An Interpretation of Conflicting Parts of Belief Functions on Two-Element Frame of Discrement
Daniel, Milan
2013 - anglický When combining belief functions by the conjunctive rules of combination, conflicts often appear, which are assigned to empty set by un-normalized conjunctive rule or normalized by Dempster's rule of combination. This contribution is devoted to an interpretation of the conflicting part of a belief function on a two-element frame of discernment. It is based on the author's idea of the unique decomposition of such function into its conflicting and non-conflicting part (CJS 2010, Otaru). A relation of conflicting part of a belief function to internal conflict of the function is also studied and a new definition of internal conflict is introduced. New internal conflict is compared with the previous approaches. Keywords: Belief function, Dempster-Shafer theory, uncertainty, Dempster's semigroup, internal conflict, conflict between belief functions, non-conflicting part of belief function, conflicting part of belief function. Klíčová slova: belief function; Dempster-Shafer theory; uncertainty; Dempster's semigroup; internal conflict; conflict between belief functions; non-conflicting part of belief function; conflicting part of belief function Dokument je dostupný na externích webových stránkách. An Interpretation of Conflicting Parts of Belief Functions on Two-Element Frame of Discrement

When combining belief functions by the conjunctive rules of combination, conflicts often appear, which are assigned to empty set by un-normalized conjunctive rule or normalized by Dempster's rule of ...

Daniel, Milan
Ústav informatiky, 2013

On using Unitary Matrices for the Investigation of GMRES convergence Behavior
Duintjer Tebbens, Jurjen
2013 - anglický Klíčová slova: GMRES method; convergence behavior; unitary linear system; unitary eigenproblem Plné texty jsou dostupné v digitálním repozitáři Akademie Věd. 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 - anglický This contribution contains a description and comparison of two methods applied to exposure optimization applied to moulding process in the automotive industry. Klíčová slova: FRAP; parameter estimation; diffusion coefficient; boundary value problem; optimization; regularization Dokument je dostupný na externích webových stránkách. 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 - anglický This contribution contains a description and comparison of two methods applied to exposure optimization applied to moulding process in the automotive industry. Klíčová slova: heat exposure; moulding process; constrained optimization; applied optimization; numerical solution Dokument je dostupný na externích webových stránkách. 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

Optimalizace osazování odběrných míst inteligentními plynoměry
Konár, Ondřej
2012 - český Klíčová slova: smart metering; zemní plyn Plné texty jsou dostupné v digitálním repozitáři NUŠL Optimalizace osazování odběrných míst inteligentními plynoměry

Konár, Ondřej
Ústav informatiky, 2012

Nonlinear Trend Modeling in the Analysis of Categorical Data
Kalina, Jan
2012 - anglický 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. Klíčová slova: contingency tables; exact unconditional test; log-linear model; logistic regression; robust estimation Dokument je dostupný na externích webových stránkách. 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 - anglický 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. Klíčová slova: robust statistics; dimension reduction; principal components; cluster analysis Plné texty jsou dostupné v digitálním repozitáři Akademie Věd. 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 - anglický 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. Klíčová slova: probability measures; possibility measures; non-numerical uncertainty degrees; set-valued uncertainty degrees; possibilistic uncertainty and set-valued entropy functions Plné texty jsou dostupné v digitálním repozitáři Akademie Věd. 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 - anglický Klíčová slova: biometrics; anatomical-physiological biometrics; behavioral biometrics; multi-factor authentication; keystroke dynamics Plné texty jsou dostupné v digitálním repozitáři NUŠL Keystroke Dynamics for Authentication in Biomedicine

Schlenker, Anna
Ústav informatiky, 2012

Informatics Europe. Svaz evropských kateder informatiky a výzkumných laboratoří
Wiedermann, Jiří
2012 - český Klíčová slova: computer science; evaluation; Informatics Europe Plné texty jsou dostupné v digitálním repozitáři NUŠL Informatics Europe. Svaz evropských kateder informatiky a výzkumných laboratoří

Wiedermann, Jiří
Ústav informatiky, 2012