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[popis] => In this paper, we are concerned with a civil engineering application of optimization, namely
the optimal design of a loaded beam. The developed optimization model includes ODE-type
constraints and chance constraints. We use the finite element method (FEM) for the approximation
of the ODE constraints. We derive a convex reformulation that transforms the problem
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the optimal design of a loaded beam. The developed optimization model includes ODE-type
constraints and chance constraints. We use the finite element method (FEM) for the approximation
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into a linear one and find its analytic solution. Afterwards, we impose chance constraints on
the stress and the deection of the beam. These chance constraints are handled by a sampling
method (Probabilistic Robust Design).
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probabilistic robust design, geometric programming
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[citace_text] => KŮDELA, J.; POPELA, P. Chance constrained optimal beam design: convex reformulation and probabilistic robust design. KYBERNETIKA, 2018, vol. 54, no. 6, p. 1201-1217. ISSN: 0023-5954.
[citace_html] => KŮDELA, J.; POPELA, P. Chance constrained optimal beam design: convex reformulation and probabilistic robust design. KYBERNETIKA, 2018, vol. 54, no. 6, p. 1201-1217. ISSN: 0023-5954.
[citace_rtf] =>
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journal="KYBERNETIKA",
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volume="54",
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constraints and chance constraints. We use the finite element method (FEM) for the approximation
of the ODE constraints. We derive a convex reformulation that transforms the problem
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In the paper, we present a solution that uses two heuristic methods: genetic algorithm and tabu search.
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title="Minimisation of Network Covering Services with Predefined Centres",
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year="2018",
journal="ECMS",
volume="2018",
number="1",
pages="282--287",
publisher="European Council for Modelling and Simulation",
address="Wilhelmshaven (Germany)",
doi="10.7148/2018-0282",
isbn="978-0-9932440-6-3",
issn="2522-2414"
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[citace_text] => ŠEDA, M.; ŠEDA, P. Stochastic Heuristics for Knapsack Problems. Advances in Intelligent Systems and Computing, 2018, vol. 837, no. 1, p. 157-166. ISSN: 2194-5357.
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[nazev_en] => Stochastic Heuristics for Knapsack Problems
[popis_en] => In this paper, we introduce knapsack problem formulations, discuss their time complexity and propose their representation and solution based on the instance size. First, deterministic methods are briefly summarized. They can be applied to small-size tasks with a single constraint. However, because of NP-completeness of the problem, more complex problem instances must be solved by means of heuristic techniques to achieve an approximation of the exact solution in a reasonable amount of time. The problem representations and parameter settings for a genetic algorithm and simulated annealing frameworks are shown.
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[popis_orig] => Článek se zabývá možnosti využití strojového učení ve vibrodiagnostice pro určení typu závady rotačního stroje. Vzorová (vstupní) data jsou simulována dle předpokládaného průběhu signálu rychlosti vibrací při konkrétní poruše. Poté jsou data zpracována a redukována pro použití aplikace „Matlab Classification learner app“, která vytvoří model pro rozpoznávání závady. Model je nakonec otestován na novém vzorku dat. Článek slouží k ověření možností této metody pro pozdější využití na reálném stroji. V této fázi je testováno předzpracování dat a výběr vhodné metody klasifikace.
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[popis] => The article deals with possibilities of use machine learning in vibrodiagnostics to determine a fault type of the rotary machine. Sample data are simulated according to the expected vibration velocity waveform signal at a specific fault. Then the data are pre-processed and reduced for using Matlab Classification Learner which creates a model for identifying faults in the new data samples. The model is finally tested on a new sample data. The article serves to verify the possibility of this method for later use on a real machine. In this phase is tested data preprocessing and a suitable classification method.
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[citace_html] => ZUTH, D.; MARADA, T. Utilization of Machine Learning in Vibrodiagnostics. Advances in Intelligent Systems and Computing, 2018, no. 2017, p. 271-278. ISSN: 2194-5357.
