Number of found documents: 1676
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Tourist interest in illicit zone of ice caves
Nováková, Eva; Kuda, František; Kubalíková, Lucie
2018 - English
Ledové sluje (Ice Caves) in the Podyjí National Park represents one of the most spectacular sites within the area. It consists of the large boulder field and several pseudokarst caverns on the north-western slope of the ridge that are very important from the ecological and geomorphological point of view. The access to the site is restricted for the visitors of National Park as there exists a risk of damage and disturbance of these unique phenomena; tourist can use the marked paths leading around the site, they can reach the top part of the ridge.\nCurrently, there are only several persons who have legal access to the site (employees of the National Park Administration and other researches with the permission issued by NP Administration). However, the installed sensor that counts the passages proved that the site is visited more frequently than it should be. The number of people who visit this site (situated within the first zone of National Park where there is no marked path and so the access is forbidden by decree) is quite alarming. Based on these findings, some proposals for the solution of this unfavourable situation are proposed and other possibilities how to avoid this undesirable phenomenon are discussed.\n Keywords: Podyji National Park; restricted area; passages monitoring Available in a digital repository NRGL
Tourist interest in illicit zone of ice caves

Ledové sluje (Ice Caves) in the Podyjí National Park represents one of the most spectacular sites within the area. It consists of the large boulder field and several pseudokarst caverns on the ...

Nováková, Eva; Kuda, František; Kubalíková, Lucie
Ústav geoniky, 2018

Two Algorithms for Risk-averse Reformulation of Multi-stage Stochastic Programming Problems
Šmíd, Martin; Kozmík, Václav
2018 - English
Many real-life applications lead to risk-averse multi-stage stochastic problems, therefore effective solution of these problems is of great importance. Many tools can be used to their solution (GAMS, Coin-OR, APML or, for smaller problems, Excel), it is, however, mostly up to researcher to reformulate the problem into its deterministic equivalent. Moreover, such solutions are usually one-time, not easy to modify for different applications. We overcome these problems by providing a front-end software package, written in C++, which enables to enter problem definitions in a way close to their mathematical definition. Creating of a deterministic equivalent (and its solution) is up to the computer. In particular, our code is able to solve linear multi-stage with Multi-period Mean-CVaR or Nested Mean-CVaR criteria. In the present paper, we describe the algorithms, transforming these problems into their deterministic equivalents. Keywords: Multi-stage stochastic programming; deterministic equivalent; multi-period CVaR; nested CVaR; optimization algorithm Fulltext is available at external website.
Two Algorithms for Risk-averse Reformulation of Multi-stage Stochastic Programming Problems

Many real-life applications lead to risk-averse multi-stage stochastic problems, therefore effective solution of these problems is of great importance. Many tools can be used to their solution (GAMS, ...

Šmíd, Martin; Kozmík, Václav
Ústav teorie informace a automatizace, 2018

Classification of distances in cosmology
Křížek, Michal; Mészáros, A.
2018 - English
In cosmology many different distances are defined: angular, comoving, Euclidean, Hubble, light-year, luminosity, Minkowski, parallax, proper motion, redshift, ... distance. There is not one single natural distance, since the universe is expanding, curved, and we look back in time. In this survey paper we will concentrate on geometrical interpretations of the above-mentioned distances. Keywords: standard cosmological model; cosmological principle; Friedmann equation; cosmological parameters; Einstein static universe Available in digital repository of the ASCR
Classification of distances in cosmology

In cosmology many different distances are defined: angular, comoving, Euclidean, Hubble, light-year, luminosity, Minkowski, parallax, proper motion, redshift, ... distance. There is not one single ...

