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17th International Conference on computers in Education, ICCE 2009

作者： Lao, C.C. Hsu, S.H. Chang, A.T. Wang, J.H. Ho, S.H. Chan, T.W. Graduate Institute of Network Learning Technology National Central University Taiwan Department of Computer Science and Information Engineering National Central University Taiwan

ISBN: (纸本)9789868473539

In this article, we would like to describe a computer supported model and an initial implementation on Chinese learning. Teacher plays a role of coordinator, while the students are the main actors. From the basis of peer instruction and negotiation of MCSCL, we designed a model which would be possible to enhance elementary student's Chinese comprehensive skill. During the peer discussion among students, those grade 4 students would appear conflicts. Hence, this study was to describe the design and the setting of our experiment, the facts that we found, and the conditions in this experiment will be discussed and analyzed.

关键词： Students

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Affective classification of movie scenes based on two-pass clustering technique

Affective classification of movie scenes based on two-pass c...

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17th International Conference on computers in Education, ICCE 2009

作者： Sung, Che-Wei Wu, Yu-Chieh Chien, Kun-Huang Yang, Jie-Chi Department of Computer Science and Information Engineering National Central University Taiwan Graduate Institute of Network Learning Technology National Central University Taiwan

ISBN: (纸本)9789868473553

Video-based learning not only provides rich content but also gives multimedia e-learning environment. In this paper, we present an affective movie classification tool, which automatically segments and labels emotion tags for the given video film. Our method integrates nine audio and visual features from each input video. Then the proposed two-pass clustering technique is used to group similar video scenes and gives labels. One good property of our method is that the need of manual annotated training data is un-required. We compared with the other famous algorithms such as ART2 and K-means. The experimental result shows that our video affect classification tool yields better accuracy (recall and precision) than the other clustering approaches. In short, it achieves ∼80% in F-measure rate for 119 testing scenes.

关键词： Self organizing maps

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Equal opportunity tactic: Balancing winning probabilities in a competitive classroom game

Equal opportunity tactic: Balancing winning probabilities in...

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17th International Conference on computers in Education, ICCE 2009

作者： Cheng, Hercy N.H. Wu, Winston M.C. Liao, Calvin C.Y. Chan, Tak-Wai Department of Computer Science and Information Engineering National Central University Taiwan Graduate Institute of Network Learning Technology National Central University Taiwan

ISBN: (纸本)9789868473539

The outcome of competition is heavily ability dependent - the more-able students always win while the less-able lose. However, individual abilities are different. Students who consistently demonstrate lower performance than their peers may feel discouraged and frustrated. These lower-performance students hardly have the same winning probabilities as more-able students. In this study the authors design equal opportunity tactic to moderate the difference in performance between more-able and less-able students. The tactic is incorporated into a competitive learning game, AnswerMatching, by assigning every student an opponent with similar ability. A preliminary experiment was also conducted to investigate the effects of the tactic. Results showed that the tactic could balance the performance as well as the belief about how well students could achieve. That is, less-able students could have similar winning probabilities to more-able students.

关键词： Students

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Being an opportunist or a hard worker: Comparison of computer-based input types for arithmetical word problems

Being an opportunist or a hard worker: Comparison of compute...

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17th International Conference on computers in Education, ICCE 2009

作者： Huang, Yana C.Y. Cheng, Solars Y.W. Liu, Ellen C.C. Wu, Winston M.C. Cheng, Hercy N.H. Chan, Tak-Wai Graduate Institute of Network Learning Technology National Central University Taiwan Department of Computer Science and Information Engineering National Central University Taiwan

ISBN: (纸本)9789868473539

The digital content has been considered as a core part of classroom learning. The way to input answers may influence student learning behaviors. This paper focuses on three computer-based input types - choice buttons, drag-and-drop, and text boxes - that are used frequently in arithmetical word problems of elementary schools. The experiment was conducted to examine how students input answers in computers and how they are engaged in learning. The results showed that the students had high accuracy when they had to type their answers;they were willing to spend time on studying the questions and creating the answers. When students were allowed to choosing or dragging-and-dropping, some of students would guess the answer by the "advantage" of computers - instant feedbacks. This paper suggests that the interface should facilitate a student to be a hard worker rather than an opportunist.

