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Algebraic analysis of the computation in the Belousov-Zhabotinksy reaction

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9th International Conference on Information Processing in Cells and Tissues, IPCAT 2012

作者： Dini, Paolo Nehaniv, Chrystopher L. Egri-Nagy, Attila Schilstra, Maria J. Royal Society Wolfson BioComputation Research Lab. Centre for Computer Science and Informatics Research University of Hertfordshire United Kingdom Department of Media and Communications London School of Economics and Political Science London United Kingdom School of Computing and Mathematics University of Western Sydney Parramatta NSW Australia

ISBN: (纸本)9783642287916

We analyse two very simple Petri nets inspired by the Oregonator model of the Belousov-Zhabotinsky reaction using our stochastic Petri net simulator. We then perform the Krohn-Rhodes holonomy decomposition of the automata derived from the Petri nets. The simplest case shows that the automaton can be expressed as a cascade of permutation-reset cyclic groups, with only 2 out of the 12 levels having only trivial permutations. The second case leads to a 35-level decomposition with 5 different simple non-abelian groups (SNAGs), the largest of which is A 9. Although the precise computational significance of these algebraic structures is not clear, the results suggest a correspondence between simple oscillations and cyclic groups, and the presence of SNAGs indicates that even extremely simple chemical systems may contain functionally complete algebras. © 2012 Springer-Verlag.

关键词： Petri nets

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A shape enhancement technique based on multi-channel salience measure

A shape enhancement technique based on multi-channel salienc...

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1st International Conference on Computational Visual Media, CVM 2012

作者： Miao, Yongwei Feng, Jieqing Wang, Jinrong Pajarola, Renato College of Computer Science and Technology Zhejiang University of Technology Hangzhou 310023 China State Key Lab. of CAD and CG Zhejiang University Hangzhou 310027 China Department of Informatics University of Zürich Zürich CH-8050 Switzerland

ISBN: (纸本)9783642342622

In this paper, we develop a novel visual saliency based shape enhancement technique for relief surfaces. It consists of three steps. Firstly, we calculate the multi-channel salience map of the underlying shape by combining three feature maps, i.e., the feature map of local height distribution, normal difference, and mean curvature variation. Secondly, we manipulate the original relief surface by a salience-domain shape manipulation function. Finally, we adjust surface normals of the original shape as the corresponding final normals of the manipulated surface. The experimental results show that our proposed algorithm can adjust the shading of the original shape and thus for improving its shape depiction. © 2012 Springer-Verlag.

关键词： computers

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Querying representative points from a pool based on synthesized queries

Querying representative points from a pool based on synthesi...

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International Joint Conference on Neural Networks

作者： Xuelei Hu Liantao Wang Bo Yuan School of Computer Science and Technology Nanjing University of Science and Technology Intelligent Computing Lab Division of Informatics Graduate School at Shenzhen Tsinghua University

ISBN: (纸本)9781467314886

How to build a compact and informative training data set autonomously is crucial for many real-world learning tasks, especially those with large amount of unlabeled data and high cost of labeling. Active learning aims to address this problem by asking queries in a smart way. Two main scenarios of querying considered in the literature are query synthesis and pool-based sampling. Since in many cases synthesized queries are meaningless or difficult for human to label, more efforts have been devoted to pool-based sampling in recent years. However, in pool-based active learning, querying requires evaluating every unlabeled data point in the pool, which is usually very time-consuming. By contrast, query synthesis has clear advantage on querying time, which is independent of the pool size. In this paper, we propose a novel framework combining query synthesis and pool-based sampling to accelerate the learning process and overcome the current limitation of query synthesis. The basic idea is to select the data point nearest to the synthesized query as the query point. We also provide two simple strategies for synthesizing informative queries. Moreover, to further speed up querying, we employ clustering techniques on the whole data set to construct a representative unlabeled data pool based on cluster centers. Experiments on several real-world data sets show that our methods have distinct advantages in time complexity and similar performance compared to pool-based uncertainty sampling methods.

关键词： Uncertainty Accuracy Approximation algorithms Learning systems Humans Nearest neighbor searches Educational institutions

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Combining free-word search and relational databases

Combining free-word search and relational databases

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6th IASTED International Conference on Software Engineering and Applications, SEA 2002

作者： Hassan, M. Alhajj, R. Ridley, M.J. School of Informatics Bradford University Bradford West Yorkshire BD7 1DP United Kingdom ADSA Lab Department of Computer Science University of Calgary Calgary AB T2N 1N4 Canada

ISBN: (纸本)0889863237

Several approaches have been proposed for bridging the gap between structured relational databases and keyword search. However, it has not been clearly shown how both features can be combined. In this paper, we describe a tool that provides a simple and direct technique for freeword search to query relational databases. Our approach allows a uniform search technique for the products of both Web designers and database developers, published on the Web. The developed system enables end users to explore a structured database using free form language (words) queries in a fashion similar to using search engines to search text files on the Web. It can be used in both Internet and Intranet application areas.