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number="2017",
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[popis] => In this paper, we deal with a problem of finding the shortest connection of points placed in the Euclidean plane. The traditional strategy starts from the complete graph and finds its minimum spanning tree. However, this approach is proportional to the second power of the number of vertices, and therefore not very efficient. Additionally, if instead of the minimum spanning trees, minimum Steiner trees are considered, then the total length of the final network is decreased. Since the Steiner tree problem is NP-hard, in the case of large instances, heuristics must be used. Here, we propose a Delaunay triangulation-based deterministic heuristic and show that it gives very good results in short times.
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[nazev_en] => Minimisation of Networks Based on Computational Geometry Data Structures
[popis_en] => In this paper, we deal with a problem of finding the shortest connection of points placed in the Euclidean plane. The traditional strategy starts from the complete graph and finds its minimum spanning tree. However, this approach is proportional to the second power of the number of vertices, and therefore not very efficient. Additionally, if instead of the minimum spanning trees, minimum Steiner trees are considered, then the total length of the final network is decreased. Since the Steiner tree problem is NP-hard, in the case of large instances, heuristics must be used. Here, we propose a Delaunay triangulation-based deterministic heuristic and show that it gives very good results in short times.
[klicova_slova_en] => spanning tree, Steiner tree, NP-hard problem, heuristic, Voronoi diagram, Delaunay triangulation
[vysledek_datum] => 2018-11-11T00:00:00+01:00
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[klicova_slova] => Graphics. multi thread programming. mesh objects. Computation. Algorithm. boundary
intersection.
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intersection.
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[identifikator] => ISBN 978-80-7598-059-5 ISSN 2464-7470
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[citace_text] => JINDRA, P.; ŠŤASTNÝ, J. Three stage object boundary intersection solver. In DIVAI 2018. DIVAI. Prague: Wolters Kluwer, 2018. p. 431-449. ISBN: 978-80-7598-059-5. ISSN: 2464-7470.
[citace_html] => JINDRA, P.; ŠŤASTNÝ, J. Three stage object boundary intersection solver. In DIVAI 2018. DIVAI. Prague: Wolters Kluwer, 2018. p. 431-449. ISBN: 978-80-7598-059-5. ISSN: 2464-7470.
[citace_rtf] =>
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booktitle="DIVAI 2018",
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[citace_text] => LÝSEK, J.; ŠŤASTNÝ, J. GRAMMATICAL EVOLUTION FOR CLASSIFICATION INTO MULTIPLE CLASSES. In Recent Advances in Soft Computing. 2019. p. 192-210. ISBN: 978-3-319-97887-1.
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[citace_rtf] =>
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booktitle="Recent Advances in Soft Computing",
year="2019",
pages="192--210",
doi="10.1007/978-3-319-97888-8\{_}17",
isbn="978-3-319-97887-1"
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[popis_en] => In this contribution the authors deal with classification problems using an approach based on grammatical evolution. The named method is used to create short executable structures which are evolved to classify
given input into multiple classes. Resulting structures are usable as computer programs for embedded devices
with low computational resources. An universal formula for fitness value calculation of the evolved individual is
introduced and an example of planar graphical objects classification in generated image dataset is presented. The presented approach is still applicable for general multi-class classification problems. The results of the proposed method are discussed and examined.
[klicova_slova_en] => grammatical evolution, multiclass classification, fitness function, object recognition, learning
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[nazev] => Fuzzy logic control application for the risk quantification of projects for automation
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[duvernost_udaju_id] => S
[popis] => This article describes the classical approach to risk quantification. This is followed by recommendations of fuzzy sets for advanced risk quantification in the automation project. Different models for fuzzification and defuzzification are presented and the optimum model variants are found with the help of the MATLAB program system. © Springer Nature Switzerland AG 2019.
[popis_orig] => This article describes the classical approach to risk quantification. This is followed by recommendations of fuzzy sets for advanced risk quantification in the automation project. Different models for fuzzification and defuzzification are presented and the optimum model variants are found with the help of the MATLAB program system. © Springer Nature Switzerland AG 2019.
