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Podklady pro výuku Závěrečné práce Statistiky Galerie fotografií Záznam o závěrečné práci na Katedře robotiky Typ práce diplomová Datum odevzdání 26. 05. 2006 Počet
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Vlasta Gazdová Published by: VŠB-Technical University of Ostrava Year of publication: 2011 Graphic design: Studio CMYK Ostrava Number of copies: 150 Not available for
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Mezi oceněnými jsou Martin Lysek a Jan Hlisnikovský. 30. 3. 2026 Aktuality 404 - Oddělení propagace a vnějších vztahů Art & Science 2026 Zveme Vás na další ročník festivalu Art&Science,
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Hermeticism teaches that the substance of any category needs in- formation, or an idea, for its organization. The law of analogy expresses that: What is below is
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High precision data carries high financial and time demands for their preparation. One of the ways, how to limit these requirements, is to automate the conversion
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Machacek, Z., Hercik, R., Slaby, R., Smart User Adaptive System for Intelligent Object Recognizing, In Studies of Computational Intelligence, 3rd International Conference
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Machacek, Z., Hercik, R., Slaby, R., Smart User Adaptive System for Intelligent Object Recognizing, In Studies of Computational Intelligence, 3rd International Conference
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Dynamic return scenario generation approach for large-scale portfolio optimisation framework. Computational Economics, 2025. https://doi.org/10.1007/s10614-023-10541-w.
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Dynamic return scenario generation approach for large-scale portfolio optimisation framework. Computational Economics, 2025. https://doi.org/10.1007/s10614-023-10541-w.
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Dynamic return scenario generation approach for large-scale portfolio optimisation framework. Computational Economics, 2025. https://doi.org/10.1007/s10614-023-10541-w.
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Dynamic return scenario generation approach for large-scale portfolio optimisation framework. Computational Economics, 2025. https://doi.org/10.1007/s10614-023-10541-w.
https://www.ekf.vsb.cz/katedra-financi/cs/veda-a-vyzkum/resene-projekty/?projectDetailId=716289053
Dynamic return scenario generation approach for large-scale portfolio optimisation framework. Computational Economics, 2025. https://doi.org/10.1007/s10614-023-10541-w.
https://www.ekf.vsb.cz/cs/veda-a-vyzkum/sgs/schvalene-projekty/?projectDetailId=716289053
Dynamic return scenario generation approach for large-scale portfolio optimisation framework. Computational Economics, 2025. https://doi.org/10.1007/s10614-023-10541-w.
https://www.ekf.vsb.cz/cs/veda-a-vyzkum/sgs/schvalene-projekty/index.html?projectDetailId=716289053
Dynamic return scenario generation approach for large-scale portfolio optimisation framework. Computational Economics, 2025. https://doi.org/10.1007/s10614-023-10541-w.
https://transactions.fs.vsb.cz/2010-1/1758.pdf
For water the chemical zero exergy equals to zero, but for the water steam it is 0 H2Oμ,e =10.38647 kJ/mol for T=283.15 K, 0 H2Oμ,e =9.78333 kJ/mol for T=288.15 K, 0 H2Oμ,e =9.18381 kJ/mol for T=293.15 K, 0 H2Oμ,e =8.80795 kJ/mol for
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The tunability of magnetic multilayers allows for optimization of properties that are desirable for applications including magnetic
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Since it further appeared that each year considerable improvement was made, as shown for example by the Shell company record in Fig. 1, which is typical for the branch, after a while nobody asked
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The main reasons are mainly problems with exact determination of outside loads parameters which have an effect on the structure during its working. The values of fatigue strength for
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https://doi.org/10.31490/9788024846972. [2] PRIESOL, Ivan. Development of Advanced Material for Precast Flow Control Accessories for