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Detecting DNA-binding Domain From Sequence and Secondary Structure Information Using Kernel-based Technique

Detecting DNA-binding Domain From Sequence and Secondary Str...

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2008 3rd International Conference on Intelligent System and knowledge engineering(第三届智能系统与知识工程国际会议)(ISKE 2008)

作者： Wang Fei Chen Lusheng Shanghai key laboratory of Intelligent Information Processing Fudan UniversityPRC Department of Computer Science and EngineeringFudan UniversityPRC Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of EducationJilin Universi

DNA-binding proteins play an important role invarious intra-and extra-cellular *** key in theprotein is DNA-binding region also called DNA-bindingdomain(DBD).However,it is hard to search the DBDsby means of homology search or hidden Markov modelsbecause of a wide variety of the *** this work,we develop a kernel-based machine learning method bycombination of multiple "l-vs-l" binary classifiers forDNA binding domain *** result shows that93.73％ accuracy is achieved for multicategory classifierand no less than 90％ accuracy for each binary *** comparison,our classifier performs better than othermachine learning methods.

关键词： Support vector machines Sequences Hidden Markov models Learning systems DNA knowledge engineering Partial response channels Protein engineering Support vector machine classification Intelligent systems

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Translating Query for Deep Web Using Ontology

Translating Query for Deep Web Using Ontology

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International Conference on computer science and Software engineering

作者： Hao Liang Wanli Zuo Fei Ren Junhua Wang College of Computer Science and Technology Department of Technology Jilin University Changchun Taxation China College of Computer Science and Technology Key Laboratory of Symbol Computation andKnowledge Engineering of the Ministry of Education Jilin University China College of Computer Science and Technology Jilin University Changchun China College of Computer Science and Technology Jilin University Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Changchun China

ISBN: (纸本)9781424439027

The e-commerce information on the surface Web is supported by the Deep Web, which can not be accessed directly by the search engines or the Web crawlers. The only way to access the backend database is through query interface. Extracting valid attributes from the query forms and automatic translating the source query into a target query is a solvable way for addressing the current limitations in accessing Deep Web data sources. To generate a valid query, we have to reconcile the key attributes and their semantic relation. We present our framework to solve the problem. To enrich the set of attributes contained in the semantic form, we use the WordNet as kinds of ontology technique and we try to find the semantic relation of the attributes in the same query from and different forms. Extensive experiments over real-word domains show the utility of our query translation framework.

关键词： Ontologies Databases computer science Educational institutions Search engines Data mining Laboratories knowledge engineering computer science education Crawlers

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Describing low-level image features using the COMM ontology

Describing low-level image features using the COMM ontology

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IEEE International Conference on Image Processing

作者： Miroslav Vacura Vojtech Svatek Carsten Saathoff Thomas Franz Raphael Troncy Prague Department of Information and Knowledge Engineering University of Economics Praque Czech Republic Institute for Computer Science University of Koblenz-Landau ISWeb Group Koblenz Germany CWI Amsterdam Netherlands

We present an innovative approach for storing and processing extracted low-level image features based on current semantic Web technologies. We propose to use the COMM multimedia ontology as a "semantic" alternative to the MPEG-7 standard, which is at the same time largely compliant with it. We describe how COMM can be used directly or through its associated Java API.

关键词： Ontologies MPEG 7 Standard Resource description framework Data mining Semantic Web XML OWL Image segmentation Feature extraction Java

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Distributed cooperative multi-robot path planning using differential evolution

Distributed cooperative multi-robot path planning using diff...

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Congress on Evolutionary Computation

作者： Jayasree Chakraborty Amit Konar Uday K. Chakraborty L.C. Jain Department of Electronics and TeleCommunication Engineering Jadavpur University Kolkata India Department of Computer Science University of Missouri Saint Louis MO USA Knowledge-Based Intelligent Engineering Systems Centre University of South Australia Adelaide SA Australia

This paper provides an alternative approach to the co-operative multi-robot path planning problem using parallel differential evolution algorithms. Both centralized and distributed realizations for multi-robot path planning have been studied, and the performances of the methods have been compared with respect to a few pre-defined yardsticks. The distributed approach to this problem out-performs its centralized version for multi-robot planning. Relative performance of the distributed version of the differential evolution algorithm has been studied with varying numbers of robots and obstacles. The distributed version of the algorithm is also compared with a PSO-based realization, and the results are competitive.

