[ad_1] Introduction Automated document classification using deep learning has gained significant interest in recent years due to the increasing amount of digital text data being generated. With the help of deep learning techniques such as…
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[ad_1] Introduction The demand for electricity continues to increase as the population grows and industries expand. This poses a challenge for the existing electric grid infrastructure, which needs to be optimized to meet the growing…
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[ad_1] Introduction With the rise of Internet of Things (IoT) devices in various industries, the need for cybersecurity measures has become more critical than ever. These devices, which are interconnected through the internet, pose unique…
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[ad_1] Introduction In recent years, the demand for online learning platforms has increased significantly, leading to the development of Learning Management Systems (LMS). LMS enable instructors to deliver course material, assess student performance, and facilitate…
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[ad_1] Introduction Augmented Reality (AR) and Virtual Reality (VR) are two rapidly advancing technologies that have gained significant attention in the field of education in recent years. These technologies have the potential to revolutionize the…
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[ad_1] Introduction The use of Artificial Intelligence (AI) technology in criminal justice systems has become increasingly prevalent in recent years. AI systems have been implemented to assist in various aspects of the criminal justice process,…
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[ad_1] Introduction Quantum machine learning (QML) has emerged as a promising field at the intersection of quantum computing and machine learning. With the potential for exponential speedup in certain computational tasks, quantum algorithms have the…
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[ad_1] Introduction Quantum-inspired optimization, based on principles of quantum mechanics, has emerged as a promising approach for solving complex optimization problems efficiently. Facility location problems are important in various real-world applications such as supply chain…
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[ad_1] Introduction: Zero-shot learning for relation extraction is an emerging field in natural language processing that aims to extract relations between entities without requiring any labeled training data for those specific relations. Traditional relation extraction…
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[ad_1] Introduction: The field of graph neural networks has emerged as a powerful tool for analyzing and processing complex data with graph structures. In recent years, there has been a growing interest in using graph…
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