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IEEE International Workshop on Intelligent Robots and Systems (IROS)

作者： Dejun Wang Jiali Zhao Seok Cheol Kee Beijing Samsung Telecomunication(BST) Science & Tech Tower Human-Computer Interaction (HCI) Laboratory Beijing China Science & Tech Tower HCI Laboratory BST Beijing China Samsung Advanced Institute of Technology HCI Laboratory Company Limited Suwon South Korea

A novel heat kernel based Monte Carlo localization (HK-MCL) algorithm is presented to solve the degeneracy problem of conventional Monte Carlo localization: real-time global localization requires the number of initial samples to be small, whereas global localization may fail if the number of initial samples is small. The degeneracy problem is solved by an optimization approach called heat kernel based perturbation (HK-perturbation), which moves the samples towards the high likelihood area. HK-perturbation integrates the average local density and importance weight of samples to determine each sample's perturbation probability. The strategy improves simulated annealing algorithm via an obvious form of temperature, both in time and space, with respect to average local density and importance weight of samples. Systematic empirical results in global localization based on sonar illustrate superior performance, when compared to other state-of-the-art updating of Monte Carlo localization.

关键词： Kernel Monte Carlo methods Simulated annealing Cost function human computer interaction Poles and towers Sonar Temperature sensors Working environment noise Indoor environments

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Low-complexity predictive trellis coded quantization of wideband speech LSF parameters

Low-complexity predictive trellis coded quantization of wide...

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Proceedings - IEEE International Conference on Acoustics, Speech, and Signal Processing

作者： Shin, Yongwon Kong, Sangwon Fischer, Thomas R. Son, Changyong Lee, Yongbeom Telecommunication R and D Center Samsung Electronics Co. Suwon Korea Republic of Sch. of Elec. Eng. and Comp. Science Hanyang Univ. Ansan Korea Republic of Sch. of Elec. Eng. and Comp. Science Washington State Univ. Pullman WA 99163 United States Human and Computer Interaction Lab. Samsung Advanced Inst. of Tech. Kiheung-Eup Yongin Korea Republic of

In this paper, low-complexity block-constrained trellis coded quantization (BC-TCQ) structures are introduced, and a predictive BC-TCQ encoding method is developed for quantization of line spectrum frequencies (LSF) parameters for wideband speech coding applications. The performance is compared to the linear predictive coding (LPC) vector quantizers used in the AMR-WB (ITUG.722.2) speech coding standard, demonstrating reduction in spectral distortion and significant reduction in encoding complexity.

关键词： Speech processing

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Dynamic community: a new conceptual framework for supporting knowledge collaboration in software development

Dynamic community: a new conceptual framework for supporting...

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Asia-Pacific Conference on Software Engineering

作者： Y. Ye Y. Yamamoto K. Kishida Department of Computer Science University of Colorado Boulder CO USA SRA Key Technology Laboratory Inc. Shinjuku Tokyo Japan Knowledge Interaction Design Laboratory RCAST University of Tokyo Tokyo Japan

Software development is a knowledge intensive activity and software developers are knowledge workers. Knowledge needed for software development is often distributed among different developers. Supporting efficient knowledge collaboration and transfer is thus essential for software development organizations to remain competitive. This paper proposes a new theory /sub y/namic community to support knowledge collaboration and discusses its application in software development. Dynamic community integrates the traditional knowledge management approach in which knowledge is formalized and accumulated in knowledge repositories, and the community-based knowledge collaboration approach in which knowledge is transferred through informal community participation and human contacts. The dynamic community theory takes into full consideration individual knowledge workers' ever-changing needs for new knowledge as well as the role of social relationship of knowledge workers in effective knowledge collaboration. This paper introduces the dynamic community theory, a general system architecture of sociotechnical environments in support of dynamic community, and its application in software development.

