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Linear and non-linear features for intrapartum cardiotocography evaluation

Linear and non-linear features for intrapartum cardiotocogra...

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Computers in Cardiology (CinC)

作者： Václav Chudáček Jiří Spilka Michal Huptych George Georgoulas Lenka Lhotská Chrysostomos Stylios Michal Koucký Petr Janků Department of Cybernetics Czech Technical University Prague Czech Republic Laboratory of Knowledge and Intelligent Computing TEI Epirus Artas Greece Obstetrics and Gynaecology clinic Charles University Prague Czech Republic Obstetrics and Gynaecology clinic University Hospital Brno Czech Republic

Since 1960's obstetricians have been using cardiotocography (CTG) to detect possible ongoing hypoxia of the fetus. CTG consists of fetal heart rate (fHR) and uterine contraction (TOCO) monitoring. The evaluation of the fHR in clinical settings is ruled by FIGO guidelines, which are based on evaluation of macroscopic morphological features derived from the fHR, such as baseline variability. Although upgrades were proposed to the guidelines - none of them is taking into account results achieved by the adult heart rate variability research. In this work, almost complete set of features previously used for fHR description is investigated and the features are assessed based on their statistical significance in the task of distinguishing the records into three FIGO classes. Inter-correlation of the features is also discussed. We assess the features on a large data set and use expert signal evaluation instead of pH values with the aim to give an overall view of the potential usefulness of the features in the clinical settings. We conclude the paper by presenting the best uncorrected feature subset according to the meta-analysis of three different ranking methods.

关键词： Fetal heart rate Heart rate variability Artificial neural networks Pediatrics Monitoring Correlation Gynecology

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Evolutionary dimensionality reduction for crack localization in ship structures using a hybrid computational intelligent approach

Evolutionary dimensionality reduction for crack localization...

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International Joint Conference on Neural Networks (IJCNN)

作者： Vassilios A. Kappatos George Georgoulas Chrysostomos D. Stylios Evangelos S. Dermatas Electrical Engineering Department University of Patras Rio-Patras Greece Department of Computer Applications in Finance and Management TEI of Ionian Islands Lefkas Greece Laboratory of Knowledge and Intelligent Computing Department of Informatics and Communications Technology TEI Epirus Artas Greece

Acoustic emission (AE) is one of the most important non-destructive testing (NDT) methods for materials and constructions. Using AE testing, the location of a single event (crack) can be classified efficiently into three typical areas in a ship hull. The problem is a typical classification problem based on the use of features extracted from piezo-sensors' signal. As in most classification problems, the extraction and selection of the most appropriate set of features plays a major role in the overall performance of the system. In this research work we investigate the use of an evolutionary algorithm to extract new features from a set of primitive features in a lower dimensional space through a linear transformation. These features are subsequently fed into a probabilistic neural network (PNN) that performs the classification. In simulation experiments, where a stiffened plate model (SPM) is partially sank into water, the localization rate in noisy environments outperforms a work, where a feature selection phase alone was used before the classification phase. The proposed hybrid computational intelligent approach shows the potential merit of using it in real life situations where the signal is distorted by noise.

关键词： Marine vehicles Computational intelligence intelligent structures Competitive intelligence Acoustic testing Feature extraction Working environment noise Acoustic emission Materials testing Nondestructive testing

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Detection of articulation disorders using Empirical Mode Decomposition and neural networks

Detection of articulation disorders using Empirical Mode Dec...

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International Joint Conference on Neural Networks (IJCNN)

作者： George Georgoulas Voula C. Georgopoulos George D. Stylios Chrysostomos D. Stylios Department of Computer Applications in Finance and Management TEI of Ionian Islands Lefkas Greece Department of Speech and Language Therapy TEI of Patras Patras Greece The Laboratory of Knowledge and Intelligent Computing Department of Informatics and Communications Technology TEI Epirus Kostakioi Artas Greece

This paper introduces a novel approach based on signal processing methods to extract features from speech signals and based on them to detect a specific type of articulation disorders. Articulation, in effect, is the specific and characteristic way that an individual produces the speech sounds. Empirical Mode Decomposition and the Hilbert Huang transform are applied to the speech signal in order to calculate the marginal spectrum of the signal. The marginal spectrum is subsequently subject to a mel-cepstrum like processing to extract features which are fed to a neural network classifier responsible for the identification of the articulation disorder. Our preliminary results suggest that this approach is very promising for the detection of the disorder under study.

关键词： Neural networks Signal processing Speech processing Pediatrics Computer errors Feature extraction Computer applications Finance Financial management Speech analysis

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Completeness of Query Operations on Resource Spaces

Completeness of Query Operations on Resource Spaces

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International Conference on Semantics, knowledge and Grid (SKG)

作者： Hai Zhuge Hai Zhuge Erlin Yao Erlin Yao China Knowledge Grid Research Group Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China

A great variety of languages can be designed by different people for different purposes to operate resource spaces. Two fundamental issues are: can we design more operations in addition to existing operations? and, how many operations are sufficient or necessary? This paper solves these problems by investigating the theoretical basis for determining how complete a selection capability is provided in a resource operation sublanguage independent of any host language. The result is very useful to the design and analysis of operating languages.

