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International Journal of Digital Content technology and its Applications 2012年第17期6卷 144-153页

作者： Zhang, Guan-Hong Odbal Department of Computer science and technology Key Lab of Network and Intelligent Information Processing Hefei University Anhui Hefei 230601 China Hefei Institutes of Physical Science of Chinese Academy Science Anhui Hefei 230031 China

There exist noisy, unparallel sentences in parallel web pages. Web page structure is subjected to some limitation for sentences alignment task for web page text. The most straightforward way of aligning sentences is using a translation lexicon. However, a major obstacle to this approach is the lack of dictionary for training. This paper presents a method for automatically align Mongolian-Chinese parallel text on the Web via vector space model. Vector space model is an algebraic model for representing any object as vectors of identifiers, such as index terms. In the statistically based vector-space model, a sentence is conceptually represented by a vector of keywords extracted from the text. Extracted keywords are composed by content words, known as terms and the weight of a term in a sentence vector can be determined tf-idf method. CHI is used to compute the association between bilingual words. Once the term weights are determined, the similarity between sentence vectors is computed via cosine measure. The experimental results indicate that the method is accurate and efficient enough to apply without human intervention.

关键词： Websites

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Coral reef mosaicking using Teardrop and Fast Image Labeling

Coral reef mosaicking using Teardrop and Fast Image Labeling

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OCEANS 2012 MTS/IEEE Yeosu Conference: The Living Ocean and Coast - Diversity of Resources and Sustainable Activities

作者： Corpuz, Francis James Naval, Prospero Capili, Eusebio Jauod, Jaylord Judilla, Roel John Soriano, Maricor Vision and Image Processing Group National Institute of Physics University of the Philippines Diliman Quezon City Philippines Department of Computer Science College of Engineering University of the Philippines Diliman Quezon City Philippines Mapua Robotics Center Special Projects Laboratory Mapua Institute of Technology Intramuros Manila Philippines

ISBN: (纸本)9781457720895

In this paper, we present an inexpensive system for diverless video capture and fast image stitching of image frames for rapid reef assessment of shallow coral reefs. Our system has two main components: 1) Teardrop, a boat-towable, winged hull apparatus designed to house a commercial digital camera, and 2) a mosaicking algorithm to stitch the coral reef video into mosaics for further appreciation and analysis. The captured reef video is then separated into image frames which are to be stitched sequentially using Fast Image Labeling. The overlap between image frames is estimated using Single-Step DFT, an efficient sub-pixel estimation algorithm. The estimated overlap is used to compute for the area to be added to the mosaic space. The overlapping section between succeeding image-pairs are stitched along a seam determined by a minimal-cost path using dynamic programming. The visibility of the seam boundaries is further minimized by utilizing blending on multi-resolution splines. Experimental results on automated reef mosaics creation from actual coral reef video taken using Teardrop shows the performance of the system described. The main contribution of this work is the demonstration of a rapid reef visualization system using a diverless system and commercially available, non-research-grade imaging equipment. © 2012 IEEE.

关键词： Reefs

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${\rm S}^{3}{\rm MKL}$: Scalable Semi-Supervised Multiple Kernel Learning for Real-World Image Applications

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IEEE Transactions on Multimedia 2012年第4期14卷 1259-1274页

作者： Shuhui Wang Qingming Huang Shuqiang Jiang Qi Tian Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China Department of Computer Science University of Texas-San Antonio San Antonio TX USA

We study the visual learning models that could work efficiently with little ground-truth annotation and a mass of noisy unlabeled data for large scale Web image applications, following the subroutine of semi-supervised learning (SSL) that has been deeply investigated in various visual classification tasks. However, most previous SSL approaches are not able to incorporate multiple descriptions for enhancing the model capacity. Furthermore, sample selection on unlabeled data was not advocated in previous studies, which may lead to unpredictable risk brought by real-world noisy data corpse. We propose a learning strategy for solving these two problems. As a core contribution, we propose a scalable semi-supervised multiple kernel learning method (S 3 MKL) to deal with the first problem. The aim is to minimize an overall objective function composed of log-likelihood empirical loss, conditional expectation consensus (CEC) on the unlabeled data and group LASSO regularization on model coefficients. We further adapt CEC into a group-wise formulation so as to better deal with the intrinsic visual property of real-world images. We propose a fast block coordinate gradient descent method with several acceleration techniques for model solution. Compared with previous approaches, our model better makes use of large scale unlabeled images with multiple feature representation with lower time complexity. Moreover, to address the issue of reducing the risk of using unlabeled data, we design a multiple kernel hashing scheme to identify the “informative” and “compact” unlabeled training data subset. Comprehensive experiments are conducted and the results show that the proposed learning framework provides promising power for real-world image applications, such as image categorization and personalized Web image re-ranking with very little user interaction.

