With the rapid development of artificial intelligence technology, its application in the field of education and teaching is becoming increasingly widespread, bringing revolutionary changes to traditional education mod...
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Credit card fraud detection is an increasingly critical issue due to the growth of digital transactions and the sophistication of fraudulent activities. This study proposes a hybrid framework combining Graph Neural Ne...
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As the last barrier of nuclear materials, the concrete containment is often in a rapidly changing extreme condition in the event of an accident. This study uses artificial intelligence (AI) techniques to establish a c...
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As the last barrier of nuclear materials, the concrete containment is often in a rapidly changing extreme condition in the event of an accident. This study uses artificial intelligence (AI) techniques to establish a correlation between the position of the containment and stress-strain values under such extreme working conditions, aiming for efficient and accurate prediction of mechanical properties. Finite element (FE) software is utilized to analyze the containment structure, generating batches of prestressed concrete models under various internal pressure conditions. The internal pressure value and three-dimensional coordinates of the containment are considered as input values in artificial intelligence algorithms, while the maximum principal stress or equivalent plastic strain as output values. This work shows that AI models can offer significant advantages in terms of time efficiency by replacing laborious finite element simulation modeling, analysis, and post-processing procedures while enabling predictions regarding containment structural stresses under extreme conditions. Furthermore, these trained models possess remarkable generalization capabilities allowing them to predict stress and strain for a wider range of internal pressure scenarios.
In view of the sudden and unpredictable nature of stroke, with patients often having no obvious symptoms or risk factors, a stroke risk prediction model based on deep neural network (DNN) and CatBoost was proposed, co...
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Synchronous generators are the most complex machines in the power plant requiring protection against constant and transient stresses for reliable operation of the power system. A differential protection scheme and a c...
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Power transmission lines are essential in any power system. The security of transmission structures continues to be a challenging issue due to supply costs and reliability. Occasionally, numerous types of faults may a...
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The glare from oncoming vehicles is the major cause for accidents at night time due to impaired visibility. This work showcases an automatic high to low beam transition system that can switch the state of headlights i...
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There is no doubt that the main issue to address in these patients is the early diagnosis of Bladder carcinoma. This work aims at initiating a new path in this research and undertakes advanced artificial intelligence ...
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The rapidly evolving cyber threat landscape requires innovative and adaptive intrusion detection solutions. Traditional signature-based intrusion detection systems, despite their high accuracy, are inherently inflexib...
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Artificial intelligence plays an important role in agricultural pest control. In order to address the issue of agricultural crop diseases, this study proposes an intelligent agricultural disease recognition technology...
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