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[vysledek_datum] => 2020-12-31T00:00:00+01:00
)
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[duvernost_udaju_id] => S
[popis] => Článek volně navazuje na autorova zamyšlení z minulých ročníků konference. Tentokrát se článek zaměřuje na souvislosti mezi diagnostikou a měřicí technikou a měřením v širším kontextu. Toto zamyšlení do jisté míry vyprovokovala současná situace Covid 19. K jejímu řešení přispívají také mnohé obory a firmy technické diagnostiky. Prezentace výsledků některými „laickými“ uživateli jsou ale přinejmenším „zajímavé“.
[popis_orig] => Článek volně navazuje na autorova zamyšlení z minulých ročníků konference. Tentokrát se článek zaměřuje na souvislosti mezi diagnostikou a měřicí technikou a měřením v širším kontextu. Toto zamyšlení do jisté míry vyprovokovala současná situace Covid 19. K jejímu řešení přispívají také mnohé obory a firmy technické diagnostiky. Prezentace výsledků některými „laickými“ uživateli jsou ale přinejmenším „zajímavé“.
[klicova_slova] => Diagnostika, metrologické charakteristiky, preciznost, přesnost, rozlišení,
[klicova_slova_orig] => Diagnostika, metrologické charakteristiky, preciznost, přesnost, rozlišení,
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[citace_text] => VDOLEČEK, F. Diagnostika a metrologické charakteristiky. Spravodaj ATD SR, 2020, roč. 16, č. 1/2019, s. 14-19. ISSN: 1337-8252.
[citace_html] => VDOLEČEK, F. Diagnostika a metrologické charakteristiky. Spravodaj ATD SR, 2020, roč. 16, č. 1/2019, s. 14-19. ISSN: 1337-8252.
[citace_rtf] =>
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author="František {Vdoleček}",
title="Diagnostika a metrologické charakteristiky",
journal="Spravodaj ATD SR",
year="2020",
volume="16",
number="1/2019",
pages="14--19",
issn="1337-8252",
url="http://www. atdsr.sk"
}
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[popis_en] => The article loosely follows the author's thoughts from previous years of the conference. This time, the article focuses on the relationship between diagnostics and measurement technology and measurement in a broader context. This reflection was to some extent provoked by the current situation of Covid 19. Many fields and companies of technical diagnostics also contribute to its solution. However, the presentation of the results by some "lay" users is at least „interesting“.
[klicova_slova_en] => Accuracy, diagnostics, metrological characteristics, precision, resolution,
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[duvernost_udaju_id] => S
[popis] => In this paper, we deal with the modification of one of D. Teichmann models, which he proposed in the habilitation thesis for the evacuation of the population living in an industrial zone with a potential threat of large scale accidents. The author focused on the emergency planning zone of the Dukovany Nuclear Power Plant, which is specific by the necessity of immediate evacuation, and thus by sufficient means of transport, which are ready for evacuation. Here, we will assume that the evacuation can be gradual and with a shuttle service.
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[klicova_slova] => emergency, evacuation, shuttle transport
[klicova_slova_orig] => emergency, evacuation, shuttle transport
[url] =>
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[citace_text] => ŠEDA, M.; PETEREK, K. Modification of the Teichmann Model of Population Evacuation in Conditions of Shuttle Transport. In Recent Advances in Soft Computing and Cybernetics. Studies in Fuzziness and Soft Computing. Cham (Switzerland): Springer, 2021. p. 279-284. ISBN: 978-3-030-61658-8.
[citace_html] => ŠEDA, M.; PETEREK, K. Modification of the Teichmann Model of Population Evacuation in Conditions of Shuttle Transport. In Recent Advances in Soft Computing and Cybernetics. Studies in Fuzziness and Soft Computing. Cham (Switzerland): Springer, 2021. p. 279-284. ISBN: 978-3-030-61658-8.
[citace_rtf] =>
[citace_bibtex] => @inbook{BUT171028,
author="Miloš {Šeda} and Kamil {Peterek}",
title="Modification of the Teichmann Model of Population Evacuation in Conditions of Shuttle Transport",
booktitle="Recent Advances in Soft Computing and Cybernetics",
year="2021",
publisher="Springer",
address="Cham (Switzerland)",
series="Studies in Fuzziness and Soft Computing",
edition="1.",
pages="279--284",
doi="10.1007/978-3-030-61659-5\{_}23",
isbn="978-3-030-61658-8"
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[nazev] => Boscovich fuzzy regression line
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[popis] => We introduce a new fuzzy linear regression method. The method is capable of approximating fuzzy relationships between an independent and a dependent variable. The independent and dependent variables are expected to be a real value and triangular fuzzy numbers, respec-tively. We demonstrate on twenty datasets that the method is reliable, and it is less sensitive to outliers, compare with possibilistic-based fuzzy regression methods. Unlike other commonly used fuzzy regression methods, the presented method is simple for implementation and it has linear time-complexity. The method guarantees non-negativity of model parameter spreads.
