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Ontology repositories: A treasure trove for content ontology design patterns 8

Ontology repositories: A treasure trove for content ontology...

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8th international Workshop on Modular Ontologies, WoMO 2014, Co-located with the 8th international conference on Formal Ontology in Information Systems, FOIS 2014

作者： Hahmann, Torsten National Center for Geographic Information and Analysis School of Computing and Information Science University of Maine OronoME United States

Ontology design patterns (ODPs) are widely accepted as important tools for accelerated design of ontologies. We revisit content patterns (CP), an important class of ODPs, and distinguish two kinds based on their degree of formalization and maturity: conceptual CPs and formalized CPs. We show how formalized CPs and the closely related knowledge patterns have natural equivalents in modular ontology repositories. Common notions of pattern reuse (including specialization, instantiation, and composition) are also expressible as logical relationships in the repository. thereby, ontology repositories support identifying mature formalized CPs and knowledge patterns and support documenting the patterns' reuse.

关键词： Ontology

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Leaf recognition Based on BGP Texture Matching 1

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8th international conference on Intelligent Systems and Knowledge Engineering (ISKE)

作者： Wu, Huisi Pu, Pengtao He, Guoqiang Zhang, Bing Zhao, Feng Shenzhen Univ Coll Comp Sci & Software Engn Shenzhen Peoples R China Shenzhen Univ Landscape Dept Shenzhen Peoples R China Shenzhen Guoyipark Dev Co Ltd Shenzhen Peoples R China

ISBN: (数字)9783642549243

ISBN: (纸本)9783642549243;9783642549236

Automatic leaf recognition has been a hot research topic as digital leaf images capturing becomes more and more convenient and popular, which is also essential for plant education. However, fast and robust automatic recognition for leafs remains a challenging problem. In this paper, we present a novel method for leaf recognition based on texture matching. To measure the similarity of two leaves which normally have different color distributions, lighting distributions, and viewing angles, we use binary Gabor pattern (BGP) matching to efficiently extract the texture feature by transforming an image into a pattern histogram. Support vector machine (SVM) classifier is then used to determine the final recognition results. Due to the robustness of combination of BGP and SVM, our method achieves an average recognition rate of up to 95.2 %.

关键词： Leaf recognition Binary Gabor pattern Rotation invariance

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Complex event service provision and composition based on event pattern matchmaking 14

Complex event service provision and composition based on eve...

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8th ACM international conference on Distributed Event-Based Systems, DEBS 2014

作者： Gao, Feng Curry, Edward Bhiri, Sami INSIGHT at NUI Galway DERI Building Galway Ireland Computer Science Department TELECOM SudParis France

ISBN: (纸本)9781450327374

Service computing has gained great success because it decouples service providers and consumers. Because of this decoupling, it is possible to reuse software applications without knowing their implementation details. However, business applications consuming complex events (and complex event processing systems in general) are not maximising the full benefits from service computing. Current service models are not suitable for describing complex events and the requirements for enabling pattern-based complex event service composition are not fully addressed. In this paper, we propose a complex event service description model that extends OWL-S and captures the exact semantics of complex events, including their patterns and attributes. We propose algorithms to create event service compositions based on event patterns. these algorithms are capable of selecting the composition plans with lowest estimated data traffic demands over the service network. Moreover, we show how to improve the efficiency of event service composition by indexing event patterns. © 2014 ACM.

关键词： Reusability

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Driving Intention Inference Based on Dynamic Bayesian Networks 8

Driving Intention Inference Based on Dynamic Bayesian Networ...

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8th international conference on Intelligent Systems and Knowledge Engineering (ISKE)

作者： Li, Fang Wang, Wuhong Feng, Guangdong Guo, Weiwei Beijing Inst Technol Dept Transportat Engn Beijing 100081 Peoples R China

ISBN: (纸本)9783642549274;9783642549267

Driving intention inference can anticipate the driving risk in advance, drivers have enough time to respond and avoid accident. there are several models for identifying driving intention in recent years. However, these methods infer driving intention without considering the impact of past driver behavior on current station, and only take a few basic factors into account, such as speed, accelerate, etc., which reduce the inference accuracy to some extent. To attack this, a fourstep framework for driving intention inference is proposed. the main contribution includes driving behavior factors selecting analysis which can choose the main impacting factors, and improving the existing inferring model based on pattern recognition method. the improved method can consider the impact of past driver behavior on current station with add Auto-regression (AR). Experiments show that our framework can provide a good result for driving intention, including lane changing and braking intention inference. Moreover, compared to the tradition model, the improved model improves the correct recognition rate.

关键词： Driving intention AR-HMM pattern recognition

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8th IFIP 12 international conference on Intelligent Information Processing, IIP 2014

8th IFIP 12 International Conference on Intelligent Informat...