关键词： Students

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An automatic wavelength control method of a tunable laser for a WDM-PON

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IEEE Photonics Technology Letters 2009年第5期21卷 325-327页

作者： Moon, Jung-Hyung Choi, Ki-Man Mun, Sil-Gu Lee, Chang-Hee Department of Electrical Engineering and Computer Science Korea Advanced Institute of Science and Technology Daejeon 305-701 Korea Republic of Next Generation Research Department Korea Telecom Network Technology Laboratory Daejeon 305-811 Korea Republic of

We propose a novel automatic wavelength control method of a tunable laser for a wavelength-division-multiplexed passive optical network (WDM-PON). By sending a low-power amplified spontaneous emission light generated from a broadband light source (BLS) to a tunable laser through a wavelength-division multiplexer, we match the wavelength of the tunable laser to a peak transmission wavelength of the multiplexer. The deviation of the wavelength of the tunable laser was less than 0.05 nm from the center of the target channel. We demonstrate up to 10-Gb/s transmission in a WDM-PON by using the proposed method. We also show that system impairments induced by the BLS are negligible. © 2009 IEEE.

关键词： Passive optical networks

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K-way tree classification based on semi-greedy structure applied to multisource remote sensing images

K-way tree classification based on semi-greedy structure app...

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2009 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2009

作者： Chang, Yang-Lang Chen, Zhi-Ming Fang, Jyh-Perng Liang, Wen-Yew Hsieh, Tung-Ju Hsu, Wei-Lieh Ren, Hsuan Chen, Kun-Shan Department of Electrical Engineering National Taipei University of Technology Taipei Taiwan Department of Computer Science and Information Engineering National Taipei University of Technology Taipei Taiwan Department of Computer Information and Network Engineering Lunghwa University of Science and Technology Taouan Taiwan Center for Space and Remote Sensing Research National Central University Chung-Li Taiwan

ISBN: (纸本)9781424433957

In this paper we present a new supervised classification method, referred to as the k-way tree semi-greedy (KTSG) classifier, for the classification of multisource remote sensing images. The generalized positive Boolean function (GPBF) classifier scheme is recently proposed based on minimum classification error (MCE) criteria to improve classification performance. It makes use of MCE criteria to apply positive and negative samples as training parameters. Unfortunately, the classification performance of GPBF is limited when the number of classes increases. This is occurred in training phase by the unbalanced numbers of positive and negative samples caused by the use of a large number of classes. The proposed KTSG overcomes this drawback by modifying the scheme from the perception of pattern-node based semi-greedy (bottom-up scheme used in GPBF) to the conception of region-based semi-greedy (also known as the top-down scheme in KTSG). It is organized by a k-way tree in which every node is composed of a set of k-dimensional positive and negative labeled samples as represented as a percentage, i.e. the corresponding ratio of number of a specific (positive) class samples to the total number of the other (negative) classes. It iteratively divides the d-dimensional hyperplane into 2d subspaces according to the centroids of the labeled (training) samples of all classes. The statistical ratios between different classes are then compared as a basis for stopping the new subspace separation and identifying which subspace belongs to which class. By delivering both positive and negative samples of different classes to KTSG learning modules, KTSG outperforms GPBF and traditional classifiers in terms of classification accuracies. The effectiveness of the proposed KTSG is evaluated by fusing MODIS/ASTER airborne simulator (MASTER) hyperspectral images and airborne synthetic aperture radar (AIRSAR) images for land cover classification during the Pacrim II campaign. ©2009 IEEE.

关键词： Remote sensing

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Stress detection based on multi-class probabilistic support vector machines for accented English speech

Stress detection based on multi-class probabilistic support ...

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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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