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[klicova_slova] => fuzzy linear regression; non-symmetric triangular fuzzy number; least absolute value;
Boscovich regression line; outlier
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Boscovich regression line; outlier
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[citace_text] => ŠKRABÁNEK, P.; MAREK, J.; POZDÍLKOVÁ, A. Boscovich fuzzy regression line. Mathematics, 2021, vol. 9, no. 6, p. 1-14. ISSN: 2227-7390.
[citace_html] => ŠKRABÁNEK, P.; MAREK, J.; POZDÍLKOVÁ, A. Boscovich fuzzy regression line. Mathematics, 2021, vol. 9, no. 6, p. 1-14. ISSN: 2227-7390.
[citace_rtf] =>
[citace_bibtex] => @article{BUT171143,
author="Pavel {Škrabánek} and Jaroslav {Marek} and Alena {Pozdílková}",
title="Boscovich fuzzy regression line",
journal="Mathematics",
year="2021",
volume="9",
number="6",
pages="1--14",
doi="10.3390/math9060685",
url="https://www.mdpi.com/2227-7390/9/6/685"
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[nazev_en] => Boscovich fuzzy regression line
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[klicova_slova_en] => fuzzy linear regression; non-symmetric triangular fuzzy number; least absolute value;
Boscovich regression line; outlier
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[nazev] => Determination of Air Jet Shape with Complex Methods Using Neural Networks
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[duvernost_udaju_id] => S
[popis] => This article deals with the computer evaluation of airflow images. The airflow is visualized by continuous gas fibers, as for example smoke, fog or another visible additive. One of the most important properties of airflow is the shape of the stream. The principle of determining the shape of the stream is the detection of the additive. For 2D images with a heterogeneous background, it may be very difficult to distinguish the additive from the environment. This paper deals with the possibility of detecting an additive in airflow images with a heterogeneous back-ground. Artificial neural networks will be used for this purpose.
[popis_orig] => This article deals with the computer evaluation of airflow images. The airflow is visualized by continuous gas fibers, as for example smoke, fog or another visible additive. One of the most important properties of airflow is the shape of the stream. The principle of determining the shape of the stream is the detection of the additive. For 2D images with a heterogeneous background, it may be very difficult to distinguish the additive from the environment. This paper deals with the possibility of detecting an additive in airflow images with a heterogeneous back-ground. Artificial neural networks will be used for this purpose.
[klicova_slova] => Additive detection; Air jet shape; Airflow; Artificial neural networks; Image processing
[klicova_slova_orig] => Additive detection; Air jet shape; Airflow; Artificial neural networks; Image processing
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[citace_text] => ŠŤASTNÝ, J.; RICHTER, J.; JURÁNEK, L. Determination of Air Jet Shape with Complex Methods Using Neural Networks. In Studies in Fuzziness and Soft Computing. Springer Nature Switzerland, 2021. p. 25-40. ISBN: 978-3-030-61658-8.
[citace_html] => ŠŤASTNÝ, J.; RICHTER, J.; JURÁNEK, L. Determination of Air Jet Shape with Complex Methods Using Neural Networks. In Studies in Fuzziness and Soft Computing. Springer Nature Switzerland, 2021. p. 25-40. ISBN: 978-3-030-61658-8.
[citace_rtf] =>
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author="Jiří {Šťastný} and Jan {Richter} and Luboš {Juránek}",
title="Determination of Air Jet Shape with Complex Methods Using Neural Networks",
booktitle="Studies in Fuzziness and Soft Computing",
year="2021",
publisher="Springer Nature Switzerland",
pages="25--40",
doi="10.1007/978-3-030-61659-5\{_}3",
isbn="978-3-030-61658-8",
url="https://link.springer.com/chapter/10.1007/978-3-030-61659-5_3"
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[nazev_en] => Determination of Air Jet Shape with Complex Methods Using Neural Networks
[popis_en] => This article deals with the computer evaluation of airflow images. The airflow is visualized by continuous gas fibers, as for example smoke, fog or another visible additive. One of the most important properties of airflow is the shape of the stream. The principle of determining the shape of the stream is the detection of the additive. For 2D images with a heterogeneous background, it may be very difficult to distinguish the additive from the environment. This paper deals with the possibility of detecting an additive in airflow images with a heterogeneous back-ground. Artificial neural networks will be used for this purpose.
