Motivation: Gene-disease associations are fundamental for understanding disease etiology and developing effective interventions and treatments. Identifying genes not yet associated with a disease due to a lack of studies is a challenging task in which prioritization based on prior knowledge is an...
01a Articolo in rivista
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In this paper the aerothermal heating of a reusable launch vehicle with the material parameters depending on temperature is retrieved. An additional information, necessary for solving the corresponding inverse problem, is taken from the temperature values in the selected point of thermal protection...
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The paper presents research on a specific approach to the issue of computed tomography with an incomplete data set. The case of incomplete information is quite common, for example when examining objects of large size or difficult to access. Algorithms devoted to this type of problems can be used to...
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Fuzzy logic systems, unlike black-box models, are known as transparent artificial intelligence systems that have explainable rules of reasoning. Type 2 fuzzy systems extend the field of application to tasks that require the introduction of uncertainty in the rules, e.g. for handling corrupted data...
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Weproposeamethodforcontent-basedretrievingsolarmagnetograms.WeusetheSDOHelioseismicandMagneticImageroutputcollectedwithSunPyPyTorchlibraries.WecreateamathematicalrepresentationofthemagneticfieldregionsoftheSunintheformofavector.Thankstothissolutionwecancompareshortvectorsinsteadofcomparingfull-...
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In order to obtain optimized elementary devices (photovoltaic modules, power transistors for energy efficiency, high-efficiency sensors) it is necessary to increase the energy conversion efficiency of these devices. A very effective approach to achieving this goal is to increase the absorption of...
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In many developed cities around the world, vehicle sharing is becoming an increasingly popular form of green transportation. While such services are associated with lower emissions and easier mobility, their management poses a significant challenge. In this paper, we examine a dataset collected in...
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This study aimed to analyze different predictive analytic techniques to forecast the risk of muscle strain injuries (MSI) in youth soccer based on training load data. Twenty-two young soccer players (age: 13.5 +/- 0.3 years) were recruited, and an injury surveillance system was applied to record...
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Periods of intensified training may increase athletes’ fatigue and impair their recovery status. Therefore, understanding internal and external load markers-related to fatigue is crucial to optimize their weekly training loads. The current investigation aimed to adopt machine learning (ML)...
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Predicting and avoiding an injury is a challenging task. By exploiting data mining techniques, this paper aims to identify existing relationships between modifiable and non-modifiable risk factors, with the final goal of predicting non-contact injuries. Twenty-three young soccer players were...