关键词： Collaborative software Programming Collaborative work Application software Software systems Laboratories Knowledge management humans computer architecture Collaborative tools

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N-fold Templated Piped Correction

N-fold Templated Piped Correction

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第一届自然语言处理联合学术会议

作者： Grace NGAI Marine CARPUAT Hong Kong Polytechnic University Department of Computing Kowloon Hong Kong Human Language Technology Center HKUST Department of Computer Science University of Science and Technology Clear Water Bay Hong Kong

We describe a broadly-applicable conservative error correcting model, N-fold Templated Piped Correction (NTPC), that consistently improves the accuracy of existing high-accuracy base models. Under circumstances where most obvious approaches actually reduce accuracy more than they improve it, NTPC nevertheless comes with little risk of accidentally degrading performance. NTPC is particularly well suited for natural language applications involving high-dimensional feature spaces, such as bracketing and disambiguation tasks, since its easily customizable templatedriven learner allows efficient search over the kind of complex feature combinations that have typically eluded the base models. We show empirically that NTPC yields small but consistent accuracy gains on top of even high-performing models like boosting. We also give evidence that the various extreme design parameters in NTPC are indeed necessary for the intended operating range, even though they diverge from usual practice.

关键词： N-fold Templated Piped Correction

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Modular structure generation by greedy network-growing algorithm

Modular structure generation by greedy network-growing algor...

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2004 IEEE Conference on Cybernetics and Intelligent Systems

作者： Kamimura, Ryotaro Takeuchi, Haruhiko Information Science Laboratory Fut. Sci. and Technol. Jt. Res. Ctr. Tokai University 1117 Kitakaname Hiratsuka Kanagawa 259-1292 Japan Human-Computer Interaction Group Inst. for Hum. Sci. and Biomed. Eng. Natl. Inst. Adv. Indust. Sci./T. 1-1-1 Higashi Tsukuba 305-8566 Japan

ISBN: (纸本)0780386442

In this paper, we propose a new method to generate modular structures. In the method, the number of elements, that is, the number of competitive units is gradually increased. To control a process of module generation, we introduce two kinds of information, that is, unit and modular information. Unit information represents information content obtained by individual elements in all modules. On the other hand, modular information is information content obtained by each module. We try to increase both types of information simultaneously. We applied our method to two classification problems: random data classification and web data classification. In both cases, we observed that modular structures were automatically generated.

关键词： computer networks

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Accelerated greedy network-growing algorithm by gaussian activation functions

Accelerated greedy network-growing algorithm by gaussian act...

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2004 IEEE Conference on Cybernetics and Intelligent Systems

ISBN: (纸本)0780386442

In this paper, we propose a new computational method for a network-growing method called greedy network-growing. We have so far introduced a network-growing algorithm called greedy network-growing based upon information theoretic competitive learning. For competitive unit outputs, we have used the inverse of the squares of Euclidean distance between input patterns and connections. The algorithm has extracted very faithful representations of input patterns. However, one problem is that learning is very slow, and sometimes ambiguous final representations are obtained. To remedy these shortcomings, we introduce a new activation function, that is, Gaussian activation functions for competitive units. By changing a parameter for the Gaussian activation functions, we can build a network that does not focus on faithful representations of input patterns, but try to extract the main characteristics of input patterns. Because this method are not concerned with detailed parts of input patterns, learning is significantly accelerated and salient features should be extracted. We applied the method to a road classification problem. Experimental results confirmed that learning was significantly accelerated and salient features could be extracted.

关键词： computer networks

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Optical coherence tomography of breast cancer: Feasibility for surgical guidance

Optical coherence tomography of breast cancer: Feasibility f...

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Biomedical Topical Meeting, BIOMED 2004

作者： Bredfeldt, Jeremy S. Luo, Wei Marks, Daniel L. Singletary, Keith W. Wisseman, Charles L. Johnson, Patricia A. Boppart, Stephen A. Beckman Institute for Advanced Science and Technology University of Illinois at Urbana-Champaign United States Department of Food Science and Human Nutrition Functional Foods for Health Program University of Illinois at Urbana-Champaign United States Surgical Pathology and Oncology Carle Foundation Hospital UrbanaIL United States Department of Electrical and Computer Engineering Beckman Institute for Advanced Science and Technology Bioengineering Program College of Medicine University of Illinois at Urbana-Champaign 405 N. Mathews Avenue UrbanaIL61801 United States

We present the use of OCT for breast cancer imaging. In situ rat mammary and excised human breast tumors were imaged. The feasibility of OCT for applications in surgical oncology of the breast is discussed. © 200... 详细信息

ISBN: (纸本)1557527695

关键词： Optical tomography

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A sequence alignment-independent method for protein classification

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Applied Bioinformatics 2004年第2-3期3卷 137-148页