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[nazev] => Tracing dsDNA Virus–Host Coevolution through Correlation of Their G-Quadruplex-Forming Sequences
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[popis] => The importance of gene expression regulation in viruses based upon G-quadruplex may point to its potential utilization in therapeutic targeting. Here, we present analyses as to the occurrence of putative G-quadruplex-forming sequences (PQS) in all reference viral dsDNA genomes and evaluate their dependence on PQS occurrence in host organisms using the G4Hunter tool. PQS frequencies differ across host taxa without regard to GC content. The overlay of PQS with annotated regions reveals the localization of PQS in specific regions. While abundance in some, such as repeat regions, is shared by all groups, others are unique. There is abundance within introns of Eukaryota-infecting viruses, but depletion of PQS in introns of bacteria-infecting viruses. We reveal a significant positive correlation between PQS frequencies in dsDNA viruses and corresponding hosts from archaea, bacteria, and eukaryotes. A strong relationship between PQS in a virus and its host indicates their close coevolution and evolutionarily reciprocal mimicking of genome organization.
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[citace_html] => BOHÁLOVÁ, N.; CANTARA, A.; BARTAS, M.; KAURA, P.; ŠŤASTNÝ, J.; PEČINKA, P.; FOJTA, M.; BRÁZDA, V. Tracing dsDNA Virus–Host Coevolution through Correlation of Their G-Quadruplex-Forming Sequences. INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES, 2021, vol. 22, no. 7, p. 1-12. ISSN: 1422-0067.
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author="Natália {Bohálová} and Alessio {Cantara} and Martin {Bartas} and Patrik {Kaura} and Jiří {Šťastný} and Petr {Pečinka} and Miroslav {Fojta} and Václav {Brázda}",
title="Tracing dsDNA Virus–Host Coevolution through Correlation of Their G-Quadruplex-Forming Sequences",
journal="INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES",
year="2021",
volume="22",
number="7",
pages="1--12",
doi="10.3390/ijms22073433",
issn="1661-6596",
url="https://www.mdpi.com/1422-0067/22/7/3433"
}
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[nazev_en] => Tracing dsDNA Virus–Host Coevolution through Correlation of Their G-Quadruplex-Forming Sequences
[popis_en] => The importance of gene expression regulation in viruses based upon G-quadruplex may point to its potential utilization in therapeutic targeting. Here, we present analyses as to the occurrence of putative G-quadruplex-forming sequences (PQS) in all reference viral dsDNA genomes and evaluate their dependence on PQS occurrence in host organisms using the G4Hunter tool. PQS frequencies differ across host taxa without regard to GC content. The overlay of PQS with annotated regions reveals the localization of PQS in specific regions. While abundance in some, such as repeat regions, is shared by all groups, others are unique. There is abundance within introns of Eukaryota-infecting viruses, but depletion of PQS in introns of bacteria-infecting viruses. We reveal a significant positive correlation between PQS frequencies in dsDNA viruses and corresponding hosts from archaea, bacteria, and eukaryotes. A strong relationship between PQS in a virus and its host indicates their close coevolution and evolutionarily reciprocal mimicking of genome organization.
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[nazev] => Analyses of viral genomes for G-quadruplex forming sequences reveal their correlation with the type of infection
[nazev_orig] => Analyses of viral genomes for G-quadruplex forming sequences reveal their correlation with the type of infection
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[popis] => G-quadruplexes contribute to the regulation of key molecular processes. Their utilization for antiviral therapy is an emerging field of contemporary research. Here we present comprehensive analyses of the presence and localization of putative G-quadruplex forming sequences (PQS) in all viral genomes currently available in the NCBI database (including subviral agents). The G4Hunter algorithm was applied to a pool of 11,000 accessible viral genomes representing 350 Mbp in total. PQS frequencies differ across evolutionary groups of viruses, and are enriched in repeats, replication origins, 5′UTRs and 3′UTRs. Importantly, PQS presence and localization is connected to viral lifecycles and corresponds to the type of viral infection rather than to nucleic acid type; while viruses routinely causing persistent infections in Metazoa hosts are enriched for PQS, viruses causing acute infections are significantly depleted for PQS. The unique localization of PQS identifies the importance of G-quadruplex-based regulation of viral replication and life cycle, providing a tool for potential therapeutic targeting.
[popis_orig] => G-quadruplexes contribute to the regulation of key molecular processes. Their utilization for antiviral therapy is an emerging field of contemporary research. Here we present comprehensive analyses of the presence and localization of putative G-quadruplex forming sequences (PQS) in all viral genomes currently available in the NCBI database (including subviral agents). The G4Hunter algorithm was applied to a pool of 11,000 accessible viral genomes representing 350 Mbp in total. PQS frequencies differ across evolutionary groups of viruses, and are enriched in repeats, replication origins, 5′UTRs and 3′UTRs. Importantly, PQS presence and localization is connected to viral lifecycles and corresponds to the type of viral infection rather than to nucleic acid type; while viruses routinely causing persistent infections in Metazoa hosts are enriched for PQS, viruses causing acute infections are significantly depleted for PQS. The unique localization of PQS identifies the importance of G-quadruplex-based regulation of viral replication and life cycle, providing a tool for potential therapeutic targeting.