关键词： Kernel Visualization Training Data models Noise measurement Training data Learning systems

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Real-valued negative selection algorithm with variable-sized self radius

Real-valued negative selection algorithm with variable-sized...

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3rd International Conference on Information Computing and Applications, ICICA 2012

作者： Zeng, Jinquan Tang, Weiwen Liu, Caiming Hu, Jianbin Peng, Lingxi School of Computer Science and Engineering University of Electronic Science and Technology of China 610054 Chengdu China Sichuan Communication Research Planning and Designing Co. Ltd. 610041 Chengdu China Laboratory of Intelligent Information Processing and Application Leshan Normal University 614004 Leshan China School of Electronics and Information Nantong University 226019 Nantong China Department of Computer and Education Software Guangzhou University 510006 Guangzhou China

ISBN: (纸本)9783642340611

Negative selection algorithm (NSA) generates the detectors based on the self space. Due to the drawbacks of the current representation of the self space in NSAs, the generated detectors cannot enough cover the non-self space and at the same time, cover some of the self space. In order to overcome the drawbacks, a new scheme of the representation of the self space is introduced with variable-sized self radius, which is called VSRNSA. Using the variable-sized self radius to represent the self space, we can generate the more quality detectors. The algorithm is tested using the well-known real world datasets;preliminary results show that the new approach enhances NSAs in increasing detection rates and decrease false alarm rates, and without increase in complexity. © 2012 Springer-Verlag.

关键词： computers

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Performance analysis of Neural Networks in combination with n-gram language models

Performance analysis of Neural Networks in combination with ...

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International Conference on Acoustics, Speech, and Signal processing (ICASSP)

作者： Ilya Oparin Martin Sundermeyer Hermann Ney Jean-Luc Gauvain LIMSI CNRS Spoken Language Processing Group France Computer Science Department Human Language Technology and Pattern Recognition RWTH Aachen University Germany

Neural Network language models (NNLMs) have recently become an important complement to conventional n-gram language models (LMs) in speech-to-text systems. However, little is known about the behavior of NNLMs. The analysis presented in this paper aims to understand which types of events are better modeled by NNLMs as compared to n-gram LMs, in what cases improvements are most substantial and why this is the case. Such an analysis is important to take further benefit from NNLMs used in combination with conventional n-gram models. The analysis is carried out for different types of neural network (feed-forward and recurrent) LMs. The results showing for which type of events NNLMs provide better probability estimates are validated on two setups that are different in their size and the degree of data homogeneity.

关键词： Artificial neural networks History Analytical models Training data Vocabulary Interpolation

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Process Calculus with Data Structure and its Model Checking Algorithm

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Physics Procedia 2012年 33卷 782-789页

作者： Qing Zheng Zi-Ning Cao Department of Computer Science and Technology Nanjing University of Aero. & Astro. Nanjing 210016 P.R. China Provincial Key Laboratory for Computer Information Processing Technology Soochow University Suzhou 215006 P.R. China National Key Laboratory of Science and Technology on Avionics System Integration Shanghai 200233 P.R. China

Model checking is one of the most important technology for automatically verification. So this paper generally proposed a method of combining CCS and Z language, to perform model checking. It combines the advantage of current CCS and Z systems, where CCS is good at describing concurrent systems, also Z is a good tool for data structure. As a result, form the new system CCS-Z. Then we give the syntax and semantics of it, at last give the model checking *** advantage of this paper is combined data stucture on the famous system CCS, and increase the capacity of system description.

关键词： Model Checking CTL Z Language CCS

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A complexity adaptive channel estimator for low power 12

A complexity adaptive channel estimator for low power

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Design, Automation and Test in Europe Conference and Exhibition

作者： Zhibin Yu C. H. van Berkel Hong Li Department of Mathematics & Computer Science Eindhoven University of Technology Eindhoven Netherlands Department of Modem & Signal Processing NXP Semiconductors Netherlands B. V. Eindhoven Netherlands

ISBN: (纸本)9783981080186

This paper presents a complexity adaptive channel estimator for low power. Channel estimation (CE) is one of the most computation intensive tasks in a software-defined radio (SDR) based OFDM demodulator. Complementary to the conventional low-power design methodology on processor architectures or circuits, we propose to reduce power also at the algorithm level. The idea is to dynamically scale the processing load of the channel estimator according to the run-time estimated channel quality. In this work, with a case study on China Mobile Multimedia Broadcasting (CMMB) standard, three practical CE algorithms are adopted to form a complexity scalable algorithm set, and signal noise ratio (SNR) is chosen to be the channel quality parameter for CE algorithm switching. In order to accurately estimate the SNR in the run-time, we also propose a noise variance estimation algorithm which is robust against fast-fading channels and introduces small computation overheads. Simulation shows that, under a pre-defined scenario for our targeting SDR demodulator, more than 50% run-time load reduction can be achieved compared with a fixed worst case channel estimator, while still fulfilling the mean square error requirement, resulting in about 25% of power reduction for the total demodulator. In addition, complexity adaption enables dynamical voltage and frequency scaling (DVFS) in a SDR demodulator which can lead to furthermore power reduction.

