Results 161 to 166 of about 15,166 (166)
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2020
The subject of the graduate qualification work is a phase direction finder with a small number of the antenna array elements. The given work is devoted to determining an optimal number and location of antenna elements and the algorithm parameters for the phase direction finder for its implementation on a modern programmable base.
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The subject of the graduate qualification work is a phase direction finder with a small number of the antenna array elements. The given work is devoted to determining an optimal number and location of antenna elements and the algorithm parameters for the phase direction finder for its implementation on a modern programmable base.
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2019
Fuzzing is an effective method to find vulnerabilities. Full code coverage during fuzzing is not trivial task to accomplish. Moreover, it is redundant because the vulnerabilities in the code are not evenly distributed. This paper describes an approach to ranking functions, which will determine the potentially most dangerous ones.
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Fuzzing is an effective method to find vulnerabilities. Full code coverage during fuzzing is not trivial task to accomplish. Moreover, it is redundant because the vulnerabilities in the code are not evenly distributed. This paper describes an approach to ranking functions, which will determine the potentially most dangerous ones.
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2018
Рданной ÑабоÑе пÑоизведено кÑаÑкое опиÑание ÑовÑеменнÑÑ ÑÐµÑ Ð½Ð¾Ð»Ð¾Ð³Ð¸ÑеÑÐºÐ¸Ñ ÑеÑений и обоÑÑÐ´Ð¾Ð²Ð°Ð½Ð¸Ñ ÐÐУ. РазÑабоÑÐ°Ð½Ñ ÑÑ ÐµÐ¼Ð° газоÑÐ½Ð°Ð±Ð¶ÐµÐ½Ð¸Ñ Ð¸ ÑепловÑе ÑÑ ÐµÐ¼Ñ ÐÐУ-ТÐЦ 26 ÐÐÑ Ð½Ð° базе газоÑÑÑбинного Ð°Ð³Ñ ...
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Рданной ÑабоÑе пÑоизведено кÑаÑкое опиÑание ÑовÑеменнÑÑ ÑÐµÑ Ð½Ð¾Ð»Ð¾Ð³Ð¸ÑеÑÐºÐ¸Ñ ÑеÑений и обоÑÑÐ´Ð¾Ð²Ð°Ð½Ð¸Ñ ÐÐУ. РазÑабоÑÐ°Ð½Ñ ÑÑ ÐµÐ¼Ð° газоÑÐ½Ð°Ð±Ð¶ÐµÐ½Ð¸Ñ Ð¸ ÑепловÑе ÑÑ ÐµÐ¼Ñ ÐÐУ-ТÐЦ 26 ÐÐÑ Ð½Ð° базе газоÑÑÑбинного Ð°Ð³Ñ ...
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2017
ÐаÑÑоÑÑÐ°Ñ Ð´Ð¸Ð¿Ð»Ð¾Ð¼Ð½Ð°Ñ ÑабоÑа пÑедÑÑавлÑÐµÑ Ñобой изÑÑение ÑлекÑÑÐ¾Ñ Ñомизма в покÑÑÑиÑÑ Ð½Ð°Ð½Ð¾ÑаÑÑиÑÑ(Au)-NiO и NiO. ÐÑÑледÑемÑе покÑÑÑÐ¸Ñ Ð±Ñли полÑÑÐµÐ½Ñ Ð¼ÐµÑодом Ñ Ð¸Ð¼Ð¸ÑеÑкого оÑÐ°Ð¶Ð´ÐµÐ½Ð¸Ñ Ð¸Ð· газовой ÑÐ°Ð·Ñ Ñ Ñа
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ÐаÑÑоÑÑÐ°Ñ Ð´Ð¸Ð¿Ð»Ð¾Ð¼Ð½Ð°Ñ ÑабоÑа пÑедÑÑавлÑÐµÑ Ñобой изÑÑение ÑлекÑÑÐ¾Ñ Ñомизма в покÑÑÑиÑÑ Ð½Ð°Ð½Ð¾ÑаÑÑиÑÑ(Au)-NiO и NiO. ÐÑÑледÑемÑе покÑÑÑÐ¸Ñ Ð±Ñли полÑÑÐµÐ½Ñ Ð¼ÐµÑодом Ñ Ð¸Ð¼Ð¸ÑеÑкого оÑÐ°Ð¶Ð´ÐµÐ½Ð¸Ñ Ð¸Ð· газовой ÑÐ°Ð·Ñ Ñ Ñа
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The purpose of the study is to choose optimal hyperparameters of privacy-preserving machine learning tools for classification of network traffic anomalies and estimate the tools vulnerability to attacks on machine learning systems. The subject of the work is security of privacy-preserving machine learning tools. The research set the following goals: 1.
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