[klicova_slova] => Acute infection; Bioinformatics; G-quadruplex; G4Hunter; Persistent infection; Viral genome
[klicova_slova_orig] => Acute infection; Bioinformatics; G-quadruplex; G4Hunter; Persistent infection; Viral genome
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title="Analyses of viral genomes for G-quadruplex forming sequences reveal their correlation with the type of infection",
journal="Biochimie",
year="2021",
volume="186",
number="1",
pages="13--27",
doi="10.1016/j.biochi.2021.03.017",
issn="0300-9084",
url="https://www.sciencedirect.com/science/article/pii/S0300908421000961"
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[nazev_en] => Analyses of viral genomes for G-quadruplex forming sequences reveal their correlation with the type of infection
[popis_en] => G-quadruplexes contribute to the regulation of key molecular processes. Their utilization for antiviral therapy is an emerging field of contemporary research. Here we present comprehensive analyses of the presence and localization of putative G-quadruplex forming sequences (PQS) in all viral genomes currently available in the NCBI database (including subviral agents). The G4Hunter algorithm was applied to a pool of 11,000 accessible viral genomes representing 350 Mbp in total. PQS frequencies differ across evolutionary groups of viruses, and are enriched in repeats, replication origins, 5′UTRs and 3′UTRs. Importantly, PQS presence and localization is connected to viral lifecycles and corresponds to the type of viral infection rather than to nucleic acid type; while viruses routinely causing persistent infections in Metazoa hosts are enriched for PQS, viruses causing acute infections are significantly depleted for PQS. The unique localization of PQS identifies the importance of G-quadruplex-based regulation of viral replication and life cycle, providing a tool for potential therapeutic targeting.
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(
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[nazev] => Classification of Deformed Objects Using Advanced LR Parsers
[nazev_orig] => Classification of Deformed Objects Using Advanced LR Parsers
[duvernost_udaju_id] => S
[popis] => An analysis of text and image data is today one of the core fields of artificial intelligence. Among the means that can be used to process this information are structural methods. However, input chain deformations can often occur when analyzing data using structural methods. These are caused, for example, by the inaccurate recording of scanning means. In order to process inaccurate input information, it is necessary to extend a grammar describing the input objects to deformation rules and a weighing system indicating the degree of deformation of the rule. However, the expanded grammar is usually ambiguous. Specially designed syntax analyzers are required to process it. These analyzers may be time consuming; for example, Early Parser calculates a new state dynamically during the analysis. To accelerate processing, a decision table can be used, where every new state is pre-defined. To process distorted inputs, it is possible to use the modified Tomita parser, which contains mechanisms for processing ambiguities, while using the LR table, which reduces dynamically computed tasks.
[popis_orig] => An analysis of text and image data is today one of the core fields of artificial intelligence. Among the means that can be used to process this information are structural methods. However, input chain deformations can often occur when analyzing data using structural methods. These are caused, for example, by the inaccurate recording of scanning means. In order to process inaccurate input information, it is necessary to extend a grammar describing the input objects to deformation rules and a weighing system indicating the degree of deformation of the rule. However, the expanded grammar is usually ambiguous. Specially designed syntax analyzers are required to process it. These analyzers may be time consuming; for example, Early Parser calculates a new state dynamically during the analysis. To accelerate processing, a decision table can be used, where every new state is pre-defined. To process distorted inputs, it is possible to use the modified Tomita parser, which contains mechanisms for processing ambiguities, while using the LR table, which reduces dynamically computed tasks.
[klicova_slova] => Early parser; Enhanced grammar; Nondeterministic grammar; Parsers; Structural methods; Tomita parser
[klicova_slova_orig] => Early parser; Enhanced grammar; Nondeterministic grammar; Parsers; Structural methods; Tomita parser
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[citace_text] => JUNEK, L.; ŠŤASTNÝ, J. Classification of Deformed Objects Using Advanced LR Parsers. In Studies in Fuzziness and Soft Computing. Springer Nature Switzerland, 2021. p. 297-308. ISBN: 978-3-030-61658-8.
[citace_html] => JUNEK, L.; ŠŤASTNÝ, J. Classification of Deformed Objects Using Advanced LR Parsers. In Studies in Fuzziness and Soft Computing. Springer Nature Switzerland, 2021. p. 297-308. ISBN: 978-3-030-61658-8.
