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Mechatronics, robotics and components for automation and control IFAC milestone report

IFAC Proceedings Volumes 2008年第2期41卷 10800-10809页

作者： S. Boverie Dongil Dan Cho H. Hashimoto M. Tomizuka Wang Wei D. Zühlke Continental Automotive France BP 83649 1 Ave.Paul Ourliac. F-31036 Toulouse CEDEX. France School of Electrical Engineering and Computer Science Seoul National University Kwanak-ku Seoul 151-742 Korea Institute of Industrial Science University of Tokyo 4-6-1 Komaba Meguro-ku Tokyo 153-8505 JAPAN Department of Mechanical Engineering University of California Berkeley CA 94720-1740 USA Research Center of Information and Control Dalian University of Technology Dalian 116024 P.R. China German Research Center for Artificial Intelligence DFKI GmbH Center for Human-Machine-Interaction PO Box 3049 D-67653 Kaiserslautern Germany

This paper presents a general overview of the technological fields of mechatronic, robotic, components for automation and control. Five technical areas are considered: component and instruments, mechatronic, robotics, cost oriented automation and human-machine systems. The paper addresses their current key problems and the recent major accomplishments. At last the most promising forecasted development and applications are considered.

关键词： Component for control Mechatronic systems Robotics Cost oriented automation Human-machine systems

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Conditionals and consequences

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Journal of Applied Logic 2007年第4 SPEC. ISS.期5卷 638-650页

作者： Kyburg Jr., Henry E. Choh Man Teng Wheeler, Gregory Departments of Philosophy and Computer Science University of Rochester Rochester NY 14627 United States Institute for Human and Machine Cognition University of West Florida Pensacola FL 32502 United States Artificial Intelligence Center - CENTRIA Universidade Nova de Lisboa 2829-516 Caparica Portugal

We examine the notion of conditionals and the role of conditionals in inductive logics and arguments. We identify three mistakes commonly made in the study of, or motivation for, non-classical logics. A nonmonotonic consequence relation based on evidential probability is formulated. With respect to this acceptance relation some rules of inference of System P are unsound, and we propose refinements that hold in our framework. © 2006 Elsevier B.V. All rights reserved.

关键词： Probabilistic logics

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A tool for collaborative construction of large biological ontologie

A tool for collaborative construction of large biological on...

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17th International Conference on Database and Expert Systems Applications, DEXA 2006

作者： Bao, Jie Hu, Zhiliang Caragea, Doina Reecy, James Honavar, Vasant G. Department of Computer Science Center for Computational Intelligence Learning and Discovery Artificial Intelligence Research Laboratory United States Department of Animal Science Iowa State University Ames IA 50011 United States

ISBN: (纸本)0769526411

In order for ontologies to be broadly useful to the scientific community, they need to capture knowledge and expertise of multiple experts and research groups. Consequently, the construction of such ontologies necessarily requires collaboration among individual experts or research groups. Support for such collaboration is largely lacking in existing ontology development environments. We describe some initial steps towards the development of a collaborative ontology development environment. Specifically, we describe an ontology editing tool COB Editor which exploits the notion of modular ontologies (or ontology packages) to support sharing, reuse, and collaborative editing of partial order (i.e., DAG-structured) ontologies. COB Editor can engage diverse and relatively autonomous communities of biologists in the process of creating the ontologies needed for annotating, integrating, and analyzing diverse sources of 'omics' data. Copyright © 2006 by The Institute of Electrical and Electronics Engineers, Inc.

关键词： Ontology

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Model-based sequential organization in cochannel speech

Model-based sequential organization in cochannel speech

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作者： Shao, Yang Wang, Deliang IEEE Department of Computer Science and Engineering Center for Cognitive Science Ohio State University Columbus OH 43210-1277 United States Computer Science and Engineering Ohio State University Columbus Department of Computer Science and Engineering Center for Cognitive Science Ohio State University Columbus IEEE Computational Intelligence Society Neural Networks Technical Committee Governing Board of the International Neural Network Society IEEE Signal Processing Society Machine Learning for Signal Processing Technical Committee

