Unmanned Aerial Vehicle (UAV)-assisted mobile edge computing (MEC) technology has garnered extensive attention with the widespread adoption of 5G technology, owing to its flexibility, improved system capacity and comp...
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This research paper presents a comparative analysis of four machinelearning models: Random Forest, Decision Tree Classifier, XG Boost, and Artificial Neural Networks (ANNs), evaluating their performance using various...
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As machinelearning evolves, many individuals and businesses utilize numerous algorithms to evaluate massive datasets and create actionable insights that aid in predicting behavior. And this type of technology is incr...
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The capacity to individually identify and categorize people across sites and apps is vital for trustworthiness, fraud prevention, and personalized experiences in online social networking. In this study, strategies for...
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Intrusion detection systems (IDS) are a key component in protecting computer systems and networks from cyber threats. In the past few years, the application of algorithms based on machinelearning (ML) and deep learni...
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machinelearning classification models are exceedingly large, complex and lack universality, not only consuming significant resources and posing difficulties in training, but also lacking in complexity, cannot achieve...
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The selection of cuts to be added to the current LP relaxation is one of the most critical task in Branch-and-Cut methods, since it strongly affects the performances of the algorithm. Recently, machinelearning techni...
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Speaker recognition depends on identifying the speaker using particular segments of the sound stream. A single speech characteristic only reveals the speaker's identity partially. Current advances in machine learn...
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Increase in population and trend for luxurious lifestyle has led to huge increase in the number of vehicles. This change has further fascinated the researchers to focus on smart transportation systems. Numerous applic...
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Federated learning (FL) is a machinelearning (ML) approach that allows a model to be trained across multiple decentralized devices holding local data samples without exchanging them. In the realm of Wireless Sensor N...
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