关键词： Search engines

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Learning sentiments from tweets with personal health information

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25th Canadian Conference on Artificial Intelligence, AI 2012

作者： Bobicev, Victoria Sokolova, Marina Jafer, Yasser Schramm, David Department of Applied Informatics Technical University of Moldova Moldova Electronic Health Information Lab. CHEO Research Institute Canada School of Electrical Engineering and Computer Science University of Ottawa Ottawa ON Canada Faculty of Medicine University of Ottawa Ottawa ON Canada Children's Hospital of Eastern Ontario Canada

ISBN: (纸本)9783642303524

We present results of sentiment analysis in Twitter messages that disclose personal health information. In these messages (tweets), users discuss ailment, treatment, medications, etc. We use the author-centric annotation model to label tweets as positive sentiments, negative sentiments or neutral. The results of the agreement among three raters are reported and discussed. We then use Machine Learning methods on multi-class and binary classification of sentiments. The obtained results are comparable with previous results in the subjectivity analysis of user-written Web content. © 2012 Springer-Verlag.

关键词： Sentiment analysis

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AUDIO-VISUAL SPEECH RECOGNITION INCORPORATING FACIAL DEPTH INFORMATION CAPTURED BY THE KINECT

AUDIO-VISUAL SPEECH RECOGNITION INCORPORATING FACIAL DEPTH I...

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European Signal Processing Conference

作者： Georgios Galatas Gerasimos Potamianos Fillia Makedon Institute of Informatics and Telecommunications NCSR "Demokritos" Dept. of Computer and Communication Engin. University of Thessaly Heracleia Lab. Dept. of Computer Science and Engin. University of Texas at Arlington

ISBN: (纸本)9781467310680

We investigate the use of facial depth data of a speaking subject, captured by the Kinect device, as an additional speech-informative modality to incorporate to a traditional audiovisual automatic speech recognizer. We present our feature extraction algorithm for both visual and accompanying depth modalities, based on a discrete cosine transform of the mouth region-of-interest data, further transformed by a two-stage linear discriminant analysis projection to incorporate speech dynamics and improve classification. For automatic speech recognition utilizing the three available data streams (audio, visual, and depth), we consider both the feature and decision fusion paradigms, the latter via a state-synchronous tri-stream hidden Markov model. We report multi-speaker recognition results on a small-vocabulary task employing our recently collected bilingual audio-visual corpus with depth information, demonstrating improved recognition performance by the addition of the proposed depth stream, across a wide range of audio conditions.

关键词： Audio-visual automatic speech recognition Depth information Multi-sensory fusion Linear discriminant analysis Microsoft Kinect Speech recognition discrete cosine transforms Visualization Feature extraction Audio mouth structures game player

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IC-DEEP: A serious games based application to assess the ergonomics of In-Vehicle Information Systems

IC-DEEP: A serious games based application to assess the erg...

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International IEEE Conference on Intelligent Transportation Systems

作者： Joel Goncalves Rosaldo J. F. Rossetti Cristina Olaverri-Monreal Department of Informatics Engineering and the Artificial Intelligence and Computer Science Lab (LIACC) Faculty of Engineering University of Porto Institute of Ergonomics Faculty of Mechanical Engineering Technische Universitat Munchen

ISBN: (纸本)9781467330640

With the number of in-vehicle information systems and the complexity of their tasks growing at a very high rate in near future, we need a clear understanding of their related distraction or mental workload and its impact on driver performance. Thus, in this paper we introduce these concepts already in the development phase of a product that will be used in an in-vehicle environment. We present the IC-DEEP (In-Car Ergonomics Evaluation Platform), which is an implementation approach in form of a Serious Game (SG) to autonomously assess, under low-time and low-cost conditions, the factors that can jeopardize the driving performance when manipulating or receiving information from in-vehicle information systems (IVISs). We evaluate the feasibility of the proposed approach and draw conclusions on its effects on behavioral changes and IVIS assessment.

关键词： Vehicles Games Usability Measurement Information systems Context Training

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A Possibilistic Approach for the Automatic Morphological Disambiguation of Arabic Texts

A Possibilistic Approach for the Automatic Morphological Dis...

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ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing (SNPD)

作者： Raja Ayed Ibrahim Bounhas Bilel Elayeb Fabrice Evrard Narjès Bellamine Ben Saoud RIADI Laboratory The National School of Computer Science Manouba University Tunisia Department of Computer Science Faculty of Sciences of Tunis Tunis Tunisia Informatics Research Institute of Toulouse Toulouse France RIADI Lab. Manouba Univ. Manouba Tunisia

This paper presents a new approach for Arabic non-vocalized texts disambiguation based on a possibilistic classifier. A morphological analyzer provides all the possible solutions and the values of the morphological features of words. When texts are vocalized, the number of solutions is reduced and in many cases, we can identify the correct analysis of the input word. The main idea of this paper is to exploit this type of texts in order to learn contextual dependencies between the different values of morphological features modeled as a possibilistic network. This knowledge is used later to disambiguate non-vocalized texts. In order to evaluate our approach, we perform experiments on a corpus of arabic stories. In this paper, we present results concerning the Part-Of-Speech (POS) which is the main morphological feature. Our results are compared to the SVM-based system called MADA.

