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作者： Sanz, Pedro J. Prats, Mario Ridao, Pere Ribas, David Oliver, Gabriel Ortiz, Alberto Computer Science and Engineering Dpt. Universitat Jaume i Castellon Spain Computer Engineering Dpt. Universitat de Girona Spain Math. and Computer Science Dpt. Universitat de les Illes Balears Palma de Mallorca Spain

ISBN: (纸本)9789537044114

Starting in January 2009, the RAUVI project is a three years coordinated research action funded by the Spanish Ministry of Research and Innovation. This paper shows the research evolution during the first half of RAUVI's live, bearing in mind that the long term objective is to design and develop an underwater autonomous robot able to perceive the environment and, by means of a specific hand-arm system, perform autonomously simple intervention tasks in shallow waters.

关键词： Human robot interaction

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Grid computing and CBR deployment: Monitoring principles for a suitable engagement

Grid computing and CBR deployment: Monitoring principles for...

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9th International Conference on Distributed Computing and Artificial Intelligence, DCAI 2012

作者： Castillo, Luis F. Isaza, Gustavo Bedia, Manuel Glez Aguilera, Miguel Correa, Juan David Universidad Nacional de Colombia Industrial Engineering Dpt. Bogotá Colombia Universidad de Caldas Computer Science and Systems Engineering Dpt. Manizales Colombia Universidad de Zaragoza Computer Science Dpt. Saragossa Spain Universidad Autónoma de Manizales Systems Engineering Manizales Colombia

ISBN: (纸本)9783642287640

This paper presents a mathematical technique for modeling the generation of Grid-solutions employing a Case based reasoning system (CBR). Roughly speaking, an intelligent system that tries to be adapted to highly dynamic environment needs an efficient integration of high-level processes (deliberative and time-costly) within low-level (reactive, faster but poorer in quality) processes. The most relevant aspect of our current approach is that, unexpectedly, the performance of the CBR-system do not get worse any time that it retrieves worse cases in situations even when it has enough time to generate better solutions. We concentrate on formal aspects of the proposed Grid-CBR system without establishing which should be the most adequate procedure in a subsequent implementation stage. The advantage of the presented scheme is that it does not depend on neither the particular problem nor a concrete environment. It consists in a formal approach that only requires, on one hand, local information about the averaged-time spent by the system in obtaining a solution and, on the other hand, an estimation about their temporal restrictions. The potential use of industry standard technologies to implement such a Grid-enabled CBR system is discussed here too. © 2012 Springer-Verlag.

关键词： Grid computing

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Reasoning in fuzzy OWL 2 with delorean

Reasoning in fuzzy OWL 2 with delorean

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6th International Workshop on Uncertainty Reasoning for the Semantic Web, URSW 2010, Held as Part of the 9th International Semantic Web Conferences, ISWC 2010 and 1st International Workshop on Uncertainty in Description Logics, UniDL2010

作者： Bobillo, Fernando Delgado, Miguel Gómez-Romero, Juan Dpt. of Computer Science and Systems Engineering University of Zaragoza Spain Dpt. of Computer Science and Artificial Intelligence University of Granada Spain Applied Artificial Intelligence Group University Carlos III Madrid Spain

ISBN: (纸本)9783642359743

Classical ontologies are not suitable to represent imprecise or vague information, which has led to several extensions using non-classical logics. In particular, several fuzzy extensions have been proposed in the literature. In this paper, we present the fuzzy ontology reasoner DeLorean, the first to support a fuzzy extension of OWL 2. We discuss how to use it for fuzzy ontology representation and reasoning, and describe some implementation details and optimization techniques. An empirical evaluation demonstrates that these optimizations considerably improve the performance of the reasoner. © 2013 Springer-Verlag Berlin Heidelberg.

关键词： Ontology

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A personalized audio server using MPEG-7 and MPEG-21 standards

A personalized audio server using MPEG-7 and MPEG-21 standar...

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5th International Workshop on Semantic Media Adaptation and Personalization, SMAP 2010

作者： Skondras, Emmanouil Michalas, Angelos Louta, Malamati Anagnostopoulos, Ioannis Dpt. of Informatics and Computer Technology Technological Educational Institute of Western Macedonia 52100 Kastoria Greece Dpt. of Informatics and Telecommunications Engineering University of Western Macedonia 50100 Kozani Greece Dpt. of Computer Science and Biomedical Informatics University of Central Greece 35100 Lamia Greece

ISBN: (纸本)9781424486007

This paper presents a semantic model which delivers personalized audio information. The personalization process is automated and decentralized. The metadata which support personalization are separated in two categories: the metadata describing user preferences stored at each user and the resource adaptation metadata stored at the server. The multimedia models MPEG-21 and MPEG-7 are used to describe metadata information. The Web Ontology Language (OWL) language is used to produce and manipulate the relative ontological descriptions. © 2010 IEEE. © 2010 IEEE.