Křížek, Michal; Mészáros, A.
Matematický ústav, 2018

Problem of competing risks with covariates: Application to an unemployment study
Volf, Petr
2018 - English
The study deals with the methods of statistical analysis in the situation of competing risks in the presence of regression. First, the problem of identification of marginal and joint distributions of competing random variables is recalled. The main objective is then to demonstrate that the parameters and, in particular, the correlation of competing variables, may depend on covariates. The approach is applied to solution of a real example with unemployment data. The model uses the Gauss copula and Cox’s regression model. Keywords: statistical analysis; competing risks; unemployment study Fulltext is available at external website.
Problem of competing risks with covariates: Application to an unemployment study

The study deals with the methods of statistical analysis in the situation of competing risks in the presence of regression. First, the problem of identification of marginal and joint distributions of ...

Volf, Petr
Ústav teorie informace a automatizace, 2018

Dynamic Bayesian Networks for the Classification of Sleep Stages
Vomlel, Jiří; Kratochvíl, Václav
2018 - English
Human sleep is traditionally classified into five (or six) stages. The manual classification is time consuming since it requires knowledge of an extensive set of rules from manuals and experienced experts. Therefore automatic classification methods appear useful for this task. In this paper we extend the approach based on Hidden Markov Models by relating certain features not only to the current time slice but also to the previous one. Dynamic Bayesian Networks that results from this generalization are thus capable of modeling features related to state transitions. Experiments on real data revealed that in this way we are able to increase the prediction accuracy. Keywords: Dynamic Bayesian Network; Sleep Analysis Fulltext is available at external website.
Dynamic Bayesian Networks for the Classification of Sleep Stages

Human sleep is traditionally classified into five (or six) stages. The manual classification is time consuming since it requires knowledge of an extensive set of rules from manuals and experienced ...

Vomlel, Jiří; Kratochvíl, Václav
Ústav teorie informace a automatizace, 2018

Neglected gravitational redshift in detections of gravitational waves
Křížek, Michal; Somer, L.
2018 - English
In 2016, the letter [1] about the first detection of gravitational waves was published. They were generated by two merging black holes that had approximately 36 and 29 Sun’s masses. However, the authors have not taken into account a large gravitational redshift of this binary system, which is a direct consequence of time dilation in a strong gravitational field. Thus the proposed masses are overestimated. In our paper we also give other arguments for this statement. Keywords: gravitational redshift; time dilatation; black holes; wavelets Available in digital repository of the ASCR
Neglected gravitational redshift in detections of gravitational waves

In 2016, the letter [1] about the first detection of gravitational waves was published. They were generated by two merging black holes that had approximately 36 and 29 Sun’s masses. However, the ...

Křížek, Michal; Somer, L.
Matematický ústav, 2018

Comparison of Shenoy’s Expectation Operator with Probabilistic Transforms and Perez’ Barycenter
Jiroušek, R.; Kratochvíl, Václav
2018 - English
Shenoy’s paper published in this Proceedings of WUPES 2018 introduces an operator that gives instructions how to compute an expected value in the Dempster-Shafer theory of evidence. Up to now, there was no direct way to get the expected value of a utility function in D-S theory. If eeded, one had to find a probability mass function corresponding to the considered belief function, and then - using this probability mass function - to compute the classical probabilistic expectation. In this paper, we take four different approaches to defining probabilistic representatives of a belief function and compare which one yields to the best approximations of Shenoy’s expected values of various utility functions. The achieved results support our conjecture that there does not exist a probabilistic representative of a belief function that would yield the same expectations as the Shenoy’s new operator. Keywords: expected utility; Dempster-Shafer theory; Shenoy's operator Fulltext is available at external website.
Comparison of Shenoy’s Expectation Operator with Probabilistic Transforms and Perez’ Barycenter

Shenoy’s paper published in this Proceedings of WUPES 2018 introduces an operator that gives instructions how to compute an expected value in the Dempster-Shafer theory of evidence. Up to now, there ...

