The three main centralities of rapid transit and suburban rail networks, closeness, betweenness, and information, which are based on route and distance, were considered useful for measuring the critical stations in a ...
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Text categorization is a crucial task in natural language *** recent years, deep learn- ing methodologies, particularly Recurrent Neural Networks (RNN) and Convolutional Neural Net- works (CNN), have made significant ...
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Industrial automation has become a cornerstone of modern manufacturing, enhancing efficiency, reliability, and scalability. The integration of intelligent control algorithms, such as fuzzy logic, neural networks, gene...
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Dialogue policy trains an agent to select dialogue actions frequently implemented via deep reinforcement learning (DRL). The model-based reinforcement methods built a world model to generate simulated data to alleviat...
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Due to the high speed of vehicle travel and road bumps, the vibration signals of engines during operation are characterized by nonstationarity and low signal-to-noise ratios, making it challenging to diagnose faults b...
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The problem of marine litter is becoming more and more serious, which poses a great threat to the marine ecological environment. The research of marine litter identification and classification problem is imminent, and...
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Alzheimer's disease detection and classification using deep learning techniques offer significant advancements in early diagnosis and progression analysis of this neurodegenerative disorder. This approach leverage...
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This paper describes the newly developed enhanced wearable protection system specifically developed to help protect the lives of coal miners by constantly assessing essential environmental/Fitness parameters. This adv...
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Fall detection systems are critical for ensuring the safety and well-being of the elderly and others with mobility challenges. This paper presents the design and development of a fall detection system employing a text...
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The advent of large language models (LLMs) represents a significant paradigm shift in autonomous threat detection within IoT networks. This paper explores the application of Large Language Models (LLMs) for autonomous...
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