关键词： Robots Collision avoidance Planning Path planning Robot kinematics Distance measurement Trajectory

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Large-scale patent classification with min-max modular support vector machines

Large-scale patent classification with min-max modular suppo...

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International Joint Conference on Neural Networks (IJCNN)

作者： Xiao-Lei Chu Chao Ma Jing Li Bao-Liang Lu Masao Utiyama Hitoshi Isahara Department of Computer Science and Engineering Shanghai Jiaotong University Shanghai China Knowledge Creating Communication Research Center National Institute of Information and Communications Technology Soraku-gun Kyoto Japan

Patent classification is a large-scale, hierarchical, imbalanced, multi-label problem. The number of samples in a real-world patent classification typically exceeds one million, and this number increases every year. An effective patent classifier must be able to deal with this situation. This paper discusses the use of min-max modular support vector machine (M 3 -SVM) to deal with large-scale patent classification problems. The method includes three steps: decomposing a large-scale and imbalanced patent classification problem into a group of relatively smaller and more balanced two-class subproblems which are independent of each other, learning these subproblems using support vector machines (SVMs) in parallel, and combining all of the trained SVMs according to the minimization and the maximization rules. M 3 -SVM has two attractive features which are urgently needed to deal with large-scale patent classification problems. First, it can be realized in a massively parallel form. Second, it can be built up incrementally. Results from experiments using the NTCIR-5 patent data set, which contains more than two million patents, have confirmed these two attractive features, and demonstrate that M 3 -SVM outperforms conventional SVMs in terms of both training time and generalization performance.

关键词： Patents Support vector machines Training Training data Classification algorithms Artificial neural networks Accuracy

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Behavioral analysis of co-operative/competitive antibody dynamics

Behavioral analysis of co-operative/competitive antibody dyn...

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Congress on Evolutionary Computation

作者： Madhumala Ghosh Amit Konar L. C. Jain Uday K. Chakraborty Department of Electronics and Tele-Communication Engineering Jadavpur University Kolkata India Knowledge-Based Intelligent Engineering Systems Centre University of South Australia Adelaide SA Australia Department of Mathematics & Computer Science University of Missouri Saint Louis MO USA

The paper presents an analysis of chaos, limit cycles and stability in the antigen-antibody interactive dynamics. Both cooperation and competition of antibodies are considered in the dynamics. The classical approach of Lyapunov has been employed here for the stability analysis of the dynamics. computer simulations have been undertaken to support the results of the analysis. Both temporal behaviors of the antibodies and their phase portraits have been given to study their chaotic, limit cyclic and stable behavior. Results of stability analysis of the dynamics have been applied in a garbage cleaning problem by a mobile robot.

关键词： Chaos Stability analysis Immune system Dynamics Oscillators Evolutionary computation Limit-cycles

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On the role of pre and post-processing in environmental data mining

On the role of pre and post-processing in environmental data...

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4th Biennial Meeting of International Congress on Environmental Modelling and Software: Integrating sciences and Information Technology for Environmental Assessment and Decision Making, iEMSs 2008

作者： Gibert, Karina Izquierdo, Joaquín Holmes, Geoff Athanasiadis, Ioannis Comas, Joaquim Sànchez-Marrè, Miquel Department of Statistics and Operation Research Technical University of Catalonia Barcelona Catalonia Spain Knowledge Engineering and Machine Learning Group Technical University of Catalonia Barcelona Catalonia Spain Centro Multidisciplinar de Modelación de Fluidos Universidad Politécnica de Valencia Spain Department of Computer Science University of Waikato New Zealand Istituto Dalle Molle di Studi sull'Intelligenza Artificiale Lugano Switzerland University of Girona Spain

ISBN: (纸本)9788476530740

The quality of discovered knowledge is highly depending on data quality. Unfortunately real data use to contain noise, uncertainty, errors, redundancies or even irrelevant information. The more complex is the reality to be analyzed, the higher the risk of getting low quality data. knowledge Discovery from Databases (KDD) offers a global framework to prepare data in the right form to perform correct analyses. On the other hand, the quality of decisions taken upon KDD results, depend not only on the quality of the results themselves, but on the capacity of the system to communicate those results in an understandable form. Environmental systems are particularly complex and environmental users particularly require clarity in their results. In this paper some details about how this can be achieved are provided. The role of the pre and post processing in the whole process of knowledge Discovery in environmental systems is discussed.

关键词： Data mining

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On Human-Machine Interaction during Online Image Classifier Training

On Human-Machine Interaction during Online Image Classifier ...