Jiroušek, R.; Kratochvíl, Václav
Ústav teorie informace a automatizace, 2018

Employing Bayesian Networks for Subjective Well-being Prediction
Švorc, Jan; Vomlel, Jiří
2018 - English
This contribution aims at using Bayesian networks for modelling the relations between the individual subjective well-being (SWB) and the individual material situation. The material situation is approximated by subjective measures (perceived economic strain, subjective evaluation of the income relative to most people in the country and to own past) and objective measures (household’s income, material deprivation, financial problems and housing defects). The suggested Bayesian network represents the relations among SWB and the variables approximating the material situation. The structure is established based on the expertise gained from literature, whereas the parameters are learnt based on empirical data from 3rd edition of European Quality of Life Study for the Czech Republic, Hungary, Poland and Slovakia conducted in 2011. Prediction accuracy of SWB is tested and compared with two benchmark models whose structures are learnt using Gobnilp software and a greedy algorithm built in Hugin software. SWB prediction accuracy of the expert model is 66,83%, which is significantly different from no information rate of 55,16%. It is slightly lower than the two machine learnt benchmark models. Keywords: Subjective well-being; Bayesian networks Fulltext is available at external website.
Employing Bayesian Networks for Subjective Well-being Prediction

This contribution aims at using Bayesian networks for modelling the relations between the individual subjective well-being (SWB) and the individual material situation. The material situation is ...

Švorc, Jan; Vomlel, Jiří
Ústav teorie informace a automatizace, 2018

Proceedings of the 11th Workshop on Uncertainty Processing
Kratochvíl, Václav; Vejnarová, Jiřina
2018 - English
The Workshop on Uncertainty Processing, better known under its abbreviation WUPES, celebrates its 30-year anniversary this year. In 1988, when the first Workshop took place, Czechoslovakia was still a communist country and a part of the Soviet bloc. Since then, many things have changed. For example, Czechoslovakia no longer exists as a country (because in 1993 it was peacefully split into two independent countries - Czechia and Slovakia). From this perspective, it is hard to believe that we have several participants who have attended most workshops in the the thirty-year history of WUPES. As of now, the Program Committee has accepted, based on the extended abstracts, 21 papers to be presented at the Workshop, and 19 out of them are to be published in the present Conference Proceedings. These papers cover diverse topics, such as information processing, decision making, and data analysis; but what is common to most of them is that they are related to uncertainty calculus - Bayesian Networks, Dempster-Shafer Theory, Belief Functions, Probabilistic Logic, Game Theory, etc. Keywords: uncertainty processing; artificial intelligence; bayesian networks Fulltext is available at external website.
Proceedings of the 11th Workshop on Uncertainty Processing

The Workshop on Uncertainty Processing, better known under its abbreviation WUPES, celebrates its 30-year anniversary this year. In 1988, when the first Workshop took place, Czechoslovakia was still a ...

Kratochvíl, Václav; Vejnarová, Jiřina
Ústav teorie informace a automatizace, 2018

Representations of Bayesian Networks by Low-Rank Models
Tichavský, Petr; Vomlel, Jiří
2018 - English
Conditional probability tables (CPTs) of discrete valued random variables may achieve high dimensions and Bayesian networks defined as the product of these CPTs may become intractable by conventional methods of BN inference because of their dimensionality. In many cases, however, these probability tables constitute tensors of relatively low rank. Such tensors can be written in the so-called Kruskal form as a sum of rank-one components. Such representation would be equivalent to adding one artificial parent to all random variables and deleting all edges between the variables. The most difficult task is to find such a representation given a set of marginals or CPTs of the random variables under consideration. In the former case, it is a problem of joint canonical polyadic (CP) decomposition of a set of tensors. The latter fitting problem can be solved in a similar manner. We apply a recently proposed alternating direction method of multipliers (ADMM), which assures that the model has a probabilistic interpretation, i.e., that all elements of all factor matrices are nonnegative. We perform experiments with several well-known Bayesian networks.\n\n Keywords: canonical polyadic tensor decomposition; conditional probability tables; marginal probability tables Fulltext is available at external website.
Representations of Bayesian Networks by Low-Rank Models

Conditional probability tables (CPTs) of discrete valued random variables may achieve high dimensions and Bayesian networks defined as the product of these CPTs may become intractable by conventional ...

Tichavský, Petr; Vomlel, Jiří
Ústav teorie informace a automatizace, 2018

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