[citace_rtf] =>
[citace_bibtex] => @inbook{BUT171739,
author="Lukáš {Junek} and Jiří {Šťastný}",
title="Classification of Deformed Objects Using Advanced LR Parsers",
booktitle="Studies in Fuzziness and Soft Computing",
year="2021",
publisher="Springer Nature Switzerland",
pages="297--308",
doi="10.1007/978-3-030-61659-5\{_}25",
isbn="978-3-030-61658-8",
url="https://link.springer.com/chapter/10.1007%2F978-3-030-61659-5_25"
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[nazev_en] => Classification of Deformed Objects Using Advanced LR Parsers
[popis_en] => An analysis of text and image data is today one of the core fields of artificial intelligence. Among the means that can be used to process this information are structural methods. However, input chain deformations can often occur when analyzing data using structural methods. These are caused, for example, by the inaccurate recording of scanning means. In order to process inaccurate input information, it is necessary to extend a grammar describing the input objects to deformation rules and a weighing system indicating the degree of deformation of the rule. However, the expanded grammar is usually ambiguous. Specially designed syntax analyzers are required to process it. These analyzers may be time consuming; for example, Early Parser calculates a new state dynamically during the analysis. To accelerate processing, a decision table can be used, where every new state is pre-defined. To process distorted inputs, it is possible to use the modified Tomita parser, which contains mechanisms for processing ambiguities, while using the LR table, which reduces dynamically computed tasks.
[klicova_slova_en] => Early parser; Enhanced grammar; Nondeterministic grammar; Parsers; Structural methods; Tomita parser
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[nazev] => Algorithm 1017: fuzzyreg: An R Package for Fitting Fuzzy Regression Models
[nazev_orig] => Algorithm 1017: fuzzyreg: An R Package for Fitting Fuzzy Regression Models
[duvernost_udaju_id] => S
[popis] => Fuzzy regression provides an alternative to statistical regression when the model is indefinite, the relationships between model parameters are vague, the sample size is low, or the data are hierarchically structured. Such cases allow to consider the choice of a regression model based on the fuzzy set theory. In fuzzyreg, we implement fuzzy linear regression methods that differ in the expectations of observational data types, outlier handling, and parameter estimation method. We provide a wrapper function that prepares data for fitting fuzzy linear models with the respective methods from a syntax established in R for fitting regression models. The function fuzzylm thus provides a novel functionality for R through standardized operations with fuzzy numbers. Additional functions allow for conversion of real-value variables to be fuzzy numbers, printing, summarizing, model plotting, and calculation of model predictions from new data using supporting functions that perform arithmetic operations with triangular fuzzy numbers. Goodness of fit and total error of the fit measures allow model comparisons. The package contains a dataset named bats with measurements of temperatures of hibernating bats and the mean annual surface temperature reflecting the climate at the sampling sites. The predictions from fuzzy linear models fitted to this dataset correspond well to the observed biological phenomenon. Fuzzy linear regression has great potential in predictive modeling where the data structure prevents statistical analysis and the modeled process exhibits inherent fuzziness.
[popis_orig] => Fuzzy regression provides an alternative to statistical regression when the model is indefinite, the relationships between model parameters are vague, the sample size is low, or the data are hierarchically structured. Such cases allow to consider the choice of a regression model based on the fuzzy set theory. In fuzzyreg, we implement fuzzy linear regression methods that differ in the expectations of observational data types, outlier handling, and parameter estimation method. We provide a wrapper function that prepares data for fitting fuzzy linear models with the respective methods from a syntax established in R for fitting regression models. The function fuzzylm thus provides a novel functionality for R through standardized operations with fuzzy numbers. Additional functions allow for conversion of real-value variables to be fuzzy numbers, printing, summarizing, model plotting, and calculation of model predictions from new data using supporting functions that perform arithmetic operations with triangular fuzzy numbers. Goodness of fit and total error of the fit measures allow model comparisons. The package contains a dataset named bats with measurements of temperatures of hibernating bats and the mean annual surface temperature reflecting the climate at the sampling sites. The predictions from fuzzy linear models fitted to this dataset correspond well to the observed biological phenomenon. Fuzzy linear regression has great potential in predictive modeling where the data structure prevents statistical analysis and the modeled process exhibits inherent fuzziness.
[klicova_slova] => Fuzzy regression; fuzzy set; possibilistic-based fuzzy regression; statistics-based fuzzy regression; R
[klicova_slova_orig] => Fuzzy regression; fuzzy set; possibilistic-based fuzzy regression; statistics-based fuzzy regression; R
[url] => https://dl.acm.org/doi/10.1145/3451389
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[citace_text] => ŠKRABÁNEK, P.; MARTÍNKOVÁ, N. Algorithm 1017: fuzzyreg: An R Package for Fitting Fuzzy Regression Models. ACM TRANSACTIONS ON MATHEMATICAL SOFTWARE, 2021, vol. 47, no. 3, p. 1-18. ISSN: 0098-3500.