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International Conference on Computational Intelligence for Modelling, Control and Automation, and International Conference on Intelligent Agents, Web Technologies and Internet Commerce

作者： Edwin Lughofer Jim Smith Praminda Caleb-Solly Muhammad Atif Tahir Christian Eitzinger Davy Sannen Hendrik Van Brussel Department of Knowledge-based Mathematical Systems Johannes Kepler University Linz Austria Department of Computer Science University of the West of England Bristol UK Profactor GmbH Steyr-Gleink Austria Department of Mechanical Engineering Katholieke Universiteit Leuven Leuven(Heverlee) Belgium

This paper considers a number of issues that arise when a trainable machine vision system learns directly from humans, rather than from a "cleaned" data set, i.e. data items which are perfectly labelled with complete accuracy. This is done within the context of a generic system for the visual surface inspection of manufactured parts. The issues treated are relevant not only to wider computer vision applications, but also to classification more generally. Some of these issues arise from the nature of humans themselves: they will be not only internally inconsistent, but will often not be completely confident about their decisions, especially if they are making decisions rapidly. People will also often differ systematically from each other in the decisions they make. Other issues may arise from the nature of the process, which may require the machine learning to have the capacity for real-time, online adaptation in response to users' input. It may be that the users cannot always provide input to a consistent level of detail. We describe how all of these issues may be tackled within a coherent methodology. Using a range of classifiers trained on real data sets from a CD imprint production process, we will present results which show that properly addressing most of these issues may actually lead to improved performance.

关键词： Man machine systems Humans Machine vision Surface treatment Inspection Manufacturing computer vision Application software Machine learning Production

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Adaptive personalization of multimodal vehicular interfaces using a hybrid recommendation approach with fuzzy preferences

Adaptive personalization of multimodal vehicular interfaces ...

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IEEE Symposium on Intelligent Vehicle

作者： Philipp Fischer Michael Cebulla Andre Berton Andreas Nurnberger Sandro Rodriguez Garzon Group Research and Advanced Engineering Department Infotainment & Telematics Daimler AG Ulm Berlin Germany Center for Automotive Information Technology Innovations (DCAITI) Technical University Berlin Germany Department of Knowledge and Language Engineering Faculty of Computer Science Otto-von-Guericke University of Magdeburg Magdeburg Germany

User-adaptive and situation-aware presentation of information on multimodal interfaces is an important research area for coping with the increasing information load on the driver. This paper describes a comprehensive recommendation approach for inferring vague individual preferences under uncertain conditions by using fuzzy preference relations. The approach was applied to rank internet information on a multimodal driver interface in the vehicle. New information gets successively downloaded to the car by using digital media broadcast and the driver can query information (e.g. press review, cheap petrol stations, snow reports) by using natural language queries. Incoming information elements are gradually matched to ontology categories by a fuzzy membership value based on term frequency. User perferences are learned from interaction and recommendations for content items is based on the resulting preference model. Three different types of fuzzy relations are aggregated to an overall preference score: explicit preferences, implicit preferences, and global preferences. The later influence preference values of one driver based on other drivers in vehicular ad-hoc networks. Therefore, the approach is not solely based on the presence of one kind of interaction data. Furthermore, the situation is modeled using the concept of granules and influences the overall preference score.

关键词： Vehicles

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Fuzzy structural algorithms to identify and characterize apnea and hypopnea episodes

Fuzzy structural algorithms to identify and characterize apn...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Abraham Otero Paulo Felix Miguel R. Alvarez Carlos Zamarron Department of Software and Knowledge Engineering University San Pablo CEU Madrid Spain Department of Electronics and Computer Science University of Santiago de Compostela Santiago de Compostela Spain Division of Respiratory Medicine University Hospital Complex of Santiago de Compostela Spain

We present a new automated method to identify apneas and hypopneas and to relate them to the drops in blood oxyhemoglobin saturation that they produce. The algorithm takes advantage of the fuzzy set theory for the representation and manipulation of the vagueness of the medical knowledge on which it is based. Its structural nature allows us to easily modify the morphological detection criteria, and to perform a detailed characterization of the identified events. Based on this proposal, a tool for screening polysomnographic records has been developed. The tool allows the physician to modify the morphological criteria that define apneas, hypopneas, and desaturations as well as to inspect the descriptors that make up their characterization. Using this tool we have analyzed five polysomnographic recordings obtaining an overall correct detection rate of 95%. The false negative rate was 6.6% and the false positive rate was 4.3%.

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