This research proposes an integrated framework of a digital twin, incorporating artificial intelligence and the Internet of Things to optimize energy management and prolong the lifespan of the battery in electric vehi...
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作者：
Shi, LuKan, ShichaoJin, YiZhang, LinnaCen, YigangBejing Jiaotong University
State Key Laboratory of Advanced Rail Autonomous Operation School of Computer Science and Technology Visual Intellgence + X International Cooperation Joint Laboratory of MOE Beijing100044 China Central South University
School of Computer Science and Engineering Changsha410083 China Beijing Jiaotong University
Key Laboratory of Big Data and Artificial Intelligence in Transportation Ministry of Education and the School of Computer Science and Technology Beijing100044 China Guizhou University
School of Mechanical Engineering Guiyang550025 China
3D Region-of-Interest (RoI) Captioning involves translating a model's understanding of specific objects within a complex 3D scene into descriptive captions. Recent advancements in Large Language Models (LLMs) have...
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This study deeply explores the application and efficacy of multidimensional three-dimensional space learning in the field of human-computer interaction (human-computer interaction) technology. Three-dimensional space ...
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ISBN:
(纸本)9783031619526;9783031619533
This study deeply explores the application and efficacy of multidimensional three-dimensional space learning in the field of human-computer interaction (human-computer interaction) technology. Three-dimensional space learning plays an important role in cultivating students' spatial cognitive abilities and creativity. At the same time, human-computer interaction technology provides extensive support through multimedia and multi-sensory input, thereby enriching and improving the teaching process. This study takes 20 college students majoring in art education as the research subjects, and uses comprehensive research methods such as questionnaires, observations, evaluations, and feedback to collect data. Subsequent analysis procedures included descriptive statistics, analysis of variance, and correlation analyzes to interpret the data. Research results show that with the support of HCI, multi-sensory three-dimensional space learning can significantly improve students' spatial imagination, creativity, understanding and mastery of three-dimensional space, while also improving students' learning interest, motivation, participation and satisfaction. The results of this study have important implications for design paradigms in both elementary education and HCI fields. This study highlights the advantages, limitations, influencing factors and operating mechanisms of multi-sensory three-dimensional spatial learning under human-computer interaction. Advocate for future exploration of the design principles, implementation strategies, applicability, and scalability of this educational model.
The network data anomaly detection technology under the Zero Trust model can predict whether the network traffic is normal and provide services for monitoring new network attacks and anomalies. This article proposes a...
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Reinforcement learning (RL) has been successfully applied in many fields for building autonomous systems, such as robotics and telecommunications. With its self-learning ability, RL provides a framework for learning f...
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ISBN:
(纸本)9798350348439;9798350384611
Reinforcement learning (RL) has been successfully applied in many fields for building autonomous systems, such as robotics and telecommunications. With its self-learning ability, RL provides a framework for learning from historical experience and adapting to dynamic environments. In response to the surge in network traffic and the evolving nature of traffic behavior, RL has emerged as a crucial technique for developing intelligent and adaptive traffic engineering (TE) solutions. However, most prior studies have focused on using a centralized unit (i.e., a single agent) to construct RL-based TE systems. While the centralized approach leverages global network information for solid performance, it encounters challenges related to scalability, dynamic network topology, and high monitoring overhead for collecting network information. This paper addresses these issues by introducing a jointly trained multi-agent reinforcement learning-based traffic engineering (MATE-JT) system, which operates as a distributed TE solution. Our approach utilizes multiple agents within a network node so that each agent can make independent routing decisions for a subset of flows. We take the approach of sharing parameters among agents and introduce a joint-training technique that facilitates simultaneous learning from multiple agents' experiences. As a result, our proposed method enhances system performance while reducing training time. We evaluate the proposed approach using various network traffic datasets and demonstrate that MATE-JT improves the performance of TE (about 6.5%) and achieves faster convergence (about 35%) in large-scale networks when compared to state-of-the-art methods.
This paper primarily discusses a pedestrian re-identification method based on multi-scale deep features. Firstly, it addresses the current issues and challenges in pedestrian re-identification. Secondly, it explores e...
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multi-stage sleep classification is crucial in diagnosing sleep disorders and in evaluating sleep quality, but conventional polysomnography techniques are intrusive and time consuming. This paper examines whether cont...
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Nowadays, it is important to work to enhance the integration of heterogeneous ontologies for the betterment of knowledge representation used by expert systems. Recently evolutionary types of metaheuristic algorithms g...
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This paper presents an improved approach to multi-face detection using ResNet50 in Python for real-world applications. The study focuses on enhancing the accuracy and efficiency of detecting multiple faces in a single...
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Gaze tracking is the process of estimating where a person is looking on the screen using only information from eye movement without additional input from the user, it contributes greatly in understanding and improving...
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