关键词： Training Possibility theory Pragmatics Uncertainty Educational institutions Testing

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On the proactive and interactive visualization for feature evolution comprehension: An industrial investigation 12

On the proactive and interactive visualization for feature e...

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International Conference on Software Engineering (ICSE)

作者： Renato Novais Camila Nunes Caio Lima Elder Cirilo Francisco Dantas Alessandro Garcia Manoel Mendonça Software Engineering Lab Computer Science Department Federal University of Bahia Bahia Brazil Opus Research Group Software Engineering Lab Informatics Department PUC-Rio Rio de Janeiro Brazil

ISBN: (纸本)9781467310673

Program comprehension is a key activity through maintenance and evolution of large-scale software systems. The understanding of a program often requires the evolution analysis of individual functionalities, so-called features. The comprehension of evolving features is not trivial as their implementations are often tangled and scattered through many modules. Even worse, existing techniques are limited in providing developers with direct means for visualizing the evolution of features' code. This work presents a proactive and interactive visualization strategy to enable feature evolution analysis. It proactively identifies code elements of evolving features and provides multiple views to present their structure under different perspectives. The novel visualization strategy was compared to a lightweight visualization strategy based on a tree-structure. We ran a controlled experiment with industry developers, who performed feature evolution comprehension tasks on an industrial-strength software. The results showed that the use of the proposed strategy presented significant gains in terms of correctness and execution time for feature evolution comprehension tasks.

关键词： Visualization Color Industries Software systems History Context

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Reports of the AAAI 2011 conference workshops

Reports of the AAAI 2011 conference workshops

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作者： Agmon, Noa Agrawal, Vikas Aha, David W. Aloimonos, Yiannis Buckley, Donagh Doshi, Prashant Geib, Christopher Grasso, Floriana Green, Nancy Johnston, Benjamin Kaliski, Burt Kiekintveld, Christopher Law, Edith Lieberman, Henry Mengshoel, Ole J. Metzler, Ted Modayil, Joseph Oard, Douglas W. Onder, Nilufer O'Sullivan, Barry Pastra, Katerina Precup, Doina Ramachandran, Sowmya Reed, Chris Sariel-Talay, Sanem Selker, Ted Shastri, Lokendra Singh, Satinder Smith, Stephen F. Srivastava, Siddharth Sukthankar, Gita Uthus, David C. Williams, Mary-Anne Department of Computer Science University of Texas at Austin United States Center for Knowledge Driven Information Systems Infosys Labs India Adaptive Systems Section Naval Research Laboratory Washington DC United States Department of Computer Science University of Maryland College Park United States EMC's Center of Excellence in Ireland Research Europe at EMC Ireland Department of Computer Science University of Georgia United States School of Informatics University of Edinburgh United Kingdom Department of Computer Science University of Liverpool United Kingdom Department of Computer Science University of North Carolina Greensboro United States Faculty of Engineering and Information Technology University of Technology Sydney Australia VeriSign Inc. United States Department of Computer Science University of Texas at El Paso United States Machine Learning Department Carnegie Mellon University United States Massachusetts Institute of Technology Media Laboratory United States Carnegie Mellon University's Silicon Valley Campus United States Darrell W. Hughes Program for Religion and Science Dialogue Oklahoma City University United States Department of Computing Science University of Alberta Canada College of Information Studies Institute for Advanced Computer Studies University of Maryland College Park United States Department of Computer Science Michigan Technological University United States Department of Computer Science University College Cork Ireland Cognitive Systems Research Insitute Athens Greece School of Computer Science McGill University Canada Stottler Henke Inc. United States School of Computing University of Dundee United Kingdom Department of Computer Engineering Istanbul Technical University Turkey Convergence Lab Infosys Technologies Ltd. United States Department of Electrical Engineering and Computer Science University of Michigan Ann Arbor United States Robotics Institute Carnegie Mellon University United States University of Wisconsin

The AAAI-11 workshop program was held Sunday and Monday, August 7-18, 2011, at the Hyatt Regency San Francisco in San Francisco, California USA. The AAAI-11 workshop program included 15 workshops covering a wide range of topics in artificial intelligence. The titles of the workshops were Activity Context Representation: Techniques and Languages;Analyzing Microtext;Applied Adversarial Reasoning and Risk Modeling;Artificial Intelligence and Smarter Living: The Conquest of Complexity;Artifiicial Intelligence for Data Center Management and Cloud Computing;Automated Action Planning for Autonomous Mobile Robots;Computational Models of Natural Argument;Generalized Planning;Human Computation;Human-Robot Interaction in Elder Care;Interactive Decision Theory and Game Theory, 2010;Language-Action Tools for Cognitive Artificial Agents: Integrating Vision, Action, and Language;Lifelong Learning from Sensorimotor Experience;Plan, Activity, and Intent Recognition;and Scalable Integration of Analytics and Visualization. This article presents short summaries of those events. Copyright © 2012, Association for the Advancement of Artificial Intelligence. All rights reserved.

关键词： Human robot interaction

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