[klicova_slova] => Intelligent Systems; Soft Computing
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[citace_text] => DAVIDOVÁ, O.; LACKO, B. Fuzzy logic control application for the risk quantification of projects for automation. In Advances in Intelligent Systems and Computing. Cham, Switzerland: Springer, 2019. p. 320-326. ISBN: 978-3-319-97887-1.
[citace_html] => DAVIDOVÁ, O.; LACKO, B. Fuzzy logic control application for the risk quantification of projects for automation. In Advances in Intelligent Systems and Computing. Cham, Switzerland: Springer, 2019. p. 320-326. ISBN: 978-3-319-97887-1.
[citace_rtf] =>
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author="Olga {Davidová} and Branislav {Lacko}",
title="Fuzzy logic control application for the risk quantification of projects for automation",
booktitle="Advances in Intelligent Systems and Computing",
year="2019",
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address="Cham, Switzerland",
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doi="10.1007/978-3-319-97888-8\{_}29",
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[poznamka_metriky] =>
[nazev_en] => Fuzzy logic control application for the risk quantification of projects for automation
[popis_en] => This article describes the classical approach to risk quantification. This is followed by recommendations of fuzzy sets for advanced risk quantification in the automation project. Different models for fuzzification and defuzzification are presented and the optimum model variants are found with the help of the MATLAB program system. © Springer Nature Switzerland AG 2019.
[klicova_slova_en] => Intelligent Systems; Soft Computing
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[10] => Array
(
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[nazev] => Automatic bird species recognition based on birds vocalization
[nazev_orig] => Automatic bird species recognition based on birds vocalization
[duvernost_udaju_id] => S
[popis] => This paper deals with a project of Automatic Bird Species Recognition Based on Bird Vocalization. Eighteen bird
species of 6 different families were analyzed. At first, human factor cepstral coefficients representing the given
signal were calculated from particular recordings. In the next phase, using the voice activity detection system,
segments of bird vocalizations were detected from which a likelihood rate, with which the given code value
corresponds to the given model, was calculated using individual hidden Markov models. For each bird species, just one respective hidden Markov model was trained. The interspecific success of 81.2% has been reached. For
classification into families, the success has reached 90.45%.
[popis_orig] => This paper deals with a project of Automatic Bird Species Recognition Based on Bird Vocalization. Eighteen bird
species of 6 different families were analyzed. At first, human factor cepstral coefficients representing the given
signal were calculated from particular recordings. In the next phase, using the voice activity detection system,
segments of bird vocalizations were detected from which a likelihood rate, with which the given code value
corresponds to the given model, was calculated using individual hidden Markov models. For each bird species, just one respective hidden Markov model was trained. The interspecific success of 81.2% has been reached. For
classification into families, the success has reached 90.45%.
[klicova_slova] => HFCC, VAD, kNN, HMM, Bird species recognition, Birdsong recognition, Classification
[klicova_slova_orig] => HFCC, VAD, kNN, HMM, Bird species recognition, Birdsong recognition, Classification
[url] => http://link.springer.com/article/10.1186/s13636-018-0143-7
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author="Jiří {Šťastný} and Michal {Munk} and Luboš {Juránek}",
title="Automatic bird species recognition based on birds vocalization",
journal="EURASIP Journal on Audio Speech and Music Processing",
year="2018",
volume="2018",
number="12",
pages="1--7",
doi="10.1186/s13636-018-0143-7",
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[popis_en] => This paper deals with a project of Automatic Bird Species Recognition Based on Bird Vocalization. Eighteen bird
species of 6 different families were analyzed. At first, human factor cepstral coefficients representing the given
signal were calculated from particular recordings. In the next phase, using the voice activity detection system,
segments of bird vocalizations were detected from which a likelihood rate, with which the given code value
corresponds to the given model, was calculated using individual hidden Markov models. For each bird species, just one respective hidden Markov model was trained. The interspecific success of 81.2% has been reached. For
classification into families, the success has reached 90.45%.
