerability that can only be detected by multidimensional m&g. This paper proposes a mathematical model FTSG that formally describes Fuzzing Test Suite Generation based on m&g, and can process multidimension input elements m&g, which is done by a Genetic Algorithm Mutation operator (GAMutator). By executionoriented input-output (I/O) analysis, the influence relationships between input elements and insecure functions in target application were collected. Based on these relationships, GAMutator can directly mutate corresponding input elements to trigger the suspected vulnerability in a target insecure function, which could never been found by one-dimension m&g fuzzing. Importantly, GAMutator does not bring the input combination explosion, and the number of test cases it generates is linear with the number of insecure functions. Finally, an experiment on Libpng has proved that FTSG could effectively enrich the ability of knowledge-based fuzzing technique to find vulnerabilities.

关键词： Genetic algorithms

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Video Enhancement Using a Robust Iterative SRR Based on a Geman&McClure Stochastic Estimation

Video Enhancement Using a Robust Iterative SRR Based on a Ge...

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International Conference on Signal Processing Systems, ICSPS

作者： Vorapoj Patanavijit Department of Computer and Network Engineering Faculty of Engineering Assumption University Bangkok Thailand

ISBN: (纸本)9781424442133

Most video enhancement algorithms assume that the noise model of the imaging system is known as AWGN thereby imaging process model violations often occur since the real noise model is not known in many practical applications. Robust statistics has emerged as a family of theories and techniques for estimation while dealing with deviations from the idealized model assumptions. In this paper, we propose a novel robust video enhancement algorithm using SRR (Super-Resolution Reconstruction) based on the stochastic regularization technique by minimizing a cost function. First, the registration process is used to estimate the relationship between the reference frame and other neighboring frames. Then, the Geman&McClure norm is used for measuring the difference between the projected estimate of the high quality image and each low high quality image and for removing outliers in the data. Moreover, Tikhonov regularization is incorporated in the proposed framework in order to remove artifacts from the final answer and to improve the rate of convergence. Finally, experimental results are presented to demonstrate the outstanding performance of the proposed algorithm in comparison to several previously published methods using standard sequences such as Foreman and Susie that are corrupted by several noise models such as AWGN, Poisson Noise, Salt & Pepper Noise and Speckle Noise.

关键词： Stochastic processes Additive white noise Gaussian noise Noise robustness Stochastic resonance AWGN Iterative algorithms Statistics Image reconstruction Cost function

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Effect of fabrication parameters on luminescent properties of ZnS:Mn nanocrystals

Effect of fabrication parameters on luminescent properties o...

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2009 Asia Communications and Photonics Conference and Exhibition, ACP 2009

作者： Shaari, Sahbudin Ab-Rahman, Mohd Syuhaimi Arif, Noor Azie Azura Mohd Institute of Micro Engineering and Nanoelectronics Universiti Kebangsaan Malaysia 43600 UKM Bangi Selangor Malaysia Computer and Network Security Research Group Department of Electrical Electronic and Systems Engineering 43600 UKM Bangi Selangor Malaysia

ISBN: (纸本)9781557528773

In this work, we mainly focused on the luminescence properties of ZnS:Mn nanocrystals. Various samples of ZnS:Mn have been characterized at different doping concentration, annealing temperature, speed and rotation time. Luminescent intensity increased with higher annealing temperature, doping concentration but decreased with higher speed and rotation time during stirring process. ©2009 Optical Society of America.

关键词： Zinc sulfide

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Video enhancement using a robust iterative SRR based on Andrew's Sine regularization technique

Video enhancement using a robust iterative SRR based on Andr...

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IEEE International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)

作者： Vorapoj Patanavijit Department of Computer and Network Engineering Faculty of Engineering Assumption University Bangkok Thailand

In this paper, we propose a alternative robust video enhancement algorithm using SRR based on the regularization ML technique. First, the classical registration process is used to estimate the relationship between the reference frame and other neighboring frames. Subsequently, the Andrew's Sine norm is used for measuring the difference between the projected estimate of the high quality image and each low high quality image and for removing outliers in the data. Moreover, Tikhonov regularization is incorporated in the proposed framework in order to remove artifacts from the final answer and to improve the rate of convergence. Later, the reconstructed video frame is estimated by minimize the total cost function. Finally, experimental results are presented to demonstrate the outstanding performance of the proposed algorithm in comparison to several previously published methods using standard sequences such as Foreman and Susie that are corrupted by several noise models such as AWGN, Poisson Noise, Salt & Pepper Noise and Speckle Noise.

关键词： Robustness Additive white noise Gaussian noise Iterative algorithms Convergence Image reconstruction Cost function Standards publication AWGN Speckle

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Video enhancement using a robust iterative SRR based on Hampel stochastic estimation

Video enhancement using a robust iterative SRR based on Hamp...