[citace_html] => ŠKRABÁNEK, P.; MARTÍNKOVÁ, N. Algorithm 1017: fuzzyreg: An R Package for Fitting Fuzzy Regression Models. ACM TRANSACTIONS ON MATHEMATICAL SOFTWARE, 2021, vol. 47, no. 3, p. 1-18. ISSN: 0098-3500.
[citace_rtf] =>
[citace_bibtex] => @article{BUT171969,
author="Pavel {Škrabánek} and Natália {Martínková}",
title="Algorithm 1017: fuzzyreg: An R Package for Fitting Fuzzy Regression Models",
journal="ACM TRANSACTIONS ON MATHEMATICAL SOFTWARE",
year="2021",
volume="47",
number="3",
pages="1--18",
doi="10.1145/3451389",
issn="0098-3500",
url="https://dl.acm.org/doi/10.1145/3451389"
}
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[nazev_en] => Algorithm 1017: fuzzyreg: An R Package for Fitting Fuzzy Regression Models
[popis_en] => Fuzzy regression provides an alternative to statistical regression when the model is indefinite, the relationships between model parameters are vague, the sample size is low, or the data are hierarchically structured. Such cases allow to consider the choice of a regression model based on the fuzzy set theory. In fuzzyreg, we implement fuzzy linear regression methods that differ in the expectations of observational data types, outlier handling, and parameter estimation method. We provide a wrapper function that prepares data for fitting fuzzy linear models with the respective methods from a syntax established in R for fitting regression models. The function fuzzylm thus provides a novel functionality for R through standardized operations with fuzzy numbers. Additional functions allow for conversion of real-value variables to be fuzzy numbers, printing, summarizing, model plotting, and calculation of model predictions from new data using supporting functions that perform arithmetic operations with triangular fuzzy numbers. Goodness of fit and total error of the fit measures allow model comparisons. The package contains a dataset named bats with measurements of temperatures of hibernating bats and the mean annual surface temperature reflecting the climate at the sampling sites. The predictions from fuzzy linear models fitted to this dataset correspond well to the observed biological phenomenon. Fuzzy linear regression has great potential in predictive modeling where the data structure prevents statistical analysis and the modeled process exhibits inherent fuzziness.
[klicova_slova_en] => Fuzzy regression; fuzzy set; possibilistic-based fuzzy regression; statistics-based fuzzy regression; R
[vysledek_datum] => 2021-06-26T00:00:00+02:00
)
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(
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[nazev] => Mixed-integer programming model for ranking universities: Letting universities choose the weights
[nazev_orig] => Mixed-integer programming model for ranking universities: Letting universities choose the weights
[duvernost_udaju_id] => S
[popis] => Regardless of the shortcomings and criticisms of world university rankings, these metrics are still widely used by students and parents to select universities and by universities to attract talented students and researchers, as well as funding. This paper proposes a new mixed-integer programming model for ranking universities. The new approach alleviates one of the criticisms – the issue of the “arbitrari-ness” of the weights used for aggregation of the individual criteria (or indicators) utilized in the contemporary rankings. Instead, the proposed model uses intervals of different sizes for the weights and lets the universities themselves “choose” the weights to optimize their position in the rankings. A numerical evaluation of the proposed ranking, based on the indicator values and weights from the Times Higher Education World University Ranking, is presented.
[popis_orig] => Regardless of the shortcomings and criticisms of world university rankings, these metrics are still widely used by students and parents to select universities and by universities to attract talented students and researchers, as well as funding. This paper proposes a new mixed-integer programming model for ranking universities. The new approach alleviates one of the criticisms – the issue of the “arbitrari-ness” of the weights used for aggregation of the individual criteria (or indicators) utilized in the contemporary rankings. Instead, the proposed model uses intervals of different sizes for the weights and lets the universities themselves “choose” the weights to optimize their position in the rankings. A numerical evaluation of the proposed ranking, based on the indicator values and weights from the Times Higher Education World University Ranking, is presented.
[klicova_slova] => Mixed integer programming; Multiple-criteria decision-making; Ranking; University ranking
[klicova_slova_orig] => Mixed integer programming; Multiple-criteria decision-making; Ranking; University ranking
[url] => https://mendel-journal.org/index.php/mendel/article/view/133
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[citace_text] => KŮDELA, J. Mixed-integer programming model for ranking universities: Letting universities choose the weights. Mendel Journal series, 2021, vol. 27, no. 1, p. 41-48. ISSN: 1803-3814.
[citace_html] => KŮDELA, J. Mixed-integer programming model for ranking universities: Letting universities choose the weights. Mendel Journal series, 2021, vol. 27, no. 1, p. 41-48. ISSN: 1803-3814.