A human listener has the ability to follow a speaker's voice while others are speaking simultaneously;in particular, the listener can organize the time-frequency energy of the same speaker across time into a single stream. In this paper, we focus on sequential organization in cochannel speech, or mixtures of two voices. We extract minimally corrupted segments, or usable speech, in cochannel speech using a robust multipitch tracking algorithm. The extracted usable speech is shown to capture speaker characteristics and improves speaker identification (SID) performance across various target-to-interferer ratios. To utilize speaker characteristics for sequential organization, we extend the traditional SID framework to cochannel speech and derive a joint objective for sequential grouping and SID, leading to a problem of search for the optimum hypothesis. Subsequently we propose a hypothesis pruning algorithm based on speaker models in order to make the search computationally efficient. Evaluation results show that the proposed system approaches the ceiling SID performance obtained with prior pitch information and yields significant improvement over alternative approaches to sequential organization. © 2006 IEEE.

关键词： Speech recognition

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Identifying interaction sites in "Recalcitrant" proteins: Predicted protein and RNA binding sites in REV proteins of HIV-1 and EIAV agree with experimental data

Identifying interaction sites in "Recalcitrant" proteins: Pr...

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11th Pacific Symposium on Biocomputing 2006, PSB 2006

作者： Terribllini, Michael Lee, Jae-Hyung Yan, Changhui Jernigan, Robert L. Carpenter, Susan Honavar, Vasant Dobbs, Drena Bioinformatics and Computational Biology Graduate Program LH. Baker Center for Bioinformatics and Biological Statistics Iowa State University Ames IA 50010 United States Department of Computer Science Iowa State University Ames IA 50010 United States Department of Biochemistry Biophysics and Molecular Biology Iowa State University Ames IA 50010 United States Department of Genetics Development and Cell Biology Iowa State University Ames IA 50010 United States Artificial Intelligence Research Laboratory Center for Computational Intelligence Learning and Discovery Iowa State University Ames IA 50010 United States Department of Veterinary Microbiology and Pathology Washington State University Pullman WA. 99164 United States

ISBN: (纸本)9812564632

Protein-protein and protein nucleic acid interactions are vitally important for a wide range of biological processes, including regulation or gene expression, protein synthesis, and replication and assembly of many viruses. We have developed machine learning approaches for predicting which amino acids of a protein participate in its interactions with other proteins and/or nucleic acids, using only the proiein sequence as input. In this paper, we describe an application of classifiers trained on datasets of well-characterized protein-protein and protein-RNA complexes for which experimental structures are available. We apply these classifiers to the problem of predicting protein and RNA binding sites in the sequence of a clinically important protein for which the structure is not known: the regulatory protein Rev, essential for the replication of HIV-I and other lentiviruses. We compare our predictions with published biochemical, genetic and partial structural information for HIV-1 and EIAV Rev and with our own published experimental mapping of RNA binding sites in EIAV Rev. The predicted and experimentally determined binding sites are in very good agreement. The ability to predict reliably the residues of a protein that directly contribute to specific binding events - without the requirement for structural information regarding either the protein or complexes in which it participates - can potentially generate new disease intervention strategies.

关键词： Binding sites

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Morphing spectral envelopes using audio flow

Morphing spectral envelopes using audio flow

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9th European Conference on Speech Communication and Technology

作者： Ezzat, Tony Meyers, Ethan Glass, Jim Poggio, Tomaso Center for Biological and Computational Learning Massachusetts Institute of Technology Cambridge MA Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology Cambridge MA

We present a method for morphing between smooth spectral magnitude envelopes of speech. An important element of our method is the notion of audio flow, which is inspired by similar notions of optical flow computed between images in computer vision applications. Audio flow defines the correspondence between two smooth spectral magnitude envelopes, and encodes the formant shifting that occurs from one sound to another. We present several algorithms for the automatic computation of audio flow from a small 20 second corpus of speech. In addition, we present an algorithm for morphing smoothly between any two spectral magnitude envelopes, given the computed audio flow between them.

关键词： Speech analysis

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VModel: A visual qualitative modeling environment for middle-school students

VModel: A visual qualitative modeling environment for middle...