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8th IFIP international conference on Intelligent Information Processing, IIP 2014

ISBN: (纸本)9783662449790

the proceedings contain 35 papers. the special focus in this conference is on Machine Learning, Data Mining, Web Mining, Multi-agent Systems, Automatic Reasoning, Decision Algorithms, Multimedia pattern recognition and Information Security. the topics include: Semi-paired probabilistic canonical correlation analysis;using bat algorithm with levy walk to solve directing orbits of chaotic systems;complex proteomes analysis using label-free mass spectrometry- based quantitative approach coupled with biomedical knowledge;online migration solver based on instructions statistics;extracting part-whole relations from online encyclopedia;topic detection and evolution analysis on microblog;adaptive mechanism based on shared learning in multi-agent system;an agent-based autonomous management approach to dynamic services;research and application analysis of feature binding mechanism;verification of branch-time property based on dynamic description logic;dynamic description logic based on DL-Lite;formalizing the matrix inversion based on the adjugate matrix in HOL4;a heuristic approach to acquisition of minimum decision rule sets in decision systems;cooperative decision algorithm for time critical assignment without explicit communication;using PDDL to solve vehicle routing problems;automated localization and accurate segmentation of optic disc based on intensity within a minimum enclosing circle;a traffic camera calibration method based on multi-rectangle;a multi-instance multi-label learning framework of image retrieval;the retrieval of shoeprint images based on the integral histogram of the Gabor transform domain;scene classification using spatial and color features;multipath convolutional-recursive neural networks for object recognition;identification of co-regulated gene network by using path consistency algorithm based on gene ontology and efficient integrity protection for P2P streaming.

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A general weighted multi-scale method for improving LBP for face recognition

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8th international conference on Ubiquitous computing and Ambient Intelligence, UCAmI 2014

作者： Wei, Xin Wang, Hui Guo, Gongde Wan, Huan School of Computing and Mathematics University of Ulster at Jordanstown Belfast United Kingdom Key Lab of Network Security and Cryptology School of Mathematics and Computer Science Fujian Normal University China

ISBN: (纸本)9783319131016

LBP (Local Binary pattern) is a popular image descriptor (feature) that has been widely used in face recognition. LBP has some parameters, and different parameter values leads to different LBP feature vectors. In practice usually only one feature vector is used for one image, thus information about image content is not utilised fully by LBP. In this paper a novel way of utilising LBP features more fully is presented. Different LBP feature vectors are extracted for one image, corresponding to different combinations of LBP parameter values. these vectors are weighted and used in a distance function. then the k-nearest neighbour classifier is used. Experiments have been conducted on the AR database. Results show this method does indeed produce better classification performance, suggesting that more information considered this way can have values. © Springer international Publishing Switzerland 2014.

关键词： Face recognition

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DESIGN OF UBIQUITOUS 3D VIRTUAL SPACES: MATCHING WIth BEHAVIOURAL patternS

DESIGN OF UBIQUITOUS 3D VIRTUAL SPACES: MATCHING WITH BEHAVI...

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8th Multi conference on Computer Science and Information Systems (MCCSIS 2014)

作者： Dafoulas, Georgios A. Saleeb, Noha Loomes, Martin Middlesex Univ Sch Sci & Technol Dept Comp Sci London NW4 4BT England

ISBN: (纸本)9789898704115

Numerous studies have recently been directed towards designing and modelling for ubiquitous computing, to attain optimum customization of environments, like social networks, to cater for users' different and specific needs. One rapidly booming group of these social networking environments is 3D Virtual Worlds, which despite emerging predominantly only within the past decade, have attracted millions of socially interacting users. However there is currently scarce research investigating optimum design criteria of 3D virtual spaces for ubiquitous computing and best adaptation to user needs inside these virtual environments. this study aims to bridge this gap in research by proposing a methodology for deriving guidelines for alignment of user behavioural patterns inside 3D virtual worlds with best design principles, which can be used to enhance the 3D environments' spaces and hence augment users' behaviour inside them. this is achieved by conducting experiments on case studies of users' educational and social behavioural patterns inside Second Life, a pronounced representative of 3D virtual environments. Changes in user avatars' diverse behaviours and activities are examined on applying different modifications to the design and modelling of the medium's spaces. thus optimum design guidelines for creating 3D virtual spaces to enhance users' behaviour are derived, consequently realizing an optimised ubiquitous 3D user interface.

关键词： Ubiquitous Environment 3D Virtual World Virtual Space Design User Behaviour pattern 3D Dynamic User Interface 3D Architecture

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Estimating p-values for deviation detection 8

Estimating p-values for deviation detection

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8th IEEE international conference on Self-Adaptive and Self-Organizing Systems (SASO)

作者： Rognvaldsson, thorsteinn Norrman, Henrik Byttner, Stefan Jarpe, Eric Halmstad Univ CAISR S-20118 Halmstad Sweden