作者： Vries, John K. Munshi, Rajan Tobi, Dror Klein-Seetharaman, Judith Benos, Panayiotis V. Bahar, Ivet Department of Molecular Genetics and Biochemistry School of Medicine University of Pittsburgh Pittsburgh PA United States Department of Pharmacology School of Medicine University of Pittsburgh Pittsburgh PA United States Language Technologies Institute Institute for Software Research International School of Computer Science Carnegie Mellon University Pittsburgh PA United States Department of Human Genetics Graduate School of Public Health University of Pittsburgh Pittsburgh PA United States Department of Molecular Genetics and Biochemistry School of Medicine University of Pittsburgh Pittsburgh PA 15213 200 Lothrop St United States

Annotation of the rapidly accumulating body of sequence data relies heavily on the detection of remote homologues and functional motifs in protein families. The most popular methods rely on sequence alignment. These include programs that use a scoring matrix to compare the probability of a potential alignment with random chance and programs that use curated multiple alignments to train profile hidden Markov models (HMMs). Related approaches depend on bootstrapping multiple alignments from a single sequence. However, alignment-based programs have limitations. They make the assumption that contiguity is conserved between homologous segments, which may not be true in genetic recombination or horizontal transfer. Alignments also become ambiguous when sequence similarity drops below 40%. This has kindled interest in classification methods that do not rely on alignment. An approach to classification without alignment based on the distribution of contiguous sequences of four amino acids (4-grams) was developed. Interest in 4-grams stemmed from the observation that almost all theoretically possible 4-grams (20⁴) occur in natural sequences and the majority of 4-grams are uniformly distributed. This implies that the probability of finding identical 4-grams by random chance in unrelated sequences is low. A Bayesian probabilistic model was developed to test this hypothesis. For each protein family in Pfam-A and PIR-PSD, a feature vector called a probe was constructed from the set of 4-grams that best characterised the family. In rigorous jackknife tests, unknown sequences from Pfam-A and PIR-PSD were compared with the probes for each family. A classification result was deemed a true positive if the probe match with the highest probability was in first place in a rank-ordered list. This was achieved in 70% of cases. Analysis of false positives suggested that the precision might approach 85% if selected families were clustered into subsets. Case studies indicated that

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Discovery of the tri-edge inequality with binary vector dissimilarity measures

Discovery of the tri-edge inequality with binary vector diss...

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International Conference on Pattern Recognition

作者： Bin Zhang S. Srihari Department of Human Genetics David Geffen School of Medicine Department of Biostatistics School of Public Health University of California Los Angeles USA Center of Excellence for Document Analysis and Recognition Department of Computer Science and Engineering State University of New York University at Buffalo USA

In certain spaces using some distance measures, the sum of any two distances is always bigger than the third one. Such a special property is called the tri-edge inequality (TEI). In this paper, the tri-edge inequality characterizing several binary distance measures is mathematically proven and experimentally verified, and the implications of TEI are discussed as well.

关键词： Pattern recognition

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Steps towards 'undigital' intelligent image processing: real-valued image coding of photoquantimetric pictures into the JLM file format for the compression of portable lightspace maps

Steps towards 'undigital' intelligent image processing: real...

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

作者： S. Mann C. Manders B.L. Belmellat L. Kansal D. Chen EyeTap Personal Imaging (ePi) Laboratory Department of Electrical and Computer Engineering University of Toronto Toronto ONT Canada Human Media Laboratory (HML) School of Computing and Information Science Queen's University Kingston ONT Canada

Recent advances in intelligent signal processing have made it possible to capture high dynamic range images which are better represented as an array of real numbers rather than the current convention of an array of integers. This paper proposes a solution to address the need for real, rather than just integer, image coding and file formats. Additionally, we propose that the real-valued data be linear in photoquantity (the quantity of light received by the camera) to avoid the image misrepresentation that occurs when a camera's non-linear dynamic range compressor and a display's dynamic range non-linear expander do not match. We present two novel image formats that achieve this: the portable lightspace map (PLM) and its compressed version the JPEG lightspace map (JLM), that builds upon the JPEG compression scheme. The results of various compression levels for real-valued data and their corresponding file sizes are reported.

关键词： Image coding Image processing Dynamic range Digital cameras Spatial resolution Optical arrays Transform coding Displays Sensor arrays Portable computers

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