Machine learning technique is full-fledged as a boosting sector to develop modeling and forecasting of complex time series observations in the present environment. This study made an attempt to inspect the future perf...
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Evaluating student performance is important for universities and institutions in the current student education landscape because it helps them create models that work better for students. The automation of various fea...
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Lip reading is a technique that aims to understand spoken words by analyzing people's lip movements. Deep learning algorithms are used as a powerful tool for detecting and recognizing lip movements more accurately...
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The paper focuses on the problem of technical social engineering attacks that encompass the manipulation of individuals to reveal sensitive information, execute actions, or breach security systems. These exploits freq...
The paper focuses on the problem of technical social engineering attacks that encompass the manipulation of individuals to reveal sensitive information, execute actions, or breach security systems. These exploits frequently capitalize on human psychology, trust, and a lack of vigilance to attain unauthorized entry to networks, systems, or data. In contrast to traditional social engineering tactics that center on psychological manipulation, technical social engineering attacks employ technological means and strategies to manipulate and beguile individuals. The paper presents an attempt to detect social engineering attacks. The approach utilized four machine learning algorithms (decision tree, random forest, K-nearest neighbor, and extreme gradient boosting). The analysis is centered on data collected from network hosts, which may serve as indicators of a potential social engineering attack. The empirical results demonstrated high detection accuracy.
Remote monitoring of objects or technological processes is used in many industries and service-oriented companies to obtain up-to-date information about the state of things or technical processes. The article is devot...
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This article discusses the use of fuzzy logic and a neural network to predict the demand for pharmaceutical products in a distributed network, in conditions of insufficient information, a large assortment and the infl...
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In the present article, we have considered the issue of selection of potential locations of trade objects as a multi-factor decision-making in the conditions of uncertainty by applying the theory of fuzzy sets. Exampl...
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Selection of insulation material and determination of its thickness are the two most important parameters that prevent heat loss. Too much thickness complicates the price and use. The low coefficient of thermal conduc...
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Long-term predictions of time series is a task with multiple applications. Exploiting neural networks for such problem has not been studied enough for financial purposes. An empirical study of specific cases with real...
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In this study, a new generalized model of thermo-viscoelasticity with three phase-lag (TPL) theory concerning memory-dependent derivative (MDD) theory is emphasized. The governing combined equations of the novel model...
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