ISBN: (纸本)9781479953677

Deviation detection is important for self-monitoring systems. To perform deviation detection well requires methods that, given only "normal" data from a distribution of unknown parametric form, can produce a reliable statistic for rejecting the null hypothesis, i.e. evidence for devating data. One measure of the strength of this evidence based on the data is the p-value, but few deviation detection methods utilize p-value estimation. We compare three methods that can be used to produce p-values: one class support vector machine (OCSVM), conformal anomaly detection (CAD), and a simple "most central pattern" (MCP) algorithm. the SVM and the CAD method should be able to handle a distribution of any shape. the methods are evaluated on synthetic data sets to test and illustrate their strengths and weaknesses, and on data from a real life self-monitoring scenario with a city bus fleet in normal traffic. the OCSVM has a Gaussian kernel for the synthetic data and a Hellinger kernel for the empirical data. the MCP method uses the Mahalanobis metric for the synthetic data and the Hellinger metric for the empirical data. the CAD uses the same metrics as the MCP method and has a k-nearest neighbour (kNN) nonconformity measure for both sets. the conclusion is that all three methods give reasonable, and quite similar, results on the real life data set but that they have clear strengths and weaknesses on the synthetic data sets. the MCP algorithm is quick and accurate when the "normal" data distribution is unimodal and symmetric (with the chosen metric) but not otherwise. the OCSVM is a bit cumbersome to use to create (quantized) p-values but is accurate and reliable when the data distribution is multimodal and asymmetric. the CAD is also accurate for multimodal and asymmetric distributions. the experiment on the vehicle data illustrate how algorithms like these can be used in a self-monitoring system that uses a fleet of vehicles to conduct deviation detection without supervision

关键词： fault tolerant computing learning (artificial intelligence) pattern classification software reliability support vector machines system monitoring CAD method Gaussian kernel Hellinger kernel Hellinger metric MCP algorithm MCP method Mahalanobis metric OCSVM asymmetric distribution city bus fleet conformal anomaly detection deviation detection method k-nearest neighbour nonconformity measure kNN nonconformity measure most central pattern algorithm multimodal distribution normal data distribution normal traffic null hypothesis one class support vector machine p-values estimation quantized p-values real life self-monitoring scenario self-monitoring system shape distribution synthetic data set vehicle data conferences Design automation Histograms Kernel Measurement Training Vehicles Computer-Aided Design normal traffic Fault tolerant computing system monitoring Null hypothesis synthetic data Support Vector Network asymmetric distribution vehicle Software reliability pattern recognition histograms data distribution Kernel p-Value

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proceedings of the 8th international conference on Computer recognition Systems CORES 2013 1

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丛书名： Advances in Intelligent Systems and computing

2013年

作者： Juliusz L. Kulikowski (auth.), Robert Burduk, Konrad Jackowski, Marek Kurzynski, Michał Wozniak, Andrzej Zolnierek (eds.)

ISBN: (数字)9783319009698

ISBN: (纸本)9783319009681;9783319009698

the computer recognition systems are nowadays one of the most promising directions in artificial intelligence. this book is the most comprehensive study of this field. It contains a collection of 86 carefully selected articles contributed by experts of pattern recognition. It reports on current research with respect to both methodology and applications. In particular, it includes the following sections:Biometrics Data Stream Classification and Big Data AnalyticsFeatures, learning, and classifiers Image processing and computer vision Medical applications Miscellaneous applications pattern recognition and image processing in roboticsSpeech and word recognitionthis book is a great reference tool for scientists who deal with the problems of designing computer pattern recognition systems. Its target readers can be the as well researchers as students of computer science, artificial intelligence or robotics.

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8th international conference on Bio-Inspired computing: theories and Applications, BIC-TA 2013

8th International Conference on Bio-Inspired Computing: Theo...

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8th international conference on Bio-Inspired computing: theories and Applications, BIC-TA 2013

ISBN: (纸本)9783642375019

the proceedings contain 148 papers. the special focus in this conference is on Bio-Inspired computing: theories and Applications. the topics include: Application of FDTD and harmony search algorithm for inverse scattering problem;Simulation of space information network SCPS-TP based on OPNET;a local elitism based membrane evolutionary algorithm for point pattern matching;prediction of coal calorific value based on a hybrid linear regression and support vector machine model;A new attempt for satisfiability problem: 3D DNA self-assembly to solve SAT problem;study of bookkeeping in the small and medium-sized enterprise;towards the development of a framework of organizational performance integrating information resource allocation and organizational change in China;New ideas for FN/RFN queries based nearest voronoi diagram;video summarization by robust low-rank subspace segmentation;kernel optimal unsupervised discriminant projection and its application to face recognition;nanostructure thin-film removal via a cylinders tool for computer touch sensing material;Research on cow epidemic monitor system based on ArcGIS engine;application of dual bilinear interpolation fuzzy algorithm in fan speed control;research on credibility of web service composition based on stochastic Petri net;Based on DNA self-assembled computing to solve MH knapsack public key cryptosystems of the knapsack problem;image representation and recognition based on directed complex network model;finite element analysis and computation of the reinforcement effect and mechanism of the ventilation roadway U-type arch;Fast distributed BFS solution for edge-disjoint paths;Stock price forecast using tree augmented Naïve (TAN) bayes;the binary anti-collision algorithm based on labeled packet.

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