关键词： Metadata

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Interoperability for embedded systems in JFML software: An Arduino-based implementation

Interoperability for embedded systems in JFML software: An A...

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2018 IEEE International Conference on Fuzzy Systems, FUZZ 2018

作者： Arcos, Francisco Jesús Soto-Hidalgo, José Manuel Vitiello, Autilia Acampora, Giovanni Alcalá-Fdez, Jesús Dpt. of Computer Science and A.I. University of Granada Granada18071 Spain Dpt. of Electronics and Computer Engineering University of Córdoba Córdoba Spain Department of Computer Science University of Salerno Salerno Italy Dpt. of Physics Ettore Pancini University of Naples Federico II Naples Italy

ISBN: (纸本)9781509060207

Fuzzy Logic Systems have been successfully used in a wide range of real-world problems. They can include a priori expert knowledge and represent systems for which it is not possible to obtain a mathematical model. The standard IEEE Std 1855TM-2016 was established to provide the fuzzy community with a unique and well-defined tool allowing a fuzzy logic system design completely independent from the specific hardware/software. Recently, the library Java Fuzzy Markup Language (JFML) offers a complete implementation of the standard, however, the actual version of the JFML does not support the development of fuzzy inference systems on specific types of hardware. The aim of this paper is to develop an interoperability module to design and running FLS for embedded systems in JFML, concretely for Arduino boards. In addition, a communication protocol between JFML and Arduino boards is also defined, removing the limited computing capacity usually offered by embedded systems. A case study with a wall-following fuzzy controller to manage a mobile robotic in two environments is developed in order to illustrate the potential of the new interoperability module. © 2018 IEEE.

关键词： Open source software

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Enhancing Concept Drift Detection in Drifting and Imbalanced Data Streams through Meta-Learning

Enhancing Concept Drift Detection in Drifting and Imbalanced...

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2023 IEEE International Conference on Big Data, BigData 2023

作者： Aguiar, Gabriel Jonas Cano, Alberto Virginia Commonwealth University Dpt. of Computer Science College of Engineering RichmondVA United States

ISBN: (纸本)9798350324457

One of the biggest challenges in learning from data streams is adapting the classification model to new data. Due to the evolving nature of data streams, they are subject to a phenomenon known as concept drift that makes previously learned knowledge and model outdated. Therefore, concept drift must be efficiently detected in order to adapt the classification model. While there exists a plethora of drift detectors, with different mechanisms, selecting the most suitable for a new stream is a difficult task, since apriori knowledge may not be available and changes over time can affect the performance of the detector. This paper proposes a framework that exploits statistical and temporal meta-features from sliding windows to dynamically recommend a suitable drift detector in real-time for unseen chunks of streams according to its properties using Meta-Learning. We performed experiments on 10 real-world data streams and 18 synthetic generated data streams that were subject to concept drift and class imbalance in order to evaluate the performance of the proposed framework. Experiments exposed that the proposed approach was able to enhance the concept drift detection in a variety of scenarios demonstrating robustness to class imbalance and the advantages of dynamically selecting the drift detector. © 2023 IEEE.

关键词： Concept Drift Data streams Machine Learning Meta-Learning

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Fuzzy ontologies and fuzzy integrals

Fuzzy ontologies and fuzzy integrals

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2011 11th International Conference on Intelligent Systems Design and applications, ISDA'11

作者： Bobillo, Fernando Straccia, Umberto Dpt. of Computer Science and Systems Engineering University of Zaragoza Spain ISTI - CNR Pisa Italy

ISBN: (纸本)9781457716751

Fuzzy ontologies extend classical ontologies to allow the representation of imprecise and vague knowledge. Although a relatively important amount of work has been carried out in the last years and they have been successfully used in several applications, several notions from fuzzy logic, such as fuzzy integrals, have not been considered yet in fuzzy ontologies. In this work, we show how to support fuzzy integrals in fuzzy ontologies. As a theoretical formalism, we provide the syntax and semantics of a fuzzy Description Logic with fuzzy integrals. We also provide a reasoning algorithm for a family of fuzzy integrals and show how to encode them into the language Fuzzy OWL 2. © 2011 IEEE.