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作者： Forbus, Kenneth D. Carney, Karen Sherin, Bruce L. Ureel II, Leo C. Department of Computer Science and Education Northwestern University American Association for Artificial Intelligence Center for the Study of Learning Instruction and Teacher Development University of Illinois Chicago Northwestern University

learning how to create, test, and revise models is a central skill in scientific reasoning. We argue that qualitative modeling provides an appropriate level of representation for helping middle-school students learn to become modelers. We describe Vmodel, a system we have created that uses visual representations and that enables middle-school students to create qualitative models. Software coaches use simple analyses of model structure plus qualitative simulation to provide feedback and explanations. This system has been used in several studies in Chicago public school classrooms, using curricula developed in collaboration with teachers. We discuss the design of the visual representation language, how Vmodel works, and evidence from school studies that indicate it is successful in helping students. Copyright © 2005, American Association for artificial intelligence. All rights reserved.

关键词： learning systems

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Discriminatively Trained Markov Model for Sequence Classification

Discriminatively Trained Markov Model for Sequence Classific...

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Fifth IEEE International Conference on Data Mining

作者： Oksana Yakhnenko Adrian Silvescu Vasant Honavar Artificial Intelligence Research Laboratory Center for Computational Intelligence Learning and Discovery Computer Science Department Iowa State University Ames IA USA

In this paper, we propose a discriminative counterpart of the directed Markov Models of order kappa - 1, or MM(kappa - 1) for sequence classification. MM(kappa - 1) models capture dependencies among neighboring elements of a sequence. The parameters of the classifiers are initialized to based on the maximum likelihood estimates for their generative counterparts. We derive gradient based update equations for the parameters of the sequence classifiers in order to maximize the conditional likelihood function. Results of our experiments with data sets drawn from biological sequence classification (specifically protein function and subcellular localization) and text classification applications show that the discriminatively trained sequence classifiers outperform their generative counterparts, confirming the benefits of discriminative training when the primary objective is classification. Our experiments also show that the discriminatively trained MM(kappa - 1) sequence classifiers are competitive with the computationally much more expensive Support Vector machines trained using kappa-gram representations of sequences.

关键词： Text categorization Proteins artificial intelligence Laboratories Computational intelligence learning computer science Maximum likelihood detection Maximum likelihood estimation Equations

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Language, Cohesion and Form

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丛书名： Studies in Natural Language Processing

2005年

作者： Masterman Margaret

ISBN: (数字)9781316924457

ISBN: (纸本)9780521454896

This volume brings together for the first time the papers of Margaret Masterman, a pioneer in the field of computational linguistics. ;Margaret Masterman was a pioneer in the field of computational linguistics. Working in the earliest days of language processing by computer, she believed that meaning, not grammar, was the key to understanding languages, and that machines could determine the meaning of sentences. She was able, even on simple machines, to undertake sophisticated experiments in machine translation, and carried out important work on the use of semantic codings and thesauri to determine the meaning structure of texts. This volume brings together Masterman's groundbreaking papers for the first time. Through his insightful commentaries, Yorick Wilks argues that Masterman came close to developing a computational theory of language meaning based on the ideas of Wittgenstein, and shows the importance of her work in the philosophy of science and the nature of iconic languages. Of key interest in computational linguistics and artificial intelligence, it will remind scholars of Masterman's significant contribution to the field.

关键词：语言学

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A Contour-Based Moving Object Detection and Tracking

A Contour-Based Moving Object Detection and Tracking

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Joint IEEE International Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance

作者： M. Yokoyama T. Poggio Advanced LSI Design & Development Division SoC Business Center Sony Corporation Tokyo Japan Center for Biological and Computational Learning Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology Cambridge MA USA

We propose a fast and robust approach to the detection and tracking of moving objects. Our method is based on using lines computed by a gradient-based optical flow and an edge detector. While it is known among researchers that gradient-based optical flow and edges are well matched for accurate computation of velocity, not much attention is paid to creating systems for detecting and tracking objects using this feature. In our method, extracted edges by using optical flow and the edge detector are restored as lines, and background lines of the previous frame are subtracted. Contours of objects are obtained by using snakes to clustered lines. Detected objects are tracked, and each tracked object has a state for handling occlusion and interference. The experimental results on outdoor-scenes show fast and robust performance of our method. The computation time of our method is 0.089 s/frame on a 900 MHz processor.

关键词： Object detection Image motion analysis Image edge detection Lighting Optical sensors Optical computing Geophysics computing Robustness Biomedical optical imaging Active contours

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