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[popis] => White-nose syndrome (WNS) is a fungal disease caused by Pseudogymnoascus destructans that is devastating to Nearctic bat populations but tolerated by Palearctic bats. Temperature is a factor known to be important for fungal growth and bat choice of hibernation. Here we investigated the effect of temperature on the pathogenic fungal growth in the wild across the Palearctic. We modelled body surface temperature of bats with respect to fungal infection intensity and disease severity and were able to relate this to the mean annual surface temperature at the site. Bats that hibernated at lower temperatures had less fungal growth and fewer skin lesions on their wings. Contrary to expectation derived from laboratory P. destructans culture experiments, natural infection intensity peaked between 5 and 6 degrees C and decreased at warmer hibernating temperature. We made predictive maps based on bat species distributions, temperature and infection intensity and disease severity data to determine not only where P. destructans will be found but also where the infection will be invasive to bats across the Palearctic. Together these data highlight the mechanistic model of the interplay between environmental and biological factors, which determine progression in a wildlife disease.
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[citace_rtf] =>
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author="MARTÍNKOVÁ, N. and PIKULA, J. and ZUKAL, J. and KOVACOVA, V. and BANDOUCHOVA, H. and BARTONIČKA, T. and BOTVINKIN, A. D. and BRICHTA, J. and DUNDAROVA, H. and KOKUREWICZ, T. and IRWIN, N. R. and LINHART, P. and ORLOV, O. L. and PIACEK, V. and ŠKRABÁNEK, P. and TIUNOV, M. P and ZAHRADNÍKOVÁ, JR A.",
title="Hibernation temperature-dependent Pseudogymnoascus destructans infection intensity in Palearctic bats",
journal="Virulence",
year="2018",
volume="9",
number="1",
pages="1734--1750",
doi="10.1080/21505594.2018.1548685",
issn="2150-5594",
url="http://dx.doi.org/10.1080/21505594.2018.1548685"
}
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[popis_en] => White-nose syndrome (WNS) is a fungal disease caused by Pseudogymnoascus destructans that is devastating to Nearctic bat populations but tolerated by Palearctic bats. Temperature is a factor known to be important for fungal growth and bat choice of hibernation. Here we investigated the effect of temperature on the pathogenic fungal growth in the wild across the Palearctic. We modelled body surface temperature of bats with respect to fungal infection intensity and disease severity and were able to relate this to the mean annual surface temperature at the site. Bats that hibernated at lower temperatures had less fungal growth and fewer skin lesions on their wings. Contrary to expectation derived from laboratory P. destructans culture experiments, natural infection intensity peaked between 5 and 6 degrees C and decreased at warmer hibernating temperature. We made predictive maps based on bat species distributions, temperature and infection intensity and disease severity data to determine not only where P. destructans will be found but also where the infection will be invasive to bats across the Palearctic. Together these data highlight the mechanistic model of the interplay between environmental and biological factors, which determine progression in a wildlife disease.
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[popis] => New ring vortex model (RVM) can help in design new nanomaterials. It is good idea to combine ring mdels with grammatical evolution.
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[citace_text] => Pavel Ošmera senor, Pavel Werner, Pavel Ošmera junior. Ring structures of nanomaterials. 2018, p. 201-205.
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[nazev] => Modelling invasive pathogen load from non-destructive sampling data
[nazev_orig] => Modelling invasive pathogen load from non-destructive sampling data
[duvernost_udaju_id] => S
[popis] => Where microbes colonizing skin surface may help maintain organism homeostasis, those that invade living skin layers cause disease. In bats, white-nose syndrome is a fungal skin infection that affects animals during hibernation and may lead to mortality in severe cases. Here, we inferred the amount of fungus that had invaded skin tissue of diseased animals. We used simulations to estimate the unobserved disease severity in a non-lethal wing punch biopsy and to relate the simulated pathology to the measured fungal load in paired biopsies. We found that a single white-nose syndrome skin lesion packed with spores and hyphae of the causative agent, Pseudogymnoascus destructans, contains 48.93 pg of the pathogen DNA, which amounts to about 1560 P destructans genomes in one skin lesion. Relating the information to the known UV fluorescence in Nearctic and Palearctic bats shows that Nearctic bats carry about 1.7 mu g of fungal DNA per cm(2), whereas Palearctic bats have 0.04 g cm(-2) of P. destructans DNA. With the information on the fungal load that had invaded the host skin, the researchers can now calculate disease severity as a function of invasive fungal growth using non-destructive UV light transillumination of each bat's wing membranes. Our results will enable and promote thorough disease severity assessment in protected bat species without the need for extensive animal and laboratory labor sacrifices.