[citace_rtf] =>
[citace_bibtex] => @article{BUT172124,
author="Jakub {Kůdela}",
title="Mixed-integer programming model for ranking universities: Letting universities choose the weights",
journal="Mendel Journal series",
year="2021",
volume="27",
number="1",
pages="41--48",
doi="10.13164/mendel.2021.1.041",
issn="1803-3814",
url="https://mendel-journal.org/index.php/mendel/article/view/133"
}
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[nazev_en] => Mixed-integer programming model for ranking universities: Letting universities choose the weights
[popis_en] => Regardless of the shortcomings and criticisms of world university rankings, these metrics are still widely used by students and parents to select universities and by universities to attract talented students and researchers, as well as funding. This paper proposes a new mixed-integer programming model for ranking universities. The new approach alleviates one of the criticisms – the issue of the “arbitrari-ness” of the weights used for aggregation of the individual criteria (or indicators) utilized in the contemporary rankings. Instead, the proposed model uses intervals of different sizes for the weights and lets the universities themselves “choose” the weights to optimize their position in the rankings. A numerical evaluation of the proposed ranking, based on the indicator values and weights from the Times Higher Education World University Ranking, is presented.
[klicova_slova_en] => Mixed integer programming; Multiple-criteria decision-making; Ranking; University ranking
[vysledek_datum] => 2021-06-21T00:00:00+02:00
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[nazev] => Comparison of Multiple Reinforcement Learning and Deep Reinforcement Learning Methods for the Task Aimed at Achieving the Goal
[nazev_orig] => Comparison of Multiple Reinforcement Learning and Deep Reinforcement Learning Methods for the Task Aimed at Achieving the Goal
[duvernost_udaju_id] => S
[popis] => Reinforcement Learning (RL) and Deep Reinforcement Learning (DRL) methods are a promising approach to solving complex tasks in the real world with physical robots. In this paper, we compare several reinforcement learning (Q-Learning, SARSA) and deep reinforcement learning (Deep Q-Network, Deep Sarsa) methods for a task aimed at achieving a specific goal using robotics arm UR3. The main optimization problem of this experiment is to find the best solution for each RL/DRL scenario and minimize the Euclidean distance accuracy error and smooth the resulting path by the Bézier spline method. The simulation and real word applications are controlled by the Robot Operating System (ROS). The learning environment is implemented using the OpenAI Gym library which uses the RVIZ simulation tool and the Gazebo 3D modeling tool for dynamics and kinematics.
[popis_orig] => Reinforcement Learning (RL) and Deep Reinforcement Learning (DRL) methods are a promising approach to solving complex tasks in the real world with physical robots. In this paper, we compare several reinforcement learning (Q-Learning, SARSA) and deep reinforcement learning (Deep Q-Network, Deep Sarsa) methods for a task aimed at achieving a specific goal using robotics arm UR3. The main optimization problem of this experiment is to find the best solution for each RL/DRL scenario and minimize the Euclidean distance accuracy error and smooth the resulting path by the Bézier spline method. The simulation and real word applications are controlled by the Robot Operating System (ROS). The learning environment is implemented using the OpenAI Gym library which uses the RVIZ simulation tool and the Gazebo 3D modeling tool for dynamics and kinematics.
[klicova_slova] => Reinforcement Learning, Deep neural network, Motion planning, Bézier spline, Robotics, UR3
[klicova_slova_orig] => Reinforcement Learning, Deep neural network, Motion planning, Bézier spline, Robotics, UR3
[url] => https://mendel-journal.org
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[citace_text] => PARÁK, R.; MATOUŠEK, R. Comparison of Multiple Reinforcement Learning and Deep Reinforcement Learning Methods for the Task Aimed at Achieving the Goal. Mendel Journal series, 2021, vol. 27, no. 1, p. 1-8. ISSN: 1803-3814.
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author="Roman {Parák} and Radomil {Matoušek}",
title="Comparison of Multiple Reinforcement Learning and Deep Reinforcement Learning Methods for the Task Aimed at Achieving the Goal",
journal="Mendel Journal series",
year="2021",
volume="27",
number="1",
pages="1--8",
doi="10.13164/mendel.2021.1.001",
issn="1803-3814",
url="https://mendel-journal.org"
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[popis_en] => Reinforcement Learning (RL) and Deep Reinforcement Learning (DRL) methods are a promising approach to solving complex tasks in the real world with physical robots. In this paper, we compare several reinforcement learning (Q-Learning, SARSA) and deep reinforcement learning (Deep Q-Network, Deep Sarsa) methods for a task aimed at achieving a specific goal using robotics arm UR3. The main optimization problem of this experiment is to find the best solution for each RL/DRL scenario and minimize the Euclidean distance accuracy error and smooth the resulting path by the Bézier spline method. The simulation and real word applications are controlled by the Robot Operating System (ROS). The learning environment is implemented using the OpenAI Gym library which uses the RVIZ simulation tool and the Gazebo 3D modeling tool for dynamics and kinematics.
