Výsledky vyhledávání - "V, Stoimenov"

Akademický článek

Applying eXplainable AI Techniques to Interpret Machine Learning Predictive Models for the Analysis of Problematic Internet Use among Adolescents

Autor: Aleksandar S. Stanimirovic, Mina S. Nikolic, Jelena J. Jovic, Dragana I. Ignjatovic Ristic, Aleksandar M. Corac, Leonid V. Stoimenov, Zoran H. Peric

Publikováno v: Elektronika ir Elektrotechnika, Vol 30, Iss 2, Pp 63-72 (2024)

This research focusses on the potential application of artificial intelligence (AI) techniques in the analysis of behavioural addictions, specifically addressing problematic Internet use among adolescents. Using tabular data from a representative sam

Externí odkaz: https://doaj.org/article/3054e4b7228d442b80944f3498d3db55

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Akademický článek

The difference between patient’s and population’s preferences for early staged breast cancer radiation therapy, focus on EBRT vs. IORT treatment options - qualitative research method

Autor: V. Stoimenov, C. Georgieva, V. Parvanova, N. Gesheva

Publikováno v: Breast, Vol 56, Iss , Pp S44- (2021)

Externí odkaz: https://doaj.org/article/5a420dc42e514d448a2aa45f1ab962eb

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Akademický článek

Switched Scalar Quantization with Adaptation Performed on both the Power and the Distribution of Speech Signal

Autor: L. V. Stoimenov, Z. H. Perić, G. M. Petković

Publikováno v: Telfor Journal, Vol 3, Iss 2, Pp 96-99 (2011)

This paper analyzes the models for switching scalar quantization of a source with the Laplacian and Gaussian distribution. We have analyzed the results of real telephone speech and proposed a model of switching scalar quantization, which, in addition

Externí odkaz: https://doaj.org/article/e837beb1348f4c64b8fbab8dcec23ed3

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The difference between patient’s and population’s preferences for early staged breast cancer radiation therapy, focus on EBRT vs. IORT treatment options - qualitative research method

Autor: N. Gesheva, V. Stoimenov, C. Georgieva, V. Parvanova

Publikováno v: Breast, Vol 56, Iss, Pp S44-(2021)

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::81cb9c22e97693fced0cc75384451b86
http://www.sciencedirect.com/science/article/pii/S0960977621001545

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Switched Scalar Optimal -law Quantization with Adaptation Performed to both the Variance and the Distribution of Speech Signal

Autor: M. Petkovic, Goran, H. Peric, Zoran, V. Stoimenov, Leonid

This paper proposes a new model of switching scalar quantization that besides the usual adaptation to the variance uses a switching technique for adaptation to the distribution of the speech signal source. By applying the new model a smaller quantiza

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=od______2659::e35c6c96bf7743ba5038fad50bacf6ae
https://zenodo.org/record/1121607

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Switched Scalar Optimal -law Quantization with Adaptation Performed to both the Variance and the Distribution of Speech Signal

Autor: Goran M. Petkovic, Zoran H. Peric, Leonid V. Stoimenov

Publikováno v: Elektronika ir Elektrotechnika. 22

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::38e9f7ae4ae0c53729936662b5c06971
https://doi.org/10.5755/j01.eee.22.1.14111

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[Testing of chemicals for control of Varroa jacobsoni infection in honeybees]

Autor: G, Kamburov, K, K'nchev, V, Stoimenov

Publikováno v: Acta microbiologica, virologica et immunologica. 2

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=pmid________::e2af0f88eb89b54c3aabd8a8f3e671bc
https://pubmed.ncbi.nlm.nih.gov/1217536

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[Amino acid metabolism in Pasteurella multocida studied using thin-layer chromatography]

Autor: M, Bonovska, L, Karaivanov, V, Stoimenov

Publikováno v: Veterinarno-meditsinski nauki. 17(1)

Amino asid metabolism was studied by thin layer chromatography in 25 Pasteurella multocida strains isolated from various manifestations of the disease chicken septicemia. Six amino acids were used: DL-ornithin, L-cystein, L-asparagin, DL-serin, L-arg

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=pmid________::1b44d8e5d01810649191e81eb8ee9fb6
https://pubmed.ncbi.nlm.nih.gov/7414930

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