[popis_orig] => Where microbes colonizing skin surface may help maintain organism homeostasis, those that invade living skin layers cause disease. In bats, white-nose syndrome is a fungal skin infection that affects animals during hibernation and may lead to mortality in severe cases. Here, we inferred the amount of fungus that had invaded skin tissue of diseased animals. We used simulations to estimate the unobserved disease severity in a non-lethal wing punch biopsy and to relate the simulated pathology to the measured fungal load in paired biopsies. We found that a single white-nose syndrome skin lesion packed with spores and hyphae of the causative agent, Pseudogymnoascus destructans, contains 48.93 pg of the pathogen DNA, which amounts to about 1560 P destructans genomes in one skin lesion. Relating the information to the known UV fluorescence in Nearctic and Palearctic bats shows that Nearctic bats carry about 1.7 mu g of fungal DNA per cm(2), whereas Palearctic bats have 0.04 g cm(-2) of P. destructans DNA. With the information on the fungal load that had invaded the host skin, the researchers can now calculate disease severity as a function of invasive fungal growth using non-destructive UV light transillumination of each bat's wing membranes. Our results will enable and promote thorough disease severity assessment in protected bat species without the need for extensive animal and laboratory labor sacrifices.
[klicova_slova] => Pathogen load; Skin lesion; Fungal infection; Pseudogymnoascus destructans; White-nose syndrome; Bat; UV light diagnostics
[klicova_slova_orig] => Pathogen load; Skin lesion; Fungal infection; Pseudogymnoascus destructans; White-nose syndrome; Bat; UV light diagnostics
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[citace_text] => Martinkova, N.; Škrabánek, P.; Pikula, J. Modelling invasive pathogen load from non-destructive sampling data. JOURNAL OF THEORETICAL BIOLOGY, 2019, no. 464, p. 98-103. ISSN: 0022-5193.
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author="Martinkova, N. and Škrabánek, P. and Pikula, J.",
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Publikace
Rok: 2018
KŮDELA, J.
POPELA, P.
Publikace
Rok: 2018
ŠEDA, M.
ŠEDA, P.
Publikace
Rok: 2018
ŠEDA, M.
ŠEDA, P.
Publikace
Rok: 2018
ZUTH, D.
Publikace
Rok: 2018
ZUTH, D.
MARADA, T.
Publikace
Rok: 2018
ŠEDA, M.
ŠEDA, P.
Publikace
Rok: 2018
JINDRA, P.
ŠŤASTNÝ, J.
Publikace
Rok: 2019
LÝSEK, J.
ŠŤASTNÝ, J.
Publikace
Rok: 2019
DAVIDOVÁ, O.
LACKO, B.
Publikace
Rok: 2018
ŠŤASTNÝ, J.
MUNK, M.
JURÁNEK, L.
Publikace
Rok: 2018
MARTÍNKOVÁ, N.
PIKULA, J.
ZUKAL, J.
KOVACOVA, V.
BANDOUCHOVA, H.
BARTONIČKA, T.
BOTVINKIN, A. D.
BRICHTA, J.
DUNDAROVA, H.
KOKUREWICZ, T.
IRWIN, N. R.
LINHART, P.
ORLOV, O. L.
PIACEK, V.
ŠKRABÁNEK, P.
TIUNOV, M. P
ZAHRADNÍKOVÁ, JR A.
Publikace
Rok: 2018
Pavel Ošmera senor, Pavel Werner, Pavel Ošmera junior
Publikace
Rok: 2019
Martinkova, N.
Škrabánek, P.
Pikula, J.
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