关键词： Channel estimation Signal to noise ratio OFDM Complexity theory Algorithm design and analysis Signal processing algorithms

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Emotion identification for evaluation of synthesized emotional speech

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6th International Conference on Speech Prosody 2012, SP 2012

作者： Steidl, Stefan Polzehl, Tim Timothy Bunnell, H. Dou, Ying Muthukumar, Prasanna Kumar Perry, Daniel Prahallad, Kishore Vaughn, Callie Black, Alan W. Metze, Florian Computer Science Department 5 University Erlangen-Nuremberg Germany Deutsche Telekom Laboratories/Technische Universität Berlin Germany Nemours Biomedical Research Wilmington United States Center for Speech and Language Processing Johns Hopkins University Baltimore United States Language Technologies Institute Carnegie Mellon University Pittsburgh United States University of California Los Angeles United States International Institute of Information Technology Hyderabad India Computer Science Department Oberlin College Oberlin United States

ISBN: (纸本)9787560848693

In this paper, we propose to evaluate the quality of emotional speech synthesis by means of an automatic emotion identification system. We test this approach using five different parametric speech synthesis systems, ranging from plain non-emotional synthesis to full re-synthesis of pre-recorded speech. We compare the results achieved with the automatic system to those of human perception tests. While preliminary, our results indicate that automatic emotion identification can be used to assess the quality of emotional speech synthesis, potentially replacing time consuming and expensive human perception tests.

关键词： Speech synthesis

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Speeding up the MATLAB complex networks package using graphic processors

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Chinese Physics B 2011年第9期20卷 460-467页

作者：张百达唐玉华吴俊杰李鑫 National laboratory for Parallel and Distributed Processing School of ComputerNational University of Defense Technology Department of Computer Science and Technology School of ComputerNational University of Defense Technology

The availability of computers and communication networks allows us to gather and analyse data on a far larger scale than previously. At present, it is believed that statistics is a suitable method to analyse networks with millions, or more, of vertices. The MATLAB language, with its mass of statistical functions, is a good choice to rapidly realize an algorithm prototype of complex networks. The performance of the MATLAB codes can be further improved by using graphic processor units （GPU）. This paper presents the strategies and performance of the GPU implementation of a complex networks package, and the Jacket toolbox of MATLAB is used. Compared with some commercially available CPU implementations, GPU can achieve a speedup of, on average, 11.3x. The experimental result proves that the GPU platform combined with the MATLAB language is a good combination for complex network research.

关键词： complex networks graphic processors unit MATLAB Jacket Toolbox

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Investigation of the improved performance in a graphene/polycrystalline BiFeO3/Pt photovoltaic heterojunction: Experiment, modeling, and application

Investigation of the improved performance in a graphene/poly...

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作者： Zang, Yongyuan Xie, Dan Chen, Yu Wu, Xiao Ren, Tianling Zhu, Hongwei Cao, Jiang-Li Plant, David Electrical and Computer Engineering McGill University Montreal QC H3A 2T8 Canada Institute of Microelectronics Tsinghua University Beijing 100084 China Key Laboratory for Advanced Manufacturing by Material Processing Technology Department of Mechanical Engineering Tsinghua University Beijing 100084 China Tsinghua University Beijing 100084 China Institute for Advanced Materials and Technology University of Science and Technology Beijing Beijing 100083 China

We report on the enhancement of photovoltaic performance in a graphene/polycrystalline BiFeO3 (BFO)/Pt heterojunction for the first time. The unique properties of the graphene electrode lead to a short circuit current density of 61 μA/cm2 and an open circuit voltage of 0.52 V in the heterojunction. These values are much higher than the results reported in polycrystalline BFO with indium tin oxide as the top electrode. A theoretical band diagram model and an equivalent electrical model considering the ferroelectric polarization, interface states, and energy band bending effect are constructed to depict the carrier transport behavior. Important photovoltaic parameters, such as conversion efficiency, illumination intensity response, ON/OFF characteristics, minority carrier lifetime, and external quantum efficiency, are investigated experimentally and theoretically. To improve the photovoltaic performance of the graphene/polycrystalline BFO/Pt heterojunction, HNO3 treatment, and CdSe quantum dots (QDs) filling/sensitizing, as two independent chemical and physical routines, were processed and compared. It can be seen that the photocurrent density exhibits a significant improvement from 61 μA/cm2 to 8.67 mA/cm2 (∼150 fold) after HNO3 treatment, while a considerable enhancement of ∼5 fold is seen with QDs filling/sensitizing. We also present and investigate an optical application of our graphene/polycrystalline BFO/Pt heterojunction as a photosensitive detector. © 2012 American Institute of Physics.

关键词： Heterojunctions

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