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A computing Model for Concept Fusing and Document Classification

A Computing Model for Concept Fusing and Document Classifica...

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International Conference on Semantics, knowledge and Grid (SKG)

作者： Nan Zhang Nan Zhang Chao He Chao He China Knowledge Grid Research Group Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China

Effective document classification is a long-pursued goal in knowledge management. This paper proposes a novel hybrid approach of semantic representation and statistical measurements. Document is divided into content segments first. By Formal Concept Analysis (FCA), their semantic links with standard concept identifiers are built up whose weights are calculated statistically. In this way, effective concept fusing and document classification can be achieved. In addition, a semantic overlay for specific documents will be constructed via concept fusing. Experiments show our approach is feasible and effective.

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The knowledge Grid and Its Methodology

The Knowledge Grid and Its Methodology

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International Conference on Semantics, knowledge and Grid (SKG)

作者： Hai Zhuge China Knowledge Grid Research Group Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy and Sciences Beijing China

In the human, society, interconnection environment and systems methodology perspectives, this paper answers the following questions: What are the knowledge Grid and its distinguished features? What are its methodology... 详细信息

关键词： Humans Social network services Environmental economics Biological system modeling Peer to peer computing Grid computing Man machine systems IP networks Semantic Web knowledge management

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R-Chord: A Semantic-based Peer Data Management Model

R-Chord: A Semantic-based Peer Data Management Model

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International Conference on Semantics, knowledge and Grid (SKG)

作者： Jie Liu Hai Zhuge Graduate School of Chinese Academy of Sciences China China Knowledge Grid Research Group Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy and Sciences Beijing China

The key issue of peer data management systems (PDMSs) is how to efficiently organize and manage distributed resources in P2P networks to accurately route queries from the peer initiating the query to appropriate peers to avoid network flooding. This paper proposes a semantic-based PDMS model, called R-Chord, by deploying the resource space model above the Chord overlay for uniformly, normally and effectively organizing and managing resources distributed in P2P networks. Experiments show that, compared to the Chord model, the R-Chord model is more flexible to support semantic-based queries and can significantly decrease the average visiting number of and visiting times on peers for answering queries.

关键词： Resource management Peer to peer computing knowledge management Computer network management Technology management Large-scale systems Relational databases XML Prototypes intelligent networks

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knowledge Energy in knowledge Flow Networks

Knowledge Energy in Knowledge Flow Networks

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International Conference on Semantics, knowledge and Grid (SKG)

作者： Hai Zhuge Weiyu Guo Xiang Li Lianhong Ding China Knowledge Grid Research Group Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China Graduate School of Chinese Academy of Sciences Beijing China Chinese Academy of Sciences Beijing Beijing CN

A knowledge flow is invisible but it plays an important role in ordering knowledge exchange in teamwork. It can help achieve effective team knowledge management by modeling, optimizing, monitoring and controlling the operation of knowledge flow processes. This paper proposes the notion of knowledge energy as the driving cause of forming an autonomous knowledge flow network, and explores the behind principles. Knowing these principles can help team managers and the support systems improve cooperation by monitoring the knowledge energy of nodes, and by evaluating and adjusting knowledge flows. A knowledge flow network management system can be the high layer of the knowledge grid to help improve the efficiency of distributed knowledge-intensive teamwork.

关键词： knowledge management Teamwork intelligent networks Monitoring Energy management Information processing Computers IP networks Prototypes Routing

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An automatic semantic relationships discovery approach 04

An automatic semantic relationships discovery approach

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13th International World Wide Web Conference on Alternate Track, Papers and Posters, WWW Alt. 2004

作者： Zhuge, Hai Zheng, Liping Zhang, Nan Li, Xiang China Knowledge Grid Research Group Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences China

ISBN: (纸本)1581139128

An important obstacle to the success of the Semantic Web is that the establishment of the semantic relationship is labor-intensive. This paper proposes an automatic semantic relationship discovering approach for constructing the semantic link network. The basic premise of this work is that the semantics of a web page can be reflected by a set of keywords, and the semantic relationship between two web pages can be determined by the semantic relationship between their keyword sets. The approach adopts the data mining algorithms to discover the semantic relationships between keyword sets, and then uses deductive and analogical reasoning to enrich the semantic relationships. The proposed algorithms have been implemented. Experiment shows that the approach is feasible.

关键词： Data mining

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Modeling the growth of future web1 13

Modeling the growth of future web1

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13th International World Wide Web Conference on Alternate Track, Papers and Posters, WWW Alt. 2004

作者： Zhuge, Hai Chen, Xue Li, Xiang China Knowledge Grid Research Group Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences China

ISBN: (纸本)1581139128

The future Web can be imagined as a life network consisting of resource nodes and semantic relationship links between them. Any node has a life span from birth -?adding it to the network -?to death -?removing it from the network. Through establishing and investigating two types of models for such a network, we obtain the same scale free distribution of semantic links. Simulations and comparisons validate the rationality of the proposed models.

关键词： Semantic Web

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