Publications

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Analysis of visual field and reaction time in correlation with the vigilance decreasing

MATOUŠEK, V., MOUČEK, R., MAUTNER, P. Analysis of visual field and reaction time in correlation with the vigilance decreasing. In Reliability of driver car interaction. Praha : UI AVČR, ČVUT Praha, 2011, s. 110-153. ISBN: 978-80-87136-12-6
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The book describes many aspects of the reliability of interactions among drivers and their vehicles; this reliability attracts the interest of researchers in many countries for a long time. The field of driver-car interaction reliability involves extremly wide spectrum of aspects concerning many areas of science and technology. Therefore a well cooperated group of specialists of 11 Czech universities, research institutes and industrial companies was estabilished with the aim to solve the main problems of the interaction reliability between road vehicle and its driver. The knowledge reached in this area are presented in this book and it will be very useful for all people who will continue in this research.

EEG data formats converting tool

MOUČEK, R., STRBAČKA, M. EEG data formats converting tool. 2011.
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The sample product enables mutual conversion of the following EEG data formats - EDF, Brain Vision and KIV. The software, implemented in Java, is used as a standalone product and as a library suitable for integration into the EEG signal processing software. Conversion and mutual compatibility of EEG data formats is one of the solutions to standardize electrophysiological data that is addressed in the INCF (International Neuroinformatics Coordinating Facility) electrophysiology Task Force - http://datasharing.incf.org/ep/Converters. The software was presented in the paper Roman Mouček, Petr Ježek: Overview of neuroinformatics infrastucture in Pilsen, CZ, 4th Congress of Neuroinfomatics, 2011, Boston, USA. The user manual for the product is in the attached file manual.pdf.

Processing and Categorization of Czech Written Documents Using Neural Networks

MAUTNER, P., MOUČEK, R. Processing and Categorization of Czech Written Documents Using Neural Networks. Neural Network World, 2012, roč. 22, č. 1, s. 53-66. ISSN: 1210-0552
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The Kohonen Self-organizing Feature Map (SOM) has been developed for clustering input vectors and for projection of continuous high-dimensional signal to discrete low-dimensional space. The application area, where the map can be also used, is the processing of text documents. Within the project WEBSOM, some methods based on SOM have been developed. These methods are suitable either for text documents information retrieval or for organization of large document collections. All methods have been tested on collections of English and Finnish written documents. This article deals with the application of WEBSOM methods to Czech written documents collections. The basic principles of WEBSOM methods, transformation of text information into the real components feature vector and results of documents classification are described. The Carpenter-Grossberg ART-2 neural network, usually used for adaptive vector clustering, was also tested as a document categorization tool. The results achieved by using this network are also presented.

Semantic Framework

JEŽEK, P., MOUČEK, R., KRAUZ, J. Semantic Framework. 2012.
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Because the Semantic Web uses its technologies for presenting data/metadata on the web and common systems are based on object-oriented languages a need for suitable mapping is emerging. This software solves the difficulties during transformation of data layer represented by object-oriented code into the semantic web structures (OWL, RDF). Since there is difference between semantic expressivity of these data representations it is necessary to fill this semantic gap. The software solves these differences in semantics and provide a possibility to add missing semantics into the Java code using Java annotations. These annotations are consequently processed by the proposed framework.

EEG Data Processor - Framework for Running Signal Processing Methods

JEŽEK, P., MOUČEK, R., MIKO, P., MARKVART, F., KOREŇ, J., KOLENA, J. EEG Data Processor - Framework for Running Signal Processing Methods. 2012.
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This software solves difficulties related to running of signal processing methods. Although several systems that implement signal processing methods exist, their sharing and remote calling is not satisfactorily solved. This software is a custom server-side approach that provides a powerful plug-in engine for integration of signal processing methods. The plug-in engine ensures high modularity and flexibility of the system. Since the implemented methods are accessible via the SOAP Web Service, integration with another system is available. There is also possible to use the system locally via a web browser. The set of basic methods is already implemented.

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