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[citace_text] => MATOUŠEK, R.; LOZI, R.; HŮLKA, T. Stabilization of Higher Periodic Orbits of the Lozi and Hénon Maps using Meta-evolutionary Approaches. In 2021 IEEE Congress on Evolutionary Computation (CEC). IEEE Congress on Evolutionary Computation (CEC). Kraków, Poland: IEEE, 2021. p. 572-579. ISBN: 978-1-7281-8393-0.
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title="Stabilization of Higher Periodic Orbits of the Lozi and Hénon Maps using Meta-evolutionary Approaches",
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year="2021",
series="IEEE Congress on Evolutionary Computation (CEC)",
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publisher="IEEE",
address="Kraków, Poland",
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[quotations] => MOURALOVÁ, K.; BEDNÁŘ, J.; PROKEŠ, T.; ZAHRADNÍČEK, R.
[title] => EDM generátor se zaměřením na energetickou úsporu, výstupní výkon a jakost výsledného povrchu
[typ] => AV
[year] => 2020
[id_vav] => 170695
)
[3] => Array
(
[quotations] => VDOLEČEK, F.
[title] => Diagnostika a metrologické charakteristiky
[typ] => PV
[year] => 2020
[id_vav] => 170740
)
[4] => Array
(
[quotations] => ŠEDA, M.; PETEREK, K.
[title] => Modification of the Teichmann Model of Population Evacuation in Conditions of Shuttle Transport
[typ] => PV
[year] => 2021
[id_vav] => 171028
)
[5] => Array
(
[quotations] => ŠKRABÁNEK, P.; MAREK, J.; POZDÍLKOVÁ, A.
[title] => Boscovich fuzzy regression line
[typ] => PV
[year] => 2021
[id_vav] => 171143
)
[6] => Array
(
[quotations] => ŠŤASTNÝ, J.; RICHTER, J.; JURÁNEK, L.
[title] => Determination of Air Jet Shape with Complex Methods Using Neural Networks
[typ] => PV
[year] => 2021
[id_vav] => 171189
)
[7] => Array
(
[quotations] => BOHÁLOVÁ, N.; CANTARA, A.; BARTAS, M.; KAURA, P.; ŠŤASTNÝ, J.; PEČINKA, P.; FOJTA, M.; BRÁZDA, V.
[title] => Tracing dsDNA Virus–Host Coevolution through Correlation of Their G-Quadruplex-Forming Sequences
[typ] => PV
[year] => 2021
[id_vav] => 171724
)
[8] => Array
(
[quotations] => BOHÁLOVÁ, N.; CANTARA, A.; BARTAS, M.; KAURA, P.; ŠŤASTNÝ, J.; PEČINKA, P.; FOJTA, M.; MERGNY, J.; BRÁZDA, V.
[title] => Analyses of viral genomes for G-quadruplex forming sequences reveal their correlation with the type of infection
[typ] => PV
[year] => 2021
[id_vav] => 171738
)
[9] => Array
(
[quotations] => JUNEK, L.; ŠŤASTNÝ, J.
[title] => Classification of Deformed Objects Using Advanced LR Parsers
[typ] => PV
[year] => 2021
[id_vav] => 171739
)
[10] => Array
(
[quotations] => ŠKRABÁNEK, P.; MARTÍNKOVÁ, N.
[title] => Algorithm 1017: fuzzyreg: An R Package for Fitting Fuzzy Regression Models
[typ] => PV
[year] => 2021
[id_vav] => 171969
)
[11] => Array
(
[quotations] => KŮDELA, J.
[title] => Mixed-integer programming model for ranking universities: Letting universities choose the weights
[typ] => PV
[year] => 2021
[id_vav] => 172124
)
[12] => Array
(
[quotations] => PARÁK, R.; MATOUŠEK, R.
[title] => Comparison of Multiple Reinforcement Learning and Deep Reinforcement Learning Methods for the Task Aimed at Achieving the Goal
[typ] => PV
[year] => 2021
[id_vav] => 172507
)
[13] => Array
(
[quotations] => MATOUŠEK, R.; LOZI, R.; HŮLKA, T.
[title] => Stabilization of Higher Periodic Orbits of the Lozi and Hénon Maps using Meta-evolutionary Approaches
[typ] => PV
[year] => 2021
[id_vav] => 172508
)
[14] => Array
(
[quotations] => MOURALOVÁ, K.; POLZER, A.; BENEŠ, L.; BEDNÁŘ, J.; ZAHRADNÍČEK, R.; KALIVODA, M.; FRIES, J.
[title] => Multicut technology used in WEDM machining of Mar-M247
[typ] => PV
[year] => 2021
[id_vav] => 172662
)
)
)