On using Unitary Matrices for the Investigation of GMRES convergence Behavior
Duintjer Tebbens, Jurjen
2013 - English Keywords: GMRES method; convergence behavior; unitary linear system; unitary eigenproblem Available in digital repository of the ASCR On using Unitary Matrices for the Investigation of GMRES convergence Behavior

Duintjer Tebbens, Jurjen
Ústav informatiky, 2013

On estimation of diffusion coefficient based on spatio-temporal FRAP images: An inverse ill-posed problem
Kaňa, Radek; Matonoha, Ctirad; Papáček, Š.; Soukup, J.
2013 - English This contribution contains a description and comparison of two methods applied to exposure optimization applied to moulding process in the automotive industry. Keywords: FRAP; parameter estimation; diffusion coefficient; boundary value problem; optimization; regularization Fulltext is available at external website. On estimation of diffusion coefficient based on spatio-temporal FRAP images: An inverse ill-posed problem

This contribution contains a description and comparison of two methods applied to exposure optimization applied to moulding process in the automotive industry.

Kaňa, Radek; Matonoha, Ctirad; Papáček, Š.; Soukup, J.
Ústav informatiky, 2013

Heat exposure optimization applied to moulding process in the automotive industry
Královcová, J.; Lukšan, Ladislav; Mlýnek, J.
2013 - English This contribution contains a description and comparison of two methods applied to exposure optimization applied to moulding process in the automotive industry. Keywords: heat exposure; moulding process; constrained optimization; applied optimization; numerical solution Fulltext is available at external website. Heat exposure optimization applied to moulding process in the automotive industry

This contribution contains a description and comparison of two methods applied to exposure optimization applied to moulding process in the automotive industry.

Královcová, J.; Lukšan, Ladislav; Mlýnek, J.
Ústav informatiky, 2013

Nonlinear Trend Modeling in the Analysis of Categorical Data
Kalina, Jan
2012 - English This paper studies various approaches to testing trend in the context of categorical data. While the linear trend is far more popular in econometric applications, a nonlinear modeling of the trend allows a more subtle information extraction from real data, especially if the linearity of the trend cannot be expected and verified by hypothesis testing. We exploit the exact unconditional approach to propose alternative versions of some trend tests. One of them is the test of relaxed trend (Liu, 1998), who proposed a generalization of the classical Cochran- Armitage test of linear trend. A numerical example on real data reveals the advantages of the test of relaxed trend compared to the classical test of linear trend. Further, we propose an exact unconditional test also for modeling association between an ordinal response and nominal regressor. Further, we propose a robust estimator of parameters in the logistic regression model, which is based on implicit weighting of individual observations. We assess the breakdown point of the newly proposed robust estimator. Keywords: contingency tables; exact unconditional test; log-linear model; logistic regression; robust estimation Fulltext is available at external website. Nonlinear Trend Modeling in the Analysis of Categorical Data

This paper studies various approaches to testing trend in the context of categorical data. While the linear trend is far more popular in econometric applications, a nonlinear modeling of the trend ...

Kalina, Jan
Ústav informatiky, 2012

Robust Knowledge Discovery from High-Dimensional Data
Kalina, Jan
2012 - English The paper is devoted to advanced robust methods for information extraction from highdimensional data. The concept of knowledge discovery is discussed together with its two important aspects: high dimensionality of the data and sensitivity to the presence of outlying data values. We propose new robust methods for knowledge discovery suitable for highdimensional data. They are based on the idea of implicit weighting, which is inspired by the least weighted squares regression estimator. We propose a highly robust method for a dimension reduction, which can be described as a robust alternative of the principal component analysis based on implicit down-weighting of less reliable data values. Further, we propose a novel robust approach to cluster analysis, which is a popular knowledge discovery method of unsupervised learning. A two-stage cluster analysis method tailor-made for highdimensional data is obtained by combining the robust principal component analysis with the robust cluster analysis. The procedure can be interpreted as a robust knowledge discovery method tailor made for high-dimensional data. Keywords: robust statistics; dimension reduction; principal components; cluster analysis Available in digital repository of the ASCR Robust Knowledge Discovery from High-Dimensional Data

The paper is devoted to advanced robust methods for information extraction from highdimensional data. The concept of knowledge discovery is discussed together with its two important aspects: high ...