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International Conference on Electrical engineering/Electronics, computer, Telecommunications and Information Technology, ECTI-CON

作者： Vorapoj Patanavijit Department of Computer and Network Engineering Faculty of Engineering Assumption University Bangkok Thailand

Many image video enhancements assume that the noise model of the imaging system is known in advance such as AWGN. However, the real noise model is not known in many practical applications. In this paper, we propose a novel robust video enhancement algorithm using SRR (super-resolution reconstruction) based on the stochastic regularization technique by minimizing a cost function. First, the classical registration process is used to estimate the relationship between the reference frame and other neighboring frames. Later, the Hampel norm is used for measuring the difference between the projected estimate of the high quality image and each low high quality image and for removing outliers in the data. Moreover, Tikhonov regularization is incorporated in the proposed framework in order to remove artifacts from the final answer and to improve the rate of convergence. Finally, experimental results are presented to demonstrate the outstanding performance of the proposed algorithm in comparison to several previously published methods using standard sequences such as Foreman and Susie that are corrupted by several noise models such as AWGN, Poisson Noise, Salt & Pepper Noise and Speckle Noise.

关键词： Stochastic processes Additive white noise Gaussian noise Noise robustness Stochastic resonance AWGN Iterative algorithms Image reconstruction Cost function Convergence

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Automatic video segmentation and story-based authoring in e-learning

Journal of Software

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Journal of Software 2009年第2期4卷 140-146页

作者： Liao, Yi-Chun Huang, Chun-Hong Department of Computer Science and Information Engineering China University of Technology Taiwan Department of Computer information and Network Engineering Lunghwa University of Science and Technology Taiwan

In e-learning, video is widely used in many course domains. We address the problem of the lecture recording and the organization of visual information through user's interaction at different steps. Our work focuses on the following three important areas: (1) synchronization method of the material contents and (2) interactions between material and users (3) construction of adaptive presentation methods in solving different knowledge levels. This paper proposes a story-based editing and browsing system with the automatic video segmentation. We also point out that a video classification technology can be further integrated to enhance the tool by using visual and audio information. In addition to the semantic segmentation, an instructional video can be edited with an instructor's story. The story-based editing is similar to hypervideo. Hypervideo is used as a hyperlink in a web. An instructor can constructs an instructional material by hypervideo links. For delivering pre-recorded lectures, we start our discussion on a multimedia presentation recording system which we had developed. © 2009 Academy Publisher.

关键词： E-learning

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Machine Learning for Signal Processing XIX - 2009 IEEE Signal Processing Society Workshop, MLSP 2009

作者： Plis, Sergey M. Potluru, Vamsi K. Calhoun, Vince D. Lane, Terran Electrical and Computer Engineering Department University of New Mexico NM 87131 United States Computer Science Department University of New Mexico NM 87131 United States Mind Research Network NM 87131 United States

ISBN: (纸本)9781424449484

Non-negative matrix factorization (NMF) is an algorithm for decomposing multivariate data into a signal dictionary and its corresponding activations. When applied to experimental data, NMF has to cope with noise, which is often highly correlated. We show that correlated noise can break the Donoho and Stodden separability conditions of a dataset and a regular NMF algorithm will fail to decompose it, even when given freedom to be able to represent the noise as a separate feature. To cope with this issue, we present an algorithm for NMF with a generalized least squares objective function (glsNMF) and derive multiplicative updates for the method together with proving their convergence. The new algorithm successfully recovers the true representation from the noisy data. Robust performance can make glsNMF a valuable tool for analyzing empirical data. © 2009 IEEE.

关键词： Least squares approximations

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Design an empathic virtual human to encourage and persuade learners in e-learning systems

Design an empathic virtual human to encourage and persuade l...

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1st ACM International Workshop on Multimedia Technologies for Distance Learning, MTDL 2009, Co-located with the 2009 ACM International Conference on Multimedia, MM'09

作者： Wang, Chin-Yeh Chen, Gwo-Dong Liu, Chen-Chung Liu, Baw-Jhiune Taiwan e-Learning and Digital Archives Program Office National Central University Taiwan Department of Computer Science and Information Engineering National Central University Taiwan Graduate Institute of Network Learning Technology National Central University Taiwan Department of Computer Science and Engineering Yuan-Ze University Taiwan

ISBN: (纸本)9781605587578

Studies indicate that making learners feel good is important only minor to clear knowledge transformation. Many studies have tried to use virtual humans as a part of interface in learning systems to increase the effect of instructions. Based on social interaction and pedagogical theories, many e-learning systems use animated films or virtual reality to boost human-computer engagement and ease their negative emotions. However, affective learning systems still need much research to improve their functionalities and usability. This study proposed a convenient approach to develop an emotionally interactive learning system;learners can express their emotions by mouse-clicking while learning. A virtual human was created to empathically react to learners in proactive and reactive ways to encourage and persuade them into persistent learning and help achieve their goals. Experimental results show that, averagely, subjects can tell virtual human's emotions and agree to its empathic reactions. Persuasion conducted by virtual human could not increase subjects' learning time, but could significantly increase their completion rate of exercises. Copyright 2009 ACM.

关键词： Learning systems

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