关键词： Fuzzy logic

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Block operator context scanning for commercial tracking

Block operator context scanning for commercial tracking

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7th Hellenic Conference on Artificial Intelligence, SETN 2012

作者： Giannoukos, Ioannis Vrachnakis, Vassilis Anagnostopoulos, Christos-Nikolaos Anagnostopoulos, Ioannis Loumos, Vassili Electrical and Computer Engineering School National Technical University of Athens Greece Cultural Technology and Communication Dpt. University of the Aegean Greece Computer Science and Biomedical Informatics Dpt. University of Central Greece Greece

ISBN: (纸本)9783642304477

The industry that designs and promotes advertising products in television channels is constantly growing. For effective market analysis and contract validation, various commercial tracker systems are employed. However, these systems mostly rely on heuristics and, since commercial broadcasting varies significantly, are often inaccurate. This paper proposes a commercial tracker system based on the Block Operator Context Scanning (Block - OCS) algorithm, which is both accurate and fast. The proposed method, similar to coarse-to-fine strategies, skips a large portion of the image sequences by focusing only on Regions of Interest. In this paper, a video matching algorithm is also proposed, which compares image sequences using time sliding windows of frames. Experimental results showed 100% accuracy and 50% speed increase compared to traditional block-based processing methods. © 2012 Springer-Verlag.

关键词： Scanning

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Mercury: Combining performance with dependability using self-virtualization

Mercury: Combining performance with dependability using self...

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36th International Conference on Parallel Processing in Xi'an, ICPP

作者： Chen, Haibo Chen, Rong Zhang, Fengzhe Zang, Binyu Yew, Pen-Chung Parallel Processing Institute Fudan University Dpt. of Computer Science and Engineering University of Minnesota at Twin-Cities

ISBN: (纸本)076952933X

There has recently been increasing interests in using system virtualization to improve the dependability of HPC cluster systems. However, it is not cost-free and may come with some performance degradation, uncertain QoS and loss of functionalities. Meanwhile, many virtualization-enabled features such as online maintenance and fault tolerance do not require virtualization being always on. This paper proposes a technique, called self-virtualization, that supports dynamically attaching and detaching a full-fledged virtual machine monitor (VMM) beneath an operating system, without disturbing applications thereon, and rid the system of potential overhead when the virtualization is not needed. This technique enables HPC clusters to reap most benefits from virtualization without sacrificing performance. This paper presents the design and implementation of Mercury, a working prototype based on Linux and Xen VMM. Our performance measurement shows that Mercury incurs very little overhead: about 0.2 ms to complete a mode switch, and negligible performance degradation compared to Linux. © 2007 IEEE.

关键词： Virtualization

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EEG time series learning and classification using a hybrid forecasting model calibrated with GVNS

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Electronic Notes in Discrete Mathematics 2017年 58卷 79-86页

作者： Coelho, V.N. Coelho, I.M. Coelho, B.N. Souza, M.J.F. Guimarães, F.G. Luz, E.J. da S. Barbosa, A.C. Coelho, M.N. Netto, G.G. Costa, R.C. Pinto, A.A. Figueiredo, A. de P. Elias, M.E.V. Filho, D.C.O.G. Oliveira, T.A. Grupo da Causa Humana Ouro Preto Brazil Instituto de Pesquisa e Desenvolvimento de Tecnologias Ouro Preto Brazil Dpt. of Computer Science at Universidade Estadual do Rio de Janeiro Brazil Dpt. of Computer Science at Universidade Federal de Ouro Preto Brazil Dpt. of Electrical Engineering at Universidade Federal de Minas Gerais Brazil

Brain activity can be seen as a time series, in particular, electroencephalogram (EEG) can measure it over a specific time period. In this regard, brain fingerprinting can be subjected to be learned by machine learning techniques. These models have been advocated as EEG-based biometric systems. In this study, we apply a recent Hybrid Focasting Model, which calibrates its if-then fuzzy rules with a hybrid GVNS metaheuristic algorithm, in order to learn those patterns. Due to the stochasticity of the VNS procedure, models with different characteristics can be generated for each individual. Some EEG recordings from 109 volunteers, measured using a 64-channels EEGs, with 160 HZ of sampling rate, are used as cases of study. Different forecasting models are calibrated with the GVNS and used for the classification purpose. New rules for classifying the individuals using forecasting models are introduced. Computational results indicate that the proposed strategy can be improved and embedded in the future biometric systems. © 2017 Elsevier B.V.

关键词： Biometrics Brain fingerprinting Electroencephalogram Forecasting and Time series Variable Neighborhood Search

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