Kalina, Jan
Ústav informatiky, 2012

Some Results on Set-Valued Possibilistic Distributions
Kramosil, Ivan
2012 - English When proposing and processing uncertainty decision making algorithms of various kinds and purposes we meet more and more often probability distributions ascribing to random events non-numerical uncertainty degrees. The reason is that we have to process systems of uncertainties for which the classical conditions like sigma-additivity or linear ordering of values are too restrictive to define sufficiently closely the nature of uncertainty we would like to specify and process. For the case of non-numerical uncertainty degrees at least the two criteria may be considered. First systems with rather complicated, but sophisticated and nontrivially formally analyzable uncertainty degrees. E.g., uncertainties supported by some algebras or partially ordered structures. Contrary, we may consider more easy non-numerical, but on the intuitive level interpretable relations. Well-known examples of such structures are set-valued possibilistic measures. Some perhaps interesting particular results in this direction will be introduced and analyzed in the contribution. Keywords: probability measures; possibility measures; non-numerical uncertainty degrees; set-valued uncertainty degrees; possibilistic uncertainty and set-valued entropy functions Available in digital repository of the ASCR Some Results on Set-Valued Possibilistic Distributions

When proposing and processing uncertainty decision making algorithms of various kinds and purposes we meet more and more often probability distributions ascribing to random events non-numerical ...

Kramosil, Ivan
Ústav informatiky, 2012

Keystroke Dynamics for Authentication in Biomedicine
Schlenker, Anna
2012 - English Keywords: biometrics; anatomical-physiological biometrics; behavioral biometrics; multi-factor authentication; keystroke dynamics Available in a digital repository NRGL Keystroke Dynamics for Authentication in Biomedicine

Schlenker, Anna
Ústav informatiky, 2012

Common Problems Using NWP Models for Prediction of Photovoltaic Power
Resler, Jaroslav; Eben, Kryštof; Krč, Pavel
2012 - English Keywords: renewable energy; photovoltaic; NWP Available in digital repository of the ASCR Common Problems Using NWP Models for Prediction of Photovoltaic Power

Resler, Jaroslav; Eben, Kryštof; Krč, Pavel
Ústav informatiky, 2012

An Algorithm for Formal Safety Verification of Complex Heterogeneous Systems
Ratschan, Stefan
2012 - English Modern technical systems are heterogeneous in the sense that they tightly integrate computational elements into physical surroundings. Computational elements usually require discrete, and physical systems continuous modeling. In this paper, we present an modeling formalism and safety verification algorithm for such heterogeneous systems. Keywords: verification; complex systems; safety Available in digital repository of the ASCR An Algorithm for Formal Safety Verification of Complex Heterogeneous Systems

Modern technical systems are heterogeneous in the sense that they tightly integrate computational elements into physical surroundings. Computational elements usually require discrete, and physical ...

Ratschan, Stefan
Ústav informatiky, 2012

Introduction to Algebra of Belief Functions on Three-element Frame of Discernment - A General Case
Daniel, Milan
2012 - English This contribution presents the second part of the introductive study of algebraic structure of belief functions (BFs) on 3-element frame of discernment. Algebraic method by Hájek & Valdés for BFs on 2-element frames is generalized to larger frame of discernment. Due to complexity of the algebraic structure, the study is divided into 2 parts, the present one is devoted to a case of general BFs. The definition of Dempster's semigroup (an algebraic structure) of BFs on 3-element frame is recalled from the first part of the study. Results related to Bayesian and quasi Bayesian BFs from the first part are also briefly recalled. Further substructures related to another subsets of general BFs are described and analyzed (including idempotents, simple complementary BFs, generalizations of subsemigroups of simple BFs) and subalgebras isomorphic to Dempster's semigroup on 2-element frame of discernment. Ideas and open problems for future research are presented. Keywords: belief function; Dempster-Shafer theory; Dempster's semigroup; homomorphisms; conflict between belief functions; uncertainty Available in digital repository of the ASCR Introduction to Algebra of Belief Functions on Three-element Frame of Discernment - A General Case

This contribution presents the second part of the introductive study of algebraic structure of belief functions (BFs) on 3-element frame of discernment. Algebraic method by Hájek & Valdés for BFs on ...

Daniel, Milan
Ústav informatiky, 2012