Lung diseases are wide group of diseases related to the respiratory system, and is ranging from acute infections to chronic disorders with multifactorial causes. Recognition of the lung disease is very crucial in the ...
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This study suggests using graph algorithms to detect healthcare fraud, a serious issue that can lead to significant financial losses and compromise patient care. Health care fraud is a representation of deceitful acts...
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Legal Outcome Prediction (LOP) is the process of predicting the possible outcome of a court case based on the case file. The aim of this work is to assess the performance of four deep learning models namely BERT, Lega...
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The growing prevalence of intelligent surveillance systems has expedited progress in video analytics, particularly in learning environments. This survey article analyzes various methods for assessing student behavior ...
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The increasing amount of digital news content has created a pressing need for automated systems that can efficiently organize and categorize articles. This study focuses on developing an automated classification syste...
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In the field of software development, ensuring the accuracy and quality of code remains a paramount concern. The task of precisely classifying code as correct or incorrect poses inherent challenges. This research intr...
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The internet’s rapid expansion has led to an increase in cyberattacks and phishing schemes that rely on uniform resource location (URL) links. In today’s digital landscape, it’s vital to identify these harmful link...
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The rapid evolution of malware necessitates advanced detection methodologies to address the limitations of traditional signature-based approaches, which often fail against zero-day malware and polymorphic attacks. Thi...
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This study compares different scheduling algorithms used in edge computing for real-time video processing. Instead of sending video data to cloud servers, the video is processed directly at the edge, reducing delays a...
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Data centers are vital to modern computing but contribute significantly to carbon emissions due to their high energy consumption. To address this, machine learning models can optimize resource allocation by analyzing ...
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