Dental Electronic Health Record Evaluation (Electronic Health Record versus WHO Dental Card)
Chleborád, K.; Zvára Jr., Karel; Dostálová, T.; Zvára, Karel; Ivančáková, R.; Zvárová, Jana; Smidl, L.; Trmal, J.; Psutka, J.
2013 - anglický Klíčová slova: dentistry; medical documentation; electronic health record Plné texty jsou dostupné na jednotlivých ústavech Akademie věd ČR. Dental Electronic Health Record Evaluation (Electronic Health Record versus WHO Dental Card)

Chleborád, K.; Zvára Jr., Karel; Dostálová, T.; Zvára, Karel; Ivančáková, R.; Zvárová, Jana; Smidl, L.; Trmal, J.; Psutka, J.
Ústav informatiky, 2013

An Alternative Approach to the Structure Determination of Hierarchical Archimedean Copulas
Górecki, J.; Holeňa, Martin
2013 - anglický Copulas offer very a flexible tool for a stochastic dependence modeling. One of the most popular classes of copulas is the class of hierarchical Archimedean copulas, which gained its popularity due to the fact that the models from the class are able to model the stochastic dependencies conveniently even in high dimensions. One critical issue when estimating a hierarchical Archimedean copula is to correctly determine its structure. The paper describes an approach to the problem of the structure determination of a hierarchical Archimedean copula, which is based on the close relationship of the copula structure and the values of measure of concordance computed on all its bivariate margins. The presented approach is conveniently summarized as a simple algorithm. Klíčová slova: hierarchical Archimedean copula; structure determination; measure of concordance; bivariate margins; nesting condition Plné texty jsou dostupné na vyžádání prostřednictvím repozitáře Akademie věd. An Alternative Approach to the Structure Determination of Hierarchical Archimedean Copulas

Copulas offer very a flexible tool for a stochastic dependence modeling. One of the most popular classes of copulas is the class of hierarchical Archimedean copulas, which gained its popularity due to ...

Górecki, J.; Holeňa, Martin
Ústav informatiky, 2013

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

Is There Something Beyond AI? Frequently Emerging, but Seldom Answered Questions about Artificial Super-Intelligence
Wiedermann, Jiří
2012 - anglický Using the contemporary theories and views of computing and of cognitive systems we indicate possible answers to the following frequently asked questions about artificial intelligence: (i) what is the "computational power" of artificial cognitive systems?; (ii) are there "levels" of intelligence?; (iii) what is the position of human intelligence w.r.t. the "levels" of intelligence?; (iv) is there a general mechanism of intelligence?; (v) can "fully-fledged" body-less intelligence exist?; (vi) can there exist a sentient cloud? We give qualified arguments suggesting that within the large class of computational models of cognitive systems the answers to the previous question are positive. These arguments are mostly based on the author's recent works related to this problematics. Klíčová slova: cognitive systems; computational models; non-uniform evolving automaton Plné texty jsou dostupné na vyžádání prostřednictvím repozitáře Akademie věd. Is There Something Beyond AI? Frequently Emerging, but Seldom Answered Questions about Artificial Super-Intelligence

Using the contemporary theories and views of computing and of cognitive systems we indicate possible answers to the following frequently asked questions about artificial intelligence: (i) what is the ...

Wiedermann, Jiří
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

Algebraic error in the numerical solution of differential equations
Liesen, J.; Papež, J.; Strakoš, Zdeněk
2012 - anglický Klíčová slova: spatial distribution of errors; algebraic error; finite element method; iterative solver Plné texty jsou dostupné na vyžádání prostřednictvím repozitáře Akademie věd. Algebraic error in the numerical solution of differential equations

Liesen, J.; Papež, J.; Strakoš, Zdeněk
Ústav informatiky, 2012

Common Problems Using NWP Models for Prediction of Photovoltaic Power
Resler, Jaroslav; Eben, Kryštof; Krč, Pavel
2012 - anglický Klíčová slova: renewable energy; photovoltaic; NWP Plné texty jsou dostupné v digitálním repozitáři Akademie Věd. 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 - anglický 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. Klíčová slova: verification; complex systems; safety Plné texty jsou dostupné v digitálním repozitáři Akademie Věd. 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